a list of (src, src) as evidence.\\r\\n missing_direct_tgt_deps_map = defaultdict(list) # The same, but for direct deps.\\r\\n\\r\\n buildroot = get_buildroot()\\r\\n abs_srcs = [os.path.join(buildroot, src) for src in srcs]\\r\\n for src in abs_srcs:\\r\\n src_tgt = next(iter(targets_by_file.get(src)))\\r\\n if src_tgt is not None:\\r\\n for actual_dep in filter(must_be_explicit_dep, actual_deps.get(src, [])):\\r\\n actual_dep_tgts = targets_by_file.get(actual_dep)\\r\\n # actual_dep_tgts is usually a singleton. If it's not, we only need one of these\\r\\n # to be in our declared deps to be OK.\\r\\n if actual_dep_tgts is None:\\r\\n missing_file_deps.add((src_tgt, actual_dep))\\r\\n elif src_tgt not in actual_dep_tgts: # Obviously intra-target deps are fine.\\r\\n canonical_actual_dep_tgt = next(iter(actual_dep_tgts))\\r\\n if actual_dep_tgts.isdisjoint(transitive_deps_by_target.get(src_tgt, [])):\\r\\n missing_tgt_deps_map[(src_tgt, canonical_actual_dep_tgt)].append((src, actual_dep))\\r\\n elif canonical_actual_dep_tgt not in src_tgt.dependencies:\\r\\n # The canonical dep is the only one a direct dependency makes sense on.\\r\\n missing_direct_tgt_deps_map[(src_tgt, canonical_actual_dep_tgt)].append(\\r\\n (src, actual_dep))\\r\\n else:\\r\\n raise TaskError('Requested dep info for unknown source file: %s' % src)\\r\\n\\r\\n return (list(missing_file_deps),\\r\\n missing_tgt_deps_map.items(),\\r\\n missing_direct_tgt_deps_map.items())\",\n \"def check_requirements(self): # pylint: disable=no-self-use\\n self.is_skipped = False\",\n \"def check_all():\\n for name, module in sorted(sys.modules.items()): # module files\\n filepath = getattr(module, '__file__', None)\\n if filepath is None:\\n # we land here when a module is an attribute of another module\\n # i.e., it exists twice in the sys.modules table, once as its\\n # canonical representation, and again having been imported\\n # within another module\\n continue\\n filepath = filepath.endswith(\\\".pyc\\\") and filepath[:-1] or filepath\\n check_one(filepath)\\n\\n for filepath in extras: # additional files\\n check_one(filepath)\",\n \"def _check_dependencies(self):\\n imgmin = exists('imgmin')\\n image_optim = exists('image_optim')\\n\\n if not imgmin or not image_optim:\\n puts(p('Dependencies have not been installed:'))\\n\\n message = 'imgmin - https://github.com/rflynn/imgmin'\\n message = s('✓ ' + message) if imgmin else e('✗ ' + message)\\n puts(message)\\n\\n message = 'image_optim - http://rubygems.org/gems/image_optim'\\n message = s('✓ ' + message) if image_optim else e('✗ ' + message)\\n puts(message)\\n\\n sys.exit(0)\",\n \"def check_shell_program_deps(deps):\\n for dep in deps:\\n success = shell_command([dep, \\\"--version\\\"])\\n if not success:\\n print(dep, \\\"är nog inte installerat :(\\\")\\n return False\\n print(\\\"Alla skal-kommandon finns!\\\")\\n return True\",\n \"def check_requirements(config, software, configFileName=None, softwareFileName=None):\\n log = logging.getLogger(__name__)\\n result_dir = config.result_dir\\n required_field = ['reference_im_fn', 'result_dir', 'selection',\\n 'num_of_iterations_per_level', 'num_of_levels', 'ants_params']\\n pyLAR.containsRequirements(config, required_field, configFileName)\\n required_software = ['EXE_BRAINSFit', 'EXE_AverageImages', 'EXE_antsRegistration', 'EXE_WarpImageMultiTransform']\\n pyLAR.containsRequirements(software, required_software, softwareFileName)\\n\\n if not config.num_of_iterations_per_level >= 0:\\n raise Exception(\\\"'num_of_iterations_per_level' must be a positive integer (>=0).\\\")\\n if not config.num_of_levels >= 1:\\n raise Exception(\\\"''num_of_levels' must be a strictly positive integer (>=1).\\\")\\n if len(config.selection) < 2:\\n raise Exception(\\\"'selection' must contain at least two values.\\\")\\n log.info('Results will be stored in:' + result_dir)\\n if not os.path.exists(result_dir):\\n os.makedirs(result_dir)\",\n \"def check_derivatives(self, order, driver_inputs, driver_outputs):\\n\\n # Put the driver connection lists into our local scope by removing\\n # the assembly name from the dotted path.\\n for j, item in enumerate(driver_inputs):\\n if isinstance(item, tuple):\\n\\n tuple_list = []\\n for tup_item in item:\\n names = tup_item.split('.', 1)\\n if names[0] == self.name:\\n tuple_list.append(names[1])\\n else:\\n tuple_list.append(tup_item)\\n\\n driver_inputs[j] = tuple(tuple_list)\\n else:\\n names = item.split('.', 1)\\n if names[0] == self.name:\\n driver_inputs[j] = names[1]\\n\\n for j, item in enumerate(driver_outputs):\\n if isinstance(item, tuple):\\n\\n tuple_list = []\\n for tup_item in item:\\n names = tup_item.split('.', 1)\\n if names[0] == self.name:\\n tuple_list.append(names[1])\\n else:\\n tuple_list.append(tup_item)\\n\\n driver_inputs[j] = tuple(tuple_list)\\n else:\\n names = item.split('.', 1)\\n if names[0] == self.name:\\n driver_outputs[j] = names[1]\\n\\n self.driver.check_derivatives(order, driver_inputs, driver_outputs)\",\n \"def CheckPrerequisites(_):\\n _LocalDataPath(RUN_SCRIPT)\\n _LocalDataPath(CONFIG_FILE)\",\n \"def test_dependencies_are_installed(self):\\n installed = [p['id'] for p in self.qi.listInstalledProducts()]\\n self.assertIn('plone.restapi', installed)\\n self.assertIn('plone.app.contenttypes', installed)\\n self.assertIn('plone.app.multilingual', installed)\",\n \"def check_prerequisites(self, env):\\n super(PopLog, self).check_prerequisites(env)\\n print(\\\" Checking prerequisites for : {0}\\\".format(self.__class__.__name__))\\n \\n for inFile in self._expectedInFiles:\\n rc, err_msg = cesmEnvLib.checkFile('{0}/{1}'.format(env['WORKDIR'],inFile), 'read')\\n if not rc:\\n print('{0}... continuing with additional plots.'.format(err_msg))\",\n \"def test_falsifications(self):\\n implications = get_conditional_independencies(asia_example.graph)\\n issues = get_falsifications(implications, asia_example.data)\\n self.assertEqual(0, len(issues.failures))\\n self.assertEqual(len(issues.evidence), len(implications))\",\n \"def init_check(self):\\n for required_file in self._required_files:\\n # Check if required files are there\\n # FIXME Sometimes it doesn't work :?\\n if required_file not in self.files:\\n self.valid = False\",\n \"def check_tech(self, dependencies):\\n states = []\\n missing = []\\n for dependency in dependencies:\\n technology_state, _ = TechnologyState.objects.get_or_create(state=self, technology=dependency.technology)\\n states.append(technology_state.acquired)\\n if not technology_state.acquired:\\n missing.append(technology_state.technology.name)\\n return all(states), missing\",\n \"def test_checkers_integration():\\n for project in AVAILABLE_CHECKERS.values():\\n assert project.get_latest_version()\\n assert project.get_latest_major_versions()\\n assert project.get_latest_minor_versions()\",\n \"def checkInstall(self, abort=False):\\n \\n for i in self.reqfiles:\\n found = False\\n files = []\\n for j in i:\\n if( os.path.exists( self.realPath() + \\\"/\\\" + j )):\\n found = True\\n else:\\n files.append( self.realPath() + \\\"/\\\" + j )\\n if( not found ):\\n if( abort ):\\n if( len( files ) > 1 ):\\n self.abort( \\\"At least one of these files: \\\" + str(files) + \\\"\\\\n\\\" \\\\\\n + \\\"is required for using this installation of \\\" + self.name )\\n else:\\n self.abort( \\\"Required file not found: \\\" + str(files) )\\n return False\\n return True\",\n \"def missing_requirements_command(args, packages=None, exit_on_failure=True):\\n requirements_files = (\\n args.requirements or Config.requirements_files or []\\n )\\n ignore_list = (\\n args.ignore or Config.ignore_list or []\\n )\\n\\n printer = Printer()\\n if not validate_files(\\n files=requirements_files,\\n printer=printer,\\n exit_on_failure=exit_on_failure):\\n return False\\n\\n requirements = RequirementCollection()\\n for requirements_file in requirements_files:\\n requirements.extend(\\n RequirementCollection.from_file(filepath=requirements_file)\\n )\\n\\n packages = (\\n packages or dependency_list(ignore_list=ignore_list)\\n )\\n\\n missing = [\\n (package, required_by)\\n for package, required_by\\n in missing_requirements(\\n packages=packages,\\n requirements=requirements,\\n ignore_list=ignore_list\\n )\\n ]\\n\\n headers = [\\n messages.PACKAGE,\\n messages.REQUIRED,\\n messages.REQUIRED_BY,\\n ]\\n\\n tabular_data = []\\n for package, requirers in missing:\\n if requirers:\\n for required_by, required_version in requirers:\\n tabular_data.append([\\n printer.colored_message(\\n message=package.key,\\n message_color=printer.color_package\\n ),\\n required_version,\\n required_by.key,\\n ])\\n else:\\n tabular_data.append([\\n printer.colored_message(\\n message=package.key,\\n message_color=printer.color_package\\n ),\\n package.version.specifier,\\n \\\"Requirements\\\",\\n ])\\n\\n if tabular_data:\\n printer.error(messages.MISSING_FOUND)\\n printer.table(headers=headers, tabular_data=tabular_data)\\n if exit_on_failure:\\n sys.exit(1)\\n return False\\n\\n printer.success(messages.MISSING_OK)\\n return True\",\n \"def validate_testdata(self):\\r\\n self._get_tcorder()\\r\\n for line in self.data:\\r\\n if not line.startswith(\\\" \\\"):\\r\\n tcname = line.strip(\\\"\\\\n\\\")\\r\\n continue\\r\\n if \\\"[Setup]\\\" in line:\\r\\n if \\\"depends\\\" in line:\\r\\n line = line.strip(\\\"\\\\n\\\").split(\\\"depends\\\")[1][1:]\\r\\n depends = line.split()[0].split(',')\\r\\n self._check_dependency(tcname, depends)\\r\\n\\r\\n if self.dependency:\\r\\n msg = \\\"Test cases are not in proper dependency order.\\\\n\\\"\\r\\n for i in self.dependency:\\r\\n msg = msg + i\\r\\n logger.warn(msg, console=False)\\r\\n notify.message(msg)\\r\\n raise DependencyException(msg)\\r\\n else:\\r\\n msg = \\\"Testcases are in correct dependency order.\\\"\\r\\n logger.warn(msg)\\r\\n notify.message(msg)\",\n \"def testGetInstallRequires(self):\\n dependencies_file = self._GetTestFilePath(['dependencies.ini'])\\n self._SkipIfPathNotExists(dependencies_file)\\n\\n dependency_helper = dependencies.DependencyHelper(\\n dependencies_file=dependencies_file)\\n\\n install_requires = dependency_helper.GetInstallRequires()\\n self.assertEqual(len(install_requires), 1)\",\n \"def session_check_requirements(session):\\n session.install('gcp-devrel-py-tools')\\n\\n if 'update' in session.posargs:\\n command = 'update-requirements'\\n else:\\n command = 'check-requirements'\\n\\n reqfiles = list(_list_files('.', 'requirements*.txt'))\\n\\n for reqfile in reqfiles:\\n session.run('gcp-devrel-py-tools', command, reqfile)\",\n \"def test_collect_integration_dependencies(self, module_repo):\\n expected_result = {\\n (\\\"HelloWorld\\\", True),\\n (\\\"Claroty\\\", True),\\n (\\\"EWS\\\", True),\\n (\\\"CrisisManagement\\\", True),\\n (\\\"CommonTypes\\\", True),\\n }\\n\\n test_input = [\\n {\\n \\\"Dummy Integration\\\": {\\n \\\"name\\\": \\\"Dummy Integration\\\",\\n \\\"fromversion\\\": \\\"5.0.0\\\",\\n \\\"pack\\\": \\\"dummy_pack\\\",\\n \\\"classifiers\\\": \\\"HelloWorld\\\",\\n \\\"mappers\\\": [\\\"Claroty-mapper\\\", \\\"EWS v2-mapper\\\"],\\n \\\"incident_types\\\": \\\"HR Ticket\\\",\\n \\\"indicator_fields\\\": \\\"CommonTypes\\\",\\n }\\n }\\n ]\\n\\n found_result = PackDependencies._collect_integrations_dependencies(\\n pack_integrations=test_input,\\n id_set=module_repo.id_set.read_json_as_dict(),\\n )\\n\\n assert set(found_result) == set(expected_result)\",\n \"def should_check_for_binary_versions(self):\\n explicitly_asked_for_binaries_check = 'CHECK_BINARIES_VERSIONS' in config_vars\\n update_was_requested = \\\"__UPDATE_INSTALLED_ITEMS__\\\" in config_vars.get(\\\"MAIN_INSTALL_TARGETS\\\", []).list()\\n retVal = explicitly_asked_for_binaries_check or update_was_requested\\n return retVal\",\n \"def install_deps_temp(self):\\n if self.distribution.install_requires:\\n self.distribution.fetch_build_eggs(\\n self.distribution.install_requires)\\n if self.distribution.tests_require:\\n self.distribution.fetch_build_eggs(self.distribution.tests_require)\",\n \"def _check_requirements(requirements: List[str]) -> Tuple[bool, bool]:\\n import pkg_resources\\n\\n failed_pkgs_msgs: List[str] = []\\n conflicting_pkgs_msgs: List[str] = []\\n\\n for req in requirements:\\n try:\\n pkg_resources.require(req)\\n except pkg_resources.DistributionNotFound as dnf:\\n failed_pkgs_msgs.append(dnf.report())\\n except pkg_resources.VersionConflict as vc:\\n conflicting_pkgs_msgs.append(vc.report())\\n except Exception:\\n msg.warn(\\n f\\\"Unable to check requirement: {req} \\\"\\n \\\"Checks are currently limited to requirement specifiers \\\"\\n \\\"(PEP 508)\\\"\\n )\\n\\n if len(failed_pkgs_msgs) or len(conflicting_pkgs_msgs):\\n msg.warn(\\n title=\\\"Missing requirements or requirement conflicts detected. Make sure your Python environment is set up \\\"\\n \\\"correctly and you installed all requirements specified in your project's requirements.txt: \\\"\\n )\\n for pgk_msg in failed_pkgs_msgs + conflicting_pkgs_msgs:\\n msg.text(pgk_msg)\\n\\n return len(failed_pkgs_msgs) > 0, len(conflicting_pkgs_msgs) > 0\",\n \"def check_requirements():\\n debug(\\\"check_requirements\\\")\\n needed = Requirements(Project).find_missing_requirements()\\n if needed:\\n info(\\\"Please add the following to your %s file:\\\\n\\\" % 'requirements.txt')\\n info(\\\"\\\\n\\\".join(str(needed)))\\n else:\\n info(\\\"Your %s includes all known herringlib task requirements\\\" % 'requirements.txt')\",\n \"def ensure_consul_dependencies(host=None, port=22):\\n log.info(\\\"Ensuring the consul dependencies are installed\\\")\\n\\n ensure_consul_dependencies_commands = (\\n ('archlinux', 'type pacman 1> /dev/null && '\\n 'pacman -S --noconfirm wget unzip screen --needed || /bin/true'),\\n ('debian', 'type apt-get 1> /dev/null && '\\n 'apt-get install -yy wget unzip screen '\\n '|| /bin/true')\\n )\\n run_multiple_labeled_commands(\\n ensure_consul_dependencies_commands, host=host, port=port,\\n failure_message=\\\"Failed to run (if {}) install consul \\\"\\n \\\"dependencies command\\\"\\n )\",\n \"def test_report_matches(build_all):\\n build_all.run(\\\"install --requires=foobar/1.0@user/testing --build=* --build=baz/*\\\")\\n build_all.assert_listed_binary({\\\"foobar/1.0@user/testing\\\": (foobar_id, \\\"Build\\\")})\\n # FIXME assert \\\"No package matching 'baz' pattern found.\\\" in build_all.out\\n\\n build_all.run(\\\"install --requires=foobar/1.0@user/testing --build=* --build=!baz/*\\\")\\n # FIXME assert \\\"No package matching 'baz' pattern found.\\\" in build_all.out\\n build_all.assert_listed_binary({\\\"foobar/1.0@user/testing\\\": (foobar_id, \\\"Build\\\")})\\n\\n build_all.run(\\\"install --requires=foobar/1.0@user/testing --build=* --build=~baz/* --build=blah\\\")\\n # FIXME assert \\\"No package matching 'blah' pattern found.\\\" in build_all.out\\n # FIXME assert \\\"No package matching 'baz' pattern found.\\\" in build_all.out\\n build_all.assert_listed_binary({\\\"foobar/1.0@user/testing\\\": (foobar_id, \\\"Build\\\")})\\n build_all.run(\\\"install --requires=foobar/1.0@user/testing --build=* --build=!baz/* --build=~blah\\\")\\n # FIXME assert \\\"No package matching 'blah' pattern found.\\\" in build_all.out\\n # FIXME assert \\\"No package matching 'baz' pattern found.\\\" in build_all.out\\n build_all.assert_listed_binary({\\\"foobar/1.0@user/testing\\\": (foobar_id, \\\"Build\\\")})\",\n \"def validate_dependencies(self, session, entry):\",\n \"def test_list_dependent_assets1(self):\\n pass\",\n \"def test_is_installed():\\n assert _is_installed('coverage') is True # regular dependency\\n assert _is_installed('pytest') is True # dev dependency\\n assert _is_installed('missing') is False # missing dependency\",\n \"def test_install_build_all_with_double_skip(build_arg, bar, foo, foobar, build_all):\\n for argument in [\\\"--build=!foo/* --build=~bar/* {}\\\".format(build_arg),\\n \\\"{} --build=!foo/* --build=~bar/*\\\".format(build_arg)]:\\n build_all.run(\\\"install --requires=foobar/1.0@user/testing {}\\\".format(argument))\\n\\n build_all.assert_listed_binary({\\\"bar/1.0@user/testing\\\": (bar_id, bar),\\n \\\"foo/1.0@user/testing\\\": (foo_id, foo),\\n \\\"foobar/1.0@user/testing\\\": (foobar_id, foobar),\\n })\",\n \"def check_cont(cont, reqs):\\n for req_k, req_v in reqs.items():\\n if req_k == 'files':\\n for fr in req_v:\\n fr_temp = fr.copy() # so subsequent calls don't have their minimum missing\\n min_count = fr_temp.pop('minimum')\\n count = 0\\n for f in cont.get('files', []):\\n is_satisfied, _ = check_cont(f, fr_temp)\\n if 'deleted' in f or not is_satisfied:\\n # Didn't find a match, on to the next one\\n continue\\n\\n count += 1\\n if count >= min_count:\\n break\\n\\n if count < min_count:\\n return False, f'Failed to find {min_count} file(s) with requirement {fr_temp} ({count} found)'\\n\\n else:\\n is_satisfied, error = check_req(cont, req_k, req_v)\\n if not is_satisfied:\\n return is_satisfied, error\\n return True, None\",\n \"def test_install_build_all_with_single_skip(build_arg, bar, foo, foobar, build_all):\\n for argument in [\\\"--build=!foo/* {}\\\".format(build_arg),\\n \\\"{} --build=!foo/*\\\".format(build_arg)]:\\n build_all.run(\\\"install --requires=foobar/1.0@user/testing {}\\\".format(argument))\\n build_all.assert_listed_binary({\\\"bar/1.0@user/testing\\\": (bar_id, bar),\\n \\\"foo/1.0@user/testing\\\": (foo_id, foo),\\n \\\"foobar/1.0@user/testing\\\": (foobar_id, foobar),\\n })\\n check_if_build_from_sources({\\\"foo\\\": foo, \\\"bar\\\": bar, \\\"foobar\\\": foobar}, build_all.out)\",\n \"def consistency_checker(model,universals,existentials):\\n universal_set=set(universals)\\n existential_set=set(existentials)\\n #Additionally to the universal and existential variables the model may\\n #contain additional auxiliary variables -- e.g. for setting default values.\\n #We consider these variables such as the existential variables.\\n auxiliary_variables_in_model={abs(l) for clause in model for l in clause \\n if (not abs(l) in universal_set) and (not abs(l) in existential_set)}\\n existential_set = existential_set.union(auxiliary_variables_in_model)\\n result, certificate = checkModelQBF(model, universal_set, existential_set)\\n return result\",\n \"def _checkin_resources(self):\\n\\n for test_prep in self._test_preps.values():\\n test_prep.sut.checkin()\",\n \"def test_build_all_dependencies_graph(self, mocker):\\n\\n def mock_find_pack_dependencies(pack_id, *_, **__):\\n dependencies = {\\n \\\"pack1\\\": [(\\\"pack2\\\", True), (\\\"pack3\\\", True)],\\n \\\"pack2\\\": [(\\\"pack3\\\", True), (\\\"pack2\\\", True)],\\n \\\"pack3\\\": [],\\n \\\"pack4\\\": [(\\\"pack6\\\", False)],\\n }\\n\\n dependencies_items = {\\n \\\"pack1\\\": {\\n (\\\"type_item_a\\\", \\\"item_a\\\"): {\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n }\\n },\\n \\\"pack2\\\": {\\n (\\\"type_item_b\\\", \\\"item_b\\\"): {\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n }\\n },\\n \\\"pack3\\\": {},\\n \\\"pack4\\\": {\\n (\\\"type_item_c\\\", \\\"item_c\\\"): {\\\"pack4\\\": [(\\\"type_item_4\\\", \\\"item4\\\")]}\\n },\\n }\\n\\n return dependencies[pack_id], dependencies_items[pack_id]\\n\\n {\\n \\\"Expanse Behavior Severity Update\\\": {\\n \\\"Expanse\\\": \\\"ExpanseParseRawIncident\\\",\\n \\\"CommonScripts\\\": \\\"IsGreaterThan\\\",\\n },\\n \\\"ExpanseParseRawIncident\\\": {\\\"Expanse\\\": \\\"ExpanseParseRawIncident\\\"},\\n \\\"Expanse Appearance\\\": {\\\"Expanse\\\": \\\"incident_expanseseverity\\\"},\\n \\\"Expanse Behavior\\\": {\\\"Expanse\\\": \\\"Expanse Behavior Severity Update\\\"},\\n }\\n mocker.patch(\\n \\\"demisto_sdk.commands.find_dependencies.find_dependencies.PackDependencies._find_pack_dependencies\\\",\\n side_effect=mock_find_pack_dependencies,\\n )\\n pack_ids = [\\\"pack1\\\", \\\"pack2\\\", \\\"pack3\\\", \\\"pack4\\\"]\\n dependency_graph = PackDependencies.build_all_dependencies_graph(\\n pack_ids, {}, False\\n )\\n\\n # Asserting Dependencies (mandatory and non-mandatory)\\n assert [n for n in dependency_graph.neighbors(\\\"pack1\\\")] == [\\\"pack2\\\", \\\"pack3\\\"]\\n assert [n for n in dependency_graph.neighbors(\\\"pack2\\\")] == [\\\"pack3\\\"]\\n assert [n for n in dependency_graph.neighbors(\\\"pack3\\\")] == []\\n assert [n for n in dependency_graph.neighbors(\\\"pack4\\\")] == [\\\"pack6\\\"]\\n\\n # Asserting mandatory dependencies\\n nodes = dependency_graph.nodes(data=True)\\n\\n assert nodes[\\\"pack1\\\"][\\\"mandatory_for_packs\\\"] == []\\n assert nodes[\\\"pack1\\\"][\\\"depending_on_items_mandatorily\\\"] == {\\n (\\\"type_item_a\\\", \\\"item_a\\\"): {\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n }\\n }\\n assert nodes[\\\"pack1\\\"][\\\"depending_on_packs\\\"] == [\\n (\\\"pack2\\\", True),\\n (\\\"pack3\\\", True),\\n ]\\n assert nodes[\\\"pack1\\\"][\\\"mandatory_for_items\\\"] == {}\\n\\n assert nodes[\\\"pack2\\\"][\\\"mandatory_for_packs\\\"] == [\\\"pack1\\\"]\\n assert nodes[\\\"pack2\\\"][\\\"depending_on_items_mandatorily\\\"] == {\\n (\\\"type_item_b\\\", \\\"item_b\\\"): {\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n }\\n }\\n assert nodes[\\\"pack2\\\"][\\\"depending_on_packs\\\"] == [\\n (\\\"pack3\\\", True),\\n (\\\"pack2\\\", True),\\n ]\\n assert nodes[\\\"pack2\\\"][\\\"mandatory_for_items\\\"] == {\\n (\\\"type_item_2\\\", \\\"item2\\\"): {\\\"pack1\\\": [(\\\"type_item_a\\\", \\\"item_a\\\")]}\\n }\\n\\n assert nodes[\\\"pack3\\\"][\\\"mandatory_for_packs\\\"] == [\\\"pack1\\\", \\\"pack2\\\"]\\n assert nodes[\\\"pack3\\\"][\\\"depending_on_items_mandatorily\\\"] == {}\\n assert nodes[\\\"pack3\\\"][\\\"depending_on_packs\\\"] == []\\n assert nodes[\\\"pack3\\\"][\\\"mandatory_for_items\\\"] == {\\n (\\\"type_item_3\\\", \\\"item3\\\"): {\\n \\\"pack1\\\": [(\\\"type_item_a\\\", \\\"item_a\\\")],\\n \\\"pack2\\\": [(\\\"type_item_b\\\", \\\"item_b\\\")],\\n }\\n }\\n\\n assert nodes[\\\"pack4\\\"][\\\"mandatory_for_packs\\\"] == []\\n assert nodes[\\\"pack4\\\"][\\\"depending_on_items_mandatorily\\\"] == {\\n (\\\"type_item_c\\\", \\\"item_c\\\"): {\\\"pack4\\\": [(\\\"type_item_4\\\", \\\"item4\\\")]}\\n }\\n assert nodes[\\\"pack4\\\"][\\\"depending_on_packs\\\"] == [(\\\"pack6\\\", False)]\\n assert nodes[\\\"pack4\\\"][\\\"mandatory_for_items\\\"] == {}\\n\\n assert nodes[\\\"pack6\\\"][\\\"mandatory_for_packs\\\"] == []\\n assert nodes[\\\"pack6\\\"][\\\"depending_on_items_mandatorily\\\"] == {}\\n assert nodes[\\\"pack6\\\"][\\\"depending_on_packs\\\"] == []\\n assert nodes[\\\"pack6\\\"][\\\"mandatory_for_items\\\"] == {}\",\n \"def run_checks(self):\\n\\n try:\\n check_obj = self.metadata.get_described_element()\\n except ObjectDoesNotExist:\\n pass\\n\\n if self.metadata.is_service_metadata:\\n if self.metadata.is_service_type(OGCServiceEnum.WMS):\\n self.check_wms(check_obj)\\n elif self.metadata.is_service_type(OGCServiceEnum.WFS):\\n self.check_wfs(check_obj)\\n\\n elif self.metadata.is_layer_metadata:\\n self.check_layer(check_obj)\\n elif self.metadata.is_featuretype_metadata:\\n self.check_featuretype(check_obj)\\n elif self.metadata.is_dataset_metadata:\\n self.check_dataset()\\n\\n # all checks are done. Calculate the health state for all monitoring results\\n health_state = HealthState.objects.create(monitoring_run=self.monitoring_run, metadata=self.metadata)\\n health_state.run_health_state()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68579435","0.6556382","0.6347779","0.63326347","0.62767583","0.62427205","0.61748946","0.6174221","0.6137063","0.60748786","0.6053641","0.5956393","0.588417","0.5882532","0.58643204","0.5854203","0.5835256","0.58289266","0.5825942","0.57865596","0.57855487","0.5742168","0.5716644","0.57165724","0.57164556","0.56999207","0.5691669","0.5658087","0.56579465","0.56486046","0.56376106","0.5629387","0.5617741","0.5604285","0.55978656","0.5592346","0.5589593","0.5588285","0.55811816","0.55650926","0.5562102","0.5555826","0.5555145","0.55547315","0.55500984","0.55239725","0.5521537","0.55137163","0.5498104","0.5497227","0.54902107","0.5487746","0.5477786","0.5475199","0.5465565","0.5426839","0.54187256","0.5388471","0.53761446","0.5371634","0.5367704","0.5365434","0.53610504","0.53594184","0.5358637","0.5356946","0.53382766","0.5333785","0.5329779","0.53273034","0.5319437","0.5308046","0.5307593","0.529985","0.5295682","0.52792084","0.5279018","0.52727014","0.526671","0.52596986","0.5247543","0.52346474","0.52330893","0.52296734","0.5229116","0.52283984","0.52183545","0.5218179","0.5212136","0.519843","0.518967","0.5189189","0.51884955","0.5185217","0.51773787","0.5174252","0.5167338","0.51645285","0.5150337","0.51490843"],"string":"[\n \"0.68579435\",\n \"0.6556382\",\n \"0.6347779\",\n \"0.63326347\",\n \"0.62767583\",\n \"0.62427205\",\n \"0.61748946\",\n \"0.6174221\",\n \"0.6137063\",\n \"0.60748786\",\n \"0.6053641\",\n \"0.5956393\",\n \"0.588417\",\n \"0.5882532\",\n \"0.58643204\",\n \"0.5854203\",\n \"0.5835256\",\n \"0.58289266\",\n \"0.5825942\",\n \"0.57865596\",\n \"0.57855487\",\n \"0.5742168\",\n \"0.5716644\",\n \"0.57165724\",\n \"0.57164556\",\n \"0.56999207\",\n \"0.5691669\",\n \"0.5658087\",\n \"0.56579465\",\n \"0.56486046\",\n \"0.56376106\",\n \"0.5629387\",\n \"0.5617741\",\n \"0.5604285\",\n \"0.55978656\",\n \"0.5592346\",\n \"0.5589593\",\n \"0.5588285\",\n \"0.55811816\",\n \"0.55650926\",\n \"0.5562102\",\n \"0.5555826\",\n \"0.5555145\",\n \"0.55547315\",\n \"0.55500984\",\n \"0.55239725\",\n \"0.5521537\",\n \"0.55137163\",\n \"0.5498104\",\n \"0.5497227\",\n \"0.54902107\",\n \"0.5487746\",\n \"0.5477786\",\n \"0.5475199\",\n \"0.5465565\",\n \"0.5426839\",\n \"0.54187256\",\n \"0.5388471\",\n \"0.53761446\",\n \"0.5371634\",\n \"0.5367704\",\n \"0.5365434\",\n \"0.53610504\",\n \"0.53594184\",\n \"0.5358637\",\n \"0.5356946\",\n \"0.53382766\",\n \"0.5333785\",\n \"0.5329779\",\n \"0.53273034\",\n \"0.5319437\",\n \"0.5308046\",\n \"0.5307593\",\n \"0.529985\",\n \"0.5295682\",\n \"0.52792084\",\n \"0.5279018\",\n \"0.52727014\",\n \"0.526671\",\n \"0.52596986\",\n \"0.5247543\",\n \"0.52346474\",\n \"0.52330893\",\n \"0.52296734\",\n \"0.5229116\",\n \"0.52283984\",\n \"0.52183545\",\n \"0.5218179\",\n \"0.5212136\",\n \"0.519843\",\n \"0.518967\",\n \"0.5189189\",\n \"0.51884955\",\n \"0.5185217\",\n \"0.51773787\",\n \"0.5174252\",\n \"0.5167338\",\n \"0.51645285\",\n \"0.5150337\",\n \"0.51490843\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6852399"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":13070,"cells":{"query":{"kind":"string","value":"Verifies that the given condition id is defined, and that its' dependencies and their transitive dependencies are all defined and valid."},"document":{"kind":"string","value":"def test_verify_dependencies(self, cond_id, conditions):\n\n if not cond_id in conditions.get_keys():\n return 1\n else:\n result = self.verify_dependencies(cond_id)\n return result"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _verify_dependencies(self, cond_id, undefined_paths, current_path):\n\n # Exception for izpack conditions:\n if cond_id in self.conditions.properties[WHITE_LIST]:\n return True\n\n # Short-circuit on well-defined conditions:\n if cond_id in self.well_defined:\n return True\n\n # Short-circuit ill-defined conditions:\n if cond_id in list(self.ill_defined.keys()):\n current_path = current_path + ((cond_id, 'ill-defined condition'),)\n undefined_paths.add(current_path)\n return False\n\n # Cycle checking:\n tup = (cond_id, 'condition')\n if tup in current_path:\n current_path += ((cond_id, 'cyclic condition reference'),)\n undefined_paths.add(current_path)\n return False\n\n # Check for undefined condition.\n if not cond_id in self.conditions.get_keys():\n tup = (cond_id, 'undefined condition')\n current_path += (tup,)\n undefined_paths.add(current_path)\n return False\n\n current_path += (tup,)\n condition = self.conditions.container[cond_id]\n condition_type = condition['type']\n\n if condition_type in list(self.condition_tests.keys()) and not \\\n self.condition_tests[condition_type](self, condition, undefined_paths, current_path):\n return False\n\n self.well_defined.add(cond_id)\n return True","def verify_dependencies(self, cond_id):\n undefined_paths = set()\n self._verify_dependencies(cond_id, undefined_paths, tuple())\n return undefined_paths","def test_verify_all_dependencies(self):\n\n for condition in self.all_references():\n result = self.verify_dependencies(condition)\n\n if result:\n self.ill_defined[condition] = result\n else:\n self.well_defined.add(condition)\n\n return self.ill_defined","def _check_conditional_dependency(obj, condition, package, severity, msg=None):\n if condition:\n if msg is None:\n msg = (\n f\"The specific parameter values of {obj.__class__.__name__}'s \"\n f\"class instance require `{package}` installed. Please run: \"\n f\"`pip install {package}` to \"\n f\"install the `{package}` package. \"\n )\n try:\n _check_soft_dependencies(package, severity=severity, obj=obj)\n except ModuleNotFoundError as e:\n raise ModuleNotFoundError(msg) from e","def check_control_dependency(\n self,\n context: SlicingContext,\n unique_instr: UniqueInstruction,\n code_object_id: int,\n ) -> bool:\n control_dependency = False\n\n if not unique_instr.is_cond_branch():\n return False\n\n code_object: CodeObjectMetaData = self._known_code_objects[code_object_id]\n cdg: ControlDependenceGraph = code_object.cdg\n curr_node = self.get_node(unique_instr.node_id, cdg)\n assert curr_node, \"Invalid node id\"\n successors = cdg.get_successors(curr_node)\n\n instr_ctrl_deps_copy = context.instr_ctrl_deps.copy()\n\n # Check if any instruction on S_C is control dependent on current instruction\n # If so: include current instruction in the slice, remove all instructions\n # control dependent on current instruction\n for instr in context.instr_ctrl_deps:\n instr_node = self.get_node(instr.node_id, cdg)\n if instr_node in successors:\n instr_ctrl_deps_copy.remove(instr)\n control_dependency = True\n context.instr_ctrl_deps = instr_ctrl_deps_copy\n\n return control_dependency","def test_are_dependency_packs_valid(self, current_file, id_set, answer):\n validator = get_validator(current_file)\n assert validator.are_dependency_packs_valid(id_set) is answer","def testConditionChecking(self):\n\n state = State.from_problem(self.prob)\n \n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition))\n\n with drive.instantiate([\"agent\", \"tru1\", \"apt2\"], self.prob):\n self.assertFalse(state.is_satisfied(drive.precondition))","def testConditionReasons(self):\n \n state = State.from_problem(self.prob)\n\n relevantVars = []\n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\n\n relevantVars = set(relevantVars)\n \n s1 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"pos1\"]])\n s2 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"apt1\"]])\n s3 = StateVariable(self.prob.functions[\"location-of\"][0], [self.prob[\"tru1\"]])\n \n self.assertEqual(len(relevantVars), 3)\n self.assert_(s1 in relevantVars)\n self.assert_(s2 in relevantVars)\n self.assert_(s3 in relevantVars)","def check_dependencies():\n\n vars_valid = check_variables(\n AirflowVars.PROJECT_ID, AirflowVars.TERRAFORM_ORGANIZATION, AirflowVars.VM_DAGS_WATCH_LIST\n )\n conns_valid = check_connections(AirflowConns.TERRAFORM)\n\n if not vars_valid or not conns_valid:\n raise AirflowException(\"Required variables or connections are missing\")","def check_deps(self):\n\t\tshutit_global.shutit_global_object.yield_to_draw()\n\t\tcfg = self.cfg\n\t\tself.log('PHASE: dependencies', level=logging.DEBUG)\n\t\tself.pause_point('\\nNow checking for dependencies between modules', print_input=False, level=3)\n\t\t# Get modules we're going to build\n\t\tto_build = [\n\t\t\tself.shutit_map[module_id] for module_id in self.shutit_map\n\t\t\tif module_id in cfg and cfg[module_id]['shutit.core.module.build']\n\t\t]\n\t\t# Add any deps we may need by extending to_build and altering cfg\n\t\tfor module in to_build:\n\t\t\tself.resolve_dependencies(to_build, module)\n\n\t\t# Dep checking\n\t\tdef err_checker(errs, triples):\n\t\t\t\"\"\"Collate error information.\n\t\t\t\"\"\"\n\t\t\tnew_triples = []\n\t\t\tfor err, triple in zip(errs, triples):\n\t\t\t\tif not err:\n\t\t\t\t\tnew_triples.append(triple)\n\t\t\t\t\tcontinue\n\t\t\t\tfound_errs.append(err)\n\t\t\treturn new_triples\n\n\t\tfound_errs = []\n\t\ttriples = []\n\t\tfor depender in to_build:\n\t\t\tfor dependee_id in depender.depends_on:\n\t\t\t\ttriples.append((depender, self.shutit_map.get(dependee_id), dependee_id))\n\n\t\ttriples = err_checker([ self.check_dependee_exists(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\n\t\ttriples = err_checker([ self.check_dependee_build(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\n\t\ttriples = err_checker([ check_dependee_order(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\n\n\t\tif found_errs:\n\t\t\treturn [(err,) for err in found_errs]\n\n\t\tself.log('Modules configured to be built (in order) are: ', level=logging.DEBUG)\n\t\tfor module_id in self.module_ids():\n\t\t\tmodule = self.shutit_map[module_id]\n\t\t\tif cfg[module_id]['shutit.core.module.build']:\n\t\t\t\tself.log(module_id + ' ' + str(module.run_order), level=logging.DEBUG)\n\t\tself.log('\\n', level=logging.DEBUG)\n\n\t\treturn []","def test_check_job_dependencies_prior_dependency_has_errors(database):\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=3)\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n sess.add_all([sub, job, job_2])\n sess.commit()\n\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\n sess.add(job_dep)\n sess.commit()\n\n check_job_dependencies(job.job_id)\n\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']","def consistency_checker(model,universals,existentials):\n universal_set=set(universals)\n existential_set=set(existentials)\n #Additionally to the universal and existential variables the model may\n #contain additional auxiliary variables -- e.g. for setting default values.\n #We consider these variables such as the existential variables.\n auxiliary_variables_in_model={abs(l) for clause in model for l in clause \n if (not abs(l) in universal_set) and (not abs(l) in existential_set)}\n existential_set = existential_set.union(auxiliary_variables_in_model)\n result, certificate = checkModelQBF(model, universal_set, existential_set)\n return result","def condition_details(\n self,\n condition_id: str,\n params: Optional[Dict] = None,\n headers: Optional[Dict] = None,\n ) -> ConditionDetails:\n method = self._get_method(\"condition_details\")\n method = method.format(**{\"id\": condition_id})\n\n return self.call_api_get(method=method, params=params, headers=headers)","def valid_dependency(self, dep):\r\n return True","def check_requirements(config=None):\n for dependency, module_requirements in (\n requirements(config, include_conditional=False).items()):\n for module_requirement in module_requirements:\n if \">=\" in module_requirement:\n module_name, required_version = module_requirement.split(\">=\")\n version_test = \">=\"\n elif \"==\" in module_requirement:\n module_name, required_version = module_requirement.split(\"==\")\n version_test = \"==\"\n else:\n module_name = module_requirement\n version_test = None\n\n try:\n module = __import__(module_name)\n except ImportError:\n logging.exception(\n \"Can't import %r which is part of %r\",\n module_name, dependency\n )\n raise MissingRequirementError(\n \"Can't import %r which is part of %r\"\n % (module_name, dependency), module_name, dependency\n )\n version = getattr(module, \"__version__\", None)\n file_path = getattr(module, \"__file__\", None)\n logger.info(\n \"Using %r version %r from %r to satisfy %r\",\n module_name, version, file_path, dependency\n )\n\n if version_test == \">=\":\n if version is None:\n raise MissingRequirementError(\n \"Version of %r isn't set as __version__ of module %r\"\n % (dependency, module_name), module_name, dependency\n )\n if LooseVersion(version) < LooseVersion(required_version):\n raise MissingRequirementError(\n \"Version of %r in %r is too old. %r < %r\"\n % (dependency, file_path, version, required_version),\n module_name, dependency\n )\n elif version_test == \"==\":\n if version is None:\n raise MissingRequirementError(\n \"Version of %r isn't set as __version__ of module %r\"\n % (dependency, module_name), module_name, dependency\n )\n if LooseVersion(version) != LooseVersion(required_version):\n raise MissingRequirementError(\n \"Unexpected version of %r in %r. %r != %r\"\n % (dependency, file_path, version, required_version),\n module_name, dependency\n )","def check_explicit_data_dependency( # noqa: C901\n self,\n context: SlicingContext,\n unique_instr: UniqueInstruction,\n traced_instr: ExecutedInstruction | None,\n ) -> tuple[bool, set[str]]:\n complete_cover = False\n partial_cover = False\n attribute_creation_uses = set()\n\n if not unique_instr.is_def():\n return False, set()\n\n # Check variable definitions\n if isinstance(traced_instr, ExecutedMemoryInstruction):\n complete_cover = self._check_variables(context, traced_instr)\n\n # When an object, of which certain used attributes are taken from,\n # is created, the slicer has to look for the definition of normal variables\n # instead of these attributes, since they are defined as variables and not\n # as attributes on class/module level.\n if traced_instr.arg_address and traced_instr.object_creation:\n attribute_uses = set()\n for use in context.attr_uses:\n if use.startswith(hex(traced_instr.arg_address)) and len(use) > len(\n hex(traced_instr.arg_address)\n ):\n complete_cover = True\n attribute_uses.add(use)\n attribute_creation_uses.add(\"_\".join(use.split(\"_\")[1:]))\n for use in attribute_uses:\n context.attr_uses.remove(use)\n\n # Check for address dependencies\n if traced_instr.is_mutable_type and traced_instr.object_creation:\n # Note that the definition of an object here means the\n # creation of the object.\n address_dependency = self._check_scope_for_def(\n context.var_uses_addresses,\n hex(traced_instr.arg_address),\n None,\n None,\n )\n if address_dependency:\n complete_cover = True\n\n # Check for the attributes which were converted to variables\n # (explained in the previous construct)\n if traced_instr.argument in context.attribute_variables:\n complete_cover = True\n context.attribute_variables.remove(str(traced_instr.argument))\n\n if isinstance(traced_instr, ExecutedAttributeInstruction):\n # check attribute defs\n if traced_instr.combined_attr in context.attr_uses:\n complete_cover = True\n context.attr_uses.remove(traced_instr.combined_attr)\n # Partial cover: modification of attribute of\n # object in search for definition\n if hex(traced_instr.src_address) in context.var_uses_addresses:\n partial_cover = True\n\n return (complete_cover or partial_cover), attribute_creation_uses","def dependencies_satisfied(self, module) -> bool:\n for k, v in module.requirements.items():\n if k not in self.modules:\n return False\n found_ver = self.modules[k].version\n if isinstance(v, str):\n return found_ver == v\n elif isinstance(v, dict):\n if \"eq\" in v and (found_ver != v[\"eq\"]):\n return False\n if \"min\" in v and (found_ver < v[\"min\"]):\n return False\n if \"max\" in v and (found_ver > v[\"max\"]):\n return False\n else:\n return True\n return True","def check_condition(self):\n\n\t\traw_context = {\n\t\t\t'folk': self.folk\n\t\t}\n\n\t\tstatus, param = self.execute(self.mission_grid, 'condition', self.pending_mission.kingdom, raw_context)\n\t\treturn status","def test_check_model_dependencies_complete(dependency_testing_model, complete_env) -> None:\n assert check_model_dependencies(\n model_cls=dependency_testing_model,\n environment=complete_env,\n raise_for_missing=False,\n )","def validate_dependencies(self, session, entry):","def satisfy(self):\n self.stub.Satisfy(\n depend_pb2.DependSatisfyRequest(depend=self.data), timeout=Cuebot.Timeout)","def test_are_integrations_in_dependency_packs(self, current_file, id_set, answer):\n validator = get_validator(current_file)\n assert validator.are_integrations_in_dependency_packs(id_set) is answer","def check_program_validity(self):\n for fact in self._facts:\n if fact not in self._predicates:\n raise Exception(\"Invalid fact, no IDB defined: \" + fact)\n for clause in self._facts[fact]:\n self.check_clause_validity(clause)\n\n for rule in self._rules:\n if rule not in self._predicates:\n raise Exception(\"Invalid rule, no IDB defined: \" + rule)\n for clause in self._rules[rule]:\n self.check_clause_validity(clause.head)\n for body_clause in clause.body:\n self.check_clause_validity(body_clause)","def mempool_assert_my_coin_id(condition: ConditionWithArgs, unspent: CoinRecord) -> Optional[Err]:\n if unspent.coin.name() != condition.vars[0]:\n return Err.ASSERT_MY_COIN_ID_FAILED\n return None","def match_conditions(id_dict, conditions, aircraft_database_df):\n q = '&'.join([ '(' + k + '==' + f'\"{str(v)}\"' + ')' for (k,v) in id_dict.items() ])\n entry = aircraft_database_df.query(q)\n if entry.empty:\n return False\n else:\n for (k, v) in conditions.items():\n if not all(entry[k].str.match(v, na=False)):\n return False\n return True","def _check_family(self):\n for (s, (b, c)), (cond, ref) in families.items():\n if s != self.SYMBOL or len(b) != self._.d:\n continue\n vars = tuple(set(sum(map(variables, b + c), ())))\n sols = _solve([SR(l) == r for l, r\n in zip(self._.b[:-1] + self._.c[1:], b + c)],\n vars)\n if any(checkConditions(cond, sol) for sol in sols\n if is_integral(sol)):\n raise InfeasibleError(refs=ref)","def condition(*args, delete: bool=True, dependency: Union[AnyStr, List[AnyStr]]=\"\", initialize:\n bool=True, script: AnyStr=\"\", state: bool=True, q=True, query=True, e=True,\n edit=True, **kwargs)->Union[None, Any]:\n pass","def check_status(self, id):\n raise NotImplementedError()","def are_all_deps_fulfilled(self, package: 'Package', only_make_check: bool = False,\n only_depends: bool = False, print_reason: bool = False) -> bool:\n\n for dep in package.relevant_deps(only_make_check=only_make_check, only_depends=only_depends):\n if not self.provided_by(dep):\n if print_reason:\n aurman_note(\n \"Dependency {} of package {} is not fulfilled\".format(\n Colors.BOLD(Colors.LIGHT_MAGENTA(dep)),\n Colors.BOLD(Colors.LIGHT_MAGENTA(package.name))\n )\n )\n return False\n else:\n return True","def dependencies_are_met(\n self,\n parent_job: Optional['Job'] = None,\n pipeline: Optional['Pipeline'] = None,\n exclude_job_id: Optional[str] = None,\n ) -> bool:\n connection = pipeline if pipeline is not None else self.connection\n\n if pipeline is not None:\n connection.watch(*[self.key_for(dependency_id) for dependency_id in self._dependency_ids])\n\n dependencies_ids = {_id.decode() for _id in connection.smembers(self.dependencies_key)}\n\n if exclude_job_id:\n dependencies_ids.discard(exclude_job_id)\n if parent_job and parent_job.id == exclude_job_id:\n parent_job = None\n\n if parent_job:\n # If parent job is canceled, treat dependency as failed\n # If parent job is not finished, we should only continue\n # if this job allows parent job to fail\n dependencies_ids.discard(parent_job.id)\n if parent_job.get_status() == JobStatus.CANCELED:\n return False\n elif parent_job._status == JobStatus.FAILED and not self.allow_dependency_failures:\n return False\n\n # If the only dependency is parent job, dependency has been met\n if not dependencies_ids:\n return True\n\n with connection.pipeline() as pipeline:\n for key in dependencies_ids:\n pipeline.hget(self.key_for(key), 'status')\n\n dependencies_statuses = pipeline.execute()\n\n allowed_statuses = [JobStatus.FINISHED]\n if self.allow_dependency_failures:\n allowed_statuses.append(JobStatus.FAILED)\n\n return all(status.decode() in allowed_statuses for status in dependencies_statuses if status)","def check(self, srcs, actual_deps):\r\n if self._check_missing_deps or self._check_missing_direct_deps or self._check_unnecessary_deps:\r\n missing_file_deps, missing_tgt_deps, missing_direct_tgt_deps = \\\r\n self._compute_missing_deps(srcs, actual_deps)\r\n\r\n buildroot = get_buildroot()\r\n def shorten(path): # Make the output easier to read.\r\n for prefix in [buildroot, self._context.ivy_home]:\r\n if path.startswith(prefix):\r\n return os.path.relpath(path, prefix)\r\n return path\r\n\r\n if self._check_missing_deps and (missing_file_deps or missing_tgt_deps):\r\n for (tgt_pair, evidence) in missing_tgt_deps:\r\n evidence_str = '\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\r\n for e in evidence])\r\n self._context.log.error(\r\n 'Missing BUILD dependency %s -> %s because:\\n%s'\r\n % (tgt_pair[0].address.reference(), tgt_pair[1].address.reference(), evidence_str))\r\n for (src_tgt, dep) in missing_file_deps:\r\n self._context.log.error('Missing BUILD dependency %s -> %s'\r\n % (src_tgt.address.reference(), shorten(dep)))\r\n if self._check_missing_deps == 'fatal':\r\n raise TaskError('Missing deps.')\r\n\r\n if self._check_missing_direct_deps:\r\n for (tgt_pair, evidence) in missing_direct_tgt_deps:\r\n evidence_str = '\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\r\n for e in evidence])\r\n self._context.log.warn('Missing direct BUILD dependency %s -> %s because:\\n%s' %\r\n (tgt_pair[0].address, tgt_pair[1].address, evidence_str))\r\n if self._check_missing_direct_deps == 'fatal':\r\n raise TaskError('Missing direct deps.')\r\n\r\n if self._check_unnecessary_deps:\r\n raise TaskError('Unnecessary dep warnings not implemented yet.')","def condition_id(self, condition_id):\n\n self._condition_id = condition_id","def get_depend_by_child_id(self, child_id):\n try:\n result = self._session.query(StepDependencyEntity).\\\n filter(StepDependencyEntity.child_id == child_id).\\\n all()\n result_dict = self.result_dict(result)\n except SQLAlchemyError as err:\n Log.an().error('sql exception [%s]', str(err))\n return False\n\n return result_dict","def test_check_job_dependencies_has_unfinished_dependencies(database):\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=0)\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n job_3 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=0)\n sess.add_all([sub, job, job_2, job_3])\n sess.commit()\n\n # Job 1 finished, it is a prerequisite for job 2 (waiting)\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\n # Job 3 is also a prerequisite of job 2, it's not done, job 2 should stay in \"waiting\"\n job_dep_2 = JobDependency(job_id=job_2.job_id, prerequisite_id=job_3.job_id)\n sess.add_all([job_dep, job_dep_2])\n sess.commit()\n\n check_job_dependencies(job.job_id)\n\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']","def check_dependencies(target_binary, target_platform, target_architecture, target_type):\n check_architecture(target_architecture)\n check_platform(target_platform)","def is_valid(self):\n return not self.missing_from_disk and not self.missing_dependency","def test_load_additive_constraints():\n solution_repo = SolutionRepository(\n os.path.join(os.path.dirname(__file__), \"requests_security_solution.txt\")\n )\n constraints = solution_repo.solution[\"idna\"].build_constraints()\n assert constraints == pkg_resources.Requirement.parse(\"idna<2.9,>=2.5\")","def _check_foreign_cols(\n self, join_condition: ColumnElement[bool], primary: bool\n ) -> None:\n\n can_sync = False\n\n foreign_cols = self._gather_columns_with_annotation(\n join_condition, \"foreign\"\n )\n\n has_foreign = bool(foreign_cols)\n\n if primary:\n can_sync = bool(self.synchronize_pairs)\n else:\n can_sync = bool(self.secondary_synchronize_pairs)\n\n if (\n self.support_sync\n and can_sync\n or (not self.support_sync and has_foreign)\n ):\n return\n\n # from here below is just determining the best error message\n # to report. Check for a join condition using any operator\n # (not just ==), perhaps they need to turn on \"viewonly=True\".\n if self.support_sync and has_foreign and not can_sync:\n err = (\n \"Could not locate any simple equality expressions \"\n \"involving locally mapped foreign key columns for \"\n \"%s join condition \"\n \"'%s' on relationship %s.\"\n % (\n primary and \"primary\" or \"secondary\",\n join_condition,\n self.prop,\n )\n )\n err += (\n \" Ensure that referencing columns are associated \"\n \"with a ForeignKey or ForeignKeyConstraint, or are \"\n \"annotated in the join condition with the foreign() \"\n \"annotation. To allow comparison operators other than \"\n \"'==', the relationship can be marked as viewonly=True.\"\n )\n\n raise sa_exc.ArgumentError(err)\n else:\n err = (\n \"Could not locate any relevant foreign key columns \"\n \"for %s join condition '%s' on relationship %s.\"\n % (\n primary and \"primary\" or \"secondary\",\n join_condition,\n self.prop,\n )\n )\n err += (\n \" Ensure that referencing columns are associated \"\n \"with a ForeignKey or ForeignKeyConstraint, or are \"\n \"annotated in the join condition with the foreign() \"\n \"annotation.\"\n )\n raise sa_exc.ArgumentError(err)","def _check_condition_set_related_reference_21(self):\n type_of_event = FFXMMConfirmationOutUtils_Override.get_event_type_MT330(self.acm_obj)\n type_of_operation = str(get_type_of_operation(self.acm_obj))\n\n if type_of_event == 'CONF':\n if type_of_operation in ['AMND', 'CANC']:\n return True\n return False\n\n return True","def checkRequiredDependencies(self):\n \n # skip dependency check for downloading only\n if( self.downloadOnly ):\n return\n\n # hard dependencies\n for req in self.reqmodules:\n if( self.parent.module(req) == None ):\n # check if there is an auto detected module\n if( self.parent.module(req, True) == None ):\n self.abort( self.name + \" requires \" + req \\\n + \" and it wasn't found in your config file!!\" )\n else:\n # use auto detected module\n self.parent.use( self.parent.module(req, True) )\n self.parent.module( req ).init()\n\n print self.name + \": auto-detected \" + req + \" version \" + self.parent.module( req ).version\n \n # build only dependencies\n if( self.mode == \"install\" ):\n mods = self.reqmodules_buildonly + self.reqmodules_external\n for req in mods:\n if( self.parent.module(req) == None ):\n # check if there is an auto detected module\n if( self.parent.module(req, True) == None ):\n self.abort( req + \" not found in your config file!! \" + self.name \\\n + \" cannot be built without \" + req )\n else:\n # use auto detected module\n self.parent.use( self.parent.module(req, True) )\n self.parent.module( req ).init()\n\n print \" - \" + self.name + \": auto-detected \" + req + \" version \" + self.parent.module( req ).version","def check_all_constraints(Instance: dict):\r\n\r\n print(\"Checking constraints...\")\r\n # Schedule constraints\r\n check_schedule(Instance)\r\n # Resources constraints\r\n check_resources(Instance)\r\n # Exclusions constraints\r\n check_exclusions(Instance)\r\n if (\r\n check_exclusions(Instance)\r\n and check_resources(Instance)\r\n and check_schedule(Instance)\r\n ):\r\n print(\"Done\")\r\n return True\r\n else:\r\n return False","def delete_depend_by_workflow_id(self, workflow_id):\n try:\n # use of a sub-query instead of join for delete is required\n # for sqlite\n sub_query = self._session.query(StepEntity.id).\\\n filter(StepEntity.workflow_id == workflow_id)\n self._session.query(StepDependencyEntity).\\\n filter(StepDependencyEntity.child_id.in_(sub_query)).\\\n delete(synchronize_session=False)\n except SQLAlchemyError as err:\n Log.an().error('sql exception [%s]', str(err))\n return False\n\n return True","def test_empty_condition(self):\n assert_that(Condition.is_valid(''), equal_to(True))","def checkMetamodelLevel(cls):\n for mmd in cls.metamodelDependencies():\n mmd.check()","def validity_constraint(self, node, condition, err_msg):\n if not condition:\n self.tree.add_error(node, err_msg)","def _sufficient_deps(cls, deps):\n if cls.MODEL_PACKAGE is None:\n return True\n else:\n for d in deps.conda:\n if cls.MODEL_PACKAGE in d:\n return True\n for d in deps.pip:\n if cls.MODEL_PACKAGE in d:\n return True\n return False","def _add_conditions(self, modcells, condition_dict):\n\n rename_dict = {}\n\n # Fill in gaps with info from pristine\n for ID in list(condition_dict):\n iter_cond_dict = condition_dict[ID].copy()\n\n ID_verdict = ID\n\n found_empty_dict_flag = False\n found_duplicate_flag = False\n found_same_ID_flag = False\n\n # If no keys defined, set this condition as pristine\n # or if only the 'identifier' is specified and it is 'pristine'\n\n if not set(iter_cond_dict):\n found_empty_dict_flag = True\n else:\n if 'identifier' in list(iter_cond_dict):\n if iter_cond_dict['identifier'] == 'pristine':\n found_empty_dict_flag = True\n\n if found_empty_dict_flag:\n # If ID is zero, just delete this case because pristine is added already (in __init__)\n # If ID not zero, need to also change all IDs in modcell to 0\n if ID != 0:\n ID_verdict = 0\n rename_dict = self._add_val_to_dict(\n rename_dict, ID_verdict, ID)\n continue\n\n else:\n valid_msk = [(k not in set(self.pristine_condition))\n for k in list(iter_cond_dict)]\n if any(valid_msk):\n raise Exception(\n f'Invalid key(s) passed in condition_dict: {list(iter_cond_dict)[valid_msk]}\\nValid keys are {list(self.pristine_condition)}')\n\n # Get keys which are not defined\n undefined_keys = set(\n self.pristine_condition) - set(iter_cond_dict)\n\n # Define undefined keys as the conditions in pristine_condition\n for undef_key in undefined_keys:\n iter_cond_dict[undef_key] = self.pristine_condition[undef_key]\n\n # Check if there are keys in current condition_dict\n if list(self.condition_dict.keys()):\n\n # get list of current 'identifier'\n identifiers_dict = self._get_key_set(\n self.condition_dict, 'identifier')\n\n # if inputted identifier is in current identifiers, append sample to list\n if iter_cond_dict['identifier'] in identifiers_dict.values():\n\n # Check for identifier in dict keys, return dict key (cell_num)\n ID_found = [key for (key, value) in identifiers_dict.items(\n ) if value == iter_cond_dict['identifier']]\n\n if (len(ID_found) == 0) or (len(ID_found) > 1):\n raise Exception(\n f\"Debugging: {len(ID_found)} identifiers found even though it should have been one: {ID_found}\")\n\n elif len(ID_found) == 1:\n ID_found = ID_found[0]\n\n # Replace ID with ID_found and append condition_dict ONLY if \\\n # it is different.\n\n if ID != ID_found:\n rename_dict = self._add_val_to_dict(\n rename_dict, ID_found, ID)\n ID_verdict = ID_found\n\n # check if condition is already defined\n for dct in self.condition_dict[ID_found]:\n if dct == iter_cond_dict:\n # If match found, delete current ID\n found_duplicate_flag = True\n continue\n\n if not found_duplicate_flag:\n # duplicate not found, append to dict\n if len(self.condition_dict[ID_found]) == 0:\n # if none in list\n self.condition_dict[ID_found] = [\n iter_cond_dict]\n else:\n # if conditions in list but none are this condition_dict\n self.condition_dict[ID_found].append(\n iter_cond_dict)\n\n else:\n # identifier was not found in self.condition_dict\n # so, must create case\n\n # Organize input IDs with all existing keys\n # If current condition_dict has matching key with inputted, find next numerical key available and rename in condition_dict and modcells\n if ID_verdict in list(self.condition_dict.keys()):\n new_key = max(list(self.condition_dict.keys())) + 1\n rename_dict = self._add_val_to_dict(\n rename_dict, new_key, ID_verdict)\n ID_verdict = new_key\n found_same_ID_flag = True\n\n if not found_same_ID_flag:\n # An original condition is found\n # Ensure that when adding a new condition, the ID is sequentially larger\n # Used to organize ID systematically\n expected_id = max(\n list(self.condition_dict.keys())) + 1\n if ID_verdict > expected_id:\n rename_dict = self._add_val_to_dict(\n rename_dict, expected_id, ID_verdict)\n ID_verdict = expected_id\n\n self.condition_dict[ID_verdict] = [iter_cond_dict]\n else:\n # self.condition_dict is blank\n raise Exception(\n \"Debugging: this should never happen because pristine case is defined in __init__ which populates self.condition_dict.\")\n\n # REPLACE IDs\n all_keys = list(modcells.keys())\n for idx in range(len(all_keys)):\n module_identifier = all_keys[idx]\n if (module_identifier == 'V') or (module_identifier == 'I'):\n raise ValueError(\n f\"Invalid module identifier, {module_identifier}. It cannot be 'I' or 'V'\")\n\n modcell_list = modcells[module_identifier]\n\n if isinstance(modcell_list, (tuple, list)):\n modcell_list = np.array(modcell_list)\n elif not isinstance(modcell_list, np.ndarray):\n raise TypeError(\n f\"Invalid object ({type(modcell_list).__name__}) was passed to modcell[{module_identifier}]. Please define a list, tuple, or array as the value.\")\n\n if len(modcell_list.shape) == 2:\n # 2d list found, therefore must process multiple modcells\n process_modcells = modcell_list\n elif len(modcell_list.shape) == 1:\n # 1d list found, put into a list for processing format\n process_modcells = [modcell_list]\n else:\n raise TypeError(\n f\"Invalid array shape ({modcell_list.shape}) passed to modcell is {len(modcell_list.shape)}D. Expected 1D or 2D iterable object.\\nHere is object:\\n{modcell_list}\")\n\n required_n_cells = self.module_parameters[\"ncells_substring\"] * \\\n self.module_parameters[\"nsubstrings\"]\n for modcell_arr in process_modcells:\n if len(modcell_arr) != required_n_cells:\n raise Exception(\n f\"An input modcell has an invalid length. The input definition has {len(modcell_arr)} when {required_n_cells} is required.\")\n\n comparator = copy.deepcopy(process_modcells)\n for replacement_id in list(rename_dict):\n for current_id in rename_dict[replacement_id]:\n # for modcell_iter in process_modcells:\n for idx in range(len(process_modcells)):\n\n indexes = []\n for i in range(len(comparator[idx])):\n if comparator[idx][i] == current_id:\n indexes.append(i)\n\n for index in indexes:\n process_modcells[idx][index] = replacement_id\n\n # Append modcells and condition_dict\n # Check if modcell key already exists\n if module_identifier in self.modcells.keys():\n for mdcel in process_modcells:\n if mdcel not in np.array(self.modcells[module_identifier]).astype(int):\n self.modcells[module_identifier] += process_modcells\n else:\n self.modcells[module_identifier] = process_modcells","def check_model(self):\n for node in self.nodes():\n cpd = self.get_cpds(node=node)\n\n if cpd is None:\n raise ValueError(\"No CPD associated with {}\".format(node))\n elif isinstance(cpd, (TabularCPD, ContinuousFactor)):\n evidence = cpd.get_evidence()\n parents = self.get_parents(node)\n if set(evidence if evidence else []) != set(parents if parents else []):\n raise ValueError(\n \"CPD associated with {node} doesn't have \"\n \"proper parents associated with it.\".format(node=node)\n )\n if not cpd.is_valid_cpd():\n raise ValueError(\n \"Sum or integral of conditional probabilites for node {node}\"\n \" is not equal to 1.\".format(node=node)\n )\n return True","def test_falsifications(self):\n implications = get_conditional_independencies(asia_example.graph)\n issues = get_falsifications(implications, asia_example.data)\n self.assertEqual(0, len(issues.failures))\n self.assertEqual(len(issues.evidence), len(implications))","def consistent(self,assignment):\n return all(con.holds(assignment)\n for con in self.constraints\n if all(v in assignment for v in con.scope))","def check_all_constraints(csp) :\n constraints=csp.get_all_constraints()\n for constraint in constraints:\n var1 = constraint.var1\n var2 = constraint.var2\n val1=csp.get_assigned_value(var1)\n val2=csp.get_assigned_value(var2)\n if val1!=None and val2!=None:\n if not constraint.check(val1,val2):\n return False\n return True","def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):\n # Check for a matching dependency type\n related = []\n\n if edge[2][\"dep\"] == dep:\n # Check for matching POS type(s)\n for pos_logic in dep_obj.keys():\n connector = None\n\n if isinstance(dep_obj[pos_logic], dict):\n for pos in dep_obj[pos_logic].keys():\n\n # Check for allowed part of speech tags in matched dependency patterns\n if (pos_logic == \"pos_in\" and pos in G.nodes[sibling_idx][\"pos\"]) or (\n pos_logic == \"pos_equals\" and pos == G.nodes[sibling_idx][\"pos\"]):\n pass\n elif pos_logic == \"pos_not\":\n if not [False if not_pos == G.nodes[sibling_idx][\"pos\"] else True for not_pos in\n dep_obj.keys()]: continue\n else:\n continue\n\n # if no additional checks, have a match\n if dep_obj[pos_logic][pos] == None or any(\n y in dep_obj[pos_logic][pos] for y in [None, \"add_sibling\"]):\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']])\n\n # if additional checks are required, process further\n if dep_obj[pos_logic][pos]:\n if \"get_cousin\" in dep_obj[pos_logic][pos]:\n related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos][\"get_cousin\"]))\n connector = G.nodes[sibling_idx]['word']\n\n if \"special\" in dep_obj[pos_logic][pos]:\n if dep == \"compound\" and pos == \"NN\":\n related = [G.nodes[sibling_idx]['word']]\n\n if None in related:\n related.remove(None)\n\n # Allows for getting cousin and returning sibling\n if \"else\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\"else\"] == \"always\":\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\n if len(related) > 0 and isinstance(related, list):\n for x in related:\n if x != None:\n all_related = _add_related(x, dep, all_related, A.index_lookup[x],\n connector=connector)\n elif \"else\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\"else\"] == True:\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\n\n return all_related","def validate_dependence_versions():\n print('Total {} instances defined'.format(len(ReleaseInfo.all_instance_releases())))\n all_instance_releases = ReleaseInfo.all_instance_releases()\n\n # Validate dependencies: each dependence should have a valid\n # version as in defined range\n for instance_name, versions in all_instance_releases.items():\n for instance_version, release_info in versions.items():\n dependencies = release_info.dependencies\n for dep in dependencies:\n dep_type = dep.type\n minv = dep.min_version\n maxv = dep.max_version\n\n assert dep_type in all_instance_releases, \\\n \"No dependence found {} for version {} of {}\" \\\n .format(dep_type, instance_version, instance_name)\n\n found = _find_a_ranged_version(dep_type, minv=minv, maxv=maxv)\n assert found, \"No valid version defined for {} with max: {}, min: {}\" \\\n .format(dep_type, maxv, minv)","def test_exists(self, condition, undefined_paths, current_path):\n var = str(condition.find('variable').text)\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\n current_path += ((var, 'undefined variable'),)\n undefined_paths.add(current_path)\n return False\n else:\n return True","def verify_DIMACS(s):\r\n comments = True\r\n configured = False\r\n number_of_literals = 0\r\n number_of_clauses = 0\r\n clauses = 0\r\n for line in s.split('\\n'):\r\n line = line.strip()\r\n if len(line) == 0:\r\n continue\r\n\r\n if line[0] != 'c':\r\n if comments:\r\n comments = False\r\n else:\r\n if not comments:\r\n return 'Comments found outside of initial comment block.'\r\n\r\n if line[0] == 'p':\r\n if not configured:\r\n match = re.match(r'p cnf ([0-9]+) ([0-9]+)', line)\r\n if not match:\r\n return 'invalid p-line.'\r\n number_of_literals = int(match.group(1))\r\n number_of_clauses = int(match.group(2))\r\n configured = True\r\n else:\r\n return 'Multiple p lines found.'\r\n elif re.match(r'-?[0-9]+', line):\r\n if not configured:\r\n return 'clause before p-line.'\r\n literals = re.split(' ', line)\r\n for literal in literals[:-1]:\r\n if abs(int(literal)) > number_of_literals:\r\n return 'Variable number greater than number of variables'\r\n if literals[-1] != '0':\r\n return 'Clause does not end with a zero.'\r\n clauses += 1\r\n if number_of_clauses != clauses:\r\n return 'Not enough clauses'\r\n if configured:\r\n return ''","def satisfied(self, fields, field, values):\n\n requires = field.get(\"requires\", [])\n\n if isinstance(requires, str):\n requires = [requires]\n\n for require in requires:\n if require not in fields or not fields[require].validate(store=False):\n return False\n\n if \"condition\" in field and self.env.from_string(field[\"condition\"]).render(**values) != \"True\":\n return False\n\n return True","def test_conceptional_relations(id, conrel, expected_ids):\n synset = germanet_data.get_synset_by_id(id)\n related = synset.relations[conrel]\n np.testing.assert_equal(sorted([syn.id for syn in related]), sorted(expected_ids))","def testConditionalEffects(self):\n \n action = Parser.parse_as(cond_load.split(\"\\n\"), Action, self.domain)\n\n self.assert_(isinstance(action.effect, ConditionalEffect))\n self.assert_(isinstance(action.effect.condition, conditions.LiteralCondition))\n self.assert_(isinstance(action.effect.effect, SimpleEffect))","def verify_dependencies(self):\n dependencies = {\n \"manufacturers\": [\n {\"name\": \"VMware\", \"slug\": \"vmware\"},\n ],\n \"platforms\": [\n {\"name\": \"VMware ESXi\", \"slug\": \"vmware-esxi\"},\n {\"name\": \"Windows\", \"slug\": \"windows\"},\n {\"name\": \"Linux\", \"slug\": \"linux\"},\n ],\n \"sites\": [{\n \"name\": \"vCenter\",\n \"slug\": \"vcenter\",\n \"comments\": \"A default virtual site created to house objects \"\n \"that have been synced from vCenter.\",\n \"tags\": [\"Synced\", \"vCenter\"]\n }],\n \"cluster_types\": [\n {\"name\": \"VMware ESXi\", \"slug\": \"vmware-esxi\"}\n ],\n \"device_roles\": [\n {\n \"name\": \"Server\",\n \"slug\": \"server\",\n \"color\": \"9e9e9e\",\n \"vm_role\": True\n }],\n \"tags\": [\n {\n \"name\": \"Orphaned\",\n \"slug\": \"orphaned\",\n \"color\": \"607d8b\",\n \"comments\": \"This applies to objects that have become \"\n \"orphaned. The source system which has \"\n \"previously provided the object no longer \"\n \"states it exists.{}\".format(\n \" An object with the 'Orphaned' tag will \"\n \"remain in this state until it ages out \"\n \"and is automatically removed.\"\n ) if settings.NB_PRUNE_ENABLED else \"\"\n },\n {\n \"name\": self.vc_tag,\n \"slug\": format_slug(self.vc_tag),\n \"comments\": \"Objects synced from vCenter host \"\n \"{}. Be careful not to modify the name or \"\n \"slug.\".format(self.vc_tag)\n }]\n }\n # For each dependency of each type verify object exists\n log.info(\"Verifying all prerequisite objects exist in NetBox.\")\n for dep_type in dependencies:\n log.debug(\n \"Checking NetBox has necessary %s objects.\", dep_type[:-1]\n )\n for dep in dependencies[dep_type]:\n self.obj_exists(nb_obj_type=dep_type, vc_data=dep)\n log.info(\"Finished verifying prerequisites.\")","def check_id(self, id):","def _check_dependency(self, tcname, depends):\r\n tcindex = self.tcorder.index(tcname)\r\n dependsindex = []\r\n for i in depends:\r\n dependsindex.append(self.tcorder.index(i))\r\n for i in dependsindex:\r\n if tcindex < i:\r\n msg = \"%s must be ordered after %s\\n\" %(tcname, self.tcorder[i])\r\n self.dependency.append(msg)","def mempool_check_conditions_dict(\n unspent: CoinRecord,\n coin_announcement_names: Set[bytes32],\n puzzle_announcement_names: Set[bytes32],\n conditions_dict: Dict[ConditionOpcode, List[ConditionWithArgs]],\n prev_transaction_block_height: uint32,\n timestamp: uint64,\n) -> Optional[Err]:\n for con_list in conditions_dict.values():\n cvp: ConditionWithArgs\n for cvp in con_list:\n error: Optional[Err] = None\n if cvp.opcode is ConditionOpcode.ASSERT_MY_COIN_ID:\n error = mempool_assert_my_coin_id(cvp, unspent)\n elif cvp.opcode is ConditionOpcode.ASSERT_COIN_ANNOUNCEMENT:\n error = mempool_assert_announcement(cvp, coin_announcement_names)\n elif cvp.opcode is ConditionOpcode.ASSERT_PUZZLE_ANNOUNCEMENT:\n error = mempool_assert_announcement(cvp, puzzle_announcement_names)\n elif cvp.opcode is ConditionOpcode.ASSERT_HEIGHT_ABSOLUTE:\n error = mempool_assert_absolute_block_height_exceeds(cvp, prev_transaction_block_height)\n elif cvp.opcode is ConditionOpcode.ASSERT_HEIGHT_RELATIVE:\n error = mempool_assert_relative_block_height_exceeds(cvp, unspent, prev_transaction_block_height)\n elif cvp.opcode is ConditionOpcode.ASSERT_SECONDS_ABSOLUTE:\n error = mempool_assert_absolute_time_exceeds(cvp, timestamp)\n elif cvp.opcode is ConditionOpcode.ASSERT_SECONDS_RELATIVE:\n error = mempool_assert_relative_time_exceeds(cvp, unspent, timestamp)\n elif cvp.opcode is ConditionOpcode.ASSERT_MY_PARENT_ID:\n error = mempool_assert_my_parent_id(cvp, unspent)\n elif cvp.opcode is ConditionOpcode.ASSERT_MY_PUZZLEHASH:\n error = mempool_assert_my_puzzlehash(cvp, unspent)\n elif cvp.opcode is ConditionOpcode.ASSERT_MY_AMOUNT:\n error = mempool_assert_my_amount(cvp, unspent)\n if error:\n return error\n\n return None","def meets_advanced_requirements(challenge_id: int, user=None) -> bool:\n model = UniqueChallengeRequirements.query.filter_by(challenge_id=challenge_id).first()\n if user is None:\n user = get_current_user()\n if not model or not model.script or user.type == \"admin\":\n # No requirements present = always allowed\n return True\n\n def completed(arg) -> bool:\n for search in arg:\n if isinstance(search, str):\n challenge = Challenges.query.filter_by(name=search).first()\n if not challenge or not has_solved(challenge.id, user):\n return False\n elif isinstance(search, int):\n if not has_solved(search, user):\n return False\n else:\n raise LispIshRuntimeError(f\"(completed) function was passed an argument that was not a string or int.\")\n return True\n\n def cohort(arg) -> bool:\n for search in arg:\n if isinstance(search, str):\n cohort = UniqueChallengeCohort.query.filter_by(name=search).first()\n if not cohort or not UniqueChallengeCohortMembership.query.filter_by(user_id=user.id, cohort_id=cohort.id).first():\n return False\n elif isinstance(search, int):\n if not UniqueChallengeCohortMembership.query.filter_by(user_id=user.id, cohort_id=search).first():\n return False\n else:\n raise LispIshRuntimeError(f\"(cohort) function was passed an argument that was not a string or int.\")\n return True\n\n def before(arg, method='before') -> bool:\n if len(arg) != 1:\n raise LispIshRuntimeError(f\"({method}) function was passed {len(arg)} arguments, expected 1.\")\n if isinstance(arg[0], int):\n return time.time() < arg[0]\n try:\n timestamp = time.strptime(str(arg[0]), \"%Y-%m-%d\")\n return time.time() < time.mktime(timestamp)\n except ValueError:\n pass\n try:\n timestamp = time.strptime(str(arg[0]), \"%Y-%m-%d %H:%M\")\n return time.time() < time.mktime(timestamp)\n except ValueError:\n raise LispIshRuntimeError(f\"({method}) function was passed an invalid date string, expected an integer or a string with format YYYY-MM-DD or YYYY-MM-DD HH:MM\")\n\n def after(arg) -> bool:\n return not before(arg, 'after')\n\n lisp = LispIsh()\n try:\n method = lisp.parse(model.script.decode('utf-8'))\n return method.evaluate({\n 'COMPLETED': completed,\n 'COHORT': cohort,\n 'BEFORE': before,\n 'AFTER': after,\n 'USER-EMAIL': lambda _: user.email,\n 'USER-NAME': lambda _: user.name,\n 'USER-ID': lambda _: user.id,\n 'USER-SCORE': lambda _: user.score,\n })\n except LispIshParseError as err:\n print(f\"Error parsing LispIsh: {err}\")\n return False\n except LispIshRuntimeError as err:\n print(f\"Error evaluating LispIsh: {err}\")\n return False","def _check_case_sol_200(sol: int,\n subcase: Subcase,\n fem2: BDF,\n p0: Any,\n isubcase: int, subcases: int,\n log: Any):\n assert 'ANALYSIS' in subcase, 'sol=%s\\n%s' % (sol, subcase)\n\n analysis = subcase.get_parameter('ANALYSIS')[0]\n # BUCKLING\n if 'DESOBJ' in subcase:\n value = subcase.get_parameter('DESOBJ')[0]\n assert value in fem2.dresps, f'value={value} not in dresps'\n else:\n fem2.log.warning('no DESOBJ (DRESPi) in this subcase; is this a buckling preload case?')\n fem2.log.warning('\\n%s' % subcase)\n\n nopt = len(fem2.dvprels) + len(fem2.dvmrels) + len(fem2.dvcrels)\n if nopt == 0:\n fem2.log.error('no DVPRELs/DVMRELs/DVCRELs found')\n\n #--------------------------------------------------------------------------\n # DCONSTR\n if 'DESSUB' not in subcase and 'DESGLB' not in subcase:\n fem2.log.warning('no DESSUB/DESGLB (DCONSTR) in this subcase;'\n ' is this a buckling preload case?')\n log.warning('\\n%s' % subcase)\n\n if 'DESSUB' in subcase:\n value = subcase.get_parameter('DESSUB')[0]\n if value not in fem2.dconstrs:\n msg = 'value=%s not in dconstrs; Allowed DCONSTRs=%s' % (\n value, np.unique(list(fem2.dconstrs.keys())))\n raise RuntimeError(msg)\n if 'DESGLB' in subcase:\n value = subcase.get_parameter('DESGLB')[0]\n if value not in fem2.dconstrs:\n msg = 'value=%s not in dconstrs; Allowed DCONSTRs=%s' % (\n value, np.unique(list(fem2.dconstrs.keys())))\n raise RuntimeError(msg)\n #--------------------------------------------------------------------------\n\n if analysis in ['STATIC', 'STATICS']:\n solution = 101\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis in ['MODE', 'MODES']:\n solution = 103\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis in ['BUCK', 'BUCKLING']:\n solution = 105\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis == 'DFREQ':\n solution = 108\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis == 'MFREQ':\n if 'GUST' in subcase:\n solution = 146\n else:\n solution = 111\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis in ['MTRAN', 'MTRANS']:\n solution = 112\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis in ['SAERO', 'DIVERG', 'DIVERGE']:\n solution = 144\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis in ['FLUT', 'FLUTTER']:\n solution = 145\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis == 'DCEIG': # direct complex eigenvalues\n solution = 107\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n #elif analysis == 'MCEIG': # modal direct complex eigenvalues\n elif analysis == 'HEAT': # heat transfer analysis\n solution = 159\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n elif analysis == 'MCEIG': # modal complex eigenvalues\n solution = 110\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\n else:\n msg = 'analysis = %s\\nsubcase =\\n%s' % (analysis, subcase)\n raise NotImplementedError(msg)","def check_model(self, model):\n self.check_initial_conditions(model)\n self.check_variables(model)","def assert_single_condition_and_sbml_file(problem_config: Dict) -> None:\n if (len(problem_config[SBML_FILES]) > 1\n or len(problem_config[CONDITION_FILES]) > 1):\n # TODO https://github.com/ICB-DCM/PEtab/issues/188\n # TODO https://github.com/ICB-DCM/PEtab/issues/189\n raise NotImplementedError(\n 'Support for multiple models or condition files is not yet '\n 'implemented.')","def test_variable(self, condition, undefined_paths, current_path):\n var = str(condition.find('name').text)\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\n current_path += ((var, 'undefined variable'),)\n undefined_paths.add(current_path)\n return False\n else:\n return True","def _assert_pip_requirements(model_uri, requirements, constraints=None, strict=False):\n local_path = _download_artifact_from_uri(model_uri)\n txt_reqs = _read_lines(os.path.join(local_path, _REQUIREMENTS_FILE_NAME))\n conda_reqs = _get_pip_deps(_read_yaml(\n os.path.join(local_path, _CONDA_ENV_FILE_NAME)))\n compare_func = set.__eq__ if strict else set.__le__\n requirements = set(requirements)\n assert compare_func(requirements, set(txt_reqs))\n assert compare_func(requirements, set(conda_reqs))\n\n if constraints is not None:\n assert f\"-c {_CONSTRAINTS_FILE_NAME}\" in txt_reqs\n assert f\"-c {_CONSTRAINTS_FILE_NAME}\" in conda_reqs\n cons = _read_lines(os.path.join(local_path, _CONSTRAINTS_FILE_NAME))\n assert compare_func(set(constraints), set(cons))","def ok(self, solution):\n if self.constraints is not None:\n for constraint in self.constraints:\n if not constraint(solution):\n return False\n return True","def satisfied_constraints(self,word_id, possible_word):\r\n constraints = self.words[word_id].constraints\r\n results = {}\r\n # print(\"word_id: {}, possible_word: {}, visited: {}, num_of_satisfied: {}\".format(word_id, possible_word, visited, num_of_satisfied)) \r\n for constraint in constraints:\r\n possibilities = []\r\n if word_id == constraint.word1:\r\n for possible_word2 in self.words[constraint.word2].domain:\r\n check = constraint.check_constraint(possible_word,possible_word2)\r\n if check:\r\n possibilities.append(possible_word2)\r\n if len(possibilities) != 0:\r\n results[constraint.word2] = possibilities\r\n elif word_id == constraint.word2:\r\n for possible_word2 in self.words[constraint.word1].domain:\r\n check = constraint.check_constraint(possible_word2,possible_word)\r\n if check:\r\n possibilities.append(possible_word2)\r\n if len(possibilities) != 0:\r\n results[constraint.word1] = possibilities\r\n return results","def check_constraints ( A, S, complete ) :\n\t\n\tok = True\n\t\n\tfor i in range(len(complete)) :\n\t\tif complete[i] :\n\t\t\tif not (dot(A[i],S) == 0) :\n\t\t\t\tok = False\n\t\t\t\tprint '\\n'\n\t\t\t\tprint '*** warning *** constraint %d not verified' % (i)\n\t\t\t\tvars_inds = (where(abs(A[i]) == 1))[0]\n\t\t\t\tprint 'variables involved:', vars_inds\n\t\t\t\tprint 'displacements:', S[vars_inds]\n\t\t\t\tprint\n\t\t\t\t#programPause = raw_input(\"Press the <ENTER> key to continue...\")\n\t\t\t\t\n\treturn ok","def mempool_assert_my_parent_id(condition: ConditionWithArgs, unspent: CoinRecord) -> Optional[Err]:\n if unspent.coin.parent_coin_info != condition.vars[0]:\n return Err.ASSERT_MY_PARENT_ID_FAILED\n return None","def _assert_postconditions(postconditions: List[Contract], resolved_kwargs: Mapping[str, Any],\n func: CallableT) -> Optional[BaseException]:\n assert 'result' in resolved_kwargs, \\\n \"Expected 'result' to be already set in resolved kwargs before calling this function.\"\n\n for contract in postconditions:\n if inspect.iscoroutinefunction(contract.condition):\n raise ValueError(\"Unexpected coroutine (async) condition {} for a sync function {}.\".format(\n contract.condition, func))\n\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\n\n check = contract.condition(**condition_kwargs)\n\n if inspect.iscoroutine(check):\n raise ValueError(\"Unexpected coroutine resulting from the condition {} for a sync function {}.\".format(\n contract.condition, func))\n\n if not_check(check=check, contract=contract):\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\n\n return exception\n\n return None","def check_requirement(self):\n raise NotImplementedError","def test_elemental_inclusion_constraint():\n name = \"Property Band gap\"\n elements = [\"Ga\", \"N\"]\n\n # Bad logic raises an error\n try:\n asdf = \"asdf\"\n c = ElementalInclusionConstraint(name=name, elements=elements, logic=asdf)\n assert False\n except CitrinationClientError:\n pass\n\n # Good logics do not raise an error\n should = \"should\"\n ElementalInclusionConstraint(name=name, elements=elements, logic=should)\n must = \"must\"\n ElementalInclusionConstraint(name=name, elements=elements, logic=must)\n exclude = \"exclude\"\n ElementalInclusionConstraint(name=name, elements=elements, logic=exclude)\n\n # Dictionary is formatted properly\n logic=\"should\"\n c = ElementalInclusionConstraint(name=name, elements=elements, logic=logic)\n\n mapped_c = c.to_dict()\n\n assert mapped_c[\"type\"] is \"elementalInclusionConstraint\"\n assert mapped_c[\"name\"] is name\n assert mapped_c[\"options\"][\"logic\"] is logic\n assert mapped_c[\"options\"][\"elements\"] is elements","def checkDeps( self ):\n\n # skip dependency check for downloading only\n if( self.downloadOnly ):\n return True\n\n # skip dependency check if package is going to be installed\n if( self.mode == \"install\" ):\n return True\n\n log.debug( 'Checking dependencies of %s', self.name )\n \n file = self.realPath() + \"/.dependencies\"\n \n r = True\n\n # if file doesn't exist return True\n if( not os.path.exists( file )):\n return True\n\n # open dependencies file\n f = open( file )\n filedeplist = {}\n for line in f.readlines():\n line = line.strip()\n if( (not line.startswith(os.linesep)) and (not line.startswith(\"#\")) \\\n and (len(line) > 0 )):\n tokens = line.split(\":\")\n filedeplist[ tokens[0] ] = tokens[1]\n f.close()\n\n log.debug( 'Dependencies read from file: %s', filedeplist )\n\n # get actual dependecies\n deplist={}\n self.getDepList(deplist)\n del deplist[self.name]\n\n log.debug( 'Dependencies found in current cfg file: %s', deplist )\n \n # compare dependencies\n for k, v in filedeplist.iteritems():\n if( deplist.has_key( k )):\n if( deplist[k] != v ):\n if( os.path.basename(deplist[k]) != os.path.basename(v) ):\n if( r ):\n print \"*** WARNING: ***\\n***\\tFollowing dependencies from \" + self.name + \" located at [ \" \\\n + self.realPath() + \" ] failed:\\n***\"\n print \"***\\t * \" + k + \" \" + os.path.basename(v) + \" differs from version \" \\\n + os.path.basename(deplist[k]) + \" defined in your config file..\"\n r = False\n else:\n if( r ): #just print this once\n print \"*** WARNING: ***\\n***\\tFollowing dependencies from \" + self.name + \" located at [ \" + self.realPath() \\\n + \" ] failed:\\n***\"\n print \"***\\t * \" + k + \" not found in your config file!!\"\n r = False\n \n\n if( not r ):\n print \"***\"\n if( self.useLink ):\n print \"***\\t\" + self.name + \" is in \\\"link\\\" mode, if you want to rebuild it with the new dependencies set it to \\\"use\\\" mode...\"\n r = True\n else:\n if( not self.parent.noAutomaticRebuilds ):\n print \"***\\t * \" + self.name + \" changed to \\\"install\\\" mode and rebuild flag set to True...\"\n self.mode = \"install\"\n self.rebuild = True\n self.preCheckDeps()\n print \"***\\n***\\tUpdating dependency tree ( modules that depend on \" + self.name + \" need also to be rebuilt )...\\n***\"\n self.updateDepTree([])\n print \"***\\n***\\tif you do NOT want to rebuild this module(s) just answer \\\"no\\\" later on in the installation process,\\n\" \\\n + \"***\\tor set the global flag ilcsoft.noAutomaticRebuilds=True in your config file...\"\n else:\n print \"***\\n***\\tglobal flag ilcsoft.noAutomaticRebuilds is set to True, nothing will be done...\\n***\"\n return r","def __satisfies_necessary_and_sufficient_conditions(g):\n # Condition 0: at least 1 Edge\n if g.get_E() == 0:\n return False\n # Condition 1: indegree(v) == outdegree(v) for every vertex\n for v in range(g.get_V()):\n if g.outdegree() != g.indegree(v):\n return False\n # Condition 2: graph is connected, ignoring isolated vertices\n h = Graph(g.get_V())\n for v in range(g.get_V()):\n for w in g.adj_vertices(v):\n h.add_edge(v, w)\n # check that all non-isolated vertices are connected\n s = DirectedEulerianCycle.__non_isolated_vertex(g)\n bfs = BreadthFirstPaths(h, s)\n for v in range(g.get_V()):\n if h.degree(v) > 0 and not bfs.has_path_to(v):\n return False\n return True","def check_integrity(self) -> None:\n for subset in self.subsets:\n if not self._check_subset_integrity(subset):\n raise ValueError(f\"subset {subset} not found or corrupt\")","def _check_c(self, constraint, *variables):\n c = {c.__class__ for c in self._layout.solver.get(*variables)}\n if constraint:\n self.assertTrue(constraint in c)\n else:\n self.assertFalse(c)","def test_incoming_conceptional_relations(id, conrel, expected_ids):\n synset = germanet_data.get_synset_by_id(id)\n related = synset.incoming_relations[conrel]\n np.testing.assert_equal(sorted([syn.id for syn in related]), sorted(expected_ids))","def check_all_constraints(csp) :\n\n for constraint in csp.get_all_constraints():\n assigned1 = csp.get_assigned_value(constraint.var1)\n assigned2 = csp.get_assigned_value(constraint.var2)\n check = constraint.check(assigned1,assigned2)\n if check==False and assigned1!=None and assigned2!=None:\n return False \n return True","def invariant(self):\n\t\treturn ((self.vcdnId > 0) and (self.popId > 0))","def validate(self):\n for rosdep_key in self:\n # Ensure all dependencies have definitions\n # i.e.: Ensure we aren't pointing to invalid rosdep keys\n for dependency in self[rosdep_key]['dependencies']:\n if dependency not in self:\n raise KeyError(\n 'Invalid Graph Structure: rosdep key `%s` does not exist in the dictionary of resolutions.'\n % dependency)\n self[dependency]['is_root'] = False\n # Check each entry for cyclical dependencies\n for rosdep_key in self:\n self.detect_cycles(rosdep_key, [])","def test_check_job_dependencies_ready(mock_sqs_queue, database):\n # Mock so it always returns the mock queue for the test\n mock_sqs_queue.return_value = SQSMockQueue\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=0)\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n sess.add_all([sub, job, job_2])\n sess.commit()\n\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\n sess.add(job_dep)\n sess.commit()\n\n check_job_dependencies(job.job_id)\n\n assert job_2.job_status_id == JOB_STATUS_DICT['ready']","def check(self):\n for req in self.requirements:\n if not self.COMPARISON_OPERATORS[req.operator](\n packaging.version.parse(get_installed_version(req.package)),\n packaging.version.parse(req.version),\n ):\n fail(f\"The cluster requires {req.package}{req.operator}{req.version}\")","def _is_conveyance_id_valid(self, conveyance_id):\n sql = \"SELECT id FROM {} WHERE id=?\".format(self.conveyance_type)\n\n try:\n query_result = self.cursor.execute(sql, (str(conveyance_id),))\n if query_result.fetchall():\n return True\n return False\n except Exception as e:\n raise Exception(\n \"An error occurred while fetching a %s in the database: query: %s - message: %s\"\n % (self.conveyance_type, sql, e)\n )","def validate(self, fgraph):\r\n\r\n if self.destroyers:\r\n ords = self.orderings(fgraph)\r\n\r\n if _contains_cycle(fgraph, ords):\r\n raise InconsistencyError(\"Dependency graph contains cycles\")\r\n else:\r\n #James's Conjecture:\r\n #If there are no destructive ops, then there can be no cycles.\r\n pass\r\n return True","def check(self,):\n self.is_valid_according_policy()","def validate(self, fgraph):\r\n\r\n if self.destroyers:\r\n ords = self.orderings(fgraph)\r\n\r\n if _contains_cycle(fgraph, ords):\r\n raise InconsistencyError(\"Dependency graph contains cycles\")\r\n else:\r\n #James's Conjecture:\r\n #If there are no destructive ops, then there can be no cycles.\r\n pass\r\n return True","def solved(self):\n if not self.all_variables_assigned():\n return False\n for constraint in self.constraints:\n if not constraint.satisfied(*[self.var_dict[name] for name in constraint.var_names]):\n return False\n return True","def check(self):\n\n constrains = pm.ls(type='constraint')\n uselessConstrains = []\n\n for const in constrains:\n connections = const.listConnections(scn=True, s=False, d=True)\n if const in connections:\n connections.remove(const)\n\n if len(connections) == 0:\n uselessConstrains.append(const)\n\n if not uselessConstrains:\n self.status = \"OK\"\n else:\n self.status = self.errorMode\n self.errorNodes = uselessConstrains\n for obj in uselessConstrains:\n self.addError(\"%s doesn't have outgoing connections.\" % obj)\n self.errorMessage = \"%s useless constrains\" % (\n len(uselessConstrains))","def addConstraintOnIdTransition(self, pos):\n super().addConstraintOnIdTransition(pos)\n\n self.s.add(Implies(self.startLoop == pos, self.faultOccursByThePast[pos]))\n\n for j in range(len(self.transitionList)):\n self.s.add(Implies(self.faultyPath[pos - 1] == j, self.stateFaultyPath[pos] == self.transitionList[j][1]))\n self.s.add(Implies(self.normalPath[pos - 1] == j, self.stateNormalPath[pos] == self.transitionList[j][1]))\n\n if pos > 0:\n self.s.add(Implies(self.startLoop == pos - 1, self.projStartStateNormal == self.stateNormalPath[pos]))\n self.s.add(Implies(self.startLoop == pos - 1, self.projStartStateFaulty == self.stateFaultyPath[pos]))\n\n self.s.add(Implies(self.endLoop == pos, self.projEndStateNormal == self.stateNormalPath[pos]))\n self.s.add(Implies(self.endLoop == pos, self.projEndStateFaulty == self.stateFaultyPath[pos]))\n\n self.s.add(Or(self.startLoop < pos, Not(self.checkSynchro[pos]), self.idTransitionFaultyPath[pos] == self.idTransitionNormalPath[pos]))","def consistency_check(self):\n for opt, opt_def in self.opt_dict.iteritems():\n selected_imp = opt_def['selected_imp']\n if selected_imp == 'none':\n continue\n else:\n mapped_opt = self.imp2opt_dict[selected_imp]\n\n if mapped_opt != opt:\n emsg = 'ERROR: imp2opt_dict fails to map {i} to {o}'\n print emsg.format(i=selected_imp, o=opt)\n\n for imp, opt in self.imp2opt_dict.iteritems():\n if imp == 'none':\n print 'ERROR: Found \"none\" as a keyword in imp2opt_dict'\n continue\n elif opt == 'none':\n continue\n else:\n selected_imp = self.opt_dict[opt]['selected_imp']\n\n if imp != selected_imp:\n emsg = 'ERROR: imp2opt_dict fails to map {i} to {o}'\n print emsg.format(i=selected_imp, o=opt)","def check_deterministic_constraints(self, x):\n return True","def check_deterministic_constraints(self, x):\n return True","def _check_if_model_ready(self, model_id):\n # check model_id is not None\n if model_id is None:\n logger.error(\"Provided model id is None. Please provide valid model id.\")\n return False\n\n # check if the model training is completed successfully to consume by next step\n model_exist = self.model_db_client.check_model_record_exists(self.experiment_id, model_id)\n if not model_exist:\n logger.error(\n f\"Model with mode_id '{model_id}' was not found in model table. \"\n \"Please create a model first\"\n )\n return False\n\n # 'model_id' found in table, check if the 'model_id' is trained\n model_to_deploy = ModelManager(\n model_db_client=self.model_db_client,\n experiment_id=self.experiment_id,\n model_id=model_id,\n )\n\n if not model_to_deploy.model_record.is_train_completed():\n logger.warning(\n f\"Model '{model_id}' is in status of \"\n f\"{model_to_deploy.model_record._train_state}, Please check later.\"\n )\n return False\n\n return True","def can_commit(self):\n for name in self.conditions:\n if name in _conditions:\n condition = _conditions[name]\n # If one condition matches, we're good\n if self.check_condition(condition):\n return True\n return False","def get_depend_def_by_step_id(self, step_id):\n try:\n result = self._session.query(StepEntity.name).\\\n filter(StepEntity.id == StepDependencyEntity.parent_id).\\\n filter(StepDependencyEntity.child_id == step_id).\\\n all()\n\n result_list = [\n row[0] for row in result\n ]\n\n except SQLAlchemyError as err:\n Log.an().error('sql exception [%s]', str(err))\n return False\n\n return result_list","def test_check_job_dependencies_not_finished(database):\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n sess.add_all([sub, job])\n sess.commit()\n\n with pytest.raises(ValueError):\n check_job_dependencies(job.job_id)","def verify(condition):\n global _is_in_verify_within\n if not condition:\n calling_frame = inspect.currentframe().f_back\n error_message = 'verify() failed at line {} in \"{}\"'.format(calling_frame.f_lineno,\n calling_frame.f_code.co_filename)\n if not _is_in_verify_within:\n print error_message\n return False\n return True"],"string":"[\n \"def _verify_dependencies(self, cond_id, undefined_paths, current_path):\\n\\n # Exception for izpack conditions:\\n if cond_id in self.conditions.properties[WHITE_LIST]:\\n return True\\n\\n # Short-circuit on well-defined conditions:\\n if cond_id in self.well_defined:\\n return True\\n\\n # Short-circuit ill-defined conditions:\\n if cond_id in list(self.ill_defined.keys()):\\n current_path = current_path + ((cond_id, 'ill-defined condition'),)\\n undefined_paths.add(current_path)\\n return False\\n\\n # Cycle checking:\\n tup = (cond_id, 'condition')\\n if tup in current_path:\\n current_path += ((cond_id, 'cyclic condition reference'),)\\n undefined_paths.add(current_path)\\n return False\\n\\n # Check for undefined condition.\\n if not cond_id in self.conditions.get_keys():\\n tup = (cond_id, 'undefined condition')\\n current_path += (tup,)\\n undefined_paths.add(current_path)\\n return False\\n\\n current_path += (tup,)\\n condition = self.conditions.container[cond_id]\\n condition_type = condition['type']\\n\\n if condition_type in list(self.condition_tests.keys()) and not \\\\\\n self.condition_tests[condition_type](self, condition, undefined_paths, current_path):\\n return False\\n\\n self.well_defined.add(cond_id)\\n return True\",\n \"def verify_dependencies(self, cond_id):\\n undefined_paths = set()\\n self._verify_dependencies(cond_id, undefined_paths, tuple())\\n return undefined_paths\",\n \"def test_verify_all_dependencies(self):\\n\\n for condition in self.all_references():\\n result = self.verify_dependencies(condition)\\n\\n if result:\\n self.ill_defined[condition] = result\\n else:\\n self.well_defined.add(condition)\\n\\n return self.ill_defined\",\n \"def _check_conditional_dependency(obj, condition, package, severity, msg=None):\\n if condition:\\n if msg is None:\\n msg = (\\n f\\\"The specific parameter values of {obj.__class__.__name__}'s \\\"\\n f\\\"class instance require `{package}` installed. Please run: \\\"\\n f\\\"`pip install {package}` to \\\"\\n f\\\"install the `{package}` package. \\\"\\n )\\n try:\\n _check_soft_dependencies(package, severity=severity, obj=obj)\\n except ModuleNotFoundError as e:\\n raise ModuleNotFoundError(msg) from e\",\n \"def check_control_dependency(\\n self,\\n context: SlicingContext,\\n unique_instr: UniqueInstruction,\\n code_object_id: int,\\n ) -> bool:\\n control_dependency = False\\n\\n if not unique_instr.is_cond_branch():\\n return False\\n\\n code_object: CodeObjectMetaData = self._known_code_objects[code_object_id]\\n cdg: ControlDependenceGraph = code_object.cdg\\n curr_node = self.get_node(unique_instr.node_id, cdg)\\n assert curr_node, \\\"Invalid node id\\\"\\n successors = cdg.get_successors(curr_node)\\n\\n instr_ctrl_deps_copy = context.instr_ctrl_deps.copy()\\n\\n # Check if any instruction on S_C is control dependent on current instruction\\n # If so: include current instruction in the slice, remove all instructions\\n # control dependent on current instruction\\n for instr in context.instr_ctrl_deps:\\n instr_node = self.get_node(instr.node_id, cdg)\\n if instr_node in successors:\\n instr_ctrl_deps_copy.remove(instr)\\n control_dependency = True\\n context.instr_ctrl_deps = instr_ctrl_deps_copy\\n\\n return control_dependency\",\n \"def test_are_dependency_packs_valid(self, current_file, id_set, answer):\\n validator = get_validator(current_file)\\n assert validator.are_dependency_packs_valid(id_set) is answer\",\n \"def testConditionChecking(self):\\n\\n state = State.from_problem(self.prob)\\n \\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition))\\n\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt2\\\"], self.prob):\\n self.assertFalse(state.is_satisfied(drive.precondition))\",\n \"def testConditionReasons(self):\\n \\n state = State.from_problem(self.prob)\\n\\n relevantVars = []\\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\\n\\n relevantVars = set(relevantVars)\\n \\n s1 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"pos1\\\"]])\\n s2 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"apt1\\\"]])\\n s3 = StateVariable(self.prob.functions[\\\"location-of\\\"][0], [self.prob[\\\"tru1\\\"]])\\n \\n self.assertEqual(len(relevantVars), 3)\\n self.assert_(s1 in relevantVars)\\n self.assert_(s2 in relevantVars)\\n self.assert_(s3 in relevantVars)\",\n \"def check_dependencies():\\n\\n vars_valid = check_variables(\\n AirflowVars.PROJECT_ID, AirflowVars.TERRAFORM_ORGANIZATION, AirflowVars.VM_DAGS_WATCH_LIST\\n )\\n conns_valid = check_connections(AirflowConns.TERRAFORM)\\n\\n if not vars_valid or not conns_valid:\\n raise AirflowException(\\\"Required variables or connections are missing\\\")\",\n \"def check_deps(self):\\n\\t\\tshutit_global.shutit_global_object.yield_to_draw()\\n\\t\\tcfg = self.cfg\\n\\t\\tself.log('PHASE: dependencies', level=logging.DEBUG)\\n\\t\\tself.pause_point('\\\\nNow checking for dependencies between modules', print_input=False, level=3)\\n\\t\\t# Get modules we're going to build\\n\\t\\tto_build = [\\n\\t\\t\\tself.shutit_map[module_id] for module_id in self.shutit_map\\n\\t\\t\\tif module_id in cfg and cfg[module_id]['shutit.core.module.build']\\n\\t\\t]\\n\\t\\t# Add any deps we may need by extending to_build and altering cfg\\n\\t\\tfor module in to_build:\\n\\t\\t\\tself.resolve_dependencies(to_build, module)\\n\\n\\t\\t# Dep checking\\n\\t\\tdef err_checker(errs, triples):\\n\\t\\t\\t\\\"\\\"\\\"Collate error information.\\n\\t\\t\\t\\\"\\\"\\\"\\n\\t\\t\\tnew_triples = []\\n\\t\\t\\tfor err, triple in zip(errs, triples):\\n\\t\\t\\t\\tif not err:\\n\\t\\t\\t\\t\\tnew_triples.append(triple)\\n\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\tfound_errs.append(err)\\n\\t\\t\\treturn new_triples\\n\\n\\t\\tfound_errs = []\\n\\t\\ttriples = []\\n\\t\\tfor depender in to_build:\\n\\t\\t\\tfor dependee_id in depender.depends_on:\\n\\t\\t\\t\\ttriples.append((depender, self.shutit_map.get(dependee_id), dependee_id))\\n\\n\\t\\ttriples = err_checker([ self.check_dependee_exists(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\\n\\t\\ttriples = err_checker([ self.check_dependee_build(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\\n\\t\\ttriples = err_checker([ check_dependee_order(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\\n\\n\\t\\tif found_errs:\\n\\t\\t\\treturn [(err,) for err in found_errs]\\n\\n\\t\\tself.log('Modules configured to be built (in order) are: ', level=logging.DEBUG)\\n\\t\\tfor module_id in self.module_ids():\\n\\t\\t\\tmodule = self.shutit_map[module_id]\\n\\t\\t\\tif cfg[module_id]['shutit.core.module.build']:\\n\\t\\t\\t\\tself.log(module_id + ' ' + str(module.run_order), level=logging.DEBUG)\\n\\t\\tself.log('\\\\n', level=logging.DEBUG)\\n\\n\\t\\treturn []\",\n \"def test_check_job_dependencies_prior_dependency_has_errors(database):\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=3)\\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n sess.add_all([sub, job, job_2])\\n sess.commit()\\n\\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\\n sess.add(job_dep)\\n sess.commit()\\n\\n check_job_dependencies(job.job_id)\\n\\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']\",\n \"def consistency_checker(model,universals,existentials):\\n universal_set=set(universals)\\n existential_set=set(existentials)\\n #Additionally to the universal and existential variables the model may\\n #contain additional auxiliary variables -- e.g. for setting default values.\\n #We consider these variables such as the existential variables.\\n auxiliary_variables_in_model={abs(l) for clause in model for l in clause \\n if (not abs(l) in universal_set) and (not abs(l) in existential_set)}\\n existential_set = existential_set.union(auxiliary_variables_in_model)\\n result, certificate = checkModelQBF(model, universal_set, existential_set)\\n return result\",\n \"def condition_details(\\n self,\\n condition_id: str,\\n params: Optional[Dict] = None,\\n headers: Optional[Dict] = None,\\n ) -> ConditionDetails:\\n method = self._get_method(\\\"condition_details\\\")\\n method = method.format(**{\\\"id\\\": condition_id})\\n\\n return self.call_api_get(method=method, params=params, headers=headers)\",\n \"def valid_dependency(self, dep):\\r\\n return True\",\n \"def check_requirements(config=None):\\n for dependency, module_requirements in (\\n requirements(config, include_conditional=False).items()):\\n for module_requirement in module_requirements:\\n if \\\">=\\\" in module_requirement:\\n module_name, required_version = module_requirement.split(\\\">=\\\")\\n version_test = \\\">=\\\"\\n elif \\\"==\\\" in module_requirement:\\n module_name, required_version = module_requirement.split(\\\"==\\\")\\n version_test = \\\"==\\\"\\n else:\\n module_name = module_requirement\\n version_test = None\\n\\n try:\\n module = __import__(module_name)\\n except ImportError:\\n logging.exception(\\n \\\"Can't import %r which is part of %r\\\",\\n module_name, dependency\\n )\\n raise MissingRequirementError(\\n \\\"Can't import %r which is part of %r\\\"\\n % (module_name, dependency), module_name, dependency\\n )\\n version = getattr(module, \\\"__version__\\\", None)\\n file_path = getattr(module, \\\"__file__\\\", None)\\n logger.info(\\n \\\"Using %r version %r from %r to satisfy %r\\\",\\n module_name, version, file_path, dependency\\n )\\n\\n if version_test == \\\">=\\\":\\n if version is None:\\n raise MissingRequirementError(\\n \\\"Version of %r isn't set as __version__ of module %r\\\"\\n % (dependency, module_name), module_name, dependency\\n )\\n if LooseVersion(version) < LooseVersion(required_version):\\n raise MissingRequirementError(\\n \\\"Version of %r in %r is too old. %r < %r\\\"\\n % (dependency, file_path, version, required_version),\\n module_name, dependency\\n )\\n elif version_test == \\\"==\\\":\\n if version is None:\\n raise MissingRequirementError(\\n \\\"Version of %r isn't set as __version__ of module %r\\\"\\n % (dependency, module_name), module_name, dependency\\n )\\n if LooseVersion(version) != LooseVersion(required_version):\\n raise MissingRequirementError(\\n \\\"Unexpected version of %r in %r. %r != %r\\\"\\n % (dependency, file_path, version, required_version),\\n module_name, dependency\\n )\",\n \"def check_explicit_data_dependency( # noqa: C901\\n self,\\n context: SlicingContext,\\n unique_instr: UniqueInstruction,\\n traced_instr: ExecutedInstruction | None,\\n ) -> tuple[bool, set[str]]:\\n complete_cover = False\\n partial_cover = False\\n attribute_creation_uses = set()\\n\\n if not unique_instr.is_def():\\n return False, set()\\n\\n # Check variable definitions\\n if isinstance(traced_instr, ExecutedMemoryInstruction):\\n complete_cover = self._check_variables(context, traced_instr)\\n\\n # When an object, of which certain used attributes are taken from,\\n # is created, the slicer has to look for the definition of normal variables\\n # instead of these attributes, since they are defined as variables and not\\n # as attributes on class/module level.\\n if traced_instr.arg_address and traced_instr.object_creation:\\n attribute_uses = set()\\n for use in context.attr_uses:\\n if use.startswith(hex(traced_instr.arg_address)) and len(use) > len(\\n hex(traced_instr.arg_address)\\n ):\\n complete_cover = True\\n attribute_uses.add(use)\\n attribute_creation_uses.add(\\\"_\\\".join(use.split(\\\"_\\\")[1:]))\\n for use in attribute_uses:\\n context.attr_uses.remove(use)\\n\\n # Check for address dependencies\\n if traced_instr.is_mutable_type and traced_instr.object_creation:\\n # Note that the definition of an object here means the\\n # creation of the object.\\n address_dependency = self._check_scope_for_def(\\n context.var_uses_addresses,\\n hex(traced_instr.arg_address),\\n None,\\n None,\\n )\\n if address_dependency:\\n complete_cover = True\\n\\n # Check for the attributes which were converted to variables\\n # (explained in the previous construct)\\n if traced_instr.argument in context.attribute_variables:\\n complete_cover = True\\n context.attribute_variables.remove(str(traced_instr.argument))\\n\\n if isinstance(traced_instr, ExecutedAttributeInstruction):\\n # check attribute defs\\n if traced_instr.combined_attr in context.attr_uses:\\n complete_cover = True\\n context.attr_uses.remove(traced_instr.combined_attr)\\n # Partial cover: modification of attribute of\\n # object in search for definition\\n if hex(traced_instr.src_address) in context.var_uses_addresses:\\n partial_cover = True\\n\\n return (complete_cover or partial_cover), attribute_creation_uses\",\n \"def dependencies_satisfied(self, module) -> bool:\\n for k, v in module.requirements.items():\\n if k not in self.modules:\\n return False\\n found_ver = self.modules[k].version\\n if isinstance(v, str):\\n return found_ver == v\\n elif isinstance(v, dict):\\n if \\\"eq\\\" in v and (found_ver != v[\\\"eq\\\"]):\\n return False\\n if \\\"min\\\" in v and (found_ver < v[\\\"min\\\"]):\\n return False\\n if \\\"max\\\" in v and (found_ver > v[\\\"max\\\"]):\\n return False\\n else:\\n return True\\n return True\",\n \"def check_condition(self):\\n\\n\\t\\traw_context = {\\n\\t\\t\\t'folk': self.folk\\n\\t\\t}\\n\\n\\t\\tstatus, param = self.execute(self.mission_grid, 'condition', self.pending_mission.kingdom, raw_context)\\n\\t\\treturn status\",\n \"def test_check_model_dependencies_complete(dependency_testing_model, complete_env) -> None:\\n assert check_model_dependencies(\\n model_cls=dependency_testing_model,\\n environment=complete_env,\\n raise_for_missing=False,\\n )\",\n \"def validate_dependencies(self, session, entry):\",\n \"def satisfy(self):\\n self.stub.Satisfy(\\n depend_pb2.DependSatisfyRequest(depend=self.data), timeout=Cuebot.Timeout)\",\n \"def test_are_integrations_in_dependency_packs(self, current_file, id_set, answer):\\n validator = get_validator(current_file)\\n assert validator.are_integrations_in_dependency_packs(id_set) is answer\",\n \"def check_program_validity(self):\\n for fact in self._facts:\\n if fact not in self._predicates:\\n raise Exception(\\\"Invalid fact, no IDB defined: \\\" + fact)\\n for clause in self._facts[fact]:\\n self.check_clause_validity(clause)\\n\\n for rule in self._rules:\\n if rule not in self._predicates:\\n raise Exception(\\\"Invalid rule, no IDB defined: \\\" + rule)\\n for clause in self._rules[rule]:\\n self.check_clause_validity(clause.head)\\n for body_clause in clause.body:\\n self.check_clause_validity(body_clause)\",\n \"def mempool_assert_my_coin_id(condition: ConditionWithArgs, unspent: CoinRecord) -> Optional[Err]:\\n if unspent.coin.name() != condition.vars[0]:\\n return Err.ASSERT_MY_COIN_ID_FAILED\\n return None\",\n \"def match_conditions(id_dict, conditions, aircraft_database_df):\\n q = '&'.join([ '(' + k + '==' + f'\\\"{str(v)}\\\"' + ')' for (k,v) in id_dict.items() ])\\n entry = aircraft_database_df.query(q)\\n if entry.empty:\\n return False\\n else:\\n for (k, v) in conditions.items():\\n if not all(entry[k].str.match(v, na=False)):\\n return False\\n return True\",\n \"def _check_family(self):\\n for (s, (b, c)), (cond, ref) in families.items():\\n if s != self.SYMBOL or len(b) != self._.d:\\n continue\\n vars = tuple(set(sum(map(variables, b + c), ())))\\n sols = _solve([SR(l) == r for l, r\\n in zip(self._.b[:-1] + self._.c[1:], b + c)],\\n vars)\\n if any(checkConditions(cond, sol) for sol in sols\\n if is_integral(sol)):\\n raise InfeasibleError(refs=ref)\",\n \"def condition(*args, delete: bool=True, dependency: Union[AnyStr, List[AnyStr]]=\\\"\\\", initialize:\\n bool=True, script: AnyStr=\\\"\\\", state: bool=True, q=True, query=True, e=True,\\n edit=True, **kwargs)->Union[None, Any]:\\n pass\",\n \"def check_status(self, id):\\n raise NotImplementedError()\",\n \"def are_all_deps_fulfilled(self, package: 'Package', only_make_check: bool = False,\\n only_depends: bool = False, print_reason: bool = False) -> bool:\\n\\n for dep in package.relevant_deps(only_make_check=only_make_check, only_depends=only_depends):\\n if not self.provided_by(dep):\\n if print_reason:\\n aurman_note(\\n \\\"Dependency {} of package {} is not fulfilled\\\".format(\\n Colors.BOLD(Colors.LIGHT_MAGENTA(dep)),\\n Colors.BOLD(Colors.LIGHT_MAGENTA(package.name))\\n )\\n )\\n return False\\n else:\\n return True\",\n \"def dependencies_are_met(\\n self,\\n parent_job: Optional['Job'] = None,\\n pipeline: Optional['Pipeline'] = None,\\n exclude_job_id: Optional[str] = None,\\n ) -> bool:\\n connection = pipeline if pipeline is not None else self.connection\\n\\n if pipeline is not None:\\n connection.watch(*[self.key_for(dependency_id) for dependency_id in self._dependency_ids])\\n\\n dependencies_ids = {_id.decode() for _id in connection.smembers(self.dependencies_key)}\\n\\n if exclude_job_id:\\n dependencies_ids.discard(exclude_job_id)\\n if parent_job and parent_job.id == exclude_job_id:\\n parent_job = None\\n\\n if parent_job:\\n # If parent job is canceled, treat dependency as failed\\n # If parent job is not finished, we should only continue\\n # if this job allows parent job to fail\\n dependencies_ids.discard(parent_job.id)\\n if parent_job.get_status() == JobStatus.CANCELED:\\n return False\\n elif parent_job._status == JobStatus.FAILED and not self.allow_dependency_failures:\\n return False\\n\\n # If the only dependency is parent job, dependency has been met\\n if not dependencies_ids:\\n return True\\n\\n with connection.pipeline() as pipeline:\\n for key in dependencies_ids:\\n pipeline.hget(self.key_for(key), 'status')\\n\\n dependencies_statuses = pipeline.execute()\\n\\n allowed_statuses = [JobStatus.FINISHED]\\n if self.allow_dependency_failures:\\n allowed_statuses.append(JobStatus.FAILED)\\n\\n return all(status.decode() in allowed_statuses for status in dependencies_statuses if status)\",\n \"def check(self, srcs, actual_deps):\\r\\n if self._check_missing_deps or self._check_missing_direct_deps or self._check_unnecessary_deps:\\r\\n missing_file_deps, missing_tgt_deps, missing_direct_tgt_deps = \\\\\\r\\n self._compute_missing_deps(srcs, actual_deps)\\r\\n\\r\\n buildroot = get_buildroot()\\r\\n def shorten(path): # Make the output easier to read.\\r\\n for prefix in [buildroot, self._context.ivy_home]:\\r\\n if path.startswith(prefix):\\r\\n return os.path.relpath(path, prefix)\\r\\n return path\\r\\n\\r\\n if self._check_missing_deps and (missing_file_deps or missing_tgt_deps):\\r\\n for (tgt_pair, evidence) in missing_tgt_deps:\\r\\n evidence_str = '\\\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\\r\\n for e in evidence])\\r\\n self._context.log.error(\\r\\n 'Missing BUILD dependency %s -> %s because:\\\\n%s'\\r\\n % (tgt_pair[0].address.reference(), tgt_pair[1].address.reference(), evidence_str))\\r\\n for (src_tgt, dep) in missing_file_deps:\\r\\n self._context.log.error('Missing BUILD dependency %s -> %s'\\r\\n % (src_tgt.address.reference(), shorten(dep)))\\r\\n if self._check_missing_deps == 'fatal':\\r\\n raise TaskError('Missing deps.')\\r\\n\\r\\n if self._check_missing_direct_deps:\\r\\n for (tgt_pair, evidence) in missing_direct_tgt_deps:\\r\\n evidence_str = '\\\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\\r\\n for e in evidence])\\r\\n self._context.log.warn('Missing direct BUILD dependency %s -> %s because:\\\\n%s' %\\r\\n (tgt_pair[0].address, tgt_pair[1].address, evidence_str))\\r\\n if self._check_missing_direct_deps == 'fatal':\\r\\n raise TaskError('Missing direct deps.')\\r\\n\\r\\n if self._check_unnecessary_deps:\\r\\n raise TaskError('Unnecessary dep warnings not implemented yet.')\",\n \"def condition_id(self, condition_id):\\n\\n self._condition_id = condition_id\",\n \"def get_depend_by_child_id(self, child_id):\\n try:\\n result = self._session.query(StepDependencyEntity).\\\\\\n filter(StepDependencyEntity.child_id == child_id).\\\\\\n all()\\n result_dict = self.result_dict(result)\\n except SQLAlchemyError as err:\\n Log.an().error('sql exception [%s]', str(err))\\n return False\\n\\n return result_dict\",\n \"def test_check_job_dependencies_has_unfinished_dependencies(database):\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=0)\\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n job_3 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=0)\\n sess.add_all([sub, job, job_2, job_3])\\n sess.commit()\\n\\n # Job 1 finished, it is a prerequisite for job 2 (waiting)\\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\\n # Job 3 is also a prerequisite of job 2, it's not done, job 2 should stay in \\\"waiting\\\"\\n job_dep_2 = JobDependency(job_id=job_2.job_id, prerequisite_id=job_3.job_id)\\n sess.add_all([job_dep, job_dep_2])\\n sess.commit()\\n\\n check_job_dependencies(job.job_id)\\n\\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']\",\n \"def check_dependencies(target_binary, target_platform, target_architecture, target_type):\\n check_architecture(target_architecture)\\n check_platform(target_platform)\",\n \"def is_valid(self):\\n return not self.missing_from_disk and not self.missing_dependency\",\n \"def test_load_additive_constraints():\\n solution_repo = SolutionRepository(\\n os.path.join(os.path.dirname(__file__), \\\"requests_security_solution.txt\\\")\\n )\\n constraints = solution_repo.solution[\\\"idna\\\"].build_constraints()\\n assert constraints == pkg_resources.Requirement.parse(\\\"idna<2.9,>=2.5\\\")\",\n \"def _check_foreign_cols(\\n self, join_condition: ColumnElement[bool], primary: bool\\n ) -> None:\\n\\n can_sync = False\\n\\n foreign_cols = self._gather_columns_with_annotation(\\n join_condition, \\\"foreign\\\"\\n )\\n\\n has_foreign = bool(foreign_cols)\\n\\n if primary:\\n can_sync = bool(self.synchronize_pairs)\\n else:\\n can_sync = bool(self.secondary_synchronize_pairs)\\n\\n if (\\n self.support_sync\\n and can_sync\\n or (not self.support_sync and has_foreign)\\n ):\\n return\\n\\n # from here below is just determining the best error message\\n # to report. Check for a join condition using any operator\\n # (not just ==), perhaps they need to turn on \\\"viewonly=True\\\".\\n if self.support_sync and has_foreign and not can_sync:\\n err = (\\n \\\"Could not locate any simple equality expressions \\\"\\n \\\"involving locally mapped foreign key columns for \\\"\\n \\\"%s join condition \\\"\\n \\\"'%s' on relationship %s.\\\"\\n % (\\n primary and \\\"primary\\\" or \\\"secondary\\\",\\n join_condition,\\n self.prop,\\n )\\n )\\n err += (\\n \\\" Ensure that referencing columns are associated \\\"\\n \\\"with a ForeignKey or ForeignKeyConstraint, or are \\\"\\n \\\"annotated in the join condition with the foreign() \\\"\\n \\\"annotation. To allow comparison operators other than \\\"\\n \\\"'==', the relationship can be marked as viewonly=True.\\\"\\n )\\n\\n raise sa_exc.ArgumentError(err)\\n else:\\n err = (\\n \\\"Could not locate any relevant foreign key columns \\\"\\n \\\"for %s join condition '%s' on relationship %s.\\\"\\n % (\\n primary and \\\"primary\\\" or \\\"secondary\\\",\\n join_condition,\\n self.prop,\\n )\\n )\\n err += (\\n \\\" Ensure that referencing columns are associated \\\"\\n \\\"with a ForeignKey or ForeignKeyConstraint, or are \\\"\\n \\\"annotated in the join condition with the foreign() \\\"\\n \\\"annotation.\\\"\\n )\\n raise sa_exc.ArgumentError(err)\",\n \"def _check_condition_set_related_reference_21(self):\\n type_of_event = FFXMMConfirmationOutUtils_Override.get_event_type_MT330(self.acm_obj)\\n type_of_operation = str(get_type_of_operation(self.acm_obj))\\n\\n if type_of_event == 'CONF':\\n if type_of_operation in ['AMND', 'CANC']:\\n return True\\n return False\\n\\n return True\",\n \"def checkRequiredDependencies(self):\\n \\n # skip dependency check for downloading only\\n if( self.downloadOnly ):\\n return\\n\\n # hard dependencies\\n for req in self.reqmodules:\\n if( self.parent.module(req) == None ):\\n # check if there is an auto detected module\\n if( self.parent.module(req, True) == None ):\\n self.abort( self.name + \\\" requires \\\" + req \\\\\\n + \\\" and it wasn't found in your config file!!\\\" )\\n else:\\n # use auto detected module\\n self.parent.use( self.parent.module(req, True) )\\n self.parent.module( req ).init()\\n\\n print self.name + \\\": auto-detected \\\" + req + \\\" version \\\" + self.parent.module( req ).version\\n \\n # build only dependencies\\n if( self.mode == \\\"install\\\" ):\\n mods = self.reqmodules_buildonly + self.reqmodules_external\\n for req in mods:\\n if( self.parent.module(req) == None ):\\n # check if there is an auto detected module\\n if( self.parent.module(req, True) == None ):\\n self.abort( req + \\\" not found in your config file!! \\\" + self.name \\\\\\n + \\\" cannot be built without \\\" + req )\\n else:\\n # use auto detected module\\n self.parent.use( self.parent.module(req, True) )\\n self.parent.module( req ).init()\\n\\n print \\\" - \\\" + self.name + \\\": auto-detected \\\" + req + \\\" version \\\" + self.parent.module( req ).version\",\n \"def check_all_constraints(Instance: dict):\\r\\n\\r\\n print(\\\"Checking constraints...\\\")\\r\\n # Schedule constraints\\r\\n check_schedule(Instance)\\r\\n # Resources constraints\\r\\n check_resources(Instance)\\r\\n # Exclusions constraints\\r\\n check_exclusions(Instance)\\r\\n if (\\r\\n check_exclusions(Instance)\\r\\n and check_resources(Instance)\\r\\n and check_schedule(Instance)\\r\\n ):\\r\\n print(\\\"Done\\\")\\r\\n return True\\r\\n else:\\r\\n return False\",\n \"def delete_depend_by_workflow_id(self, workflow_id):\\n try:\\n # use of a sub-query instead of join for delete is required\\n # for sqlite\\n sub_query = self._session.query(StepEntity.id).\\\\\\n filter(StepEntity.workflow_id == workflow_id)\\n self._session.query(StepDependencyEntity).\\\\\\n filter(StepDependencyEntity.child_id.in_(sub_query)).\\\\\\n delete(synchronize_session=False)\\n except SQLAlchemyError as err:\\n Log.an().error('sql exception [%s]', str(err))\\n return False\\n\\n return True\",\n \"def test_empty_condition(self):\\n assert_that(Condition.is_valid(''), equal_to(True))\",\n \"def checkMetamodelLevel(cls):\\n for mmd in cls.metamodelDependencies():\\n mmd.check()\",\n \"def validity_constraint(self, node, condition, err_msg):\\n if not condition:\\n self.tree.add_error(node, err_msg)\",\n \"def _sufficient_deps(cls, deps):\\n if cls.MODEL_PACKAGE is None:\\n return True\\n else:\\n for d in deps.conda:\\n if cls.MODEL_PACKAGE in d:\\n return True\\n for d in deps.pip:\\n if cls.MODEL_PACKAGE in d:\\n return True\\n return False\",\n \"def _add_conditions(self, modcells, condition_dict):\\n\\n rename_dict = {}\\n\\n # Fill in gaps with info from pristine\\n for ID in list(condition_dict):\\n iter_cond_dict = condition_dict[ID].copy()\\n\\n ID_verdict = ID\\n\\n found_empty_dict_flag = False\\n found_duplicate_flag = False\\n found_same_ID_flag = False\\n\\n # If no keys defined, set this condition as pristine\\n # or if only the 'identifier' is specified and it is 'pristine'\\n\\n if not set(iter_cond_dict):\\n found_empty_dict_flag = True\\n else:\\n if 'identifier' in list(iter_cond_dict):\\n if iter_cond_dict['identifier'] == 'pristine':\\n found_empty_dict_flag = True\\n\\n if found_empty_dict_flag:\\n # If ID is zero, just delete this case because pristine is added already (in __init__)\\n # If ID not zero, need to also change all IDs in modcell to 0\\n if ID != 0:\\n ID_verdict = 0\\n rename_dict = self._add_val_to_dict(\\n rename_dict, ID_verdict, ID)\\n continue\\n\\n else:\\n valid_msk = [(k not in set(self.pristine_condition))\\n for k in list(iter_cond_dict)]\\n if any(valid_msk):\\n raise Exception(\\n f'Invalid key(s) passed in condition_dict: {list(iter_cond_dict)[valid_msk]}\\\\nValid keys are {list(self.pristine_condition)}')\\n\\n # Get keys which are not defined\\n undefined_keys = set(\\n self.pristine_condition) - set(iter_cond_dict)\\n\\n # Define undefined keys as the conditions in pristine_condition\\n for undef_key in undefined_keys:\\n iter_cond_dict[undef_key] = self.pristine_condition[undef_key]\\n\\n # Check if there are keys in current condition_dict\\n if list(self.condition_dict.keys()):\\n\\n # get list of current 'identifier'\\n identifiers_dict = self._get_key_set(\\n self.condition_dict, 'identifier')\\n\\n # if inputted identifier is in current identifiers, append sample to list\\n if iter_cond_dict['identifier'] in identifiers_dict.values():\\n\\n # Check for identifier in dict keys, return dict key (cell_num)\\n ID_found = [key for (key, value) in identifiers_dict.items(\\n ) if value == iter_cond_dict['identifier']]\\n\\n if (len(ID_found) == 0) or (len(ID_found) > 1):\\n raise Exception(\\n f\\\"Debugging: {len(ID_found)} identifiers found even though it should have been one: {ID_found}\\\")\\n\\n elif len(ID_found) == 1:\\n ID_found = ID_found[0]\\n\\n # Replace ID with ID_found and append condition_dict ONLY if \\\\\\n # it is different.\\n\\n if ID != ID_found:\\n rename_dict = self._add_val_to_dict(\\n rename_dict, ID_found, ID)\\n ID_verdict = ID_found\\n\\n # check if condition is already defined\\n for dct in self.condition_dict[ID_found]:\\n if dct == iter_cond_dict:\\n # If match found, delete current ID\\n found_duplicate_flag = True\\n continue\\n\\n if not found_duplicate_flag:\\n # duplicate not found, append to dict\\n if len(self.condition_dict[ID_found]) == 0:\\n # if none in list\\n self.condition_dict[ID_found] = [\\n iter_cond_dict]\\n else:\\n # if conditions in list but none are this condition_dict\\n self.condition_dict[ID_found].append(\\n iter_cond_dict)\\n\\n else:\\n # identifier was not found in self.condition_dict\\n # so, must create case\\n\\n # Organize input IDs with all existing keys\\n # If current condition_dict has matching key with inputted, find next numerical key available and rename in condition_dict and modcells\\n if ID_verdict in list(self.condition_dict.keys()):\\n new_key = max(list(self.condition_dict.keys())) + 1\\n rename_dict = self._add_val_to_dict(\\n rename_dict, new_key, ID_verdict)\\n ID_verdict = new_key\\n found_same_ID_flag = True\\n\\n if not found_same_ID_flag:\\n # An original condition is found\\n # Ensure that when adding a new condition, the ID is sequentially larger\\n # Used to organize ID systematically\\n expected_id = max(\\n list(self.condition_dict.keys())) + 1\\n if ID_verdict > expected_id:\\n rename_dict = self._add_val_to_dict(\\n rename_dict, expected_id, ID_verdict)\\n ID_verdict = expected_id\\n\\n self.condition_dict[ID_verdict] = [iter_cond_dict]\\n else:\\n # self.condition_dict is blank\\n raise Exception(\\n \\\"Debugging: this should never happen because pristine case is defined in __init__ which populates self.condition_dict.\\\")\\n\\n # REPLACE IDs\\n all_keys = list(modcells.keys())\\n for idx in range(len(all_keys)):\\n module_identifier = all_keys[idx]\\n if (module_identifier == 'V') or (module_identifier == 'I'):\\n raise ValueError(\\n f\\\"Invalid module identifier, {module_identifier}. It cannot be 'I' or 'V'\\\")\\n\\n modcell_list = modcells[module_identifier]\\n\\n if isinstance(modcell_list, (tuple, list)):\\n modcell_list = np.array(modcell_list)\\n elif not isinstance(modcell_list, np.ndarray):\\n raise TypeError(\\n f\\\"Invalid object ({type(modcell_list).__name__}) was passed to modcell[{module_identifier}]. Please define a list, tuple, or array as the value.\\\")\\n\\n if len(modcell_list.shape) == 2:\\n # 2d list found, therefore must process multiple modcells\\n process_modcells = modcell_list\\n elif len(modcell_list.shape) == 1:\\n # 1d list found, put into a list for processing format\\n process_modcells = [modcell_list]\\n else:\\n raise TypeError(\\n f\\\"Invalid array shape ({modcell_list.shape}) passed to modcell is {len(modcell_list.shape)}D. Expected 1D or 2D iterable object.\\\\nHere is object:\\\\n{modcell_list}\\\")\\n\\n required_n_cells = self.module_parameters[\\\"ncells_substring\\\"] * \\\\\\n self.module_parameters[\\\"nsubstrings\\\"]\\n for modcell_arr in process_modcells:\\n if len(modcell_arr) != required_n_cells:\\n raise Exception(\\n f\\\"An input modcell has an invalid length. The input definition has {len(modcell_arr)} when {required_n_cells} is required.\\\")\\n\\n comparator = copy.deepcopy(process_modcells)\\n for replacement_id in list(rename_dict):\\n for current_id in rename_dict[replacement_id]:\\n # for modcell_iter in process_modcells:\\n for idx in range(len(process_modcells)):\\n\\n indexes = []\\n for i in range(len(comparator[idx])):\\n if comparator[idx][i] == current_id:\\n indexes.append(i)\\n\\n for index in indexes:\\n process_modcells[idx][index] = replacement_id\\n\\n # Append modcells and condition_dict\\n # Check if modcell key already exists\\n if module_identifier in self.modcells.keys():\\n for mdcel in process_modcells:\\n if mdcel not in np.array(self.modcells[module_identifier]).astype(int):\\n self.modcells[module_identifier] += process_modcells\\n else:\\n self.modcells[module_identifier] = process_modcells\",\n \"def check_model(self):\\n for node in self.nodes():\\n cpd = self.get_cpds(node=node)\\n\\n if cpd is None:\\n raise ValueError(\\\"No CPD associated with {}\\\".format(node))\\n elif isinstance(cpd, (TabularCPD, ContinuousFactor)):\\n evidence = cpd.get_evidence()\\n parents = self.get_parents(node)\\n if set(evidence if evidence else []) != set(parents if parents else []):\\n raise ValueError(\\n \\\"CPD associated with {node} doesn't have \\\"\\n \\\"proper parents associated with it.\\\".format(node=node)\\n )\\n if not cpd.is_valid_cpd():\\n raise ValueError(\\n \\\"Sum or integral of conditional probabilites for node {node}\\\"\\n \\\" is not equal to 1.\\\".format(node=node)\\n )\\n return True\",\n \"def test_falsifications(self):\\n implications = get_conditional_independencies(asia_example.graph)\\n issues = get_falsifications(implications, asia_example.data)\\n self.assertEqual(0, len(issues.failures))\\n self.assertEqual(len(issues.evidence), len(implications))\",\n \"def consistent(self,assignment):\\n return all(con.holds(assignment)\\n for con in self.constraints\\n if all(v in assignment for v in con.scope))\",\n \"def check_all_constraints(csp) :\\n constraints=csp.get_all_constraints()\\n for constraint in constraints:\\n var1 = constraint.var1\\n var2 = constraint.var2\\n val1=csp.get_assigned_value(var1)\\n val2=csp.get_assigned_value(var2)\\n if val1!=None and val2!=None:\\n if not constraint.check(val1,val2):\\n return False\\n return True\",\n \"def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):\\n # Check for a matching dependency type\\n related = []\\n\\n if edge[2][\\\"dep\\\"] == dep:\\n # Check for matching POS type(s)\\n for pos_logic in dep_obj.keys():\\n connector = None\\n\\n if isinstance(dep_obj[pos_logic], dict):\\n for pos in dep_obj[pos_logic].keys():\\n\\n # Check for allowed part of speech tags in matched dependency patterns\\n if (pos_logic == \\\"pos_in\\\" and pos in G.nodes[sibling_idx][\\\"pos\\\"]) or (\\n pos_logic == \\\"pos_equals\\\" and pos == G.nodes[sibling_idx][\\\"pos\\\"]):\\n pass\\n elif pos_logic == \\\"pos_not\\\":\\n if not [False if not_pos == G.nodes[sibling_idx][\\\"pos\\\"] else True for not_pos in\\n dep_obj.keys()]: continue\\n else:\\n continue\\n\\n # if no additional checks, have a match\\n if dep_obj[pos_logic][pos] == None or any(\\n y in dep_obj[pos_logic][pos] for y in [None, \\\"add_sibling\\\"]):\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']])\\n\\n # if additional checks are required, process further\\n if dep_obj[pos_logic][pos]:\\n if \\\"get_cousin\\\" in dep_obj[pos_logic][pos]:\\n related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos][\\\"get_cousin\\\"]))\\n connector = G.nodes[sibling_idx]['word']\\n\\n if \\\"special\\\" in dep_obj[pos_logic][pos]:\\n if dep == \\\"compound\\\" and pos == \\\"NN\\\":\\n related = [G.nodes[sibling_idx]['word']]\\n\\n if None in related:\\n related.remove(None)\\n\\n # Allows for getting cousin and returning sibling\\n if \\\"else\\\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\\\"else\\\"] == \\\"always\\\":\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\\n if len(related) > 0 and isinstance(related, list):\\n for x in related:\\n if x != None:\\n all_related = _add_related(x, dep, all_related, A.index_lookup[x],\\n connector=connector)\\n elif \\\"else\\\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\\\"else\\\"] == True:\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\\n\\n return all_related\",\n \"def validate_dependence_versions():\\n print('Total {} instances defined'.format(len(ReleaseInfo.all_instance_releases())))\\n all_instance_releases = ReleaseInfo.all_instance_releases()\\n\\n # Validate dependencies: each dependence should have a valid\\n # version as in defined range\\n for instance_name, versions in all_instance_releases.items():\\n for instance_version, release_info in versions.items():\\n dependencies = release_info.dependencies\\n for dep in dependencies:\\n dep_type = dep.type\\n minv = dep.min_version\\n maxv = dep.max_version\\n\\n assert dep_type in all_instance_releases, \\\\\\n \\\"No dependence found {} for version {} of {}\\\" \\\\\\n .format(dep_type, instance_version, instance_name)\\n\\n found = _find_a_ranged_version(dep_type, minv=minv, maxv=maxv)\\n assert found, \\\"No valid version defined for {} with max: {}, min: {}\\\" \\\\\\n .format(dep_type, maxv, minv)\",\n \"def test_exists(self, condition, undefined_paths, current_path):\\n var = str(condition.find('variable').text)\\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\\n current_path += ((var, 'undefined variable'),)\\n undefined_paths.add(current_path)\\n return False\\n else:\\n return True\",\n \"def verify_DIMACS(s):\\r\\n comments = True\\r\\n configured = False\\r\\n number_of_literals = 0\\r\\n number_of_clauses = 0\\r\\n clauses = 0\\r\\n for line in s.split('\\\\n'):\\r\\n line = line.strip()\\r\\n if len(line) == 0:\\r\\n continue\\r\\n\\r\\n if line[0] != 'c':\\r\\n if comments:\\r\\n comments = False\\r\\n else:\\r\\n if not comments:\\r\\n return 'Comments found outside of initial comment block.'\\r\\n\\r\\n if line[0] == 'p':\\r\\n if not configured:\\r\\n match = re.match(r'p cnf ([0-9]+) ([0-9]+)', line)\\r\\n if not match:\\r\\n return 'invalid p-line.'\\r\\n number_of_literals = int(match.group(1))\\r\\n number_of_clauses = int(match.group(2))\\r\\n configured = True\\r\\n else:\\r\\n return 'Multiple p lines found.'\\r\\n elif re.match(r'-?[0-9]+', line):\\r\\n if not configured:\\r\\n return 'clause before p-line.'\\r\\n literals = re.split(' ', line)\\r\\n for literal in literals[:-1]:\\r\\n if abs(int(literal)) > number_of_literals:\\r\\n return 'Variable number greater than number of variables'\\r\\n if literals[-1] != '0':\\r\\n return 'Clause does not end with a zero.'\\r\\n clauses += 1\\r\\n if number_of_clauses != clauses:\\r\\n return 'Not enough clauses'\\r\\n if configured:\\r\\n return ''\",\n \"def satisfied(self, fields, field, values):\\n\\n requires = field.get(\\\"requires\\\", [])\\n\\n if isinstance(requires, str):\\n requires = [requires]\\n\\n for require in requires:\\n if require not in fields or not fields[require].validate(store=False):\\n return False\\n\\n if \\\"condition\\\" in field and self.env.from_string(field[\\\"condition\\\"]).render(**values) != \\\"True\\\":\\n return False\\n\\n return True\",\n \"def test_conceptional_relations(id, conrel, expected_ids):\\n synset = germanet_data.get_synset_by_id(id)\\n related = synset.relations[conrel]\\n np.testing.assert_equal(sorted([syn.id for syn in related]), sorted(expected_ids))\",\n \"def testConditionalEffects(self):\\n \\n action = Parser.parse_as(cond_load.split(\\\"\\\\n\\\"), Action, self.domain)\\n\\n self.assert_(isinstance(action.effect, ConditionalEffect))\\n self.assert_(isinstance(action.effect.condition, conditions.LiteralCondition))\\n self.assert_(isinstance(action.effect.effect, SimpleEffect))\",\n \"def verify_dependencies(self):\\n dependencies = {\\n \\\"manufacturers\\\": [\\n {\\\"name\\\": \\\"VMware\\\", \\\"slug\\\": \\\"vmware\\\"},\\n ],\\n \\\"platforms\\\": [\\n {\\\"name\\\": \\\"VMware ESXi\\\", \\\"slug\\\": \\\"vmware-esxi\\\"},\\n {\\\"name\\\": \\\"Windows\\\", \\\"slug\\\": \\\"windows\\\"},\\n {\\\"name\\\": \\\"Linux\\\", \\\"slug\\\": \\\"linux\\\"},\\n ],\\n \\\"sites\\\": [{\\n \\\"name\\\": \\\"vCenter\\\",\\n \\\"slug\\\": \\\"vcenter\\\",\\n \\\"comments\\\": \\\"A default virtual site created to house objects \\\"\\n \\\"that have been synced from vCenter.\\\",\\n \\\"tags\\\": [\\\"Synced\\\", \\\"vCenter\\\"]\\n }],\\n \\\"cluster_types\\\": [\\n {\\\"name\\\": \\\"VMware ESXi\\\", \\\"slug\\\": \\\"vmware-esxi\\\"}\\n ],\\n \\\"device_roles\\\": [\\n {\\n \\\"name\\\": \\\"Server\\\",\\n \\\"slug\\\": \\\"server\\\",\\n \\\"color\\\": \\\"9e9e9e\\\",\\n \\\"vm_role\\\": True\\n }],\\n \\\"tags\\\": [\\n {\\n \\\"name\\\": \\\"Orphaned\\\",\\n \\\"slug\\\": \\\"orphaned\\\",\\n \\\"color\\\": \\\"607d8b\\\",\\n \\\"comments\\\": \\\"This applies to objects that have become \\\"\\n \\\"orphaned. The source system which has \\\"\\n \\\"previously provided the object no longer \\\"\\n \\\"states it exists.{}\\\".format(\\n \\\" An object with the 'Orphaned' tag will \\\"\\n \\\"remain in this state until it ages out \\\"\\n \\\"and is automatically removed.\\\"\\n ) if settings.NB_PRUNE_ENABLED else \\\"\\\"\\n },\\n {\\n \\\"name\\\": self.vc_tag,\\n \\\"slug\\\": format_slug(self.vc_tag),\\n \\\"comments\\\": \\\"Objects synced from vCenter host \\\"\\n \\\"{}. Be careful not to modify the name or \\\"\\n \\\"slug.\\\".format(self.vc_tag)\\n }]\\n }\\n # For each dependency of each type verify object exists\\n log.info(\\\"Verifying all prerequisite objects exist in NetBox.\\\")\\n for dep_type in dependencies:\\n log.debug(\\n \\\"Checking NetBox has necessary %s objects.\\\", dep_type[:-1]\\n )\\n for dep in dependencies[dep_type]:\\n self.obj_exists(nb_obj_type=dep_type, vc_data=dep)\\n log.info(\\\"Finished verifying prerequisites.\\\")\",\n \"def check_id(self, id):\",\n \"def _check_dependency(self, tcname, depends):\\r\\n tcindex = self.tcorder.index(tcname)\\r\\n dependsindex = []\\r\\n for i in depends:\\r\\n dependsindex.append(self.tcorder.index(i))\\r\\n for i in dependsindex:\\r\\n if tcindex < i:\\r\\n msg = \\\"%s must be ordered after %s\\\\n\\\" %(tcname, self.tcorder[i])\\r\\n self.dependency.append(msg)\",\n \"def mempool_check_conditions_dict(\\n unspent: CoinRecord,\\n coin_announcement_names: Set[bytes32],\\n puzzle_announcement_names: Set[bytes32],\\n conditions_dict: Dict[ConditionOpcode, List[ConditionWithArgs]],\\n prev_transaction_block_height: uint32,\\n timestamp: uint64,\\n) -> Optional[Err]:\\n for con_list in conditions_dict.values():\\n cvp: ConditionWithArgs\\n for cvp in con_list:\\n error: Optional[Err] = None\\n if cvp.opcode is ConditionOpcode.ASSERT_MY_COIN_ID:\\n error = mempool_assert_my_coin_id(cvp, unspent)\\n elif cvp.opcode is ConditionOpcode.ASSERT_COIN_ANNOUNCEMENT:\\n error = mempool_assert_announcement(cvp, coin_announcement_names)\\n elif cvp.opcode is ConditionOpcode.ASSERT_PUZZLE_ANNOUNCEMENT:\\n error = mempool_assert_announcement(cvp, puzzle_announcement_names)\\n elif cvp.opcode is ConditionOpcode.ASSERT_HEIGHT_ABSOLUTE:\\n error = mempool_assert_absolute_block_height_exceeds(cvp, prev_transaction_block_height)\\n elif cvp.opcode is ConditionOpcode.ASSERT_HEIGHT_RELATIVE:\\n error = mempool_assert_relative_block_height_exceeds(cvp, unspent, prev_transaction_block_height)\\n elif cvp.opcode is ConditionOpcode.ASSERT_SECONDS_ABSOLUTE:\\n error = mempool_assert_absolute_time_exceeds(cvp, timestamp)\\n elif cvp.opcode is ConditionOpcode.ASSERT_SECONDS_RELATIVE:\\n error = mempool_assert_relative_time_exceeds(cvp, unspent, timestamp)\\n elif cvp.opcode is ConditionOpcode.ASSERT_MY_PARENT_ID:\\n error = mempool_assert_my_parent_id(cvp, unspent)\\n elif cvp.opcode is ConditionOpcode.ASSERT_MY_PUZZLEHASH:\\n error = mempool_assert_my_puzzlehash(cvp, unspent)\\n elif cvp.opcode is ConditionOpcode.ASSERT_MY_AMOUNT:\\n error = mempool_assert_my_amount(cvp, unspent)\\n if error:\\n return error\\n\\n return None\",\n \"def meets_advanced_requirements(challenge_id: int, user=None) -> bool:\\n model = UniqueChallengeRequirements.query.filter_by(challenge_id=challenge_id).first()\\n if user is None:\\n user = get_current_user()\\n if not model or not model.script or user.type == \\\"admin\\\":\\n # No requirements present = always allowed\\n return True\\n\\n def completed(arg) -> bool:\\n for search in arg:\\n if isinstance(search, str):\\n challenge = Challenges.query.filter_by(name=search).first()\\n if not challenge or not has_solved(challenge.id, user):\\n return False\\n elif isinstance(search, int):\\n if not has_solved(search, user):\\n return False\\n else:\\n raise LispIshRuntimeError(f\\\"(completed) function was passed an argument that was not a string or int.\\\")\\n return True\\n\\n def cohort(arg) -> bool:\\n for search in arg:\\n if isinstance(search, str):\\n cohort = UniqueChallengeCohort.query.filter_by(name=search).first()\\n if not cohort or not UniqueChallengeCohortMembership.query.filter_by(user_id=user.id, cohort_id=cohort.id).first():\\n return False\\n elif isinstance(search, int):\\n if not UniqueChallengeCohortMembership.query.filter_by(user_id=user.id, cohort_id=search).first():\\n return False\\n else:\\n raise LispIshRuntimeError(f\\\"(cohort) function was passed an argument that was not a string or int.\\\")\\n return True\\n\\n def before(arg, method='before') -> bool:\\n if len(arg) != 1:\\n raise LispIshRuntimeError(f\\\"({method}) function was passed {len(arg)} arguments, expected 1.\\\")\\n if isinstance(arg[0], int):\\n return time.time() < arg[0]\\n try:\\n timestamp = time.strptime(str(arg[0]), \\\"%Y-%m-%d\\\")\\n return time.time() < time.mktime(timestamp)\\n except ValueError:\\n pass\\n try:\\n timestamp = time.strptime(str(arg[0]), \\\"%Y-%m-%d %H:%M\\\")\\n return time.time() < time.mktime(timestamp)\\n except ValueError:\\n raise LispIshRuntimeError(f\\\"({method}) function was passed an invalid date string, expected an integer or a string with format YYYY-MM-DD or YYYY-MM-DD HH:MM\\\")\\n\\n def after(arg) -> bool:\\n return not before(arg, 'after')\\n\\n lisp = LispIsh()\\n try:\\n method = lisp.parse(model.script.decode('utf-8'))\\n return method.evaluate({\\n 'COMPLETED': completed,\\n 'COHORT': cohort,\\n 'BEFORE': before,\\n 'AFTER': after,\\n 'USER-EMAIL': lambda _: user.email,\\n 'USER-NAME': lambda _: user.name,\\n 'USER-ID': lambda _: user.id,\\n 'USER-SCORE': lambda _: user.score,\\n })\\n except LispIshParseError as err:\\n print(f\\\"Error parsing LispIsh: {err}\\\")\\n return False\\n except LispIshRuntimeError as err:\\n print(f\\\"Error evaluating LispIsh: {err}\\\")\\n return False\",\n \"def _check_case_sol_200(sol: int,\\n subcase: Subcase,\\n fem2: BDF,\\n p0: Any,\\n isubcase: int, subcases: int,\\n log: Any):\\n assert 'ANALYSIS' in subcase, 'sol=%s\\\\n%s' % (sol, subcase)\\n\\n analysis = subcase.get_parameter('ANALYSIS')[0]\\n # BUCKLING\\n if 'DESOBJ' in subcase:\\n value = subcase.get_parameter('DESOBJ')[0]\\n assert value in fem2.dresps, f'value={value} not in dresps'\\n else:\\n fem2.log.warning('no DESOBJ (DRESPi) in this subcase; is this a buckling preload case?')\\n fem2.log.warning('\\\\n%s' % subcase)\\n\\n nopt = len(fem2.dvprels) + len(fem2.dvmrels) + len(fem2.dvcrels)\\n if nopt == 0:\\n fem2.log.error('no DVPRELs/DVMRELs/DVCRELs found')\\n\\n #--------------------------------------------------------------------------\\n # DCONSTR\\n if 'DESSUB' not in subcase and 'DESGLB' not in subcase:\\n fem2.log.warning('no DESSUB/DESGLB (DCONSTR) in this subcase;'\\n ' is this a buckling preload case?')\\n log.warning('\\\\n%s' % subcase)\\n\\n if 'DESSUB' in subcase:\\n value = subcase.get_parameter('DESSUB')[0]\\n if value not in fem2.dconstrs:\\n msg = 'value=%s not in dconstrs; Allowed DCONSTRs=%s' % (\\n value, np.unique(list(fem2.dconstrs.keys())))\\n raise RuntimeError(msg)\\n if 'DESGLB' in subcase:\\n value = subcase.get_parameter('DESGLB')[0]\\n if value not in fem2.dconstrs:\\n msg = 'value=%s not in dconstrs; Allowed DCONSTRs=%s' % (\\n value, np.unique(list(fem2.dconstrs.keys())))\\n raise RuntimeError(msg)\\n #--------------------------------------------------------------------------\\n\\n if analysis in ['STATIC', 'STATICS']:\\n solution = 101\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis in ['MODE', 'MODES']:\\n solution = 103\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis in ['BUCK', 'BUCKLING']:\\n solution = 105\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis == 'DFREQ':\\n solution = 108\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis == 'MFREQ':\\n if 'GUST' in subcase:\\n solution = 146\\n else:\\n solution = 111\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis in ['MTRAN', 'MTRANS']:\\n solution = 112\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis in ['SAERO', 'DIVERG', 'DIVERGE']:\\n solution = 144\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis in ['FLUT', 'FLUTTER']:\\n solution = 145\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis == 'DCEIG': # direct complex eigenvalues\\n solution = 107\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n #elif analysis == 'MCEIG': # modal direct complex eigenvalues\\n elif analysis == 'HEAT': # heat transfer analysis\\n solution = 159\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n elif analysis == 'MCEIG': # modal complex eigenvalues\\n solution = 110\\n check_case(solution, subcase, fem2, p0, isubcase, subcases)\\n else:\\n msg = 'analysis = %s\\\\nsubcase =\\\\n%s' % (analysis, subcase)\\n raise NotImplementedError(msg)\",\n \"def check_model(self, model):\\n self.check_initial_conditions(model)\\n self.check_variables(model)\",\n \"def assert_single_condition_and_sbml_file(problem_config: Dict) -> None:\\n if (len(problem_config[SBML_FILES]) > 1\\n or len(problem_config[CONDITION_FILES]) > 1):\\n # TODO https://github.com/ICB-DCM/PEtab/issues/188\\n # TODO https://github.com/ICB-DCM/PEtab/issues/189\\n raise NotImplementedError(\\n 'Support for multiple models or condition files is not yet '\\n 'implemented.')\",\n \"def test_variable(self, condition, undefined_paths, current_path):\\n var = str(condition.find('name').text)\\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\\n current_path += ((var, 'undefined variable'),)\\n undefined_paths.add(current_path)\\n return False\\n else:\\n return True\",\n \"def _assert_pip_requirements(model_uri, requirements, constraints=None, strict=False):\\n local_path = _download_artifact_from_uri(model_uri)\\n txt_reqs = _read_lines(os.path.join(local_path, _REQUIREMENTS_FILE_NAME))\\n conda_reqs = _get_pip_deps(_read_yaml(\\n os.path.join(local_path, _CONDA_ENV_FILE_NAME)))\\n compare_func = set.__eq__ if strict else set.__le__\\n requirements = set(requirements)\\n assert compare_func(requirements, set(txt_reqs))\\n assert compare_func(requirements, set(conda_reqs))\\n\\n if constraints is not None:\\n assert f\\\"-c {_CONSTRAINTS_FILE_NAME}\\\" in txt_reqs\\n assert f\\\"-c {_CONSTRAINTS_FILE_NAME}\\\" in conda_reqs\\n cons = _read_lines(os.path.join(local_path, _CONSTRAINTS_FILE_NAME))\\n assert compare_func(set(constraints), set(cons))\",\n \"def ok(self, solution):\\n if self.constraints is not None:\\n for constraint in self.constraints:\\n if not constraint(solution):\\n return False\\n return True\",\n \"def satisfied_constraints(self,word_id, possible_word):\\r\\n constraints = self.words[word_id].constraints\\r\\n results = {}\\r\\n # print(\\\"word_id: {}, possible_word: {}, visited: {}, num_of_satisfied: {}\\\".format(word_id, possible_word, visited, num_of_satisfied)) \\r\\n for constraint in constraints:\\r\\n possibilities = []\\r\\n if word_id == constraint.word1:\\r\\n for possible_word2 in self.words[constraint.word2].domain:\\r\\n check = constraint.check_constraint(possible_word,possible_word2)\\r\\n if check:\\r\\n possibilities.append(possible_word2)\\r\\n if len(possibilities) != 0:\\r\\n results[constraint.word2] = possibilities\\r\\n elif word_id == constraint.word2:\\r\\n for possible_word2 in self.words[constraint.word1].domain:\\r\\n check = constraint.check_constraint(possible_word2,possible_word)\\r\\n if check:\\r\\n possibilities.append(possible_word2)\\r\\n if len(possibilities) != 0:\\r\\n results[constraint.word1] = possibilities\\r\\n return results\",\n \"def check_constraints ( A, S, complete ) :\\n\\t\\n\\tok = True\\n\\t\\n\\tfor i in range(len(complete)) :\\n\\t\\tif complete[i] :\\n\\t\\t\\tif not (dot(A[i],S) == 0) :\\n\\t\\t\\t\\tok = False\\n\\t\\t\\t\\tprint '\\\\n'\\n\\t\\t\\t\\tprint '*** warning *** constraint %d not verified' % (i)\\n\\t\\t\\t\\tvars_inds = (where(abs(A[i]) == 1))[0]\\n\\t\\t\\t\\tprint 'variables involved:', vars_inds\\n\\t\\t\\t\\tprint 'displacements:', S[vars_inds]\\n\\t\\t\\t\\tprint\\n\\t\\t\\t\\t#programPause = raw_input(\\\"Press the <ENTER> key to continue...\\\")\\n\\t\\t\\t\\t\\n\\treturn ok\",\n \"def mempool_assert_my_parent_id(condition: ConditionWithArgs, unspent: CoinRecord) -> Optional[Err]:\\n if unspent.coin.parent_coin_info != condition.vars[0]:\\n return Err.ASSERT_MY_PARENT_ID_FAILED\\n return None\",\n \"def _assert_postconditions(postconditions: List[Contract], resolved_kwargs: Mapping[str, Any],\\n func: CallableT) -> Optional[BaseException]:\\n assert 'result' in resolved_kwargs, \\\\\\n \\\"Expected 'result' to be already set in resolved kwargs before calling this function.\\\"\\n\\n for contract in postconditions:\\n if inspect.iscoroutinefunction(contract.condition):\\n raise ValueError(\\\"Unexpected coroutine (async) condition {} for a sync function {}.\\\".format(\\n contract.condition, func))\\n\\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\\n\\n check = contract.condition(**condition_kwargs)\\n\\n if inspect.iscoroutine(check):\\n raise ValueError(\\\"Unexpected coroutine resulting from the condition {} for a sync function {}.\\\".format(\\n contract.condition, func))\\n\\n if not_check(check=check, contract=contract):\\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\\n\\n return exception\\n\\n return None\",\n \"def check_requirement(self):\\n raise NotImplementedError\",\n \"def test_elemental_inclusion_constraint():\\n name = \\\"Property Band gap\\\"\\n elements = [\\\"Ga\\\", \\\"N\\\"]\\n\\n # Bad logic raises an error\\n try:\\n asdf = \\\"asdf\\\"\\n c = ElementalInclusionConstraint(name=name, elements=elements, logic=asdf)\\n assert False\\n except CitrinationClientError:\\n pass\\n\\n # Good logics do not raise an error\\n should = \\\"should\\\"\\n ElementalInclusionConstraint(name=name, elements=elements, logic=should)\\n must = \\\"must\\\"\\n ElementalInclusionConstraint(name=name, elements=elements, logic=must)\\n exclude = \\\"exclude\\\"\\n ElementalInclusionConstraint(name=name, elements=elements, logic=exclude)\\n\\n # Dictionary is formatted properly\\n logic=\\\"should\\\"\\n c = ElementalInclusionConstraint(name=name, elements=elements, logic=logic)\\n\\n mapped_c = c.to_dict()\\n\\n assert mapped_c[\\\"type\\\"] is \\\"elementalInclusionConstraint\\\"\\n assert mapped_c[\\\"name\\\"] is name\\n assert mapped_c[\\\"options\\\"][\\\"logic\\\"] is logic\\n assert mapped_c[\\\"options\\\"][\\\"elements\\\"] is elements\",\n \"def checkDeps( self ):\\n\\n # skip dependency check for downloading only\\n if( self.downloadOnly ):\\n return True\\n\\n # skip dependency check if package is going to be installed\\n if( self.mode == \\\"install\\\" ):\\n return True\\n\\n log.debug( 'Checking dependencies of %s', self.name )\\n \\n file = self.realPath() + \\\"/.dependencies\\\"\\n \\n r = True\\n\\n # if file doesn't exist return True\\n if( not os.path.exists( file )):\\n return True\\n\\n # open dependencies file\\n f = open( file )\\n filedeplist = {}\\n for line in f.readlines():\\n line = line.strip()\\n if( (not line.startswith(os.linesep)) and (not line.startswith(\\\"#\\\")) \\\\\\n and (len(line) > 0 )):\\n tokens = line.split(\\\":\\\")\\n filedeplist[ tokens[0] ] = tokens[1]\\n f.close()\\n\\n log.debug( 'Dependencies read from file: %s', filedeplist )\\n\\n # get actual dependecies\\n deplist={}\\n self.getDepList(deplist)\\n del deplist[self.name]\\n\\n log.debug( 'Dependencies found in current cfg file: %s', deplist )\\n \\n # compare dependencies\\n for k, v in filedeplist.iteritems():\\n if( deplist.has_key( k )):\\n if( deplist[k] != v ):\\n if( os.path.basename(deplist[k]) != os.path.basename(v) ):\\n if( r ):\\n print \\\"*** WARNING: ***\\\\n***\\\\tFollowing dependencies from \\\" + self.name + \\\" located at [ \\\" \\\\\\n + self.realPath() + \\\" ] failed:\\\\n***\\\"\\n print \\\"***\\\\t * \\\" + k + \\\" \\\" + os.path.basename(v) + \\\" differs from version \\\" \\\\\\n + os.path.basename(deplist[k]) + \\\" defined in your config file..\\\"\\n r = False\\n else:\\n if( r ): #just print this once\\n print \\\"*** WARNING: ***\\\\n***\\\\tFollowing dependencies from \\\" + self.name + \\\" located at [ \\\" + self.realPath() \\\\\\n + \\\" ] failed:\\\\n***\\\"\\n print \\\"***\\\\t * \\\" + k + \\\" not found in your config file!!\\\"\\n r = False\\n \\n\\n if( not r ):\\n print \\\"***\\\"\\n if( self.useLink ):\\n print \\\"***\\\\t\\\" + self.name + \\\" is in \\\\\\\"link\\\\\\\" mode, if you want to rebuild it with the new dependencies set it to \\\\\\\"use\\\\\\\" mode...\\\"\\n r = True\\n else:\\n if( not self.parent.noAutomaticRebuilds ):\\n print \\\"***\\\\t * \\\" + self.name + \\\" changed to \\\\\\\"install\\\\\\\" mode and rebuild flag set to True...\\\"\\n self.mode = \\\"install\\\"\\n self.rebuild = True\\n self.preCheckDeps()\\n print \\\"***\\\\n***\\\\tUpdating dependency tree ( modules that depend on \\\" + self.name + \\\" need also to be rebuilt )...\\\\n***\\\"\\n self.updateDepTree([])\\n print \\\"***\\\\n***\\\\tif you do NOT want to rebuild this module(s) just answer \\\\\\\"no\\\\\\\" later on in the installation process,\\\\n\\\" \\\\\\n + \\\"***\\\\tor set the global flag ilcsoft.noAutomaticRebuilds=True in your config file...\\\"\\n else:\\n print \\\"***\\\\n***\\\\tglobal flag ilcsoft.noAutomaticRebuilds is set to True, nothing will be done...\\\\n***\\\"\\n return r\",\n \"def __satisfies_necessary_and_sufficient_conditions(g):\\n # Condition 0: at least 1 Edge\\n if g.get_E() == 0:\\n return False\\n # Condition 1: indegree(v) == outdegree(v) for every vertex\\n for v in range(g.get_V()):\\n if g.outdegree() != g.indegree(v):\\n return False\\n # Condition 2: graph is connected, ignoring isolated vertices\\n h = Graph(g.get_V())\\n for v in range(g.get_V()):\\n for w in g.adj_vertices(v):\\n h.add_edge(v, w)\\n # check that all non-isolated vertices are connected\\n s = DirectedEulerianCycle.__non_isolated_vertex(g)\\n bfs = BreadthFirstPaths(h, s)\\n for v in range(g.get_V()):\\n if h.degree(v) > 0 and not bfs.has_path_to(v):\\n return False\\n return True\",\n \"def check_integrity(self) -> None:\\n for subset in self.subsets:\\n if not self._check_subset_integrity(subset):\\n raise ValueError(f\\\"subset {subset} not found or corrupt\\\")\",\n \"def _check_c(self, constraint, *variables):\\n c = {c.__class__ for c in self._layout.solver.get(*variables)}\\n if constraint:\\n self.assertTrue(constraint in c)\\n else:\\n self.assertFalse(c)\",\n \"def test_incoming_conceptional_relations(id, conrel, expected_ids):\\n synset = germanet_data.get_synset_by_id(id)\\n related = synset.incoming_relations[conrel]\\n np.testing.assert_equal(sorted([syn.id for syn in related]), sorted(expected_ids))\",\n \"def check_all_constraints(csp) :\\n\\n for constraint in csp.get_all_constraints():\\n assigned1 = csp.get_assigned_value(constraint.var1)\\n assigned2 = csp.get_assigned_value(constraint.var2)\\n check = constraint.check(assigned1,assigned2)\\n if check==False and assigned1!=None and assigned2!=None:\\n return False \\n return True\",\n \"def invariant(self):\\n\\t\\treturn ((self.vcdnId > 0) and (self.popId > 0))\",\n \"def validate(self):\\n for rosdep_key in self:\\n # Ensure all dependencies have definitions\\n # i.e.: Ensure we aren't pointing to invalid rosdep keys\\n for dependency in self[rosdep_key]['dependencies']:\\n if dependency not in self:\\n raise KeyError(\\n 'Invalid Graph Structure: rosdep key `%s` does not exist in the dictionary of resolutions.'\\n % dependency)\\n self[dependency]['is_root'] = False\\n # Check each entry for cyclical dependencies\\n for rosdep_key in self:\\n self.detect_cycles(rosdep_key, [])\",\n \"def test_check_job_dependencies_ready(mock_sqs_queue, database):\\n # Mock so it always returns the mock queue for the test\\n mock_sqs_queue.return_value = SQSMockQueue\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=0)\\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n sess.add_all([sub, job, job_2])\\n sess.commit()\\n\\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\\n sess.add(job_dep)\\n sess.commit()\\n\\n check_job_dependencies(job.job_id)\\n\\n assert job_2.job_status_id == JOB_STATUS_DICT['ready']\",\n \"def check(self):\\n for req in self.requirements:\\n if not self.COMPARISON_OPERATORS[req.operator](\\n packaging.version.parse(get_installed_version(req.package)),\\n packaging.version.parse(req.version),\\n ):\\n fail(f\\\"The cluster requires {req.package}{req.operator}{req.version}\\\")\",\n \"def _is_conveyance_id_valid(self, conveyance_id):\\n sql = \\\"SELECT id FROM {} WHERE id=?\\\".format(self.conveyance_type)\\n\\n try:\\n query_result = self.cursor.execute(sql, (str(conveyance_id),))\\n if query_result.fetchall():\\n return True\\n return False\\n except Exception as e:\\n raise Exception(\\n \\\"An error occurred while fetching a %s in the database: query: %s - message: %s\\\"\\n % (self.conveyance_type, sql, e)\\n )\",\n \"def validate(self, fgraph):\\r\\n\\r\\n if self.destroyers:\\r\\n ords = self.orderings(fgraph)\\r\\n\\r\\n if _contains_cycle(fgraph, ords):\\r\\n raise InconsistencyError(\\\"Dependency graph contains cycles\\\")\\r\\n else:\\r\\n #James's Conjecture:\\r\\n #If there are no destructive ops, then there can be no cycles.\\r\\n pass\\r\\n return True\",\n \"def check(self,):\\n self.is_valid_according_policy()\",\n \"def validate(self, fgraph):\\r\\n\\r\\n if self.destroyers:\\r\\n ords = self.orderings(fgraph)\\r\\n\\r\\n if _contains_cycle(fgraph, ords):\\r\\n raise InconsistencyError(\\\"Dependency graph contains cycles\\\")\\r\\n else:\\r\\n #James's Conjecture:\\r\\n #If there are no destructive ops, then there can be no cycles.\\r\\n pass\\r\\n return True\",\n \"def solved(self):\\n if not self.all_variables_assigned():\\n return False\\n for constraint in self.constraints:\\n if not constraint.satisfied(*[self.var_dict[name] for name in constraint.var_names]):\\n return False\\n return True\",\n \"def check(self):\\n\\n constrains = pm.ls(type='constraint')\\n uselessConstrains = []\\n\\n for const in constrains:\\n connections = const.listConnections(scn=True, s=False, d=True)\\n if const in connections:\\n connections.remove(const)\\n\\n if len(connections) == 0:\\n uselessConstrains.append(const)\\n\\n if not uselessConstrains:\\n self.status = \\\"OK\\\"\\n else:\\n self.status = self.errorMode\\n self.errorNodes = uselessConstrains\\n for obj in uselessConstrains:\\n self.addError(\\\"%s doesn't have outgoing connections.\\\" % obj)\\n self.errorMessage = \\\"%s useless constrains\\\" % (\\n len(uselessConstrains))\",\n \"def addConstraintOnIdTransition(self, pos):\\n super().addConstraintOnIdTransition(pos)\\n\\n self.s.add(Implies(self.startLoop == pos, self.faultOccursByThePast[pos]))\\n\\n for j in range(len(self.transitionList)):\\n self.s.add(Implies(self.faultyPath[pos - 1] == j, self.stateFaultyPath[pos] == self.transitionList[j][1]))\\n self.s.add(Implies(self.normalPath[pos - 1] == j, self.stateNormalPath[pos] == self.transitionList[j][1]))\\n\\n if pos > 0:\\n self.s.add(Implies(self.startLoop == pos - 1, self.projStartStateNormal == self.stateNormalPath[pos]))\\n self.s.add(Implies(self.startLoop == pos - 1, self.projStartStateFaulty == self.stateFaultyPath[pos]))\\n\\n self.s.add(Implies(self.endLoop == pos, self.projEndStateNormal == self.stateNormalPath[pos]))\\n self.s.add(Implies(self.endLoop == pos, self.projEndStateFaulty == self.stateFaultyPath[pos]))\\n\\n self.s.add(Or(self.startLoop < pos, Not(self.checkSynchro[pos]), self.idTransitionFaultyPath[pos] == self.idTransitionNormalPath[pos]))\",\n \"def consistency_check(self):\\n for opt, opt_def in self.opt_dict.iteritems():\\n selected_imp = opt_def['selected_imp']\\n if selected_imp == 'none':\\n continue\\n else:\\n mapped_opt = self.imp2opt_dict[selected_imp]\\n\\n if mapped_opt != opt:\\n emsg = 'ERROR: imp2opt_dict fails to map {i} to {o}'\\n print emsg.format(i=selected_imp, o=opt)\\n\\n for imp, opt in self.imp2opt_dict.iteritems():\\n if imp == 'none':\\n print 'ERROR: Found \\\"none\\\" as a keyword in imp2opt_dict'\\n continue\\n elif opt == 'none':\\n continue\\n else:\\n selected_imp = self.opt_dict[opt]['selected_imp']\\n\\n if imp != selected_imp:\\n emsg = 'ERROR: imp2opt_dict fails to map {i} to {o}'\\n print emsg.format(i=selected_imp, o=opt)\",\n \"def check_deterministic_constraints(self, x):\\n return True\",\n \"def check_deterministic_constraints(self, x):\\n return True\",\n \"def _check_if_model_ready(self, model_id):\\n # check model_id is not None\\n if model_id is None:\\n logger.error(\\\"Provided model id is None. Please provide valid model id.\\\")\\n return False\\n\\n # check if the model training is completed successfully to consume by next step\\n model_exist = self.model_db_client.check_model_record_exists(self.experiment_id, model_id)\\n if not model_exist:\\n logger.error(\\n f\\\"Model with mode_id '{model_id}' was not found in model table. \\\"\\n \\\"Please create a model first\\\"\\n )\\n return False\\n\\n # 'model_id' found in table, check if the 'model_id' is trained\\n model_to_deploy = ModelManager(\\n model_db_client=self.model_db_client,\\n experiment_id=self.experiment_id,\\n model_id=model_id,\\n )\\n\\n if not model_to_deploy.model_record.is_train_completed():\\n logger.warning(\\n f\\\"Model '{model_id}' is in status of \\\"\\n f\\\"{model_to_deploy.model_record._train_state}, Please check later.\\\"\\n )\\n return False\\n\\n return True\",\n \"def can_commit(self):\\n for name in self.conditions:\\n if name in _conditions:\\n condition = _conditions[name]\\n # If one condition matches, we're good\\n if self.check_condition(condition):\\n return True\\n return False\",\n \"def get_depend_def_by_step_id(self, step_id):\\n try:\\n result = self._session.query(StepEntity.name).\\\\\\n filter(StepEntity.id == StepDependencyEntity.parent_id).\\\\\\n filter(StepDependencyEntity.child_id == step_id).\\\\\\n all()\\n\\n result_list = [\\n row[0] for row in result\\n ]\\n\\n except SQLAlchemyError as err:\\n Log.an().error('sql exception [%s]', str(err))\\n return False\\n\\n return result_list\",\n \"def test_check_job_dependencies_not_finished(database):\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n sess.add_all([sub, job])\\n sess.commit()\\n\\n with pytest.raises(ValueError):\\n check_job_dependencies(job.job_id)\",\n \"def verify(condition):\\n global _is_in_verify_within\\n if not condition:\\n calling_frame = inspect.currentframe().f_back\\n error_message = 'verify() failed at line {} in \\\"{}\\\"'.format(calling_frame.f_lineno,\\n calling_frame.f_code.co_filename)\\n if not _is_in_verify_within:\\n print error_message\\n return False\\n return True\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7233518","0.71392715","0.60746115","0.5732978","0.5654439","0.5454553","0.5448558","0.5441111","0.52943414","0.52780235","0.5251414","0.5139405","0.51285505","0.51267743","0.51252174","0.5048138","0.50332785","0.5028958","0.49913806","0.4958716","0.49567008","0.49434626","0.4937245","0.4930527","0.49145195","0.49110186","0.48902562","0.48675665","0.48236367","0.48172572","0.4816776","0.48064846","0.4797315","0.47830275","0.47567952","0.47554523","0.4751694","0.47412977","0.47292447","0.47245225","0.4721807","0.4716706","0.47097567","0.47019014","0.4672199","0.46457013","0.46453932","0.4642783","0.46388865","0.46348834","0.4632939","0.46259466","0.4620529","0.46198872","0.46134478","0.46124405","0.46116614","0.4609533","0.4604698","0.4602495","0.45947832","0.45928103","0.4590021","0.4583683","0.4574005","0.45714894","0.45646802","0.45643446","0.45560378","0.4555879","0.45557877","0.45528778","0.4547192","0.45429155","0.4541618","0.45369172","0.45314738","0.4523791","0.4523731","0.45198303","0.45183396","0.45093074","0.45087472","0.4506533","0.45062393","0.45044163","0.44965488","0.44948184","0.4486739","0.44837853","0.44791594","0.4477988","0.44684356","0.4468014","0.4468014","0.4467797","0.44606096","0.4460033","0.44513777","0.4446322"],"string":"[\n \"0.7233518\",\n \"0.71392715\",\n \"0.60746115\",\n \"0.5732978\",\n \"0.5654439\",\n \"0.5454553\",\n \"0.5448558\",\n \"0.5441111\",\n \"0.52943414\",\n \"0.52780235\",\n \"0.5251414\",\n \"0.5139405\",\n \"0.51285505\",\n \"0.51267743\",\n \"0.51252174\",\n \"0.5048138\",\n \"0.50332785\",\n \"0.5028958\",\n \"0.49913806\",\n \"0.4958716\",\n \"0.49567008\",\n \"0.49434626\",\n \"0.4937245\",\n \"0.4930527\",\n \"0.49145195\",\n \"0.49110186\",\n \"0.48902562\",\n \"0.48675665\",\n \"0.48236367\",\n \"0.48172572\",\n \"0.4816776\",\n \"0.48064846\",\n \"0.4797315\",\n \"0.47830275\",\n \"0.47567952\",\n \"0.47554523\",\n \"0.4751694\",\n \"0.47412977\",\n \"0.47292447\",\n \"0.47245225\",\n \"0.4721807\",\n \"0.4716706\",\n \"0.47097567\",\n \"0.47019014\",\n \"0.4672199\",\n \"0.46457013\",\n \"0.46453932\",\n \"0.4642783\",\n \"0.46388865\",\n \"0.46348834\",\n \"0.4632939\",\n \"0.46259466\",\n \"0.4620529\",\n \"0.46198872\",\n \"0.46134478\",\n \"0.46124405\",\n \"0.46116614\",\n \"0.4609533\",\n \"0.4604698\",\n \"0.4602495\",\n \"0.45947832\",\n \"0.45928103\",\n \"0.4590021\",\n \"0.4583683\",\n \"0.4574005\",\n \"0.45714894\",\n \"0.45646802\",\n \"0.45643446\",\n \"0.45560378\",\n \"0.4555879\",\n \"0.45557877\",\n \"0.45528778\",\n \"0.4547192\",\n \"0.45429155\",\n \"0.4541618\",\n \"0.45369172\",\n \"0.45314738\",\n \"0.4523791\",\n \"0.4523731\",\n \"0.45198303\",\n \"0.45183396\",\n \"0.45093074\",\n \"0.45087472\",\n \"0.4506533\",\n \"0.45062393\",\n \"0.45044163\",\n \"0.44965488\",\n \"0.44948184\",\n \"0.4486739\",\n \"0.44837853\",\n \"0.44791594\",\n \"0.4477988\",\n \"0.44684356\",\n \"0.4468014\",\n \"0.4468014\",\n \"0.4467797\",\n \"0.44606096\",\n \"0.4460033\",\n \"0.44513777\",\n \"0.4446322\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.78313273"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13071,"cells":{"query":{"kind":"string","value":"Performs a depthfirst search of a condition's dependencies in order to verify that all dependencies and transitive dependencies are defined and valid."},"document":{"kind":"string","value":"def verify_dependencies(self, cond_id):\n undefined_paths = set()\n self._verify_dependencies(cond_id, undefined_paths, tuple())\n return undefined_paths"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_verify_dependencies(self, cond_id, conditions):\n\n if not cond_id in conditions.get_keys():\n return 1\n else:\n result = self.verify_dependencies(cond_id)\n return result","def _verify_dependencies(self, cond_id, undefined_paths, current_path):\n\n # Exception for izpack conditions:\n if cond_id in self.conditions.properties[WHITE_LIST]:\n return True\n\n # Short-circuit on well-defined conditions:\n if cond_id in self.well_defined:\n return True\n\n # Short-circuit ill-defined conditions:\n if cond_id in list(self.ill_defined.keys()):\n current_path = current_path + ((cond_id, 'ill-defined condition'),)\n undefined_paths.add(current_path)\n return False\n\n # Cycle checking:\n tup = (cond_id, 'condition')\n if tup in current_path:\n current_path += ((cond_id, 'cyclic condition reference'),)\n undefined_paths.add(current_path)\n return False\n\n # Check for undefined condition.\n if not cond_id in self.conditions.get_keys():\n tup = (cond_id, 'undefined condition')\n current_path += (tup,)\n undefined_paths.add(current_path)\n return False\n\n current_path += (tup,)\n condition = self.conditions.container[cond_id]\n condition_type = condition['type']\n\n if condition_type in list(self.condition_tests.keys()) and not \\\n self.condition_tests[condition_type](self, condition, undefined_paths, current_path):\n return False\n\n self.well_defined.add(cond_id)\n return True","def _check_conditional_dependency(obj, condition, package, severity, msg=None):\n if condition:\n if msg is None:\n msg = (\n f\"The specific parameter values of {obj.__class__.__name__}'s \"\n f\"class instance require `{package}` installed. Please run: \"\n f\"`pip install {package}` to \"\n f\"install the `{package}` package. \"\n )\n try:\n _check_soft_dependencies(package, severity=severity, obj=obj)\n except ModuleNotFoundError as e:\n raise ModuleNotFoundError(msg) from e","def check_deps(self):\n\t\tshutit_global.shutit_global_object.yield_to_draw()\n\t\tcfg = self.cfg\n\t\tself.log('PHASE: dependencies', level=logging.DEBUG)\n\t\tself.pause_point('\\nNow checking for dependencies between modules', print_input=False, level=3)\n\t\t# Get modules we're going to build\n\t\tto_build = [\n\t\t\tself.shutit_map[module_id] for module_id in self.shutit_map\n\t\t\tif module_id in cfg and cfg[module_id]['shutit.core.module.build']\n\t\t]\n\t\t# Add any deps we may need by extending to_build and altering cfg\n\t\tfor module in to_build:\n\t\t\tself.resolve_dependencies(to_build, module)\n\n\t\t# Dep checking\n\t\tdef err_checker(errs, triples):\n\t\t\t\"\"\"Collate error information.\n\t\t\t\"\"\"\n\t\t\tnew_triples = []\n\t\t\tfor err, triple in zip(errs, triples):\n\t\t\t\tif not err:\n\t\t\t\t\tnew_triples.append(triple)\n\t\t\t\t\tcontinue\n\t\t\t\tfound_errs.append(err)\n\t\t\treturn new_triples\n\n\t\tfound_errs = []\n\t\ttriples = []\n\t\tfor depender in to_build:\n\t\t\tfor dependee_id in depender.depends_on:\n\t\t\t\ttriples.append((depender, self.shutit_map.get(dependee_id), dependee_id))\n\n\t\ttriples = err_checker([ self.check_dependee_exists(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\n\t\ttriples = err_checker([ self.check_dependee_build(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\n\t\ttriples = err_checker([ check_dependee_order(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\n\n\t\tif found_errs:\n\t\t\treturn [(err,) for err in found_errs]\n\n\t\tself.log('Modules configured to be built (in order) are: ', level=logging.DEBUG)\n\t\tfor module_id in self.module_ids():\n\t\t\tmodule = self.shutit_map[module_id]\n\t\t\tif cfg[module_id]['shutit.core.module.build']:\n\t\t\t\tself.log(module_id + ' ' + str(module.run_order), level=logging.DEBUG)\n\t\tself.log('\\n', level=logging.DEBUG)\n\n\t\treturn []","def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):\n # Check for a matching dependency type\n related = []\n\n if edge[2][\"dep\"] == dep:\n # Check for matching POS type(s)\n for pos_logic in dep_obj.keys():\n connector = None\n\n if isinstance(dep_obj[pos_logic], dict):\n for pos in dep_obj[pos_logic].keys():\n\n # Check for allowed part of speech tags in matched dependency patterns\n if (pos_logic == \"pos_in\" and pos in G.nodes[sibling_idx][\"pos\"]) or (\n pos_logic == \"pos_equals\" and pos == G.nodes[sibling_idx][\"pos\"]):\n pass\n elif pos_logic == \"pos_not\":\n if not [False if not_pos == G.nodes[sibling_idx][\"pos\"] else True for not_pos in\n dep_obj.keys()]: continue\n else:\n continue\n\n # if no additional checks, have a match\n if dep_obj[pos_logic][pos] == None or any(\n y in dep_obj[pos_logic][pos] for y in [None, \"add_sibling\"]):\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']])\n\n # if additional checks are required, process further\n if dep_obj[pos_logic][pos]:\n if \"get_cousin\" in dep_obj[pos_logic][pos]:\n related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos][\"get_cousin\"]))\n connector = G.nodes[sibling_idx]['word']\n\n if \"special\" in dep_obj[pos_logic][pos]:\n if dep == \"compound\" and pos == \"NN\":\n related = [G.nodes[sibling_idx]['word']]\n\n if None in related:\n related.remove(None)\n\n # Allows for getting cousin and returning sibling\n if \"else\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\"else\"] == \"always\":\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\n if len(related) > 0 and isinstance(related, list):\n for x in related:\n if x != None:\n all_related = _add_related(x, dep, all_related, A.index_lookup[x],\n connector=connector)\n elif \"else\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\"else\"] == True:\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\n\n return all_related","def test_verify_all_dependencies(self):\n\n for condition in self.all_references():\n result = self.verify_dependencies(condition)\n\n if result:\n self.ill_defined[condition] = result\n else:\n self.well_defined.add(condition)\n\n return self.ill_defined","def find_dependencies(root):\n \n symbol_table = create_symbol_table(root)\n\n names = []\n #Set the depth of the root node\n set_depth(root, 0)\n #Stack of nodes to visit\n stack = Stack(root)\n \n #List of (src, dest) of dependencies\n dependency_table = DTable(symbol_table=symbol_table)\n\n for node, children, ntype in stack:\n \n stack.check_and_push_scope()\n\n #A Name is being loaded, therefore \n if ntype == \"Name\" and is_load(children):\n \"\"\"\n \"\"\"\n dependency_table.append( (stack.scopes, node))\n \n elif ntype == \"Assign\":\n #TODO need to add assignments and then revoke them\n #for child in children:\n #print children\n pass\n\n \n elif ntype == \"Attribute\":\n #TODO: attribute chains can be arbitrarily long\n #dep_dest = \"{}.{}\".format(node.value.id, node.attr)\n #print \"{} => {}\".format(scopes_to_str(scopes), dep_dest)\n\n #TODO: Can't just do dependency_table.append( (scopes, node))\n #since the unique_id function won't match the create the dep string like \n #{node.value.id}.{node.attr}.\n #Either generalize unique_id or something else.\n \n #Don't add children\n continue\n \n set_lineno(node, children)\n #Add children to stack\n #This musn't always be performed\n for child in children[::-1]:\n set_depth(child, node.depth + 1)\n stack.append(child)\n\n print \"dependency table is \"\n print dependency_table","def checkMetamodelLevel(cls):\n for mmd in cls.metamodelDependencies():\n mmd.check()","def test_walk_graph(self):\n def assertDependencyWalk(target, results, postorder=False):\n targets = []\n self.build_graph.walk_transitive_dependency_graph([target.address],\n lambda x: targets.append(x),\n postorder=postorder)\n self.assertEquals(results, targets)\n\n def assertDependeeWalk(target, results, postorder=False):\n targets = []\n self.build_graph.walk_transitive_dependee_graph([target.address],\n lambda x: targets.append(x),\n postorder=postorder)\n self.assertEquals(results, targets)\n\n a = self.make_target('a')\n b = self.make_target('b', dependencies=[a])\n c = self.make_target('c', dependencies=[b])\n d = self.make_target('d', dependencies=[c, a])\n e = self.make_target('e', dependencies=[d])\n\n assertDependencyWalk(a, [a])\n assertDependencyWalk(b, [b, a])\n assertDependencyWalk(c, [c, b, a])\n assertDependencyWalk(d, [d, c, b, a])\n assertDependencyWalk(e, [e, d, c, b, a])\n\n assertDependeeWalk(a, [a, b, c, d, e])\n assertDependeeWalk(b, [b, c, d, e])\n assertDependeeWalk(c, [c, d, e])\n assertDependeeWalk(d, [d, e])\n assertDependeeWalk(e, [e])\n\n assertDependencyWalk(a, [a], postorder=True)\n assertDependencyWalk(b, [a, b], postorder=True)\n assertDependencyWalk(c, [a, b, c], postorder=True)\n assertDependencyWalk(d, [a, b, c, d], postorder=True)\n assertDependencyWalk(e, [a, b, c, d, e], postorder=True)\n\n assertDependeeWalk(a, [e, d, c, b, a], postorder=True)\n assertDependeeWalk(b, [e, d, c, b], postorder=True)\n assertDependeeWalk(c, [e, d, c], postorder=True)\n assertDependeeWalk(d, [e, d], postorder=True)\n assertDependeeWalk(e, [e], postorder=True)\n\n #Try a case where postorder traversal is not identical to reversed preorder traversal\n c = self.make_target('c1', dependencies=[])\n d = self.make_target('d1', dependencies=[c])\n b = self.make_target('b1', dependencies=[c, d])\n e = self.make_target('e1', dependencies=[b])\n a = self.make_target('a1', dependencies=[b, e])\n\n assertDependencyWalk(a, [a, b, c, d, e])\n assertDependencyWalk(a, [c, d, b, e, a], postorder=True)","def _check_cyclic_defaults(template: JSONDict) -> List[Error]:\n stencil = view_by_default(template)\n dependencies = _sections_default_dependencies(stencil)\n # for nx we need to translate from tuples of lists to tuples of tuples\n dependencies_hashable = [\n (tuple(_from), tuple(_to)) for (_from, _to) in dependencies\n ]\n G = nx.DiGraph(dependencies_hashable)\n cycles = nx.simple_cycles(G)\n errors = []\n for c in cycles:\n errors.append(\n Error(\n c[0],\n f\"Keyword depends cyclically on keyword {location_in_dict(address=c[1])}\", # noqa: E501\n )\n )\n return errors","def checkRequiredDependencies(self):\n \n # skip dependency check for downloading only\n if( self.downloadOnly ):\n return\n\n # hard dependencies\n for req in self.reqmodules:\n if( self.parent.module(req) == None ):\n # check if there is an auto detected module\n if( self.parent.module(req, True) == None ):\n self.abort( self.name + \" requires \" + req \\\n + \" and it wasn't found in your config file!!\" )\n else:\n # use auto detected module\n self.parent.use( self.parent.module(req, True) )\n self.parent.module( req ).init()\n\n print self.name + \": auto-detected \" + req + \" version \" + self.parent.module( req ).version\n \n # build only dependencies\n if( self.mode == \"install\" ):\n mods = self.reqmodules_buildonly + self.reqmodules_external\n for req in mods:\n if( self.parent.module(req) == None ):\n # check if there is an auto detected module\n if( self.parent.module(req, True) == None ):\n self.abort( req + \" not found in your config file!! \" + self.name \\\n + \" cannot be built without \" + req )\n else:\n # use auto detected module\n self.parent.use( self.parent.module(req, True) )\n self.parent.module( req ).init()\n\n print \" - \" + self.name + \": auto-detected \" + req + \" version \" + self.parent.module( req ).version","def test_check_job_dependencies_prior_dependency_has_errors(database):\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=3)\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n sess.add_all([sub, job, job_2])\n sess.commit()\n\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\n sess.add(job_dep)\n sess.commit()\n\n check_job_dependencies(job.job_id)\n\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']","def dependencies(self, dep_context):\n if self.strict_deps:\n return strict_dependencies(self.target, dep_context)\n else:\n return all_dependencies(self.target, dep_context)","def check_packages(options):\n print '\\033[1;33m# Checking direct VIKI dependencies\\033[1;m'\n installed_ok = dependencies.check_installed_packages()\n print '\\n\\033[1;33m# Checking second level ROS dependencies, using rosdep\\033[1;m'\n second_level_ok = dependencies.get_second_level_dependencies()\n\n if installed_ok and second_level_ok:\n print '\\033[1;32mAll dependencies satisfied!\\033[1;m'\n else:\n print '\\033[1;31mTry running [viki install-dependencies] to install the dependencies\\033[1;m'","def testCheckDependencies(self):\n dependencies_file = self._GetTestFilePath(['dependencies.ini'])\n self._SkipIfPathNotExists(dependencies_file)\n\n dependency_helper = dependencies.DependencyHelper(\n dependencies_file=dependencies_file)\n\n dependency_helper.CheckDependencies(verbose_output=False)","def check_dependencies():\n\n vars_valid = check_variables(\n AirflowVars.PROJECT_ID, AirflowVars.TERRAFORM_ORGANIZATION, AirflowVars.VM_DAGS_WATCH_LIST\n )\n conns_valid = check_connections(AirflowConns.TERRAFORM)\n\n if not vars_valid or not conns_valid:\n raise AirflowException(\"Required variables or connections are missing\")","def test_build_all_dependencies_graph(self, mocker):\n\n def mock_find_pack_dependencies(pack_id, *_, **__):\n dependencies = {\n \"pack1\": [(\"pack2\", True), (\"pack3\", True)],\n \"pack2\": [(\"pack3\", True), (\"pack2\", True)],\n \"pack3\": [],\n \"pack4\": [(\"pack6\", False)],\n }\n\n dependencies_items = {\n \"pack1\": {\n (\"type_item_a\", \"item_a\"): {\n \"pack2\": [(\"type_item_2\", \"item2\")],\n \"pack3\": [(\"type_item_3\", \"item3\")],\n }\n },\n \"pack2\": {\n (\"type_item_b\", \"item_b\"): {\n \"pack3\": [(\"type_item_3\", \"item3\")],\n \"pack2\": [(\"type_item_2\", \"item2\")],\n }\n },\n \"pack3\": {},\n \"pack4\": {\n (\"type_item_c\", \"item_c\"): {\"pack4\": [(\"type_item_4\", \"item4\")]}\n },\n }\n\n return dependencies[pack_id], dependencies_items[pack_id]\n\n {\n \"Expanse Behavior Severity Update\": {\n \"Expanse\": \"ExpanseParseRawIncident\",\n \"CommonScripts\": \"IsGreaterThan\",\n },\n \"ExpanseParseRawIncident\": {\"Expanse\": \"ExpanseParseRawIncident\"},\n \"Expanse Appearance\": {\"Expanse\": \"incident_expanseseverity\"},\n \"Expanse Behavior\": {\"Expanse\": \"Expanse Behavior Severity Update\"},\n }\n mocker.patch(\n \"demisto_sdk.commands.find_dependencies.find_dependencies.PackDependencies._find_pack_dependencies\",\n side_effect=mock_find_pack_dependencies,\n )\n pack_ids = [\"pack1\", \"pack2\", \"pack3\", \"pack4\"]\n dependency_graph = PackDependencies.build_all_dependencies_graph(\n pack_ids, {}, False\n )\n\n # Asserting Dependencies (mandatory and non-mandatory)\n assert [n for n in dependency_graph.neighbors(\"pack1\")] == [\"pack2\", \"pack3\"]\n assert [n for n in dependency_graph.neighbors(\"pack2\")] == [\"pack3\"]\n assert [n for n in dependency_graph.neighbors(\"pack3\")] == []\n assert [n for n in dependency_graph.neighbors(\"pack4\")] == [\"pack6\"]\n\n # Asserting mandatory dependencies\n nodes = dependency_graph.nodes(data=True)\n\n assert nodes[\"pack1\"][\"mandatory_for_packs\"] == []\n assert nodes[\"pack1\"][\"depending_on_items_mandatorily\"] == {\n (\"type_item_a\", \"item_a\"): {\n \"pack2\": [(\"type_item_2\", \"item2\")],\n \"pack3\": [(\"type_item_3\", \"item3\")],\n }\n }\n assert nodes[\"pack1\"][\"depending_on_packs\"] == [\n (\"pack2\", True),\n (\"pack3\", True),\n ]\n assert nodes[\"pack1\"][\"mandatory_for_items\"] == {}\n\n assert nodes[\"pack2\"][\"mandatory_for_packs\"] == [\"pack1\"]\n assert nodes[\"pack2\"][\"depending_on_items_mandatorily\"] == {\n (\"type_item_b\", \"item_b\"): {\n \"pack3\": [(\"type_item_3\", \"item3\")],\n \"pack2\": [(\"type_item_2\", \"item2\")],\n }\n }\n assert nodes[\"pack2\"][\"depending_on_packs\"] == [\n (\"pack3\", True),\n (\"pack2\", True),\n ]\n assert nodes[\"pack2\"][\"mandatory_for_items\"] == {\n (\"type_item_2\", \"item2\"): {\"pack1\": [(\"type_item_a\", \"item_a\")]}\n }\n\n assert nodes[\"pack3\"][\"mandatory_for_packs\"] == [\"pack1\", \"pack2\"]\n assert nodes[\"pack3\"][\"depending_on_items_mandatorily\"] == {}\n assert nodes[\"pack3\"][\"depending_on_packs\"] == []\n assert nodes[\"pack3\"][\"mandatory_for_items\"] == {\n (\"type_item_3\", \"item3\"): {\n \"pack1\": [(\"type_item_a\", \"item_a\")],\n \"pack2\": [(\"type_item_b\", \"item_b\")],\n }\n }\n\n assert nodes[\"pack4\"][\"mandatory_for_packs\"] == []\n assert nodes[\"pack4\"][\"depending_on_items_mandatorily\"] == {\n (\"type_item_c\", \"item_c\"): {\"pack4\": [(\"type_item_4\", \"item4\")]}\n }\n assert nodes[\"pack4\"][\"depending_on_packs\"] == [(\"pack6\", False)]\n assert nodes[\"pack4\"][\"mandatory_for_items\"] == {}\n\n assert nodes[\"pack6\"][\"mandatory_for_packs\"] == []\n assert nodes[\"pack6\"][\"depending_on_items_mandatorily\"] == {}\n assert nodes[\"pack6\"][\"depending_on_packs\"] == []\n assert nodes[\"pack6\"][\"mandatory_for_items\"] == {}","def checkDeps( self ):\n\n # skip dependency check for downloading only\n if( self.downloadOnly ):\n return True\n\n # skip dependency check if package is going to be installed\n if( self.mode == \"install\" ):\n return True\n\n log.debug( 'Checking dependencies of %s', self.name )\n \n file = self.realPath() + \"/.dependencies\"\n \n r = True\n\n # if file doesn't exist return True\n if( not os.path.exists( file )):\n return True\n\n # open dependencies file\n f = open( file )\n filedeplist = {}\n for line in f.readlines():\n line = line.strip()\n if( (not line.startswith(os.linesep)) and (not line.startswith(\"#\")) \\\n and (len(line) > 0 )):\n tokens = line.split(\":\")\n filedeplist[ tokens[0] ] = tokens[1]\n f.close()\n\n log.debug( 'Dependencies read from file: %s', filedeplist )\n\n # get actual dependecies\n deplist={}\n self.getDepList(deplist)\n del deplist[self.name]\n\n log.debug( 'Dependencies found in current cfg file: %s', deplist )\n \n # compare dependencies\n for k, v in filedeplist.iteritems():\n if( deplist.has_key( k )):\n if( deplist[k] != v ):\n if( os.path.basename(deplist[k]) != os.path.basename(v) ):\n if( r ):\n print \"*** WARNING: ***\\n***\\tFollowing dependencies from \" + self.name + \" located at [ \" \\\n + self.realPath() + \" ] failed:\\n***\"\n print \"***\\t * \" + k + \" \" + os.path.basename(v) + \" differs from version \" \\\n + os.path.basename(deplist[k]) + \" defined in your config file..\"\n r = False\n else:\n if( r ): #just print this once\n print \"*** WARNING: ***\\n***\\tFollowing dependencies from \" + self.name + \" located at [ \" + self.realPath() \\\n + \" ] failed:\\n***\"\n print \"***\\t * \" + k + \" not found in your config file!!\"\n r = False\n \n\n if( not r ):\n print \"***\"\n if( self.useLink ):\n print \"***\\t\" + self.name + \" is in \\\"link\\\" mode, if you want to rebuild it with the new dependencies set it to \\\"use\\\" mode...\"\n r = True\n else:\n if( not self.parent.noAutomaticRebuilds ):\n print \"***\\t * \" + self.name + \" changed to \\\"install\\\" mode and rebuild flag set to True...\"\n self.mode = \"install\"\n self.rebuild = True\n self.preCheckDeps()\n print \"***\\n***\\tUpdating dependency tree ( modules that depend on \" + self.name + \" need also to be rebuilt )...\\n***\"\n self.updateDepTree([])\n print \"***\\n***\\tif you do NOT want to rebuild this module(s) just answer \\\"no\\\" later on in the installation process,\\n\" \\\n + \"***\\tor set the global flag ilcsoft.noAutomaticRebuilds=True in your config file...\"\n else:\n print \"***\\n***\\tglobal flag ilcsoft.noAutomaticRebuilds is set to True, nothing will be done...\\n***\"\n return r","def XXXcheck_class_dependencies(self, node):\n # keep track of types which are used by methods arguments\n used_types = {}\n for method in node[\"methods\"]:\n self.check_function_dependencies(method, used_types)\n\n modules = {}\n for typ in used_types.values():\n if typ.f_module:\n for mname, only in typ.f_module.items():\n module = modules.setdefault(mname, {})\n if only: # Empty list means no ONLY clause\n for oname in only:\n module[oname] = True\n\n # Always add C_PTR, needed for class F_derived_member\n modules.setdefault(\"iso_c_binding\", {})[\"C_PTR\"] = True\n\n F_modules = [] # array of tuples ( name, (only1, only2) )\n for mname in sorted(modules):\n F_modules.append((mname, sorted(modules[mname])))\n node.F_module_dependencies = F_modules","def dependencies_satisfied(self, module) -> bool:\n for k, v in module.requirements.items():\n if k not in self.modules:\n return False\n found_ver = self.modules[k].version\n if isinstance(v, str):\n return found_ver == v\n elif isinstance(v, dict):\n if \"eq\" in v and (found_ver != v[\"eq\"]):\n return False\n if \"min\" in v and (found_ver < v[\"min\"]):\n return False\n if \"max\" in v and (found_ver > v[\"max\"]):\n return False\n else:\n return True\n return True","def dependencies(artifact_or_id):\n artifact = r.coerce_to_artifact(artifact_or_id)\n visited = []\n queue = [artifact]\n while queue:\n a, *queue = queue\n\n if a in visited:\n continue\n\n visited.append(a)\n queue.extend(_artifact_branches(a))\n\n visited.reverse()\n return visited","def checkOptionalDependencies(self):\n \n # skip dependency check for downloading only\n if( self.downloadOnly ):\n return\n\n # soft dependencies\n failed = []\n for opt in self.optmodules:\n mod = self.parent.module(opt)\n if( mod == None ):\n failed.append(opt)\n \n # remove soft dependencies that were not found\n self.buildWithout(failed)","def testConditionChecking(self):\n\n state = State.from_problem(self.prob)\n \n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition))\n\n with drive.instantiate([\"agent\", \"tru1\", \"apt2\"], self.prob):\n self.assertFalse(state.is_satisfied(drive.precondition))","def dependencies(self, dep_context):\n if self.strict_deps:\n return self.target.strict_dependencies(dep_context)\n else:\n return list(self.target.closure(bfs=True, **dep_context.target_closure_kwargs))","def _check_dependency(self, tcname, depends):\r\n tcindex = self.tcorder.index(tcname)\r\n dependsindex = []\r\n for i in depends:\r\n dependsindex.append(self.tcorder.index(i))\r\n for i in dependsindex:\r\n if tcindex < i:\r\n msg = \"%s must be ordered after %s\\n\" %(tcname, self.tcorder[i])\r\n self.dependency.append(msg)","def _identify_required_grads(self):\n self.grad_expected += 1\n if self.grad_expected == 1: # only backpropagate once from each node\n for child in self.children:\n child._identify_required_grads()","def validate(self):\n for rosdep_key in self:\n # Ensure all dependencies have definitions\n # i.e.: Ensure we aren't pointing to invalid rosdep keys\n for dependency in self[rosdep_key]['dependencies']:\n if dependency not in self:\n raise KeyError(\n 'Invalid Graph Structure: rosdep key `%s` does not exist in the dictionary of resolutions.'\n % dependency)\n self[dependency]['is_root'] = False\n # Check each entry for cyclical dependencies\n for rosdep_key in self:\n self.detect_cycles(rosdep_key, [])","def test_grandchildren():\n\n # note c.upto(\"status\").desired.grandchildren\n # this is the same as *c.upto(\"status\").desired in python3.5+\n res = conf.status.conditions.choose(lambda c: (c.type, c.reason, c.upto(\"status\").desired.grandchildren))\n assert \"type\" in res\n assert \"reason\" in res\n assert \"version\" in res\n assert \"image\" in res\n assert \"force\" in res","def verify_dependencies(self):\n dependencies = {\n \"manufacturers\": [\n {\"name\": \"VMware\", \"slug\": \"vmware\"},\n ],\n \"platforms\": [\n {\"name\": \"VMware ESXi\", \"slug\": \"vmware-esxi\"},\n {\"name\": \"Windows\", \"slug\": \"windows\"},\n {\"name\": \"Linux\", \"slug\": \"linux\"},\n ],\n \"sites\": [{\n \"name\": \"vCenter\",\n \"slug\": \"vcenter\",\n \"comments\": \"A default virtual site created to house objects \"\n \"that have been synced from vCenter.\",\n \"tags\": [\"Synced\", \"vCenter\"]\n }],\n \"cluster_types\": [\n {\"name\": \"VMware ESXi\", \"slug\": \"vmware-esxi\"}\n ],\n \"device_roles\": [\n {\n \"name\": \"Server\",\n \"slug\": \"server\",\n \"color\": \"9e9e9e\",\n \"vm_role\": True\n }],\n \"tags\": [\n {\n \"name\": \"Orphaned\",\n \"slug\": \"orphaned\",\n \"color\": \"607d8b\",\n \"comments\": \"This applies to objects that have become \"\n \"orphaned. The source system which has \"\n \"previously provided the object no longer \"\n \"states it exists.{}\".format(\n \" An object with the 'Orphaned' tag will \"\n \"remain in this state until it ages out \"\n \"and is automatically removed.\"\n ) if settings.NB_PRUNE_ENABLED else \"\"\n },\n {\n \"name\": self.vc_tag,\n \"slug\": format_slug(self.vc_tag),\n \"comments\": \"Objects synced from vCenter host \"\n \"{}. Be careful not to modify the name or \"\n \"slug.\".format(self.vc_tag)\n }]\n }\n # For each dependency of each type verify object exists\n log.info(\"Verifying all prerequisite objects exist in NetBox.\")\n for dep_type in dependencies:\n log.debug(\n \"Checking NetBox has necessary %s objects.\", dep_type[:-1]\n )\n for dep in dependencies[dep_type]:\n self.obj_exists(nb_obj_type=dep_type, vc_data=dep)\n log.info(\"Finished verifying prerequisites.\")","def test_nested():\n res = conf.status.conditions.choose(lambda c: (c.type, c.reason, c.root.metadata.choose(lambda m: (m[\"name\"], m.uid))))\n assert \"type\" in res # from conditions\n assert \"reason\" in res # from conditions\n assert \"name\" in res # from metadata\n assert \"uid\" in res # from metadata","def check_requirements_feasibility(self, requirements):\n\n subgraphs = []\n\n # FIXME need to fix this if there are multiple sources\n feasibilities = []\n for requirement in requirements:\n visited_cells = {}\n feasible, cs_root = self._check_requirement_feasibility(requirement.root, 0,\n self.sources[0], visited_cells, 0)\n feasibilities.append(feasible)\n\n if feasible == True:\n subgraph = ConveyanceSubgraph(cs_root[0][1])\n subgraphs.append(subgraph)\n\n print(\"Requirement '%s' feasibility: %r\" % (requirement.name,\n feasible))\n print()\n\n return feasibilities, subgraphs","def is_dependency_subgraph(graph, subgraph_candidate,\n node_attrib='label', edge_attrib='label'):\n if len(subgraph_candidate) > 1:\n if nx.is_weakly_connected(subgraph_candidate):\n if includes_all_subgraph_rules(graph, subgraph_candidate,\n node_attrib=node_attrib,\n edge_attrib=edge_attrib):\n return True\n return False","def make_dependence_cmp():\r\n\r\n depends = make_depends()\r\n\r\n def dependence(a, b):\r\n \"\"\" A cmp function for nodes in a graph - does a depend on b?\r\n\r\n Returns positive number if a depends on b\r\n Returns negative number if b depends on a\r\n Returns 0 otherwise\r\n \"\"\"\r\n if depends((a, b)):\r\n return 1\r\n if depends((b, a)):\r\n return -1\r\n return 0\r\n\r\n return dependence","def check_prerequisites(self, env):\n super(PassiveTracersDepth, self).check_prerequisites(env)\n print(' Checking prerequisites for : {0}'.format(self.__class__.__name__))","def _recurse(self, name):\n if name in self._current:\n state.log.fail(f\"Detected recursive dependency involving package '{name}'\")\n else:\n self._current.add(name)\n if name in self.packages:\n self._current.remove(name)\n return self.packages[name] is not None\n module = self._tryImport(name)\n if module is None:\n self.packages[name] = None\n self._current.remove(name)\n return False\n for dependency in module.dependencies.get(\"required\", ()):\n if not self._recurse(dependency):\n # We can't configure this package because a required\n # dependency wasn't found. But this package might itself be\n # optional, so we don't die yet.\n self.packages[name] = None\n self._current.remove(name)\n state.log.warn(\n f\"Could not load all dependencies for package '{name}' (missing {dependency}).\"\n )\n return False\n for dependency in module.dependencies.get(\"optional\", ()):\n self._recurse(dependency)\n # This comes last to ensure the ordering puts all dependencies first.\n self.packages[name] = module\n self._current.remove(name)\n return True","def _sufficient_deps(cls, deps):\n if cls.MODEL_PACKAGE is None:\n return True\n else:\n for d in deps.conda:\n if cls.MODEL_PACKAGE in d:\n return True\n for d in deps.pip:\n if cls.MODEL_PACKAGE in d:\n return True\n return False","def dfs(i, adj_dict, edges, checked, cycle, start):\n for vertex in adj_dict[i]:\n pos = search_pos(i, vertex, edges, checked)\n if pos != -1:\n checked[pos] = True\n if vertex[0] == start and not (False in checked):\n cycle.append((vertex[0], i, vertex[1]))\n return True\n if dfs(vertex[0], adj_dict, edges, checked, cycle, start):\n cycle.append((vertex[0], i, vertex[1]))\n return True\n checked[pos] = False\n return False","def are_all_deps_fulfilled(self, package: 'Package', only_make_check: bool = False,\n only_depends: bool = False, print_reason: bool = False) -> bool:\n\n for dep in package.relevant_deps(only_make_check=only_make_check, only_depends=only_depends):\n if not self.provided_by(dep):\n if print_reason:\n aurman_note(\n \"Dependency {} of package {} is not fulfilled\".format(\n Colors.BOLD(Colors.LIGHT_MAGENTA(dep)),\n Colors.BOLD(Colors.LIGHT_MAGENTA(package.name))\n )\n )\n return False\n else:\n return True","def check_requirements(config=None):\n for dependency, module_requirements in (\n requirements(config, include_conditional=False).items()):\n for module_requirement in module_requirements:\n if \">=\" in module_requirement:\n module_name, required_version = module_requirement.split(\">=\")\n version_test = \">=\"\n elif \"==\" in module_requirement:\n module_name, required_version = module_requirement.split(\"==\")\n version_test = \"==\"\n else:\n module_name = module_requirement\n version_test = None\n\n try:\n module = __import__(module_name)\n except ImportError:\n logging.exception(\n \"Can't import %r which is part of %r\",\n module_name, dependency\n )\n raise MissingRequirementError(\n \"Can't import %r which is part of %r\"\n % (module_name, dependency), module_name, dependency\n )\n version = getattr(module, \"__version__\", None)\n file_path = getattr(module, \"__file__\", None)\n logger.info(\n \"Using %r version %r from %r to satisfy %r\",\n module_name, version, file_path, dependency\n )\n\n if version_test == \">=\":\n if version is None:\n raise MissingRequirementError(\n \"Version of %r isn't set as __version__ of module %r\"\n % (dependency, module_name), module_name, dependency\n )\n if LooseVersion(version) < LooseVersion(required_version):\n raise MissingRequirementError(\n \"Version of %r in %r is too old. %r < %r\"\n % (dependency, file_path, version, required_version),\n module_name, dependency\n )\n elif version_test == \"==\":\n if version is None:\n raise MissingRequirementError(\n \"Version of %r isn't set as __version__ of module %r\"\n % (dependency, module_name), module_name, dependency\n )\n if LooseVersion(version) != LooseVersion(required_version):\n raise MissingRequirementError(\n \"Unexpected version of %r in %r. %r != %r\"\n % (dependency, file_path, version, required_version),\n module_name, dependency\n )","def test_get_flat_dependency_tree(self):\n with open(str(Path(__file__).parent.parent.parent) +\n '/data/manifests/golist2.json', 'rb') as fp:\n fs = FileStorage(stream=fp, filename='golist.json')\n sa_post_request = StackAnalysesPostRequest(manifest=fs, file_path='/tmp/bin',\n ecosystem='golang', show_transitive=True)\n sa = StackAnalyses(sa_post_request)\n sa._manifest_file_info = {\n 'filename': sa.params.manifest.filename,\n 'filepath': sa.params.file_path,\n 'content': sa.params.manifest.read().decode('utf-8')\n }\n save_in_db, packages = sa._get_flat_dependency_tree()\n assert isinstance(save_in_db, dict)\n assert isinstance(save_in_db['result'], list)\n assert isinstance(save_in_db['result'][0]['details'], list)\n assert isinstance(save_in_db['result'][0]['details'][0], dict)\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'], list)\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'], list)\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'][0], dict)\n assert save_in_db['result'][0]['details'][0]['_resolved'][0]['package'], \\\n 'github.com/thoughtworks/talisman'\n assert save_in_db['result'][0]['details'][0]['_resolved'][0]['version'], '0.3.3'\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'][0]['deps'], list)\n assert save_in_db['result'][0]['details'][0]['_resolved'][0]['deps'][0]['package'], \\\n 'github.com/hashicorp/vault/vault'\n assert isinstance(packages, list)","def testConditionReasons(self):\n \n state = State.from_problem(self.prob)\n\n relevantVars = []\n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\n\n relevantVars = set(relevantVars)\n \n s1 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"pos1\"]])\n s2 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"apt1\"]])\n s3 = StateVariable(self.prob.functions[\"location-of\"][0], [self.prob[\"tru1\"]])\n \n self.assertEqual(len(relevantVars), 3)\n self.assert_(s1 in relevantVars)\n self.assert_(s2 in relevantVars)\n self.assert_(s3 in relevantVars)","def dep_solving(packages: Sequence['Package'], installed_system: 'System', upstream_system: 'System') -> List[\n List['Package']]:\n\n deps_to_deep_check = set()\n single_first = False\n\n while True:\n current_solutions = [DepAlgoSolution([], [], set())]\n found_problems = set()\n\n # calc solutions\n # for every single package first\n if single_first:\n for package in packages:\n new_solutions = []\n for solution in current_solutions:\n solution.dict_call_as_needed = {package.name: True}\n new_solutions.extend(\n package.solutions_for_dep_problem(\n solution, found_problems, installed_system, upstream_system, deps_to_deep_check\n )\n )\n current_solutions = new_solutions\n\n # now for all packages together\n for solution in current_solutions:\n solution.dict_call_as_needed = {}\n for package in packages:\n solution.dict_call_as_needed[package.name] = True\n for package in packages:\n new_solutions = []\n for solution in current_solutions:\n new_solutions.extend(\n package.solutions_for_dep_problem(\n solution, found_problems, installed_system, upstream_system, deps_to_deep_check\n )\n )\n current_solutions = new_solutions\n\n # delete invalid solutions\n current_solutions = [solution for solution in current_solutions if solution.is_valid]\n\n # in case of at least one solution, we are done\n if current_solutions:\n break\n\n deps_to_deep_check_length = len(deps_to_deep_check)\n for problem in found_problems:\n problem_packages_names = set([package.name for package in problem.relevant_packages])\n deps_to_deep_check |= problem_packages_names\n\n # if there are no new deps to deep check, we are done, too\n if len(deps_to_deep_check) == deps_to_deep_check_length and single_first:\n break\n elif len(deps_to_deep_check) == deps_to_deep_check_length:\n if len(packages) > 1:\n single_first = True\n else:\n break\n\n # output for user\n if found_problems and not current_solutions:\n aurman_error(\n \"While searching for solutions the following errors occurred:\\n{}\\n\".format(\n \"\\n\".join([aurman_note(problem, False, False) for problem in found_problems])\n ), True\n )\n\n return [solution.packages_in_solution for solution in current_solutions]","def test_check_model_dependencies_complete(dependency_testing_model, complete_env) -> None:\n assert check_model_dependencies(\n model_cls=dependency_testing_model,\n environment=complete_env,\n raise_for_missing=False,\n )","def testCheckTestDependencies(self):\n dependencies_file = self._GetTestFilePath(['dependencies.ini'])\n self._SkipIfPathNotExists(dependencies_file)\n\n dependency_helper = dependencies.DependencyHelper(\n dependencies_file=dependencies_file)\n\n dependency_helper.CheckTestDependencies(verbose_output=False)","def __satisfies_necessary_and_sufficient_conditions(g):\n # Condition 0: at least 1 Edge\n if g.get_E() == 0:\n return False\n # Condition 1: indegree(v) == outdegree(v) for every vertex\n for v in range(g.get_V()):\n if g.outdegree() != g.indegree(v):\n return False\n # Condition 2: graph is connected, ignoring isolated vertices\n h = Graph(g.get_V())\n for v in range(g.get_V()):\n for w in g.adj_vertices(v):\n h.add_edge(v, w)\n # check that all non-isolated vertices are connected\n s = DirectedEulerianCycle.__non_isolated_vertex(g)\n bfs = BreadthFirstPaths(h, s)\n for v in range(g.get_V()):\n if h.degree(v) > 0 and not bfs.has_path_to(v):\n return False\n return True","def checkroot(self):\n\t\tif len(self.deps) == 0:\n\t\t\treturn True\n\t\trootspan = self.wordspans[self.head_pos]\n\t\tfor head in self.deps:\n\t\t\tif head < rootspan[0] or head > rootspan[1]:\n\t\t\t\treturn False\n\t\t\tfor dependent in self.deps[head]:\n\t\t\t\tif dependent[0] < rootspan[0] or dependent[0] > rootspan[1]:\n\t\t\t\t\treturn False\n\t\treturn True","def check_model(self):\n for node in self.nodes():\n cpd = self.get_cpds(node=node)\n\n if cpd is None:\n raise ValueError(\"No CPD associated with {}\".format(node))\n elif isinstance(cpd, (TabularCPD, ContinuousFactor)):\n evidence = cpd.get_evidence()\n parents = self.get_parents(node)\n if set(evidence if evidence else []) != set(parents if parents else []):\n raise ValueError(\n \"CPD associated with {node} doesn't have \"\n \"proper parents associated with it.\".format(node=node)\n )\n if not cpd.is_valid_cpd():\n raise ValueError(\n \"Sum or integral of conditional probabilites for node {node}\"\n \" is not equal to 1.\".format(node=node)\n )\n return True","def __dependency_traverse(self, v, visited, results):\n if v in visited:\n return\n visited.add(v)\n # Create list of input data\n data = []\n for p in v.predecessors():\n # Traverse dependencies that have not been visited yet\n self.__dependency_traverse(p, visited, results)\n data.append(results[p])\n data = data[0] if len(data) == 1 else data\n # Flatten list of input data if there is only one element\n results[v] = self.traverse_vertex(v, data)\n # Traverse transforms that require this dependency and have not been visited\n for n in v.successors():\n self.__dependency_traverse(n, visited, results)","def check_flow_conditions(triple, fwd, rev, overlap):\n\n p1, p2, p3 = [self.paths[triple[x]] for x in [0,1,2]]\n p2_end_index = len(p2) - rev + overlap\n #print(\"p2_end_index = {}\".format(p2_end_index))\n p1_start_index = fwd + 1\n #print(\"p1_start_index = {}\".format(p1_start_index))\n #print(\"p1 subset: {}\".format(p1[p1_start_index - 1:]))\n #print(\"p2 subset = {}\".format(p2[:p2_end_index]))\n p_prime = p2[:p2_end_index] + p1[p1_start_index - 1:]\n #print(\"p_prime = {}\".format(p_prime))\n\n # try to rebalance\n if flow_condition(p1, p2, triple):\n print(\"Rebalance opportunity found. Now rebalancing.\")\n self.rebalances += 1\n return(True)\n\n # try to splice and merge\n if flow_condition(p_prime, p3, triple):\n print(\"Splice+merge opportunity found. Now splicing.\")\n self.splices += 1\n return(True)\n\n return(False)","def _resolve_dependencies(self):\n matching_versions = dict()\n\n # Initialization of the BFS\n bfs_stack = list()\n for requirement_name, spec_str in sorted(self.spec_requirements, key=lambda x: x[0].lower()):\n self._add_spec(requirement_name, spec_str)\n bfs_stack.append(requirement_name)\n\n # Main loop\n while bfs_stack:\n # Stack Unwind\n requirement_name = bfs_stack.pop(0)\n available_versions = self._get_available_versions(requirement_name)\n spec = self._get_spec(requirement_name)\n best_matching_version = spec.select(available_versions)\n if best_matching_version is None:\n msg = 'Unmatched dependency for {}\\nSpecification requirement: {}\\nAvailable versions: {}\\n' \\\n 'Use NPM semver calculator to resolve: https://semver.npmjs.com/'\n error = msg.format(requirement_name, spec, ', '.join(reversed(map(str, available_versions))))\n raise RequirementMatchError(error)\n\n matching_versions[requirement_name] = best_matching_version\n\n # BFS stack population with dependencies\n dependencies = self._get_dependencies(requirement_name, best_matching_version)\n for dependency_name, dependency_version in dependencies:\n self._add_spec(dependency_name, dependency_version)\n bfs_stack.append(dependency_name)\n\n return matching_versions","def check_dependencies(cls):\n\n missing = []\n for name in cls.DEPENDENCIES:\n try:\n import_module(name)\n except ModuleNotFoundError:\n missing.append(name)\n\n if any(missing):\n msg = ('The sup3r stitching module depends on the following '\n 'special dependencies that were not found in the active '\n 'environment: {}'.format(missing))\n logger.error(msg)\n raise ModuleNotFoundError(msg)","def check_feasibility(nodes, edges, T, I, S, S_out):\n # 1. All nodes are end ancestors\n def isAncestor(start, node):\n marked[node] = True\n try: successors = I[node]\n except: successors = []\n if 'end' in successors:\n end_ancestor[start] = True\n if not end_ancestor[start]:\n for successor in successors:\n if not marked[successor]:\n isAncestor(start, successor)\n\n # 2. All nodes are start descendants\n def isDescendant(node):\n start_descendant[node] = True\n try: successors = I[node]\n except: successors = []\n for successor in successors:\n if successor != 'end' and start_descendant[successor] == False:\n isDescendant(successor)\n \n # Find extra edges if condition fails.\n def make_connected(edges, state, check_cond='desc'):\n component_nodes = [k for k, v in state.items() if v == False]\n directed_nodes = [k for k, v in state.items() if v == True]\n source = directed_nodes if check_cond == 'desc' else component_nodes\n target = component_nodes if check_cond == 'desc' else directed_nodes\n extra_edges = dict()\n for node in source:\n for a in T[node]:\n if a in target:\n extra_edges[(node, a)] = S_out[node][a]\n if len(extra_edges) == 0:\n S_comp = {k: v for k, v in S.items() if k in component_nodes}\n if check_cond == 'desc':\n edges.append(('start', max(S_comp, key=S_comp.get)))\n if 'start' not in I:\n I['start'] = dict()\n I['start'][max(S_comp, key=S_comp.get)] = 1\n else:\n edges.append((max(S_comp, key=S_comp.get), 'end'))\n if max(S_comp, key=S_comp.get) not in I:\n I[max(S_comp, key=S_comp.get)] = dict()\n I[max(S_comp, key=S_comp.get)]['end'] = 1\n else:\n extra_edge = max(extra_edges, key=extra_edges.get)\n edges.append((extra_edge[0], extra_edge[1]))\n if extra_edge[0] not in I:\n I[extra_edge[0]] = dict()\n I[extra_edge[0]][extra_edge[1]] = 1\n\n while True:\n end_ancestor = dict.fromkeys(nodes, False)\n for v in nodes:\n marked = dict.fromkeys(nodes, False)\n isAncestor(v, v)\n if all(end_ancestor.values()): break\n else: make_connected(edges, end_ancestor, 'anc')\n\n while True:\n start_descendant = dict.fromkeys(nodes, False)\n isDescendant('start')\n if all(start_descendant.values()): break\n else: make_connected(edges, start_descendant, 'desc')","def test_check_job_dependencies_has_unfinished_dependencies(database):\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=0)\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n job_3 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=0)\n sess.add_all([sub, job, job_2, job_3])\n sess.commit()\n\n # Job 1 finished, it is a prerequisite for job 2 (waiting)\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\n # Job 3 is also a prerequisite of job 2, it's not done, job 2 should stay in \"waiting\"\n job_dep_2 = JobDependency(job_id=job_2.job_id, prerequisite_id=job_3.job_id)\n sess.add_all([job_dep, job_dep_2])\n sess.commit()\n\n check_job_dependencies(job.job_id)\n\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']","def _check_family(self):\n for (s, (b, c)), (cond, ref) in families.items():\n if s != self.SYMBOL or len(b) != self._.d:\n continue\n vars = tuple(set(sum(map(variables, b + c), ())))\n sols = _solve([SR(l) == r for l, r\n in zip(self._.b[:-1] + self._.c[1:], b + c)],\n vars)\n if any(checkConditions(cond, sol) for sol in sols\n if is_integral(sol)):\n raise InfeasibleError(refs=ref)","def depthFirstSearch(problem):\n \"*** YOUR CODE HERE ***\"\n \n util.raiseNotDefined()","def depthFirstSearch(problem):\n \"*** YOUR CODE HERE ***\"\n util.raiseNotDefined()","def _contains_cycle(fgraph, orderings):\r\n\r\n # These are lists of Variable instances\r\n inputs = fgraph.inputs\r\n outputs = fgraph.outputs\r\n\r\n\r\n # this is hard-coded reimplementation of functions from graph.py\r\n # reason: go faster, prepare for port to C.\r\n # specifically, it could be replaced with a wrapper\r\n # around graph.io_toposort that returns True iff io_toposort raises\r\n # a ValueError containing the substring 'cycle'.\r\n # This implementation is optimized for the destroyhandler and runs\r\n # slightly faster than io_toposort.\r\n\r\n # this is performance-critical code. it is the largest single-function\r\n # bottleneck when compiling large graphs.\r\n\r\n assert isinstance(outputs, (tuple, list, deque))\r\n\r\n # TODO: For more speed - use a defaultdict for the orderings\r\n # (defaultdict runs faster than dict in the case where the key\r\n # is not in the dictionary, at least in CPython)\r\n\r\n iset = set(inputs)\r\n\r\n # IG: I tried converting parent_counts to use an id for the key,\r\n # so that the dict would do reference counting on its keys.\r\n # This caused a slowdown.\r\n # Separate benchmark tests showed that calling id is about\r\n # half as expensive as a dictionary access, and that the\r\n # dictionary also runs slower when storing ids than when\r\n # storing objects.\r\n\r\n\r\n # dict mapping an Apply or Variable instance to the number\r\n # of its parents (including parents imposed by orderings)\r\n # that haven't been visited yet\r\n parent_counts = {}\r\n # dict mapping an Apply or Variable instance to its children\r\n node_to_children = {}\r\n\r\n # visitable: A container holding all Variable and Apply instances\r\n # that can currently be visited according to the graph topology\r\n # (ie, whose parents have already been visited)\r\n # TODO: visitable is a fifo_queue. could this run faster if we\r\n # implement it as a stack rather than a deque?\r\n # TODO: visitable need not be a fifo_queue, any kind of container\r\n # that we can throw things into and take things out of quickly will\r\n # work. is there another kind of container that could run faster?\r\n # we don't care about the traversal order here as much as we do\r\n # in io_toposort because we aren't trying to generate an ordering\r\n # on the nodes\r\n visitable = deque()\r\n\r\n # IG: visitable could in principle be initialized to fgraph.inputs\r\n # + fgraph.orphans... if there were an fgraph.orphans structure.\r\n # I tried making one and maintaining it caused a huge slowdown.\r\n # This may be because I made it a list, so it would have a\r\n # deterministic iteration order, in hopes of using it to speed\r\n # up toposort as well.\r\n # I think since we need to scan through all variables and nodes\r\n # to make parent_counts anyway, it's cheap enough to always\r\n # detect orphans at cycle detection / toposort time\r\n\r\n\r\n # Pass through all the nodes to build visitable, parent_count, and\r\n # node_to_children\r\n for var in fgraph.variables:\r\n\r\n # this is faster than calling get_parents\r\n owner = var.owner\r\n if owner:\r\n parents = [ owner ]\r\n else:\r\n parents = []\r\n\r\n # variables don't appear in orderings, so we don't need to worry\r\n # about that here\r\n\r\n if parents:\r\n for parent in parents:\r\n # insert node in node_to_children[r]\r\n # (if r is not already in node_to_children,\r\n # intialize it to [])\r\n node_to_children.setdefault(parent, []).append(var)\r\n parent_counts[var] = len(parents)\r\n else:\r\n visitable.append(var)\r\n parent_counts[var] = 0\r\n\r\n for a_n in fgraph.apply_nodes:\r\n parents = list(a_n.inputs)\r\n # This is faster than conditionally extending\r\n # IG: I tried using a shared empty_list = [] constructed\r\n # outside of the for loop to avoid constructing multiple\r\n # lists, but this was not any faster.\r\n parents.extend(orderings.get(a_n, []))\r\n\r\n if parents:\r\n for parent in parents:\r\n # insert node in node_to_children[r]\r\n # (if r is not already in node_to_children,\r\n # intialize it to [])\r\n node_to_children.setdefault(parent, []).append(a_n)\r\n parent_counts[a_n] = len(parents)\r\n else:\r\n # an Apply with no inputs would be a weird case, but I'm\r\n # not sure we forbid it\r\n visitable.append(a_n)\r\n parent_counts[a_n] = 0\r\n\r\n # at this point,\r\n # parent_counts.keys() == fgraph.apply_nodes + fgraph.variables\r\n\r\n\r\n\r\n # Now we actually check for cycles\r\n # As long as there are nodes that can be visited while respecting\r\n # the topology, we keep visiting nodes\r\n # If we run out of visitable nodes and we haven't visited all nodes,\r\n # then there was a cycle. It blocked the traversal because some\r\n # node couldn't be visited until one of its descendants had been\r\n # visited too.\r\n # This is a standard cycle detection algorithm.\r\n\r\n visited = 0\r\n while visitable:\r\n # Since each node is inserted into the visitable queue exactly\r\n # once, it comes out of the queue exactly once\r\n # That means we can decrement its children's unvisited parent count\r\n # and increment the visited node count without double-counting\r\n node = visitable.popleft()\r\n visited += 1\r\n for client in node_to_children.get(node,[]):\r\n parent_counts[client] -= 1\r\n # If all of a node's parents have been visited,\r\n # it may now be visited too\r\n if not parent_counts[client]:\r\n visitable.append(client)\r\n\r\n\r\n return visited != len(parent_counts)","def validate(self, fgraph):\r\n\r\n if self.destroyers:\r\n ords = self.orderings(fgraph)\r\n\r\n if _contains_cycle(fgraph, ords):\r\n raise InconsistencyError(\"Dependency graph contains cycles\")\r\n else:\r\n #James's Conjecture:\r\n #If there are no destructive ops, then there can be no cycles.\r\n pass\r\n return True","def validate(self, fgraph):\r\n\r\n if self.destroyers:\r\n ords = self.orderings(fgraph)\r\n\r\n if _contains_cycle(fgraph, ords):\r\n raise InconsistencyError(\"Dependency graph contains cycles\")\r\n else:\r\n #James's Conjecture:\r\n #If there are no destructive ops, then there can be no cycles.\r\n pass\r\n return True","def check(self, srcs, actual_deps):\r\n if self._check_missing_deps or self._check_missing_direct_deps or self._check_unnecessary_deps:\r\n missing_file_deps, missing_tgt_deps, missing_direct_tgt_deps = \\\r\n self._compute_missing_deps(srcs, actual_deps)\r\n\r\n buildroot = get_buildroot()\r\n def shorten(path): # Make the output easier to read.\r\n for prefix in [buildroot, self._context.ivy_home]:\r\n if path.startswith(prefix):\r\n return os.path.relpath(path, prefix)\r\n return path\r\n\r\n if self._check_missing_deps and (missing_file_deps or missing_tgt_deps):\r\n for (tgt_pair, evidence) in missing_tgt_deps:\r\n evidence_str = '\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\r\n for e in evidence])\r\n self._context.log.error(\r\n 'Missing BUILD dependency %s -> %s because:\\n%s'\r\n % (tgt_pair[0].address.reference(), tgt_pair[1].address.reference(), evidence_str))\r\n for (src_tgt, dep) in missing_file_deps:\r\n self._context.log.error('Missing BUILD dependency %s -> %s'\r\n % (src_tgt.address.reference(), shorten(dep)))\r\n if self._check_missing_deps == 'fatal':\r\n raise TaskError('Missing deps.')\r\n\r\n if self._check_missing_direct_deps:\r\n for (tgt_pair, evidence) in missing_direct_tgt_deps:\r\n evidence_str = '\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\r\n for e in evidence])\r\n self._context.log.warn('Missing direct BUILD dependency %s -> %s because:\\n%s' %\r\n (tgt_pair[0].address, tgt_pair[1].address, evidence_str))\r\n if self._check_missing_direct_deps == 'fatal':\r\n raise TaskError('Missing direct deps.')\r\n\r\n if self._check_unnecessary_deps:\r\n raise TaskError('Unnecessary dep warnings not implemented yet.')","def check_dependencies(target_binary, target_platform, target_architecture, target_type):\n check_architecture(target_architecture)\n check_platform(target_platform)","def condition(*args, delete: bool=True, dependency: Union[AnyStr, List[AnyStr]]=\"\", initialize:\n bool=True, script: AnyStr=\"\", state: bool=True, q=True, query=True, e=True,\n edit=True, **kwargs)->Union[None, Any]:\n pass","def check_dag_acyclic(self, start, inputs):\n for binding in inputs.values():\n if start == binding.io_owner:\n return False\n for p in binding.parents:\n if not self.check_dag_acyclic(start, p.io_owner.input_bindings.bindings):\n return False\n\n return True","def is_order_constrained(paths, constraints, j, k):\r\n for q in range(j, k):\r\n # search between j and k.\r\n first_path = paths[q]\r\n for constraint in constraints:\r\n if first_path is not constraint[0]:\r\n # Constraint does not apply to the value at q.\r\n continue\r\n for m in range(q + 1, k):\r\n second_path = paths[m]\r\n if second_path is constraint[1]:\r\n # Constraint demands the order must be first_path then second_path.\r\n return True\r\n return False","def check_cont(cont, reqs):\n for req_k, req_v in reqs.items():\n if req_k == 'files':\n for fr in req_v:\n fr_temp = fr.copy() # so subsequent calls don't have their minimum missing\n min_count = fr_temp.pop('minimum')\n count = 0\n for f in cont.get('files', []):\n is_satisfied, _ = check_cont(f, fr_temp)\n if 'deleted' in f or not is_satisfied:\n # Didn't find a match, on to the next one\n continue\n\n count += 1\n if count >= min_count:\n break\n\n if count < min_count:\n return False, f'Failed to find {min_count} file(s) with requirement {fr_temp} ({count} found)'\n\n else:\n is_satisfied, error = check_req(cont, req_k, req_v)\n if not is_satisfied:\n return is_satisfied, error\n return True, None","def initial_has_dependencies(tree, to_process):\r\n has_dependencies = []\r\n for n in tree.nontips(include_self=True):\r\n if n not in to_process:\r\n has_dependencies.append(n)\r\n return has_dependencies","def check_go_dependencies(self, gocat_dir):\n for d in self.dependencies:\n dep_result = subprocess.run('go list \"{}\"'.format(d), shell=True, cwd=gocat_dir,\n stdout=subprocess.PIPE, stderr=subprocess.DEVNULL)\n if (dep_result.stdout.decode()).strip() != d:\n return False\n return True","def _compute_missing_deps(self, srcs, actual_deps):\r\n def must_be_explicit_dep(dep):\r\n # We don't require explicit deps on the java runtime, so we shouldn't consider that\r\n # a missing dep.\r\n return not dep.startswith(self._context.java_home)\r\n\r\n # TODO: If recomputing these every time becomes a performance issue, memoize for\r\n # already-seen targets and incrementally compute for new targets not seen in a previous\r\n # partition, in this or a previous chunk.\r\n targets_by_file = self._compute_targets_by_file()\r\n transitive_deps_by_target = self._compute_transitive_deps_by_target()\r\n\r\n # Find deps that are actual but not specified.\r\n with self._context.new_workunit(name='scan_deps'):\r\n missing_file_deps = OrderedSet() # (src, src).\r\n missing_tgt_deps_map = defaultdict(list) # (tgt, tgt) -> a list of (src, src) as evidence.\r\n missing_direct_tgt_deps_map = defaultdict(list) # The same, but for direct deps.\r\n\r\n buildroot = get_buildroot()\r\n abs_srcs = [os.path.join(buildroot, src) for src in srcs]\r\n for src in abs_srcs:\r\n src_tgt = next(iter(targets_by_file.get(src)))\r\n if src_tgt is not None:\r\n for actual_dep in filter(must_be_explicit_dep, actual_deps.get(src, [])):\r\n actual_dep_tgts = targets_by_file.get(actual_dep)\r\n # actual_dep_tgts is usually a singleton. If it's not, we only need one of these\r\n # to be in our declared deps to be OK.\r\n if actual_dep_tgts is None:\r\n missing_file_deps.add((src_tgt, actual_dep))\r\n elif src_tgt not in actual_dep_tgts: # Obviously intra-target deps are fine.\r\n canonical_actual_dep_tgt = next(iter(actual_dep_tgts))\r\n if actual_dep_tgts.isdisjoint(transitive_deps_by_target.get(src_tgt, [])):\r\n missing_tgt_deps_map[(src_tgt, canonical_actual_dep_tgt)].append((src, actual_dep))\r\n elif canonical_actual_dep_tgt not in src_tgt.dependencies:\r\n # The canonical dep is the only one a direct dependency makes sense on.\r\n missing_direct_tgt_deps_map[(src_tgt, canonical_actual_dep_tgt)].append(\r\n (src, actual_dep))\r\n else:\r\n raise TaskError('Requested dep info for unknown source file: %s' % src)\r\n\r\n return (list(missing_file_deps),\r\n missing_tgt_deps_map.items(),\r\n missing_direct_tgt_deps_map.items())","def check_if_cycles_exist(root):\n previous = None\n queue = [root]\n while queue:\n current_node = queue.pop()\n if current_node.marked > 1:\n return not current_node.is_in_context\n\n for item in current_node.imports:\n\n # Mark the current node as parent, so that we could trace the path from this node to the start node.\n item.parent = current_node\n if item.marked and previous:\n\n # This is a possible cycle, but maybe the import statement that started this all is under the function\n # definition that is required\n import_that_started = get_import_context(item)\n for lineno, imports in previous.func_imports.items():\n for import_obj in imports:\n # Compare the function definition line with the import line\n if import_obj in item.func_defs\\\n and import_that_started > item.func_defs[import_obj]:\n item.is_in_context = True\n previous = item\n queue.append(item)\n\n current_node.marked += 1\n\n return False","def is_deps_satisfied(req_col, req_ver, collections):\n for existed_col, existed_ver in collections:\n if req_col == existed_col:\n # If there is no version constraint, return True when collection matches\n if not req_ver:\n return True\n else:\n # If there is no version in the found layer, then don't use this layer.\n if not existed_ver:\n continue\n (op, dep_version) = req_ver.split()\n success = bb.utils.vercmp_string_op(existed_ver, dep_version, op)\n if success:\n return True\n # Return False when not found\n return False","def test_get_dependencies_subgraph_by_dfs(\n self, source_node, expected_nodes_in, expected_nodes_out\n ):\n graph = nx.DiGraph()\n graph.add_node(\"pack1\")\n graph.add_node(\"pack2\")\n graph.add_node(\"pack3\")\n graph.add_node(\"pack4\")\n graph.add_edge(\"pack1\", \"pack2\")\n graph.add_edge(\"pack2\", \"pack3\")\n dfs_graph = PackDependencies.get_dependencies_subgraph_by_dfs(\n graph, source_node\n )\n for i in expected_nodes_in:\n assert i in dfs_graph.nodes()\n for i in expected_nodes_out:\n assert i not in dfs_graph.nodes()","def _get_transitive_dependencies_helper(self, target, excluded_set, accumulator, depth_limit=30):\n if depth_limit <= 0:\n raise Exception(\"Dependency depth limit exceeded, resolving: %s\" % (str(target),) )\n if target in excluded_set:\n return\n for c in self.get(target).requires:\n if c not in excluded_set:\n self._get_transitive_dependencies_helper(c, excluded_set, accumulator, depth_limit=depth_limit-1)\n accumulator.append(target)\n excluded_set.add(target)","def consistency_checker(model,universals,existentials):\n universal_set=set(universals)\n existential_set=set(existentials)\n #Additionally to the universal and existential variables the model may\n #contain additional auxiliary variables -- e.g. for setting default values.\n #We consider these variables such as the existential variables.\n auxiliary_variables_in_model={abs(l) for clause in model for l in clause \n if (not abs(l) in universal_set) and (not abs(l) in existential_set)}\n existential_set = existential_set.union(auxiliary_variables_in_model)\n result, certificate = checkModelQBF(model, universal_set, existential_set)\n return result","def dep_tree(self, root):\n \n graph = {}\n for key,extract in self.extracts.items():\n graph[key] = set(extract.get('depends',[]))\n \n def _recurse(node):\n l = set([node])\n for n in graph[node]:\n l = l | _recurse(n)\n \n return l\n \n return _recurse(root)","def find_circular_dependencies(bundleDefinitions, undeclared):\n\n logging.info(\"\\n#{0}\\nChecking for circular dependencies\".format('-'*60))\n\n circularDependencies = []\n\n for bundle in sorted(bundleDefinitions):\n\n # Don't continue with check if the bundle is already part of a circular dependency\n if not bundle_already_in_circ_dep(bundle, circularDependencies) :\n logging.info(' {0}'.format(bundle))\n dependencyPath = [bundle]\n\n for dependentBundle in bundleDefinitions[bundle]['bundle_dependency']:\n if dependentBundle not in undeclared :\n add_dependency(dependentBundle, dependencyPath, bundleDefinitions, undeclared, circularDependencies)\n if \"_CIRC_DEP_\" in dependencyPath:\n break\n dependencyPath.remove(dependentBundle)\n\n return circularDependencies","def get_dependencies(self, target, graph, dep_list):\n \n if graph == OrderedDict(): return\n if target in graph:\n dep_list.append(graph)\n return dep_list\n for key in graph:\n self.get_dependencies(target, graph[key], dep_list)\n return dep_list","def _check_c(self, constraint, *variables):\n c = {c.__class__ for c in self._layout.solver.get(*variables)}\n if constraint:\n self.assertTrue(constraint in c)\n else:\n self.assertFalse(c)","def dependency_order(self):\n seen = set()\n\n def _prune_visited(node):\n if node in seen:\n return True\n seen.add(node)\n return False\n\n for target in self.targets:\n if target in seen:\n continue\n for node in target.postorder(prune_fn=_prune_visited):\n yield node.data","def valid_dependency(self, dep):\r\n return True","def valid_tree(phi):\n q = deque([phi]) # queue of nodes to check\n visited = list() # already checked\n\n # save the indim of the root node, and make sure all the indims\n # of the children are the same\n indim = phi.indim\n retval = True\n varsfound = 0\n\n while len(q) > 0:\n # node to check\n node = q.popleft()\n\n # check outdim\n if isinstance(node, amnet.Variable):\n retval &= (node.outdim == node.indim)\n varsfound += 1\n elif isinstance(node, amnet.Linear):\n m, n = node.w.shape\n retval &= (node.outdim == m)\n retval &= (node.x.outdim == n)\n retval &= (all([bi == 0 for bi in node.b])) # check value\n elif isinstance(node, amnet.Constant):\n retval &= (node.outdim == len(node.b))\n retval &= (all([wij == 0 for wij in np.nditer(node.w)])) # check value\n elif isinstance(node, amnet.Affine):\n m, n = node.w.shape\n retval &= (node.outdim == m)\n retval &= (node.x.outdim == n)\n retval &= (m == len(node.b))\n elif isinstance(node, amnet.Mu):\n retval &= (node.outdim == node.x.outdim)\n retval &= (node.outdim == node.y.outdim)\n retval &= (node.z.outdim == 1)\n elif isinstance(node, amnet.Stack):\n retval &= (node.outdim == node.x.outdim + node.y.outdim)\n else:\n retval = False # unknown node type\n\n # check indim\n retval &= (node.indim == indim)\n\n # short-circuit if an inconsistency has been found\n if not retval:\n return False\n\n # add children to queue\n if not(any(node is e for e in visited)):\n visited.append(node)\n #q.extend(children(node))\n q.extend([c for c in children(node) if c not in visited])\n\n # finished iterating\n # TODO: also check if graph is cyclic\n return (varsfound == 1)","def check_requirements(self):\n # first, separate plugins based on those with and without dependeices.\n remaining = set()\n loaded = set()\n\n for k, v in self.modules.items():\n if v.requirements:\n remaining.add(v)\n else:\n loaded.add(k)\n self.module_call_order.append(v)\n\n for r in remaining:\n # first we check to make sure that all dependencies are satisfied.\n if not self.dependencies_satisfied(r):\n raise Exception(f\"Oops! Module {r} is not satisfied! It desires: {r.requirements}\")\n\n # now confident that all versions check out, arrange the plugins into a suitable load order.\n # no reason to do anything fancy without requirements though.\n if not remaining:\n return\n\n while True:\n new_remaining = remaining.copy()\n for m in remaining:\n if loaded.issuperset({r for r in m.requirements.keys()}):\n new_remaining.remove(m)\n loaded.add(m.name)\n self.module_call_order.append(m)\n if len(new_remaining) < len(remaining):\n # this is good.. we made progress!\n remaining = new_remaining\n if not remaining:\n # hooray! No more plugins to process\n break\n else:\n # this is bad. we are not making progress.\n raise Exception(\"dependency load order is not progressing!\")","def check_dag(self):\n self.create_dag()\n\n self.check_connected_components()\n\n self.check_for_cycles()","def validate_dependencies(self, session, entry):","def check_dependencies(work_dir, fits_dir, fitsbase):\n # Print to screen what processing steps have been selected\n print \"The following processing steps have been selected:\\n\"\n if params.do_rfifind:\n print \" - PRESTO rfifind (RFI mitigation tools)\"\n if params.do_prepsub:\n print \" - PRESTO prepsubband (dedispersion)\"\n if params.do_candsearch:\n print \" - PRESTO acceleration search and candidate sifting\"\n if params.do_presto_sp:\n print \" - PRESTO singlepulse search (singlepulse.py)\"\n # Print to screen what processing steps are being skipped\n print \"\\nThe following processing steps are being skipped:\\n\"\n if params.do_rfifind == 0:\n print \" - PRESTO rfifind (RFI mitigation tools)\"\n if params.do_prepsub == 0:\n print \" - PRESTO prepsubband (dedispersion)\"\n if params.do_candsearch == 0:\n print \" - PRESTO acceleration search and candidate sifting\"\n if params.do_presto_sp == 0:\n print \" - PRESTO singlepulse search (singlepulse.py)\"\n print \"\\nChecking dependencies...\\n\"\n # There must be at least one .fits file in the fits directory\n fl = glob(fits_dir + '/%s*.fits' %fitsbase)\n if len(fl):\n print \" Found %d file(s) in %s:\\n\" %(len(fl), fits_dir)\n for i in fl:\n print \" %s\\n\" %(i.split('/')[-1])\n else:\n print \" No %s*.fits files found in %s !\\n Exiting...\\n\" %(fitsbase, fits_dir)\n sys.exit(0)\n # If skipping the RFIFIND step in processing but want to do\n # processing steps further down the line, then there must be a\n # rfi_products folder in the results directory with a .mask file\n # in it\n if params.do_rfifind == 0 and params.use_mask and \\\n (params.do_prepsub or params.do_candsearch or params.do_presto_sp):\n mlist = glob(work_dir + '/rfi_products/*.mask')\n if len(mlist):\n print \" Using RFI .mask:\\n %s\\n\" %(mlist[0])\n else:\n print \" No RFI .mask found in %s/rfi_products!\\n Exiting...\\n\"\\\n %(work_dir)\n sys.exit(0)\n # If skipping the PREPSUBBAND step in processing but want to\n # do processing steps further down the line, then there must be\n # de-dispersed time series files in the results directory of\n # the form basename*DM*.dat and basename*DM*.inf\n if params.do_prepsub == 0 and (params.do_candsearch or \n params.do_presto_sp):\n dats = glob(work_dir + '/*DM*dat')\n infs = glob(work_dir + '/*DM*inf')\n if not (len(dats) and len(infs)):\n print \" No .dat and/or .inf files in %s!\\n Exiting...\\n\" %(work_dir)\n sys.exit(0)\n # If we haven't exited by now, then things should be good\n print \"\\nLooks good...\\n\\n\"\n # Pause for a few seconds so you can actually read the output\n time.sleep(5)","def all_DU_paths(CG, T):\n path_to_visit = []\n path_not_visited = []\n for var in CG.var:\n vert_var_in_defv=set()\n vert_var_in_refv=set()\n for vert in CG.vertices:\n if var in vert.defv:\n vert_var_in_defv.add(vert.label)\n elif var in vert.refv:\n vert_var_in_refv.add(vert.label)\n couples = product(vert_var_in_defv, vert_var_in_refv)\n for vert_def, vert_ref in couples:\n #paths_remaining = list(CG.simple_partial_paths[(vert_def, vert_ref)])\n path_to_visit += list(CG.simple_partial_paths[(vert_def, vert_ref)])\n path_not_visited += list(CG.simple_partial_paths[(vert_def, vert_ref)])\n for t in T:\n path, variables = apply_path(CG, t)\n vert_found = False\n for label in path:\n cur_vertice=find_vertice_with_label(CG,label)\n if vert_def == label:\n vert_found = True\n\n elif vert_ref == label and vert_found:\n if path in path_not_visited:\n path_not_visited.remove(path)\n break\n\n elif vert_ref != label and var in cur_vertice.refv:\n break\n #print('Test failed')\n #print(paths_remaining, var,vert_def, vert_ref, path)\n #return False\n\n #if paths_remaining:\n # print('Test failed')\n # print(paths_remaining, var, vert_def, vert_ref, path)\n # return False\n\n Graph.coverage_criteria2(path_to_visit, \"not_visited\", path_not_visited)\n if path_not_visited:\n print('Test failed')\n \n else:\n print('Test passed')\n return True","def compute_dependencies(repositories, requirement, transitive=False):\n pool = Pool(repositories)\n neighbors = _neighbors_in_repositories(pool, transitive)\n dependencies = _neighbors_for_requirement(pool, neighbors, requirement)\n return dependencies","def resolver_dependencies(pkg, db_manifest):\n print(\"[root-get] DEBUG: Resolving dependencies without DAG: direct strategy\")\n try:\n if db_manifest[pkg][\"deps\"] is not None:\n for dep in db_manifest[pkg][\"deps\"]:\n print(\"[root-get] Installing dependency \" + dep)\n if not install_dep_pkg(dep, db_manifest):\n return False\n else:\n print(\"[root-get] Dependency {0:s} is sucessfully installed and deployed\".format(dep))\n else:\n print(\"[root-get] No dependencies for {0:s} \".format(pkg))\n except:\n pass","def validate_dependence_versions():\n print('Total {} instances defined'.format(len(ReleaseInfo.all_instance_releases())))\n all_instance_releases = ReleaseInfo.all_instance_releases()\n\n # Validate dependencies: each dependence should have a valid\n # version as in defined range\n for instance_name, versions in all_instance_releases.items():\n for instance_version, release_info in versions.items():\n dependencies = release_info.dependencies\n for dep in dependencies:\n dep_type = dep.type\n minv = dep.min_version\n maxv = dep.max_version\n\n assert dep_type in all_instance_releases, \\\n \"No dependence found {} for version {} of {}\" \\\n .format(dep_type, instance_version, instance_name)\n\n found = _find_a_ranged_version(dep_type, minv=minv, maxv=maxv)\n assert found, \"No valid version defined for {} with max: {}, min: {}\" \\\n .format(dep_type, maxv, minv)","def is_allowed(self):\n if self.structure.variable_dependant_path:\n # fill in empty part of the path with the current path\n if len(self.structure.variable_dependant_path) == 3:\n dependant_var_path = (\n self.path[0],\n ) + self.structure.variable_dependant_path\n elif len(self.structure.variable_dependant_path) == 2:\n dependant_var_path = (\n self.path[0],\n self.path[1],\n ) + self.structure.variable_dependant_path\n elif len(self.structure.variable_dependant_path) == 1:\n dependant_var_path = (\n self.path[0],\n self.path[1],\n self.path[2],\n ) + self.structure.variable_dependant_path\n else:\n dependant_var_path = None\n\n # get dependency\n dependant_var = None\n mf_data = self._simulation_data.mfdata\n if dependant_var_path in mf_data:\n dependant_var = mf_data[dependant_var_path]\n\n # resolve dependency\n if self.structure.variable_value_when_active[0] == \"Exists\":\n exists = self.structure.variable_value_when_active[1]\n if dependant_var and exists.lower() == \"true\":\n return True\n elif not dependant_var and exists.lower() == \"false\":\n return True\n else:\n return False\n elif not dependant_var:\n return False\n elif self.structure.variable_value_when_active[0] == \">\":\n min_val = self.structure.variable_value_when_active[1]\n if dependant_var > float(min_val):\n return True\n else:\n return False\n elif self.structure.variable_value_when_active[0] == \"<\":\n max_val = self.structure.variable_value_when_active[1]\n if dependant_var < float(max_val):\n return True\n else:\n return False\n return True","def deps_for(nodes, key):\n\n def _deps(key, path):\n if key not in nodes:\n return [key]\n\n if key in path:\n msg = \"Cycle detected between {} and {}\".format(\n path[0], path[-1])\n raise GraphError(msg)\n\n deps = nodes[key][\"required\"]\n trans = [_deps(dep, path + [key]) for dep in deps]\n return set(util.concat(deps, *trans))\n\n return _deps(key, [])","def test_dfs():\r\n assert DFS(valid_graph, sorted(list(valid_graph.get_graph().nodes))[0]) == \\\r\n list(nx.dfs_preorder_nodes(valid_graph.get_graph(), sorted(list(valid_graph.get_graph().nodes))[0]))","def get_dependency_rules(graph, root_node=None,\n node_attrib='label', edge_attrib='label'):\n rules = set()\n\n if not root_node:\n # root node is the first element in a topological sort of the graph\n root_node = nx.topological_sort(graph)[0]\n\n for source, target in nx.dfs_edges(graph, root_node):\n rules.add( (ensure_utf8(graph.node[source].get(node_attrib, source)),\n ensure_utf8(graph[source][target].get(edge_attrib, '')),\n ensure_utf8(graph.node[target].get(node_attrib, target))) )\n return rules","def depends((a, b)):\r\n return (any(bout in a.inputs for bout in b.outputs)\r\n or any(depends((ainp.owner, b)) for ainp in a.inputs\r\n if ainp.owner))","def test_3():\n h = iotbx.pdb.input(source_info=None, lines=test_pdb_3).construct_hierarchy()\n asc = h.atom_selection_cache()\n ncs_inp = iotbx.ncs.input(\n hierarchy=h,\n params=ncs_pars.ncs_search)\n ncs_groups = ncs_inp.get_ncs_restraints_group_list()\n assert len(ncs_groups) == 1\n # group 1\n assert ncs_groups[0].master_iselection.all_eq(\n asc.selection(string = \"chain A\").iselection())\n g1_c = ncs_groups[0].copies\n assert len(g1_c)==1\n assert g1_c[0].iselection.all_eq(\n asc.selection(string = \"chain B\").iselection())","def check_dependencies():\n check_python_version()\n\n dependencies = [\"sqlite3\"]\n\n for dependency in dependencies:\n try:\n __import__(dependency)\n except ImportError as e:\n raise CuckooStartupError(\"Unable to import \\\"%s\\\"\" % dependency)\n\n return True","def test_get_all_prerequisites(self):\n c1 = content.ContentMetadata.objects.using(self.the_channel_id).get(title=\"c1\")\n root = content.ContentMetadata.objects.using(self.the_channel_id).get(title=\"root\")\n # if root is the prerequisite of c1\n expected_output = content.ContentMetadata.objects.using(self.the_channel_id).filter(title__in=[\"root\"])\n actual_output = api.get_all_prerequisites(channel_id=self.the_channel_id, content=c1)\n self.assertEqual(set(expected_output), set(actual_output))\n # then c1 should not be the prerequisite of root\n expected_output = content.ContentMetadata.objects.using(self.the_channel_id).filter(title__in=[\"c1\"])\n actual_output = api.get_all_prerequisites(channel_id=self.the_channel_id, content=root)\n self.assertNotEqual(set(actual_output), set(expected_output))","def CheckForDs(subgraphs_cnt, subgraphs_total, subgraph_loops, subgraph_dims, ds):\n for i in subgraphs_cnt.keys():\n# print\n# print i\n# print subgraphs_total, subgraph_loops\n\n if subgraphs_total[i] >= subgraph_loops[i] + 1:\n# if True:\n if subgraphs_cnt[i] >= RequiredDecompositions(subgraph_dims[i]) and i not in ds.keys():\n return i\n return None","def find_dependants_recurse(key, rev_tree, previous=None):\n if previous is None:\n previous = set()\n if not key in rev_tree:\n return []\n this_level_dependants = set(rev_tree[key])\n next_level_dependants = set()\n for dependant in this_level_dependants:\n if dependant in previous:\n continue\n tmp_previous = previous.copy()\n tmp_previous.add(dependant)\n next_level_dependants.update(\n find_dependants_recurse(dependant, rev_tree,\n previous=tmp_previous,\n ))\n # ensures reloading order on the final list\n # by postponing the reload of modules in this level\n # that also appear later on the tree\n dependants = (list(this_level_dependants.difference(\n next_level_dependants)) +\n list(next_level_dependants))\n return dependants","def buildall(target):\n if not is_acyclic(target):\n raise CircularDependency()\n\n def needsbuild(dataset):\n if dataset.exists and \\\n any(not par.exists or dataset.is_older_than(par)\n for par in dataset.parents()):\n return True, PARENTNEWER\n elif not dataset.exists:\n return True, MISSING\n else:\n return False, None\n\n def mark_children_breadthfirst(roots, parents):\n \"\"\" Mark build order for all ancestors, beginning with the roots. \"\"\"\n marks = {}\n queue = [(0, root) for root in roots]\n while len(queue) != 0:\n i, dep = queue.pop(0)\n marks[dep] = i\n for child in filter(lambda d: d in parents, dep.children(0)):\n iold = marks.get(child, -1)\n if i > iold:\n marks[child] = i\n queue.append((i+1, child))\n return marks\n\n # Map of Dataset -> integer, where the integer indicates the build step\n marks = mark_children_breadthfirst(target.roots(), set(target.parents()))\n\n groups = []\n maxi = 0\n for dep, i in marks.items():\n nb, reason = needsbuild(dep)\n if nb:\n while i >= maxi:\n groups.append([])\n maxi += 1\n groups[i].append((dep, reason))\n\n for group in groups:\n yield group\n\n if needsbuild(target)[0]:\n yield [(target, MISSING)]","def test_solve_nestedcs():\n\n import numpy as np\n from crpm.setup_nestedcs import setup_nestedcs\n from crpm.fwdprop import fwdprop\n from crpm.lossfunctions import loss\n from crpm.gradientdecent import gradientdecent\n\n #init numpy seed\n np.random.seed(40017)\n\n #setup model\n model, data = setup_nestedcs()\n\n #calculate initial mean squared error\n pred, _ = fwdprop(data[0:2,], model)\n icost, _ = loss(\"mse\", pred, data[-1,])\n #print(icost)\n\n #train model\n pred, cost, _ = gradientdecent(model, data[0:2,], data[-1,], \"mse\")\n\n #print(model)\n #print(icost)\n #print(cost)\n assert icost > cost\n assert cost < .08"],"string":"[\n \"def test_verify_dependencies(self, cond_id, conditions):\\n\\n if not cond_id in conditions.get_keys():\\n return 1\\n else:\\n result = self.verify_dependencies(cond_id)\\n return result\",\n \"def _verify_dependencies(self, cond_id, undefined_paths, current_path):\\n\\n # Exception for izpack conditions:\\n if cond_id in self.conditions.properties[WHITE_LIST]:\\n return True\\n\\n # Short-circuit on well-defined conditions:\\n if cond_id in self.well_defined:\\n return True\\n\\n # Short-circuit ill-defined conditions:\\n if cond_id in list(self.ill_defined.keys()):\\n current_path = current_path + ((cond_id, 'ill-defined condition'),)\\n undefined_paths.add(current_path)\\n return False\\n\\n # Cycle checking:\\n tup = (cond_id, 'condition')\\n if tup in current_path:\\n current_path += ((cond_id, 'cyclic condition reference'),)\\n undefined_paths.add(current_path)\\n return False\\n\\n # Check for undefined condition.\\n if not cond_id in self.conditions.get_keys():\\n tup = (cond_id, 'undefined condition')\\n current_path += (tup,)\\n undefined_paths.add(current_path)\\n return False\\n\\n current_path += (tup,)\\n condition = self.conditions.container[cond_id]\\n condition_type = condition['type']\\n\\n if condition_type in list(self.condition_tests.keys()) and not \\\\\\n self.condition_tests[condition_type](self, condition, undefined_paths, current_path):\\n return False\\n\\n self.well_defined.add(cond_id)\\n return True\",\n \"def _check_conditional_dependency(obj, condition, package, severity, msg=None):\\n if condition:\\n if msg is None:\\n msg = (\\n f\\\"The specific parameter values of {obj.__class__.__name__}'s \\\"\\n f\\\"class instance require `{package}` installed. Please run: \\\"\\n f\\\"`pip install {package}` to \\\"\\n f\\\"install the `{package}` package. \\\"\\n )\\n try:\\n _check_soft_dependencies(package, severity=severity, obj=obj)\\n except ModuleNotFoundError as e:\\n raise ModuleNotFoundError(msg) from e\",\n \"def check_deps(self):\\n\\t\\tshutit_global.shutit_global_object.yield_to_draw()\\n\\t\\tcfg = self.cfg\\n\\t\\tself.log('PHASE: dependencies', level=logging.DEBUG)\\n\\t\\tself.pause_point('\\\\nNow checking for dependencies between modules', print_input=False, level=3)\\n\\t\\t# Get modules we're going to build\\n\\t\\tto_build = [\\n\\t\\t\\tself.shutit_map[module_id] for module_id in self.shutit_map\\n\\t\\t\\tif module_id in cfg and cfg[module_id]['shutit.core.module.build']\\n\\t\\t]\\n\\t\\t# Add any deps we may need by extending to_build and altering cfg\\n\\t\\tfor module in to_build:\\n\\t\\t\\tself.resolve_dependencies(to_build, module)\\n\\n\\t\\t# Dep checking\\n\\t\\tdef err_checker(errs, triples):\\n\\t\\t\\t\\\"\\\"\\\"Collate error information.\\n\\t\\t\\t\\\"\\\"\\\"\\n\\t\\t\\tnew_triples = []\\n\\t\\t\\tfor err, triple in zip(errs, triples):\\n\\t\\t\\t\\tif not err:\\n\\t\\t\\t\\t\\tnew_triples.append(triple)\\n\\t\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\tfound_errs.append(err)\\n\\t\\t\\treturn new_triples\\n\\n\\t\\tfound_errs = []\\n\\t\\ttriples = []\\n\\t\\tfor depender in to_build:\\n\\t\\t\\tfor dependee_id in depender.depends_on:\\n\\t\\t\\t\\ttriples.append((depender, self.shutit_map.get(dependee_id), dependee_id))\\n\\n\\t\\ttriples = err_checker([ self.check_dependee_exists(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\\n\\t\\ttriples = err_checker([ self.check_dependee_build(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\\n\\t\\ttriples = err_checker([ check_dependee_order(depender, dependee, dependee_id) for depender, dependee, dependee_id in triples ], triples)\\n\\n\\t\\tif found_errs:\\n\\t\\t\\treturn [(err,) for err in found_errs]\\n\\n\\t\\tself.log('Modules configured to be built (in order) are: ', level=logging.DEBUG)\\n\\t\\tfor module_id in self.module_ids():\\n\\t\\t\\tmodule = self.shutit_map[module_id]\\n\\t\\t\\tif cfg[module_id]['shutit.core.module.build']:\\n\\t\\t\\t\\tself.log(module_id + ' ' + str(module.run_order), level=logging.DEBUG)\\n\\t\\tself.log('\\\\n', level=logging.DEBUG)\\n\\n\\t\\treturn []\",\n \"def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):\\n # Check for a matching dependency type\\n related = []\\n\\n if edge[2][\\\"dep\\\"] == dep:\\n # Check for matching POS type(s)\\n for pos_logic in dep_obj.keys():\\n connector = None\\n\\n if isinstance(dep_obj[pos_logic], dict):\\n for pos in dep_obj[pos_logic].keys():\\n\\n # Check for allowed part of speech tags in matched dependency patterns\\n if (pos_logic == \\\"pos_in\\\" and pos in G.nodes[sibling_idx][\\\"pos\\\"]) or (\\n pos_logic == \\\"pos_equals\\\" and pos == G.nodes[sibling_idx][\\\"pos\\\"]):\\n pass\\n elif pos_logic == \\\"pos_not\\\":\\n if not [False if not_pos == G.nodes[sibling_idx][\\\"pos\\\"] else True for not_pos in\\n dep_obj.keys()]: continue\\n else:\\n continue\\n\\n # if no additional checks, have a match\\n if dep_obj[pos_logic][pos] == None or any(\\n y in dep_obj[pos_logic][pos] for y in [None, \\\"add_sibling\\\"]):\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']])\\n\\n # if additional checks are required, process further\\n if dep_obj[pos_logic][pos]:\\n if \\\"get_cousin\\\" in dep_obj[pos_logic][pos]:\\n related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos][\\\"get_cousin\\\"]))\\n connector = G.nodes[sibling_idx]['word']\\n\\n if \\\"special\\\" in dep_obj[pos_logic][pos]:\\n if dep == \\\"compound\\\" and pos == \\\"NN\\\":\\n related = [G.nodes[sibling_idx]['word']]\\n\\n if None in related:\\n related.remove(None)\\n\\n # Allows for getting cousin and returning sibling\\n if \\\"else\\\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\\\"else\\\"] == \\\"always\\\":\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\\n if len(related) > 0 and isinstance(related, list):\\n for x in related:\\n if x != None:\\n all_related = _add_related(x, dep, all_related, A.index_lookup[x],\\n connector=connector)\\n elif \\\"else\\\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\\\"else\\\"] == True:\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\\n\\n return all_related\",\n \"def test_verify_all_dependencies(self):\\n\\n for condition in self.all_references():\\n result = self.verify_dependencies(condition)\\n\\n if result:\\n self.ill_defined[condition] = result\\n else:\\n self.well_defined.add(condition)\\n\\n return self.ill_defined\",\n \"def find_dependencies(root):\\n \\n symbol_table = create_symbol_table(root)\\n\\n names = []\\n #Set the depth of the root node\\n set_depth(root, 0)\\n #Stack of nodes to visit\\n stack = Stack(root)\\n \\n #List of (src, dest) of dependencies\\n dependency_table = DTable(symbol_table=symbol_table)\\n\\n for node, children, ntype in stack:\\n \\n stack.check_and_push_scope()\\n\\n #A Name is being loaded, therefore \\n if ntype == \\\"Name\\\" and is_load(children):\\n \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n dependency_table.append( (stack.scopes, node))\\n \\n elif ntype == \\\"Assign\\\":\\n #TODO need to add assignments and then revoke them\\n #for child in children:\\n #print children\\n pass\\n\\n \\n elif ntype == \\\"Attribute\\\":\\n #TODO: attribute chains can be arbitrarily long\\n #dep_dest = \\\"{}.{}\\\".format(node.value.id, node.attr)\\n #print \\\"{} => {}\\\".format(scopes_to_str(scopes), dep_dest)\\n\\n #TODO: Can't just do dependency_table.append( (scopes, node))\\n #since the unique_id function won't match the create the dep string like \\n #{node.value.id}.{node.attr}.\\n #Either generalize unique_id or something else.\\n \\n #Don't add children\\n continue\\n \\n set_lineno(node, children)\\n #Add children to stack\\n #This musn't always be performed\\n for child in children[::-1]:\\n set_depth(child, node.depth + 1)\\n stack.append(child)\\n\\n print \\\"dependency table is \\\"\\n print dependency_table\",\n \"def checkMetamodelLevel(cls):\\n for mmd in cls.metamodelDependencies():\\n mmd.check()\",\n \"def test_walk_graph(self):\\n def assertDependencyWalk(target, results, postorder=False):\\n targets = []\\n self.build_graph.walk_transitive_dependency_graph([target.address],\\n lambda x: targets.append(x),\\n postorder=postorder)\\n self.assertEquals(results, targets)\\n\\n def assertDependeeWalk(target, results, postorder=False):\\n targets = []\\n self.build_graph.walk_transitive_dependee_graph([target.address],\\n lambda x: targets.append(x),\\n postorder=postorder)\\n self.assertEquals(results, targets)\\n\\n a = self.make_target('a')\\n b = self.make_target('b', dependencies=[a])\\n c = self.make_target('c', dependencies=[b])\\n d = self.make_target('d', dependencies=[c, a])\\n e = self.make_target('e', dependencies=[d])\\n\\n assertDependencyWalk(a, [a])\\n assertDependencyWalk(b, [b, a])\\n assertDependencyWalk(c, [c, b, a])\\n assertDependencyWalk(d, [d, c, b, a])\\n assertDependencyWalk(e, [e, d, c, b, a])\\n\\n assertDependeeWalk(a, [a, b, c, d, e])\\n assertDependeeWalk(b, [b, c, d, e])\\n assertDependeeWalk(c, [c, d, e])\\n assertDependeeWalk(d, [d, e])\\n assertDependeeWalk(e, [e])\\n\\n assertDependencyWalk(a, [a], postorder=True)\\n assertDependencyWalk(b, [a, b], postorder=True)\\n assertDependencyWalk(c, [a, b, c], postorder=True)\\n assertDependencyWalk(d, [a, b, c, d], postorder=True)\\n assertDependencyWalk(e, [a, b, c, d, e], postorder=True)\\n\\n assertDependeeWalk(a, [e, d, c, b, a], postorder=True)\\n assertDependeeWalk(b, [e, d, c, b], postorder=True)\\n assertDependeeWalk(c, [e, d, c], postorder=True)\\n assertDependeeWalk(d, [e, d], postorder=True)\\n assertDependeeWalk(e, [e], postorder=True)\\n\\n #Try a case where postorder traversal is not identical to reversed preorder traversal\\n c = self.make_target('c1', dependencies=[])\\n d = self.make_target('d1', dependencies=[c])\\n b = self.make_target('b1', dependencies=[c, d])\\n e = self.make_target('e1', dependencies=[b])\\n a = self.make_target('a1', dependencies=[b, e])\\n\\n assertDependencyWalk(a, [a, b, c, d, e])\\n assertDependencyWalk(a, [c, d, b, e, a], postorder=True)\",\n \"def _check_cyclic_defaults(template: JSONDict) -> List[Error]:\\n stencil = view_by_default(template)\\n dependencies = _sections_default_dependencies(stencil)\\n # for nx we need to translate from tuples of lists to tuples of tuples\\n dependencies_hashable = [\\n (tuple(_from), tuple(_to)) for (_from, _to) in dependencies\\n ]\\n G = nx.DiGraph(dependencies_hashable)\\n cycles = nx.simple_cycles(G)\\n errors = []\\n for c in cycles:\\n errors.append(\\n Error(\\n c[0],\\n f\\\"Keyword depends cyclically on keyword {location_in_dict(address=c[1])}\\\", # noqa: E501\\n )\\n )\\n return errors\",\n \"def checkRequiredDependencies(self):\\n \\n # skip dependency check for downloading only\\n if( self.downloadOnly ):\\n return\\n\\n # hard dependencies\\n for req in self.reqmodules:\\n if( self.parent.module(req) == None ):\\n # check if there is an auto detected module\\n if( self.parent.module(req, True) == None ):\\n self.abort( self.name + \\\" requires \\\" + req \\\\\\n + \\\" and it wasn't found in your config file!!\\\" )\\n else:\\n # use auto detected module\\n self.parent.use( self.parent.module(req, True) )\\n self.parent.module( req ).init()\\n\\n print self.name + \\\": auto-detected \\\" + req + \\\" version \\\" + self.parent.module( req ).version\\n \\n # build only dependencies\\n if( self.mode == \\\"install\\\" ):\\n mods = self.reqmodules_buildonly + self.reqmodules_external\\n for req in mods:\\n if( self.parent.module(req) == None ):\\n # check if there is an auto detected module\\n if( self.parent.module(req, True) == None ):\\n self.abort( req + \\\" not found in your config file!! \\\" + self.name \\\\\\n + \\\" cannot be built without \\\" + req )\\n else:\\n # use auto detected module\\n self.parent.use( self.parent.module(req, True) )\\n self.parent.module( req ).init()\\n\\n print \\\" - \\\" + self.name + \\\": auto-detected \\\" + req + \\\" version \\\" + self.parent.module( req ).version\",\n \"def test_check_job_dependencies_prior_dependency_has_errors(database):\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=3)\\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n sess.add_all([sub, job, job_2])\\n sess.commit()\\n\\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\\n sess.add(job_dep)\\n sess.commit()\\n\\n check_job_dependencies(job.job_id)\\n\\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']\",\n \"def dependencies(self, dep_context):\\n if self.strict_deps:\\n return strict_dependencies(self.target, dep_context)\\n else:\\n return all_dependencies(self.target, dep_context)\",\n \"def check_packages(options):\\n print '\\\\033[1;33m# Checking direct VIKI dependencies\\\\033[1;m'\\n installed_ok = dependencies.check_installed_packages()\\n print '\\\\n\\\\033[1;33m# Checking second level ROS dependencies, using rosdep\\\\033[1;m'\\n second_level_ok = dependencies.get_second_level_dependencies()\\n\\n if installed_ok and second_level_ok:\\n print '\\\\033[1;32mAll dependencies satisfied!\\\\033[1;m'\\n else:\\n print '\\\\033[1;31mTry running [viki install-dependencies] to install the dependencies\\\\033[1;m'\",\n \"def testCheckDependencies(self):\\n dependencies_file = self._GetTestFilePath(['dependencies.ini'])\\n self._SkipIfPathNotExists(dependencies_file)\\n\\n dependency_helper = dependencies.DependencyHelper(\\n dependencies_file=dependencies_file)\\n\\n dependency_helper.CheckDependencies(verbose_output=False)\",\n \"def check_dependencies():\\n\\n vars_valid = check_variables(\\n AirflowVars.PROJECT_ID, AirflowVars.TERRAFORM_ORGANIZATION, AirflowVars.VM_DAGS_WATCH_LIST\\n )\\n conns_valid = check_connections(AirflowConns.TERRAFORM)\\n\\n if not vars_valid or not conns_valid:\\n raise AirflowException(\\\"Required variables or connections are missing\\\")\",\n \"def test_build_all_dependencies_graph(self, mocker):\\n\\n def mock_find_pack_dependencies(pack_id, *_, **__):\\n dependencies = {\\n \\\"pack1\\\": [(\\\"pack2\\\", True), (\\\"pack3\\\", True)],\\n \\\"pack2\\\": [(\\\"pack3\\\", True), (\\\"pack2\\\", True)],\\n \\\"pack3\\\": [],\\n \\\"pack4\\\": [(\\\"pack6\\\", False)],\\n }\\n\\n dependencies_items = {\\n \\\"pack1\\\": {\\n (\\\"type_item_a\\\", \\\"item_a\\\"): {\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n }\\n },\\n \\\"pack2\\\": {\\n (\\\"type_item_b\\\", \\\"item_b\\\"): {\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n }\\n },\\n \\\"pack3\\\": {},\\n \\\"pack4\\\": {\\n (\\\"type_item_c\\\", \\\"item_c\\\"): {\\\"pack4\\\": [(\\\"type_item_4\\\", \\\"item4\\\")]}\\n },\\n }\\n\\n return dependencies[pack_id], dependencies_items[pack_id]\\n\\n {\\n \\\"Expanse Behavior Severity Update\\\": {\\n \\\"Expanse\\\": \\\"ExpanseParseRawIncident\\\",\\n \\\"CommonScripts\\\": \\\"IsGreaterThan\\\",\\n },\\n \\\"ExpanseParseRawIncident\\\": {\\\"Expanse\\\": \\\"ExpanseParseRawIncident\\\"},\\n \\\"Expanse Appearance\\\": {\\\"Expanse\\\": \\\"incident_expanseseverity\\\"},\\n \\\"Expanse Behavior\\\": {\\\"Expanse\\\": \\\"Expanse Behavior Severity Update\\\"},\\n }\\n mocker.patch(\\n \\\"demisto_sdk.commands.find_dependencies.find_dependencies.PackDependencies._find_pack_dependencies\\\",\\n side_effect=mock_find_pack_dependencies,\\n )\\n pack_ids = [\\\"pack1\\\", \\\"pack2\\\", \\\"pack3\\\", \\\"pack4\\\"]\\n dependency_graph = PackDependencies.build_all_dependencies_graph(\\n pack_ids, {}, False\\n )\\n\\n # Asserting Dependencies (mandatory and non-mandatory)\\n assert [n for n in dependency_graph.neighbors(\\\"pack1\\\")] == [\\\"pack2\\\", \\\"pack3\\\"]\\n assert [n for n in dependency_graph.neighbors(\\\"pack2\\\")] == [\\\"pack3\\\"]\\n assert [n for n in dependency_graph.neighbors(\\\"pack3\\\")] == []\\n assert [n for n in dependency_graph.neighbors(\\\"pack4\\\")] == [\\\"pack6\\\"]\\n\\n # Asserting mandatory dependencies\\n nodes = dependency_graph.nodes(data=True)\\n\\n assert nodes[\\\"pack1\\\"][\\\"mandatory_for_packs\\\"] == []\\n assert nodes[\\\"pack1\\\"][\\\"depending_on_items_mandatorily\\\"] == {\\n (\\\"type_item_a\\\", \\\"item_a\\\"): {\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n }\\n }\\n assert nodes[\\\"pack1\\\"][\\\"depending_on_packs\\\"] == [\\n (\\\"pack2\\\", True),\\n (\\\"pack3\\\", True),\\n ]\\n assert nodes[\\\"pack1\\\"][\\\"mandatory_for_items\\\"] == {}\\n\\n assert nodes[\\\"pack2\\\"][\\\"mandatory_for_packs\\\"] == [\\\"pack1\\\"]\\n assert nodes[\\\"pack2\\\"][\\\"depending_on_items_mandatorily\\\"] == {\\n (\\\"type_item_b\\\", \\\"item_b\\\"): {\\n \\\"pack3\\\": [(\\\"type_item_3\\\", \\\"item3\\\")],\\n \\\"pack2\\\": [(\\\"type_item_2\\\", \\\"item2\\\")],\\n }\\n }\\n assert nodes[\\\"pack2\\\"][\\\"depending_on_packs\\\"] == [\\n (\\\"pack3\\\", True),\\n (\\\"pack2\\\", True),\\n ]\\n assert nodes[\\\"pack2\\\"][\\\"mandatory_for_items\\\"] == {\\n (\\\"type_item_2\\\", \\\"item2\\\"): {\\\"pack1\\\": [(\\\"type_item_a\\\", \\\"item_a\\\")]}\\n }\\n\\n assert nodes[\\\"pack3\\\"][\\\"mandatory_for_packs\\\"] == [\\\"pack1\\\", \\\"pack2\\\"]\\n assert nodes[\\\"pack3\\\"][\\\"depending_on_items_mandatorily\\\"] == {}\\n assert nodes[\\\"pack3\\\"][\\\"depending_on_packs\\\"] == []\\n assert nodes[\\\"pack3\\\"][\\\"mandatory_for_items\\\"] == {\\n (\\\"type_item_3\\\", \\\"item3\\\"): {\\n \\\"pack1\\\": [(\\\"type_item_a\\\", \\\"item_a\\\")],\\n \\\"pack2\\\": [(\\\"type_item_b\\\", \\\"item_b\\\")],\\n }\\n }\\n\\n assert nodes[\\\"pack4\\\"][\\\"mandatory_for_packs\\\"] == []\\n assert nodes[\\\"pack4\\\"][\\\"depending_on_items_mandatorily\\\"] == {\\n (\\\"type_item_c\\\", \\\"item_c\\\"): {\\\"pack4\\\": [(\\\"type_item_4\\\", \\\"item4\\\")]}\\n }\\n assert nodes[\\\"pack4\\\"][\\\"depending_on_packs\\\"] == [(\\\"pack6\\\", False)]\\n assert nodes[\\\"pack4\\\"][\\\"mandatory_for_items\\\"] == {}\\n\\n assert nodes[\\\"pack6\\\"][\\\"mandatory_for_packs\\\"] == []\\n assert nodes[\\\"pack6\\\"][\\\"depending_on_items_mandatorily\\\"] == {}\\n assert nodes[\\\"pack6\\\"][\\\"depending_on_packs\\\"] == []\\n assert nodes[\\\"pack6\\\"][\\\"mandatory_for_items\\\"] == {}\",\n \"def checkDeps( self ):\\n\\n # skip dependency check for downloading only\\n if( self.downloadOnly ):\\n return True\\n\\n # skip dependency check if package is going to be installed\\n if( self.mode == \\\"install\\\" ):\\n return True\\n\\n log.debug( 'Checking dependencies of %s', self.name )\\n \\n file = self.realPath() + \\\"/.dependencies\\\"\\n \\n r = True\\n\\n # if file doesn't exist return True\\n if( not os.path.exists( file )):\\n return True\\n\\n # open dependencies file\\n f = open( file )\\n filedeplist = {}\\n for line in f.readlines():\\n line = line.strip()\\n if( (not line.startswith(os.linesep)) and (not line.startswith(\\\"#\\\")) \\\\\\n and (len(line) > 0 )):\\n tokens = line.split(\\\":\\\")\\n filedeplist[ tokens[0] ] = tokens[1]\\n f.close()\\n\\n log.debug( 'Dependencies read from file: %s', filedeplist )\\n\\n # get actual dependecies\\n deplist={}\\n self.getDepList(deplist)\\n del deplist[self.name]\\n\\n log.debug( 'Dependencies found in current cfg file: %s', deplist )\\n \\n # compare dependencies\\n for k, v in filedeplist.iteritems():\\n if( deplist.has_key( k )):\\n if( deplist[k] != v ):\\n if( os.path.basename(deplist[k]) != os.path.basename(v) ):\\n if( r ):\\n print \\\"*** WARNING: ***\\\\n***\\\\tFollowing dependencies from \\\" + self.name + \\\" located at [ \\\" \\\\\\n + self.realPath() + \\\" ] failed:\\\\n***\\\"\\n print \\\"***\\\\t * \\\" + k + \\\" \\\" + os.path.basename(v) + \\\" differs from version \\\" \\\\\\n + os.path.basename(deplist[k]) + \\\" defined in your config file..\\\"\\n r = False\\n else:\\n if( r ): #just print this once\\n print \\\"*** WARNING: ***\\\\n***\\\\tFollowing dependencies from \\\" + self.name + \\\" located at [ \\\" + self.realPath() \\\\\\n + \\\" ] failed:\\\\n***\\\"\\n print \\\"***\\\\t * \\\" + k + \\\" not found in your config file!!\\\"\\n r = False\\n \\n\\n if( not r ):\\n print \\\"***\\\"\\n if( self.useLink ):\\n print \\\"***\\\\t\\\" + self.name + \\\" is in \\\\\\\"link\\\\\\\" mode, if you want to rebuild it with the new dependencies set it to \\\\\\\"use\\\\\\\" mode...\\\"\\n r = True\\n else:\\n if( not self.parent.noAutomaticRebuilds ):\\n print \\\"***\\\\t * \\\" + self.name + \\\" changed to \\\\\\\"install\\\\\\\" mode and rebuild flag set to True...\\\"\\n self.mode = \\\"install\\\"\\n self.rebuild = True\\n self.preCheckDeps()\\n print \\\"***\\\\n***\\\\tUpdating dependency tree ( modules that depend on \\\" + self.name + \\\" need also to be rebuilt )...\\\\n***\\\"\\n self.updateDepTree([])\\n print \\\"***\\\\n***\\\\tif you do NOT want to rebuild this module(s) just answer \\\\\\\"no\\\\\\\" later on in the installation process,\\\\n\\\" \\\\\\n + \\\"***\\\\tor set the global flag ilcsoft.noAutomaticRebuilds=True in your config file...\\\"\\n else:\\n print \\\"***\\\\n***\\\\tglobal flag ilcsoft.noAutomaticRebuilds is set to True, nothing will be done...\\\\n***\\\"\\n return r\",\n \"def XXXcheck_class_dependencies(self, node):\\n # keep track of types which are used by methods arguments\\n used_types = {}\\n for method in node[\\\"methods\\\"]:\\n self.check_function_dependencies(method, used_types)\\n\\n modules = {}\\n for typ in used_types.values():\\n if typ.f_module:\\n for mname, only in typ.f_module.items():\\n module = modules.setdefault(mname, {})\\n if only: # Empty list means no ONLY clause\\n for oname in only:\\n module[oname] = True\\n\\n # Always add C_PTR, needed for class F_derived_member\\n modules.setdefault(\\\"iso_c_binding\\\", {})[\\\"C_PTR\\\"] = True\\n\\n F_modules = [] # array of tuples ( name, (only1, only2) )\\n for mname in sorted(modules):\\n F_modules.append((mname, sorted(modules[mname])))\\n node.F_module_dependencies = F_modules\",\n \"def dependencies_satisfied(self, module) -> bool:\\n for k, v in module.requirements.items():\\n if k not in self.modules:\\n return False\\n found_ver = self.modules[k].version\\n if isinstance(v, str):\\n return found_ver == v\\n elif isinstance(v, dict):\\n if \\\"eq\\\" in v and (found_ver != v[\\\"eq\\\"]):\\n return False\\n if \\\"min\\\" in v and (found_ver < v[\\\"min\\\"]):\\n return False\\n if \\\"max\\\" in v and (found_ver > v[\\\"max\\\"]):\\n return False\\n else:\\n return True\\n return True\",\n \"def dependencies(artifact_or_id):\\n artifact = r.coerce_to_artifact(artifact_or_id)\\n visited = []\\n queue = [artifact]\\n while queue:\\n a, *queue = queue\\n\\n if a in visited:\\n continue\\n\\n visited.append(a)\\n queue.extend(_artifact_branches(a))\\n\\n visited.reverse()\\n return visited\",\n \"def checkOptionalDependencies(self):\\n \\n # skip dependency check for downloading only\\n if( self.downloadOnly ):\\n return\\n\\n # soft dependencies\\n failed = []\\n for opt in self.optmodules:\\n mod = self.parent.module(opt)\\n if( mod == None ):\\n failed.append(opt)\\n \\n # remove soft dependencies that were not found\\n self.buildWithout(failed)\",\n \"def testConditionChecking(self):\\n\\n state = State.from_problem(self.prob)\\n \\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition))\\n\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt2\\\"], self.prob):\\n self.assertFalse(state.is_satisfied(drive.precondition))\",\n \"def dependencies(self, dep_context):\\n if self.strict_deps:\\n return self.target.strict_dependencies(dep_context)\\n else:\\n return list(self.target.closure(bfs=True, **dep_context.target_closure_kwargs))\",\n \"def _check_dependency(self, tcname, depends):\\r\\n tcindex = self.tcorder.index(tcname)\\r\\n dependsindex = []\\r\\n for i in depends:\\r\\n dependsindex.append(self.tcorder.index(i))\\r\\n for i in dependsindex:\\r\\n if tcindex < i:\\r\\n msg = \\\"%s must be ordered after %s\\\\n\\\" %(tcname, self.tcorder[i])\\r\\n self.dependency.append(msg)\",\n \"def _identify_required_grads(self):\\n self.grad_expected += 1\\n if self.grad_expected == 1: # only backpropagate once from each node\\n for child in self.children:\\n child._identify_required_grads()\",\n \"def validate(self):\\n for rosdep_key in self:\\n # Ensure all dependencies have definitions\\n # i.e.: Ensure we aren't pointing to invalid rosdep keys\\n for dependency in self[rosdep_key]['dependencies']:\\n if dependency not in self:\\n raise KeyError(\\n 'Invalid Graph Structure: rosdep key `%s` does not exist in the dictionary of resolutions.'\\n % dependency)\\n self[dependency]['is_root'] = False\\n # Check each entry for cyclical dependencies\\n for rosdep_key in self:\\n self.detect_cycles(rosdep_key, [])\",\n \"def test_grandchildren():\\n\\n # note c.upto(\\\"status\\\").desired.grandchildren\\n # this is the same as *c.upto(\\\"status\\\").desired in python3.5+\\n res = conf.status.conditions.choose(lambda c: (c.type, c.reason, c.upto(\\\"status\\\").desired.grandchildren))\\n assert \\\"type\\\" in res\\n assert \\\"reason\\\" in res\\n assert \\\"version\\\" in res\\n assert \\\"image\\\" in res\\n assert \\\"force\\\" in res\",\n \"def verify_dependencies(self):\\n dependencies = {\\n \\\"manufacturers\\\": [\\n {\\\"name\\\": \\\"VMware\\\", \\\"slug\\\": \\\"vmware\\\"},\\n ],\\n \\\"platforms\\\": [\\n {\\\"name\\\": \\\"VMware ESXi\\\", \\\"slug\\\": \\\"vmware-esxi\\\"},\\n {\\\"name\\\": \\\"Windows\\\", \\\"slug\\\": \\\"windows\\\"},\\n {\\\"name\\\": \\\"Linux\\\", \\\"slug\\\": \\\"linux\\\"},\\n ],\\n \\\"sites\\\": [{\\n \\\"name\\\": \\\"vCenter\\\",\\n \\\"slug\\\": \\\"vcenter\\\",\\n \\\"comments\\\": \\\"A default virtual site created to house objects \\\"\\n \\\"that have been synced from vCenter.\\\",\\n \\\"tags\\\": [\\\"Synced\\\", \\\"vCenter\\\"]\\n }],\\n \\\"cluster_types\\\": [\\n {\\\"name\\\": \\\"VMware ESXi\\\", \\\"slug\\\": \\\"vmware-esxi\\\"}\\n ],\\n \\\"device_roles\\\": [\\n {\\n \\\"name\\\": \\\"Server\\\",\\n \\\"slug\\\": \\\"server\\\",\\n \\\"color\\\": \\\"9e9e9e\\\",\\n \\\"vm_role\\\": True\\n }],\\n \\\"tags\\\": [\\n {\\n \\\"name\\\": \\\"Orphaned\\\",\\n \\\"slug\\\": \\\"orphaned\\\",\\n \\\"color\\\": \\\"607d8b\\\",\\n \\\"comments\\\": \\\"This applies to objects that have become \\\"\\n \\\"orphaned. The source system which has \\\"\\n \\\"previously provided the object no longer \\\"\\n \\\"states it exists.{}\\\".format(\\n \\\" An object with the 'Orphaned' tag will \\\"\\n \\\"remain in this state until it ages out \\\"\\n \\\"and is automatically removed.\\\"\\n ) if settings.NB_PRUNE_ENABLED else \\\"\\\"\\n },\\n {\\n \\\"name\\\": self.vc_tag,\\n \\\"slug\\\": format_slug(self.vc_tag),\\n \\\"comments\\\": \\\"Objects synced from vCenter host \\\"\\n \\\"{}. Be careful not to modify the name or \\\"\\n \\\"slug.\\\".format(self.vc_tag)\\n }]\\n }\\n # For each dependency of each type verify object exists\\n log.info(\\\"Verifying all prerequisite objects exist in NetBox.\\\")\\n for dep_type in dependencies:\\n log.debug(\\n \\\"Checking NetBox has necessary %s objects.\\\", dep_type[:-1]\\n )\\n for dep in dependencies[dep_type]:\\n self.obj_exists(nb_obj_type=dep_type, vc_data=dep)\\n log.info(\\\"Finished verifying prerequisites.\\\")\",\n \"def test_nested():\\n res = conf.status.conditions.choose(lambda c: (c.type, c.reason, c.root.metadata.choose(lambda m: (m[\\\"name\\\"], m.uid))))\\n assert \\\"type\\\" in res # from conditions\\n assert \\\"reason\\\" in res # from conditions\\n assert \\\"name\\\" in res # from metadata\\n assert \\\"uid\\\" in res # from metadata\",\n \"def check_requirements_feasibility(self, requirements):\\n\\n subgraphs = []\\n\\n # FIXME need to fix this if there are multiple sources\\n feasibilities = []\\n for requirement in requirements:\\n visited_cells = {}\\n feasible, cs_root = self._check_requirement_feasibility(requirement.root, 0,\\n self.sources[0], visited_cells, 0)\\n feasibilities.append(feasible)\\n\\n if feasible == True:\\n subgraph = ConveyanceSubgraph(cs_root[0][1])\\n subgraphs.append(subgraph)\\n\\n print(\\\"Requirement '%s' feasibility: %r\\\" % (requirement.name,\\n feasible))\\n print()\\n\\n return feasibilities, subgraphs\",\n \"def is_dependency_subgraph(graph, subgraph_candidate,\\n node_attrib='label', edge_attrib='label'):\\n if len(subgraph_candidate) > 1:\\n if nx.is_weakly_connected(subgraph_candidate):\\n if includes_all_subgraph_rules(graph, subgraph_candidate,\\n node_attrib=node_attrib,\\n edge_attrib=edge_attrib):\\n return True\\n return False\",\n \"def make_dependence_cmp():\\r\\n\\r\\n depends = make_depends()\\r\\n\\r\\n def dependence(a, b):\\r\\n \\\"\\\"\\\" A cmp function for nodes in a graph - does a depend on b?\\r\\n\\r\\n Returns positive number if a depends on b\\r\\n Returns negative number if b depends on a\\r\\n Returns 0 otherwise\\r\\n \\\"\\\"\\\"\\r\\n if depends((a, b)):\\r\\n return 1\\r\\n if depends((b, a)):\\r\\n return -1\\r\\n return 0\\r\\n\\r\\n return dependence\",\n \"def check_prerequisites(self, env):\\n super(PassiveTracersDepth, self).check_prerequisites(env)\\n print(' Checking prerequisites for : {0}'.format(self.__class__.__name__))\",\n \"def _recurse(self, name):\\n if name in self._current:\\n state.log.fail(f\\\"Detected recursive dependency involving package '{name}'\\\")\\n else:\\n self._current.add(name)\\n if name in self.packages:\\n self._current.remove(name)\\n return self.packages[name] is not None\\n module = self._tryImport(name)\\n if module is None:\\n self.packages[name] = None\\n self._current.remove(name)\\n return False\\n for dependency in module.dependencies.get(\\\"required\\\", ()):\\n if not self._recurse(dependency):\\n # We can't configure this package because a required\\n # dependency wasn't found. But this package might itself be\\n # optional, so we don't die yet.\\n self.packages[name] = None\\n self._current.remove(name)\\n state.log.warn(\\n f\\\"Could not load all dependencies for package '{name}' (missing {dependency}).\\\"\\n )\\n return False\\n for dependency in module.dependencies.get(\\\"optional\\\", ()):\\n self._recurse(dependency)\\n # This comes last to ensure the ordering puts all dependencies first.\\n self.packages[name] = module\\n self._current.remove(name)\\n return True\",\n \"def _sufficient_deps(cls, deps):\\n if cls.MODEL_PACKAGE is None:\\n return True\\n else:\\n for d in deps.conda:\\n if cls.MODEL_PACKAGE in d:\\n return True\\n for d in deps.pip:\\n if cls.MODEL_PACKAGE in d:\\n return True\\n return False\",\n \"def dfs(i, adj_dict, edges, checked, cycle, start):\\n for vertex in adj_dict[i]:\\n pos = search_pos(i, vertex, edges, checked)\\n if pos != -1:\\n checked[pos] = True\\n if vertex[0] == start and not (False in checked):\\n cycle.append((vertex[0], i, vertex[1]))\\n return True\\n if dfs(vertex[0], adj_dict, edges, checked, cycle, start):\\n cycle.append((vertex[0], i, vertex[1]))\\n return True\\n checked[pos] = False\\n return False\",\n \"def are_all_deps_fulfilled(self, package: 'Package', only_make_check: bool = False,\\n only_depends: bool = False, print_reason: bool = False) -> bool:\\n\\n for dep in package.relevant_deps(only_make_check=only_make_check, only_depends=only_depends):\\n if not self.provided_by(dep):\\n if print_reason:\\n aurman_note(\\n \\\"Dependency {} of package {} is not fulfilled\\\".format(\\n Colors.BOLD(Colors.LIGHT_MAGENTA(dep)),\\n Colors.BOLD(Colors.LIGHT_MAGENTA(package.name))\\n )\\n )\\n return False\\n else:\\n return True\",\n \"def check_requirements(config=None):\\n for dependency, module_requirements in (\\n requirements(config, include_conditional=False).items()):\\n for module_requirement in module_requirements:\\n if \\\">=\\\" in module_requirement:\\n module_name, required_version = module_requirement.split(\\\">=\\\")\\n version_test = \\\">=\\\"\\n elif \\\"==\\\" in module_requirement:\\n module_name, required_version = module_requirement.split(\\\"==\\\")\\n version_test = \\\"==\\\"\\n else:\\n module_name = module_requirement\\n version_test = None\\n\\n try:\\n module = __import__(module_name)\\n except ImportError:\\n logging.exception(\\n \\\"Can't import %r which is part of %r\\\",\\n module_name, dependency\\n )\\n raise MissingRequirementError(\\n \\\"Can't import %r which is part of %r\\\"\\n % (module_name, dependency), module_name, dependency\\n )\\n version = getattr(module, \\\"__version__\\\", None)\\n file_path = getattr(module, \\\"__file__\\\", None)\\n logger.info(\\n \\\"Using %r version %r from %r to satisfy %r\\\",\\n module_name, version, file_path, dependency\\n )\\n\\n if version_test == \\\">=\\\":\\n if version is None:\\n raise MissingRequirementError(\\n \\\"Version of %r isn't set as __version__ of module %r\\\"\\n % (dependency, module_name), module_name, dependency\\n )\\n if LooseVersion(version) < LooseVersion(required_version):\\n raise MissingRequirementError(\\n \\\"Version of %r in %r is too old. %r < %r\\\"\\n % (dependency, file_path, version, required_version),\\n module_name, dependency\\n )\\n elif version_test == \\\"==\\\":\\n if version is None:\\n raise MissingRequirementError(\\n \\\"Version of %r isn't set as __version__ of module %r\\\"\\n % (dependency, module_name), module_name, dependency\\n )\\n if LooseVersion(version) != LooseVersion(required_version):\\n raise MissingRequirementError(\\n \\\"Unexpected version of %r in %r. %r != %r\\\"\\n % (dependency, file_path, version, required_version),\\n module_name, dependency\\n )\",\n \"def test_get_flat_dependency_tree(self):\\n with open(str(Path(__file__).parent.parent.parent) +\\n '/data/manifests/golist2.json', 'rb') as fp:\\n fs = FileStorage(stream=fp, filename='golist.json')\\n sa_post_request = StackAnalysesPostRequest(manifest=fs, file_path='/tmp/bin',\\n ecosystem='golang', show_transitive=True)\\n sa = StackAnalyses(sa_post_request)\\n sa._manifest_file_info = {\\n 'filename': sa.params.manifest.filename,\\n 'filepath': sa.params.file_path,\\n 'content': sa.params.manifest.read().decode('utf-8')\\n }\\n save_in_db, packages = sa._get_flat_dependency_tree()\\n assert isinstance(save_in_db, dict)\\n assert isinstance(save_in_db['result'], list)\\n assert isinstance(save_in_db['result'][0]['details'], list)\\n assert isinstance(save_in_db['result'][0]['details'][0], dict)\\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'], list)\\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'], list)\\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'][0], dict)\\n assert save_in_db['result'][0]['details'][0]['_resolved'][0]['package'], \\\\\\n 'github.com/thoughtworks/talisman'\\n assert save_in_db['result'][0]['details'][0]['_resolved'][0]['version'], '0.3.3'\\n assert isinstance(save_in_db['result'][0]['details'][0]['_resolved'][0]['deps'], list)\\n assert save_in_db['result'][0]['details'][0]['_resolved'][0]['deps'][0]['package'], \\\\\\n 'github.com/hashicorp/vault/vault'\\n assert isinstance(packages, list)\",\n \"def testConditionReasons(self):\\n \\n state = State.from_problem(self.prob)\\n\\n relevantVars = []\\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\\n\\n relevantVars = set(relevantVars)\\n \\n s1 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"pos1\\\"]])\\n s2 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"apt1\\\"]])\\n s3 = StateVariable(self.prob.functions[\\\"location-of\\\"][0], [self.prob[\\\"tru1\\\"]])\\n \\n self.assertEqual(len(relevantVars), 3)\\n self.assert_(s1 in relevantVars)\\n self.assert_(s2 in relevantVars)\\n self.assert_(s3 in relevantVars)\",\n \"def dep_solving(packages: Sequence['Package'], installed_system: 'System', upstream_system: 'System') -> List[\\n List['Package']]:\\n\\n deps_to_deep_check = set()\\n single_first = False\\n\\n while True:\\n current_solutions = [DepAlgoSolution([], [], set())]\\n found_problems = set()\\n\\n # calc solutions\\n # for every single package first\\n if single_first:\\n for package in packages:\\n new_solutions = []\\n for solution in current_solutions:\\n solution.dict_call_as_needed = {package.name: True}\\n new_solutions.extend(\\n package.solutions_for_dep_problem(\\n solution, found_problems, installed_system, upstream_system, deps_to_deep_check\\n )\\n )\\n current_solutions = new_solutions\\n\\n # now for all packages together\\n for solution in current_solutions:\\n solution.dict_call_as_needed = {}\\n for package in packages:\\n solution.dict_call_as_needed[package.name] = True\\n for package in packages:\\n new_solutions = []\\n for solution in current_solutions:\\n new_solutions.extend(\\n package.solutions_for_dep_problem(\\n solution, found_problems, installed_system, upstream_system, deps_to_deep_check\\n )\\n )\\n current_solutions = new_solutions\\n\\n # delete invalid solutions\\n current_solutions = [solution for solution in current_solutions if solution.is_valid]\\n\\n # in case of at least one solution, we are done\\n if current_solutions:\\n break\\n\\n deps_to_deep_check_length = len(deps_to_deep_check)\\n for problem in found_problems:\\n problem_packages_names = set([package.name for package in problem.relevant_packages])\\n deps_to_deep_check |= problem_packages_names\\n\\n # if there are no new deps to deep check, we are done, too\\n if len(deps_to_deep_check) == deps_to_deep_check_length and single_first:\\n break\\n elif len(deps_to_deep_check) == deps_to_deep_check_length:\\n if len(packages) > 1:\\n single_first = True\\n else:\\n break\\n\\n # output for user\\n if found_problems and not current_solutions:\\n aurman_error(\\n \\\"While searching for solutions the following errors occurred:\\\\n{}\\\\n\\\".format(\\n \\\"\\\\n\\\".join([aurman_note(problem, False, False) for problem in found_problems])\\n ), True\\n )\\n\\n return [solution.packages_in_solution for solution in current_solutions]\",\n \"def test_check_model_dependencies_complete(dependency_testing_model, complete_env) -> None:\\n assert check_model_dependencies(\\n model_cls=dependency_testing_model,\\n environment=complete_env,\\n raise_for_missing=False,\\n )\",\n \"def testCheckTestDependencies(self):\\n dependencies_file = self._GetTestFilePath(['dependencies.ini'])\\n self._SkipIfPathNotExists(dependencies_file)\\n\\n dependency_helper = dependencies.DependencyHelper(\\n dependencies_file=dependencies_file)\\n\\n dependency_helper.CheckTestDependencies(verbose_output=False)\",\n \"def __satisfies_necessary_and_sufficient_conditions(g):\\n # Condition 0: at least 1 Edge\\n if g.get_E() == 0:\\n return False\\n # Condition 1: indegree(v) == outdegree(v) for every vertex\\n for v in range(g.get_V()):\\n if g.outdegree() != g.indegree(v):\\n return False\\n # Condition 2: graph is connected, ignoring isolated vertices\\n h = Graph(g.get_V())\\n for v in range(g.get_V()):\\n for w in g.adj_vertices(v):\\n h.add_edge(v, w)\\n # check that all non-isolated vertices are connected\\n s = DirectedEulerianCycle.__non_isolated_vertex(g)\\n bfs = BreadthFirstPaths(h, s)\\n for v in range(g.get_V()):\\n if h.degree(v) > 0 and not bfs.has_path_to(v):\\n return False\\n return True\",\n \"def checkroot(self):\\n\\t\\tif len(self.deps) == 0:\\n\\t\\t\\treturn True\\n\\t\\trootspan = self.wordspans[self.head_pos]\\n\\t\\tfor head in self.deps:\\n\\t\\t\\tif head < rootspan[0] or head > rootspan[1]:\\n\\t\\t\\t\\treturn False\\n\\t\\t\\tfor dependent in self.deps[head]:\\n\\t\\t\\t\\tif dependent[0] < rootspan[0] or dependent[0] > rootspan[1]:\\n\\t\\t\\t\\t\\treturn False\\n\\t\\treturn True\",\n \"def check_model(self):\\n for node in self.nodes():\\n cpd = self.get_cpds(node=node)\\n\\n if cpd is None:\\n raise ValueError(\\\"No CPD associated with {}\\\".format(node))\\n elif isinstance(cpd, (TabularCPD, ContinuousFactor)):\\n evidence = cpd.get_evidence()\\n parents = self.get_parents(node)\\n if set(evidence if evidence else []) != set(parents if parents else []):\\n raise ValueError(\\n \\\"CPD associated with {node} doesn't have \\\"\\n \\\"proper parents associated with it.\\\".format(node=node)\\n )\\n if not cpd.is_valid_cpd():\\n raise ValueError(\\n \\\"Sum or integral of conditional probabilites for node {node}\\\"\\n \\\" is not equal to 1.\\\".format(node=node)\\n )\\n return True\",\n \"def __dependency_traverse(self, v, visited, results):\\n if v in visited:\\n return\\n visited.add(v)\\n # Create list of input data\\n data = []\\n for p in v.predecessors():\\n # Traverse dependencies that have not been visited yet\\n self.__dependency_traverse(p, visited, results)\\n data.append(results[p])\\n data = data[0] if len(data) == 1 else data\\n # Flatten list of input data if there is only one element\\n results[v] = self.traverse_vertex(v, data)\\n # Traverse transforms that require this dependency and have not been visited\\n for n in v.successors():\\n self.__dependency_traverse(n, visited, results)\",\n \"def check_flow_conditions(triple, fwd, rev, overlap):\\n\\n p1, p2, p3 = [self.paths[triple[x]] for x in [0,1,2]]\\n p2_end_index = len(p2) - rev + overlap\\n #print(\\\"p2_end_index = {}\\\".format(p2_end_index))\\n p1_start_index = fwd + 1\\n #print(\\\"p1_start_index = {}\\\".format(p1_start_index))\\n #print(\\\"p1 subset: {}\\\".format(p1[p1_start_index - 1:]))\\n #print(\\\"p2 subset = {}\\\".format(p2[:p2_end_index]))\\n p_prime = p2[:p2_end_index] + p1[p1_start_index - 1:]\\n #print(\\\"p_prime = {}\\\".format(p_prime))\\n\\n # try to rebalance\\n if flow_condition(p1, p2, triple):\\n print(\\\"Rebalance opportunity found. Now rebalancing.\\\")\\n self.rebalances += 1\\n return(True)\\n\\n # try to splice and merge\\n if flow_condition(p_prime, p3, triple):\\n print(\\\"Splice+merge opportunity found. Now splicing.\\\")\\n self.splices += 1\\n return(True)\\n\\n return(False)\",\n \"def _resolve_dependencies(self):\\n matching_versions = dict()\\n\\n # Initialization of the BFS\\n bfs_stack = list()\\n for requirement_name, spec_str in sorted(self.spec_requirements, key=lambda x: x[0].lower()):\\n self._add_spec(requirement_name, spec_str)\\n bfs_stack.append(requirement_name)\\n\\n # Main loop\\n while bfs_stack:\\n # Stack Unwind\\n requirement_name = bfs_stack.pop(0)\\n available_versions = self._get_available_versions(requirement_name)\\n spec = self._get_spec(requirement_name)\\n best_matching_version = spec.select(available_versions)\\n if best_matching_version is None:\\n msg = 'Unmatched dependency for {}\\\\nSpecification requirement: {}\\\\nAvailable versions: {}\\\\n' \\\\\\n 'Use NPM semver calculator to resolve: https://semver.npmjs.com/'\\n error = msg.format(requirement_name, spec, ', '.join(reversed(map(str, available_versions))))\\n raise RequirementMatchError(error)\\n\\n matching_versions[requirement_name] = best_matching_version\\n\\n # BFS stack population with dependencies\\n dependencies = self._get_dependencies(requirement_name, best_matching_version)\\n for dependency_name, dependency_version in dependencies:\\n self._add_spec(dependency_name, dependency_version)\\n bfs_stack.append(dependency_name)\\n\\n return matching_versions\",\n \"def check_dependencies(cls):\\n\\n missing = []\\n for name in cls.DEPENDENCIES:\\n try:\\n import_module(name)\\n except ModuleNotFoundError:\\n missing.append(name)\\n\\n if any(missing):\\n msg = ('The sup3r stitching module depends on the following '\\n 'special dependencies that were not found in the active '\\n 'environment: {}'.format(missing))\\n logger.error(msg)\\n raise ModuleNotFoundError(msg)\",\n \"def check_feasibility(nodes, edges, T, I, S, S_out):\\n # 1. All nodes are end ancestors\\n def isAncestor(start, node):\\n marked[node] = True\\n try: successors = I[node]\\n except: successors = []\\n if 'end' in successors:\\n end_ancestor[start] = True\\n if not end_ancestor[start]:\\n for successor in successors:\\n if not marked[successor]:\\n isAncestor(start, successor)\\n\\n # 2. All nodes are start descendants\\n def isDescendant(node):\\n start_descendant[node] = True\\n try: successors = I[node]\\n except: successors = []\\n for successor in successors:\\n if successor != 'end' and start_descendant[successor] == False:\\n isDescendant(successor)\\n \\n # Find extra edges if condition fails.\\n def make_connected(edges, state, check_cond='desc'):\\n component_nodes = [k for k, v in state.items() if v == False]\\n directed_nodes = [k for k, v in state.items() if v == True]\\n source = directed_nodes if check_cond == 'desc' else component_nodes\\n target = component_nodes if check_cond == 'desc' else directed_nodes\\n extra_edges = dict()\\n for node in source:\\n for a in T[node]:\\n if a in target:\\n extra_edges[(node, a)] = S_out[node][a]\\n if len(extra_edges) == 0:\\n S_comp = {k: v for k, v in S.items() if k in component_nodes}\\n if check_cond == 'desc':\\n edges.append(('start', max(S_comp, key=S_comp.get)))\\n if 'start' not in I:\\n I['start'] = dict()\\n I['start'][max(S_comp, key=S_comp.get)] = 1\\n else:\\n edges.append((max(S_comp, key=S_comp.get), 'end'))\\n if max(S_comp, key=S_comp.get) not in I:\\n I[max(S_comp, key=S_comp.get)] = dict()\\n I[max(S_comp, key=S_comp.get)]['end'] = 1\\n else:\\n extra_edge = max(extra_edges, key=extra_edges.get)\\n edges.append((extra_edge[0], extra_edge[1]))\\n if extra_edge[0] not in I:\\n I[extra_edge[0]] = dict()\\n I[extra_edge[0]][extra_edge[1]] = 1\\n\\n while True:\\n end_ancestor = dict.fromkeys(nodes, False)\\n for v in nodes:\\n marked = dict.fromkeys(nodes, False)\\n isAncestor(v, v)\\n if all(end_ancestor.values()): break\\n else: make_connected(edges, end_ancestor, 'anc')\\n\\n while True:\\n start_descendant = dict.fromkeys(nodes, False)\\n isDescendant('start')\\n if all(start_descendant.values()): break\\n else: make_connected(edges, start_descendant, 'desc')\",\n \"def test_check_job_dependencies_has_unfinished_dependencies(database):\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=0)\\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n job_3 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=0)\\n sess.add_all([sub, job, job_2, job_3])\\n sess.commit()\\n\\n # Job 1 finished, it is a prerequisite for job 2 (waiting)\\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\\n # Job 3 is also a prerequisite of job 2, it's not done, job 2 should stay in \\\"waiting\\\"\\n job_dep_2 = JobDependency(job_id=job_2.job_id, prerequisite_id=job_3.job_id)\\n sess.add_all([job_dep, job_dep_2])\\n sess.commit()\\n\\n check_job_dependencies(job.job_id)\\n\\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']\",\n \"def _check_family(self):\\n for (s, (b, c)), (cond, ref) in families.items():\\n if s != self.SYMBOL or len(b) != self._.d:\\n continue\\n vars = tuple(set(sum(map(variables, b + c), ())))\\n sols = _solve([SR(l) == r for l, r\\n in zip(self._.b[:-1] + self._.c[1:], b + c)],\\n vars)\\n if any(checkConditions(cond, sol) for sol in sols\\n if is_integral(sol)):\\n raise InfeasibleError(refs=ref)\",\n \"def depthFirstSearch(problem):\\n \\\"*** YOUR CODE HERE ***\\\"\\n \\n util.raiseNotDefined()\",\n \"def depthFirstSearch(problem):\\n \\\"*** YOUR CODE HERE ***\\\"\\n util.raiseNotDefined()\",\n \"def _contains_cycle(fgraph, orderings):\\r\\n\\r\\n # These are lists of Variable instances\\r\\n inputs = fgraph.inputs\\r\\n outputs = fgraph.outputs\\r\\n\\r\\n\\r\\n # this is hard-coded reimplementation of functions from graph.py\\r\\n # reason: go faster, prepare for port to C.\\r\\n # specifically, it could be replaced with a wrapper\\r\\n # around graph.io_toposort that returns True iff io_toposort raises\\r\\n # a ValueError containing the substring 'cycle'.\\r\\n # This implementation is optimized for the destroyhandler and runs\\r\\n # slightly faster than io_toposort.\\r\\n\\r\\n # this is performance-critical code. it is the largest single-function\\r\\n # bottleneck when compiling large graphs.\\r\\n\\r\\n assert isinstance(outputs, (tuple, list, deque))\\r\\n\\r\\n # TODO: For more speed - use a defaultdict for the orderings\\r\\n # (defaultdict runs faster than dict in the case where the key\\r\\n # is not in the dictionary, at least in CPython)\\r\\n\\r\\n iset = set(inputs)\\r\\n\\r\\n # IG: I tried converting parent_counts to use an id for the key,\\r\\n # so that the dict would do reference counting on its keys.\\r\\n # This caused a slowdown.\\r\\n # Separate benchmark tests showed that calling id is about\\r\\n # half as expensive as a dictionary access, and that the\\r\\n # dictionary also runs slower when storing ids than when\\r\\n # storing objects.\\r\\n\\r\\n\\r\\n # dict mapping an Apply or Variable instance to the number\\r\\n # of its parents (including parents imposed by orderings)\\r\\n # that haven't been visited yet\\r\\n parent_counts = {}\\r\\n # dict mapping an Apply or Variable instance to its children\\r\\n node_to_children = {}\\r\\n\\r\\n # visitable: A container holding all Variable and Apply instances\\r\\n # that can currently be visited according to the graph topology\\r\\n # (ie, whose parents have already been visited)\\r\\n # TODO: visitable is a fifo_queue. could this run faster if we\\r\\n # implement it as a stack rather than a deque?\\r\\n # TODO: visitable need not be a fifo_queue, any kind of container\\r\\n # that we can throw things into and take things out of quickly will\\r\\n # work. is there another kind of container that could run faster?\\r\\n # we don't care about the traversal order here as much as we do\\r\\n # in io_toposort because we aren't trying to generate an ordering\\r\\n # on the nodes\\r\\n visitable = deque()\\r\\n\\r\\n # IG: visitable could in principle be initialized to fgraph.inputs\\r\\n # + fgraph.orphans... if there were an fgraph.orphans structure.\\r\\n # I tried making one and maintaining it caused a huge slowdown.\\r\\n # This may be because I made it a list, so it would have a\\r\\n # deterministic iteration order, in hopes of using it to speed\\r\\n # up toposort as well.\\r\\n # I think since we need to scan through all variables and nodes\\r\\n # to make parent_counts anyway, it's cheap enough to always\\r\\n # detect orphans at cycle detection / toposort time\\r\\n\\r\\n\\r\\n # Pass through all the nodes to build visitable, parent_count, and\\r\\n # node_to_children\\r\\n for var in fgraph.variables:\\r\\n\\r\\n # this is faster than calling get_parents\\r\\n owner = var.owner\\r\\n if owner:\\r\\n parents = [ owner ]\\r\\n else:\\r\\n parents = []\\r\\n\\r\\n # variables don't appear in orderings, so we don't need to worry\\r\\n # about that here\\r\\n\\r\\n if parents:\\r\\n for parent in parents:\\r\\n # insert node in node_to_children[r]\\r\\n # (if r is not already in node_to_children,\\r\\n # intialize it to [])\\r\\n node_to_children.setdefault(parent, []).append(var)\\r\\n parent_counts[var] = len(parents)\\r\\n else:\\r\\n visitable.append(var)\\r\\n parent_counts[var] = 0\\r\\n\\r\\n for a_n in fgraph.apply_nodes:\\r\\n parents = list(a_n.inputs)\\r\\n # This is faster than conditionally extending\\r\\n # IG: I tried using a shared empty_list = [] constructed\\r\\n # outside of the for loop to avoid constructing multiple\\r\\n # lists, but this was not any faster.\\r\\n parents.extend(orderings.get(a_n, []))\\r\\n\\r\\n if parents:\\r\\n for parent in parents:\\r\\n # insert node in node_to_children[r]\\r\\n # (if r is not already in node_to_children,\\r\\n # intialize it to [])\\r\\n node_to_children.setdefault(parent, []).append(a_n)\\r\\n parent_counts[a_n] = len(parents)\\r\\n else:\\r\\n # an Apply with no inputs would be a weird case, but I'm\\r\\n # not sure we forbid it\\r\\n visitable.append(a_n)\\r\\n parent_counts[a_n] = 0\\r\\n\\r\\n # at this point,\\r\\n # parent_counts.keys() == fgraph.apply_nodes + fgraph.variables\\r\\n\\r\\n\\r\\n\\r\\n # Now we actually check for cycles\\r\\n # As long as there are nodes that can be visited while respecting\\r\\n # the topology, we keep visiting nodes\\r\\n # If we run out of visitable nodes and we haven't visited all nodes,\\r\\n # then there was a cycle. It blocked the traversal because some\\r\\n # node couldn't be visited until one of its descendants had been\\r\\n # visited too.\\r\\n # This is a standard cycle detection algorithm.\\r\\n\\r\\n visited = 0\\r\\n while visitable:\\r\\n # Since each node is inserted into the visitable queue exactly\\r\\n # once, it comes out of the queue exactly once\\r\\n # That means we can decrement its children's unvisited parent count\\r\\n # and increment the visited node count without double-counting\\r\\n node = visitable.popleft()\\r\\n visited += 1\\r\\n for client in node_to_children.get(node,[]):\\r\\n parent_counts[client] -= 1\\r\\n # If all of a node's parents have been visited,\\r\\n # it may now be visited too\\r\\n if not parent_counts[client]:\\r\\n visitable.append(client)\\r\\n\\r\\n\\r\\n return visited != len(parent_counts)\",\n \"def validate(self, fgraph):\\r\\n\\r\\n if self.destroyers:\\r\\n ords = self.orderings(fgraph)\\r\\n\\r\\n if _contains_cycle(fgraph, ords):\\r\\n raise InconsistencyError(\\\"Dependency graph contains cycles\\\")\\r\\n else:\\r\\n #James's Conjecture:\\r\\n #If there are no destructive ops, then there can be no cycles.\\r\\n pass\\r\\n return True\",\n \"def validate(self, fgraph):\\r\\n\\r\\n if self.destroyers:\\r\\n ords = self.orderings(fgraph)\\r\\n\\r\\n if _contains_cycle(fgraph, ords):\\r\\n raise InconsistencyError(\\\"Dependency graph contains cycles\\\")\\r\\n else:\\r\\n #James's Conjecture:\\r\\n #If there are no destructive ops, then there can be no cycles.\\r\\n pass\\r\\n return True\",\n \"def check(self, srcs, actual_deps):\\r\\n if self._check_missing_deps or self._check_missing_direct_deps or self._check_unnecessary_deps:\\r\\n missing_file_deps, missing_tgt_deps, missing_direct_tgt_deps = \\\\\\r\\n self._compute_missing_deps(srcs, actual_deps)\\r\\n\\r\\n buildroot = get_buildroot()\\r\\n def shorten(path): # Make the output easier to read.\\r\\n for prefix in [buildroot, self._context.ivy_home]:\\r\\n if path.startswith(prefix):\\r\\n return os.path.relpath(path, prefix)\\r\\n return path\\r\\n\\r\\n if self._check_missing_deps and (missing_file_deps or missing_tgt_deps):\\r\\n for (tgt_pair, evidence) in missing_tgt_deps:\\r\\n evidence_str = '\\\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\\r\\n for e in evidence])\\r\\n self._context.log.error(\\r\\n 'Missing BUILD dependency %s -> %s because:\\\\n%s'\\r\\n % (tgt_pair[0].address.reference(), tgt_pair[1].address.reference(), evidence_str))\\r\\n for (src_tgt, dep) in missing_file_deps:\\r\\n self._context.log.error('Missing BUILD dependency %s -> %s'\\r\\n % (src_tgt.address.reference(), shorten(dep)))\\r\\n if self._check_missing_deps == 'fatal':\\r\\n raise TaskError('Missing deps.')\\r\\n\\r\\n if self._check_missing_direct_deps:\\r\\n for (tgt_pair, evidence) in missing_direct_tgt_deps:\\r\\n evidence_str = '\\\\n'.join([' %s uses %s' % (shorten(e[0]), shorten(e[1]))\\r\\n for e in evidence])\\r\\n self._context.log.warn('Missing direct BUILD dependency %s -> %s because:\\\\n%s' %\\r\\n (tgt_pair[0].address, tgt_pair[1].address, evidence_str))\\r\\n if self._check_missing_direct_deps == 'fatal':\\r\\n raise TaskError('Missing direct deps.')\\r\\n\\r\\n if self._check_unnecessary_deps:\\r\\n raise TaskError('Unnecessary dep warnings not implemented yet.')\",\n \"def check_dependencies(target_binary, target_platform, target_architecture, target_type):\\n check_architecture(target_architecture)\\n check_platform(target_platform)\",\n \"def condition(*args, delete: bool=True, dependency: Union[AnyStr, List[AnyStr]]=\\\"\\\", initialize:\\n bool=True, script: AnyStr=\\\"\\\", state: bool=True, q=True, query=True, e=True,\\n edit=True, **kwargs)->Union[None, Any]:\\n pass\",\n \"def check_dag_acyclic(self, start, inputs):\\n for binding in inputs.values():\\n if start == binding.io_owner:\\n return False\\n for p in binding.parents:\\n if not self.check_dag_acyclic(start, p.io_owner.input_bindings.bindings):\\n return False\\n\\n return True\",\n \"def is_order_constrained(paths, constraints, j, k):\\r\\n for q in range(j, k):\\r\\n # search between j and k.\\r\\n first_path = paths[q]\\r\\n for constraint in constraints:\\r\\n if first_path is not constraint[0]:\\r\\n # Constraint does not apply to the value at q.\\r\\n continue\\r\\n for m in range(q + 1, k):\\r\\n second_path = paths[m]\\r\\n if second_path is constraint[1]:\\r\\n # Constraint demands the order must be first_path then second_path.\\r\\n return True\\r\\n return False\",\n \"def check_cont(cont, reqs):\\n for req_k, req_v in reqs.items():\\n if req_k == 'files':\\n for fr in req_v:\\n fr_temp = fr.copy() # so subsequent calls don't have their minimum missing\\n min_count = fr_temp.pop('minimum')\\n count = 0\\n for f in cont.get('files', []):\\n is_satisfied, _ = check_cont(f, fr_temp)\\n if 'deleted' in f or not is_satisfied:\\n # Didn't find a match, on to the next one\\n continue\\n\\n count += 1\\n if count >= min_count:\\n break\\n\\n if count < min_count:\\n return False, f'Failed to find {min_count} file(s) with requirement {fr_temp} ({count} found)'\\n\\n else:\\n is_satisfied, error = check_req(cont, req_k, req_v)\\n if not is_satisfied:\\n return is_satisfied, error\\n return True, None\",\n \"def initial_has_dependencies(tree, to_process):\\r\\n has_dependencies = []\\r\\n for n in tree.nontips(include_self=True):\\r\\n if n not in to_process:\\r\\n has_dependencies.append(n)\\r\\n return has_dependencies\",\n \"def check_go_dependencies(self, gocat_dir):\\n for d in self.dependencies:\\n dep_result = subprocess.run('go list \\\"{}\\\"'.format(d), shell=True, cwd=gocat_dir,\\n stdout=subprocess.PIPE, stderr=subprocess.DEVNULL)\\n if (dep_result.stdout.decode()).strip() != d:\\n return False\\n return True\",\n \"def _compute_missing_deps(self, srcs, actual_deps):\\r\\n def must_be_explicit_dep(dep):\\r\\n # We don't require explicit deps on the java runtime, so we shouldn't consider that\\r\\n # a missing dep.\\r\\n return not dep.startswith(self._context.java_home)\\r\\n\\r\\n # TODO: If recomputing these every time becomes a performance issue, memoize for\\r\\n # already-seen targets and incrementally compute for new targets not seen in a previous\\r\\n # partition, in this or a previous chunk.\\r\\n targets_by_file = self._compute_targets_by_file()\\r\\n transitive_deps_by_target = self._compute_transitive_deps_by_target()\\r\\n\\r\\n # Find deps that are actual but not specified.\\r\\n with self._context.new_workunit(name='scan_deps'):\\r\\n missing_file_deps = OrderedSet() # (src, src).\\r\\n missing_tgt_deps_map = defaultdict(list) # (tgt, tgt) -> a list of (src, src) as evidence.\\r\\n missing_direct_tgt_deps_map = defaultdict(list) # The same, but for direct deps.\\r\\n\\r\\n buildroot = get_buildroot()\\r\\n abs_srcs = [os.path.join(buildroot, src) for src in srcs]\\r\\n for src in abs_srcs:\\r\\n src_tgt = next(iter(targets_by_file.get(src)))\\r\\n if src_tgt is not None:\\r\\n for actual_dep in filter(must_be_explicit_dep, actual_deps.get(src, [])):\\r\\n actual_dep_tgts = targets_by_file.get(actual_dep)\\r\\n # actual_dep_tgts is usually a singleton. If it's not, we only need one of these\\r\\n # to be in our declared deps to be OK.\\r\\n if actual_dep_tgts is None:\\r\\n missing_file_deps.add((src_tgt, actual_dep))\\r\\n elif src_tgt not in actual_dep_tgts: # Obviously intra-target deps are fine.\\r\\n canonical_actual_dep_tgt = next(iter(actual_dep_tgts))\\r\\n if actual_dep_tgts.isdisjoint(transitive_deps_by_target.get(src_tgt, [])):\\r\\n missing_tgt_deps_map[(src_tgt, canonical_actual_dep_tgt)].append((src, actual_dep))\\r\\n elif canonical_actual_dep_tgt not in src_tgt.dependencies:\\r\\n # The canonical dep is the only one a direct dependency makes sense on.\\r\\n missing_direct_tgt_deps_map[(src_tgt, canonical_actual_dep_tgt)].append(\\r\\n (src, actual_dep))\\r\\n else:\\r\\n raise TaskError('Requested dep info for unknown source file: %s' % src)\\r\\n\\r\\n return (list(missing_file_deps),\\r\\n missing_tgt_deps_map.items(),\\r\\n missing_direct_tgt_deps_map.items())\",\n \"def check_if_cycles_exist(root):\\n previous = None\\n queue = [root]\\n while queue:\\n current_node = queue.pop()\\n if current_node.marked > 1:\\n return not current_node.is_in_context\\n\\n for item in current_node.imports:\\n\\n # Mark the current node as parent, so that we could trace the path from this node to the start node.\\n item.parent = current_node\\n if item.marked and previous:\\n\\n # This is a possible cycle, but maybe the import statement that started this all is under the function\\n # definition that is required\\n import_that_started = get_import_context(item)\\n for lineno, imports in previous.func_imports.items():\\n for import_obj in imports:\\n # Compare the function definition line with the import line\\n if import_obj in item.func_defs\\\\\\n and import_that_started > item.func_defs[import_obj]:\\n item.is_in_context = True\\n previous = item\\n queue.append(item)\\n\\n current_node.marked += 1\\n\\n return False\",\n \"def is_deps_satisfied(req_col, req_ver, collections):\\n for existed_col, existed_ver in collections:\\n if req_col == existed_col:\\n # If there is no version constraint, return True when collection matches\\n if not req_ver:\\n return True\\n else:\\n # If there is no version in the found layer, then don't use this layer.\\n if not existed_ver:\\n continue\\n (op, dep_version) = req_ver.split()\\n success = bb.utils.vercmp_string_op(existed_ver, dep_version, op)\\n if success:\\n return True\\n # Return False when not found\\n return False\",\n \"def test_get_dependencies_subgraph_by_dfs(\\n self, source_node, expected_nodes_in, expected_nodes_out\\n ):\\n graph = nx.DiGraph()\\n graph.add_node(\\\"pack1\\\")\\n graph.add_node(\\\"pack2\\\")\\n graph.add_node(\\\"pack3\\\")\\n graph.add_node(\\\"pack4\\\")\\n graph.add_edge(\\\"pack1\\\", \\\"pack2\\\")\\n graph.add_edge(\\\"pack2\\\", \\\"pack3\\\")\\n dfs_graph = PackDependencies.get_dependencies_subgraph_by_dfs(\\n graph, source_node\\n )\\n for i in expected_nodes_in:\\n assert i in dfs_graph.nodes()\\n for i in expected_nodes_out:\\n assert i not in dfs_graph.nodes()\",\n \"def _get_transitive_dependencies_helper(self, target, excluded_set, accumulator, depth_limit=30):\\n if depth_limit <= 0:\\n raise Exception(\\\"Dependency depth limit exceeded, resolving: %s\\\" % (str(target),) )\\n if target in excluded_set:\\n return\\n for c in self.get(target).requires:\\n if c not in excluded_set:\\n self._get_transitive_dependencies_helper(c, excluded_set, accumulator, depth_limit=depth_limit-1)\\n accumulator.append(target)\\n excluded_set.add(target)\",\n \"def consistency_checker(model,universals,existentials):\\n universal_set=set(universals)\\n existential_set=set(existentials)\\n #Additionally to the universal and existential variables the model may\\n #contain additional auxiliary variables -- e.g. for setting default values.\\n #We consider these variables such as the existential variables.\\n auxiliary_variables_in_model={abs(l) for clause in model for l in clause \\n if (not abs(l) in universal_set) and (not abs(l) in existential_set)}\\n existential_set = existential_set.union(auxiliary_variables_in_model)\\n result, certificate = checkModelQBF(model, universal_set, existential_set)\\n return result\",\n \"def dep_tree(self, root):\\n \\n graph = {}\\n for key,extract in self.extracts.items():\\n graph[key] = set(extract.get('depends',[]))\\n \\n def _recurse(node):\\n l = set([node])\\n for n in graph[node]:\\n l = l | _recurse(n)\\n \\n return l\\n \\n return _recurse(root)\",\n \"def find_circular_dependencies(bundleDefinitions, undeclared):\\n\\n logging.info(\\\"\\\\n#{0}\\\\nChecking for circular dependencies\\\".format('-'*60))\\n\\n circularDependencies = []\\n\\n for bundle in sorted(bundleDefinitions):\\n\\n # Don't continue with check if the bundle is already part of a circular dependency\\n if not bundle_already_in_circ_dep(bundle, circularDependencies) :\\n logging.info(' {0}'.format(bundle))\\n dependencyPath = [bundle]\\n\\n for dependentBundle in bundleDefinitions[bundle]['bundle_dependency']:\\n if dependentBundle not in undeclared :\\n add_dependency(dependentBundle, dependencyPath, bundleDefinitions, undeclared, circularDependencies)\\n if \\\"_CIRC_DEP_\\\" in dependencyPath:\\n break\\n dependencyPath.remove(dependentBundle)\\n\\n return circularDependencies\",\n \"def get_dependencies(self, target, graph, dep_list):\\n \\n if graph == OrderedDict(): return\\n if target in graph:\\n dep_list.append(graph)\\n return dep_list\\n for key in graph:\\n self.get_dependencies(target, graph[key], dep_list)\\n return dep_list\",\n \"def _check_c(self, constraint, *variables):\\n c = {c.__class__ for c in self._layout.solver.get(*variables)}\\n if constraint:\\n self.assertTrue(constraint in c)\\n else:\\n self.assertFalse(c)\",\n \"def dependency_order(self):\\n seen = set()\\n\\n def _prune_visited(node):\\n if node in seen:\\n return True\\n seen.add(node)\\n return False\\n\\n for target in self.targets:\\n if target in seen:\\n continue\\n for node in target.postorder(prune_fn=_prune_visited):\\n yield node.data\",\n \"def valid_dependency(self, dep):\\r\\n return True\",\n \"def valid_tree(phi):\\n q = deque([phi]) # queue of nodes to check\\n visited = list() # already checked\\n\\n # save the indim of the root node, and make sure all the indims\\n # of the children are the same\\n indim = phi.indim\\n retval = True\\n varsfound = 0\\n\\n while len(q) > 0:\\n # node to check\\n node = q.popleft()\\n\\n # check outdim\\n if isinstance(node, amnet.Variable):\\n retval &= (node.outdim == node.indim)\\n varsfound += 1\\n elif isinstance(node, amnet.Linear):\\n m, n = node.w.shape\\n retval &= (node.outdim == m)\\n retval &= (node.x.outdim == n)\\n retval &= (all([bi == 0 for bi in node.b])) # check value\\n elif isinstance(node, amnet.Constant):\\n retval &= (node.outdim == len(node.b))\\n retval &= (all([wij == 0 for wij in np.nditer(node.w)])) # check value\\n elif isinstance(node, amnet.Affine):\\n m, n = node.w.shape\\n retval &= (node.outdim == m)\\n retval &= (node.x.outdim == n)\\n retval &= (m == len(node.b))\\n elif isinstance(node, amnet.Mu):\\n retval &= (node.outdim == node.x.outdim)\\n retval &= (node.outdim == node.y.outdim)\\n retval &= (node.z.outdim == 1)\\n elif isinstance(node, amnet.Stack):\\n retval &= (node.outdim == node.x.outdim + node.y.outdim)\\n else:\\n retval = False # unknown node type\\n\\n # check indim\\n retval &= (node.indim == indim)\\n\\n # short-circuit if an inconsistency has been found\\n if not retval:\\n return False\\n\\n # add children to queue\\n if not(any(node is e for e in visited)):\\n visited.append(node)\\n #q.extend(children(node))\\n q.extend([c for c in children(node) if c not in visited])\\n\\n # finished iterating\\n # TODO: also check if graph is cyclic\\n return (varsfound == 1)\",\n \"def check_requirements(self):\\n # first, separate plugins based on those with and without dependeices.\\n remaining = set()\\n loaded = set()\\n\\n for k, v in self.modules.items():\\n if v.requirements:\\n remaining.add(v)\\n else:\\n loaded.add(k)\\n self.module_call_order.append(v)\\n\\n for r in remaining:\\n # first we check to make sure that all dependencies are satisfied.\\n if not self.dependencies_satisfied(r):\\n raise Exception(f\\\"Oops! Module {r} is not satisfied! It desires: {r.requirements}\\\")\\n\\n # now confident that all versions check out, arrange the plugins into a suitable load order.\\n # no reason to do anything fancy without requirements though.\\n if not remaining:\\n return\\n\\n while True:\\n new_remaining = remaining.copy()\\n for m in remaining:\\n if loaded.issuperset({r for r in m.requirements.keys()}):\\n new_remaining.remove(m)\\n loaded.add(m.name)\\n self.module_call_order.append(m)\\n if len(new_remaining) < len(remaining):\\n # this is good.. we made progress!\\n remaining = new_remaining\\n if not remaining:\\n # hooray! No more plugins to process\\n break\\n else:\\n # this is bad. we are not making progress.\\n raise Exception(\\\"dependency load order is not progressing!\\\")\",\n \"def check_dag(self):\\n self.create_dag()\\n\\n self.check_connected_components()\\n\\n self.check_for_cycles()\",\n \"def validate_dependencies(self, session, entry):\",\n \"def check_dependencies(work_dir, fits_dir, fitsbase):\\n # Print to screen what processing steps have been selected\\n print \\\"The following processing steps have been selected:\\\\n\\\"\\n if params.do_rfifind:\\n print \\\" - PRESTO rfifind (RFI mitigation tools)\\\"\\n if params.do_prepsub:\\n print \\\" - PRESTO prepsubband (dedispersion)\\\"\\n if params.do_candsearch:\\n print \\\" - PRESTO acceleration search and candidate sifting\\\"\\n if params.do_presto_sp:\\n print \\\" - PRESTO singlepulse search (singlepulse.py)\\\"\\n # Print to screen what processing steps are being skipped\\n print \\\"\\\\nThe following processing steps are being skipped:\\\\n\\\"\\n if params.do_rfifind == 0:\\n print \\\" - PRESTO rfifind (RFI mitigation tools)\\\"\\n if params.do_prepsub == 0:\\n print \\\" - PRESTO prepsubband (dedispersion)\\\"\\n if params.do_candsearch == 0:\\n print \\\" - PRESTO acceleration search and candidate sifting\\\"\\n if params.do_presto_sp == 0:\\n print \\\" - PRESTO singlepulse search (singlepulse.py)\\\"\\n print \\\"\\\\nChecking dependencies...\\\\n\\\"\\n # There must be at least one .fits file in the fits directory\\n fl = glob(fits_dir + '/%s*.fits' %fitsbase)\\n if len(fl):\\n print \\\" Found %d file(s) in %s:\\\\n\\\" %(len(fl), fits_dir)\\n for i in fl:\\n print \\\" %s\\\\n\\\" %(i.split('/')[-1])\\n else:\\n print \\\" No %s*.fits files found in %s !\\\\n Exiting...\\\\n\\\" %(fitsbase, fits_dir)\\n sys.exit(0)\\n # If skipping the RFIFIND step in processing but want to do\\n # processing steps further down the line, then there must be a\\n # rfi_products folder in the results directory with a .mask file\\n # in it\\n if params.do_rfifind == 0 and params.use_mask and \\\\\\n (params.do_prepsub or params.do_candsearch or params.do_presto_sp):\\n mlist = glob(work_dir + '/rfi_products/*.mask')\\n if len(mlist):\\n print \\\" Using RFI .mask:\\\\n %s\\\\n\\\" %(mlist[0])\\n else:\\n print \\\" No RFI .mask found in %s/rfi_products!\\\\n Exiting...\\\\n\\\"\\\\\\n %(work_dir)\\n sys.exit(0)\\n # If skipping the PREPSUBBAND step in processing but want to\\n # do processing steps further down the line, then there must be\\n # de-dispersed time series files in the results directory of\\n # the form basename*DM*.dat and basename*DM*.inf\\n if params.do_prepsub == 0 and (params.do_candsearch or \\n params.do_presto_sp):\\n dats = glob(work_dir + '/*DM*dat')\\n infs = glob(work_dir + '/*DM*inf')\\n if not (len(dats) and len(infs)):\\n print \\\" No .dat and/or .inf files in %s!\\\\n Exiting...\\\\n\\\" %(work_dir)\\n sys.exit(0)\\n # If we haven't exited by now, then things should be good\\n print \\\"\\\\nLooks good...\\\\n\\\\n\\\"\\n # Pause for a few seconds so you can actually read the output\\n time.sleep(5)\",\n \"def all_DU_paths(CG, T):\\n path_to_visit = []\\n path_not_visited = []\\n for var in CG.var:\\n vert_var_in_defv=set()\\n vert_var_in_refv=set()\\n for vert in CG.vertices:\\n if var in vert.defv:\\n vert_var_in_defv.add(vert.label)\\n elif var in vert.refv:\\n vert_var_in_refv.add(vert.label)\\n couples = product(vert_var_in_defv, vert_var_in_refv)\\n for vert_def, vert_ref in couples:\\n #paths_remaining = list(CG.simple_partial_paths[(vert_def, vert_ref)])\\n path_to_visit += list(CG.simple_partial_paths[(vert_def, vert_ref)])\\n path_not_visited += list(CG.simple_partial_paths[(vert_def, vert_ref)])\\n for t in T:\\n path, variables = apply_path(CG, t)\\n vert_found = False\\n for label in path:\\n cur_vertice=find_vertice_with_label(CG,label)\\n if vert_def == label:\\n vert_found = True\\n\\n elif vert_ref == label and vert_found:\\n if path in path_not_visited:\\n path_not_visited.remove(path)\\n break\\n\\n elif vert_ref != label and var in cur_vertice.refv:\\n break\\n #print('Test failed')\\n #print(paths_remaining, var,vert_def, vert_ref, path)\\n #return False\\n\\n #if paths_remaining:\\n # print('Test failed')\\n # print(paths_remaining, var, vert_def, vert_ref, path)\\n # return False\\n\\n Graph.coverage_criteria2(path_to_visit, \\\"not_visited\\\", path_not_visited)\\n if path_not_visited:\\n print('Test failed')\\n \\n else:\\n print('Test passed')\\n return True\",\n \"def compute_dependencies(repositories, requirement, transitive=False):\\n pool = Pool(repositories)\\n neighbors = _neighbors_in_repositories(pool, transitive)\\n dependencies = _neighbors_for_requirement(pool, neighbors, requirement)\\n return dependencies\",\n \"def resolver_dependencies(pkg, db_manifest):\\n print(\\\"[root-get] DEBUG: Resolving dependencies without DAG: direct strategy\\\")\\n try:\\n if db_manifest[pkg][\\\"deps\\\"] is not None:\\n for dep in db_manifest[pkg][\\\"deps\\\"]:\\n print(\\\"[root-get] Installing dependency \\\" + dep)\\n if not install_dep_pkg(dep, db_manifest):\\n return False\\n else:\\n print(\\\"[root-get] Dependency {0:s} is sucessfully installed and deployed\\\".format(dep))\\n else:\\n print(\\\"[root-get] No dependencies for {0:s} \\\".format(pkg))\\n except:\\n pass\",\n \"def validate_dependence_versions():\\n print('Total {} instances defined'.format(len(ReleaseInfo.all_instance_releases())))\\n all_instance_releases = ReleaseInfo.all_instance_releases()\\n\\n # Validate dependencies: each dependence should have a valid\\n # version as in defined range\\n for instance_name, versions in all_instance_releases.items():\\n for instance_version, release_info in versions.items():\\n dependencies = release_info.dependencies\\n for dep in dependencies:\\n dep_type = dep.type\\n minv = dep.min_version\\n maxv = dep.max_version\\n\\n assert dep_type in all_instance_releases, \\\\\\n \\\"No dependence found {} for version {} of {}\\\" \\\\\\n .format(dep_type, instance_version, instance_name)\\n\\n found = _find_a_ranged_version(dep_type, minv=minv, maxv=maxv)\\n assert found, \\\"No valid version defined for {} with max: {}, min: {}\\\" \\\\\\n .format(dep_type, maxv, minv)\",\n \"def is_allowed(self):\\n if self.structure.variable_dependant_path:\\n # fill in empty part of the path with the current path\\n if len(self.structure.variable_dependant_path) == 3:\\n dependant_var_path = (\\n self.path[0],\\n ) + self.structure.variable_dependant_path\\n elif len(self.structure.variable_dependant_path) == 2:\\n dependant_var_path = (\\n self.path[0],\\n self.path[1],\\n ) + self.structure.variable_dependant_path\\n elif len(self.structure.variable_dependant_path) == 1:\\n dependant_var_path = (\\n self.path[0],\\n self.path[1],\\n self.path[2],\\n ) + self.structure.variable_dependant_path\\n else:\\n dependant_var_path = None\\n\\n # get dependency\\n dependant_var = None\\n mf_data = self._simulation_data.mfdata\\n if dependant_var_path in mf_data:\\n dependant_var = mf_data[dependant_var_path]\\n\\n # resolve dependency\\n if self.structure.variable_value_when_active[0] == \\\"Exists\\\":\\n exists = self.structure.variable_value_when_active[1]\\n if dependant_var and exists.lower() == \\\"true\\\":\\n return True\\n elif not dependant_var and exists.lower() == \\\"false\\\":\\n return True\\n else:\\n return False\\n elif not dependant_var:\\n return False\\n elif self.structure.variable_value_when_active[0] == \\\">\\\":\\n min_val = self.structure.variable_value_when_active[1]\\n if dependant_var > float(min_val):\\n return True\\n else:\\n return False\\n elif self.structure.variable_value_when_active[0] == \\\"<\\\":\\n max_val = self.structure.variable_value_when_active[1]\\n if dependant_var < float(max_val):\\n return True\\n else:\\n return False\\n return True\",\n \"def deps_for(nodes, key):\\n\\n def _deps(key, path):\\n if key not in nodes:\\n return [key]\\n\\n if key in path:\\n msg = \\\"Cycle detected between {} and {}\\\".format(\\n path[0], path[-1])\\n raise GraphError(msg)\\n\\n deps = nodes[key][\\\"required\\\"]\\n trans = [_deps(dep, path + [key]) for dep in deps]\\n return set(util.concat(deps, *trans))\\n\\n return _deps(key, [])\",\n \"def test_dfs():\\r\\n assert DFS(valid_graph, sorted(list(valid_graph.get_graph().nodes))[0]) == \\\\\\r\\n list(nx.dfs_preorder_nodes(valid_graph.get_graph(), sorted(list(valid_graph.get_graph().nodes))[0]))\",\n \"def get_dependency_rules(graph, root_node=None,\\n node_attrib='label', edge_attrib='label'):\\n rules = set()\\n\\n if not root_node:\\n # root node is the first element in a topological sort of the graph\\n root_node = nx.topological_sort(graph)[0]\\n\\n for source, target in nx.dfs_edges(graph, root_node):\\n rules.add( (ensure_utf8(graph.node[source].get(node_attrib, source)),\\n ensure_utf8(graph[source][target].get(edge_attrib, '')),\\n ensure_utf8(graph.node[target].get(node_attrib, target))) )\\n return rules\",\n \"def depends((a, b)):\\r\\n return (any(bout in a.inputs for bout in b.outputs)\\r\\n or any(depends((ainp.owner, b)) for ainp in a.inputs\\r\\n if ainp.owner))\",\n \"def test_3():\\n h = iotbx.pdb.input(source_info=None, lines=test_pdb_3).construct_hierarchy()\\n asc = h.atom_selection_cache()\\n ncs_inp = iotbx.ncs.input(\\n hierarchy=h,\\n params=ncs_pars.ncs_search)\\n ncs_groups = ncs_inp.get_ncs_restraints_group_list()\\n assert len(ncs_groups) == 1\\n # group 1\\n assert ncs_groups[0].master_iselection.all_eq(\\n asc.selection(string = \\\"chain A\\\").iselection())\\n g1_c = ncs_groups[0].copies\\n assert len(g1_c)==1\\n assert g1_c[0].iselection.all_eq(\\n asc.selection(string = \\\"chain B\\\").iselection())\",\n \"def check_dependencies():\\n check_python_version()\\n\\n dependencies = [\\\"sqlite3\\\"]\\n\\n for dependency in dependencies:\\n try:\\n __import__(dependency)\\n except ImportError as e:\\n raise CuckooStartupError(\\\"Unable to import \\\\\\\"%s\\\\\\\"\\\" % dependency)\\n\\n return True\",\n \"def test_get_all_prerequisites(self):\\n c1 = content.ContentMetadata.objects.using(self.the_channel_id).get(title=\\\"c1\\\")\\n root = content.ContentMetadata.objects.using(self.the_channel_id).get(title=\\\"root\\\")\\n # if root is the prerequisite of c1\\n expected_output = content.ContentMetadata.objects.using(self.the_channel_id).filter(title__in=[\\\"root\\\"])\\n actual_output = api.get_all_prerequisites(channel_id=self.the_channel_id, content=c1)\\n self.assertEqual(set(expected_output), set(actual_output))\\n # then c1 should not be the prerequisite of root\\n expected_output = content.ContentMetadata.objects.using(self.the_channel_id).filter(title__in=[\\\"c1\\\"])\\n actual_output = api.get_all_prerequisites(channel_id=self.the_channel_id, content=root)\\n self.assertNotEqual(set(actual_output), set(expected_output))\",\n \"def CheckForDs(subgraphs_cnt, subgraphs_total, subgraph_loops, subgraph_dims, ds):\\n for i in subgraphs_cnt.keys():\\n# print\\n# print i\\n# print subgraphs_total, subgraph_loops\\n\\n if subgraphs_total[i] >= subgraph_loops[i] + 1:\\n# if True:\\n if subgraphs_cnt[i] >= RequiredDecompositions(subgraph_dims[i]) and i not in ds.keys():\\n return i\\n return None\",\n \"def find_dependants_recurse(key, rev_tree, previous=None):\\n if previous is None:\\n previous = set()\\n if not key in rev_tree:\\n return []\\n this_level_dependants = set(rev_tree[key])\\n next_level_dependants = set()\\n for dependant in this_level_dependants:\\n if dependant in previous:\\n continue\\n tmp_previous = previous.copy()\\n tmp_previous.add(dependant)\\n next_level_dependants.update(\\n find_dependants_recurse(dependant, rev_tree,\\n previous=tmp_previous,\\n ))\\n # ensures reloading order on the final list\\n # by postponing the reload of modules in this level\\n # that also appear later on the tree\\n dependants = (list(this_level_dependants.difference(\\n next_level_dependants)) +\\n list(next_level_dependants))\\n return dependants\",\n \"def buildall(target):\\n if not is_acyclic(target):\\n raise CircularDependency()\\n\\n def needsbuild(dataset):\\n if dataset.exists and \\\\\\n any(not par.exists or dataset.is_older_than(par)\\n for par in dataset.parents()):\\n return True, PARENTNEWER\\n elif not dataset.exists:\\n return True, MISSING\\n else:\\n return False, None\\n\\n def mark_children_breadthfirst(roots, parents):\\n \\\"\\\"\\\" Mark build order for all ancestors, beginning with the roots. \\\"\\\"\\\"\\n marks = {}\\n queue = [(0, root) for root in roots]\\n while len(queue) != 0:\\n i, dep = queue.pop(0)\\n marks[dep] = i\\n for child in filter(lambda d: d in parents, dep.children(0)):\\n iold = marks.get(child, -1)\\n if i > iold:\\n marks[child] = i\\n queue.append((i+1, child))\\n return marks\\n\\n # Map of Dataset -> integer, where the integer indicates the build step\\n marks = mark_children_breadthfirst(target.roots(), set(target.parents()))\\n\\n groups = []\\n maxi = 0\\n for dep, i in marks.items():\\n nb, reason = needsbuild(dep)\\n if nb:\\n while i >= maxi:\\n groups.append([])\\n maxi += 1\\n groups[i].append((dep, reason))\\n\\n for group in groups:\\n yield group\\n\\n if needsbuild(target)[0]:\\n yield [(target, MISSING)]\",\n \"def test_solve_nestedcs():\\n\\n import numpy as np\\n from crpm.setup_nestedcs import setup_nestedcs\\n from crpm.fwdprop import fwdprop\\n from crpm.lossfunctions import loss\\n from crpm.gradientdecent import gradientdecent\\n\\n #init numpy seed\\n np.random.seed(40017)\\n\\n #setup model\\n model, data = setup_nestedcs()\\n\\n #calculate initial mean squared error\\n pred, _ = fwdprop(data[0:2,], model)\\n icost, _ = loss(\\\"mse\\\", pred, data[-1,])\\n #print(icost)\\n\\n #train model\\n pred, cost, _ = gradientdecent(model, data[0:2,], data[-1,], \\\"mse\\\")\\n\\n #print(model)\\n #print(icost)\\n #print(cost)\\n assert icost > cost\\n assert cost < .08\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6695402","0.6293103","0.60720724","0.60228133","0.5990557","0.5964589","0.59326696","0.5578468","0.5578364","0.53697","0.5355786","0.53459734","0.53228617","0.53076524","0.5307568","0.5283302","0.5280135","0.527394","0.5268686","0.5262103","0.52600974","0.5248824","0.5226644","0.5223192","0.5220016","0.5199381","0.51770365","0.5141885","0.51380193","0.5128205","0.51207095","0.5119971","0.5118776","0.5114501","0.51028407","0.50895727","0.508363","0.507556","0.5063559","0.5061258","0.50528675","0.5051327","0.50496364","0.5038368","0.50320596","0.5029528","0.50274795","0.5018072","0.5007663","0.5006118","0.4991442","0.49797156","0.49760422","0.49685058","0.4968465","0.49595076","0.49534655","0.4943968","0.49434882","0.49390662","0.49356213","0.492333","0.4922344","0.49128985","0.4910248","0.48989862","0.48968208","0.489054","0.48825806","0.487691","0.48749968","0.4869455","0.486891","0.48610136","0.48516777","0.484917","0.48490575","0.48366544","0.48216426","0.48203027","0.4814793","0.48041674","0.47991833","0.47780898","0.4775086","0.47736305","0.47710872","0.4747912","0.47432753","0.4737084","0.46990246","0.46967775","0.46899086","0.46824604","0.46793708","0.46774647","0.4676623","0.46763042","0.4672462","0.4671652"],"string":"[\n \"0.6695402\",\n \"0.6293103\",\n \"0.60720724\",\n \"0.60228133\",\n \"0.5990557\",\n \"0.5964589\",\n \"0.59326696\",\n \"0.5578468\",\n \"0.5578364\",\n \"0.53697\",\n \"0.5355786\",\n \"0.53459734\",\n \"0.53228617\",\n \"0.53076524\",\n \"0.5307568\",\n \"0.5283302\",\n \"0.5280135\",\n \"0.527394\",\n \"0.5268686\",\n \"0.5262103\",\n \"0.52600974\",\n \"0.5248824\",\n \"0.5226644\",\n \"0.5223192\",\n \"0.5220016\",\n \"0.5199381\",\n \"0.51770365\",\n \"0.5141885\",\n \"0.51380193\",\n \"0.5128205\",\n \"0.51207095\",\n \"0.5119971\",\n \"0.5118776\",\n \"0.5114501\",\n \"0.51028407\",\n \"0.50895727\",\n \"0.508363\",\n \"0.507556\",\n \"0.5063559\",\n \"0.5061258\",\n \"0.50528675\",\n \"0.5051327\",\n \"0.50496364\",\n \"0.5038368\",\n \"0.50320596\",\n \"0.5029528\",\n \"0.50274795\",\n \"0.5018072\",\n \"0.5007663\",\n \"0.5006118\",\n \"0.4991442\",\n \"0.49797156\",\n \"0.49760422\",\n \"0.49685058\",\n \"0.4968465\",\n \"0.49595076\",\n \"0.49534655\",\n \"0.4943968\",\n \"0.49434882\",\n \"0.49390662\",\n \"0.49356213\",\n \"0.492333\",\n \"0.4922344\",\n \"0.49128985\",\n \"0.4910248\",\n \"0.48989862\",\n \"0.48968208\",\n \"0.489054\",\n \"0.48825806\",\n \"0.487691\",\n \"0.48749968\",\n \"0.4869455\",\n \"0.486891\",\n \"0.48610136\",\n \"0.48516777\",\n \"0.484917\",\n \"0.48490575\",\n \"0.48366544\",\n \"0.48216426\",\n \"0.48203027\",\n \"0.4814793\",\n \"0.48041674\",\n \"0.47991833\",\n \"0.47780898\",\n \"0.4775086\",\n \"0.47736305\",\n \"0.47710872\",\n \"0.4747912\",\n \"0.47432753\",\n \"0.4737084\",\n \"0.46990246\",\n \"0.46967775\",\n \"0.46899086\",\n \"0.46824604\",\n \"0.46793708\",\n \"0.46774647\",\n \"0.4676623\",\n \"0.46763042\",\n \"0.4672462\",\n \"0.4671652\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5844651"},"document_rank":{"kind":"string","value":"7"}}},{"rowIdx":13072,"cells":{"query":{"kind":"string","value":"Given the soup for a condition, test that its dependencies are validly defined."},"document":{"kind":"string","value":"def _verify_dependencies(self, cond_id, undefined_paths, current_path):\n\n # Exception for izpack conditions:\n if cond_id in self.conditions.properties[WHITE_LIST]:\n return True\n\n # Short-circuit on well-defined conditions:\n if cond_id in self.well_defined:\n return True\n\n # Short-circuit ill-defined conditions:\n if cond_id in list(self.ill_defined.keys()):\n current_path = current_path + ((cond_id, 'ill-defined condition'),)\n undefined_paths.add(current_path)\n return False\n\n # Cycle checking:\n tup = (cond_id, 'condition')\n if tup in current_path:\n current_path += ((cond_id, 'cyclic condition reference'),)\n undefined_paths.add(current_path)\n return False\n\n # Check for undefined condition.\n if not cond_id in self.conditions.get_keys():\n tup = (cond_id, 'undefined condition')\n current_path += (tup,)\n undefined_paths.add(current_path)\n return False\n\n current_path += (tup,)\n condition = self.conditions.container[cond_id]\n condition_type = condition['type']\n\n if condition_type in list(self.condition_tests.keys()) and not \\\n self.condition_tests[condition_type](self, condition, undefined_paths, current_path):\n return False\n\n self.well_defined.add(cond_id)\n return True"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def testConditionChecking(self):\n\n state = State.from_problem(self.prob)\n \n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition))\n\n with drive.instantiate([\"agent\", \"tru1\", \"apt2\"], self.prob):\n self.assertFalse(state.is_satisfied(drive.precondition))","def testConditionReasons(self):\n \n state = State.from_problem(self.prob)\n\n relevantVars = []\n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\n\n relevantVars = set(relevantVars)\n \n s1 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"pos1\"]])\n s2 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"apt1\"]])\n s3 = StateVariable(self.prob.functions[\"location-of\"][0], [self.prob[\"tru1\"]])\n \n self.assertEqual(len(relevantVars), 3)\n self.assert_(s1 in relevantVars)\n self.assert_(s2 in relevantVars)\n self.assert_(s3 in relevantVars)","def test_verify_dependencies(self, cond_id, conditions):\n\n if not cond_id in conditions.get_keys():\n return 1\n else:\n result = self.verify_dependencies(cond_id)\n return result","def _check_conditional_dependency(obj, condition, package, severity, msg=None):\n if condition:\n if msg is None:\n msg = (\n f\"The specific parameter values of {obj.__class__.__name__}'s \"\n f\"class instance require `{package}` installed. Please run: \"\n f\"`pip install {package}` to \"\n f\"install the `{package}` package. \"\n )\n try:\n _check_soft_dependencies(package, severity=severity, obj=obj)\n except ModuleNotFoundError as e:\n raise ModuleNotFoundError(msg) from e","def valid_dependency(self, dep):\r\n return True","def _alert_condition(self, soup: BeautifulSoup) -> bool:\n raise NotImplementedError()","def dependencies_satisfied(self, module) -> bool:\n for k, v in module.requirements.items():\n if k not in self.modules:\n return False\n found_ver = self.modules[k].version\n if isinstance(v, str):\n return found_ver == v\n elif isinstance(v, dict):\n if \"eq\" in v and (found_ver != v[\"eq\"]):\n return False\n if \"min\" in v and (found_ver < v[\"min\"]):\n return False\n if \"max\" in v and (found_ver > v[\"max\"]):\n return False\n else:\n return True\n return True","def test_condition_syntax(self):\n\n base = abs_path('./specs/')\n ps = Parser(base+'script3-1.py', base)\n\n spec = {'constraints': [{'block': 'A', 'condition': 'B=b1'}]}\n with self.assertRaises(ParseError):\n read_wrapper(spec, ps)\n\n spec = {'constraints': [{'block': 'A', 'condition': 'B b1'}]}\n with self.assertRaises(ParseError):\n read_wrapper(spec, ps)\n\n spec = {'constraints': [{'block': 'A', 'condition': 'B == 2.5'}]}\n read_wrapper(spec, ps)","def satisfied(self, fields, field, values):\n\n requires = field.get(\"requires\", [])\n\n if isinstance(requires, str):\n requires = [requires]\n\n for require in requires:\n if require not in fields or not fields[require].validate(store=False):\n return False\n\n if \"condition\" in field and self.env.from_string(field[\"condition\"]).render(**values) != \"True\":\n return False\n\n return True","def test_available(self):\n feature_guard = _make_requires(True, \"Error text\")\n results = []\n\n @feature_guard\n def inner():\n results.append(True)\n return True\n\n assert inner() is True\n assert [True] == results","def test_empty_condition(self):\n assert_that(Condition.is_valid(''), equal_to(True))","def conditions():\n pass","def test_verify_all_dependencies(self):\n\n for condition in self.all_references():\n result = self.verify_dependencies(condition)\n\n if result:\n self.ill_defined[condition] = result\n else:\n self.well_defined.add(condition)\n\n return self.ill_defined","def check_requirements(self): # pylint: disable=no-self-use\n self.is_skipped = False","def check_condition(self):\n\n\t\traw_context = {\n\t\t\t'folk': self.folk\n\t\t}\n\n\t\tstatus, param = self.execute(self.mission_grid, 'condition', self.pending_mission.kingdom, raw_context)\n\t\treturn status","def check_requirements(config=None):\n for dependency, module_requirements in (\n requirements(config, include_conditional=False).items()):\n for module_requirement in module_requirements:\n if \">=\" in module_requirement:\n module_name, required_version = module_requirement.split(\">=\")\n version_test = \">=\"\n elif \"==\" in module_requirement:\n module_name, required_version = module_requirement.split(\"==\")\n version_test = \"==\"\n else:\n module_name = module_requirement\n version_test = None\n\n try:\n module = __import__(module_name)\n except ImportError:\n logging.exception(\n \"Can't import %r which is part of %r\",\n module_name, dependency\n )\n raise MissingRequirementError(\n \"Can't import %r which is part of %r\"\n % (module_name, dependency), module_name, dependency\n )\n version = getattr(module, \"__version__\", None)\n file_path = getattr(module, \"__file__\", None)\n logger.info(\n \"Using %r version %r from %r to satisfy %r\",\n module_name, version, file_path, dependency\n )\n\n if version_test == \">=\":\n if version is None:\n raise MissingRequirementError(\n \"Version of %r isn't set as __version__ of module %r\"\n % (dependency, module_name), module_name, dependency\n )\n if LooseVersion(version) < LooseVersion(required_version):\n raise MissingRequirementError(\n \"Version of %r in %r is too old. %r < %r\"\n % (dependency, file_path, version, required_version),\n module_name, dependency\n )\n elif version_test == \"==\":\n if version is None:\n raise MissingRequirementError(\n \"Version of %r isn't set as __version__ of module %r\"\n % (dependency, module_name), module_name, dependency\n )\n if LooseVersion(version) != LooseVersion(required_version):\n raise MissingRequirementError(\n \"Unexpected version of %r in %r. %r != %r\"\n % (dependency, file_path, version, required_version),\n module_name, dependency\n )","def test_AnvilResearchStudy_Condition(anvil_research_studies_with_observations):\n _validate_ResearchStudy_Condition(anvil_research_studies_with_observations)","def _isCondition(self, column):\n\n for _, values in self._model.parameters.items():\n if column in values['depends']:\n return True\n return False","def test_are_dependency_packs_valid(self, current_file, id_set, answer):\n validator = get_validator(current_file)\n assert validator.are_dependency_packs_valid(id_set) is answer","def test_zt_requirement(self):\n test_passes = False\n try:\n self.parser.extract_zt(\"FOOBAR\")\n test_passes = False\n except:\n test_passes = True\n self.assertTrue(test_passes)","def condition_forward_checking(csp, var) :\n return False","def condition_forward_checking(csp, var) :\n return False","def check_condition(self, comment):\n if comment.id in self.touched_comment_ids:\n return False, None\n # First check for keywords in comment, for now we don't care about formatting after the keyword\n has_keyword = self.check_word_in_list_in_string(self.keywords, comment.body)\n if not has_keyword:\n return False, None\n # Next we check if we have states or abbreviations\n abbrevs = self.check_comment_for_dictionary_keys_and_values(comment, self.states)\n if len(abbrevs) < 1:\n return False, None\n if str(comment.author) == self.bot_name:\n return False, None\n for reply in comment.replies:\n if str(reply.author) == self.bot_name:\n return False, None\n\n return True, abbrevs","def testConditionBuilderErrors(self):\n\t\ttests = [r'2elem==1', r'elem=<3', r'elem == 0xXY']\n\n\t\tfor test in tests:\n\t\t\tself.assertRaises(ParserError, parseSearchCondition, test)","def testConditionalEffects(self):\n \n action = Parser.parse_as(cond_load.split(\"\\n\"), Action, self.domain)\n\n self.assert_(isinstance(action.effect, ConditionalEffect))\n self.assert_(isinstance(action.effect.condition, conditions.LiteralCondition))\n self.assert_(isinstance(action.effect.effect, SimpleEffect))","def is_valid(self):\n return not self.missing_from_disk and not self.missing_dependency","def __satisfies_necessary_and_sufficient_conditions(g):\n # Condition 0: at least 1 Edge\n if g.get_E() == 0:\n return False\n # Condition 1: indegree(v) == outdegree(v) for every vertex\n for v in range(g.get_V()):\n if g.outdegree() != g.indegree(v):\n return False\n # Condition 2: graph is connected, ignoring isolated vertices\n h = Graph(g.get_V())\n for v in range(g.get_V()):\n for w in g.adj_vertices(v):\n h.add_edge(v, w)\n # check that all non-isolated vertices are connected\n s = DirectedEulerianCycle.__non_isolated_vertex(g)\n bfs = BreadthFirstPaths(h, s)\n for v in range(g.get_V()):\n if h.degree(v) > 0 and not bfs.has_path_to(v):\n return False\n return True","def are_all_deps_fulfilled(self, package: 'Package', only_make_check: bool = False,\n only_depends: bool = False, print_reason: bool = False) -> bool:\n\n for dep in package.relevant_deps(only_make_check=only_make_check, only_depends=only_depends):\n if not self.provided_by(dep):\n if print_reason:\n aurman_note(\n \"Dependency {} of package {} is not fulfilled\".format(\n Colors.BOLD(Colors.LIGHT_MAGENTA(dep)),\n Colors.BOLD(Colors.LIGHT_MAGENTA(package.name))\n )\n )\n return False\n else:\n return True","def _sufficient_deps(cls, deps):\n if cls.MODEL_PACKAGE is None:\n return True\n else:\n for d in deps.conda:\n if cls.MODEL_PACKAGE in d:\n return True\n for d in deps.pip:\n if cls.MODEL_PACKAGE in d:\n return True\n return False","def test_check_job_dependencies_prior_dependency_has_errors(database):\n sess = database.session\n sub = SubmissionFactory(submission_id=1)\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\n number_of_errors=3)\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\n sess.add_all([sub, job, job_2])\n sess.commit()\n\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\n sess.add(job_dep)\n sess.commit()\n\n check_job_dependencies(job.job_id)\n\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']","def dependencies_met():\n # Check Java VM command line runner.\n try:\n Popen(['java'], shell=False, stderr=PIPE).communicate()[1]\n except:\n print 'Dependecy unmet. Java virtual machine command line runner not ' \\\n 'found.'\n return False\n # Check selenium-server.jar is ready to run.\n output = Popen(('java -jar %s -unrecognized_argument' % SELENIUM_RC_PATH\n ).split(), shell=False, stderr=PIPE).communicate()[1]\n if not re.search('Usage: java -jar selenium-server.jar', output):\n print 'Dependecy unmet. Selenium RC server (selenium-server.jar) not ' \\\n 'found.'\n return False\n # Check selenium RC python driver is available.\n try:\n import selenium\n except:\n print 'Dependecy unmet. Selenium RC python driver (selenium.py) not ' \\\n 'found.'\n return False\n # Check CherryPy wsgi server is available.\n try:\n import wsgiserver\n except:\n print 'Dependecy unmet. CherryPy wsgi server (wsgiserver.py) not found.'\n return False\n # Check fixture support is implemented for the database engine.\n if not settings.DATABASE_ENGINE in ['sqlite3', 'postgresql_psycopg2']:\n print 'Dependecy unmet. Fixture support for database engine %s not ' \\\n 'implemented.' % settings.DATABASE_ENGINE\n return False\n return True","def check_prerequisites(self, prequisites):\n for prereq in prequisites:\n # check for origin requirements\n if prereq.origin: \n if prereq.origin not in self.origins:\n print(f\"ORIGIN WRONG\")\n return False\n # check for additional header requirements\n if prereq.additional_header:\n if (not prereq.additional_header.open_flag and \n prereq.additional_header not in self.headers.all()):\n print(f\"WE DONT HAVE THE RIGHT HEADER SELECTED\")\n return False \n # check for header/skill requirements\n # did the user purchase the required header, or is the header open?\n if prereq.header:\n if (not prereq.header.open_flag and \n prereq.header not in self.headers.all()):\n print(f\"WE DONT HAVE THE RIGHT HEADER SELECTED\")\n return False \n # check for the number of different skills in the header.\n purchased_skills = HeaderSkill.objects.filter(\n header=prereq.header,\n skill__id__in=self.skills.values_list('skill__skill_id', flat=True)\n )\n if prereq.number_of_different_skills > purchased_skills.count(): \n print(f\"NUMBER OF SKILLS WRONG:{prereq.number_of_different_skills}:{purchased_skills.count()}\")\n return False\n # figure out the total skill points\n total = 0\n for skill in purchased_skills:\n total += skill.header.cost * skill.characterskills_set.get(character=self).count\n # check for skill requirements\n if prereq.skill:\n try:\n result = self.skills.get(skill__skill=prereq.skill)\n return result.count >= prereq.number_of_purchases\n except CharacterSkills.DoesNotExist:\n return False\n # if we made it this far, we can assume all prerequisites\n # have been met.\n return True","def testConditionBuilder(self):\n\t\ttests = {\n\t\t\tr'elem==1': [['elem'], op.EQ, 1],\n\t\t\tr'(elem==2)': [[['elem'], op.EQ, 2]],\n\t\t\tr'elem > 1 and elem2 < 5.54':\n\t\t\t\t[['elem'], op.GT, 1, op.AND, ['elem2'], op.LT, 5.54],\n\t\t\tr'not elem <= \"aaa\" and not elem2 ~ \"zzz\"':\n\t\t\t\t[op.NOT, ['elem'], op.LTE, \"aaa\", op.AND, op.NOT,\n\t\t\t\t['elem2'], op.REGEXP, \"zzz\"],\n\t\t\tr'not (elem.abc.def == 0xabcd) and (elem2 < 3)':\n\t\t\t\t[op.NOT, [['elem', 'abc', 'def'], op.EQ, b\"\\xab\\xcd\"],\n\t\t\t\top.AND, [['elem2'], op.LT, 3]],\n\t\t\tr'not (elem.2 != 4) or (not key.2.3 != 1) and not key.1 !~ \"abc\"':\n\t\t\t\t[op.NOT, [op.NOT, ['elem', 2], op.EQ, 4], op.OR,\n\t\t\t\t[['key', 2, 3], op.EQ, 1], op.AND,\n\t\t\t\t['key', 1], op.REGEXP, 'abc'],\n\t\t\tr'and == 2': [['and'], op.EQ, 2],\n\t\t\tr'': None\n\t\t}\n\n\t\tfor test in tests:\n\t\t\tself.assertEqual(tests[test], parseSearchCondition(test))","def assert_single_condition_and_sbml_file(problem_config: Dict) -> None:\n if (len(problem_config[SBML_FILES]) > 1\n or len(problem_config[CONDITION_FILES]) > 1):\n # TODO https://github.com/ICB-DCM/PEtab/issues/188\n # TODO https://github.com/ICB-DCM/PEtab/issues/189\n raise NotImplementedError(\n 'Support for multiple models or condition files is not yet '\n 'implemented.')","def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):\n # Check for a matching dependency type\n related = []\n\n if edge[2][\"dep\"] == dep:\n # Check for matching POS type(s)\n for pos_logic in dep_obj.keys():\n connector = None\n\n if isinstance(dep_obj[pos_logic], dict):\n for pos in dep_obj[pos_logic].keys():\n\n # Check for allowed part of speech tags in matched dependency patterns\n if (pos_logic == \"pos_in\" and pos in G.nodes[sibling_idx][\"pos\"]) or (\n pos_logic == \"pos_equals\" and pos == G.nodes[sibling_idx][\"pos\"]):\n pass\n elif pos_logic == \"pos_not\":\n if not [False if not_pos == G.nodes[sibling_idx][\"pos\"] else True for not_pos in\n dep_obj.keys()]: continue\n else:\n continue\n\n # if no additional checks, have a match\n if dep_obj[pos_logic][pos] == None or any(\n y in dep_obj[pos_logic][pos] for y in [None, \"add_sibling\"]):\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']])\n\n # if additional checks are required, process further\n if dep_obj[pos_logic][pos]:\n if \"get_cousin\" in dep_obj[pos_logic][pos]:\n related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos][\"get_cousin\"]))\n connector = G.nodes[sibling_idx]['word']\n\n if \"special\" in dep_obj[pos_logic][pos]:\n if dep == \"compound\" and pos == \"NN\":\n related = [G.nodes[sibling_idx]['word']]\n\n if None in related:\n related.remove(None)\n\n # Allows for getting cousin and returning sibling\n if \"else\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\"else\"] == \"always\":\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\n if len(related) > 0 and isinstance(related, list):\n for x in related:\n if x != None:\n all_related = _add_related(x, dep, all_related, A.index_lookup[x],\n connector=connector)\n elif \"else\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\"else\"] == True:\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\n\n return all_related","def check_requirement(self):\n raise NotImplementedError","def dependencies_are_met(\n self,\n parent_job: Optional['Job'] = None,\n pipeline: Optional['Pipeline'] = None,\n exclude_job_id: Optional[str] = None,\n ) -> bool:\n connection = pipeline if pipeline is not None else self.connection\n\n if pipeline is not None:\n connection.watch(*[self.key_for(dependency_id) for dependency_id in self._dependency_ids])\n\n dependencies_ids = {_id.decode() for _id in connection.smembers(self.dependencies_key)}\n\n if exclude_job_id:\n dependencies_ids.discard(exclude_job_id)\n if parent_job and parent_job.id == exclude_job_id:\n parent_job = None\n\n if parent_job:\n # If parent job is canceled, treat dependency as failed\n # If parent job is not finished, we should only continue\n # if this job allows parent job to fail\n dependencies_ids.discard(parent_job.id)\n if parent_job.get_status() == JobStatus.CANCELED:\n return False\n elif parent_job._status == JobStatus.FAILED and not self.allow_dependency_failures:\n return False\n\n # If the only dependency is parent job, dependency has been met\n if not dependencies_ids:\n return True\n\n with connection.pipeline() as pipeline:\n for key in dependencies_ids:\n pipeline.hget(self.key_for(key), 'status')\n\n dependencies_statuses = pipeline.execute()\n\n allowed_statuses = [JobStatus.FINISHED]\n if self.allow_dependency_failures:\n allowed_statuses.append(JobStatus.FAILED)\n\n return all(status.decode() in allowed_statuses for status in dependencies_statuses if status)","def uses_requirement(requirement, field):\n\n if hasattr(field.requires, \"other\") or requirement in str(field.requires):\n if hasattr(field.requires, \"other\"):\n if requirement in str(field.requires.other):\n return True\n elif requirement in str(field.requires):\n return True\n return False","def requirement_is_satisfied(requirement, working_set, newest):\n\n if newest: return False\n\n try:\n working_set.require(requirement)\n return True\n except:\n pass\n\n return False","def evaluate_package_conditions(package, ros_distro):\n # Conditional fields were introduced in package format 3.\n # Earlier formats should have their conditions evaluated with no context so\n # the evaluated_condition is set to True in all cases.\n if package.package_format >= 3:\n package.evaluate_conditions(package_conditional_context(ros_distro))","def condition_is_valid(self):\n cond = self.condition.lower()\n cond = re.sub('\\s+', ' ', cond)\n\n for ap in self.available_functions:\n ap = ap.lower()\n\n ret = re.search(ap, cond)\n if ret:\n # [('a', 'b'), ('a', 'b'), ...]\n self.used_functions[ap] = re.findall(ap, cond)\n cond = re.sub(ap, ' ', cond)\n\n # print self.used_functions\n for op in ['and', 'or', 'not']:\n cond = re.sub('\\s%s\\s' % op, ' ', cond)\n\n cond = re.sub('\\(', '', cond)\n cond = re.sub('\\)', '', cond)\n cond = re.sub('\\s+', '', cond)\n\n return len(cond) == 0","def validate_dom_elem(check, js=False):\n if js:\n known_elems = [x[0] for x in dm.DOMElem.query.with_entities(dm.DOMElem.js_name)]\n else:\n known_elems = [x[0] for x in dm.DOMElem.query.with_entities(dm.DOMElem.bs_name)]\n if check not in known_elems:\n raise InvalidDOMElem(f\"Provided Parent element does not match any {'JavaScript' if js else 'BeautifulSoup'} element tag listed in basketbot DB\")","def test_headlines_dependencies(self) -> None:\n\n def has_dep(dep: str) -> bool:\n for h in self.report.headlines:\n if self.rules.get_headline_rules(\n h.name\n ) == self.rules.get_headline_rules(dep):\n return True\n return False\n\n for headline in self.report.headlines:\n rule: Optional[HeadlineRules] = self.rules.get_headline_rules(headline.name)\n if not rule:\n continue\n\n for dependency_group in rule.dependencies:\n is_match: bool = False\n for dependency in dependency_group:\n if has_dep(dependency):\n is_match = True\n break\n if not is_match:\n dependencies_list: str = \", \".join(dependency_group)\n self.add_error(\n f\"Rubriken {headline.name} kräver att en av följande \"\n f\"rubriker finns med i dokumentet: {dependencies_list}.\",\n headline=headline,\n )","def satisfyRequirements(path):\n if not hasVerb(path):\n return False\n if not hasConceptsAtTheEnds(path):\n return False\n if not isConceptDefinition(path):\n return False\n\n return True","def validate_dependencies(self, session, entry):","def has_required(self) -> bool:\n return any(child.is_required() for child in self.children)","def isConditional(self) -> bool:\n ...","def check_dependencies(target_binary, target_platform, target_architecture, target_type):\n check_architecture(target_architecture)\n check_platform(target_platform)","def check_condition(self, element):\n conditional = element.getAttribute(\"conditional\")\n\n # No condition, then we execute this statement.\n #\n if len(conditional) == 0:\n return True\n\n # We have a conditional. See if it begins with a '!', which inverts\n # our test.\n #\n result = True\n oc = conditional\n if conditional[0] == '!':\n result = False\n conditional = conditional[1:]\n\n if self.settings is not None and conditional in self.settings.ids:\n if self.settings.value(conditional) is True:\n return result\n return not result\n return not result","def condition_satisfied (self, node, i) :\n valid_options = []\n for nnode in self.graph.next_nodes(node):\n if self.val_l[nnode] == i :\n return False\n if (self.val_l[nnode] == self.undefined\n or self.val_l[nnode] == self.infinity) :\n valid_options.append(nnode)\n for options in valid_options:\n if i not in self.graph.next_nodes(options) :\n return False\n return True","def _validate_order(self, order, account, quotation, strategy_name):\n if quotation.volume < order.volume:\n print('Limit volume bardata volume:%d, untraded volume:%d, date:%s' % \n (quotation.volume, order.volume, quotation.date))\n return False\n\n # Calculate this order's margin\n if order.offset == 'open': \n posid = order.instrument+'-'+order.direction\n margin_ratio = account.portfolios[strategy_name].positions[posid].margin_ratio = quotation.margin_ratio\n multiplier = account.portfolios[strategy_name].positions[posid].multiplier = quotation.multiplier\n margin = order.price * order.volume * margin_ratio * multiplier\n if margin > account.available:\n print('Lack of capital available:%f, margin:%f' % (account.available, margin))\n return False\n return True\n elif order.offset == 'close':\n if order.direction == 'long':\n posid = order.instrument+'-'+'short'\n elif order.direction == 'short':\n posid = order.instrument+'-'+'long'\n hold_posi_quantity = account.portfolios[strategy_name].positions[posid].total_position\n try:\n assert order.volume > 0, 'close volume need greater than zero %d'%(order.volume)\n assert order.volume <= hold_posi_quantity, 'close volume need lower than hold posi quantity %d:%d'%(order.volume,\n hold_posi_quantity)\n except AssertionError as e:\n #print(e)\n return False\n return True\n elif order.offset == 'closetoday':\n order.direction = 'long' if order.direction == 'short' else 'short'\n posid = order.instrument+'-'+order.direction\n td_hold_posi_quantity = account.portfolios[strategy_name].positions[posid].today_position\n try:\n assert order.volume < td_hold_posi_quantity, 'close today position need lower than today hold position'\n except AssertionError as e:\n print(e)\n return False\n return True\n else:\n return False","def test_with_definitions():\n soup = generate_case(\"with_definitions\")\n\n tests.html_schema_doc_asserts.assert_property_names(\n soup,\n [\"billing_address\", \"street_address\", \"city\", \"state\", \"futureProperty\", \"shipping_address\"],\n )\n tests.html_schema_doc_asserts.assert_types(\n soup, [\"object\", \"object\", \"string\", \"string\", \"string\", \"null\", \"object\"]\n )\n tests.html_schema_doc_asserts.assert_required(soup, [False, True, True, True, False, False])","async def _assert_preconditions_async(preconditions: List[List[Contract]],\n resolved_kwargs: Mapping[str, Any]) -> Optional[BaseException]:\n exception = None # type: Optional[BaseException]\n\n # Assert the preconditions in groups. This is necessary to implement \"require else\" logic when a class\n # weakens the preconditions of its base class.\n\n for group in preconditions:\n exception = None\n\n for contract in group:\n assert exception is None, \"No exception as long as pre-condition group is satisfiable.\"\n\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\n\n if inspect.iscoroutinefunction(contract.condition):\n check = await contract.condition(**condition_kwargs)\n else:\n check_or_coroutine = contract.condition(**condition_kwargs)\n if inspect.iscoroutine(check_or_coroutine):\n check = await check_or_coroutine\n else:\n check = check_or_coroutine\n\n if not_check(check=check, contract=contract):\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\n break\n\n # The group of preconditions was satisfied, no need to check the other groups.\n if exception is None:\n break\n\n return exception","def test_condition(c, flag_dict, unspecified_val):\n\n for ci in c:\n if ci.name not in flag_dict:\n if not unspecified_val:\n return False\n elif ci.enabled != flag_dict[ci.name]:\n return False\n return True","def condition(*args, delete: bool=True, dependency: Union[AnyStr, List[AnyStr]]=\"\", initialize:\n bool=True, script: AnyStr=\"\", state: bool=True, q=True, query=True, e=True,\n edit=True, **kwargs)->Union[None, Any]:\n pass","def _check_dependency(self, tcname, depends):\r\n tcindex = self.tcorder.index(tcname)\r\n dependsindex = []\r\n for i in depends:\r\n dependsindex.append(self.tcorder.index(i))\r\n for i in dependsindex:\r\n if tcindex < i:\r\n msg = \"%s must be ordered after %s\\n\" %(tcname, self.tcorder[i])\r\n self.dependency.append(msg)","def _check_family(self):\n for (s, (b, c)), (cond, ref) in families.items():\n if s != self.SYMBOL or len(b) != self._.d:\n continue\n vars = tuple(set(sum(map(variables, b + c), ())))\n sols = _solve([SR(l) == r for l, r\n in zip(self._.b[:-1] + self._.c[1:], b + c)],\n vars)\n if any(checkConditions(cond, sol) for sol in sols\n if is_integral(sol)):\n raise InfeasibleError(refs=ref)","def test_has_error(html, expected):\n from scraper import has_error\n assert has_error(html) == expected","def check_dependencies():\n\n vars_valid = check_variables(\n AirflowVars.PROJECT_ID, AirflowVars.TERRAFORM_ORGANIZATION, AirflowVars.VM_DAGS_WATCH_LIST\n )\n conns_valid = check_connections(AirflowConns.TERRAFORM)\n\n if not vars_valid or not conns_valid:\n raise AirflowException(\"Required variables or connections are missing\")","def _validate_ResearchStudy_Condition(research_studies_with_observations):\n research_studies_with_observations = {r.relativePath(): r for r in research_studies_with_observations if\n r.__class__.__name__ == 'ResearchStudy'}\n research_studies_missing_condition = dict(**research_studies_with_observations)\n for research_study in research_studies_with_observations.values():\n if research_study.condition and len(research_study.condition) > 0:\n # print(f\"{research_study.relativePath()} has condition {research_study.condition[0].as_json()}\")\n del research_studies_missing_condition[research_study.relativePath()]\n # for k in research_studies_missing_condition:\n # from pprint import pprint\n # pprint(research_studies_missing_condition[k].as_json())\n # break\n assert len(\n research_studies_missing_condition) == 0, f\"{len(research_studies_missing_condition)} of {len(research_studies_with_observations)} ResearchStudies missing Condition codeable concept\\n{research_studies_missing_condition.keys()}\"","def ready_to_proceed(self):\n if self.current_step is None or self.step_position == StepPosition.Before:\n return False\n\n for condition, _ in self.current_step.conditions:\n if condition.satisfied():\n return True\n return False","def _validate_ResearchStudy_Condition(research_studies_with_observations):\n research_studies = {r.relativePath(): r for r in research_studies_with_observations if\n r.__class__.__name__ == 'ResearchStudy'}\n research_studies_missing_condition = dict(**research_studies)\n for research_study in research_studies.values():\n if research_study.condition and len(research_study.condition) > 0:\n # print(f\"{research_study.relativePath()} has condition {research_study.condition[0].as_json()}\")\n del research_studies_missing_condition[research_study.relativePath()]\n # for k in research_studies_missing_condition:\n # from pprint import pprint\n # pprint(research_studies_missing_condition[k].as_json())\n # break```\n assert len(\n research_studies_missing_condition) == 0, f\"{len(research_studies_missing_condition)} of {len(research_studies)} ResearchStudies missing Condition codeable concept\\n{research_studies_missing_condition.keys()}\"","def is_pre_test_survey_valid(survey, inclusion_criteria):\n for ic in inclusion_criteria:\n if not eval(ic):\n return False\n\n return True","async def test_dependencies(self):\n response = await self.collect(get_request_text=self.xml)\n expected_entities = [\n dict(\n key=\"12345\",\n url=\"https://owasp_dependency_check#l1_12345\",\n file_name=self.file_name,\n file_path=self.file_path,\n )\n ]\n self.assert_measurement(response, value=\"1\", entities=expected_entities)","def require(e):\n\n if e is True:\n return\n if any(unwrap(e).eq(a) for a in assumptions):\n return\n\n solver = get_solver()\n solver.add(unwrap(e))\n sat = solver.check()\n if sat == z3.unsat:\n raise RuntimeError(\"Unsatisfiable assumption %s\" % e)\n elif sat != z3.sat:\n raise RuntimeError(\"Uncheckable assumption %s\" % e)","def check(steps: Steps, error_message: str, condition) -> bool:\n if steps:\n step = steps.get_last_step()\n if not callable(condition):\n raise ValueError(\"The 'condition' argument \"\n \"must be a callable object\")\n else:\n if not condition():\n raise ValueError(error_message)\n else:\n step.set_status(Status.PASSED)\n return True\n\n return False","def test_if_true():\n\n true_values = [True, 1, 2.0, object(), \"foo\", int]\n assert all(true_values)\n\n def f_if():\n if x:\n print(\"x is True\")\n\n for x in true_values:\n check_component(\n prune_cfg,\n f_if,\n additional_bindings=dict(x=x),\n expected_source=\"\"\"\n def f_if():\n print('x is True')\n \"\"\",\n )\n\n def f_if_else():\n if x:\n print(\"x is True\")\n else:\n print(\"x is False\")\n\n check_component(\n prune_cfg,\n f_if_else,\n additional_bindings=dict(x=2),\n expected_source=\"\"\"\n def f_if_else():\n print(\"x is True\")\n \"\"\",\n )","def test_option_marked_correct(self):\r\n\r\n conditions = [\r\n {'input_type': 'radio', 'value': self.VALUE_DICT}]\r\n\r\n self.context['status'] = 'correct'\r\n\r\n for test_conditions in conditions:\r\n self.context.update(test_conditions)\r\n xml = self.render_to_xml(self.context)\r\n xpath = \"//section[@id='forinput1_choiceinput_0bc' and\\\r\n @class='choicetextgroup_correct']\"\r\n self.assert_has_xpath(xml, xpath, self.context)\r\n\r\n # Should NOT mark the whole problem\r\n xpath = \"//div[@class='indicator_container']/span\"\r\n self.assert_no_xpath(xml, xpath, self.context)","def condition(self) -> global___Expression:","def condition(self) -> global___Expression:","def check(self, description: Description) -> bool:","def test_conditional():\n # verify that conditioning increases the likelihood of getting a sample with the specified\n # categorical value","def is_satisfied(self, item: Any) -> bool:","def meetsreqs(request, requirements):\n for requirement in requirements:\n if requirement(request) == False:\n return False\n return True","def test_option_marked_correct(self):\r\n conditions = [\r\n {'input_type': 'radio', 'value': '2'},\r\n {'input_type': 'radio', 'value': ['2']}]\r\n\r\n self.context['status'] = Status('correct')\r\n\r\n for test_conditions in conditions:\r\n self.context.update(test_conditions)\r\n xml = self.render_to_xml(self.context)\r\n xpath = \"//label[@class='choicegroup_correct']\"\r\n self.assert_has_xpath(xml, xpath, self.context)\r\n\r\n # Should NOT mark the whole problem\r\n xpath = \"//div[@class='indicator_container']/span\"\r\n self.assert_no_xpath(xml, xpath, self.context)","def _assert_postconditions(postconditions: List[Contract], resolved_kwargs: Mapping[str, Any],\n func: CallableT) -> Optional[BaseException]:\n assert 'result' in resolved_kwargs, \\\n \"Expected 'result' to be already set in resolved kwargs before calling this function.\"\n\n for contract in postconditions:\n if inspect.iscoroutinefunction(contract.condition):\n raise ValueError(\"Unexpected coroutine (async) condition {} for a sync function {}.\".format(\n contract.condition, func))\n\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\n\n check = contract.condition(**condition_kwargs)\n\n if inspect.iscoroutine(check):\n raise ValueError(\"Unexpected coroutine resulting from the condition {} for a sync function {}.\".format(\n contract.condition, func))\n\n if not_check(check=check, contract=contract):\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\n\n return exception\n\n return None","def _assert_preconditions(preconditions: List[List[Contract]], resolved_kwargs: Mapping[str, Any],\n func: CallableT) -> Optional[BaseException]:\n exception = None # type: Optional[BaseException]\n\n # Assert the preconditions in groups. This is necessary to implement \"require else\" logic when a class\n # weakens the preconditions of its base class.\n\n for group in preconditions:\n exception = None\n\n for contract in group:\n assert exception is None, \"No exception as long as pre-condition group is satisfiable.\"\n\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\n\n if inspect.iscoroutinefunction(contract.condition):\n raise ValueError(\"Unexpected coroutine (async) condition {} for a sync function {}.\".format(\n contract.condition, func))\n\n check = contract.condition(**condition_kwargs)\n\n if inspect.iscoroutine(check):\n raise ValueError(\"Unexpected coroutine resulting from the condition {} for a sync function {}.\".format(\n contract.condition, func))\n\n if not_check(check=check, contract=contract):\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\n break\n\n # The group of preconditions was satisfied, no need to check the other groups.\n if exception is None:\n break\n\n return exception","def test_check_model_dependencies_complete(dependency_testing_model, complete_env) -> None:\n assert check_model_dependencies(\n model_cls=dependency_testing_model,\n environment=complete_env,\n raise_for_missing=False,\n )","def condition(self):\n return True","def test_nested():\n res = conf.status.conditions.choose(lambda c: (c.type, c.reason, c.root.metadata.choose(lambda m: (m[\"name\"], m.uid))))\n assert \"type\" in res # from conditions\n assert \"reason\" in res # from conditions\n assert \"name\" in res # from metadata\n assert \"uid\" in res # from metadata","def test_headlines_required(self) -> None:\n for rule in self.rules.headlines:\n if not rule.required:\n continue\n is_match: bool = False\n for headline in self.report.headlines:\n if self.rules.get_headline_rules(headline.name) == rule:\n is_match = True\n break\n if not is_match:\n self.add_error(f\"Rubriken {rule.name} som måste vara med saknas.\")","def test_condition_split(self):\n self.write_contents(\n 'external/wpt/fail.html.ini', \"\"\"\\\n [fail.html]\n expected:\n if product == \"content_shell\": FAIL\n \"\"\")\n self.update(\n {\n 'run_info': {\n 'product': 'content_shell',\n 'os': 'mac',\n 'port': 'mac12',\n },\n 'results': [{\n 'test': '/fail.html',\n 'status': 'TIMEOUT',\n 'expected': 'FAIL',\n }],\n }, {\n 'run_info': {\n 'product': 'content_shell',\n 'os': 'win',\n 'port': 'win11',\n },\n 'results': [{\n 'test': '/fail.html',\n 'status': 'FAIL',\n 'expected': 'FAIL',\n }],\n }, {\n 'run_info': {\n 'product': 'chrome',\n 'os': 'linux',\n 'port': 'trusty',\n },\n 'results': [{\n 'test': '/fail.html',\n 'status': 'PASS',\n 'expected': 'PASS',\n }],\n },\n overwrite_conditions='yes')\n path = self.finder.path_from_web_tests('external', 'wpt',\n 'fail.html.ini')\n lines = self.tool.filesystem.read_text_file(path).splitlines()\n expected = textwrap.dedent(\"\"\"\\\n [fail.html]\n expected:\n if (product == \"content_shell\") and (os == \"win\"): FAIL\n if (product == \"content_shell\") and (os == \"mac\"): TIMEOUT\n \"\"\")\n # TODO(crbug.com/1299650): The branch order appears unstable, which we\n # should fix upstream to avoid create spurious diffs.\n self.assertEqual(sorted(lines, reverse=True), expected.splitlines())","def Require(condition):\n if not condition:\n Revert()\n return True","def check(self,):\n self.is_valid_according_policy()","def check_explicit_data_dependency( # noqa: C901\n self,\n context: SlicingContext,\n unique_instr: UniqueInstruction,\n traced_instr: ExecutedInstruction | None,\n ) -> tuple[bool, set[str]]:\n complete_cover = False\n partial_cover = False\n attribute_creation_uses = set()\n\n if not unique_instr.is_def():\n return False, set()\n\n # Check variable definitions\n if isinstance(traced_instr, ExecutedMemoryInstruction):\n complete_cover = self._check_variables(context, traced_instr)\n\n # When an object, of which certain used attributes are taken from,\n # is created, the slicer has to look for the definition of normal variables\n # instead of these attributes, since they are defined as variables and not\n # as attributes on class/module level.\n if traced_instr.arg_address and traced_instr.object_creation:\n attribute_uses = set()\n for use in context.attr_uses:\n if use.startswith(hex(traced_instr.arg_address)) and len(use) > len(\n hex(traced_instr.arg_address)\n ):\n complete_cover = True\n attribute_uses.add(use)\n attribute_creation_uses.add(\"_\".join(use.split(\"_\")[1:]))\n for use in attribute_uses:\n context.attr_uses.remove(use)\n\n # Check for address dependencies\n if traced_instr.is_mutable_type and traced_instr.object_creation:\n # Note that the definition of an object here means the\n # creation of the object.\n address_dependency = self._check_scope_for_def(\n context.var_uses_addresses,\n hex(traced_instr.arg_address),\n None,\n None,\n )\n if address_dependency:\n complete_cover = True\n\n # Check for the attributes which were converted to variables\n # (explained in the previous construct)\n if traced_instr.argument in context.attribute_variables:\n complete_cover = True\n context.attribute_variables.remove(str(traced_instr.argument))\n\n if isinstance(traced_instr, ExecutedAttributeInstruction):\n # check attribute defs\n if traced_instr.combined_attr in context.attr_uses:\n complete_cover = True\n context.attr_uses.remove(traced_instr.combined_attr)\n # Partial cover: modification of attribute of\n # object in search for definition\n if hex(traced_instr.src_address) in context.var_uses_addresses:\n partial_cover = True\n\n return (complete_cover or partial_cover), attribute_creation_uses","def validate_dependence_versions():\n print('Total {} instances defined'.format(len(ReleaseInfo.all_instance_releases())))\n all_instance_releases = ReleaseInfo.all_instance_releases()\n\n # Validate dependencies: each dependence should have a valid\n # version as in defined range\n for instance_name, versions in all_instance_releases.items():\n for instance_version, release_info in versions.items():\n dependencies = release_info.dependencies\n for dep in dependencies:\n dep_type = dep.type\n minv = dep.min_version\n maxv = dep.max_version\n\n assert dep_type in all_instance_releases, \\\n \"No dependence found {} for version {} of {}\" \\\n .format(dep_type, instance_version, instance_name)\n\n found = _find_a_ranged_version(dep_type, minv=minv, maxv=maxv)\n assert found, \"No valid version defined for {} with max: {}, min: {}\" \\\n .format(dep_type, maxv, minv)","def validate(self):\n super(PipelineContext, self).validate()\n for instrument, imap in self.selections.normal_items():\n self._check_nested(\"instrument\", instrument, imap)\n\n # Will raise pkg_resources.RequirementParseError if the requirement\n # is malformed:\n self.get_asdf_standard_requirement()","def check(self):\n for req in self.requirements:\n if not self.COMPARISON_OPERATORS[req.operator](\n packaging.version.parse(get_installed_version(req.package)),\n packaging.version.parse(req.version),\n ):\n fail(f\"The cluster requires {req.package}{req.operator}{req.version}\")","def test_KidsFirstResearchStudy_Condition(kids_first_research_studies_with_observations):\n _validate_ResearchStudy_Condition(kids_first_research_studies_with_observations)","def test_java(self, condition, undefined_paths, current_path):\n cond_id = str(condition.get('id'))\n\n try:\n cid = str(condition.find('class').text)\n except AttributeError:\n current_path += ((cond_id, 'ill-defined java condition'),)\n undefined_paths.add(current_path)\n return False\n\n if not cid:\n current_path += ((cid, 'ill-defined java condition'),)\n undefined_paths.add(current_path)\n return False\n\n classes = self.verifier.get_container('classes').get_keys()\n if not cid in classes:\n current_path += ((cid, 'java class'),)\n undefined_paths.add(current_path)\n return False","def test_check_is_required(fake_check):\n assert fake_check.is_required()","def test_variable(self, condition, undefined_paths, current_path):\n var = str(condition.find('name').text)\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\n current_path += ((var, 'undefined variable'),)\n undefined_paths.add(current_path)\n return False\n else:\n return True","def test_falsifications(self):\n implications = get_conditional_independencies(asia_example.graph)\n issues = get_falsifications(implications, asia_example.data)\n self.assertEqual(0, len(issues.failures))\n self.assertEqual(len(issues.evidence), len(implications))","def _parse(self, engine):\n\t\tself.condition = engine.evaluate(self.args, recursive=True)\n\t\tif not self.condition:\n\t\t\traise AssertionError('\"assert\" layer failed. Condition evaluated '\n\t\t\t\t'to: {} (type={})'.format(\n\t\t\t\t\tself.condition,\n\t\t\t\t\ttype(self.condition)\n\t\t\t\t))","def checkRequiredDependencies(self):\n \n # skip dependency check for downloading only\n if( self.downloadOnly ):\n return\n\n # hard dependencies\n for req in self.reqmodules:\n if( self.parent.module(req) == None ):\n # check if there is an auto detected module\n if( self.parent.module(req, True) == None ):\n self.abort( self.name + \" requires \" + req \\\n + \" and it wasn't found in your config file!!\" )\n else:\n # use auto detected module\n self.parent.use( self.parent.module(req, True) )\n self.parent.module( req ).init()\n\n print self.name + \": auto-detected \" + req + \" version \" + self.parent.module( req ).version\n \n # build only dependencies\n if( self.mode == \"install\" ):\n mods = self.reqmodules_buildonly + self.reqmodules_external\n for req in mods:\n if( self.parent.module(req) == None ):\n # check if there is an auto detected module\n if( self.parent.module(req, True) == None ):\n self.abort( req + \" not found in your config file!! \" + self.name \\\n + \" cannot be built without \" + req )\n else:\n # use auto detected module\n self.parent.use( self.parent.module(req, True) )\n self.parent.module( req ).init()\n\n print \" - \" + self.name + \": auto-detected \" + req + \" version \" + self.parent.module( req ).version","def testConditionsAreOrdered(self):\n self.Check(\"\"\"\n from __future__ import google_type_annotations\n from typing import Optional\n def f(x: Optional[NoneType]) -> int:\n if x is not None:\n x = None\n if x is None:\n x = 1\n return x\n \"\"\")","def satisfy(self):\n self.stub.Satisfy(\n depend_pb2.DependSatisfyRequest(depend=self.data), timeout=Cuebot.Timeout)","def _assert_pip_requirements(model_uri, requirements, constraints=None, strict=False):\n local_path = _download_artifact_from_uri(model_uri)\n txt_reqs = _read_lines(os.path.join(local_path, _REQUIREMENTS_FILE_NAME))\n conda_reqs = _get_pip_deps(_read_yaml(\n os.path.join(local_path, _CONDA_ENV_FILE_NAME)))\n compare_func = set.__eq__ if strict else set.__le__\n requirements = set(requirements)\n assert compare_func(requirements, set(txt_reqs))\n assert compare_func(requirements, set(conda_reqs))\n\n if constraints is not None:\n assert f\"-c {_CONSTRAINTS_FILE_NAME}\" in txt_reqs\n assert f\"-c {_CONSTRAINTS_FILE_NAME}\" in conda_reqs\n cons = _read_lines(os.path.join(local_path, _CONSTRAINTS_FILE_NAME))\n assert compare_func(set(constraints), set(cons))","def condition_for_function(f, abi, all_not_in_ABI):\n\n\tcondition = []\n\tfor n in f.entry_points:\n\t\t[category, num] = api.get_category_for_name( n )\n\t\tif category not in abi:\n\t\t\tcondition.append( 'defined(need_%s)' % (gl_XML.real_category_name( category )) )\n\t\telif all_not_in_ABI:\n\t\t\treturn []\n\n\treturn condition","def input_check(self):\n\n if self.species == 'He': assert self.line_model == 'voigt'\n n_upper_range, e_dens_range, temp_range, b_field_range = get_param_ranges(self.line_model)\n\n if np.isnan(n_upper_range).sum() <= 1:\n assert (self.n_upper in range(n_upper_range[0], n_upper_range[1]))\n if np.isnan(e_dens_range).sum() <= 1:\n assert (e_dens_range[0] <= self.e_dens <= e_dens_range[1])\n if np.isnan(temp_range).sum() <= 1:\n assert (temp_range[0] <= self.temp <= temp_range[1])\n if np.isnan(b_field_range).sum() <= 1:\n assert (b_field_range[0] <= self.b_field <= b_field_range[1])"],"string":"[\n \"def testConditionChecking(self):\\n\\n state = State.from_problem(self.prob)\\n \\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition))\\n\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt2\\\"], self.prob):\\n self.assertFalse(state.is_satisfied(drive.precondition))\",\n \"def testConditionReasons(self):\\n \\n state = State.from_problem(self.prob)\\n\\n relevantVars = []\\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\\n\\n relevantVars = set(relevantVars)\\n \\n s1 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"pos1\\\"]])\\n s2 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"apt1\\\"]])\\n s3 = StateVariable(self.prob.functions[\\\"location-of\\\"][0], [self.prob[\\\"tru1\\\"]])\\n \\n self.assertEqual(len(relevantVars), 3)\\n self.assert_(s1 in relevantVars)\\n self.assert_(s2 in relevantVars)\\n self.assert_(s3 in relevantVars)\",\n \"def test_verify_dependencies(self, cond_id, conditions):\\n\\n if not cond_id in conditions.get_keys():\\n return 1\\n else:\\n result = self.verify_dependencies(cond_id)\\n return result\",\n \"def _check_conditional_dependency(obj, condition, package, severity, msg=None):\\n if condition:\\n if msg is None:\\n msg = (\\n f\\\"The specific parameter values of {obj.__class__.__name__}'s \\\"\\n f\\\"class instance require `{package}` installed. Please run: \\\"\\n f\\\"`pip install {package}` to \\\"\\n f\\\"install the `{package}` package. \\\"\\n )\\n try:\\n _check_soft_dependencies(package, severity=severity, obj=obj)\\n except ModuleNotFoundError as e:\\n raise ModuleNotFoundError(msg) from e\",\n \"def valid_dependency(self, dep):\\r\\n return True\",\n \"def _alert_condition(self, soup: BeautifulSoup) -> bool:\\n raise NotImplementedError()\",\n \"def dependencies_satisfied(self, module) -> bool:\\n for k, v in module.requirements.items():\\n if k not in self.modules:\\n return False\\n found_ver = self.modules[k].version\\n if isinstance(v, str):\\n return found_ver == v\\n elif isinstance(v, dict):\\n if \\\"eq\\\" in v and (found_ver != v[\\\"eq\\\"]):\\n return False\\n if \\\"min\\\" in v and (found_ver < v[\\\"min\\\"]):\\n return False\\n if \\\"max\\\" in v and (found_ver > v[\\\"max\\\"]):\\n return False\\n else:\\n return True\\n return True\",\n \"def test_condition_syntax(self):\\n\\n base = abs_path('./specs/')\\n ps = Parser(base+'script3-1.py', base)\\n\\n spec = {'constraints': [{'block': 'A', 'condition': 'B=b1'}]}\\n with self.assertRaises(ParseError):\\n read_wrapper(spec, ps)\\n\\n spec = {'constraints': [{'block': 'A', 'condition': 'B b1'}]}\\n with self.assertRaises(ParseError):\\n read_wrapper(spec, ps)\\n\\n spec = {'constraints': [{'block': 'A', 'condition': 'B == 2.5'}]}\\n read_wrapper(spec, ps)\",\n \"def satisfied(self, fields, field, values):\\n\\n requires = field.get(\\\"requires\\\", [])\\n\\n if isinstance(requires, str):\\n requires = [requires]\\n\\n for require in requires:\\n if require not in fields or not fields[require].validate(store=False):\\n return False\\n\\n if \\\"condition\\\" in field and self.env.from_string(field[\\\"condition\\\"]).render(**values) != \\\"True\\\":\\n return False\\n\\n return True\",\n \"def test_available(self):\\n feature_guard = _make_requires(True, \\\"Error text\\\")\\n results = []\\n\\n @feature_guard\\n def inner():\\n results.append(True)\\n return True\\n\\n assert inner() is True\\n assert [True] == results\",\n \"def test_empty_condition(self):\\n assert_that(Condition.is_valid(''), equal_to(True))\",\n \"def conditions():\\n pass\",\n \"def test_verify_all_dependencies(self):\\n\\n for condition in self.all_references():\\n result = self.verify_dependencies(condition)\\n\\n if result:\\n self.ill_defined[condition] = result\\n else:\\n self.well_defined.add(condition)\\n\\n return self.ill_defined\",\n \"def check_requirements(self): # pylint: disable=no-self-use\\n self.is_skipped = False\",\n \"def check_condition(self):\\n\\n\\t\\traw_context = {\\n\\t\\t\\t'folk': self.folk\\n\\t\\t}\\n\\n\\t\\tstatus, param = self.execute(self.mission_grid, 'condition', self.pending_mission.kingdom, raw_context)\\n\\t\\treturn status\",\n \"def check_requirements(config=None):\\n for dependency, module_requirements in (\\n requirements(config, include_conditional=False).items()):\\n for module_requirement in module_requirements:\\n if \\\">=\\\" in module_requirement:\\n module_name, required_version = module_requirement.split(\\\">=\\\")\\n version_test = \\\">=\\\"\\n elif \\\"==\\\" in module_requirement:\\n module_name, required_version = module_requirement.split(\\\"==\\\")\\n version_test = \\\"==\\\"\\n else:\\n module_name = module_requirement\\n version_test = None\\n\\n try:\\n module = __import__(module_name)\\n except ImportError:\\n logging.exception(\\n \\\"Can't import %r which is part of %r\\\",\\n module_name, dependency\\n )\\n raise MissingRequirementError(\\n \\\"Can't import %r which is part of %r\\\"\\n % (module_name, dependency), module_name, dependency\\n )\\n version = getattr(module, \\\"__version__\\\", None)\\n file_path = getattr(module, \\\"__file__\\\", None)\\n logger.info(\\n \\\"Using %r version %r from %r to satisfy %r\\\",\\n module_name, version, file_path, dependency\\n )\\n\\n if version_test == \\\">=\\\":\\n if version is None:\\n raise MissingRequirementError(\\n \\\"Version of %r isn't set as __version__ of module %r\\\"\\n % (dependency, module_name), module_name, dependency\\n )\\n if LooseVersion(version) < LooseVersion(required_version):\\n raise MissingRequirementError(\\n \\\"Version of %r in %r is too old. %r < %r\\\"\\n % (dependency, file_path, version, required_version),\\n module_name, dependency\\n )\\n elif version_test == \\\"==\\\":\\n if version is None:\\n raise MissingRequirementError(\\n \\\"Version of %r isn't set as __version__ of module %r\\\"\\n % (dependency, module_name), module_name, dependency\\n )\\n if LooseVersion(version) != LooseVersion(required_version):\\n raise MissingRequirementError(\\n \\\"Unexpected version of %r in %r. %r != %r\\\"\\n % (dependency, file_path, version, required_version),\\n module_name, dependency\\n )\",\n \"def test_AnvilResearchStudy_Condition(anvil_research_studies_with_observations):\\n _validate_ResearchStudy_Condition(anvil_research_studies_with_observations)\",\n \"def _isCondition(self, column):\\n\\n for _, values in self._model.parameters.items():\\n if column in values['depends']:\\n return True\\n return False\",\n \"def test_are_dependency_packs_valid(self, current_file, id_set, answer):\\n validator = get_validator(current_file)\\n assert validator.are_dependency_packs_valid(id_set) is answer\",\n \"def test_zt_requirement(self):\\n test_passes = False\\n try:\\n self.parser.extract_zt(\\\"FOOBAR\\\")\\n test_passes = False\\n except:\\n test_passes = True\\n self.assertTrue(test_passes)\",\n \"def condition_forward_checking(csp, var) :\\n return False\",\n \"def condition_forward_checking(csp, var) :\\n return False\",\n \"def check_condition(self, comment):\\n if comment.id in self.touched_comment_ids:\\n return False, None\\n # First check for keywords in comment, for now we don't care about formatting after the keyword\\n has_keyword = self.check_word_in_list_in_string(self.keywords, comment.body)\\n if not has_keyword:\\n return False, None\\n # Next we check if we have states or abbreviations\\n abbrevs = self.check_comment_for_dictionary_keys_and_values(comment, self.states)\\n if len(abbrevs) < 1:\\n return False, None\\n if str(comment.author) == self.bot_name:\\n return False, None\\n for reply in comment.replies:\\n if str(reply.author) == self.bot_name:\\n return False, None\\n\\n return True, abbrevs\",\n \"def testConditionBuilderErrors(self):\\n\\t\\ttests = [r'2elem==1', r'elem=<3', r'elem == 0xXY']\\n\\n\\t\\tfor test in tests:\\n\\t\\t\\tself.assertRaises(ParserError, parseSearchCondition, test)\",\n \"def testConditionalEffects(self):\\n \\n action = Parser.parse_as(cond_load.split(\\\"\\\\n\\\"), Action, self.domain)\\n\\n self.assert_(isinstance(action.effect, ConditionalEffect))\\n self.assert_(isinstance(action.effect.condition, conditions.LiteralCondition))\\n self.assert_(isinstance(action.effect.effect, SimpleEffect))\",\n \"def is_valid(self):\\n return not self.missing_from_disk and not self.missing_dependency\",\n \"def __satisfies_necessary_and_sufficient_conditions(g):\\n # Condition 0: at least 1 Edge\\n if g.get_E() == 0:\\n return False\\n # Condition 1: indegree(v) == outdegree(v) for every vertex\\n for v in range(g.get_V()):\\n if g.outdegree() != g.indegree(v):\\n return False\\n # Condition 2: graph is connected, ignoring isolated vertices\\n h = Graph(g.get_V())\\n for v in range(g.get_V()):\\n for w in g.adj_vertices(v):\\n h.add_edge(v, w)\\n # check that all non-isolated vertices are connected\\n s = DirectedEulerianCycle.__non_isolated_vertex(g)\\n bfs = BreadthFirstPaths(h, s)\\n for v in range(g.get_V()):\\n if h.degree(v) > 0 and not bfs.has_path_to(v):\\n return False\\n return True\",\n \"def are_all_deps_fulfilled(self, package: 'Package', only_make_check: bool = False,\\n only_depends: bool = False, print_reason: bool = False) -> bool:\\n\\n for dep in package.relevant_deps(only_make_check=only_make_check, only_depends=only_depends):\\n if not self.provided_by(dep):\\n if print_reason:\\n aurman_note(\\n \\\"Dependency {} of package {} is not fulfilled\\\".format(\\n Colors.BOLD(Colors.LIGHT_MAGENTA(dep)),\\n Colors.BOLD(Colors.LIGHT_MAGENTA(package.name))\\n )\\n )\\n return False\\n else:\\n return True\",\n \"def _sufficient_deps(cls, deps):\\n if cls.MODEL_PACKAGE is None:\\n return True\\n else:\\n for d in deps.conda:\\n if cls.MODEL_PACKAGE in d:\\n return True\\n for d in deps.pip:\\n if cls.MODEL_PACKAGE in d:\\n return True\\n return False\",\n \"def test_check_job_dependencies_prior_dependency_has_errors(database):\\n sess = database.session\\n sub = SubmissionFactory(submission_id=1)\\n job = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['finished'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'],\\n number_of_errors=3)\\n job_2 = JobFactory(submission_id=sub.submission_id, job_status_id=JOB_STATUS_DICT['waiting'],\\n job_type_id=JOB_TYPE_DICT['csv_record_validation'], file_type_id=FILE_TYPE_DICT['award'])\\n sess.add_all([sub, job, job_2])\\n sess.commit()\\n\\n # Job 1 finished, it is a prerequisite for job 2 (waiting) but it has errors\\n job_dep = JobDependency(job_id=job_2.job_id, prerequisite_id=job.job_id)\\n sess.add(job_dep)\\n sess.commit()\\n\\n check_job_dependencies(job.job_id)\\n\\n assert job_2.job_status_id == JOB_STATUS_DICT['waiting']\",\n \"def dependencies_met():\\n # Check Java VM command line runner.\\n try:\\n Popen(['java'], shell=False, stderr=PIPE).communicate()[1]\\n except:\\n print 'Dependecy unmet. Java virtual machine command line runner not ' \\\\\\n 'found.'\\n return False\\n # Check selenium-server.jar is ready to run.\\n output = Popen(('java -jar %s -unrecognized_argument' % SELENIUM_RC_PATH\\n ).split(), shell=False, stderr=PIPE).communicate()[1]\\n if not re.search('Usage: java -jar selenium-server.jar', output):\\n print 'Dependecy unmet. Selenium RC server (selenium-server.jar) not ' \\\\\\n 'found.'\\n return False\\n # Check selenium RC python driver is available.\\n try:\\n import selenium\\n except:\\n print 'Dependecy unmet. Selenium RC python driver (selenium.py) not ' \\\\\\n 'found.'\\n return False\\n # Check CherryPy wsgi server is available.\\n try:\\n import wsgiserver\\n except:\\n print 'Dependecy unmet. CherryPy wsgi server (wsgiserver.py) not found.'\\n return False\\n # Check fixture support is implemented for the database engine.\\n if not settings.DATABASE_ENGINE in ['sqlite3', 'postgresql_psycopg2']:\\n print 'Dependecy unmet. Fixture support for database engine %s not ' \\\\\\n 'implemented.' % settings.DATABASE_ENGINE\\n return False\\n return True\",\n \"def check_prerequisites(self, prequisites):\\n for prereq in prequisites:\\n # check for origin requirements\\n if prereq.origin: \\n if prereq.origin not in self.origins:\\n print(f\\\"ORIGIN WRONG\\\")\\n return False\\n # check for additional header requirements\\n if prereq.additional_header:\\n if (not prereq.additional_header.open_flag and \\n prereq.additional_header not in self.headers.all()):\\n print(f\\\"WE DONT HAVE THE RIGHT HEADER SELECTED\\\")\\n return False \\n # check for header/skill requirements\\n # did the user purchase the required header, or is the header open?\\n if prereq.header:\\n if (not prereq.header.open_flag and \\n prereq.header not in self.headers.all()):\\n print(f\\\"WE DONT HAVE THE RIGHT HEADER SELECTED\\\")\\n return False \\n # check for the number of different skills in the header.\\n purchased_skills = HeaderSkill.objects.filter(\\n header=prereq.header,\\n skill__id__in=self.skills.values_list('skill__skill_id', flat=True)\\n )\\n if prereq.number_of_different_skills > purchased_skills.count(): \\n print(f\\\"NUMBER OF SKILLS WRONG:{prereq.number_of_different_skills}:{purchased_skills.count()}\\\")\\n return False\\n # figure out the total skill points\\n total = 0\\n for skill in purchased_skills:\\n total += skill.header.cost * skill.characterskills_set.get(character=self).count\\n # check for skill requirements\\n if prereq.skill:\\n try:\\n result = self.skills.get(skill__skill=prereq.skill)\\n return result.count >= prereq.number_of_purchases\\n except CharacterSkills.DoesNotExist:\\n return False\\n # if we made it this far, we can assume all prerequisites\\n # have been met.\\n return True\",\n \"def testConditionBuilder(self):\\n\\t\\ttests = {\\n\\t\\t\\tr'elem==1': [['elem'], op.EQ, 1],\\n\\t\\t\\tr'(elem==2)': [[['elem'], op.EQ, 2]],\\n\\t\\t\\tr'elem > 1 and elem2 < 5.54':\\n\\t\\t\\t\\t[['elem'], op.GT, 1, op.AND, ['elem2'], op.LT, 5.54],\\n\\t\\t\\tr'not elem <= \\\"aaa\\\" and not elem2 ~ \\\"zzz\\\"':\\n\\t\\t\\t\\t[op.NOT, ['elem'], op.LTE, \\\"aaa\\\", op.AND, op.NOT,\\n\\t\\t\\t\\t['elem2'], op.REGEXP, \\\"zzz\\\"],\\n\\t\\t\\tr'not (elem.abc.def == 0xabcd) and (elem2 < 3)':\\n\\t\\t\\t\\t[op.NOT, [['elem', 'abc', 'def'], op.EQ, b\\\"\\\\xab\\\\xcd\\\"],\\n\\t\\t\\t\\top.AND, [['elem2'], op.LT, 3]],\\n\\t\\t\\tr'not (elem.2 != 4) or (not key.2.3 != 1) and not key.1 !~ \\\"abc\\\"':\\n\\t\\t\\t\\t[op.NOT, [op.NOT, ['elem', 2], op.EQ, 4], op.OR,\\n\\t\\t\\t\\t[['key', 2, 3], op.EQ, 1], op.AND,\\n\\t\\t\\t\\t['key', 1], op.REGEXP, 'abc'],\\n\\t\\t\\tr'and == 2': [['and'], op.EQ, 2],\\n\\t\\t\\tr'': None\\n\\t\\t}\\n\\n\\t\\tfor test in tests:\\n\\t\\t\\tself.assertEqual(tests[test], parseSearchCondition(test))\",\n \"def assert_single_condition_and_sbml_file(problem_config: Dict) -> None:\\n if (len(problem_config[SBML_FILES]) > 1\\n or len(problem_config[CONDITION_FILES]) > 1):\\n # TODO https://github.com/ICB-DCM/PEtab/issues/188\\n # TODO https://github.com/ICB-DCM/PEtab/issues/189\\n raise NotImplementedError(\\n 'Support for multiple models or condition files is not yet '\\n 'implemented.')\",\n \"def _check_criteria(dep, dep_obj, all_related, edge, sibling_idx):\\n # Check for a matching dependency type\\n related = []\\n\\n if edge[2][\\\"dep\\\"] == dep:\\n # Check for matching POS type(s)\\n for pos_logic in dep_obj.keys():\\n connector = None\\n\\n if isinstance(dep_obj[pos_logic], dict):\\n for pos in dep_obj[pos_logic].keys():\\n\\n # Check for allowed part of speech tags in matched dependency patterns\\n if (pos_logic == \\\"pos_in\\\" and pos in G.nodes[sibling_idx][\\\"pos\\\"]) or (\\n pos_logic == \\\"pos_equals\\\" and pos == G.nodes[sibling_idx][\\\"pos\\\"]):\\n pass\\n elif pos_logic == \\\"pos_not\\\":\\n if not [False if not_pos == G.nodes[sibling_idx][\\\"pos\\\"] else True for not_pos in\\n dep_obj.keys()]: continue\\n else:\\n continue\\n\\n # if no additional checks, have a match\\n if dep_obj[pos_logic][pos] == None or any(\\n y in dep_obj[pos_logic][pos] for y in [None, \\\"add_sibling\\\"]):\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']])\\n\\n # if additional checks are required, process further\\n if dep_obj[pos_logic][pos]:\\n if \\\"get_cousin\\\" in dep_obj[pos_logic][pos]:\\n related.extend(_get_cousin(sibling_idx, dep_obj[pos_logic][pos][\\\"get_cousin\\\"]))\\n connector = G.nodes[sibling_idx]['word']\\n\\n if \\\"special\\\" in dep_obj[pos_logic][pos]:\\n if dep == \\\"compound\\\" and pos == \\\"NN\\\":\\n related = [G.nodes[sibling_idx]['word']]\\n\\n if None in related:\\n related.remove(None)\\n\\n # Allows for getting cousin and returning sibling\\n if \\\"else\\\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\\\"else\\\"] == \\\"always\\\":\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\\n if len(related) > 0 and isinstance(related, list):\\n for x in related:\\n if x != None:\\n all_related = _add_related(x, dep, all_related, A.index_lookup[x],\\n connector=connector)\\n elif \\\"else\\\" in dep_obj[pos_logic][pos].keys() and dep_obj[pos_logic][pos][\\\"else\\\"] == True:\\n all_related = _add_related(G.nodes[sibling_idx]['word'], dep, all_related,\\n A.index_lookup[G.nodes[sibling_idx]['word']], connector=connector)\\n\\n return all_related\",\n \"def check_requirement(self):\\n raise NotImplementedError\",\n \"def dependencies_are_met(\\n self,\\n parent_job: Optional['Job'] = None,\\n pipeline: Optional['Pipeline'] = None,\\n exclude_job_id: Optional[str] = None,\\n ) -> bool:\\n connection = pipeline if pipeline is not None else self.connection\\n\\n if pipeline is not None:\\n connection.watch(*[self.key_for(dependency_id) for dependency_id in self._dependency_ids])\\n\\n dependencies_ids = {_id.decode() for _id in connection.smembers(self.dependencies_key)}\\n\\n if exclude_job_id:\\n dependencies_ids.discard(exclude_job_id)\\n if parent_job and parent_job.id == exclude_job_id:\\n parent_job = None\\n\\n if parent_job:\\n # If parent job is canceled, treat dependency as failed\\n # If parent job is not finished, we should only continue\\n # if this job allows parent job to fail\\n dependencies_ids.discard(parent_job.id)\\n if parent_job.get_status() == JobStatus.CANCELED:\\n return False\\n elif parent_job._status == JobStatus.FAILED and not self.allow_dependency_failures:\\n return False\\n\\n # If the only dependency is parent job, dependency has been met\\n if not dependencies_ids:\\n return True\\n\\n with connection.pipeline() as pipeline:\\n for key in dependencies_ids:\\n pipeline.hget(self.key_for(key), 'status')\\n\\n dependencies_statuses = pipeline.execute()\\n\\n allowed_statuses = [JobStatus.FINISHED]\\n if self.allow_dependency_failures:\\n allowed_statuses.append(JobStatus.FAILED)\\n\\n return all(status.decode() in allowed_statuses for status in dependencies_statuses if status)\",\n \"def uses_requirement(requirement, field):\\n\\n if hasattr(field.requires, \\\"other\\\") or requirement in str(field.requires):\\n if hasattr(field.requires, \\\"other\\\"):\\n if requirement in str(field.requires.other):\\n return True\\n elif requirement in str(field.requires):\\n return True\\n return False\",\n \"def requirement_is_satisfied(requirement, working_set, newest):\\n\\n if newest: return False\\n\\n try:\\n working_set.require(requirement)\\n return True\\n except:\\n pass\\n\\n return False\",\n \"def evaluate_package_conditions(package, ros_distro):\\n # Conditional fields were introduced in package format 3.\\n # Earlier formats should have their conditions evaluated with no context so\\n # the evaluated_condition is set to True in all cases.\\n if package.package_format >= 3:\\n package.evaluate_conditions(package_conditional_context(ros_distro))\",\n \"def condition_is_valid(self):\\n cond = self.condition.lower()\\n cond = re.sub('\\\\s+', ' ', cond)\\n\\n for ap in self.available_functions:\\n ap = ap.lower()\\n\\n ret = re.search(ap, cond)\\n if ret:\\n # [('a', 'b'), ('a', 'b'), ...]\\n self.used_functions[ap] = re.findall(ap, cond)\\n cond = re.sub(ap, ' ', cond)\\n\\n # print self.used_functions\\n for op in ['and', 'or', 'not']:\\n cond = re.sub('\\\\s%s\\\\s' % op, ' ', cond)\\n\\n cond = re.sub('\\\\(', '', cond)\\n cond = re.sub('\\\\)', '', cond)\\n cond = re.sub('\\\\s+', '', cond)\\n\\n return len(cond) == 0\",\n \"def validate_dom_elem(check, js=False):\\n if js:\\n known_elems = [x[0] for x in dm.DOMElem.query.with_entities(dm.DOMElem.js_name)]\\n else:\\n known_elems = [x[0] for x in dm.DOMElem.query.with_entities(dm.DOMElem.bs_name)]\\n if check not in known_elems:\\n raise InvalidDOMElem(f\\\"Provided Parent element does not match any {'JavaScript' if js else 'BeautifulSoup'} element tag listed in basketbot DB\\\")\",\n \"def test_headlines_dependencies(self) -> None:\\n\\n def has_dep(dep: str) -> bool:\\n for h in self.report.headlines:\\n if self.rules.get_headline_rules(\\n h.name\\n ) == self.rules.get_headline_rules(dep):\\n return True\\n return False\\n\\n for headline in self.report.headlines:\\n rule: Optional[HeadlineRules] = self.rules.get_headline_rules(headline.name)\\n if not rule:\\n continue\\n\\n for dependency_group in rule.dependencies:\\n is_match: bool = False\\n for dependency in dependency_group:\\n if has_dep(dependency):\\n is_match = True\\n break\\n if not is_match:\\n dependencies_list: str = \\\", \\\".join(dependency_group)\\n self.add_error(\\n f\\\"Rubriken {headline.name} kräver att en av följande \\\"\\n f\\\"rubriker finns med i dokumentet: {dependencies_list}.\\\",\\n headline=headline,\\n )\",\n \"def satisfyRequirements(path):\\n if not hasVerb(path):\\n return False\\n if not hasConceptsAtTheEnds(path):\\n return False\\n if not isConceptDefinition(path):\\n return False\\n\\n return True\",\n \"def validate_dependencies(self, session, entry):\",\n \"def has_required(self) -> bool:\\n return any(child.is_required() for child in self.children)\",\n \"def isConditional(self) -> bool:\\n ...\",\n \"def check_dependencies(target_binary, target_platform, target_architecture, target_type):\\n check_architecture(target_architecture)\\n check_platform(target_platform)\",\n \"def check_condition(self, element):\\n conditional = element.getAttribute(\\\"conditional\\\")\\n\\n # No condition, then we execute this statement.\\n #\\n if len(conditional) == 0:\\n return True\\n\\n # We have a conditional. See if it begins with a '!', which inverts\\n # our test.\\n #\\n result = True\\n oc = conditional\\n if conditional[0] == '!':\\n result = False\\n conditional = conditional[1:]\\n\\n if self.settings is not None and conditional in self.settings.ids:\\n if self.settings.value(conditional) is True:\\n return result\\n return not result\\n return not result\",\n \"def condition_satisfied (self, node, i) :\\n valid_options = []\\n for nnode in self.graph.next_nodes(node):\\n if self.val_l[nnode] == i :\\n return False\\n if (self.val_l[nnode] == self.undefined\\n or self.val_l[nnode] == self.infinity) :\\n valid_options.append(nnode)\\n for options in valid_options:\\n if i not in self.graph.next_nodes(options) :\\n return False\\n return True\",\n \"def _validate_order(self, order, account, quotation, strategy_name):\\n if quotation.volume < order.volume:\\n print('Limit volume bardata volume:%d, untraded volume:%d, date:%s' % \\n (quotation.volume, order.volume, quotation.date))\\n return False\\n\\n # Calculate this order's margin\\n if order.offset == 'open': \\n posid = order.instrument+'-'+order.direction\\n margin_ratio = account.portfolios[strategy_name].positions[posid].margin_ratio = quotation.margin_ratio\\n multiplier = account.portfolios[strategy_name].positions[posid].multiplier = quotation.multiplier\\n margin = order.price * order.volume * margin_ratio * multiplier\\n if margin > account.available:\\n print('Lack of capital available:%f, margin:%f' % (account.available, margin))\\n return False\\n return True\\n elif order.offset == 'close':\\n if order.direction == 'long':\\n posid = order.instrument+'-'+'short'\\n elif order.direction == 'short':\\n posid = order.instrument+'-'+'long'\\n hold_posi_quantity = account.portfolios[strategy_name].positions[posid].total_position\\n try:\\n assert order.volume > 0, 'close volume need greater than zero %d'%(order.volume)\\n assert order.volume <= hold_posi_quantity, 'close volume need lower than hold posi quantity %d:%d'%(order.volume,\\n hold_posi_quantity)\\n except AssertionError as e:\\n #print(e)\\n return False\\n return True\\n elif order.offset == 'closetoday':\\n order.direction = 'long' if order.direction == 'short' else 'short'\\n posid = order.instrument+'-'+order.direction\\n td_hold_posi_quantity = account.portfolios[strategy_name].positions[posid].today_position\\n try:\\n assert order.volume < td_hold_posi_quantity, 'close today position need lower than today hold position'\\n except AssertionError as e:\\n print(e)\\n return False\\n return True\\n else:\\n return False\",\n \"def test_with_definitions():\\n soup = generate_case(\\\"with_definitions\\\")\\n\\n tests.html_schema_doc_asserts.assert_property_names(\\n soup,\\n [\\\"billing_address\\\", \\\"street_address\\\", \\\"city\\\", \\\"state\\\", \\\"futureProperty\\\", \\\"shipping_address\\\"],\\n )\\n tests.html_schema_doc_asserts.assert_types(\\n soup, [\\\"object\\\", \\\"object\\\", \\\"string\\\", \\\"string\\\", \\\"string\\\", \\\"null\\\", \\\"object\\\"]\\n )\\n tests.html_schema_doc_asserts.assert_required(soup, [False, True, True, True, False, False])\",\n \"async def _assert_preconditions_async(preconditions: List[List[Contract]],\\n resolved_kwargs: Mapping[str, Any]) -> Optional[BaseException]:\\n exception = None # type: Optional[BaseException]\\n\\n # Assert the preconditions in groups. This is necessary to implement \\\"require else\\\" logic when a class\\n # weakens the preconditions of its base class.\\n\\n for group in preconditions:\\n exception = None\\n\\n for contract in group:\\n assert exception is None, \\\"No exception as long as pre-condition group is satisfiable.\\\"\\n\\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\\n\\n if inspect.iscoroutinefunction(contract.condition):\\n check = await contract.condition(**condition_kwargs)\\n else:\\n check_or_coroutine = contract.condition(**condition_kwargs)\\n if inspect.iscoroutine(check_or_coroutine):\\n check = await check_or_coroutine\\n else:\\n check = check_or_coroutine\\n\\n if not_check(check=check, contract=contract):\\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\\n break\\n\\n # The group of preconditions was satisfied, no need to check the other groups.\\n if exception is None:\\n break\\n\\n return exception\",\n \"def test_condition(c, flag_dict, unspecified_val):\\n\\n for ci in c:\\n if ci.name not in flag_dict:\\n if not unspecified_val:\\n return False\\n elif ci.enabled != flag_dict[ci.name]:\\n return False\\n return True\",\n \"def condition(*args, delete: bool=True, dependency: Union[AnyStr, List[AnyStr]]=\\\"\\\", initialize:\\n bool=True, script: AnyStr=\\\"\\\", state: bool=True, q=True, query=True, e=True,\\n edit=True, **kwargs)->Union[None, Any]:\\n pass\",\n \"def _check_dependency(self, tcname, depends):\\r\\n tcindex = self.tcorder.index(tcname)\\r\\n dependsindex = []\\r\\n for i in depends:\\r\\n dependsindex.append(self.tcorder.index(i))\\r\\n for i in dependsindex:\\r\\n if tcindex < i:\\r\\n msg = \\\"%s must be ordered after %s\\\\n\\\" %(tcname, self.tcorder[i])\\r\\n self.dependency.append(msg)\",\n \"def _check_family(self):\\n for (s, (b, c)), (cond, ref) in families.items():\\n if s != self.SYMBOL or len(b) != self._.d:\\n continue\\n vars = tuple(set(sum(map(variables, b + c), ())))\\n sols = _solve([SR(l) == r for l, r\\n in zip(self._.b[:-1] + self._.c[1:], b + c)],\\n vars)\\n if any(checkConditions(cond, sol) for sol in sols\\n if is_integral(sol)):\\n raise InfeasibleError(refs=ref)\",\n \"def test_has_error(html, expected):\\n from scraper import has_error\\n assert has_error(html) == expected\",\n \"def check_dependencies():\\n\\n vars_valid = check_variables(\\n AirflowVars.PROJECT_ID, AirflowVars.TERRAFORM_ORGANIZATION, AirflowVars.VM_DAGS_WATCH_LIST\\n )\\n conns_valid = check_connections(AirflowConns.TERRAFORM)\\n\\n if not vars_valid or not conns_valid:\\n raise AirflowException(\\\"Required variables or connections are missing\\\")\",\n \"def _validate_ResearchStudy_Condition(research_studies_with_observations):\\n research_studies_with_observations = {r.relativePath(): r for r in research_studies_with_observations if\\n r.__class__.__name__ == 'ResearchStudy'}\\n research_studies_missing_condition = dict(**research_studies_with_observations)\\n for research_study in research_studies_with_observations.values():\\n if research_study.condition and len(research_study.condition) > 0:\\n # print(f\\\"{research_study.relativePath()} has condition {research_study.condition[0].as_json()}\\\")\\n del research_studies_missing_condition[research_study.relativePath()]\\n # for k in research_studies_missing_condition:\\n # from pprint import pprint\\n # pprint(research_studies_missing_condition[k].as_json())\\n # break\\n assert len(\\n research_studies_missing_condition) == 0, f\\\"{len(research_studies_missing_condition)} of {len(research_studies_with_observations)} ResearchStudies missing Condition codeable concept\\\\n{research_studies_missing_condition.keys()}\\\"\",\n \"def ready_to_proceed(self):\\n if self.current_step is None or self.step_position == StepPosition.Before:\\n return False\\n\\n for condition, _ in self.current_step.conditions:\\n if condition.satisfied():\\n return True\\n return False\",\n \"def _validate_ResearchStudy_Condition(research_studies_with_observations):\\n research_studies = {r.relativePath(): r for r in research_studies_with_observations if\\n r.__class__.__name__ == 'ResearchStudy'}\\n research_studies_missing_condition = dict(**research_studies)\\n for research_study in research_studies.values():\\n if research_study.condition and len(research_study.condition) > 0:\\n # print(f\\\"{research_study.relativePath()} has condition {research_study.condition[0].as_json()}\\\")\\n del research_studies_missing_condition[research_study.relativePath()]\\n # for k in research_studies_missing_condition:\\n # from pprint import pprint\\n # pprint(research_studies_missing_condition[k].as_json())\\n # break```\\n assert len(\\n research_studies_missing_condition) == 0, f\\\"{len(research_studies_missing_condition)} of {len(research_studies)} ResearchStudies missing Condition codeable concept\\\\n{research_studies_missing_condition.keys()}\\\"\",\n \"def is_pre_test_survey_valid(survey, inclusion_criteria):\\n for ic in inclusion_criteria:\\n if not eval(ic):\\n return False\\n\\n return True\",\n \"async def test_dependencies(self):\\n response = await self.collect(get_request_text=self.xml)\\n expected_entities = [\\n dict(\\n key=\\\"12345\\\",\\n url=\\\"https://owasp_dependency_check#l1_12345\\\",\\n file_name=self.file_name,\\n file_path=self.file_path,\\n )\\n ]\\n self.assert_measurement(response, value=\\\"1\\\", entities=expected_entities)\",\n \"def require(e):\\n\\n if e is True:\\n return\\n if any(unwrap(e).eq(a) for a in assumptions):\\n return\\n\\n solver = get_solver()\\n solver.add(unwrap(e))\\n sat = solver.check()\\n if sat == z3.unsat:\\n raise RuntimeError(\\\"Unsatisfiable assumption %s\\\" % e)\\n elif sat != z3.sat:\\n raise RuntimeError(\\\"Uncheckable assumption %s\\\" % e)\",\n \"def check(steps: Steps, error_message: str, condition) -> bool:\\n if steps:\\n step = steps.get_last_step()\\n if not callable(condition):\\n raise ValueError(\\\"The 'condition' argument \\\"\\n \\\"must be a callable object\\\")\\n else:\\n if not condition():\\n raise ValueError(error_message)\\n else:\\n step.set_status(Status.PASSED)\\n return True\\n\\n return False\",\n \"def test_if_true():\\n\\n true_values = [True, 1, 2.0, object(), \\\"foo\\\", int]\\n assert all(true_values)\\n\\n def f_if():\\n if x:\\n print(\\\"x is True\\\")\\n\\n for x in true_values:\\n check_component(\\n prune_cfg,\\n f_if,\\n additional_bindings=dict(x=x),\\n expected_source=\\\"\\\"\\\"\\n def f_if():\\n print('x is True')\\n \\\"\\\"\\\",\\n )\\n\\n def f_if_else():\\n if x:\\n print(\\\"x is True\\\")\\n else:\\n print(\\\"x is False\\\")\\n\\n check_component(\\n prune_cfg,\\n f_if_else,\\n additional_bindings=dict(x=2),\\n expected_source=\\\"\\\"\\\"\\n def f_if_else():\\n print(\\\"x is True\\\")\\n \\\"\\\"\\\",\\n )\",\n \"def test_option_marked_correct(self):\\r\\n\\r\\n conditions = [\\r\\n {'input_type': 'radio', 'value': self.VALUE_DICT}]\\r\\n\\r\\n self.context['status'] = 'correct'\\r\\n\\r\\n for test_conditions in conditions:\\r\\n self.context.update(test_conditions)\\r\\n xml = self.render_to_xml(self.context)\\r\\n xpath = \\\"//section[@id='forinput1_choiceinput_0bc' and\\\\\\r\\n @class='choicetextgroup_correct']\\\"\\r\\n self.assert_has_xpath(xml, xpath, self.context)\\r\\n\\r\\n # Should NOT mark the whole problem\\r\\n xpath = \\\"//div[@class='indicator_container']/span\\\"\\r\\n self.assert_no_xpath(xml, xpath, self.context)\",\n \"def condition(self) -> global___Expression:\",\n \"def condition(self) -> global___Expression:\",\n \"def check(self, description: Description) -> bool:\",\n \"def test_conditional():\\n # verify that conditioning increases the likelihood of getting a sample with the specified\\n # categorical value\",\n \"def is_satisfied(self, item: Any) -> bool:\",\n \"def meetsreqs(request, requirements):\\n for requirement in requirements:\\n if requirement(request) == False:\\n return False\\n return True\",\n \"def test_option_marked_correct(self):\\r\\n conditions = [\\r\\n {'input_type': 'radio', 'value': '2'},\\r\\n {'input_type': 'radio', 'value': ['2']}]\\r\\n\\r\\n self.context['status'] = Status('correct')\\r\\n\\r\\n for test_conditions in conditions:\\r\\n self.context.update(test_conditions)\\r\\n xml = self.render_to_xml(self.context)\\r\\n xpath = \\\"//label[@class='choicegroup_correct']\\\"\\r\\n self.assert_has_xpath(xml, xpath, self.context)\\r\\n\\r\\n # Should NOT mark the whole problem\\r\\n xpath = \\\"//div[@class='indicator_container']/span\\\"\\r\\n self.assert_no_xpath(xml, xpath, self.context)\",\n \"def _assert_postconditions(postconditions: List[Contract], resolved_kwargs: Mapping[str, Any],\\n func: CallableT) -> Optional[BaseException]:\\n assert 'result' in resolved_kwargs, \\\\\\n \\\"Expected 'result' to be already set in resolved kwargs before calling this function.\\\"\\n\\n for contract in postconditions:\\n if inspect.iscoroutinefunction(contract.condition):\\n raise ValueError(\\\"Unexpected coroutine (async) condition {} for a sync function {}.\\\".format(\\n contract.condition, func))\\n\\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\\n\\n check = contract.condition(**condition_kwargs)\\n\\n if inspect.iscoroutine(check):\\n raise ValueError(\\\"Unexpected coroutine resulting from the condition {} for a sync function {}.\\\".format(\\n contract.condition, func))\\n\\n if not_check(check=check, contract=contract):\\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\\n\\n return exception\\n\\n return None\",\n \"def _assert_preconditions(preconditions: List[List[Contract]], resolved_kwargs: Mapping[str, Any],\\n func: CallableT) -> Optional[BaseException]:\\n exception = None # type: Optional[BaseException]\\n\\n # Assert the preconditions in groups. This is necessary to implement \\\"require else\\\" logic when a class\\n # weakens the preconditions of its base class.\\n\\n for group in preconditions:\\n exception = None\\n\\n for contract in group:\\n assert exception is None, \\\"No exception as long as pre-condition group is satisfiable.\\\"\\n\\n condition_kwargs = select_condition_kwargs(contract=contract, resolved_kwargs=resolved_kwargs)\\n\\n if inspect.iscoroutinefunction(contract.condition):\\n raise ValueError(\\\"Unexpected coroutine (async) condition {} for a sync function {}.\\\".format(\\n contract.condition, func))\\n\\n check = contract.condition(**condition_kwargs)\\n\\n if inspect.iscoroutine(check):\\n raise ValueError(\\\"Unexpected coroutine resulting from the condition {} for a sync function {}.\\\".format(\\n contract.condition, func))\\n\\n if not_check(check=check, contract=contract):\\n exception = _create_violation_error(contract=contract, resolved_kwargs=resolved_kwargs)\\n break\\n\\n # The group of preconditions was satisfied, no need to check the other groups.\\n if exception is None:\\n break\\n\\n return exception\",\n \"def test_check_model_dependencies_complete(dependency_testing_model, complete_env) -> None:\\n assert check_model_dependencies(\\n model_cls=dependency_testing_model,\\n environment=complete_env,\\n raise_for_missing=False,\\n )\",\n \"def condition(self):\\n return True\",\n \"def test_nested():\\n res = conf.status.conditions.choose(lambda c: (c.type, c.reason, c.root.metadata.choose(lambda m: (m[\\\"name\\\"], m.uid))))\\n assert \\\"type\\\" in res # from conditions\\n assert \\\"reason\\\" in res # from conditions\\n assert \\\"name\\\" in res # from metadata\\n assert \\\"uid\\\" in res # from metadata\",\n \"def test_headlines_required(self) -> None:\\n for rule in self.rules.headlines:\\n if not rule.required:\\n continue\\n is_match: bool = False\\n for headline in self.report.headlines:\\n if self.rules.get_headline_rules(headline.name) == rule:\\n is_match = True\\n break\\n if not is_match:\\n self.add_error(f\\\"Rubriken {rule.name} som måste vara med saknas.\\\")\",\n \"def test_condition_split(self):\\n self.write_contents(\\n 'external/wpt/fail.html.ini', \\\"\\\"\\\"\\\\\\n [fail.html]\\n expected:\\n if product == \\\"content_shell\\\": FAIL\\n \\\"\\\"\\\")\\n self.update(\\n {\\n 'run_info': {\\n 'product': 'content_shell',\\n 'os': 'mac',\\n 'port': 'mac12',\\n },\\n 'results': [{\\n 'test': '/fail.html',\\n 'status': 'TIMEOUT',\\n 'expected': 'FAIL',\\n }],\\n }, {\\n 'run_info': {\\n 'product': 'content_shell',\\n 'os': 'win',\\n 'port': 'win11',\\n },\\n 'results': [{\\n 'test': '/fail.html',\\n 'status': 'FAIL',\\n 'expected': 'FAIL',\\n }],\\n }, {\\n 'run_info': {\\n 'product': 'chrome',\\n 'os': 'linux',\\n 'port': 'trusty',\\n },\\n 'results': [{\\n 'test': '/fail.html',\\n 'status': 'PASS',\\n 'expected': 'PASS',\\n }],\\n },\\n overwrite_conditions='yes')\\n path = self.finder.path_from_web_tests('external', 'wpt',\\n 'fail.html.ini')\\n lines = self.tool.filesystem.read_text_file(path).splitlines()\\n expected = textwrap.dedent(\\\"\\\"\\\"\\\\\\n [fail.html]\\n expected:\\n if (product == \\\"content_shell\\\") and (os == \\\"win\\\"): FAIL\\n if (product == \\\"content_shell\\\") and (os == \\\"mac\\\"): TIMEOUT\\n \\\"\\\"\\\")\\n # TODO(crbug.com/1299650): The branch order appears unstable, which we\\n # should fix upstream to avoid create spurious diffs.\\n self.assertEqual(sorted(lines, reverse=True), expected.splitlines())\",\n \"def Require(condition):\\n if not condition:\\n Revert()\\n return True\",\n \"def check(self,):\\n self.is_valid_according_policy()\",\n \"def check_explicit_data_dependency( # noqa: C901\\n self,\\n context: SlicingContext,\\n unique_instr: UniqueInstruction,\\n traced_instr: ExecutedInstruction | None,\\n ) -> tuple[bool, set[str]]:\\n complete_cover = False\\n partial_cover = False\\n attribute_creation_uses = set()\\n\\n if not unique_instr.is_def():\\n return False, set()\\n\\n # Check variable definitions\\n if isinstance(traced_instr, ExecutedMemoryInstruction):\\n complete_cover = self._check_variables(context, traced_instr)\\n\\n # When an object, of which certain used attributes are taken from,\\n # is created, the slicer has to look for the definition of normal variables\\n # instead of these attributes, since they are defined as variables and not\\n # as attributes on class/module level.\\n if traced_instr.arg_address and traced_instr.object_creation:\\n attribute_uses = set()\\n for use in context.attr_uses:\\n if use.startswith(hex(traced_instr.arg_address)) and len(use) > len(\\n hex(traced_instr.arg_address)\\n ):\\n complete_cover = True\\n attribute_uses.add(use)\\n attribute_creation_uses.add(\\\"_\\\".join(use.split(\\\"_\\\")[1:]))\\n for use in attribute_uses:\\n context.attr_uses.remove(use)\\n\\n # Check for address dependencies\\n if traced_instr.is_mutable_type and traced_instr.object_creation:\\n # Note that the definition of an object here means the\\n # creation of the object.\\n address_dependency = self._check_scope_for_def(\\n context.var_uses_addresses,\\n hex(traced_instr.arg_address),\\n None,\\n None,\\n )\\n if address_dependency:\\n complete_cover = True\\n\\n # Check for the attributes which were converted to variables\\n # (explained in the previous construct)\\n if traced_instr.argument in context.attribute_variables:\\n complete_cover = True\\n context.attribute_variables.remove(str(traced_instr.argument))\\n\\n if isinstance(traced_instr, ExecutedAttributeInstruction):\\n # check attribute defs\\n if traced_instr.combined_attr in context.attr_uses:\\n complete_cover = True\\n context.attr_uses.remove(traced_instr.combined_attr)\\n # Partial cover: modification of attribute of\\n # object in search for definition\\n if hex(traced_instr.src_address) in context.var_uses_addresses:\\n partial_cover = True\\n\\n return (complete_cover or partial_cover), attribute_creation_uses\",\n \"def validate_dependence_versions():\\n print('Total {} instances defined'.format(len(ReleaseInfo.all_instance_releases())))\\n all_instance_releases = ReleaseInfo.all_instance_releases()\\n\\n # Validate dependencies: each dependence should have a valid\\n # version as in defined range\\n for instance_name, versions in all_instance_releases.items():\\n for instance_version, release_info in versions.items():\\n dependencies = release_info.dependencies\\n for dep in dependencies:\\n dep_type = dep.type\\n minv = dep.min_version\\n maxv = dep.max_version\\n\\n assert dep_type in all_instance_releases, \\\\\\n \\\"No dependence found {} for version {} of {}\\\" \\\\\\n .format(dep_type, instance_version, instance_name)\\n\\n found = _find_a_ranged_version(dep_type, minv=minv, maxv=maxv)\\n assert found, \\\"No valid version defined for {} with max: {}, min: {}\\\" \\\\\\n .format(dep_type, maxv, minv)\",\n \"def validate(self):\\n super(PipelineContext, self).validate()\\n for instrument, imap in self.selections.normal_items():\\n self._check_nested(\\\"instrument\\\", instrument, imap)\\n\\n # Will raise pkg_resources.RequirementParseError if the requirement\\n # is malformed:\\n self.get_asdf_standard_requirement()\",\n \"def check(self):\\n for req in self.requirements:\\n if not self.COMPARISON_OPERATORS[req.operator](\\n packaging.version.parse(get_installed_version(req.package)),\\n packaging.version.parse(req.version),\\n ):\\n fail(f\\\"The cluster requires {req.package}{req.operator}{req.version}\\\")\",\n \"def test_KidsFirstResearchStudy_Condition(kids_first_research_studies_with_observations):\\n _validate_ResearchStudy_Condition(kids_first_research_studies_with_observations)\",\n \"def test_java(self, condition, undefined_paths, current_path):\\n cond_id = str(condition.get('id'))\\n\\n try:\\n cid = str(condition.find('class').text)\\n except AttributeError:\\n current_path += ((cond_id, 'ill-defined java condition'),)\\n undefined_paths.add(current_path)\\n return False\\n\\n if not cid:\\n current_path += ((cid, 'ill-defined java condition'),)\\n undefined_paths.add(current_path)\\n return False\\n\\n classes = self.verifier.get_container('classes').get_keys()\\n if not cid in classes:\\n current_path += ((cid, 'java class'),)\\n undefined_paths.add(current_path)\\n return False\",\n \"def test_check_is_required(fake_check):\\n assert fake_check.is_required()\",\n \"def test_variable(self, condition, undefined_paths, current_path):\\n var = str(condition.find('name').text)\\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\\n current_path += ((var, 'undefined variable'),)\\n undefined_paths.add(current_path)\\n return False\\n else:\\n return True\",\n \"def test_falsifications(self):\\n implications = get_conditional_independencies(asia_example.graph)\\n issues = get_falsifications(implications, asia_example.data)\\n self.assertEqual(0, len(issues.failures))\\n self.assertEqual(len(issues.evidence), len(implications))\",\n \"def _parse(self, engine):\\n\\t\\tself.condition = engine.evaluate(self.args, recursive=True)\\n\\t\\tif not self.condition:\\n\\t\\t\\traise AssertionError('\\\"assert\\\" layer failed. Condition evaluated '\\n\\t\\t\\t\\t'to: {} (type={})'.format(\\n\\t\\t\\t\\t\\tself.condition,\\n\\t\\t\\t\\t\\ttype(self.condition)\\n\\t\\t\\t\\t))\",\n \"def checkRequiredDependencies(self):\\n \\n # skip dependency check for downloading only\\n if( self.downloadOnly ):\\n return\\n\\n # hard dependencies\\n for req in self.reqmodules:\\n if( self.parent.module(req) == None ):\\n # check if there is an auto detected module\\n if( self.parent.module(req, True) == None ):\\n self.abort( self.name + \\\" requires \\\" + req \\\\\\n + \\\" and it wasn't found in your config file!!\\\" )\\n else:\\n # use auto detected module\\n self.parent.use( self.parent.module(req, True) )\\n self.parent.module( req ).init()\\n\\n print self.name + \\\": auto-detected \\\" + req + \\\" version \\\" + self.parent.module( req ).version\\n \\n # build only dependencies\\n if( self.mode == \\\"install\\\" ):\\n mods = self.reqmodules_buildonly + self.reqmodules_external\\n for req in mods:\\n if( self.parent.module(req) == None ):\\n # check if there is an auto detected module\\n if( self.parent.module(req, True) == None ):\\n self.abort( req + \\\" not found in your config file!! \\\" + self.name \\\\\\n + \\\" cannot be built without \\\" + req )\\n else:\\n # use auto detected module\\n self.parent.use( self.parent.module(req, True) )\\n self.parent.module( req ).init()\\n\\n print \\\" - \\\" + self.name + \\\": auto-detected \\\" + req + \\\" version \\\" + self.parent.module( req ).version\",\n \"def testConditionsAreOrdered(self):\\n self.Check(\\\"\\\"\\\"\\n from __future__ import google_type_annotations\\n from typing import Optional\\n def f(x: Optional[NoneType]) -> int:\\n if x is not None:\\n x = None\\n if x is None:\\n x = 1\\n return x\\n \\\"\\\"\\\")\",\n \"def satisfy(self):\\n self.stub.Satisfy(\\n depend_pb2.DependSatisfyRequest(depend=self.data), timeout=Cuebot.Timeout)\",\n \"def _assert_pip_requirements(model_uri, requirements, constraints=None, strict=False):\\n local_path = _download_artifact_from_uri(model_uri)\\n txt_reqs = _read_lines(os.path.join(local_path, _REQUIREMENTS_FILE_NAME))\\n conda_reqs = _get_pip_deps(_read_yaml(\\n os.path.join(local_path, _CONDA_ENV_FILE_NAME)))\\n compare_func = set.__eq__ if strict else set.__le__\\n requirements = set(requirements)\\n assert compare_func(requirements, set(txt_reqs))\\n assert compare_func(requirements, set(conda_reqs))\\n\\n if constraints is not None:\\n assert f\\\"-c {_CONSTRAINTS_FILE_NAME}\\\" in txt_reqs\\n assert f\\\"-c {_CONSTRAINTS_FILE_NAME}\\\" in conda_reqs\\n cons = _read_lines(os.path.join(local_path, _CONSTRAINTS_FILE_NAME))\\n assert compare_func(set(constraints), set(cons))\",\n \"def condition_for_function(f, abi, all_not_in_ABI):\\n\\n\\tcondition = []\\n\\tfor n in f.entry_points:\\n\\t\\t[category, num] = api.get_category_for_name( n )\\n\\t\\tif category not in abi:\\n\\t\\t\\tcondition.append( 'defined(need_%s)' % (gl_XML.real_category_name( category )) )\\n\\t\\telif all_not_in_ABI:\\n\\t\\t\\treturn []\\n\\n\\treturn condition\",\n \"def input_check(self):\\n\\n if self.species == 'He': assert self.line_model == 'voigt'\\n n_upper_range, e_dens_range, temp_range, b_field_range = get_param_ranges(self.line_model)\\n\\n if np.isnan(n_upper_range).sum() <= 1:\\n assert (self.n_upper in range(n_upper_range[0], n_upper_range[1]))\\n if np.isnan(e_dens_range).sum() <= 1:\\n assert (e_dens_range[0] <= self.e_dens <= e_dens_range[1])\\n if np.isnan(temp_range).sum() <= 1:\\n assert (temp_range[0] <= self.temp <= temp_range[1])\\n if np.isnan(b_field_range).sum() <= 1:\\n assert (b_field_range[0] <= self.b_field <= b_field_range[1])\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6394948","0.6064821","0.6038692","0.60127705","0.5969924","0.5887158","0.5801091","0.5776576","0.57205003","0.56385154","0.5614725","0.56072754","0.5539833","0.5475634","0.54365665","0.54158586","0.54152584","0.53983265","0.5347427","0.5322336","0.53194696","0.53194696","0.53169954","0.530525","0.52991325","0.529741","0.52888894","0.52828056","0.52557445","0.52420264","0.5232942","0.52321666","0.52289504","0.5223285","0.52107275","0.5205611","0.5194215","0.51853204","0.51809174","0.5178118","0.51688707","0.5167001","0.5146702","0.514108","0.5135398","0.5124657","0.512425","0.51201344","0.50983727","0.5090485","0.50859505","0.5085707","0.5085166","0.5082581","0.5081285","0.50636727","0.5060406","0.50591695","0.5057118","0.5056871","0.50564814","0.50548124","0.505316","0.5048335","0.50308853","0.50307065","0.50247985","0.5018778","0.5003849","0.5003849","0.5002762","0.50007343","0.49990863","0.49967626","0.49891624","0.4984127","0.49718073","0.49672994","0.49671504","0.49607518","0.4955104","0.49491832","0.4947581","0.49451047","0.493923","0.49300036","0.49275607","0.49271303","0.49263743","0.4926279","0.49251917","0.49243283","0.4922923","0.49211383","0.4915373","0.49114865","0.4910593","0.49093905","0.4903417","0.48993734"],"string":"[\n \"0.6394948\",\n \"0.6064821\",\n \"0.6038692\",\n \"0.60127705\",\n \"0.5969924\",\n \"0.5887158\",\n \"0.5801091\",\n \"0.5776576\",\n \"0.57205003\",\n \"0.56385154\",\n \"0.5614725\",\n \"0.56072754\",\n \"0.5539833\",\n \"0.5475634\",\n \"0.54365665\",\n \"0.54158586\",\n \"0.54152584\",\n \"0.53983265\",\n \"0.5347427\",\n \"0.5322336\",\n \"0.53194696\",\n \"0.53194696\",\n \"0.53169954\",\n \"0.530525\",\n \"0.52991325\",\n \"0.529741\",\n \"0.52888894\",\n \"0.52828056\",\n \"0.52557445\",\n \"0.52420264\",\n \"0.5232942\",\n \"0.52321666\",\n \"0.52289504\",\n \"0.5223285\",\n \"0.52107275\",\n \"0.5205611\",\n \"0.5194215\",\n \"0.51853204\",\n \"0.51809174\",\n \"0.5178118\",\n \"0.51688707\",\n \"0.5167001\",\n \"0.5146702\",\n \"0.514108\",\n \"0.5135398\",\n \"0.5124657\",\n \"0.512425\",\n \"0.51201344\",\n \"0.50983727\",\n \"0.5090485\",\n \"0.50859505\",\n \"0.5085707\",\n \"0.5085166\",\n \"0.5082581\",\n \"0.5081285\",\n \"0.50636727\",\n \"0.5060406\",\n \"0.50591695\",\n \"0.5057118\",\n \"0.5056871\",\n \"0.50564814\",\n \"0.50548124\",\n \"0.505316\",\n \"0.5048335\",\n \"0.50308853\",\n \"0.50307065\",\n \"0.50247985\",\n \"0.5018778\",\n \"0.5003849\",\n \"0.5003849\",\n \"0.5002762\",\n \"0.50007343\",\n \"0.49990863\",\n \"0.49967626\",\n \"0.49891624\",\n \"0.4984127\",\n \"0.49718073\",\n \"0.49672994\",\n \"0.49671504\",\n \"0.49607518\",\n \"0.4955104\",\n \"0.49491832\",\n \"0.4947581\",\n \"0.49451047\",\n \"0.493923\",\n \"0.49300036\",\n \"0.49275607\",\n \"0.49271303\",\n \"0.49263743\",\n \"0.4926279\",\n \"0.49251917\",\n \"0.49243283\",\n \"0.4922923\",\n \"0.49211383\",\n \"0.4915373\",\n \"0.49114865\",\n \"0.4910593\",\n \"0.49093905\",\n \"0.4903417\",\n \"0.48993734\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.63148606"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":13073,"cells":{"query":{"kind":"string","value":"Tests if a 'variable' type condition is correctly defined."},"document":{"kind":"string","value":"def test_variable(self, condition, undefined_paths, current_path):\n var = str(condition.find('name').text)\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\n current_path += ((var, 'undefined variable'),)\n undefined_paths.add(current_path)\n return False\n else:\n return True"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _validate_variable(self, variable):\n if variable is not None:\n # test type\n if not self.validate_type(variable):\n return False\n\n return True","def isvar(var):\n return _coconut_tail_call(isinstance, var, (Const, Var))","def _check_variable_definition(variable_name, variable_attrs):\n\n # Variable name must be type str\n if type(variable_name) != str:\n raise TypeError(\"Invalid variable name: \"+str(variable_name)+\" (must be string)\")\n\n # todo - add more tests to check validity of variable definition","def _is_op_defined(t_vars) -> bool:\n return all(t_var.name.startswith(\"Variable\") for t_var in t_vars)","def _assigns_typevar(node: nodes.NodeNG | None) -> bool:\n if isinstance(node, astroid.Call):\n inferred = utils.safe_infer(node.func)\n if (\n isinstance(inferred, astroid.ClassDef)\n and inferred.qname() in TYPE_VAR_QNAME\n ):\n return True\n return False","def _is_typevar(typeval: Type) -> bool:\n return isinstance(typeval, TypeVar) # type: ignore","def is_variable(item):\n return len(item) > 0 and item[0].upper() == item[0]","def _check_typevar(self, name: str, node: nodes.AssignName) -> None:\n if isinstance(node.parent, nodes.Assign):\n keywords = node.assign_type().value.keywords\n args = node.assign_type().value.args\n elif isinstance(node.parent, nodes.Tuple):\n keywords = (\n node.assign_type().value.elts[node.parent.elts.index(node)].keywords\n )\n args = node.assign_type().value.elts[node.parent.elts.index(node)].args\n\n variance = TypeVarVariance.invariant\n name_arg = None\n for kw in keywords:\n if variance == TypeVarVariance.double_variant:\n pass\n elif kw.arg == \"covariant\" and kw.value.value:\n variance = (\n TypeVarVariance.covariant\n if variance != TypeVarVariance.contravariant\n else TypeVarVariance.double_variant\n )\n elif kw.arg == \"contravariant\" and kw.value.value:\n variance = (\n TypeVarVariance.contravariant\n if variance != TypeVarVariance.covariant\n else TypeVarVariance.double_variant\n )\n\n if kw.arg == \"name\" and isinstance(kw.value, nodes.Const):\n name_arg = kw.value.value\n\n if name_arg is None and args and isinstance(args[0], nodes.Const):\n name_arg = args[0].value\n\n if variance == TypeVarVariance.double_variant:\n self.add_message(\n \"typevar-double-variance\",\n node=node,\n confidence=interfaces.INFERENCE,\n )\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(\"\",),\n confidence=interfaces.INFERENCE,\n )\n elif variance == TypeVarVariance.covariant and not name.endswith(\"_co\"):\n suggest_name = f\"{re.sub('_contra$', '', name)}_co\"\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(f'. \"{name}\" is covariant, use \"{suggest_name}\" instead'),\n confidence=interfaces.INFERENCE,\n )\n elif variance == TypeVarVariance.contravariant and not name.endswith(\"_contra\"):\n suggest_name = f\"{re.sub('_co$', '', name)}_contra\"\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(f'. \"{name}\" is contravariant, use \"{suggest_name}\" instead'),\n confidence=interfaces.INFERENCE,\n )\n elif variance == TypeVarVariance.invariant and (\n name.endswith(\"_co\") or name.endswith(\"_contra\")\n ):\n suggest_name = re.sub(\"_contra$|_co$\", \"\", name)\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(f'. \"{name}\" is invariant, use \"{suggest_name}\" instead'),\n confidence=interfaces.INFERENCE,\n )\n\n if name_arg is not None and name_arg != name:\n self.add_message(\n \"typevar-name-mismatch\",\n node=node,\n args=(name_arg, name),\n confidence=interfaces.INFERENCE,\n )","def has_value(var) :\n return var != None","def _should_use_varname_value(self, value):\n if isinstance(value, KnownValue):\n return type(value.val) in six.integer_types\n elif (\n type(value) is TypedValue\n ): # Only replace exactly TypedValue(int), not subtypes\n return value.typ in six.integer_types\n else:\n return value is UNRESOLVED_VALUE","def check_input_type(var, type_name):\n\n type_options = [\"int\", \"float\", \"Date\", \"Region\"]\n if type_name == type_options[0]:\n if int(var):\n return True\n else:\n return False\n elif type_name == type_options[1]:\n if float(var):\n return True\n else:\n return False\n elif type_name == type_options[2]:\n if datetime.date.fromisoformat(var):\n return True\n else:\n return False\n elif type_name == type_options[3]:\n valid_regions = [\"NW\", \"SW\", \"MN\", \"MS\", \"NE\", \"SE\"]\n is_valid = False\n for region in valid_regions:\n if var == region:\n is_valid = True\n return is_valid\n else:\n Exception(\"This type doesn't exist in the checker!\")","def test_exists(self, condition, undefined_paths, current_path):\n var = str(condition.find('variable').text)\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\n current_path += ((var, 'undefined variable'),)\n undefined_paths.add(current_path)\n return False\n else:\n return True","def typematch(variable, expectedtype):\n\n # Return the result\n return isinstance(variable, expectedtype)","def is_tvar(x):\n return type(x) is T.TensorVariable","def _is_var_declaration(fortress, filename, start):\n v = \"var \"\n return fortress.source_code[filename][start : start + len(v)] == v","def has_type_var(annotation) -> bool:\n return any(\n is_type_var(arg) or has_type_var(arg)\n for arg in getattr(annotation, \"__args__\", [])\n )","def _isintvar(self, index):\n return 251 <= self._typlist[index] <= 253","def is_variable(arg: Expr) -> bool:\n return str(arg)[0].islower()","def _isintvar(self, index):\n return 65528 <= self._typlist[index] <= 65530","def id_is_variable(self):\n return not self.defined","def isVariableDefined(self, varID):\n \n for i in range(self.varList.count()):\n item = self.varList.item(i)\n if varID == item.getVariable().id and not item.isQuickplotItem():\n return True\n return False","def check_variable_line(self, line):\n self.E_str = \"check_variable_line\"\n line, any_vars = self.find_vars_in_str(line)\n words = [i for i in line.split('=') if i]\n words = self.fix_words(words)\n\n if len(words) < 2:\n self.print_error(\"The syntax for declaring variables is: \"\n + \"'<name> = <value>'\")","def validVarConstructType(self,vartype):\r\n indArray = vartype.find('[]')\r\n if indArray>0:\r\n thisType = vartype[0:indArray]\r\n isArray = True\r\n else:\r\n thisType = vartype\r\n isArray = False\r\n \r\n if thisType in ('rng','range'):\r\n type = 'range'\r\n elif thisType in ('rate'):\r\n type = 'rate'\r\n elif thisType in ('amt','amount'):\r\n type = 'amount'\r\n elif thisType in ('minamt','minamount'):\r\n type = 'minamount'\r\n elif thisType in ('bool'):\r\n type = 'bool'\r\n else:\r\n print 'variable type must be range, rate, amount, minamount, bool (or abbreviated forms)'\r\n return False, ''\r\n \r\n return True, type, isArray","def has_variable(self, col: str, name: str) -> bool:\n if self.scope is None:\n raise ValueError(\"Can't access variables on unbound modules\")\n return self.scope.has_variable(col, name)","def is_type_var(annotation) -> bool:\n\n return isinstance(annotation, typing.TypeVar) # type:ignore","def has_variable(self, name):\n return name in self._variables","def varIsValid(self, var):\n if len(var.getAxisList()) != 1:\n return False\n if self.myParent.numValues() != self.myParent.numValues():\n return False\n return True","def validVarConstruct(self,thisvar):\r\n validLength = self.validVarConstructLength(thisvar)\r\n if not validLength:\r\n return False, '', '', False\r\n validName, varName = self.validVarConstructName(thisvar[0])\r\n if not validName:\r\n return False, '', '', False \r\n validType, varType, varArray = self.validVarConstructType(thisvar[1])\r\n if not validType:\r\n return False, '', '', False\r\n \r\n return True, varName, varType, varArray","def has_var(self, var_name: str) -> bool:\n is_var = var_name.startswith('var$')\n\n class Scopes:\n Global = self.global_variables\n Task = self.task_variables\n Local = self.local_variables\n\n scope = Scopes.Local\n\n if is_var:\n var_name = var_name[3:]\n if var_name.startswith('$$$'):\n scope = Scopes.Global\n var_name = var_name[3:]\n elif var_name.startswith('$$'):\n scope = Scopes.Task\n var_name = var_name[2:]\n elif var_name.startswith('$'):\n scope = Scopes.Local\n var_name = var_name[1:]\n\n return var_name in scope.vars","def condition_forward_checking(csp, var) :\n return False","def condition_forward_checking(csp, var) :\n return False","def validVarConstructLength(self,varlen):\r\n if len(varlen)!=2:\r\n print 'variable must specify name and type'\r\n return False\r\n else:\r\n return True","def is_variable(pattern):\n return (type(pattern) is str\n and pattern[0] == '?'\n and len(pattern) > 1\n and pattern[1] != '*'\n and pattern[1] in string.ascii_letters\n and ' ' not in pattern)","def _check_typevar(self) -> PossibleResult[T]:\n if _is_typevar(self.constructor): # type: ignore\n return Deserialize(\n obj=self.obj,\n constructor=(\n Union[self.constructor.__constraints__] # type: ignore\n if self.constructor.__constraints__ # type: ignore\n else object\n ),\n depth=self.new_depth,\n convert_primitives=self.convert_primitives,\n ).run()\n return NO_RESULT","def _var_check(self):\n missing = set()\n for v in self.variables:\n if getattr(self, v) is None:\n missing.add(v)\n self.missing = missing","def check_evidence(self, variable_name, variable_value):\n for i in xrange(0, len(self.sample_nodes)):\n if self.sample_nodes[i].name == variable_name:\n if self.sample_nodes[i].value == variable_value:\n return True\n else:\n return False\n\n print \"whoops, I guess the evidence variable was not assigned in the event\"\n return None","def f_exists(self, varname):\r\n return (varname in self.locals_ptr)","def is_variable_string(value):\n if not isinstance(value, basestring):\n return False\n return bool(_property_string_pattern.match(value))","def _check_variable(string, varname):\r\n prefix = '[(, ]' # Any character with the exception of '(, '\r\n suffix = '[), ]' # Any character with the exception of '), '\r\n pattern = prefix + varname + suffix\r\n re.match(pattern, string)","def isSetVariable(self):\n return _libsbml.Rule_isSetVariable(self)","def test_types(question):\n instance = question[\"instance\"]\n for name, data in instance.get(\"variables\", {}).items():\n assert \"optional\" not in data or isinstance(data[\"optional\"], bool)\n if data.get(\"type\") == \"boolean\":\n assert \"value\" not in data or isinstance(data[\"value\"], bool)\n elif data.get(\"type\") in [\"integer\", \"long\"]:\n assert \"value\" not in data or isinstance(data[\"value\"], int)","def _check_valid_condition(self, get_params):\n try:\n variable = get_params(self.variable)\n except: # noqa e722\n variable = None\n value = self.value\n\n # if None, return oppositely\n if variable is None:\n return not self.default\n\n # convert the value to a correct type\n if isinstance(variable, bool):\n value = bool(self.value)\n elif isinstance(variable, Number):\n try:\n value = int(self.value)\n except: # noqa e722\n try:\n value = float(self.value)\n except: # noqa e722\n # could not parse\n return not self.default\n\n # compare and return the result\n if self.condition == \"=\":\n return (variable == value) == self.default\n elif self.condition == \">\":\n return (variable > value) == self.default\n elif self.condition == \"<\":\n return (variable < value) == self.default","def __contains__(self, var: Union[Variable, int]) -> bool:\n if isinstance(var, Variable):\n return var in self.scope_vars\n return var in self.scope_vids","def legal_for(self, fvs : {EVar}) -> bool:\n vs = {(v, v.type) for (v, pool) in self.vars()}\n return all((v, v.type) in vs for v in fvs)","def isVar(self, t: str) -> bool:\n return t[0] != t[0].lower()","def _check_variables(datasets, necessary_short_names):\n dataset_name = datasets[0]['dataset']\n necessary_short_names = set(necessary_short_names)\n short_names = set(group_metadata(datasets, 'short_name').keys())\n if short_names != necessary_short_names:\n raise ValueError(\n f\"Expected variables {necessary_short_names} for dataset \"\n f\"'{dataset_name}', got {short_names}\")","def check_var_attrs(self, cls, node):\n ast = node.ast\n declarator = ast.declarator\n attrs = declarator.attrs\n for attr in attrs:\n if attr[0] == \"_\": # internal attribute\n continue\n # XXX - deref on class/struct members\n if attr not in [\"name\", \"readonly\", \"dimension\", \"deref\"]:\n raise RuntimeError(\n \"Illegal attribute '{}' for variable '{}' at line {}\".format(\n attr, node.name, node.linenumber\n ) + \"\\nonly 'name', 'readonly', 'dimension' and 'deref' are allowed on variables\"\n )\n\n is_ptr = declarator.is_indirect()\n if attrs[\"dimension\"] and not is_ptr:\n raise RuntimeError(\n \"dimension attribute can only be \"\n \"used on pointer and references\"\n )\n\n self.parse_attrs(node, ast)","def testConditionReasons(self):\n \n state = State.from_problem(self.prob)\n\n relevantVars = []\n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\n\n relevantVars = set(relevantVars)\n \n s1 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"pos1\"]])\n s2 = StateVariable(self.prob.functions[\"city-of\"][0], [self.prob[\"apt1\"]])\n s3 = StateVariable(self.prob.functions[\"location-of\"][0], [self.prob[\"tru1\"]])\n \n self.assertEqual(len(relevantVars), 3)\n self.assert_(s1 in relevantVars)\n self.assert_(s2 in relevantVars)\n self.assert_(s3 in relevantVars)","def _check_var_conflicts(s, variables):\n # check conflicts with variable names\n vars_redefined = {x for x in s if x in variables}\n if vars_redefined:\n raise Exception('Variables redefined: {v}'.format(v=vars_redefined))\n # check conflicts with values of arbitrary finite data types\n for var, domain in variables.items():\n # not arbitrary finite type ?\n if not isinstance(domain, list):\n continue\n # var has arbitrary finite type\n conflicting_values = {x for x in s if x in domain}\n if conflicting_values:\n raise Exception(\n 'Values redefined: {v}'.format(v=conflicting_values))","def has_variables(text):\n matches = _property_pattern.findall(text)\n return len(matches) > 0","def _is_loop_invariant(self, var):\n # does it rely on unknown source?\n if var.find(\"#u\") != -1:\n return False\n # constant\n if AsmParser.is_constant(var):\n return True\n # get an update set for a variable\n update_set = self._get_update_set(var)\n log.debug(\" UPDATE_SET: %s\" % update_set)\n # if nothing is changed, it is loop-invariant\n if not update_set:\n return True\n # if the same value is updated, it is loop-invariant\n return self._update_same(update_set)","def is_var (string):\n if (string[0] == '?'):\n return True\n return False","def _isnumvar(self, index):\n return 65526 <= self._typlist[index] <= 65530","def is_var(argument):\n if argument[0] in list(string.ascii_uppercase):\n return True\n return False","def variable_type(self, variable): # pragma: no cover\n raise NotImplementedError('Implemented in child class')","def is_allowed(self):\n if self.structure.variable_dependant_path:\n # fill in empty part of the path with the current path\n if len(self.structure.variable_dependant_path) == 3:\n dependant_var_path = (\n self.path[0],\n ) + self.structure.variable_dependant_path\n elif len(self.structure.variable_dependant_path) == 2:\n dependant_var_path = (\n self.path[0],\n self.path[1],\n ) + self.structure.variable_dependant_path\n elif len(self.structure.variable_dependant_path) == 1:\n dependant_var_path = (\n self.path[0],\n self.path[1],\n self.path[2],\n ) + self.structure.variable_dependant_path\n else:\n dependant_var_path = None\n\n # get dependency\n dependant_var = None\n mf_data = self._simulation_data.mfdata\n if dependant_var_path in mf_data:\n dependant_var = mf_data[dependant_var_path]\n\n # resolve dependency\n if self.structure.variable_value_when_active[0] == \"Exists\":\n exists = self.structure.variable_value_when_active[1]\n if dependant_var and exists.lower() == \"true\":\n return True\n elif not dependant_var and exists.lower() == \"false\":\n return True\n else:\n return False\n elif not dependant_var:\n return False\n elif self.structure.variable_value_when_active[0] == \">\":\n min_val = self.structure.variable_value_when_active[1]\n if dependant_var > float(min_val):\n return True\n else:\n return False\n elif self.structure.variable_value_when_active[0] == \"<\":\n max_val = self.structure.variable_value_when_active[1]\n if dependant_var < float(max_val):\n return True\n else:\n return False\n return True","def ensure_type(var, *expected_types, _up_extra_frames=0):\n for t in expected_types:\n if isinstance(var, t):\n return True\n type_err = f'Type-checking caller: {get_caller_function(_up_extra_frames=_up_extra_frames)}(): For object (value = {var}), ' \\\n f'expected type(s) was {expected_types} but instead found {type(var)}'\n logger.error(type_err)\n raise TypeError(type_err)","def isConditional(self) -> bool:\n ...","def hasEditVariable(self, variable: Variable, /) -> bool:\n ...","def _check_variables_in_raw_data(self):\n # make sure that all of the necessary variables are present\n # or mapped via the variable dict\n for key in [key for key in self._map_cols.keys()\n if key not in ['block', 'choice_accuracy', 'ID']]:\n assert self._map_cols[key] in self._raw_data.columns,\\\n 'missing {} from raw data df columns'.format(\n self._map_cols[key])\n\n condition_codes = self._raw_data[self._map_cols['condition']].unique()\n for cond in ['go', 'stop']:\n assert self._map_codes[cond] in condition_codes,\\\n ('missing {} from column: '.format(self._map_codes[cond]),\n self._map_cols[\"condition\"])\n\n # check that all unique non-nan values in the accuracy column \n # can be mapped onto either correct or incorrect,\n # as defined by the values in the var_dict.\n if self._map_cols['choice_accuracy'] in self._raw_data.columns:\n raw_acc_codes = self._raw_data[\n self._map_cols['choice_accuracy']].unique()\n raw_acc_codes = [i for i in raw_acc_codes if i==i]\n map_acc_codes = [self._map_codes['correct'],\n self._map_codes['incorrect']]\n for acc_code in raw_acc_codes:\n assert acc_code in map_acc_codes,\\\n '{} present in {} column.'. format(\n acc_code, self._cols[\"choice_accuracy\"]\n )\n\n return True","def is_variable(s):\n return s[0] >= 'u' and s[0] <= 'z' and s.isalnum()","def check(self):\n\n return self.variable.check(self.cval, self.conditional)","def has_assignment_for(self, var):\n return self.variable_to_value.get(var) != None","def is_null(var):\r\n if var is None or not var: return True\r\n if any(isinstance(var, s) for s in [str, list, tuple, set]) and len(var) == 0: return True\r\n if isinstance(var, str) and var == '': return True\r\n if any( isinstance(var, s) for s in [int, float, complex, bool] ) and int(var) == 0: return True\r\n return False","def validVarConstructStorage(self,varStorage):\r\n if varStorage in fortaxStorageName.integer:\r\n storage = fortaxStorage.integer\r\n elif varStorage in fortaxStorageName.logical:\r\n storage = fortaxStorage.logical\r\n elif varStorage in fortaxStorageName.double:\r\n storage = fortaxStorage.double\r\n elif varStorage in fortaxStorageName.integerarray:\r\n storage = fortaxStorage.integerarray\r\n elif varStorage in fortaxStorageName.logicalarray:\r\n storage = fortaxStorage.logicalarray\r\n elif varStorage in fortaxStorageName.doublearray:\r\n storage = fortaxStorage.doublearray\r\n else:\r\n print 'storage must be integer, integerarray, logical, logicalarray, double, doublearray (or abbreviated forms)'\r\n return False\r\n return True, storage","def check_if_statement(self, line):\n line = re.sub(\"^if *\", \"\", line)\n if '(' not in line or ')' not in line:\n self.print_error(\"Syntax error: If statements take the syntax if (condition) { ... }\",\n errorFunc=SyntaxError)\n\n\n # remove the brackets\n statement, _ = gen_parse.get_str_between_delims(line, \"(\", \")\")\n\n\n # Check all variables have been declared\n any_vars = [i.strip('$') for i in re.findall(VAR_REGEX, statement)]\n for var_name in any_vars:\n if var_name not in self.variables:\n self.print_error(f\"Unknown variable: {var_name}\")","def require(var, condition, msg='wrong length'):\n if not condition:\n raise SyntaxError(tostr(var)+': '+msg)","def _is_type_in_scope(self, name):","def __validateTemplateVariables(self, vars):\n for requiredVarName in self.varNames():\n if requiredVarName not in vars:\n raise VariableNotFoundError(\n 'Could not find a value for the variable {0}'.format(\n requiredVarName\n )\n )","def is_var_line(line):\n if '=' in line:\n # Check it isn't some other command\n for cmd in CMD_LIST:\n if re.findall(f\"^{cmd} \", line):\n return False\n\n str_txt, non_str = gen_parse.get_str_between_delims(line, '\"')\n if any(j in non_str for j in '<>-+/*^'):\n return False\n return True\n else:\n return False","def __checkInput(self, var):\n try:\n int(var)\n\n except:\n return False\n\n else:\n return True","def isSetVariable(self):\n return _libsbml.EventAssignment_isSetVariable(self)","def is_distributed_variable(v):\n return (isinstance(v, values_lib.DistributedValues) and\n isinstance(v, variables.Variable))","def check_variables(self, model):\n for rhs_var in model.rhs.keys():\n if rhs_var.name in model.variables.keys():\n var = model.variables[rhs_var.name]\n\n different_shapes = not np.array_equal(\n model.rhs[rhs_var].shape, var.shape\n )\n\n not_concatenation = not isinstance(var, pybamm.Concatenation)\n\n not_mult_by_one_vec = not (\n isinstance(\n var, (pybamm.Multiplication, pybamm.MatrixMultiplication)\n )\n and (\n pybamm.is_matrix_one(var.left)\n or pybamm.is_matrix_one(var.right)\n )\n )\n\n if different_shapes and not_concatenation and not_mult_by_one_vec:\n raise pybamm.ModelError(\n \"variable and its eqn must have the same shape after \"\n \"discretisation but variable.shape = \"\n \"{} and rhs.shape = {} for variable '{}'. \".format(\n var.shape, model.rhs[rhs_var].shape, var\n )\n )","def has_component(self, var_name):\n if var_name in self._var_names:\n return True\n else:\n return False","def test_has_exactly_type():\r\n\r\n return has_exactly_type(1, int) and not has_exactly_type(True, int) and has_exactly_type(True, bool)","def check_variables(self, valid_variables, valid_functions):\r\n if self.case_sensitive:\r\n casify = lambda x: x\r\n else:\r\n casify = lambda x: x.lower() # Lowercase for case insens.\r\n\r\n # Test if casify(X) is valid, but return the actual bad input (i.e. X)\r\n bad_vars = set(var for var in self.variables_used\r\n if casify(var) not in valid_variables)\r\n bad_vars.update(func for func in self.functions_used\r\n if casify(func) not in valid_functions)\r\n\r\n if bad_vars:\r\n raise UndefinedVariable(' '.join(sorted(bad_vars)))","def _check_for_variables(parser):\n for section in parser.sections():\n for key,value in parser.items(section):\n if len(re.findall(r\"\\$\", value))>0:\n #print value\n return True\n return False","def _check_valid_basic(self, get_params):\n try:\n if get_params(self.variable):\n return self.default\n except: # noqa e722\n pass\n return not self.default","def _validate_variable_parameters(func, params):\n if params is not None:\n for param in params:\n param_name, field_type = param['name'], param['field_type']\n if param_name not in func.__code__.co_varnames:\n raise AssertionError(\"Unknown parameter name {0} specified for\"\\\n \" variable {1}\".format(\n param_name, func.__name__))\n\n if field_type not in FIELD_LIST:\n raise AssertionError(\"Unknown field type {0} specified for\"\\\n \" variable {1} param {2}\".format(\n field_type, func.__name__, param_name))","def test_condition_vars(self):\n\n # If condition variables didn't work, a ``NameError`` would be raised.\n self.assertRaises(NotImplementedError, self.table.where,\n 'c_string > bound', {'bound': 0})\n\n def where_with_locals():\n bound = 'foo' # this wouldn't cause an error\n # silence pyflakes warnings\n self.assertIsInstance(bound, str)\n self.table.where('c_string > bound', {'bound': 0})\n self.assertRaises(NotImplementedError, where_with_locals)\n\n def where_with_globals():\n global _gvar\n _gvar = 'foo' # this wouldn't cause an error\n # silence pyflakes warnings\n self.assertIsInstance(_gvar, str)\n try:\n self.table.where('c_string > _gvar', {'_gvar': 0})\n finally:\n del _gvar # to keep global namespace clean\n self.assertRaises(NotImplementedError, where_with_globals)","def _isstrvar(self, index):\n return self._typlist[index] <= 244","def meets_condition(db_type: str):\n\t\t...","def check_occuring_variables(formula,variables_to_consider,allowed_variables) :\n variable_set=set(allowed_variables)\n for clause in formula :\n variables_in_clause = {abs(l) for l in clause if abs(l) in variables_to_consider}\n if not variables_in_clause <= variable_set:\n return False, [v for v in variables_in_clause if not v in variable_set] \n return True, []","def assert_variable_name(parsed_file: ModelRunInfo, variable_name: str):\n assert parsed_file.variable_name == variable_name","def do_check(var, varname, type=None, regex_tuple=None, value_tuple=None, can_be_none=False):\n\n if isinstance(var, list) or isinstance(var, set) or isinstance(var, tuple):\n\n x = 0\n for item in var:\n do_check(item, \"%s[%s]\" % (varname, x), type, regex_tuple, value_tuple, can_be_none)\n x = x + 1\n\n return\n\n if var is None and can_be_none:\n return\n\n if var is None and not can_be_none:\n raise ValueError(_none_error % varname)\n\n if type is not None:\n if not isinstance(var, type):\n bad_type = var.__class__.__name__\n raise ValueError(_type_error % (varname, type, bad_type))\n\n if regex_tuple is not None:\n if not isinstance(var, six.string_types):\n raise ValueError('%s was about to undergo a regex check, but is not of type basestring! Regex check was not performed' % (varname))\n if re.match(regex_tuple.regex, var) is None:\n raise ValueError(_regex_error % (varname, regex_tuple.title, var))\n\n if value_tuple is not None:\n if var not in value_tuple:\n raise ValueError(_tuple_error % (varname, value_tuple, var))\n return","def test_single_var(self):\r\n x, y, z = tensor.vectors('x', 'y', 'z')\r\n self.check([\r\n (x, x, (({}, True), )),\r\n (x, y, (({}, False), ({y: x}, True), )),\r\n (x, tensor.neg(x), (({}, False), )),\r\n (x, tensor.neg(y), (({}, False), )),\r\n ])","def is_splitable_var(var: Any) -> bool:\n if isinstance(var, DataSample):\n return True\n if isinstance(var, torch.Tensor):\n return True\n if isinstance(var, np.ndarray):\n return True\n if isinstance(var, abc.Sequence) and not isinstance(var, str):\n return True\n return False","def test_bool(self, env: yaenv.Env):\n _val = env.bool('BOOL_VAR')\n assert not _val and type(_val) == bool\n _val = env.bool('INT_VAR')\n assert _val and type(_val) == bool\n _val = env.bool('MISSING', True)\n assert _val and type(_val) == bool\n with pytest.raises(yaenv.EnvError) as err:\n _ = env.bool('FLOAT_VAR')\n assert 'Invalid boolean' in str(err.value)\n assert env.bool('MISSING') is None","def gen_type_assertion(var_name: str, ty: type) -> str:\n\n tys = type_str(ty)\n vars = [c for c in 'abcdefghijklmnop' if c != var_name][::-1]\n\n def helper(var_name, tys):\n tys = tys.strip()\n pre_bracket = tys.split(\"[\")[0].lower() # part before [ (or the entire string if no bracket\n ans = f\"type({var_name}) is {pre_bracket}\"\n if \"[\" in tys:\n inside = tys[tys.index(\"[\") + 1:-1]\n new_var = vars.pop()\n if pre_bracket == \"list\" or pre_bracket == \"set\":\n inside_check = helper(new_var, inside)\n # if \" and \" in inside_check:\n # inside_check = \"(\" + inside_check + \")\"\n ans += f\" and all({inside_check} for {new_var} in {var_name})\"\n elif pre_bracket == \"dict\":\n depth = 0\n for i, c in enumerate(inside):\n if c == \"[\":\n depth += 1\n elif c == \"]\":\n depth -= 1\n elif c == \",\" and depth == 0:\n break\n assert depth == 0 and c == \",\", \"Dict[(expecting comma inside)]\"\n key_var = vars.pop()\n key_check = helper(key_var, tys[:i])\n val_check = helper(new_var, tys[i + 1:])\n ans += f\" and all({key_check} and {val_check} for {key_var}, {new_var} in {var_name}.items())\"\n else:\n assert False, f\"Unknown type `{tys}`\"\n return ans\n\n return f\"assert {helper(var_name, tys)}, '{var_name} must be of type {tys}'\"","def test_valid_variables(self):\n with open(DEFINITIONS_SETTINGS_FILE, 'r') as openDefFile:\n definitionsContents = json.loads(openDefFile.read())\n with open(VARIABLES_SETTINGS_FILE, 'r') as openVarFile:\n variablesContents = json.loads(openVarFile.read())\n\n variablePattern = re.compile(r'{[^{^}]*}')\n for dictKey, dictContents in definitionsContents.items():\n variables = variablePattern.findall(str(dictContents))\n if len(variables) > 0:\n for variable in variables:\n valid = False\n for variableKey, variableItem in variablesContents.items():\n if variable == variableItem:\n valid = True\n break\n self.assertTrue(valid)","def _is_sync_var(self, vdef):\n # Pick memory variables among invaraint-loop variables\n if AsmParser.is_memory(vdef):\n # Thread local variable (e.g., %fs:0x28) cannot\n # be a sync. variable\n if AsmParser.is_thread_local_memory(self.arch, vdef):\n return False\n\n # Pick variables, which are written in a lexical form\n # This is needed since we will read the synchronization\n # variables in runtime.\n for rd_wrt in self.syncinfo.rd_wrt_set:\n if vdef.find(rd_wrt) != -1:\n return True\n return False","def __contains__(self, value):\n return value in self.var_names","def validate_var(path,scheme,var,val):\n if 'type' not in scheme:\n raise InvalidConfigTemplate(var+'.type: missing')\n typ=scheme.type\n if not isinstance(typ,str):\n raise InvalidConfigTemplate(var+'.type: must be a string')\n allowed=scheme.get('allowed',[])\n if not isinstance(allowed,list) and not isinstance(allowed,list_eval):\n raise InvalidConfigTemplate(var+'.allowed: must be a list')\n validate_type(path,var,typ,val,allowed)","def declare_variable(var, bound_variables):\n varname = var.name\n vartype = var.vartype\n\n # check if it is bound and has already been seen\n if bound_variables is not None and varname in bound_variables:\n yvar = bound_variables[varname].yices_term\n var.bound = True\n return yvar\n\n # check if it has already been seen\n yvar = Terms.get_by_name(varname)\n if yvar is not None:\n #now we need to see if it is free or bound\n tag = Terms.constructor(yvar)\n if tag == Constructor.VARIABLE:\n var.bound = True\n bound_variables[varname] = var\n return yvar\n\n type_term = vartype.yices_term\n type_name = vartype.name\n\n var_term = None\n\n if bound_variables is not None:\n # we need to make a yices variable not an uninterpreted term\n var_term = Terms.new_variable(type_term, varname)\n if var_term is None:\n sys.stderr.write(f'declare_variable: Term.new_variable failed {Yices.error_string()}\\n')\n return None\n bound_variables[varname] = var\n var.bound = True\n else:\n var_term = Terms.new_uninterpreted_term(type_term, varname)\n if var_term is None:\n sys.stderr.write(f'declare_variable: Term.new_uninterpreted_term failed {Yices.error_string()}\\n')\n return None\n\n YicesSignature.types_to_variables[type_name].add(var)\n\n return var_term","def check_fc(constraint, variable):\n values = []\n\n # Get the current scope\n variables = constraint.get_scope()\n\n # Track the unassigned value and create a list of values for the constraint we're checking\n for var in variables:\n values.append(var.get_assigned_value())\n # None is the index of the uninitialized value\n variable_index = values.index(None)\n\n # Pruned values\n pruned_variables = []\n\n # Check each domain, prune those that do not satisfy it\n for domain in variable.cur_domain():\n values[variable_index] = domain\n if not constraint.check(values):\n variable.prune_value(domain)\n pruned_variables.append((variable, domain))\n\n # Check for domain wipeout\n if variable.cur_domain_size() != 0:\n return (False, pruned_variables)\n elif variable.cur_domain_size() == 0:\n return (True, pruned_variables)","def _isstrvar(self, index):\n return self._typlist[index] <= 32768","def __contains__(self, name):\n return name in self._variables","def check_variable_copy_condition(\n nlp, phase_idx: int, use_from_phase_idx: int, name: str, decision_variable_attribute: str\n ):\n return (\n use_from_phase_idx is not None\n and use_from_phase_idx < phase_idx\n and name in getattr(nlp[use_from_phase_idx], decision_variable_attribute)\n )","def required_field(variable_to_test: any, err_string: str) -> None:\n if variable_to_test is None:\n print('\\n' + err_string + '\\n')\n sys.exit(1)"],"string":"[\n \"def _validate_variable(self, variable):\\n if variable is not None:\\n # test type\\n if not self.validate_type(variable):\\n return False\\n\\n return True\",\n \"def isvar(var):\\n return _coconut_tail_call(isinstance, var, (Const, Var))\",\n \"def _check_variable_definition(variable_name, variable_attrs):\\n\\n # Variable name must be type str\\n if type(variable_name) != str:\\n raise TypeError(\\\"Invalid variable name: \\\"+str(variable_name)+\\\" (must be string)\\\")\\n\\n # todo - add more tests to check validity of variable definition\",\n \"def _is_op_defined(t_vars) -> bool:\\n return all(t_var.name.startswith(\\\"Variable\\\") for t_var in t_vars)\",\n \"def _assigns_typevar(node: nodes.NodeNG | None) -> bool:\\n if isinstance(node, astroid.Call):\\n inferred = utils.safe_infer(node.func)\\n if (\\n isinstance(inferred, astroid.ClassDef)\\n and inferred.qname() in TYPE_VAR_QNAME\\n ):\\n return True\\n return False\",\n \"def _is_typevar(typeval: Type) -> bool:\\n return isinstance(typeval, TypeVar) # type: ignore\",\n \"def is_variable(item):\\n return len(item) > 0 and item[0].upper() == item[0]\",\n \"def _check_typevar(self, name: str, node: nodes.AssignName) -> None:\\n if isinstance(node.parent, nodes.Assign):\\n keywords = node.assign_type().value.keywords\\n args = node.assign_type().value.args\\n elif isinstance(node.parent, nodes.Tuple):\\n keywords = (\\n node.assign_type().value.elts[node.parent.elts.index(node)].keywords\\n )\\n args = node.assign_type().value.elts[node.parent.elts.index(node)].args\\n\\n variance = TypeVarVariance.invariant\\n name_arg = None\\n for kw in keywords:\\n if variance == TypeVarVariance.double_variant:\\n pass\\n elif kw.arg == \\\"covariant\\\" and kw.value.value:\\n variance = (\\n TypeVarVariance.covariant\\n if variance != TypeVarVariance.contravariant\\n else TypeVarVariance.double_variant\\n )\\n elif kw.arg == \\\"contravariant\\\" and kw.value.value:\\n variance = (\\n TypeVarVariance.contravariant\\n if variance != TypeVarVariance.covariant\\n else TypeVarVariance.double_variant\\n )\\n\\n if kw.arg == \\\"name\\\" and isinstance(kw.value, nodes.Const):\\n name_arg = kw.value.value\\n\\n if name_arg is None and args and isinstance(args[0], nodes.Const):\\n name_arg = args[0].value\\n\\n if variance == TypeVarVariance.double_variant:\\n self.add_message(\\n \\\"typevar-double-variance\\\",\\n node=node,\\n confidence=interfaces.INFERENCE,\\n )\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(\\\"\\\",),\\n confidence=interfaces.INFERENCE,\\n )\\n elif variance == TypeVarVariance.covariant and not name.endswith(\\\"_co\\\"):\\n suggest_name = f\\\"{re.sub('_contra$', '', name)}_co\\\"\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(f'. \\\"{name}\\\" is covariant, use \\\"{suggest_name}\\\" instead'),\\n confidence=interfaces.INFERENCE,\\n )\\n elif variance == TypeVarVariance.contravariant and not name.endswith(\\\"_contra\\\"):\\n suggest_name = f\\\"{re.sub('_co$', '', name)}_contra\\\"\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(f'. \\\"{name}\\\" is contravariant, use \\\"{suggest_name}\\\" instead'),\\n confidence=interfaces.INFERENCE,\\n )\\n elif variance == TypeVarVariance.invariant and (\\n name.endswith(\\\"_co\\\") or name.endswith(\\\"_contra\\\")\\n ):\\n suggest_name = re.sub(\\\"_contra$|_co$\\\", \\\"\\\", name)\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(f'. \\\"{name}\\\" is invariant, use \\\"{suggest_name}\\\" instead'),\\n confidence=interfaces.INFERENCE,\\n )\\n\\n if name_arg is not None and name_arg != name:\\n self.add_message(\\n \\\"typevar-name-mismatch\\\",\\n node=node,\\n args=(name_arg, name),\\n confidence=interfaces.INFERENCE,\\n )\",\n \"def has_value(var) :\\n return var != None\",\n \"def _should_use_varname_value(self, value):\\n if isinstance(value, KnownValue):\\n return type(value.val) in six.integer_types\\n elif (\\n type(value) is TypedValue\\n ): # Only replace exactly TypedValue(int), not subtypes\\n return value.typ in six.integer_types\\n else:\\n return value is UNRESOLVED_VALUE\",\n \"def check_input_type(var, type_name):\\n\\n type_options = [\\\"int\\\", \\\"float\\\", \\\"Date\\\", \\\"Region\\\"]\\n if type_name == type_options[0]:\\n if int(var):\\n return True\\n else:\\n return False\\n elif type_name == type_options[1]:\\n if float(var):\\n return True\\n else:\\n return False\\n elif type_name == type_options[2]:\\n if datetime.date.fromisoformat(var):\\n return True\\n else:\\n return False\\n elif type_name == type_options[3]:\\n valid_regions = [\\\"NW\\\", \\\"SW\\\", \\\"MN\\\", \\\"MS\\\", \\\"NE\\\", \\\"SE\\\"]\\n is_valid = False\\n for region in valid_regions:\\n if var == region:\\n is_valid = True\\n return is_valid\\n else:\\n Exception(\\\"This type doesn't exist in the checker!\\\")\",\n \"def test_exists(self, condition, undefined_paths, current_path):\\n var = str(condition.find('variable').text)\\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\\n current_path += ((var, 'undefined variable'),)\\n undefined_paths.add(current_path)\\n return False\\n else:\\n return True\",\n \"def typematch(variable, expectedtype):\\n\\n # Return the result\\n return isinstance(variable, expectedtype)\",\n \"def is_tvar(x):\\n return type(x) is T.TensorVariable\",\n \"def _is_var_declaration(fortress, filename, start):\\n v = \\\"var \\\"\\n return fortress.source_code[filename][start : start + len(v)] == v\",\n \"def has_type_var(annotation) -> bool:\\n return any(\\n is_type_var(arg) or has_type_var(arg)\\n for arg in getattr(annotation, \\\"__args__\\\", [])\\n )\",\n \"def _isintvar(self, index):\\n return 251 <= self._typlist[index] <= 253\",\n \"def is_variable(arg: Expr) -> bool:\\n return str(arg)[0].islower()\",\n \"def _isintvar(self, index):\\n return 65528 <= self._typlist[index] <= 65530\",\n \"def id_is_variable(self):\\n return not self.defined\",\n \"def isVariableDefined(self, varID):\\n \\n for i in range(self.varList.count()):\\n item = self.varList.item(i)\\n if varID == item.getVariable().id and not item.isQuickplotItem():\\n return True\\n return False\",\n \"def check_variable_line(self, line):\\n self.E_str = \\\"check_variable_line\\\"\\n line, any_vars = self.find_vars_in_str(line)\\n words = [i for i in line.split('=') if i]\\n words = self.fix_words(words)\\n\\n if len(words) < 2:\\n self.print_error(\\\"The syntax for declaring variables is: \\\"\\n + \\\"'<name> = <value>'\\\")\",\n \"def validVarConstructType(self,vartype):\\r\\n indArray = vartype.find('[]')\\r\\n if indArray>0:\\r\\n thisType = vartype[0:indArray]\\r\\n isArray = True\\r\\n else:\\r\\n thisType = vartype\\r\\n isArray = False\\r\\n \\r\\n if thisType in ('rng','range'):\\r\\n type = 'range'\\r\\n elif thisType in ('rate'):\\r\\n type = 'rate'\\r\\n elif thisType in ('amt','amount'):\\r\\n type = 'amount'\\r\\n elif thisType in ('minamt','minamount'):\\r\\n type = 'minamount'\\r\\n elif thisType in ('bool'):\\r\\n type = 'bool'\\r\\n else:\\r\\n print 'variable type must be range, rate, amount, minamount, bool (or abbreviated forms)'\\r\\n return False, ''\\r\\n \\r\\n return True, type, isArray\",\n \"def has_variable(self, col: str, name: str) -> bool:\\n if self.scope is None:\\n raise ValueError(\\\"Can't access variables on unbound modules\\\")\\n return self.scope.has_variable(col, name)\",\n \"def is_type_var(annotation) -> bool:\\n\\n return isinstance(annotation, typing.TypeVar) # type:ignore\",\n \"def has_variable(self, name):\\n return name in self._variables\",\n \"def varIsValid(self, var):\\n if len(var.getAxisList()) != 1:\\n return False\\n if self.myParent.numValues() != self.myParent.numValues():\\n return False\\n return True\",\n \"def validVarConstruct(self,thisvar):\\r\\n validLength = self.validVarConstructLength(thisvar)\\r\\n if not validLength:\\r\\n return False, '', '', False\\r\\n validName, varName = self.validVarConstructName(thisvar[0])\\r\\n if not validName:\\r\\n return False, '', '', False \\r\\n validType, varType, varArray = self.validVarConstructType(thisvar[1])\\r\\n if not validType:\\r\\n return False, '', '', False\\r\\n \\r\\n return True, varName, varType, varArray\",\n \"def has_var(self, var_name: str) -> bool:\\n is_var = var_name.startswith('var$')\\n\\n class Scopes:\\n Global = self.global_variables\\n Task = self.task_variables\\n Local = self.local_variables\\n\\n scope = Scopes.Local\\n\\n if is_var:\\n var_name = var_name[3:]\\n if var_name.startswith('$$$'):\\n scope = Scopes.Global\\n var_name = var_name[3:]\\n elif var_name.startswith('$$'):\\n scope = Scopes.Task\\n var_name = var_name[2:]\\n elif var_name.startswith('$'):\\n scope = Scopes.Local\\n var_name = var_name[1:]\\n\\n return var_name in scope.vars\",\n \"def condition_forward_checking(csp, var) :\\n return False\",\n \"def condition_forward_checking(csp, var) :\\n return False\",\n \"def validVarConstructLength(self,varlen):\\r\\n if len(varlen)!=2:\\r\\n print 'variable must specify name and type'\\r\\n return False\\r\\n else:\\r\\n return True\",\n \"def is_variable(pattern):\\n return (type(pattern) is str\\n and pattern[0] == '?'\\n and len(pattern) > 1\\n and pattern[1] != '*'\\n and pattern[1] in string.ascii_letters\\n and ' ' not in pattern)\",\n \"def _check_typevar(self) -> PossibleResult[T]:\\n if _is_typevar(self.constructor): # type: ignore\\n return Deserialize(\\n obj=self.obj,\\n constructor=(\\n Union[self.constructor.__constraints__] # type: ignore\\n if self.constructor.__constraints__ # type: ignore\\n else object\\n ),\\n depth=self.new_depth,\\n convert_primitives=self.convert_primitives,\\n ).run()\\n return NO_RESULT\",\n \"def _var_check(self):\\n missing = set()\\n for v in self.variables:\\n if getattr(self, v) is None:\\n missing.add(v)\\n self.missing = missing\",\n \"def check_evidence(self, variable_name, variable_value):\\n for i in xrange(0, len(self.sample_nodes)):\\n if self.sample_nodes[i].name == variable_name:\\n if self.sample_nodes[i].value == variable_value:\\n return True\\n else:\\n return False\\n\\n print \\\"whoops, I guess the evidence variable was not assigned in the event\\\"\\n return None\",\n \"def f_exists(self, varname):\\r\\n return (varname in self.locals_ptr)\",\n \"def is_variable_string(value):\\n if not isinstance(value, basestring):\\n return False\\n return bool(_property_string_pattern.match(value))\",\n \"def _check_variable(string, varname):\\r\\n prefix = '[(, ]' # Any character with the exception of '(, '\\r\\n suffix = '[), ]' # Any character with the exception of '), '\\r\\n pattern = prefix + varname + suffix\\r\\n re.match(pattern, string)\",\n \"def isSetVariable(self):\\n return _libsbml.Rule_isSetVariable(self)\",\n \"def test_types(question):\\n instance = question[\\\"instance\\\"]\\n for name, data in instance.get(\\\"variables\\\", {}).items():\\n assert \\\"optional\\\" not in data or isinstance(data[\\\"optional\\\"], bool)\\n if data.get(\\\"type\\\") == \\\"boolean\\\":\\n assert \\\"value\\\" not in data or isinstance(data[\\\"value\\\"], bool)\\n elif data.get(\\\"type\\\") in [\\\"integer\\\", \\\"long\\\"]:\\n assert \\\"value\\\" not in data or isinstance(data[\\\"value\\\"], int)\",\n \"def _check_valid_condition(self, get_params):\\n try:\\n variable = get_params(self.variable)\\n except: # noqa e722\\n variable = None\\n value = self.value\\n\\n # if None, return oppositely\\n if variable is None:\\n return not self.default\\n\\n # convert the value to a correct type\\n if isinstance(variable, bool):\\n value = bool(self.value)\\n elif isinstance(variable, Number):\\n try:\\n value = int(self.value)\\n except: # noqa e722\\n try:\\n value = float(self.value)\\n except: # noqa e722\\n # could not parse\\n return not self.default\\n\\n # compare and return the result\\n if self.condition == \\\"=\\\":\\n return (variable == value) == self.default\\n elif self.condition == \\\">\\\":\\n return (variable > value) == self.default\\n elif self.condition == \\\"<\\\":\\n return (variable < value) == self.default\",\n \"def __contains__(self, var: Union[Variable, int]) -> bool:\\n if isinstance(var, Variable):\\n return var in self.scope_vars\\n return var in self.scope_vids\",\n \"def legal_for(self, fvs : {EVar}) -> bool:\\n vs = {(v, v.type) for (v, pool) in self.vars()}\\n return all((v, v.type) in vs for v in fvs)\",\n \"def isVar(self, t: str) -> bool:\\n return t[0] != t[0].lower()\",\n \"def _check_variables(datasets, necessary_short_names):\\n dataset_name = datasets[0]['dataset']\\n necessary_short_names = set(necessary_short_names)\\n short_names = set(group_metadata(datasets, 'short_name').keys())\\n if short_names != necessary_short_names:\\n raise ValueError(\\n f\\\"Expected variables {necessary_short_names} for dataset \\\"\\n f\\\"'{dataset_name}', got {short_names}\\\")\",\n \"def check_var_attrs(self, cls, node):\\n ast = node.ast\\n declarator = ast.declarator\\n attrs = declarator.attrs\\n for attr in attrs:\\n if attr[0] == \\\"_\\\": # internal attribute\\n continue\\n # XXX - deref on class/struct members\\n if attr not in [\\\"name\\\", \\\"readonly\\\", \\\"dimension\\\", \\\"deref\\\"]:\\n raise RuntimeError(\\n \\\"Illegal attribute '{}' for variable '{}' at line {}\\\".format(\\n attr, node.name, node.linenumber\\n ) + \\\"\\\\nonly 'name', 'readonly', 'dimension' and 'deref' are allowed on variables\\\"\\n )\\n\\n is_ptr = declarator.is_indirect()\\n if attrs[\\\"dimension\\\"] and not is_ptr:\\n raise RuntimeError(\\n \\\"dimension attribute can only be \\\"\\n \\\"used on pointer and references\\\"\\n )\\n\\n self.parse_attrs(node, ast)\",\n \"def testConditionReasons(self):\\n \\n state = State.from_problem(self.prob)\\n\\n relevantVars = []\\n drive = self.dom.get_action(\\\"drive\\\")\\n with drive.instantiate([\\\"agent\\\", \\\"tru1\\\", \\\"apt1\\\"], self.prob):\\n self.assert_(state.is_satisfied(drive.precondition, relevantVars))\\n\\n relevantVars = set(relevantVars)\\n \\n s1 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"pos1\\\"]])\\n s2 = StateVariable(self.prob.functions[\\\"city-of\\\"][0], [self.prob[\\\"apt1\\\"]])\\n s3 = StateVariable(self.prob.functions[\\\"location-of\\\"][0], [self.prob[\\\"tru1\\\"]])\\n \\n self.assertEqual(len(relevantVars), 3)\\n self.assert_(s1 in relevantVars)\\n self.assert_(s2 in relevantVars)\\n self.assert_(s3 in relevantVars)\",\n \"def _check_var_conflicts(s, variables):\\n # check conflicts with variable names\\n vars_redefined = {x for x in s if x in variables}\\n if vars_redefined:\\n raise Exception('Variables redefined: {v}'.format(v=vars_redefined))\\n # check conflicts with values of arbitrary finite data types\\n for var, domain in variables.items():\\n # not arbitrary finite type ?\\n if not isinstance(domain, list):\\n continue\\n # var has arbitrary finite type\\n conflicting_values = {x for x in s if x in domain}\\n if conflicting_values:\\n raise Exception(\\n 'Values redefined: {v}'.format(v=conflicting_values))\",\n \"def has_variables(text):\\n matches = _property_pattern.findall(text)\\n return len(matches) > 0\",\n \"def _is_loop_invariant(self, var):\\n # does it rely on unknown source?\\n if var.find(\\\"#u\\\") != -1:\\n return False\\n # constant\\n if AsmParser.is_constant(var):\\n return True\\n # get an update set for a variable\\n update_set = self._get_update_set(var)\\n log.debug(\\\" UPDATE_SET: %s\\\" % update_set)\\n # if nothing is changed, it is loop-invariant\\n if not update_set:\\n return True\\n # if the same value is updated, it is loop-invariant\\n return self._update_same(update_set)\",\n \"def is_var (string):\\n if (string[0] == '?'):\\n return True\\n return False\",\n \"def _isnumvar(self, index):\\n return 65526 <= self._typlist[index] <= 65530\",\n \"def is_var(argument):\\n if argument[0] in list(string.ascii_uppercase):\\n return True\\n return False\",\n \"def variable_type(self, variable): # pragma: no cover\\n raise NotImplementedError('Implemented in child class')\",\n \"def is_allowed(self):\\n if self.structure.variable_dependant_path:\\n # fill in empty part of the path with the current path\\n if len(self.structure.variable_dependant_path) == 3:\\n dependant_var_path = (\\n self.path[0],\\n ) + self.structure.variable_dependant_path\\n elif len(self.structure.variable_dependant_path) == 2:\\n dependant_var_path = (\\n self.path[0],\\n self.path[1],\\n ) + self.structure.variable_dependant_path\\n elif len(self.structure.variable_dependant_path) == 1:\\n dependant_var_path = (\\n self.path[0],\\n self.path[1],\\n self.path[2],\\n ) + self.structure.variable_dependant_path\\n else:\\n dependant_var_path = None\\n\\n # get dependency\\n dependant_var = None\\n mf_data = self._simulation_data.mfdata\\n if dependant_var_path in mf_data:\\n dependant_var = mf_data[dependant_var_path]\\n\\n # resolve dependency\\n if self.structure.variable_value_when_active[0] == \\\"Exists\\\":\\n exists = self.structure.variable_value_when_active[1]\\n if dependant_var and exists.lower() == \\\"true\\\":\\n return True\\n elif not dependant_var and exists.lower() == \\\"false\\\":\\n return True\\n else:\\n return False\\n elif not dependant_var:\\n return False\\n elif self.structure.variable_value_when_active[0] == \\\">\\\":\\n min_val = self.structure.variable_value_when_active[1]\\n if dependant_var > float(min_val):\\n return True\\n else:\\n return False\\n elif self.structure.variable_value_when_active[0] == \\\"<\\\":\\n max_val = self.structure.variable_value_when_active[1]\\n if dependant_var < float(max_val):\\n return True\\n else:\\n return False\\n return True\",\n \"def ensure_type(var, *expected_types, _up_extra_frames=0):\\n for t in expected_types:\\n if isinstance(var, t):\\n return True\\n type_err = f'Type-checking caller: {get_caller_function(_up_extra_frames=_up_extra_frames)}(): For object (value = {var}), ' \\\\\\n f'expected type(s) was {expected_types} but instead found {type(var)}'\\n logger.error(type_err)\\n raise TypeError(type_err)\",\n \"def isConditional(self) -> bool:\\n ...\",\n \"def hasEditVariable(self, variable: Variable, /) -> bool:\\n ...\",\n \"def _check_variables_in_raw_data(self):\\n # make sure that all of the necessary variables are present\\n # or mapped via the variable dict\\n for key in [key for key in self._map_cols.keys()\\n if key not in ['block', 'choice_accuracy', 'ID']]:\\n assert self._map_cols[key] in self._raw_data.columns,\\\\\\n 'missing {} from raw data df columns'.format(\\n self._map_cols[key])\\n\\n condition_codes = self._raw_data[self._map_cols['condition']].unique()\\n for cond in ['go', 'stop']:\\n assert self._map_codes[cond] in condition_codes,\\\\\\n ('missing {} from column: '.format(self._map_codes[cond]),\\n self._map_cols[\\\"condition\\\"])\\n\\n # check that all unique non-nan values in the accuracy column \\n # can be mapped onto either correct or incorrect,\\n # as defined by the values in the var_dict.\\n if self._map_cols['choice_accuracy'] in self._raw_data.columns:\\n raw_acc_codes = self._raw_data[\\n self._map_cols['choice_accuracy']].unique()\\n raw_acc_codes = [i for i in raw_acc_codes if i==i]\\n map_acc_codes = [self._map_codes['correct'],\\n self._map_codes['incorrect']]\\n for acc_code in raw_acc_codes:\\n assert acc_code in map_acc_codes,\\\\\\n '{} present in {} column.'. format(\\n acc_code, self._cols[\\\"choice_accuracy\\\"]\\n )\\n\\n return True\",\n \"def is_variable(s):\\n return s[0] >= 'u' and s[0] <= 'z' and s.isalnum()\",\n \"def check(self):\\n\\n return self.variable.check(self.cval, self.conditional)\",\n \"def has_assignment_for(self, var):\\n return self.variable_to_value.get(var) != None\",\n \"def is_null(var):\\r\\n if var is None or not var: return True\\r\\n if any(isinstance(var, s) for s in [str, list, tuple, set]) and len(var) == 0: return True\\r\\n if isinstance(var, str) and var == '': return True\\r\\n if any( isinstance(var, s) for s in [int, float, complex, bool] ) and int(var) == 0: return True\\r\\n return False\",\n \"def validVarConstructStorage(self,varStorage):\\r\\n if varStorage in fortaxStorageName.integer:\\r\\n storage = fortaxStorage.integer\\r\\n elif varStorage in fortaxStorageName.logical:\\r\\n storage = fortaxStorage.logical\\r\\n elif varStorage in fortaxStorageName.double:\\r\\n storage = fortaxStorage.double\\r\\n elif varStorage in fortaxStorageName.integerarray:\\r\\n storage = fortaxStorage.integerarray\\r\\n elif varStorage in fortaxStorageName.logicalarray:\\r\\n storage = fortaxStorage.logicalarray\\r\\n elif varStorage in fortaxStorageName.doublearray:\\r\\n storage = fortaxStorage.doublearray\\r\\n else:\\r\\n print 'storage must be integer, integerarray, logical, logicalarray, double, doublearray (or abbreviated forms)'\\r\\n return False\\r\\n return True, storage\",\n \"def check_if_statement(self, line):\\n line = re.sub(\\\"^if *\\\", \\\"\\\", line)\\n if '(' not in line or ')' not in line:\\n self.print_error(\\\"Syntax error: If statements take the syntax if (condition) { ... }\\\",\\n errorFunc=SyntaxError)\\n\\n\\n # remove the brackets\\n statement, _ = gen_parse.get_str_between_delims(line, \\\"(\\\", \\\")\\\")\\n\\n\\n # Check all variables have been declared\\n any_vars = [i.strip('$') for i in re.findall(VAR_REGEX, statement)]\\n for var_name in any_vars:\\n if var_name not in self.variables:\\n self.print_error(f\\\"Unknown variable: {var_name}\\\")\",\n \"def require(var, condition, msg='wrong length'):\\n if not condition:\\n raise SyntaxError(tostr(var)+': '+msg)\",\n \"def _is_type_in_scope(self, name):\",\n \"def __validateTemplateVariables(self, vars):\\n for requiredVarName in self.varNames():\\n if requiredVarName not in vars:\\n raise VariableNotFoundError(\\n 'Could not find a value for the variable {0}'.format(\\n requiredVarName\\n )\\n )\",\n \"def is_var_line(line):\\n if '=' in line:\\n # Check it isn't some other command\\n for cmd in CMD_LIST:\\n if re.findall(f\\\"^{cmd} \\\", line):\\n return False\\n\\n str_txt, non_str = gen_parse.get_str_between_delims(line, '\\\"')\\n if any(j in non_str for j in '<>-+/*^'):\\n return False\\n return True\\n else:\\n return False\",\n \"def __checkInput(self, var):\\n try:\\n int(var)\\n\\n except:\\n return False\\n\\n else:\\n return True\",\n \"def isSetVariable(self):\\n return _libsbml.EventAssignment_isSetVariable(self)\",\n \"def is_distributed_variable(v):\\n return (isinstance(v, values_lib.DistributedValues) and\\n isinstance(v, variables.Variable))\",\n \"def check_variables(self, model):\\n for rhs_var in model.rhs.keys():\\n if rhs_var.name in model.variables.keys():\\n var = model.variables[rhs_var.name]\\n\\n different_shapes = not np.array_equal(\\n model.rhs[rhs_var].shape, var.shape\\n )\\n\\n not_concatenation = not isinstance(var, pybamm.Concatenation)\\n\\n not_mult_by_one_vec = not (\\n isinstance(\\n var, (pybamm.Multiplication, pybamm.MatrixMultiplication)\\n )\\n and (\\n pybamm.is_matrix_one(var.left)\\n or pybamm.is_matrix_one(var.right)\\n )\\n )\\n\\n if different_shapes and not_concatenation and not_mult_by_one_vec:\\n raise pybamm.ModelError(\\n \\\"variable and its eqn must have the same shape after \\\"\\n \\\"discretisation but variable.shape = \\\"\\n \\\"{} and rhs.shape = {} for variable '{}'. \\\".format(\\n var.shape, model.rhs[rhs_var].shape, var\\n )\\n )\",\n \"def has_component(self, var_name):\\n if var_name in self._var_names:\\n return True\\n else:\\n return False\",\n \"def test_has_exactly_type():\\r\\n\\r\\n return has_exactly_type(1, int) and not has_exactly_type(True, int) and has_exactly_type(True, bool)\",\n \"def check_variables(self, valid_variables, valid_functions):\\r\\n if self.case_sensitive:\\r\\n casify = lambda x: x\\r\\n else:\\r\\n casify = lambda x: x.lower() # Lowercase for case insens.\\r\\n\\r\\n # Test if casify(X) is valid, but return the actual bad input (i.e. X)\\r\\n bad_vars = set(var for var in self.variables_used\\r\\n if casify(var) not in valid_variables)\\r\\n bad_vars.update(func for func in self.functions_used\\r\\n if casify(func) not in valid_functions)\\r\\n\\r\\n if bad_vars:\\r\\n raise UndefinedVariable(' '.join(sorted(bad_vars)))\",\n \"def _check_for_variables(parser):\\n for section in parser.sections():\\n for key,value in parser.items(section):\\n if len(re.findall(r\\\"\\\\$\\\", value))>0:\\n #print value\\n return True\\n return False\",\n \"def _check_valid_basic(self, get_params):\\n try:\\n if get_params(self.variable):\\n return self.default\\n except: # noqa e722\\n pass\\n return not self.default\",\n \"def _validate_variable_parameters(func, params):\\n if params is not None:\\n for param in params:\\n param_name, field_type = param['name'], param['field_type']\\n if param_name not in func.__code__.co_varnames:\\n raise AssertionError(\\\"Unknown parameter name {0} specified for\\\"\\\\\\n \\\" variable {1}\\\".format(\\n param_name, func.__name__))\\n\\n if field_type not in FIELD_LIST:\\n raise AssertionError(\\\"Unknown field type {0} specified for\\\"\\\\\\n \\\" variable {1} param {2}\\\".format(\\n field_type, func.__name__, param_name))\",\n \"def test_condition_vars(self):\\n\\n # If condition variables didn't work, a ``NameError`` would be raised.\\n self.assertRaises(NotImplementedError, self.table.where,\\n 'c_string > bound', {'bound': 0})\\n\\n def where_with_locals():\\n bound = 'foo' # this wouldn't cause an error\\n # silence pyflakes warnings\\n self.assertIsInstance(bound, str)\\n self.table.where('c_string > bound', {'bound': 0})\\n self.assertRaises(NotImplementedError, where_with_locals)\\n\\n def where_with_globals():\\n global _gvar\\n _gvar = 'foo' # this wouldn't cause an error\\n # silence pyflakes warnings\\n self.assertIsInstance(_gvar, str)\\n try:\\n self.table.where('c_string > _gvar', {'_gvar': 0})\\n finally:\\n del _gvar # to keep global namespace clean\\n self.assertRaises(NotImplementedError, where_with_globals)\",\n \"def _isstrvar(self, index):\\n return self._typlist[index] <= 244\",\n \"def meets_condition(db_type: str):\\n\\t\\t...\",\n \"def check_occuring_variables(formula,variables_to_consider,allowed_variables) :\\n variable_set=set(allowed_variables)\\n for clause in formula :\\n variables_in_clause = {abs(l) for l in clause if abs(l) in variables_to_consider}\\n if not variables_in_clause <= variable_set:\\n return False, [v for v in variables_in_clause if not v in variable_set] \\n return True, []\",\n \"def assert_variable_name(parsed_file: ModelRunInfo, variable_name: str):\\n assert parsed_file.variable_name == variable_name\",\n \"def do_check(var, varname, type=None, regex_tuple=None, value_tuple=None, can_be_none=False):\\n\\n if isinstance(var, list) or isinstance(var, set) or isinstance(var, tuple):\\n\\n x = 0\\n for item in var:\\n do_check(item, \\\"%s[%s]\\\" % (varname, x), type, regex_tuple, value_tuple, can_be_none)\\n x = x + 1\\n\\n return\\n\\n if var is None and can_be_none:\\n return\\n\\n if var is None and not can_be_none:\\n raise ValueError(_none_error % varname)\\n\\n if type is not None:\\n if not isinstance(var, type):\\n bad_type = var.__class__.__name__\\n raise ValueError(_type_error % (varname, type, bad_type))\\n\\n if regex_tuple is not None:\\n if not isinstance(var, six.string_types):\\n raise ValueError('%s was about to undergo a regex check, but is not of type basestring! Regex check was not performed' % (varname))\\n if re.match(regex_tuple.regex, var) is None:\\n raise ValueError(_regex_error % (varname, regex_tuple.title, var))\\n\\n if value_tuple is not None:\\n if var not in value_tuple:\\n raise ValueError(_tuple_error % (varname, value_tuple, var))\\n return\",\n \"def test_single_var(self):\\r\\n x, y, z = tensor.vectors('x', 'y', 'z')\\r\\n self.check([\\r\\n (x, x, (({}, True), )),\\r\\n (x, y, (({}, False), ({y: x}, True), )),\\r\\n (x, tensor.neg(x), (({}, False), )),\\r\\n (x, tensor.neg(y), (({}, False), )),\\r\\n ])\",\n \"def is_splitable_var(var: Any) -> bool:\\n if isinstance(var, DataSample):\\n return True\\n if isinstance(var, torch.Tensor):\\n return True\\n if isinstance(var, np.ndarray):\\n return True\\n if isinstance(var, abc.Sequence) and not isinstance(var, str):\\n return True\\n return False\",\n \"def test_bool(self, env: yaenv.Env):\\n _val = env.bool('BOOL_VAR')\\n assert not _val and type(_val) == bool\\n _val = env.bool('INT_VAR')\\n assert _val and type(_val) == bool\\n _val = env.bool('MISSING', True)\\n assert _val and type(_val) == bool\\n with pytest.raises(yaenv.EnvError) as err:\\n _ = env.bool('FLOAT_VAR')\\n assert 'Invalid boolean' in str(err.value)\\n assert env.bool('MISSING') is None\",\n \"def gen_type_assertion(var_name: str, ty: type) -> str:\\n\\n tys = type_str(ty)\\n vars = [c for c in 'abcdefghijklmnop' if c != var_name][::-1]\\n\\n def helper(var_name, tys):\\n tys = tys.strip()\\n pre_bracket = tys.split(\\\"[\\\")[0].lower() # part before [ (or the entire string if no bracket\\n ans = f\\\"type({var_name}) is {pre_bracket}\\\"\\n if \\\"[\\\" in tys:\\n inside = tys[tys.index(\\\"[\\\") + 1:-1]\\n new_var = vars.pop()\\n if pre_bracket == \\\"list\\\" or pre_bracket == \\\"set\\\":\\n inside_check = helper(new_var, inside)\\n # if \\\" and \\\" in inside_check:\\n # inside_check = \\\"(\\\" + inside_check + \\\")\\\"\\n ans += f\\\" and all({inside_check} for {new_var} in {var_name})\\\"\\n elif pre_bracket == \\\"dict\\\":\\n depth = 0\\n for i, c in enumerate(inside):\\n if c == \\\"[\\\":\\n depth += 1\\n elif c == \\\"]\\\":\\n depth -= 1\\n elif c == \\\",\\\" and depth == 0:\\n break\\n assert depth == 0 and c == \\\",\\\", \\\"Dict[(expecting comma inside)]\\\"\\n key_var = vars.pop()\\n key_check = helper(key_var, tys[:i])\\n val_check = helper(new_var, tys[i + 1:])\\n ans += f\\\" and all({key_check} and {val_check} for {key_var}, {new_var} in {var_name}.items())\\\"\\n else:\\n assert False, f\\\"Unknown type `{tys}`\\\"\\n return ans\\n\\n return f\\\"assert {helper(var_name, tys)}, '{var_name} must be of type {tys}'\\\"\",\n \"def test_valid_variables(self):\\n with open(DEFINITIONS_SETTINGS_FILE, 'r') as openDefFile:\\n definitionsContents = json.loads(openDefFile.read())\\n with open(VARIABLES_SETTINGS_FILE, 'r') as openVarFile:\\n variablesContents = json.loads(openVarFile.read())\\n\\n variablePattern = re.compile(r'{[^{^}]*}')\\n for dictKey, dictContents in definitionsContents.items():\\n variables = variablePattern.findall(str(dictContents))\\n if len(variables) > 0:\\n for variable in variables:\\n valid = False\\n for variableKey, variableItem in variablesContents.items():\\n if variable == variableItem:\\n valid = True\\n break\\n self.assertTrue(valid)\",\n \"def _is_sync_var(self, vdef):\\n # Pick memory variables among invaraint-loop variables\\n if AsmParser.is_memory(vdef):\\n # Thread local variable (e.g., %fs:0x28) cannot\\n # be a sync. variable\\n if AsmParser.is_thread_local_memory(self.arch, vdef):\\n return False\\n\\n # Pick variables, which are written in a lexical form\\n # This is needed since we will read the synchronization\\n # variables in runtime.\\n for rd_wrt in self.syncinfo.rd_wrt_set:\\n if vdef.find(rd_wrt) != -1:\\n return True\\n return False\",\n \"def __contains__(self, value):\\n return value in self.var_names\",\n \"def validate_var(path,scheme,var,val):\\n if 'type' not in scheme:\\n raise InvalidConfigTemplate(var+'.type: missing')\\n typ=scheme.type\\n if not isinstance(typ,str):\\n raise InvalidConfigTemplate(var+'.type: must be a string')\\n allowed=scheme.get('allowed',[])\\n if not isinstance(allowed,list) and not isinstance(allowed,list_eval):\\n raise InvalidConfigTemplate(var+'.allowed: must be a list')\\n validate_type(path,var,typ,val,allowed)\",\n \"def declare_variable(var, bound_variables):\\n varname = var.name\\n vartype = var.vartype\\n\\n # check if it is bound and has already been seen\\n if bound_variables is not None and varname in bound_variables:\\n yvar = bound_variables[varname].yices_term\\n var.bound = True\\n return yvar\\n\\n # check if it has already been seen\\n yvar = Terms.get_by_name(varname)\\n if yvar is not None:\\n #now we need to see if it is free or bound\\n tag = Terms.constructor(yvar)\\n if tag == Constructor.VARIABLE:\\n var.bound = True\\n bound_variables[varname] = var\\n return yvar\\n\\n type_term = vartype.yices_term\\n type_name = vartype.name\\n\\n var_term = None\\n\\n if bound_variables is not None:\\n # we need to make a yices variable not an uninterpreted term\\n var_term = Terms.new_variable(type_term, varname)\\n if var_term is None:\\n sys.stderr.write(f'declare_variable: Term.new_variable failed {Yices.error_string()}\\\\n')\\n return None\\n bound_variables[varname] = var\\n var.bound = True\\n else:\\n var_term = Terms.new_uninterpreted_term(type_term, varname)\\n if var_term is None:\\n sys.stderr.write(f'declare_variable: Term.new_uninterpreted_term failed {Yices.error_string()}\\\\n')\\n return None\\n\\n YicesSignature.types_to_variables[type_name].add(var)\\n\\n return var_term\",\n \"def check_fc(constraint, variable):\\n values = []\\n\\n # Get the current scope\\n variables = constraint.get_scope()\\n\\n # Track the unassigned value and create a list of values for the constraint we're checking\\n for var in variables:\\n values.append(var.get_assigned_value())\\n # None is the index of the uninitialized value\\n variable_index = values.index(None)\\n\\n # Pruned values\\n pruned_variables = []\\n\\n # Check each domain, prune those that do not satisfy it\\n for domain in variable.cur_domain():\\n values[variable_index] = domain\\n if not constraint.check(values):\\n variable.prune_value(domain)\\n pruned_variables.append((variable, domain))\\n\\n # Check for domain wipeout\\n if variable.cur_domain_size() != 0:\\n return (False, pruned_variables)\\n elif variable.cur_domain_size() == 0:\\n return (True, pruned_variables)\",\n \"def _isstrvar(self, index):\\n return self._typlist[index] <= 32768\",\n \"def __contains__(self, name):\\n return name in self._variables\",\n \"def check_variable_copy_condition(\\n nlp, phase_idx: int, use_from_phase_idx: int, name: str, decision_variable_attribute: str\\n ):\\n return (\\n use_from_phase_idx is not None\\n and use_from_phase_idx < phase_idx\\n and name in getattr(nlp[use_from_phase_idx], decision_variable_attribute)\\n )\",\n \"def required_field(variable_to_test: any, err_string: str) -> None:\\n if variable_to_test is None:\\n print('\\\\n' + err_string + '\\\\n')\\n sys.exit(1)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.71227634","0.6907246","0.6733456","0.65082616","0.64736354","0.645199","0.64293915","0.63758117","0.6359905","0.63548344","0.63531965","0.63153076","0.6288625","0.62509894","0.62427473","0.62259036","0.6190489","0.6148015","0.6144128","0.6127952","0.6122063","0.61206627","0.61156344","0.59590524","0.59487283","0.59395254","0.59152746","0.5911148","0.59111047","0.5899859","0.5899859","0.58719134","0.5866765","0.5850022","0.5841629","0.581042","0.58024496","0.57690823","0.5761737","0.5752911","0.57374036","0.5732264","0.5721598","0.57187325","0.57125676","0.57036805","0.56967556","0.5696496","0.56858516","0.5669147","0.5669126","0.56463856","0.56348664","0.56281734","0.55886763","0.5588665","0.5585577","0.5583456","0.5581264","0.55770695","0.5575168","0.55700797","0.55623305","0.5546092","0.5533963","0.55326754","0.5525572","0.5514171","0.55139214","0.55121845","0.5510192","0.55067164","0.55042994","0.5497286","0.5495142","0.54853505","0.54617983","0.5460424","0.5459462","0.5454106","0.5446562","0.5429932","0.5401699","0.5401633","0.53977615","0.5392425","0.5382831","0.5379878","0.5377905","0.53698236","0.53632337","0.5360905","0.53441256","0.53430426","0.532743","0.53261334","0.5325288","0.5313545","0.5312494","0.5293229"],"string":"[\n \"0.71227634\",\n \"0.6907246\",\n \"0.6733456\",\n \"0.65082616\",\n \"0.64736354\",\n \"0.645199\",\n \"0.64293915\",\n \"0.63758117\",\n \"0.6359905\",\n \"0.63548344\",\n \"0.63531965\",\n \"0.63153076\",\n \"0.6288625\",\n \"0.62509894\",\n \"0.62427473\",\n \"0.62259036\",\n \"0.6190489\",\n \"0.6148015\",\n \"0.6144128\",\n \"0.6127952\",\n \"0.6122063\",\n \"0.61206627\",\n \"0.61156344\",\n \"0.59590524\",\n \"0.59487283\",\n \"0.59395254\",\n \"0.59152746\",\n \"0.5911148\",\n \"0.59111047\",\n \"0.5899859\",\n \"0.5899859\",\n \"0.58719134\",\n \"0.5866765\",\n \"0.5850022\",\n \"0.5841629\",\n \"0.581042\",\n \"0.58024496\",\n \"0.57690823\",\n \"0.5761737\",\n \"0.5752911\",\n \"0.57374036\",\n \"0.5732264\",\n \"0.5721598\",\n \"0.57187325\",\n \"0.57125676\",\n \"0.57036805\",\n \"0.56967556\",\n \"0.5696496\",\n \"0.56858516\",\n \"0.5669147\",\n \"0.5669126\",\n \"0.56463856\",\n \"0.56348664\",\n \"0.56281734\",\n \"0.55886763\",\n \"0.5588665\",\n \"0.5585577\",\n \"0.5583456\",\n \"0.5581264\",\n \"0.55770695\",\n \"0.5575168\",\n \"0.55700797\",\n \"0.55623305\",\n \"0.5546092\",\n \"0.5533963\",\n \"0.55326754\",\n \"0.5525572\",\n \"0.5514171\",\n \"0.55139214\",\n \"0.55121845\",\n \"0.5510192\",\n \"0.55067164\",\n \"0.55042994\",\n \"0.5497286\",\n \"0.5495142\",\n \"0.54853505\",\n \"0.54617983\",\n \"0.5460424\",\n \"0.5459462\",\n \"0.5454106\",\n \"0.5446562\",\n \"0.5429932\",\n \"0.5401699\",\n \"0.5401633\",\n \"0.53977615\",\n \"0.5392425\",\n \"0.5382831\",\n \"0.5379878\",\n \"0.5377905\",\n \"0.53698236\",\n \"0.53632337\",\n \"0.5360905\",\n \"0.53441256\",\n \"0.53430426\",\n \"0.532743\",\n \"0.53261334\",\n \"0.5325288\",\n \"0.5313545\",\n \"0.5312494\",\n \"0.5293229\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.71669835"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13074,"cells":{"query":{"kind":"string","value":"Tests if an 'exists' type condition is welldefined."},"document":{"kind":"string","value":"def test_exists(self, condition, undefined_paths, current_path):\n var = str(condition.find('variable').text)\n if not var in self.variables.get_keys() and self.fail_on_undefined_vars:\n current_path += ((var, 'undefined variable'),)\n undefined_paths.add(current_path)\n return False\n else:\n return True"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def exist(x):\n return x is not None","def exists(self):\n return True","def exists(self):\n return True","def definition_exists(name: str) -> bool:\n try:\n return bool(lookup_definition(name))\n except:\n return False","def exists(self):\n return self.obj is not None","def objExists(*args, **kwargs)->bool:\n pass","def exists(self):\n self.cursor.execute(f\"\"\"\n SELECT 1\n FROM {self.table_name}\n WHERE {self.lookup_type}='{self.word}'\n \"\"\")\n return True if self.cursor.fetchone() else False","def exists(self) -> bool:\n try:\n result = self.get()\n except KeyError:\n return False\n return True","def __bool__(self):\n return self.taxonomy.exists","def exist(self):","def check_exists(cls, **kwargs):\n return bool(cls.query.filter_by(**kwargs).first())","def exists(self, arg):\n raise NotImplementedError","def test_exists_false(self):\n self.assertFalse(Sample.exists('Not_a_Sample', self.sample_template))","def _exists (self):\n cursor = self._exec (self.select)\n return bool (cursor.fetchall ())","def f_exists(self, varname):\r\n return (varname in self.locals_ptr)","def is_present(cls):\n raise NotImplementedError()","def hasattr(x, name) -> bool:\n pass","def test_exists_false(self):\n self.assertFalse(PrepTemplate.exists(2))","def isExist(data):\n return True/False","def _exists(cursor, table, data):\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\n return bool(cursor.fetchone())","def key_exists(key, dictionary):\n return key in dictionary and dictionary[key] is not None","def test_exists_false(self):\n self.assertFalse(PrepSample.exists('Not_a_Sample', self.prep_template))","def exists(self):\n return bool(self.get())","def test_exists(self):\n d = self._examineOrSelect()\n self._response(b'* 3 EXISTS')\n self.assertEqual(\n self.successResultOf(d),\n {'READ-WRITE': False, 'EXISTS': 3})","def exists(self):\n if self._exists is None:\n self._exists = \\\n bool(\n self.oxdb.get_executed_cursor(\n EXISTS, self.variable_name).fetchone())\n\n return self._exists","def exists(self, obj):\n return False","def exists(self, name):\n raise NotImplementedError()","def exists(self):\n return _os.path.exists(self.__str__())","def exists(self, path: str) -> bool:\n pass","def exists(path: str) -> bool:\n pass","def exists(self):\n return os.path.isfile(self.location)","async def exists(self, payload: TPayload) -> bool:","def exists(path):\n return get_instance(path).exists(path)","def test_exists_true(self):\n self.assertTrue(PrepTemplate.exists(1))","def exists_type(self, type):\n for i in range(1, self.grid_size - 1):\n for j in range(1, self.grid_size - 1):\n obj = self.grid.get(i, j)\n if obj and obj.type == type:\n return True\n return False","def exists():\n check50.include(\"data\")\n check50.exists(\"adventure.py\")\n check50.exists(\"room.py\")","def is_valid(self, ifname):\n self.ensure_mapping()\n return ifname in self.generic_mapping","def exists(path: str) -> bool:\n result = Stat._result(path, throw=False)\n return not isinstance(result, BaseException)","def _verify_key_exists(self, key, lookup_dict):\n exists = False\n if get_occurrence_of_key(lookup_dict, key) > 0:\n exists = True\n return exists","def key_exists(dictionary, key):\n\n exists = dictionary.get(key, None)\n return exists is not None","def Exists(self, path: str) -> bool:\n ...","def test_exists(self):\n with self.assertRaises(IncompetentQiitaDeveloperError):\n BaseSample.exists('SKM7.640188', SampleTemplate(1))","def test_exist(self):\n with self.assertRaises(IncompetentQiitaDeveloperError):\n MetadataTemplate.exists(self.study)","def exists(self):\n return self.properties.get(\"Exists\", None)","def exists(self) -> bool:\n doc_ref = self.doc_ref\n if isinstance(doc_ref, DocumentReference):\n return doc_ref.get().exists\n return False","def exists(sim):\n return (sim['N'] > 0)","def exists(key: Union[MetadataKey, DatasetKey]) -> bool:\n if key.disk_format not in STRATEGIES:\n raise\n return STRATEGIES[key.disk_format].exists(key)","def exists(self):\r\n return os.path.exists(self.full_path)","def test_exists_true(self):\n self.assertTrue(SampleTemplate.exists(self.test_study.id))","def file_exists(fpath):\n # @todo - Use any()\n \n if os.path.exists(fpath) and os.path.isfile(fpath) and os.stat(fpath).st_size != 0:\n return True\n else: \n return False","def exists(self):\n return len(list(self.measures)) > 0","def exists(self, path):\n return self.dir_exists(path) or self.file_exists(path)","def __contains__(self, name):\n return hasattr(self, name)","def _has(self, key):\n path = self._get_key_path(key)\n return exists(path)","def not_exists(self, **kwargs):\n if 'timeout' in kwargs:\n timeout = (kwargs['timeout'])\n else:\n timeout = 30\n\n start_time = time()\n\n kwargs['timeout'] = 0 # we want exists to return immediately\n while True:\n elem = self.exists(**kwargs)\n if not elem:\n return True\n\n if time() - start_time > timeout:\n return False","def exists(self):\n try:\n self.world.find(self.ehandle)\n except KeyError:\n return False\n else:\n return True","def test_exists_false(self):\n self.assertFalse(SampleTemplate.exists(self.new_study.id))","def exists(self, answer):\n return self.find(answer) is not None","def function_exists(val, scope = globals()):\n if not isinstance(scope, dict):\n return (hasattr(scope, val) and callable(getattr(scope, val)))\n else:\n return (scope.has_key(val) and callable(scope[val]))","def check_list_exists(this_list=[]):\n if isinstance(this_list, list) and len(this_list) > 0:\n return True\n else:\n return False","def is_element_exists(self, locator_type, locator):\n try:\n self.wait_until_element_find(locator_type, locator)\n except TimeoutException:\n return False\n return True","def exists(self):\n return self.path.exists()","def exists (self, db):\n return hasattr(self, db) and isinstance(getattr(self, db), Database)","def check_action_type_exists(\n action_type_id: int\n) -> None:\n if not db.session.query(db.exists().where(models.ActionType.id == action_type_id)).scalar():\n raise errors.ActionTypeDoesNotExistError()","def exists(self, key_name: str) -> bool:\n pass","def test_has_exactly_type():\r\n\r\n return has_exactly_type(1, int) and not has_exactly_type(True, int) and has_exactly_type(True, bool)","def check_if_exists(self, bookID):\n query = f\"\"\"SELECT * from {TABLE} WHERE bookID = '{bookID}';\"\"\"\n res = self.cursor.execute(query)\n\n if self.cursor.fetchall():\n return True\n else:\n return False","def exists(self) -> bool:\n self.connection.describe_activity_type(self.domain.name, self.name, self.version)\n return True","def _is_element_present():\r\n return self.q(css=element_selector).present","def is_file_exists(self):\n pass","def exists(identifier, network):\n foo = next(load(identifier, network), None)\n return foo is not None","def _has(self, name):\n return hasattr(self._, name)","def type_exists(self, doc_dict, server=False):\n es = self.get_es()\n type_string = self.get_type_string(doc_dict)\n\n if server and self.online:\n type_path = \"%(index)s/%(type_string)s\" % (\n {\n 'index': self.es_index,\n 'type_string': type_string\n })\n head_result = es.head(type_path)\n self.seen_types[type_string] = head_result\n return head_result\n else:\n return type_string in self.seen_types","def _item_exists(self, location):\n \"Does nothing\"","def exists(self, selector):\n return not self.main_frame.findFirstElement(selector).isNull()\n\n\n #TODO: Still not work.","def exists(path: str) -> bool:\n return _fs().exists(path)","def exists(self, path: PathLike):","def __contains__(self, key):\n return hasattr(self, key)","def exists(self):\n\t\tif self.hasUdim:\n\t\t\treturn len( self.udimPaths ) != 0\n\t\treturn super( textureFile, self ).exists","def particleExists(*args, **kwargs)->bool:\n pass","def exists(self, url):\n return (self.base_path / url).exists()","def global_exists(self, global_name):\n return self.evaluate('!(typeof %s === \"undefined\");' %\n global_name)","def resource_exists(uri: Optional[str]) -> bool:\n\n if uri is None:\n return True\n\n # TODO Replace after finding way to pass custom fs through FireO validator\n if uri.startswith(\"gs://\"):\n return True\n\n else:\n # Get file system\n fs, uri = url_to_fs(uri)\n\n # Check exists\n if fs.exists(uri):\n return True\n\n return False","def test_exists_true(self):\n self.assertTrue(Sample.exists(self.sample_id, self.sample_template))","def exists(self) -> bool:\n p = pathlib.Path(self.summary_path)\n return p.exists()","def exists(self):\n return Criteria(op=\"$exists\", left=self, right=True)","def exists(self) -> bool:\n return self._file_exists()","def exists(self):\n\n if self:\n pass","def exists(_env):\n return True","def exists(_env):\n return True","def is_defined(self, name):\n return name in self._definitions","def _url_exists(self, url):\n return url_exists(url)","def testForExistence(self):\n self.assertTrue(cached_list_logic.isCachedListExists('cached_list'))\n self.assertFalse(cached_list_logic.isCachedListExists('none_existent'))","def exists(self, Search_ID):\n if self.get_id(Search_ID) is None:\n return False\n else:\n return True","def exists(self):\n if self._result_cache is None:\n return self.query.has_results(using=self.db)\n return bool(self._result_cache)","def __contains__(self, key):\n return self._lookup(key).value is not None","def exists(self):\n # TODO: What about broken sym-links?\n return os.path.exists(self.path)","def exists(self):\n\n return os.path.exists(self.path)","def has(self) -> bool:\n\n return self.scopefunc() in self.registry","def exists(obj: Dict, path: str) -> bool:\n\n return get(obj, path) is not None"],"string":"[\n \"def exist(x):\\n return x is not None\",\n \"def exists(self):\\n return True\",\n \"def exists(self):\\n return True\",\n \"def definition_exists(name: str) -> bool:\\n try:\\n return bool(lookup_definition(name))\\n except:\\n return False\",\n \"def exists(self):\\n return self.obj is not None\",\n \"def objExists(*args, **kwargs)->bool:\\n pass\",\n \"def exists(self):\\n self.cursor.execute(f\\\"\\\"\\\"\\n SELECT 1\\n FROM {self.table_name}\\n WHERE {self.lookup_type}='{self.word}'\\n \\\"\\\"\\\")\\n return True if self.cursor.fetchone() else False\",\n \"def exists(self) -> bool:\\n try:\\n result = self.get()\\n except KeyError:\\n return False\\n return True\",\n \"def __bool__(self):\\n return self.taxonomy.exists\",\n \"def exist(self):\",\n \"def check_exists(cls, **kwargs):\\n return bool(cls.query.filter_by(**kwargs).first())\",\n \"def exists(self, arg):\\n raise NotImplementedError\",\n \"def test_exists_false(self):\\n self.assertFalse(Sample.exists('Not_a_Sample', self.sample_template))\",\n \"def _exists (self):\\n cursor = self._exec (self.select)\\n return bool (cursor.fetchall ())\",\n \"def f_exists(self, varname):\\r\\n return (varname in self.locals_ptr)\",\n \"def is_present(cls):\\n raise NotImplementedError()\",\n \"def hasattr(x, name) -> bool:\\n pass\",\n \"def test_exists_false(self):\\n self.assertFalse(PrepTemplate.exists(2))\",\n \"def isExist(data):\\n return True/False\",\n \"def _exists(cursor, table, data):\\n cursor.execute('SELECT 1 FROM {} WHERE ({}) = ({})'.format(table, *_query_fields(data)), data)\\n return bool(cursor.fetchone())\",\n \"def key_exists(key, dictionary):\\n return key in dictionary and dictionary[key] is not None\",\n \"def test_exists_false(self):\\n self.assertFalse(PrepSample.exists('Not_a_Sample', self.prep_template))\",\n \"def exists(self):\\n return bool(self.get())\",\n \"def test_exists(self):\\n d = self._examineOrSelect()\\n self._response(b'* 3 EXISTS')\\n self.assertEqual(\\n self.successResultOf(d),\\n {'READ-WRITE': False, 'EXISTS': 3})\",\n \"def exists(self):\\n if self._exists is None:\\n self._exists = \\\\\\n bool(\\n self.oxdb.get_executed_cursor(\\n EXISTS, self.variable_name).fetchone())\\n\\n return self._exists\",\n \"def exists(self, obj):\\n return False\",\n \"def exists(self, name):\\n raise NotImplementedError()\",\n \"def exists(self):\\n return _os.path.exists(self.__str__())\",\n \"def exists(self, path: str) -> bool:\\n pass\",\n \"def exists(path: str) -> bool:\\n pass\",\n \"def exists(self):\\n return os.path.isfile(self.location)\",\n \"async def exists(self, payload: TPayload) -> bool:\",\n \"def exists(path):\\n return get_instance(path).exists(path)\",\n \"def test_exists_true(self):\\n self.assertTrue(PrepTemplate.exists(1))\",\n \"def exists_type(self, type):\\n for i in range(1, self.grid_size - 1):\\n for j in range(1, self.grid_size - 1):\\n obj = self.grid.get(i, j)\\n if obj and obj.type == type:\\n return True\\n return False\",\n \"def exists():\\n check50.include(\\\"data\\\")\\n check50.exists(\\\"adventure.py\\\")\\n check50.exists(\\\"room.py\\\")\",\n \"def is_valid(self, ifname):\\n self.ensure_mapping()\\n return ifname in self.generic_mapping\",\n \"def exists(path: str) -> bool:\\n result = Stat._result(path, throw=False)\\n return not isinstance(result, BaseException)\",\n \"def _verify_key_exists(self, key, lookup_dict):\\n exists = False\\n if get_occurrence_of_key(lookup_dict, key) > 0:\\n exists = True\\n return exists\",\n \"def key_exists(dictionary, key):\\n\\n exists = dictionary.get(key, None)\\n return exists is not None\",\n \"def Exists(self, path: str) -> bool:\\n ...\",\n \"def test_exists(self):\\n with self.assertRaises(IncompetentQiitaDeveloperError):\\n BaseSample.exists('SKM7.640188', SampleTemplate(1))\",\n \"def test_exist(self):\\n with self.assertRaises(IncompetentQiitaDeveloperError):\\n MetadataTemplate.exists(self.study)\",\n \"def exists(self):\\n return self.properties.get(\\\"Exists\\\", None)\",\n \"def exists(self) -> bool:\\n doc_ref = self.doc_ref\\n if isinstance(doc_ref, DocumentReference):\\n return doc_ref.get().exists\\n return False\",\n \"def exists(sim):\\n return (sim['N'] > 0)\",\n \"def exists(key: Union[MetadataKey, DatasetKey]) -> bool:\\n if key.disk_format not in STRATEGIES:\\n raise\\n return STRATEGIES[key.disk_format].exists(key)\",\n \"def exists(self):\\r\\n return os.path.exists(self.full_path)\",\n \"def test_exists_true(self):\\n self.assertTrue(SampleTemplate.exists(self.test_study.id))\",\n \"def file_exists(fpath):\\n # @todo - Use any()\\n \\n if os.path.exists(fpath) and os.path.isfile(fpath) and os.stat(fpath).st_size != 0:\\n return True\\n else: \\n return False\",\n \"def exists(self):\\n return len(list(self.measures)) > 0\",\n \"def exists(self, path):\\n return self.dir_exists(path) or self.file_exists(path)\",\n \"def __contains__(self, name):\\n return hasattr(self, name)\",\n \"def _has(self, key):\\n path = self._get_key_path(key)\\n return exists(path)\",\n \"def not_exists(self, **kwargs):\\n if 'timeout' in kwargs:\\n timeout = (kwargs['timeout'])\\n else:\\n timeout = 30\\n\\n start_time = time()\\n\\n kwargs['timeout'] = 0 # we want exists to return immediately\\n while True:\\n elem = self.exists(**kwargs)\\n if not elem:\\n return True\\n\\n if time() - start_time > timeout:\\n return False\",\n \"def exists(self):\\n try:\\n self.world.find(self.ehandle)\\n except KeyError:\\n return False\\n else:\\n return True\",\n \"def test_exists_false(self):\\n self.assertFalse(SampleTemplate.exists(self.new_study.id))\",\n \"def exists(self, answer):\\n return self.find(answer) is not None\",\n \"def function_exists(val, scope = globals()):\\n if not isinstance(scope, dict):\\n return (hasattr(scope, val) and callable(getattr(scope, val)))\\n else:\\n return (scope.has_key(val) and callable(scope[val]))\",\n \"def check_list_exists(this_list=[]):\\n if isinstance(this_list, list) and len(this_list) > 0:\\n return True\\n else:\\n return False\",\n \"def is_element_exists(self, locator_type, locator):\\n try:\\n self.wait_until_element_find(locator_type, locator)\\n except TimeoutException:\\n return False\\n return True\",\n \"def exists(self):\\n return self.path.exists()\",\n \"def exists (self, db):\\n return hasattr(self, db) and isinstance(getattr(self, db), Database)\",\n \"def check_action_type_exists(\\n action_type_id: int\\n) -> None:\\n if not db.session.query(db.exists().where(models.ActionType.id == action_type_id)).scalar():\\n raise errors.ActionTypeDoesNotExistError()\",\n \"def exists(self, key_name: str) -> bool:\\n pass\",\n \"def test_has_exactly_type():\\r\\n\\r\\n return has_exactly_type(1, int) and not has_exactly_type(True, int) and has_exactly_type(True, bool)\",\n \"def check_if_exists(self, bookID):\\n query = f\\\"\\\"\\\"SELECT * from {TABLE} WHERE bookID = '{bookID}';\\\"\\\"\\\"\\n res = self.cursor.execute(query)\\n\\n if self.cursor.fetchall():\\n return True\\n else:\\n return False\",\n \"def exists(self) -> bool:\\n self.connection.describe_activity_type(self.domain.name, self.name, self.version)\\n return True\",\n \"def _is_element_present():\\r\\n return self.q(css=element_selector).present\",\n \"def is_file_exists(self):\\n pass\",\n \"def exists(identifier, network):\\n foo = next(load(identifier, network), None)\\n return foo is not None\",\n \"def _has(self, name):\\n return hasattr(self._, name)\",\n \"def type_exists(self, doc_dict, server=False):\\n es = self.get_es()\\n type_string = self.get_type_string(doc_dict)\\n\\n if server and self.online:\\n type_path = \\\"%(index)s/%(type_string)s\\\" % (\\n {\\n 'index': self.es_index,\\n 'type_string': type_string\\n })\\n head_result = es.head(type_path)\\n self.seen_types[type_string] = head_result\\n return head_result\\n else:\\n return type_string in self.seen_types\",\n \"def _item_exists(self, location):\\n \\\"Does nothing\\\"\",\n \"def exists(self, selector):\\n return not self.main_frame.findFirstElement(selector).isNull()\\n\\n\\n #TODO: Still not work.\",\n \"def exists(path: str) -> bool:\\n return _fs().exists(path)\",\n \"def exists(self, path: PathLike):\",\n \"def __contains__(self, key):\\n return hasattr(self, key)\",\n \"def exists(self):\\n\\t\\tif self.hasUdim:\\n\\t\\t\\treturn len( self.udimPaths ) != 0\\n\\t\\treturn super( textureFile, self ).exists\",\n \"def particleExists(*args, **kwargs)->bool:\\n pass\",\n \"def exists(self, url):\\n return (self.base_path / url).exists()\",\n \"def global_exists(self, global_name):\\n return self.evaluate('!(typeof %s === \\\"undefined\\\");' %\\n global_name)\",\n \"def resource_exists(uri: Optional[str]) -> bool:\\n\\n if uri is None:\\n return True\\n\\n # TODO Replace after finding way to pass custom fs through FireO validator\\n if uri.startswith(\\\"gs://\\\"):\\n return True\\n\\n else:\\n # Get file system\\n fs, uri = url_to_fs(uri)\\n\\n # Check exists\\n if fs.exists(uri):\\n return True\\n\\n return False\",\n \"def test_exists_true(self):\\n self.assertTrue(Sample.exists(self.sample_id, self.sample_template))\",\n \"def exists(self) -> bool:\\n p = pathlib.Path(self.summary_path)\\n return p.exists()\",\n \"def exists(self):\\n return Criteria(op=\\\"$exists\\\", left=self, right=True)\",\n \"def exists(self) -> bool:\\n return self._file_exists()\",\n \"def exists(self):\\n\\n if self:\\n pass\",\n \"def exists(_env):\\n return True\",\n \"def exists(_env):\\n return True\",\n \"def is_defined(self, name):\\n return name in self._definitions\",\n \"def _url_exists(self, url):\\n return url_exists(url)\",\n \"def testForExistence(self):\\n self.assertTrue(cached_list_logic.isCachedListExists('cached_list'))\\n self.assertFalse(cached_list_logic.isCachedListExists('none_existent'))\",\n \"def exists(self, Search_ID):\\n if self.get_id(Search_ID) is None:\\n return False\\n else:\\n return True\",\n \"def exists(self):\\n if self._result_cache is None:\\n return self.query.has_results(using=self.db)\\n return bool(self._result_cache)\",\n \"def __contains__(self, key):\\n return self._lookup(key).value is not None\",\n \"def exists(self):\\n # TODO: What about broken sym-links?\\n return os.path.exists(self.path)\",\n \"def exists(self):\\n\\n return os.path.exists(self.path)\",\n \"def has(self) -> bool:\\n\\n return self.scopefunc() in self.registry\",\n \"def exists(obj: Dict, path: str) -> bool:\\n\\n return get(obj, path) is not None\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6585829","0.6297913","0.6297913","0.6214394","0.6142705","0.60860187","0.604842","0.59506786","0.5899629","0.58844423","0.5882149","0.58796376","0.5875572","0.58542025","0.5844161","0.5812089","0.5798914","0.5771523","0.57615334","0.57554024","0.5733867","0.5725383","0.5723663","0.57234466","0.5719646","0.57043266","0.5687087","0.5686868","0.5684246","0.5676519","0.5665183","0.5658522","0.5647626","0.563648","0.5636077","0.5632423","0.562719","0.56170976","0.5613771","0.56130326","0.56094354","0.56091774","0.5594333","0.55907065","0.55670613","0.5563753","0.5563345","0.55569565","0.5548727","0.55328006","0.5530604","0.5517299","0.5506952","0.5499174","0.5485159","0.5475219","0.54643273","0.5464279","0.54606104","0.54520935","0.5442523","0.5440782","0.5433536","0.54328704","0.5431133","0.5425629","0.542475","0.54234856","0.5418161","0.54179394","0.5416965","0.5409057","0.54085165","0.5404134","0.54034305","0.5400544","0.539307","0.53926164","0.5391424","0.538666","0.5385466","0.53827566","0.5382434","0.5377062","0.5372198","0.537061","0.53644526","0.53558975","0.53549534","0.53549534","0.5352265","0.53521454","0.5351987","0.53404933","0.53390324","0.5328203","0.53200585","0.53163105","0.5306996","0.5299718"],"string":"[\n \"0.6585829\",\n \"0.6297913\",\n \"0.6297913\",\n \"0.6214394\",\n \"0.6142705\",\n \"0.60860187\",\n \"0.604842\",\n \"0.59506786\",\n \"0.5899629\",\n \"0.58844423\",\n \"0.5882149\",\n \"0.58796376\",\n \"0.5875572\",\n \"0.58542025\",\n \"0.5844161\",\n \"0.5812089\",\n \"0.5798914\",\n \"0.5771523\",\n \"0.57615334\",\n \"0.57554024\",\n \"0.5733867\",\n \"0.5725383\",\n \"0.5723663\",\n \"0.57234466\",\n \"0.5719646\",\n \"0.57043266\",\n \"0.5687087\",\n \"0.5686868\",\n \"0.5684246\",\n \"0.5676519\",\n \"0.5665183\",\n \"0.5658522\",\n \"0.5647626\",\n \"0.563648\",\n \"0.5636077\",\n \"0.5632423\",\n \"0.562719\",\n \"0.56170976\",\n \"0.5613771\",\n \"0.56130326\",\n \"0.56094354\",\n \"0.56091774\",\n \"0.5594333\",\n \"0.55907065\",\n \"0.55670613\",\n \"0.5563753\",\n \"0.5563345\",\n \"0.55569565\",\n \"0.5548727\",\n \"0.55328006\",\n \"0.5530604\",\n \"0.5517299\",\n \"0.5506952\",\n \"0.5499174\",\n \"0.5485159\",\n \"0.5475219\",\n \"0.54643273\",\n \"0.5464279\",\n \"0.54606104\",\n \"0.54520935\",\n \"0.5442523\",\n \"0.5440782\",\n \"0.5433536\",\n \"0.54328704\",\n \"0.5431133\",\n \"0.5425629\",\n \"0.542475\",\n \"0.54234856\",\n \"0.5418161\",\n \"0.54179394\",\n \"0.5416965\",\n \"0.5409057\",\n \"0.54085165\",\n \"0.5404134\",\n \"0.54034305\",\n \"0.5400544\",\n \"0.539307\",\n \"0.53926164\",\n \"0.5391424\",\n \"0.538666\",\n \"0.5385466\",\n \"0.53827566\",\n \"0.5382434\",\n \"0.5377062\",\n \"0.5372198\",\n \"0.537061\",\n \"0.53644526\",\n \"0.53558975\",\n \"0.53549534\",\n \"0.53549534\",\n \"0.5352265\",\n \"0.53521454\",\n \"0.5351987\",\n \"0.53404933\",\n \"0.53390324\",\n \"0.5328203\",\n \"0.53200585\",\n \"0.53163105\",\n \"0.5306996\",\n \"0.5299718\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62473893"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":13075,"cells":{"query":{"kind":"string","value":"Tests if a 'java' type condition is welldefined. ie, if the class that the java var is a field of exists. my.package.MyClass myStaticField true"},"document":{"kind":"string","value":"def test_java(self, condition, undefined_paths, current_path):\n cond_id = str(condition.get('id'))\n\n try:\n cid = str(condition.find('class').text)\n except AttributeError:\n current_path += ((cond_id, 'ill-defined java condition'),)\n undefined_paths.add(current_path)\n return False\n\n if not cid:\n current_path += ((cid, 'ill-defined java condition'),)\n undefined_paths.add(current_path)\n return False\n\n classes = self.verifier.get_container('classes').get_keys()\n if not cid in classes:\n current_path += ((cid, 'java class'),)\n undefined_paths.add(current_path)\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def check_field_type(field_class):\n if field_class == 'TextField':\n field_type = 'Text field'\n elif field_class == 'NumericField':\n field_type = 'Numeric field'\n elif field_class == 'DateField':\n field_type = 'Date field'\n elif field_class == 'DateTimeField':\n field_type = 'Date & time field'\n elif field_class == 'TimeField':\n field_type = 'Time field'\n elif field_class == 'LookupField':\n field_type = 'Select box field'\n elif field_class == 'MultipleLookupField':\n field_type = 'Multiple select field'\n\n return field_type","def has_type_var(annotation) -> bool:\n return any(\n is_type_var(arg) or has_type_var(arg)\n for arg in getattr(annotation, \"__args__\", [])\n )","def _assigns_typevar(node: nodes.NodeNG | None) -> bool:\n if isinstance(node, astroid.Call):\n inferred = utils.safe_infer(node.func)\n if (\n isinstance(inferred, astroid.ClassDef)\n and inferred.qname() in TYPE_VAR_QNAME\n ):\n return True\n return False","def match_classvar(typ):\n return abstract_utils.match_type_container(typ, \"typing.ClassVar\")","def _is_typevar(typeval: Type) -> bool:\n return isinstance(typeval, TypeVar) # type: ignore","def _check_typevar(self) -> PossibleResult[T]:\n if _is_typevar(self.constructor): # type: ignore\n return Deserialize(\n obj=self.obj,\n constructor=(\n Union[self.constructor.__constraints__] # type: ignore\n if self.constructor.__constraints__ # type: ignore\n else object\n ),\n depth=self.new_depth,\n convert_primitives=self.convert_primitives,\n ).run()\n return NO_RESULT","def is_type(verifield, required):\n return verifield is None or isinstance(verifield, required)","def is_my_case(self, type_):\n return (\n isinstance(self.__apply_sequence(type_), self.declaration_class)\n )","def _check(self, class_):\r\n\r\n if isinstance(class_, (types.FunctionType, types.LambdaType,\r\n types.ClassType, types.InstanceType)):\r\n return False\r\n if not hasattr(class_, '__dict__'):\r\n if not hasattr(class_, '__slots__'):\r\n return False\r\n return True","def is_type_var(annotation) -> bool:\n\n return isinstance(annotation, typing.TypeVar) # type:ignore","def is_field(item):\n return isinstance(item, Field)","def meets_condition(db_type: str):\n\t\t...","def filter_func(fieldname):\n if fieldname.startswith('_'):\n return False\n value = getattr(class_, fieldname)\n \n return isinstance(value, type)","def check_type(self):\n return True","def _is_user_class(obj):\n type_dict = type(obj).__dict__\n is_user_class = '_pandas_type' in type_dict\n return is_user_class","def is_field(field, type_name):\n\n # Backward compatibility from when Component was Field\n if type_name == 'TRAIT' or isinstance(field, schema.Component):\n return type_name == 'TRAIT' and isinstance(field, schema.Component)\n\n return field.data_type == getattr(schema.Field.DataType, type_name)","def local_type(verifield, type_name):\n from polyglot.pyapi.meta import retrieve_schema_table_fields\n from polyglot.pyapi.instance import create_instance_validators\n from polyglot.models.schema import Instance\n (tenant_id, schema_id, table_id) = type_name.split(\"::\")\n fields = retrieve_schema_table_fields(tenant_id, schema_id, table_id)\n validators = Instance._validations\n validators['instance_data'] = create_instance_validators(fields)\n instance = Instance(**instance)\n instance.validate(validators)\n instance._validations = validators\n return not((hasattr(instance, 'validation_errors') \n and instance.validation_errors) \\\n or instance.instance_data.get('validation_errors', {}))","def _is_initvar_instance(typeval: Type) -> bool:\n return isinstance(typeval, InitVar)","def check_input_type(var, type_name):\n\n type_options = [\"int\", \"float\", \"Date\", \"Region\"]\n if type_name == type_options[0]:\n if int(var):\n return True\n else:\n return False\n elif type_name == type_options[1]:\n if float(var):\n return True\n else:\n return False\n elif type_name == type_options[2]:\n if datetime.date.fromisoformat(var):\n return True\n else:\n return False\n elif type_name == type_options[3]:\n valid_regions = [\"NW\", \"SW\", \"MN\", \"MS\", \"NE\", \"SE\"]\n is_valid = False\n for region in valid_regions:\n if var == region:\n is_valid = True\n return is_valid\n else:\n Exception(\"This type doesn't exist in the checker!\")","def is_scala(self):\r\n return self.has_label('scala')","def isvar(var):\n return _coconut_tail_call(isinstance, var, (Const, Var))","def has_fields(class_or_instance):\n return hasattr(class_or_instance, _FIELDS)","def _check_field_annotations(cls: Type):\n cls_annotations = cls.__dict__.get(\"__annotations__\", {})\n cls.__annotations__ = cls_annotations\n\n for field_name, field in cls.__dict__.items():\n if not isinstance(field, (StrawberryField, dataclasses.Field)):\n # Not a dataclasses.Field, nor a StrawberryField. Ignore\n continue\n\n # If the field is a StrawberryField we need to do a bit of extra work\n # to make sure dataclasses.dataclass is ready for it\n if isinstance(field, StrawberryField):\n\n # Make sure the cls has an annotation\n if field_name not in cls_annotations:\n # If the field uses the default resolver, the field _must_ be\n # annotated\n if not field.base_resolver:\n raise MissingFieldAnnotationError(field_name)\n\n # The resolver _must_ have a return type annotation\n # TODO: Maybe check this immediately when adding resolver to\n # field\n if field.base_resolver.type is None:\n raise MissingReturnAnnotationError(field_name)\n\n cls_annotations[field_name] = field.base_resolver.type\n\n # TODO: Make sure the cls annotation agrees with the field's type\n # >>> if cls_annotations[field_name] != field.base_resolver.type:\n # >>> # TODO: Proper error\n # >>> raise Exception\n\n # If somehow a non-StrawberryField field is added to the cls without annotations\n # it raises an exception. This would occur if someone manually uses\n # dataclasses.field\n if field_name not in cls_annotations:\n # Field object exists but did not get an annotation\n raise MissingFieldAnnotationError(field_name)","def isclass(object):\r\n return isinstance(object, (type, types.ClassType))","def _is_primitive_type(io: type) -> bool:\n return any(io.__module__.startswith(mldesigner_pkg) and item.__name__ == param_name for item in getmro(io))","def _isinstance(cls, x):\n return isinstance(x, cls.PYTHON_TYPE_CHECK)","def _isinstancetype(an_obj):\n if an_obj is None: return False\n if not PY3K:\n return isinstance(an_obj, types.InstanceType)\n typstr = str(type(an_obj))\n # the following logic works, as PyRAF users expect, in both v2 and v3\n return typstr==\"<type 'instance'>\" or \\\n (typstr.startswith(\"<class '\") and ('.' in typstr))","def is_java(self):\r\n return self.has_label('java')","def test_types(question):\n instance = question[\"instance\"]\n for name, data in instance.get(\"variables\", {}).items():\n assert \"optional\" not in data or isinstance(data[\"optional\"], bool)\n if data.get(\"type\") == \"boolean\":\n assert \"value\" not in data or isinstance(data[\"value\"], bool)\n elif data.get(\"type\") in [\"integer\", \"long\"]:\n assert \"value\" not in data or isinstance(data[\"value\"], int)","def class_is(cls: Class) -> bool:\n pass","def test_class_attribute() -> None:\n assert get_type_hints(lmp.tknzr._bpe.BPETknzr) == {'tknzr_name': ClassVar[str]}\n assert lmp.tknzr._bpe.BPETknzr.tknzr_name == 'BPE'","def _is_type_in_scope(self, name):","def ensure_type(var, *expected_types, _up_extra_frames=0):\n for t in expected_types:\n if isinstance(var, t):\n return True\n type_err = f'Type-checking caller: {get_caller_function(_up_extra_frames=_up_extra_frames)}(): For object (value = {var}), ' \\\n f'expected type(s) was {expected_types} but instead found {type(var)}'\n logger.error(type_err)\n raise TypeError(type_err)","def is_boost_class(obj: Any) -> bool:\n return \"Boost.Python.class\" in str(type(obj))","def exists(field):\n try:\n float(field)\n return True\n except:\n return False","def _is_dataclass_instance(obj):\n return hasattr(type(obj), '__dataclass_fields__')","def is_type(self, typ):\n return typ == self.__class__.__name__","def is_unknown(t):\n if isinstance(t, (pytd.ClassType, pytd.NamedType, pytd.Class, StrictType)):\n return escape.is_unknown(t.name)\n elif isinstance(t, str):\n return escape.is_unknown(t)\n else:\n return False","def typematch(variable, expectedtype):\n\n # Return the result\n return isinstance(variable, expectedtype)","def CheckType(self, *args, **kwargs):\n pass","def isclass(object):\n if not inspect.isclass(object):\n return False\n if isbuiltin(object):\n return False\n return type not in inspect.getmro(object)","def _valid_typable_object(ui_object, platform=Platform.ANDROID):\n if platform == Platform.ANDROID:\n return ui_object.obj_type in _TYPABLE_OBJECT_DESC.keys()\n else:\n assert False, 'Wrong Platform'","def checkType(self, value):\n pass","def isclassinstance(object):\n if not hasattr(object, \"__class__\"):\n return False\n if isbuiltin(object.__class__):\n return False\n return True","def is_private_field(self, node, f):\n\n if f.private:\n return True\n if f.anonymous_node:\n return True\n if f.name == 'g_type_instance':\n return True # this field on GObject is not exposed\n\n field_typenode = self._transformer.lookup_typenode(f.type)\n if not field_typenode:\n return False\n\n if getattr(field_typenode, 'disguised', False):\n return True # guess that it's a pointer to a private struct\n # this also catches fields of type GdkAtom, since that is disguised\n # as well. Not sure whether that's correct or not.\n\n if not isinstance(node, ast.Class):\n return False # parent instance heuristics only apply to classes\n\n if node.parent_type:\n parent_typenode = self._transformer.lookup_typenode(node.parent_type)\n if field_typenode == parent_typenode:\n return True # guess that it's a parent instance field\n\n return False","def _value_is_dynamic(self,obj,objtype=None):\n return hasattr(super(Dynamic,self).__get__(obj,objtype),'_Dynamic_last')","def is_builtin_dataclass(_cls: Type[Any]) -> bool:\n import dataclasses\n\n return not hasattr(_cls, '__processed__') and dataclasses.is_dataclass(_cls)","def _valid_typable_object_with_name(ui_object, platform=Platform.ANDROID):\n if platform == Platform.ANDROID:\n return (ui_object.obj_type in _TYPABLE_OBJECT_DESC.keys() and\n _valid_object_with_name(ui_object))\n else:\n assert False, 'Wrong Platform'","def validatePredefinedType(self, type: int) -> bool:\n ...","def is_type(obj):\n return type(obj) is type or type(obj) is types.ClassType","def get_check_types():","def HasField(self,\n fully_qualified_fieldname: str,\n run_unsafe: bool = False) -> bool:\n return self.GetField(fully_qualified_fieldname, run_unsafe) is not None","def _should_use_varname_value(self, value):\n if isinstance(value, KnownValue):\n return type(value.val) in six.integer_types\n elif (\n type(value) is TypedValue\n ): # Only replace exactly TypedValue(int), not subtypes\n return value.typ in six.integer_types\n else:\n return value is UNRESOLVED_VALUE","def variable_type(self, variable): # pragma: no cover\n raise NotImplementedError('Implemented in child class')","def _isintvar(self, index):\n return 251 <= self._typlist[index] <= 253","def construction_for_another_type(cname, graphtype):\n for t in constructions:\n if t == graphtype:\n continue\n if cname in constructions[t]:\n return True\n return False","def has_value(var) :\n return var != None","def has_apt(klass):\n return False","def isdatatype(object):\n return isinstance(object, (str, int, bool, float, type(None)))","def is_field(self, proof = True):\n return True","def is_type(obj: Any) -> bool:\n return type(obj).__name__ == \"type\"","def is_null(var):\r\n if var is None or not var: return True\r\n if any(isinstance(var, s) for s in [str, list, tuple, set]) and len(var) == 0: return True\r\n if isinstance(var, str) and var == '': return True\r\n if any( isinstance(var, s) for s in [int, float, complex, bool] ) and int(var) == 0: return True\r\n return False","def is_jvm(self):\r\n return self.has_label('jvm')","def IsLocalField(self, field_name):\n if not self._field_universe:\n return False\n return self._field_universe.IsFieldDefined(field_name, self.namespace)","def validate_is_instance(var: Any,\n var_name: str,\n instance_type: Any,\n class_name: Optional[str] = None,\n log_metadata_validation_failures: bool = True) -> None:\n if var is None:\n return\n splits = str(instance_type).split(\"<class \")[-1].split(\"'\")\n if len(splits) > 1:\n print_type = splits[1]\n else:\n print_type = splits[0]\n if log_metadata_validation_failures:\n if class_name is None:\n logging.debug(\n \"XAI Validation :: Metadata: Variable `%s` should be of type `%s`\",\n var_name, print_type)\n else:\n logging.debug(\n \"XAI Validation :: Metadata: [%s] Variable `%s` should be of type \"\n \"`%s`\", class_name, var_name, print_type)\n if not isinstance(var, instance_type):\n raise TypeError(\"{} must be of type {}. Got {}\".format(\n var_name, str(instance_type), str(type(var))))","def get_type_check(self, arg, option):\n pass","def is_type(self, type_name):\n\n return type_name in self._symtab","def _check_typevar(self, name: str, node: nodes.AssignName) -> None:\n if isinstance(node.parent, nodes.Assign):\n keywords = node.assign_type().value.keywords\n args = node.assign_type().value.args\n elif isinstance(node.parent, nodes.Tuple):\n keywords = (\n node.assign_type().value.elts[node.parent.elts.index(node)].keywords\n )\n args = node.assign_type().value.elts[node.parent.elts.index(node)].args\n\n variance = TypeVarVariance.invariant\n name_arg = None\n for kw in keywords:\n if variance == TypeVarVariance.double_variant:\n pass\n elif kw.arg == \"covariant\" and kw.value.value:\n variance = (\n TypeVarVariance.covariant\n if variance != TypeVarVariance.contravariant\n else TypeVarVariance.double_variant\n )\n elif kw.arg == \"contravariant\" and kw.value.value:\n variance = (\n TypeVarVariance.contravariant\n if variance != TypeVarVariance.covariant\n else TypeVarVariance.double_variant\n )\n\n if kw.arg == \"name\" and isinstance(kw.value, nodes.Const):\n name_arg = kw.value.value\n\n if name_arg is None and args and isinstance(args[0], nodes.Const):\n name_arg = args[0].value\n\n if variance == TypeVarVariance.double_variant:\n self.add_message(\n \"typevar-double-variance\",\n node=node,\n confidence=interfaces.INFERENCE,\n )\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(\"\",),\n confidence=interfaces.INFERENCE,\n )\n elif variance == TypeVarVariance.covariant and not name.endswith(\"_co\"):\n suggest_name = f\"{re.sub('_contra$', '', name)}_co\"\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(f'. \"{name}\" is covariant, use \"{suggest_name}\" instead'),\n confidence=interfaces.INFERENCE,\n )\n elif variance == TypeVarVariance.contravariant and not name.endswith(\"_contra\"):\n suggest_name = f\"{re.sub('_co$', '', name)}_contra\"\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(f'. \"{name}\" is contravariant, use \"{suggest_name}\" instead'),\n confidence=interfaces.INFERENCE,\n )\n elif variance == TypeVarVariance.invariant and (\n name.endswith(\"_co\") or name.endswith(\"_contra\")\n ):\n suggest_name = re.sub(\"_contra$|_co$\", \"\", name)\n self.add_message(\n \"typevar-name-incorrect-variance\",\n node=node,\n args=(f'. \"{name}\" is invariant, use \"{suggest_name}\" instead'),\n confidence=interfaces.INFERENCE,\n )\n\n if name_arg is not None and name_arg != name:\n self.add_message(\n \"typevar-name-mismatch\",\n node=node,\n args=(name_arg, name),\n confidence=interfaces.INFERENCE,\n )","def scalar_object_check(py_object, c_object):\n\n try :\n check_type = check_type_registry[c_object.dtype, c_object.precision]\n except KeyError:\n errors.report(PYCCEL_RESTRICTION_TODO, symbol=c_object.dtype,severity='fatal')\n\n check_func = FunctionDef(name = check_type,\n body = [],\n arguments = [Variable(dtype=PyccelPyObject(), name = 'o', is_pointer=True)],\n results = [Variable(dtype=NativeBool(), name = 'r')])\n\n return FunctionCall(check_func, [py_object])","def has_classname(self):\n return self.unpack_word(0x4A) > 0","def validVarConstructType(self,vartype):\r\n indArray = vartype.find('[]')\r\n if indArray>0:\r\n thisType = vartype[0:indArray]\r\n isArray = True\r\n else:\r\n thisType = vartype\r\n isArray = False\r\n \r\n if thisType in ('rng','range'):\r\n type = 'range'\r\n elif thisType in ('rate'):\r\n type = 'rate'\r\n elif thisType in ('amt','amount'):\r\n type = 'amount'\r\n elif thisType in ('minamt','minamount'):\r\n type = 'minamount'\r\n elif thisType in ('bool'):\r\n type = 'bool'\r\n else:\r\n print 'variable type must be range, rate, amount, minamount, bool (or abbreviated forms)'\r\n return False, ''\r\n \r\n return True, type, isArray","def _isintvar(self, index):\n return 65528 <= self._typlist[index] <= 65530","def has_vector_type(obj: _std_typing.Any) -> bool:\n return obj.dtype == sc.DType.vector3","def is_of_type(cls, value) -> bool:\n # UTF8 = 'utf-8'\n # UTF16 = 'utf-16'\n # UTF32 = 'utf-32'\n # ASCII = 'ascii'\n # BINARY = 'binary'\n # OCTAL = 'octal'\n # HEXADECIMAL = 'hexadecimal'\n # CP1252 = 'cp1252'\n # WINDOWS1252 = 'windows-1252'\n # UNICODEESCAPE = 'unicode-escape'\n\n v = None\n if cls == cls.UTF8 or cls == cls.UTF16 or cls == cls.UTF32 or cls == cls.UNICODEESCAPE:\n try:\n v = bytes(value)\n except:\n return False\n\n if cls == cls.ASCII:\n try:\n v = ascii(value)\n except:\n return False\n\n if cls == cls.BINARY:\n try:\n v = bin(value)\n except:\n return False\n\n if cls == cls.OCTAL:\n try:\n v = oct(value)\n except:\n return False\n\n if cls == cls.HEXADECIMAL:\n try:\n v = hex(value)\n except:\n return False\n\n if cls == cls.WINDOWS1252 or cls == cls.CP1252:\n try:\n v = str(value)\n except:\n return False\n return True","def is_kind_of_class(obj, a_class):\n if isinstance(obj, a_class) is True:\n return True\n else:\n return False","def predicate(cls: nodes.ClassDef) -> bool:\n if cls.name in CLASS_NAME_SKIPLIST:\n # class looks like an API model class, but it isn't.\n return False\n\n if not cls.name.endswith(\"API\") and \"schema\" not in cls.locals:\n # class does not look like an API model class.\n return False\n\n return True","def test_has_exactly_type():\r\n\r\n return has_exactly_type(1, int) and not has_exactly_type(True, int) and has_exactly_type(True, bool)","def accepts_type(self, *args):\n return _ida_hexrays.lvar_t_accepts_type(self, *args)","def is_python(self):\r\n return self.has_label('python')","def isConditional(self) -> bool:\n ...","def getvartype(self,j_): # 3\n res,resargs = self.__obj.getvartype(j_)\n if res != 0:\n result,msg = self.__getlasterror(res)\n raise Error(rescode(res),msg)\n _vartype_return_value = resargs\n _vartype_return_value = variabletype(_vartype_return_value)\n return _vartype_return_value","def _is_simple_type(cls):\n return all([\n AnnotationWrapper(anno).is_simple_in_opt_and_not_opt\n for anno in cls._used_annotations()\n ])","def _is_run_type(cls, object_):\n # Do a string comparison instead of using isinstance() to avoid needing\n # to import lyse or other modules with these classes.\n return (type(object_).__name__ in cls._RUN_TYPES)","def has_field_type(self, field_type):\n if not hasattr(self, '_field_types'):\n self._field_types = {}\n if not self._field_types.has_key(field_type):\n try:\n # First check self.fields.\n for f in self.fields:\n if isinstance(f, field_type):\n raise StopIteration\n # Failing that, check related fields.\n for rel_obj, rel_field in self.get_inline_related_objects():\n for f in rel_obj.fields:\n if isinstance(f, field_type):\n raise StopIteration\n except StopIteration:\n self._field_types[field_type] = True\n else:\n self._field_types[field_type] = False\n return self._field_types[field_type]","def is_kind_of_class(obj, a_class):\n return(isinstance(obj, a_class))","def predicate(obj):\n return inspect.isclass(obj) and issubclass(obj, MafColumnRecord)","def test(types, _):\n return 'Date' in types and 'Postal Code' in types","def check_global_attr_type(ds, attr, attr_type):\n if attr not in ds.ncattrs():\n return 0\n\n global_attr = getattr(ds, attr)\n\n if attr_type == 'int':\n attr_type_class = int\n elif attr_type == 'float':\n attr_type_class = float\n elif attr_type == 'str':\n attr_type_class = str\n else:\n return 1\n\n if len(str(global_attr)) == 0:\n return 2\n\n if np.dtype(type(global_attr)) != np.dtype(attr_type_class):\n return 3\n\n return 4","def __check(self, v):\n v = base_type(v)\n if not self._restriction_test(v):\n raise ValueError, \"did not match restricted type\"\n return True","def type_match(cls, line):\n match = Ftype_type_decl.__type_decl_re__.match(line.strip())\n # End if\n return match","def __instancecheck__(self, instance):\n\n if isinstance(instance, ObjCInstance):\n return bool(instance.isKindOfClass(self))\n else:\n return False","def _ValidateField(self, field_tuple, entity):\n if not self._field_universe.IsFieldDefined(field_tuple.field,\n field_tuple.namespace):\n self.AddFinding(\n findings_lib.UndefinedFieldError(entity, field_tuple.field))\n return False\n return True","def is_kind_of_class(obj, a_class):\n if isinstance(obj, a_class):\n return True\n else:\n return False","def is_kind_of_class(obj, a_class):\n if isinstance(obj, a_class):\n return True\n else:\n return False","def is_valid_field(self, field: DSLSelectable) -> bool:\n\n assert isinstance(self, DSLField)\n\n if isinstance(field, (DSLFragment, DSLInlineFragment)):\n return True\n\n assert isinstance(field, DSLField)\n\n if isinstance(field, DSLMetaField):\n return field.name == \"__typename\"\n\n parent_type = get_named_type(self.field.type)\n\n if not isinstance(parent_type, (GraphQLInterfaceType, GraphQLObjectType)):\n return False\n\n if field.name in parent_type.fields.keys():\n return parent_type.fields[field.name].type == field.field.type\n\n return False","def is_kind_of_class(obj, a_class):\n return (isinstance(obj, a_class))","def _is_typing_object(type_object):\n return type_object.__module__ == \"typing\"","def has_required(self, obj: T) -> bool:\n if (ufp_required_field := self.ufp_required_field) is None:\n return True\n if TYPE_CHECKING:\n # `ufp_required_field` is defined as a `str` in the dataclass, but\n # `__post_init__` converts it to a `tuple[str, ...]` to avoid\n # doing it at run time in `get_nested_attr` which is usually called\n # millions of times per day. This tells mypy that it's a tuple.\n assert isinstance(ufp_required_field, tuple)\n return bool(get_nested_attr(obj, ufp_required_field))","def is_kind_of_class(obj, a_class):\n if isinstance(obj, a_class):\n return True\n return False","def verify_type(self, obj):\n return isinstance(obj, self.type_)"],"string":"[\n \"def check_field_type(field_class):\\n if field_class == 'TextField':\\n field_type = 'Text field'\\n elif field_class == 'NumericField':\\n field_type = 'Numeric field'\\n elif field_class == 'DateField':\\n field_type = 'Date field'\\n elif field_class == 'DateTimeField':\\n field_type = 'Date & time field'\\n elif field_class == 'TimeField':\\n field_type = 'Time field'\\n elif field_class == 'LookupField':\\n field_type = 'Select box field'\\n elif field_class == 'MultipleLookupField':\\n field_type = 'Multiple select field'\\n\\n return field_type\",\n \"def has_type_var(annotation) -> bool:\\n return any(\\n is_type_var(arg) or has_type_var(arg)\\n for arg in getattr(annotation, \\\"__args__\\\", [])\\n )\",\n \"def _assigns_typevar(node: nodes.NodeNG | None) -> bool:\\n if isinstance(node, astroid.Call):\\n inferred = utils.safe_infer(node.func)\\n if (\\n isinstance(inferred, astroid.ClassDef)\\n and inferred.qname() in TYPE_VAR_QNAME\\n ):\\n return True\\n return False\",\n \"def match_classvar(typ):\\n return abstract_utils.match_type_container(typ, \\\"typing.ClassVar\\\")\",\n \"def _is_typevar(typeval: Type) -> bool:\\n return isinstance(typeval, TypeVar) # type: ignore\",\n \"def _check_typevar(self) -> PossibleResult[T]:\\n if _is_typevar(self.constructor): # type: ignore\\n return Deserialize(\\n obj=self.obj,\\n constructor=(\\n Union[self.constructor.__constraints__] # type: ignore\\n if self.constructor.__constraints__ # type: ignore\\n else object\\n ),\\n depth=self.new_depth,\\n convert_primitives=self.convert_primitives,\\n ).run()\\n return NO_RESULT\",\n \"def is_type(verifield, required):\\n return verifield is None or isinstance(verifield, required)\",\n \"def is_my_case(self, type_):\\n return (\\n isinstance(self.__apply_sequence(type_), self.declaration_class)\\n )\",\n \"def _check(self, class_):\\r\\n\\r\\n if isinstance(class_, (types.FunctionType, types.LambdaType,\\r\\n types.ClassType, types.InstanceType)):\\r\\n return False\\r\\n if not hasattr(class_, '__dict__'):\\r\\n if not hasattr(class_, '__slots__'):\\r\\n return False\\r\\n return True\",\n \"def is_type_var(annotation) -> bool:\\n\\n return isinstance(annotation, typing.TypeVar) # type:ignore\",\n \"def is_field(item):\\n return isinstance(item, Field)\",\n \"def meets_condition(db_type: str):\\n\\t\\t...\",\n \"def filter_func(fieldname):\\n if fieldname.startswith('_'):\\n return False\\n value = getattr(class_, fieldname)\\n \\n return isinstance(value, type)\",\n \"def check_type(self):\\n return True\",\n \"def _is_user_class(obj):\\n type_dict = type(obj).__dict__\\n is_user_class = '_pandas_type' in type_dict\\n return is_user_class\",\n \"def is_field(field, type_name):\\n\\n # Backward compatibility from when Component was Field\\n if type_name == 'TRAIT' or isinstance(field, schema.Component):\\n return type_name == 'TRAIT' and isinstance(field, schema.Component)\\n\\n return field.data_type == getattr(schema.Field.DataType, type_name)\",\n \"def local_type(verifield, type_name):\\n from polyglot.pyapi.meta import retrieve_schema_table_fields\\n from polyglot.pyapi.instance import create_instance_validators\\n from polyglot.models.schema import Instance\\n (tenant_id, schema_id, table_id) = type_name.split(\\\"::\\\")\\n fields = retrieve_schema_table_fields(tenant_id, schema_id, table_id)\\n validators = Instance._validations\\n validators['instance_data'] = create_instance_validators(fields)\\n instance = Instance(**instance)\\n instance.validate(validators)\\n instance._validations = validators\\n return not((hasattr(instance, 'validation_errors') \\n and instance.validation_errors) \\\\\\n or instance.instance_data.get('validation_errors', {}))\",\n \"def _is_initvar_instance(typeval: Type) -> bool:\\n return isinstance(typeval, InitVar)\",\n \"def check_input_type(var, type_name):\\n\\n type_options = [\\\"int\\\", \\\"float\\\", \\\"Date\\\", \\\"Region\\\"]\\n if type_name == type_options[0]:\\n if int(var):\\n return True\\n else:\\n return False\\n elif type_name == type_options[1]:\\n if float(var):\\n return True\\n else:\\n return False\\n elif type_name == type_options[2]:\\n if datetime.date.fromisoformat(var):\\n return True\\n else:\\n return False\\n elif type_name == type_options[3]:\\n valid_regions = [\\\"NW\\\", \\\"SW\\\", \\\"MN\\\", \\\"MS\\\", \\\"NE\\\", \\\"SE\\\"]\\n is_valid = False\\n for region in valid_regions:\\n if var == region:\\n is_valid = True\\n return is_valid\\n else:\\n Exception(\\\"This type doesn't exist in the checker!\\\")\",\n \"def is_scala(self):\\r\\n return self.has_label('scala')\",\n \"def isvar(var):\\n return _coconut_tail_call(isinstance, var, (Const, Var))\",\n \"def has_fields(class_or_instance):\\n return hasattr(class_or_instance, _FIELDS)\",\n \"def _check_field_annotations(cls: Type):\\n cls_annotations = cls.__dict__.get(\\\"__annotations__\\\", {})\\n cls.__annotations__ = cls_annotations\\n\\n for field_name, field in cls.__dict__.items():\\n if not isinstance(field, (StrawberryField, dataclasses.Field)):\\n # Not a dataclasses.Field, nor a StrawberryField. Ignore\\n continue\\n\\n # If the field is a StrawberryField we need to do a bit of extra work\\n # to make sure dataclasses.dataclass is ready for it\\n if isinstance(field, StrawberryField):\\n\\n # Make sure the cls has an annotation\\n if field_name not in cls_annotations:\\n # If the field uses the default resolver, the field _must_ be\\n # annotated\\n if not field.base_resolver:\\n raise MissingFieldAnnotationError(field_name)\\n\\n # The resolver _must_ have a return type annotation\\n # TODO: Maybe check this immediately when adding resolver to\\n # field\\n if field.base_resolver.type is None:\\n raise MissingReturnAnnotationError(field_name)\\n\\n cls_annotations[field_name] = field.base_resolver.type\\n\\n # TODO: Make sure the cls annotation agrees with the field's type\\n # >>> if cls_annotations[field_name] != field.base_resolver.type:\\n # >>> # TODO: Proper error\\n # >>> raise Exception\\n\\n # If somehow a non-StrawberryField field is added to the cls without annotations\\n # it raises an exception. This would occur if someone manually uses\\n # dataclasses.field\\n if field_name not in cls_annotations:\\n # Field object exists but did not get an annotation\\n raise MissingFieldAnnotationError(field_name)\",\n \"def isclass(object):\\r\\n return isinstance(object, (type, types.ClassType))\",\n \"def _is_primitive_type(io: type) -> bool:\\n return any(io.__module__.startswith(mldesigner_pkg) and item.__name__ == param_name for item in getmro(io))\",\n \"def _isinstance(cls, x):\\n return isinstance(x, cls.PYTHON_TYPE_CHECK)\",\n \"def _isinstancetype(an_obj):\\n if an_obj is None: return False\\n if not PY3K:\\n return isinstance(an_obj, types.InstanceType)\\n typstr = str(type(an_obj))\\n # the following logic works, as PyRAF users expect, in both v2 and v3\\n return typstr==\\\"<type 'instance'>\\\" or \\\\\\n (typstr.startswith(\\\"<class '\\\") and ('.' in typstr))\",\n \"def is_java(self):\\r\\n return self.has_label('java')\",\n \"def test_types(question):\\n instance = question[\\\"instance\\\"]\\n for name, data in instance.get(\\\"variables\\\", {}).items():\\n assert \\\"optional\\\" not in data or isinstance(data[\\\"optional\\\"], bool)\\n if data.get(\\\"type\\\") == \\\"boolean\\\":\\n assert \\\"value\\\" not in data or isinstance(data[\\\"value\\\"], bool)\\n elif data.get(\\\"type\\\") in [\\\"integer\\\", \\\"long\\\"]:\\n assert \\\"value\\\" not in data or isinstance(data[\\\"value\\\"], int)\",\n \"def class_is(cls: Class) -> bool:\\n pass\",\n \"def test_class_attribute() -> None:\\n assert get_type_hints(lmp.tknzr._bpe.BPETknzr) == {'tknzr_name': ClassVar[str]}\\n assert lmp.tknzr._bpe.BPETknzr.tknzr_name == 'BPE'\",\n \"def _is_type_in_scope(self, name):\",\n \"def ensure_type(var, *expected_types, _up_extra_frames=0):\\n for t in expected_types:\\n if isinstance(var, t):\\n return True\\n type_err = f'Type-checking caller: {get_caller_function(_up_extra_frames=_up_extra_frames)}(): For object (value = {var}), ' \\\\\\n f'expected type(s) was {expected_types} but instead found {type(var)}'\\n logger.error(type_err)\\n raise TypeError(type_err)\",\n \"def is_boost_class(obj: Any) -> bool:\\n return \\\"Boost.Python.class\\\" in str(type(obj))\",\n \"def exists(field):\\n try:\\n float(field)\\n return True\\n except:\\n return False\",\n \"def _is_dataclass_instance(obj):\\n return hasattr(type(obj), '__dataclass_fields__')\",\n \"def is_type(self, typ):\\n return typ == self.__class__.__name__\",\n \"def is_unknown(t):\\n if isinstance(t, (pytd.ClassType, pytd.NamedType, pytd.Class, StrictType)):\\n return escape.is_unknown(t.name)\\n elif isinstance(t, str):\\n return escape.is_unknown(t)\\n else:\\n return False\",\n \"def typematch(variable, expectedtype):\\n\\n # Return the result\\n return isinstance(variable, expectedtype)\",\n \"def CheckType(self, *args, **kwargs):\\n pass\",\n \"def isclass(object):\\n if not inspect.isclass(object):\\n return False\\n if isbuiltin(object):\\n return False\\n return type not in inspect.getmro(object)\",\n \"def _valid_typable_object(ui_object, platform=Platform.ANDROID):\\n if platform == Platform.ANDROID:\\n return ui_object.obj_type in _TYPABLE_OBJECT_DESC.keys()\\n else:\\n assert False, 'Wrong Platform'\",\n \"def checkType(self, value):\\n pass\",\n \"def isclassinstance(object):\\n if not hasattr(object, \\\"__class__\\\"):\\n return False\\n if isbuiltin(object.__class__):\\n return False\\n return True\",\n \"def is_private_field(self, node, f):\\n\\n if f.private:\\n return True\\n if f.anonymous_node:\\n return True\\n if f.name == 'g_type_instance':\\n return True # this field on GObject is not exposed\\n\\n field_typenode = self._transformer.lookup_typenode(f.type)\\n if not field_typenode:\\n return False\\n\\n if getattr(field_typenode, 'disguised', False):\\n return True # guess that it's a pointer to a private struct\\n # this also catches fields of type GdkAtom, since that is disguised\\n # as well. Not sure whether that's correct or not.\\n\\n if not isinstance(node, ast.Class):\\n return False # parent instance heuristics only apply to classes\\n\\n if node.parent_type:\\n parent_typenode = self._transformer.lookup_typenode(node.parent_type)\\n if field_typenode == parent_typenode:\\n return True # guess that it's a parent instance field\\n\\n return False\",\n \"def _value_is_dynamic(self,obj,objtype=None):\\n return hasattr(super(Dynamic,self).__get__(obj,objtype),'_Dynamic_last')\",\n \"def is_builtin_dataclass(_cls: Type[Any]) -> bool:\\n import dataclasses\\n\\n return not hasattr(_cls, '__processed__') and dataclasses.is_dataclass(_cls)\",\n \"def _valid_typable_object_with_name(ui_object, platform=Platform.ANDROID):\\n if platform == Platform.ANDROID:\\n return (ui_object.obj_type in _TYPABLE_OBJECT_DESC.keys() and\\n _valid_object_with_name(ui_object))\\n else:\\n assert False, 'Wrong Platform'\",\n \"def validatePredefinedType(self, type: int) -> bool:\\n ...\",\n \"def is_type(obj):\\n return type(obj) is type or type(obj) is types.ClassType\",\n \"def get_check_types():\",\n \"def HasField(self,\\n fully_qualified_fieldname: str,\\n run_unsafe: bool = False) -> bool:\\n return self.GetField(fully_qualified_fieldname, run_unsafe) is not None\",\n \"def _should_use_varname_value(self, value):\\n if isinstance(value, KnownValue):\\n return type(value.val) in six.integer_types\\n elif (\\n type(value) is TypedValue\\n ): # Only replace exactly TypedValue(int), not subtypes\\n return value.typ in six.integer_types\\n else:\\n return value is UNRESOLVED_VALUE\",\n \"def variable_type(self, variable): # pragma: no cover\\n raise NotImplementedError('Implemented in child class')\",\n \"def _isintvar(self, index):\\n return 251 <= self._typlist[index] <= 253\",\n \"def construction_for_another_type(cname, graphtype):\\n for t in constructions:\\n if t == graphtype:\\n continue\\n if cname in constructions[t]:\\n return True\\n return False\",\n \"def has_value(var) :\\n return var != None\",\n \"def has_apt(klass):\\n return False\",\n \"def isdatatype(object):\\n return isinstance(object, (str, int, bool, float, type(None)))\",\n \"def is_field(self, proof = True):\\n return True\",\n \"def is_type(obj: Any) -> bool:\\n return type(obj).__name__ == \\\"type\\\"\",\n \"def is_null(var):\\r\\n if var is None or not var: return True\\r\\n if any(isinstance(var, s) for s in [str, list, tuple, set]) and len(var) == 0: return True\\r\\n if isinstance(var, str) and var == '': return True\\r\\n if any( isinstance(var, s) for s in [int, float, complex, bool] ) and int(var) == 0: return True\\r\\n return False\",\n \"def is_jvm(self):\\r\\n return self.has_label('jvm')\",\n \"def IsLocalField(self, field_name):\\n if not self._field_universe:\\n return False\\n return self._field_universe.IsFieldDefined(field_name, self.namespace)\",\n \"def validate_is_instance(var: Any,\\n var_name: str,\\n instance_type: Any,\\n class_name: Optional[str] = None,\\n log_metadata_validation_failures: bool = True) -> None:\\n if var is None:\\n return\\n splits = str(instance_type).split(\\\"<class \\\")[-1].split(\\\"'\\\")\\n if len(splits) > 1:\\n print_type = splits[1]\\n else:\\n print_type = splits[0]\\n if log_metadata_validation_failures:\\n if class_name is None:\\n logging.debug(\\n \\\"XAI Validation :: Metadata: Variable `%s` should be of type `%s`\\\",\\n var_name, print_type)\\n else:\\n logging.debug(\\n \\\"XAI Validation :: Metadata: [%s] Variable `%s` should be of type \\\"\\n \\\"`%s`\\\", class_name, var_name, print_type)\\n if not isinstance(var, instance_type):\\n raise TypeError(\\\"{} must be of type {}. Got {}\\\".format(\\n var_name, str(instance_type), str(type(var))))\",\n \"def get_type_check(self, arg, option):\\n pass\",\n \"def is_type(self, type_name):\\n\\n return type_name in self._symtab\",\n \"def _check_typevar(self, name: str, node: nodes.AssignName) -> None:\\n if isinstance(node.parent, nodes.Assign):\\n keywords = node.assign_type().value.keywords\\n args = node.assign_type().value.args\\n elif isinstance(node.parent, nodes.Tuple):\\n keywords = (\\n node.assign_type().value.elts[node.parent.elts.index(node)].keywords\\n )\\n args = node.assign_type().value.elts[node.parent.elts.index(node)].args\\n\\n variance = TypeVarVariance.invariant\\n name_arg = None\\n for kw in keywords:\\n if variance == TypeVarVariance.double_variant:\\n pass\\n elif kw.arg == \\\"covariant\\\" and kw.value.value:\\n variance = (\\n TypeVarVariance.covariant\\n if variance != TypeVarVariance.contravariant\\n else TypeVarVariance.double_variant\\n )\\n elif kw.arg == \\\"contravariant\\\" and kw.value.value:\\n variance = (\\n TypeVarVariance.contravariant\\n if variance != TypeVarVariance.covariant\\n else TypeVarVariance.double_variant\\n )\\n\\n if kw.arg == \\\"name\\\" and isinstance(kw.value, nodes.Const):\\n name_arg = kw.value.value\\n\\n if name_arg is None and args and isinstance(args[0], nodes.Const):\\n name_arg = args[0].value\\n\\n if variance == TypeVarVariance.double_variant:\\n self.add_message(\\n \\\"typevar-double-variance\\\",\\n node=node,\\n confidence=interfaces.INFERENCE,\\n )\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(\\\"\\\",),\\n confidence=interfaces.INFERENCE,\\n )\\n elif variance == TypeVarVariance.covariant and not name.endswith(\\\"_co\\\"):\\n suggest_name = f\\\"{re.sub('_contra$', '', name)}_co\\\"\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(f'. \\\"{name}\\\" is covariant, use \\\"{suggest_name}\\\" instead'),\\n confidence=interfaces.INFERENCE,\\n )\\n elif variance == TypeVarVariance.contravariant and not name.endswith(\\\"_contra\\\"):\\n suggest_name = f\\\"{re.sub('_co$', '', name)}_contra\\\"\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(f'. \\\"{name}\\\" is contravariant, use \\\"{suggest_name}\\\" instead'),\\n confidence=interfaces.INFERENCE,\\n )\\n elif variance == TypeVarVariance.invariant and (\\n name.endswith(\\\"_co\\\") or name.endswith(\\\"_contra\\\")\\n ):\\n suggest_name = re.sub(\\\"_contra$|_co$\\\", \\\"\\\", name)\\n self.add_message(\\n \\\"typevar-name-incorrect-variance\\\",\\n node=node,\\n args=(f'. \\\"{name}\\\" is invariant, use \\\"{suggest_name}\\\" instead'),\\n confidence=interfaces.INFERENCE,\\n )\\n\\n if name_arg is not None and name_arg != name:\\n self.add_message(\\n \\\"typevar-name-mismatch\\\",\\n node=node,\\n args=(name_arg, name),\\n confidence=interfaces.INFERENCE,\\n )\",\n \"def scalar_object_check(py_object, c_object):\\n\\n try :\\n check_type = check_type_registry[c_object.dtype, c_object.precision]\\n except KeyError:\\n errors.report(PYCCEL_RESTRICTION_TODO, symbol=c_object.dtype,severity='fatal')\\n\\n check_func = FunctionDef(name = check_type,\\n body = [],\\n arguments = [Variable(dtype=PyccelPyObject(), name = 'o', is_pointer=True)],\\n results = [Variable(dtype=NativeBool(), name = 'r')])\\n\\n return FunctionCall(check_func, [py_object])\",\n \"def has_classname(self):\\n return self.unpack_word(0x4A) > 0\",\n \"def validVarConstructType(self,vartype):\\r\\n indArray = vartype.find('[]')\\r\\n if indArray>0:\\r\\n thisType = vartype[0:indArray]\\r\\n isArray = True\\r\\n else:\\r\\n thisType = vartype\\r\\n isArray = False\\r\\n \\r\\n if thisType in ('rng','range'):\\r\\n type = 'range'\\r\\n elif thisType in ('rate'):\\r\\n type = 'rate'\\r\\n elif thisType in ('amt','amount'):\\r\\n type = 'amount'\\r\\n elif thisType in ('minamt','minamount'):\\r\\n type = 'minamount'\\r\\n elif thisType in ('bool'):\\r\\n type = 'bool'\\r\\n else:\\r\\n print 'variable type must be range, rate, amount, minamount, bool (or abbreviated forms)'\\r\\n return False, ''\\r\\n \\r\\n return True, type, isArray\",\n \"def _isintvar(self, index):\\n return 65528 <= self._typlist[index] <= 65530\",\n \"def has_vector_type(obj: _std_typing.Any) -> bool:\\n return obj.dtype == sc.DType.vector3\",\n \"def is_of_type(cls, value) -> bool:\\n # UTF8 = 'utf-8'\\n # UTF16 = 'utf-16'\\n # UTF32 = 'utf-32'\\n # ASCII = 'ascii'\\n # BINARY = 'binary'\\n # OCTAL = 'octal'\\n # HEXADECIMAL = 'hexadecimal'\\n # CP1252 = 'cp1252'\\n # WINDOWS1252 = 'windows-1252'\\n # UNICODEESCAPE = 'unicode-escape'\\n\\n v = None\\n if cls == cls.UTF8 or cls == cls.UTF16 or cls == cls.UTF32 or cls == cls.UNICODEESCAPE:\\n try:\\n v = bytes(value)\\n except:\\n return False\\n\\n if cls == cls.ASCII:\\n try:\\n v = ascii(value)\\n except:\\n return False\\n\\n if cls == cls.BINARY:\\n try:\\n v = bin(value)\\n except:\\n return False\\n\\n if cls == cls.OCTAL:\\n try:\\n v = oct(value)\\n except:\\n return False\\n\\n if cls == cls.HEXADECIMAL:\\n try:\\n v = hex(value)\\n except:\\n return False\\n\\n if cls == cls.WINDOWS1252 or cls == cls.CP1252:\\n try:\\n v = str(value)\\n except:\\n return False\\n return True\",\n \"def is_kind_of_class(obj, a_class):\\n if isinstance(obj, a_class) is True:\\n return True\\n else:\\n return False\",\n \"def predicate(cls: nodes.ClassDef) -> bool:\\n if cls.name in CLASS_NAME_SKIPLIST:\\n # class looks like an API model class, but it isn't.\\n return False\\n\\n if not cls.name.endswith(\\\"API\\\") and \\\"schema\\\" not in cls.locals:\\n # class does not look like an API model class.\\n return False\\n\\n return True\",\n \"def test_has_exactly_type():\\r\\n\\r\\n return has_exactly_type(1, int) and not has_exactly_type(True, int) and has_exactly_type(True, bool)\",\n \"def accepts_type(self, *args):\\n return _ida_hexrays.lvar_t_accepts_type(self, *args)\",\n \"def is_python(self):\\r\\n return self.has_label('python')\",\n \"def isConditional(self) -> bool:\\n ...\",\n \"def getvartype(self,j_): # 3\\n res,resargs = self.__obj.getvartype(j_)\\n if res != 0:\\n result,msg = self.__getlasterror(res)\\n raise Error(rescode(res),msg)\\n _vartype_return_value = resargs\\n _vartype_return_value = variabletype(_vartype_return_value)\\n return _vartype_return_value\",\n \"def _is_simple_type(cls):\\n return all([\\n AnnotationWrapper(anno).is_simple_in_opt_and_not_opt\\n for anno in cls._used_annotations()\\n ])\",\n \"def _is_run_type(cls, object_):\\n # Do a string comparison instead of using isinstance() to avoid needing\\n # to import lyse or other modules with these classes.\\n return (type(object_).__name__ in cls._RUN_TYPES)\",\n \"def has_field_type(self, field_type):\\n if not hasattr(self, '_field_types'):\\n self._field_types = {}\\n if not self._field_types.has_key(field_type):\\n try:\\n # First check self.fields.\\n for f in self.fields:\\n if isinstance(f, field_type):\\n raise StopIteration\\n # Failing that, check related fields.\\n for rel_obj, rel_field in self.get_inline_related_objects():\\n for f in rel_obj.fields:\\n if isinstance(f, field_type):\\n raise StopIteration\\n except StopIteration:\\n self._field_types[field_type] = True\\n else:\\n self._field_types[field_type] = False\\n return self._field_types[field_type]\",\n \"def is_kind_of_class(obj, a_class):\\n return(isinstance(obj, a_class))\",\n \"def predicate(obj):\\n return inspect.isclass(obj) and issubclass(obj, MafColumnRecord)\",\n \"def test(types, _):\\n return 'Date' in types and 'Postal Code' in types\",\n \"def check_global_attr_type(ds, attr, attr_type):\\n if attr not in ds.ncattrs():\\n return 0\\n\\n global_attr = getattr(ds, attr)\\n\\n if attr_type == 'int':\\n attr_type_class = int\\n elif attr_type == 'float':\\n attr_type_class = float\\n elif attr_type == 'str':\\n attr_type_class = str\\n else:\\n return 1\\n\\n if len(str(global_attr)) == 0:\\n return 2\\n\\n if np.dtype(type(global_attr)) != np.dtype(attr_type_class):\\n return 3\\n\\n return 4\",\n \"def __check(self, v):\\n v = base_type(v)\\n if not self._restriction_test(v):\\n raise ValueError, \\\"did not match restricted type\\\"\\n return True\",\n \"def type_match(cls, line):\\n match = Ftype_type_decl.__type_decl_re__.match(line.strip())\\n # End if\\n return match\",\n \"def __instancecheck__(self, instance):\\n\\n if isinstance(instance, ObjCInstance):\\n return bool(instance.isKindOfClass(self))\\n else:\\n return False\",\n \"def _ValidateField(self, field_tuple, entity):\\n if not self._field_universe.IsFieldDefined(field_tuple.field,\\n field_tuple.namespace):\\n self.AddFinding(\\n findings_lib.UndefinedFieldError(entity, field_tuple.field))\\n return False\\n return True\",\n \"def is_kind_of_class(obj, a_class):\\n if isinstance(obj, a_class):\\n return True\\n else:\\n return False\",\n \"def is_kind_of_class(obj, a_class):\\n if isinstance(obj, a_class):\\n return True\\n else:\\n return False\",\n \"def is_valid_field(self, field: DSLSelectable) -> bool:\\n\\n assert isinstance(self, DSLField)\\n\\n if isinstance(field, (DSLFragment, DSLInlineFragment)):\\n return True\\n\\n assert isinstance(field, DSLField)\\n\\n if isinstance(field, DSLMetaField):\\n return field.name == \\\"__typename\\\"\\n\\n parent_type = get_named_type(self.field.type)\\n\\n if not isinstance(parent_type, (GraphQLInterfaceType, GraphQLObjectType)):\\n return False\\n\\n if field.name in parent_type.fields.keys():\\n return parent_type.fields[field.name].type == field.field.type\\n\\n return False\",\n \"def is_kind_of_class(obj, a_class):\\n return (isinstance(obj, a_class))\",\n \"def _is_typing_object(type_object):\\n return type_object.__module__ == \\\"typing\\\"\",\n \"def has_required(self, obj: T) -> bool:\\n if (ufp_required_field := self.ufp_required_field) is None:\\n return True\\n if TYPE_CHECKING:\\n # `ufp_required_field` is defined as a `str` in the dataclass, but\\n # `__post_init__` converts it to a `tuple[str, ...]` to avoid\\n # doing it at run time in `get_nested_attr` which is usually called\\n # millions of times per day. This tells mypy that it's a tuple.\\n assert isinstance(ufp_required_field, tuple)\\n return bool(get_nested_attr(obj, ufp_required_field))\",\n \"def is_kind_of_class(obj, a_class):\\n if isinstance(obj, a_class):\\n return True\\n return False\",\n \"def verify_type(self, obj):\\n return isinstance(obj, self.type_)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5906985","0.5887892","0.5847857","0.58403444","0.58391064","0.58101076","0.57811445","0.5773369","0.5730297","0.567376","0.56302613","0.55703485","0.55521667","0.5544753","0.5519627","0.5511953","0.54748327","0.54581445","0.5455314","0.5455117","0.54478294","0.541336","0.53930265","0.53358656","0.53249997","0.5317362","0.5302079","0.53020644","0.5297996","0.52840596","0.5282151","0.5255362","0.5246804","0.52445954","0.52408105","0.5230825","0.5218114","0.5209122","0.5191848","0.51824534","0.518199","0.5181539","0.5164439","0.51435554","0.51025057","0.5093837","0.50759673","0.50721115","0.5055158","0.5033405","0.50302374","0.50107884","0.500867","0.5006558","0.5004969","0.50025386","0.49999386","0.49830645","0.49701706","0.4952215","0.49498406","0.49321726","0.49316388","0.49274847","0.4918097","0.4915666","0.4903832","0.48949412","0.4893918","0.48909566","0.48848754","0.4883862","0.48838058","0.48786566","0.48749554","0.4867591","0.4853864","0.4843968","0.48374763","0.48345068","0.48322734","0.48292783","0.48288614","0.4828712","0.48285317","0.48279697","0.4815875","0.48151025","0.48089173","0.47908467","0.47845268","0.47827742","0.47810033","0.47810033","0.47764605","0.47701558","0.476632","0.476021","0.4758682","0.47572035"],"string":"[\n \"0.5906985\",\n \"0.5887892\",\n \"0.5847857\",\n \"0.58403444\",\n \"0.58391064\",\n \"0.58101076\",\n \"0.57811445\",\n \"0.5773369\",\n \"0.5730297\",\n \"0.567376\",\n \"0.56302613\",\n \"0.55703485\",\n \"0.55521667\",\n \"0.5544753\",\n \"0.5519627\",\n \"0.5511953\",\n \"0.54748327\",\n \"0.54581445\",\n \"0.5455314\",\n \"0.5455117\",\n \"0.54478294\",\n \"0.541336\",\n \"0.53930265\",\n \"0.53358656\",\n \"0.53249997\",\n \"0.5317362\",\n \"0.5302079\",\n \"0.53020644\",\n \"0.5297996\",\n \"0.52840596\",\n \"0.5282151\",\n \"0.5255362\",\n \"0.5246804\",\n \"0.52445954\",\n \"0.52408105\",\n \"0.5230825\",\n \"0.5218114\",\n \"0.5209122\",\n \"0.5191848\",\n \"0.51824534\",\n \"0.518199\",\n \"0.5181539\",\n \"0.5164439\",\n \"0.51435554\",\n \"0.51025057\",\n \"0.5093837\",\n \"0.50759673\",\n \"0.50721115\",\n \"0.5055158\",\n \"0.5033405\",\n \"0.50302374\",\n \"0.50107884\",\n \"0.500867\",\n \"0.5006558\",\n \"0.5004969\",\n \"0.50025386\",\n \"0.49999386\",\n \"0.49830645\",\n \"0.49701706\",\n \"0.4952215\",\n \"0.49498406\",\n \"0.49321726\",\n \"0.49316388\",\n \"0.49274847\",\n \"0.4918097\",\n \"0.4915666\",\n \"0.4903832\",\n \"0.48949412\",\n \"0.4893918\",\n \"0.48909566\",\n \"0.48848754\",\n \"0.4883862\",\n \"0.48838058\",\n \"0.48786566\",\n \"0.48749554\",\n \"0.4867591\",\n \"0.4853864\",\n \"0.4843968\",\n \"0.48374763\",\n \"0.48345068\",\n \"0.48322734\",\n \"0.48292783\",\n \"0.48288614\",\n \"0.4828712\",\n \"0.48285317\",\n \"0.48279697\",\n \"0.4815875\",\n \"0.48151025\",\n \"0.48089173\",\n \"0.47908467\",\n \"0.47845268\",\n \"0.47827742\",\n \"0.47810033\",\n \"0.47810033\",\n \"0.47764605\",\n \"0.47701558\",\n \"0.476632\",\n \"0.476021\",\n \"0.4758682\",\n \"0.47572035\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5669835"},"document_rank":{"kind":"string","value":"10"}}},{"rowIdx":13076,"cells":{"query":{"kind":"string","value":"Unzips a list of tuples, x."},"document":{"kind":"string","value":"def unzip(self, x):\n if (len(x)>0):\n return list(zip(*x))\n else:\n return x, list()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def unzip(pairs):\n return tuple(zip(*pairs))","def unzip(zipped):\n return zip(*zipped)","def unzip(seq):\n return zip(*seq)","def unzip(seq: Iterable) -> tuple:\n seq = iter(seq)\n # check how many iterators we need\n try:\n first = tuple(next(seq))\n except StopIteration:\n return tuple()\n # and create them\n niters = len(first)\n seqs = itertools.tee(itertoolz.cons(first, seq), niters)\n return tuple(itertools.starmap(itertoolz.pluck, enumerate(seqs)))","def unzip(seq):\n seq = iter(seq)\n # check how many iterators we need\n try:\n first = tuple(next(seq))\n except StopIteration:\n return tuple()\n # and create them\n niters = len(first)\n seqs = tee(cons(first, seq), niters)\n return tuple(starmap(pluck, enumerate(seqs)))","def lzip(*args):\n return list(zip(*args))","def unzip(i, iterable):\n return [x[i] for x in iterable]","def unzip(ls, nout):\n out = list(zip(*ls))\n if not out:\n out = [()] * nout\n return out","def unzip(iterable: Iterable[Tuple[Any, ...]]) -> Tuple[Iterator[Any], ...]:\n first, iterator = _common.peek(iter(iterable))\n if first is None:\n return ()\n tees = itertools.tee(iterator, len(first))\n return (map(operator.itemgetter(i), tee) for i, tee in enumerate(tees))","def unzip3(self) -> Tuple[List, List, List]:\n lista, listb, listc = [], [], []\n for a, b, c in self.array:\n lista.append(a)\n listb.append(b)\n listc.append(c)\n return lista, listb, listc","def unzip2(self) -> Tuple[List, List]:\n lista, listb = [], []\n for a, b in self.array:\n lista.append(a)\n listb.append(b)\n return lista, listb","def x_unzip(xid=None):\n\t_loadconfig()\n\tnavimport.conf.print_zips()\n\n\txrec = None\n\tif xid == None:\n\t\txrec = _prompt_xid(\"No to unzip >\")\n\telse:\n\t\txrec = navimport.conf.get_xplane_zip_info(0)\n\n\tif xrec != None:\n\t\tprint xrec\n\n\t\ts = \"unzip \"\n\t\ts += \" -d \" + navimport.conf.work_dir(\"/xplane_unzipped/%s\" % xrec['zip_dir'])\n\t\ts += \" \"\n\t\ts += navimport.conf.work_dir(\"/xplane_zips/%s\" % xrec['file_name'])\n\t\tlocal(s)","def unzip_lst(lst):\n unzipped = list(zip(*lst))\n unzipped_lsts = [list(tp) for tp in unzipped]\n return unzipped_lsts","def unzip_finite(\n iterable: Iterable[Tuple[Any, ...]],\n) -> Tuple[Iterator[Any], ...]:\n for zipped in zip(*iterable):\n yield zipped","def _unpack_tuple(x):\n if len(x) == 1:\n return x[0]\n else:\n return x","def _unpack_tuple(x):\n if len(x) == 1:\n return x[0]\n else:\n return x","def unzip_batch(batch):\n unzip = [[i for i, j in batch],\n [j for i, j in batch]]\n return np.transpose(unzip[0]), np.transpose(unzip[1])","def myzip(*iterables):\n result_list = []\n for i in range(len(iterables[0])): \n lst = []\n for k in iterables:\n lst.append(k[i])\n result_list.append(tuple(lst))\n return result_list","def zip() -> List:\n pass","def Unpack(Items):\n \n import numpy as np\n \n nda = np.array(Items)\n \n if len(nda.shape) < 2:\n msg = \"The input argument is a list of length 1. There is nothing to\" \\\n + \" unpack.\"\n \n raise Exception(msg)\n \n dim = nda.shape[1]\n \n # Initialise unpacked lists:\n X = []\n Y = []\n Z = []\n \n if dim == 2:\n # Unpack tuple and store in X, Y:\n for x, y in Items:\n X.append(x)\n Y.append(y)\n \n return X, Y\n \n elif dim == 3:\n # Unpack tuple and store in X, Y, Z:\n for x, y, z in Items:\n X.append(x)\n Y.append(y)\n Z.append(z)\n \n return X, Y, Z\n \n else:\n msg = f\"The input argument has dim = {dim}. Only dim = 2 or dim = 3 \"\\\n + \"is allowed.\"\n \n raise Exception(msg)","def easy_unpack(elements: Tuple[int]) -> Tuple[int]:\n\n return itemgetter(0, 2, -2)(elements)","def decompose_atom_list(atom_list):\n transpose = list(zip(*atom_list))\n if len(transpose) == 4:\n elements = np.array(transpose[0])\n array_a = np.array(transpose[1]).reshape(-1, 1)\n array_b = np.array(transpose[2]).reshape(-1, 1)\n array_c = np.array(transpose[3]).reshape(-1, 1)\n array_ab = np.concatenate((array_a, array_b), axis=1)\n coordinates = np.concatenate((array_ab, array_c), axis=1)\n return elements, coordinates\n elif len(transpose) == 5:\n elements = np.array(transpose[0])\n atom_ids = np.array(transpose[1])\n array_a = np.array(transpose[2]).reshape(-1, 1)\n array_b = np.array(transpose[3]).reshape(-1, 1)\n array_c = np.array(transpose[4]).reshape(-1, 1)\n array_ab = np.concatenate((array_a, array_b), axis=1)\n coordinates = np.concatenate((array_ab, array_c), axis=1)\n return elements, atom_ids, coordinates\n else:\n raise _FunctionError(\n \"The decompose_atom_list() function accepts only list of lists \"\n \" with only 4 or 5 items per sublist.\")","def unflatten(self, x):\n dims = [c.flat_dim for c in self.spaces]\n flat_x = np.split(x, np.cumsum(dims)[:-1])\n return tuple(c.unflatten(xi) for c, xi in zip(self.spaces, flat_x))","def from_tuples(cls, tuples):\n x, y = zip(*tuples)\n return cls(x, y)","async def azip(*aiters):\n anext_tuple = tuple([_.__aiter__() for _ in aiters])\n while True:\n try:\n next_tuple = tuple([await _.__anext__() for _ in anext_tuple])\n except StopAsyncIteration:\n break\n yield next_tuple","def transpose(lst):\n return list(zip(*lst))","def vstack (tup ):\n\tl = len(tup[0])\n\tfor j in tup:\n\t\tif l!=len(j):\n\t\t\tprint \"error: dimensions don't match\"\n\t\t\treturn\n\tm = [];\n\tfor i in range(0,len(tup)):\n\t\tm.extend(zip(*tup[i]))\n\treturn zip(*m)","def unzip_data():\n zip_ref = zipfile.ZipFile(data_zip, 'r')\n zip_ref.extractall('')\n zip_ref.close()","def unzip(input_file, output_file):\n output_file = validator.validate_unzip(input_file, output_file)\n process = subprocess.Popen([PBWT_BIN, 'unzip', input_file, output_file],\n stdout=subprocess.PIPE)\n process_results(str(process.communicate()[0]))","def vec2tuple(x):\n return (x.x, x.y, x.z)","def element_to_tuple(list_of_elements):\n return list(map(lambda x: tuple(x), list_of_elements))","def _swapxy(data):\n return [(y, x) for (x, y) in data]","def main():\n zipper_two_lists_tests()\n zipper_two_tuples_tests()\n zipper_list_and_tuple_tests()","def zip(*args: Union[Iterable[ObservableBase], ObservableBase],\n result_mapper: Mapper = None) -> ObservableBase:\n from ..operators.observable.zip import zip as _zip\n return _zip(*args, result_mapper=result_mapper)","def zip(self, *others):\n plothers = plist(others)\n if plothers.any(lambda x: len(x) != len(self)):\n raise ValueError('plist.zip arguments must all have the same length as self (%d)' % len(self))\n try:\n return plist([x.zip(*plothers.__getitem___(i)) for i, x in enumerate(self)], root=self.__root__)\n except Exception:\n pass\n zipped = [x for x in zip(self, *others)] # 3.6 compatibility\n return plist(zipped, root=self.__root__[0:len(zipped):1])","def unzip_and_untar(item):\n print(\"Unpacking %s\" % item)\n\n f = tarfile.open(item, mode=\"r\")\n f.extractall(path=\"working\")\n f.close()","def zipper_list_and_tuple_tests():\n assert_with_message(zipper((1, 2, 3), [\"hello\", \"mr.\", \"world\"]), [(1, \"hello\"), (2, \"mr.\"), (3, \"world\")])\n assert_with_message(zipper([1, 2, 3], (\"hello\", \"mr.\", \"world\")), [(1, \"hello\"), (2, \"mr.\"), (3, \"world\")])\n assert_with_message(zipper([1, 2, 3], ()), [])\n assert_with_message(zipper([], (\"hello\", \"mr.\", \"world\")), [])\n assert_with_message(zipper([], ()), [])\n print(\"All tests with a list and a tuple as parameters passed!\")","def _collate_fn(batch):\r\n batch = list(zip(*batch))\r\n batch[0] = torch.stack(batch[0])\r\n batch[1] = list(batch[1])\r\n batch[2] = torch.stack(batch[2])\r\n return tuple(batch)","def derive(self, inputs):\n\t\ttry:\n\t\t\tr = [x[self.target] for x in inputs[0]]\n\t\t\tif self.force_numpy:\n\t\t\t\tr = numpy.array(r)\n\t\t\treturn r\n\t\texcept IndexError:\n\t\t\tlogger.error('Failed to unzip input data: %s', inputs)\n\t\t\traise","def zip_lsts(lsts):\n lengths = [len(lst) for lst in lsts]\n assert len(list(set(lengths))) == 1 # assert that the lsts have the same lengths\n zipped_lst = [list(tp) for tp in list(zip(*lsts))]\n return zipped_lst","def generic_generator(*args):\n for zips in zip(*args):\n yield zips","def gen_4_tuples(it):\n\n return list(zip(it[0::4], it[1::4], it[2::4], it[3::4]))","def gen_4_tuples(it):\n\n return list(zip(it[0::4], it[1::4], it[2::4], it[3::4]))","def zip(self, *lists):\n return _(zip(self._, *lists))","def rearrange_batch(batch):\n return list(zip(*batch))","def unzip(zipped):\n new_params = OrderedDict()\n for kk, vv in zipped.items():\n new_params[kk] = vv.get_value()\n return new_params","def _unzip(filename, branch=None):\n try:\n file = zipfile.ZipFile(filename)\n basename = os.path.dirname(filename)\n basename = basename.replace(\".zip\", \"\")\n file.extractall(path=basename)\n return basename, filename\n except Exception as e:\n six.print_(e)","def decode_tuple1(as_bytes: typing.List[int]) -> tuple:\n raise NotImplementedError()","def tuple_map(x):\n return x * 2","def zip2(*iterables, default=None):\n pack = [default] * len(iterables)\n # benchmarck this fonction using (unordered) set() or (ordered) dict() : seem that using dict() is a little bit quicker than set(), which is a bit quicker than list().\n #iterators = [(i, iter(it)) for i, it in enumerate(iterables)] # list()\n #iterators = {(i, iter(it)) for i, it in enumerate(iterables)} # unordered set() : https://docs.python.org/3/tutorial/datastructures.html#sets\n iterators = {i: iter(it) for i, it in enumerate(iterables)} # ordered dict() : https://docs.python.org/3/tutorial/datastructures.html#dictionaries\n todel = [] # using set() or dict()\n while True:\n #oi = 0 # using list()\n #for ii, (i, it) in enumerate(iterators): # using list()\n #for i, it in iterators: # using set()\n for i, it in iterators.items(): # using dict()\n for v in it:\n pack[i] = v\n break\n else:\n pack[i] = default\n #iterators.pop(ii - oi) ; oi += 1 # using list()\n #todel.append((i, it)) # using set()\n todel.append(i) # using dict()\n if todel:\n #for i in todel: iterators.remove(i) # using set()\n for i in todel: del iterators[i] # using dict()\n todel[:] = ()\n if iterators: yield tuple(pack)\n else: break","def exactZip(*args):\n lengths = [len(a) for a in args]\n if len(set(lengths)) <= 1:\n return zip(*args)\n else:\n raise ValueError(\"Iterables were of different lengths; {0}\".format(args))","def zip(*args, **kwargs):\n args = [list(iterable) for iterable in args]\n n = max(map(len, args))\n v = kwargs.get(\"default\", None)\n return _zip(*[i + [v] * (n - len(i)) for i in args])","def aind(x):\n\treturn tuple(x.T)","def unzip_all(input_file: pathlib.Path) -> Tuple[pathlib.Path, tempfile.TemporaryDirectory]:\n output_temp_dir = tempfile.TemporaryDirectory()\n output_path = pathlib.Path(output_temp_dir.name)\n\n extract_zip(input_file, output_path)\n\n return output_path, output_temp_dir","def easy_unpack_my(elements):\n try:\n res = tuple(elements[i] for i in [0, 2, -2])\n except IndexError:\n res = 0\n return res","def recombine_zip(x):\r\n overlap_zip = {10118: 10001, 10119: 10001, 10120: 10001, 10121: 10001, 10122: 10001, 10123: 10001, 10041: 10004, 10275: 10004,\r\n 10043: 10005, 10081: 10005, 10203: 10005, 10259: 10005, 10260: 10005, 10265: 10005, 10270: 10005, 10271: 10005,\r\n 10286: 10005, 10278: 10007, 10279: 10007, 10047: 10010, 10158: 10016, 10165: 10017, 10166: 10017, 10167: 10017,\r\n 10168: 10017, 10169: 10017, 10170: 10017, 10171: 10017, 10172: 10017, 10173: 10017, 10174: 10017, 10175: 10017,\r\n 10176: 10017, 10177: 10017, 10178: 10017, 10097: 10019, 10103: 10019, 10104: 10019, 10105: 10019, 10106: 10019,\r\n 10107: 10019, 10111: 10019, 10020: 10019, 10112: 10019, 10162: 10021, 10055: 10022, 10151: 10022, 10152: 10022,\r\n 10153: 10022, 10154: 10022, 10155: 10022, 10096: 10036, 10110: 10036, 10196: 10036, 10045: 10038, 10080: 10048,\r\n 10285: 10281, 10069: 10023, 11451: 11433, 10115: 10027, 11109:11101}\r\n \r\n if x in overlap_zip.keys():\r\n return overlap_zip[x]\r\n if x in overlap_zip.values():\r\n return x\r\n else:\r\n return x","def unflatten(x: List, y: List) -> List:\n def func(cum, this):\n x_crop, res = cum\n return [\n x_crop[len(this):], res + [x_crop[:len(this)]]\n ]\n\n return functools.reduce(func, list(y), [list(x), []])[-1]","def zip_with_singletons(*args):\n return zip(*(arg if isinstance(arg, list) else itertools.repeat(arg) for arg in args))","def longzip(a, b):\n aiter = iter(a)\n biter = iter(b)\n try:\n for item1 in aiter:\n yield item1, next(biter)\n except StopIteration:\n for item1 in aiter:\n yield item1, None\n else:\n for item2 in biter:\n yield None, item2","def unpack(self):\n return list(itertools.chain(*[arg.unpack()\n for arg in self.args\n if isinstance(arg, _Unpackable)]))","def decode_tuple2(as_bytes: typing.List[int]) -> tuple:\n raise NotImplementedError()","def pairwise(iterable):\n a = iter(iterable)\n return zip(a, a, a)","def get_tuples(outputs) -> list:\n return list(map(get_tuples_helper, outputs))","def unzip(input_filename, extract_dir):\n if not zipfile.is_zipfile(input_filename):\n raise ValueError(\"%s is not a zip file\" % (input_filename))\n zip_ds = zipfile.ZipFile(input_filename)\n zip_ds.extractall(path=extract_dir)\n zip_ds.close()","def split_in_pairs(arg: Iterable) -> Iterable[Tuple]:\n # We are using zip_longest with one clever hack:\n # https://docs.python.org/3/library/itertools.html#itertools.zip_longest\n # We create an iterator out of the list and then pass the same iterator to\n # the function two times. Thus the function consumes a different element\n # from the iterator each time and produces the desired result.\n iterator = iter(arg)\n return zip_longest(iterator, iterator)","def unzip(zip_path, output_file, data_folder):\n\n print('Unzipping file: {}'.format(zip_path))\n pyunpack.Archive(zip_path).extractall(data_folder)\n\n # Checks if unzip was successful\n if not os.path.exists(output_file):\n raise ValueError(\n 'Error in unzipping process! {} not found.'.format(output_file))","def unzip(zip_path, cleanup=False):\n zfile = zipfile.ZipFile(zip_path, 'r')\n zfile.extractall(os.path.dirname(zip_path))\n zfile.close()\n if cleanup:\n os.remove(zip_path)","def pairwise(iterable):\n a = iter(iterable)\n return zip(a, a)","def ex_list(data):\n return tuple(data)","def pairwise(iterable: Iterable,\n tuple_size: int):\n return zip_longest(*(islice(it, pos, None) for pos, it in enumerate(tee(iterable, tuple_size))))","def unzipArchives(zip_file, password):\n with ZipFile(zip_file) as archive:\n archive.extractall(pwd=bytes(password, \"utf8\"))","def tups(self, args=None, lo=None, hi=None, reverse=None, max=None,\n include=False, txn=None):\n return itertools.imap(ITEMGETTER_0,\n self.pairs(args, lo, hi, reverse, max, include, txn))","def decode_tuple3(as_bytes: typing.List[int]) -> tuple:\n raise NotImplementedError()","def tuple_from_sequence(*args):\n return tuple(args)","def main():\n list1 = ListNode(1)\n list1.next = ListNode(3)\n list1.next.next = ListNode(5)\n\n list2 = ListNode(2)\n list2.next = ListNode(4)\n list2.next.next = ListNode(6)\n\n result = zipper(list1,list2)\n print(result)","def tupleofwords_to_wordoftuples(tupleofwords):\n return list(zip_longest(*tupleofwords, fillvalue=None))","def stagger_tuple(elements_list, initial=None):\n res = []\n previous_element = initial\n for element in elements_list:\n if previous_element is not None:\n res.append((previous_element, element))\n previous_element = element\n return res","def unzip_file(data_zip, path_unzip):\r\n with zipfile.ZipFile(data_zip, \"r\") as zip_temp:\r\n zip_temp.extractall(path_unzip)","def deltas(L):\n return map(sub, tuple(L)[1:], L)","def pairwise(iterable):\n a, b = itertools.tee(iterable)\n next(b, None)\n return list(zip(a, b))","def pairwise(iterable):\n a, b = itertools.tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = itertools.tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = itertools.tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = tee(iterable)\n next(b, None)\n return zip(a, b)","def pairwise(iterable):\n a, b = tee(iterable)\n next(b, None)\n\n return zip(a, b)","def pairwise(iterable):\n a, b = tee(iterable)\n next(b, None)\n\n return zip(a, b)","def transpose_list_of_lists(lol):\n assert lol, \"cannot pass the empty list\"\n return [list(x) for x in zip(*lol)]","def __fix_tuple(self, xy_tup):\n if self.__swapxy:\n return xy_tup[::-1]\n return xy_tup","def transpose_lists(lists):\n return list(map(list, zip(*lists)))","def transpose(seqseq):\n return zip(*seqseq)","def strip_tuple(tuple_list, tuple_index = 0):\n elem_list = []\n for i in range(0, len(tuple_list)):\n elem_list.append(tuple_list[i][tuple_index])\n return elem_list","def test_unstack():\n x = np.arange(1, 13).reshape((3, 2, 2)).astype(np.int32)\n axis = 0\n x_tensor = paddle.to_tensor(x)\n out_list = paddle.unstack(x_tensor, axis=axis)\n length = len(out_list)\n for i in range(length):\n ept = x[i, :, :]\n npt.assert_allclose(out_list[i].numpy(), ept)","def from_zip(cls, *args, **kwargs):\n return cls().add_zip(*args, **kwargs)","def _repack(linear, n=3):\n return list(zip(*[iter(linear)] * n))","def pairwise(iterable):\n a, b = itertools.tee(iterable)\n next(b, None)\n return itertools.zip_longest(a, b)","def _create_zip(*iterables, fillvalue=None, type_longest=False):\n\n if type_longest:\n from itertools import zip_longest\n\n zipped = zip_longest(*iterables, fillvalue=fillvalue)\n else:\n zipped = zip(*iterables)\n return zipped","def tuple_merge(tuples):\n\n\t# Add your code here\n\treturn"],"string":"[\n \"def unzip(pairs):\\n return tuple(zip(*pairs))\",\n \"def unzip(zipped):\\n return zip(*zipped)\",\n \"def unzip(seq):\\n return zip(*seq)\",\n \"def unzip(seq: Iterable) -> tuple:\\n seq = iter(seq)\\n # check how many iterators we need\\n try:\\n first = tuple(next(seq))\\n except StopIteration:\\n return tuple()\\n # and create them\\n niters = len(first)\\n seqs = itertools.tee(itertoolz.cons(first, seq), niters)\\n return tuple(itertools.starmap(itertoolz.pluck, enumerate(seqs)))\",\n \"def unzip(seq):\\n seq = iter(seq)\\n # check how many iterators we need\\n try:\\n first = tuple(next(seq))\\n except StopIteration:\\n return tuple()\\n # and create them\\n niters = len(first)\\n seqs = tee(cons(first, seq), niters)\\n return tuple(starmap(pluck, enumerate(seqs)))\",\n \"def lzip(*args):\\n return list(zip(*args))\",\n \"def unzip(i, iterable):\\n return [x[i] for x in iterable]\",\n \"def unzip(ls, nout):\\n out = list(zip(*ls))\\n if not out:\\n out = [()] * nout\\n return out\",\n \"def unzip(iterable: Iterable[Tuple[Any, ...]]) -> Tuple[Iterator[Any], ...]:\\n first, iterator = _common.peek(iter(iterable))\\n if first is None:\\n return ()\\n tees = itertools.tee(iterator, len(first))\\n return (map(operator.itemgetter(i), tee) for i, tee in enumerate(tees))\",\n \"def unzip3(self) -> Tuple[List, List, List]:\\n lista, listb, listc = [], [], []\\n for a, b, c in self.array:\\n lista.append(a)\\n listb.append(b)\\n listc.append(c)\\n return lista, listb, listc\",\n \"def unzip2(self) -> Tuple[List, List]:\\n lista, listb = [], []\\n for a, b in self.array:\\n lista.append(a)\\n listb.append(b)\\n return lista, listb\",\n \"def x_unzip(xid=None):\\n\\t_loadconfig()\\n\\tnavimport.conf.print_zips()\\n\\n\\txrec = None\\n\\tif xid == None:\\n\\t\\txrec = _prompt_xid(\\\"No to unzip >\\\")\\n\\telse:\\n\\t\\txrec = navimport.conf.get_xplane_zip_info(0)\\n\\n\\tif xrec != None:\\n\\t\\tprint xrec\\n\\n\\t\\ts = \\\"unzip \\\"\\n\\t\\ts += \\\" -d \\\" + navimport.conf.work_dir(\\\"/xplane_unzipped/%s\\\" % xrec['zip_dir'])\\n\\t\\ts += \\\" \\\"\\n\\t\\ts += navimport.conf.work_dir(\\\"/xplane_zips/%s\\\" % xrec['file_name'])\\n\\t\\tlocal(s)\",\n \"def unzip_lst(lst):\\n unzipped = list(zip(*lst))\\n unzipped_lsts = [list(tp) for tp in unzipped]\\n return unzipped_lsts\",\n \"def unzip_finite(\\n iterable: Iterable[Tuple[Any, ...]],\\n) -> Tuple[Iterator[Any], ...]:\\n for zipped in zip(*iterable):\\n yield zipped\",\n \"def _unpack_tuple(x):\\n if len(x) == 1:\\n return x[0]\\n else:\\n return x\",\n \"def _unpack_tuple(x):\\n if len(x) == 1:\\n return x[0]\\n else:\\n return x\",\n \"def unzip_batch(batch):\\n unzip = [[i for i, j in batch],\\n [j for i, j in batch]]\\n return np.transpose(unzip[0]), np.transpose(unzip[1])\",\n \"def myzip(*iterables):\\n result_list = []\\n for i in range(len(iterables[0])): \\n lst = []\\n for k in iterables:\\n lst.append(k[i])\\n result_list.append(tuple(lst))\\n return result_list\",\n \"def zip() -> List:\\n pass\",\n \"def Unpack(Items):\\n \\n import numpy as np\\n \\n nda = np.array(Items)\\n \\n if len(nda.shape) < 2:\\n msg = \\\"The input argument is a list of length 1. There is nothing to\\\" \\\\\\n + \\\" unpack.\\\"\\n \\n raise Exception(msg)\\n \\n dim = nda.shape[1]\\n \\n # Initialise unpacked lists:\\n X = []\\n Y = []\\n Z = []\\n \\n if dim == 2:\\n # Unpack tuple and store in X, Y:\\n for x, y in Items:\\n X.append(x)\\n Y.append(y)\\n \\n return X, Y\\n \\n elif dim == 3:\\n # Unpack tuple and store in X, Y, Z:\\n for x, y, z in Items:\\n X.append(x)\\n Y.append(y)\\n Z.append(z)\\n \\n return X, Y, Z\\n \\n else:\\n msg = f\\\"The input argument has dim = {dim}. Only dim = 2 or dim = 3 \\\"\\\\\\n + \\\"is allowed.\\\"\\n \\n raise Exception(msg)\",\n \"def easy_unpack(elements: Tuple[int]) -> Tuple[int]:\\n\\n return itemgetter(0, 2, -2)(elements)\",\n \"def decompose_atom_list(atom_list):\\n transpose = list(zip(*atom_list))\\n if len(transpose) == 4:\\n elements = np.array(transpose[0])\\n array_a = np.array(transpose[1]).reshape(-1, 1)\\n array_b = np.array(transpose[2]).reshape(-1, 1)\\n array_c = np.array(transpose[3]).reshape(-1, 1)\\n array_ab = np.concatenate((array_a, array_b), axis=1)\\n coordinates = np.concatenate((array_ab, array_c), axis=1)\\n return elements, coordinates\\n elif len(transpose) == 5:\\n elements = np.array(transpose[0])\\n atom_ids = np.array(transpose[1])\\n array_a = np.array(transpose[2]).reshape(-1, 1)\\n array_b = np.array(transpose[3]).reshape(-1, 1)\\n array_c = np.array(transpose[4]).reshape(-1, 1)\\n array_ab = np.concatenate((array_a, array_b), axis=1)\\n coordinates = np.concatenate((array_ab, array_c), axis=1)\\n return elements, atom_ids, coordinates\\n else:\\n raise _FunctionError(\\n \\\"The decompose_atom_list() function accepts only list of lists \\\"\\n \\\" with only 4 or 5 items per sublist.\\\")\",\n \"def unflatten(self, x):\\n dims = [c.flat_dim for c in self.spaces]\\n flat_x = np.split(x, np.cumsum(dims)[:-1])\\n return tuple(c.unflatten(xi) for c, xi in zip(self.spaces, flat_x))\",\n \"def from_tuples(cls, tuples):\\n x, y = zip(*tuples)\\n return cls(x, y)\",\n \"async def azip(*aiters):\\n anext_tuple = tuple([_.__aiter__() for _ in aiters])\\n while True:\\n try:\\n next_tuple = tuple([await _.__anext__() for _ in anext_tuple])\\n except StopAsyncIteration:\\n break\\n yield next_tuple\",\n \"def transpose(lst):\\n return list(zip(*lst))\",\n \"def vstack (tup ):\\n\\tl = len(tup[0])\\n\\tfor j in tup:\\n\\t\\tif l!=len(j):\\n\\t\\t\\tprint \\\"error: dimensions don't match\\\"\\n\\t\\t\\treturn\\n\\tm = [];\\n\\tfor i in range(0,len(tup)):\\n\\t\\tm.extend(zip(*tup[i]))\\n\\treturn zip(*m)\",\n \"def unzip_data():\\n zip_ref = zipfile.ZipFile(data_zip, 'r')\\n zip_ref.extractall('')\\n zip_ref.close()\",\n \"def unzip(input_file, output_file):\\n output_file = validator.validate_unzip(input_file, output_file)\\n process = subprocess.Popen([PBWT_BIN, 'unzip', input_file, output_file],\\n stdout=subprocess.PIPE)\\n process_results(str(process.communicate()[0]))\",\n \"def vec2tuple(x):\\n return (x.x, x.y, x.z)\",\n \"def element_to_tuple(list_of_elements):\\n return list(map(lambda x: tuple(x), list_of_elements))\",\n \"def _swapxy(data):\\n return [(y, x) for (x, y) in data]\",\n \"def main():\\n zipper_two_lists_tests()\\n zipper_two_tuples_tests()\\n zipper_list_and_tuple_tests()\",\n \"def zip(*args: Union[Iterable[ObservableBase], ObservableBase],\\n result_mapper: Mapper = None) -> ObservableBase:\\n from ..operators.observable.zip import zip as _zip\\n return _zip(*args, result_mapper=result_mapper)\",\n \"def zip(self, *others):\\n plothers = plist(others)\\n if plothers.any(lambda x: len(x) != len(self)):\\n raise ValueError('plist.zip arguments must all have the same length as self (%d)' % len(self))\\n try:\\n return plist([x.zip(*plothers.__getitem___(i)) for i, x in enumerate(self)], root=self.__root__)\\n except Exception:\\n pass\\n zipped = [x for x in zip(self, *others)] # 3.6 compatibility\\n return plist(zipped, root=self.__root__[0:len(zipped):1])\",\n \"def unzip_and_untar(item):\\n print(\\\"Unpacking %s\\\" % item)\\n\\n f = tarfile.open(item, mode=\\\"r\\\")\\n f.extractall(path=\\\"working\\\")\\n f.close()\",\n \"def zipper_list_and_tuple_tests():\\n assert_with_message(zipper((1, 2, 3), [\\\"hello\\\", \\\"mr.\\\", \\\"world\\\"]), [(1, \\\"hello\\\"), (2, \\\"mr.\\\"), (3, \\\"world\\\")])\\n assert_with_message(zipper([1, 2, 3], (\\\"hello\\\", \\\"mr.\\\", \\\"world\\\")), [(1, \\\"hello\\\"), (2, \\\"mr.\\\"), (3, \\\"world\\\")])\\n assert_with_message(zipper([1, 2, 3], ()), [])\\n assert_with_message(zipper([], (\\\"hello\\\", \\\"mr.\\\", \\\"world\\\")), [])\\n assert_with_message(zipper([], ()), [])\\n print(\\\"All tests with a list and a tuple as parameters passed!\\\")\",\n \"def _collate_fn(batch):\\r\\n batch = list(zip(*batch))\\r\\n batch[0] = torch.stack(batch[0])\\r\\n batch[1] = list(batch[1])\\r\\n batch[2] = torch.stack(batch[2])\\r\\n return tuple(batch)\",\n \"def derive(self, inputs):\\n\\t\\ttry:\\n\\t\\t\\tr = [x[self.target] for x in inputs[0]]\\n\\t\\t\\tif self.force_numpy:\\n\\t\\t\\t\\tr = numpy.array(r)\\n\\t\\t\\treturn r\\n\\t\\texcept IndexError:\\n\\t\\t\\tlogger.error('Failed to unzip input data: %s', inputs)\\n\\t\\t\\traise\",\n \"def zip_lsts(lsts):\\n lengths = [len(lst) for lst in lsts]\\n assert len(list(set(lengths))) == 1 # assert that the lsts have the same lengths\\n zipped_lst = [list(tp) for tp in list(zip(*lsts))]\\n return zipped_lst\",\n \"def generic_generator(*args):\\n for zips in zip(*args):\\n yield zips\",\n \"def gen_4_tuples(it):\\n\\n return list(zip(it[0::4], it[1::4], it[2::4], it[3::4]))\",\n \"def gen_4_tuples(it):\\n\\n return list(zip(it[0::4], it[1::4], it[2::4], it[3::4]))\",\n \"def zip(self, *lists):\\n return _(zip(self._, *lists))\",\n \"def rearrange_batch(batch):\\n return list(zip(*batch))\",\n \"def unzip(zipped):\\n new_params = OrderedDict()\\n for kk, vv in zipped.items():\\n new_params[kk] = vv.get_value()\\n return new_params\",\n \"def _unzip(filename, branch=None):\\n try:\\n file = zipfile.ZipFile(filename)\\n basename = os.path.dirname(filename)\\n basename = basename.replace(\\\".zip\\\", \\\"\\\")\\n file.extractall(path=basename)\\n return basename, filename\\n except Exception as e:\\n six.print_(e)\",\n \"def decode_tuple1(as_bytes: typing.List[int]) -> tuple:\\n raise NotImplementedError()\",\n \"def tuple_map(x):\\n return x * 2\",\n \"def zip2(*iterables, default=None):\\n pack = [default] * len(iterables)\\n # benchmarck this fonction using (unordered) set() or (ordered) dict() : seem that using dict() is a little bit quicker than set(), which is a bit quicker than list().\\n #iterators = [(i, iter(it)) for i, it in enumerate(iterables)] # list()\\n #iterators = {(i, iter(it)) for i, it in enumerate(iterables)} # unordered set() : https://docs.python.org/3/tutorial/datastructures.html#sets\\n iterators = {i: iter(it) for i, it in enumerate(iterables)} # ordered dict() : https://docs.python.org/3/tutorial/datastructures.html#dictionaries\\n todel = [] # using set() or dict()\\n while True:\\n #oi = 0 # using list()\\n #for ii, (i, it) in enumerate(iterators): # using list()\\n #for i, it in iterators: # using set()\\n for i, it in iterators.items(): # using dict()\\n for v in it:\\n pack[i] = v\\n break\\n else:\\n pack[i] = default\\n #iterators.pop(ii - oi) ; oi += 1 # using list()\\n #todel.append((i, it)) # using set()\\n todel.append(i) # using dict()\\n if todel:\\n #for i in todel: iterators.remove(i) # using set()\\n for i in todel: del iterators[i] # using dict()\\n todel[:] = ()\\n if iterators: yield tuple(pack)\\n else: break\",\n \"def exactZip(*args):\\n lengths = [len(a) for a in args]\\n if len(set(lengths)) <= 1:\\n return zip(*args)\\n else:\\n raise ValueError(\\\"Iterables were of different lengths; {0}\\\".format(args))\",\n \"def zip(*args, **kwargs):\\n args = [list(iterable) for iterable in args]\\n n = max(map(len, args))\\n v = kwargs.get(\\\"default\\\", None)\\n return _zip(*[i + [v] * (n - len(i)) for i in args])\",\n \"def aind(x):\\n\\treturn tuple(x.T)\",\n \"def unzip_all(input_file: pathlib.Path) -> Tuple[pathlib.Path, tempfile.TemporaryDirectory]:\\n output_temp_dir = tempfile.TemporaryDirectory()\\n output_path = pathlib.Path(output_temp_dir.name)\\n\\n extract_zip(input_file, output_path)\\n\\n return output_path, output_temp_dir\",\n \"def easy_unpack_my(elements):\\n try:\\n res = tuple(elements[i] for i in [0, 2, -2])\\n except IndexError:\\n res = 0\\n return res\",\n \"def recombine_zip(x):\\r\\n overlap_zip = {10118: 10001, 10119: 10001, 10120: 10001, 10121: 10001, 10122: 10001, 10123: 10001, 10041: 10004, 10275: 10004,\\r\\n 10043: 10005, 10081: 10005, 10203: 10005, 10259: 10005, 10260: 10005, 10265: 10005, 10270: 10005, 10271: 10005,\\r\\n 10286: 10005, 10278: 10007, 10279: 10007, 10047: 10010, 10158: 10016, 10165: 10017, 10166: 10017, 10167: 10017,\\r\\n 10168: 10017, 10169: 10017, 10170: 10017, 10171: 10017, 10172: 10017, 10173: 10017, 10174: 10017, 10175: 10017,\\r\\n 10176: 10017, 10177: 10017, 10178: 10017, 10097: 10019, 10103: 10019, 10104: 10019, 10105: 10019, 10106: 10019,\\r\\n 10107: 10019, 10111: 10019, 10020: 10019, 10112: 10019, 10162: 10021, 10055: 10022, 10151: 10022, 10152: 10022,\\r\\n 10153: 10022, 10154: 10022, 10155: 10022, 10096: 10036, 10110: 10036, 10196: 10036, 10045: 10038, 10080: 10048,\\r\\n 10285: 10281, 10069: 10023, 11451: 11433, 10115: 10027, 11109:11101}\\r\\n \\r\\n if x in overlap_zip.keys():\\r\\n return overlap_zip[x]\\r\\n if x in overlap_zip.values():\\r\\n return x\\r\\n else:\\r\\n return x\",\n \"def unflatten(x: List, y: List) -> List:\\n def func(cum, this):\\n x_crop, res = cum\\n return [\\n x_crop[len(this):], res + [x_crop[:len(this)]]\\n ]\\n\\n return functools.reduce(func, list(y), [list(x), []])[-1]\",\n \"def zip_with_singletons(*args):\\n return zip(*(arg if isinstance(arg, list) else itertools.repeat(arg) for arg in args))\",\n \"def longzip(a, b):\\n aiter = iter(a)\\n biter = iter(b)\\n try:\\n for item1 in aiter:\\n yield item1, next(biter)\\n except StopIteration:\\n for item1 in aiter:\\n yield item1, None\\n else:\\n for item2 in biter:\\n yield None, item2\",\n \"def unpack(self):\\n return list(itertools.chain(*[arg.unpack()\\n for arg in self.args\\n if isinstance(arg, _Unpackable)]))\",\n \"def decode_tuple2(as_bytes: typing.List[int]) -> tuple:\\n raise NotImplementedError()\",\n \"def pairwise(iterable):\\n a = iter(iterable)\\n return zip(a, a, a)\",\n \"def get_tuples(outputs) -> list:\\n return list(map(get_tuples_helper, outputs))\",\n \"def unzip(input_filename, extract_dir):\\n if not zipfile.is_zipfile(input_filename):\\n raise ValueError(\\\"%s is not a zip file\\\" % (input_filename))\\n zip_ds = zipfile.ZipFile(input_filename)\\n zip_ds.extractall(path=extract_dir)\\n zip_ds.close()\",\n \"def split_in_pairs(arg: Iterable) -> Iterable[Tuple]:\\n # We are using zip_longest with one clever hack:\\n # https://docs.python.org/3/library/itertools.html#itertools.zip_longest\\n # We create an iterator out of the list and then pass the same iterator to\\n # the function two times. Thus the function consumes a different element\\n # from the iterator each time and produces the desired result.\\n iterator = iter(arg)\\n return zip_longest(iterator, iterator)\",\n \"def unzip(zip_path, output_file, data_folder):\\n\\n print('Unzipping file: {}'.format(zip_path))\\n pyunpack.Archive(zip_path).extractall(data_folder)\\n\\n # Checks if unzip was successful\\n if not os.path.exists(output_file):\\n raise ValueError(\\n 'Error in unzipping process! {} not found.'.format(output_file))\",\n \"def unzip(zip_path, cleanup=False):\\n zfile = zipfile.ZipFile(zip_path, 'r')\\n zfile.extractall(os.path.dirname(zip_path))\\n zfile.close()\\n if cleanup:\\n os.remove(zip_path)\",\n \"def pairwise(iterable):\\n a = iter(iterable)\\n return zip(a, a)\",\n \"def ex_list(data):\\n return tuple(data)\",\n \"def pairwise(iterable: Iterable,\\n tuple_size: int):\\n return zip_longest(*(islice(it, pos, None) for pos, it in enumerate(tee(iterable, tuple_size))))\",\n \"def unzipArchives(zip_file, password):\\n with ZipFile(zip_file) as archive:\\n archive.extractall(pwd=bytes(password, \\\"utf8\\\"))\",\n \"def tups(self, args=None, lo=None, hi=None, reverse=None, max=None,\\n include=False, txn=None):\\n return itertools.imap(ITEMGETTER_0,\\n self.pairs(args, lo, hi, reverse, max, include, txn))\",\n \"def decode_tuple3(as_bytes: typing.List[int]) -> tuple:\\n raise NotImplementedError()\",\n \"def tuple_from_sequence(*args):\\n return tuple(args)\",\n \"def main():\\n list1 = ListNode(1)\\n list1.next = ListNode(3)\\n list1.next.next = ListNode(5)\\n\\n list2 = ListNode(2)\\n list2.next = ListNode(4)\\n list2.next.next = ListNode(6)\\n\\n result = zipper(list1,list2)\\n print(result)\",\n \"def tupleofwords_to_wordoftuples(tupleofwords):\\n return list(zip_longest(*tupleofwords, fillvalue=None))\",\n \"def stagger_tuple(elements_list, initial=None):\\n res = []\\n previous_element = initial\\n for element in elements_list:\\n if previous_element is not None:\\n res.append((previous_element, element))\\n previous_element = element\\n return res\",\n \"def unzip_file(data_zip, path_unzip):\\r\\n with zipfile.ZipFile(data_zip, \\\"r\\\") as zip_temp:\\r\\n zip_temp.extractall(path_unzip)\",\n \"def deltas(L):\\n return map(sub, tuple(L)[1:], L)\",\n \"def pairwise(iterable):\\n a, b = itertools.tee(iterable)\\n next(b, None)\\n return list(zip(a, b))\",\n \"def pairwise(iterable):\\n a, b = itertools.tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = itertools.tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = itertools.tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = tee(iterable)\\n next(b, None)\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = tee(iterable)\\n next(b, None)\\n\\n return zip(a, b)\",\n \"def pairwise(iterable):\\n a, b = tee(iterable)\\n next(b, None)\\n\\n return zip(a, b)\",\n \"def transpose_list_of_lists(lol):\\n assert lol, \\\"cannot pass the empty list\\\"\\n return [list(x) for x in zip(*lol)]\",\n \"def __fix_tuple(self, xy_tup):\\n if self.__swapxy:\\n return xy_tup[::-1]\\n return xy_tup\",\n \"def transpose_lists(lists):\\n return list(map(list, zip(*lists)))\",\n \"def transpose(seqseq):\\n return zip(*seqseq)\",\n \"def strip_tuple(tuple_list, tuple_index = 0):\\n elem_list = []\\n for i in range(0, len(tuple_list)):\\n elem_list.append(tuple_list[i][tuple_index])\\n return elem_list\",\n \"def test_unstack():\\n x = np.arange(1, 13).reshape((3, 2, 2)).astype(np.int32)\\n axis = 0\\n x_tensor = paddle.to_tensor(x)\\n out_list = paddle.unstack(x_tensor, axis=axis)\\n length = len(out_list)\\n for i in range(length):\\n ept = x[i, :, :]\\n npt.assert_allclose(out_list[i].numpy(), ept)\",\n \"def from_zip(cls, *args, **kwargs):\\n return cls().add_zip(*args, **kwargs)\",\n \"def _repack(linear, n=3):\\n return list(zip(*[iter(linear)] * n))\",\n \"def pairwise(iterable):\\n a, b = itertools.tee(iterable)\\n next(b, None)\\n return itertools.zip_longest(a, b)\",\n \"def _create_zip(*iterables, fillvalue=None, type_longest=False):\\n\\n if type_longest:\\n from itertools import zip_longest\\n\\n zipped = zip_longest(*iterables, fillvalue=fillvalue)\\n else:\\n zipped = zip(*iterables)\\n return zipped\",\n \"def tuple_merge(tuples):\\n\\n\\t# Add your code here\\n\\treturn\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.75591034","0.6889838","0.68766","0.6743751","0.6709593","0.6456803","0.63671273","0.62731713","0.6267873","0.6260321","0.6234096","0.6152076","0.60384727","0.60337454","0.5970998","0.5970998","0.5949191","0.5846596","0.5812543","0.5775136","0.57129973","0.5703603","0.5631889","0.54450405","0.53926265","0.5385803","0.53790486","0.53475875","0.532716","0.5304803","0.5291875","0.52747","0.52736187","0.52134246","0.5198242","0.5171108","0.5132063","0.5128878","0.5123484","0.5123142","0.5113596","0.5082205","0.5082205","0.50769734","0.5067046","0.50594294","0.504425","0.5029327","0.5020068","0.5015257","0.50032467","0.4975148","0.4971246","0.49608222","0.4956394","0.4951698","0.4951131","0.49377754","0.49310112","0.48931536","0.48918733","0.48906034","0.4885972","0.48781726","0.48732463","0.48717558","0.4859538","0.4849778","0.48431876","0.48382032","0.48318073","0.4830778","0.48300025","0.4827234","0.48248515","0.48177195","0.4808547","0.48085186","0.48068586","0.48063964","0.47929338","0.47929338","0.47929338","0.47831923","0.47831923","0.47831923","0.47831923","0.47703186","0.47703186","0.4763168","0.47569236","0.47543854","0.47542846","0.47515187","0.47500414","0.47491306","0.47465616","0.47442567","0.4743497","0.4743248"],"string":"[\n \"0.75591034\",\n \"0.6889838\",\n \"0.68766\",\n \"0.6743751\",\n \"0.6709593\",\n \"0.6456803\",\n \"0.63671273\",\n \"0.62731713\",\n \"0.6267873\",\n \"0.6260321\",\n \"0.6234096\",\n \"0.6152076\",\n \"0.60384727\",\n \"0.60337454\",\n \"0.5970998\",\n \"0.5970998\",\n \"0.5949191\",\n \"0.5846596\",\n \"0.5812543\",\n \"0.5775136\",\n \"0.57129973\",\n \"0.5703603\",\n \"0.5631889\",\n \"0.54450405\",\n \"0.53926265\",\n \"0.5385803\",\n \"0.53790486\",\n \"0.53475875\",\n \"0.532716\",\n \"0.5304803\",\n \"0.5291875\",\n \"0.52747\",\n \"0.52736187\",\n \"0.52134246\",\n \"0.5198242\",\n \"0.5171108\",\n \"0.5132063\",\n \"0.5128878\",\n \"0.5123484\",\n \"0.5123142\",\n \"0.5113596\",\n \"0.5082205\",\n \"0.5082205\",\n \"0.50769734\",\n \"0.5067046\",\n \"0.50594294\",\n \"0.504425\",\n \"0.5029327\",\n \"0.5020068\",\n \"0.5015257\",\n \"0.50032467\",\n \"0.4975148\",\n \"0.4971246\",\n \"0.49608222\",\n \"0.4956394\",\n \"0.4951698\",\n \"0.4951131\",\n \"0.49377754\",\n \"0.49310112\",\n \"0.48931536\",\n \"0.48918733\",\n \"0.48906034\",\n \"0.4885972\",\n \"0.48781726\",\n \"0.48732463\",\n \"0.48717558\",\n \"0.4859538\",\n \"0.4849778\",\n \"0.48431876\",\n \"0.48382032\",\n \"0.48318073\",\n \"0.4830778\",\n \"0.48300025\",\n \"0.4827234\",\n \"0.48248515\",\n \"0.48177195\",\n \"0.4808547\",\n \"0.48085186\",\n \"0.48068586\",\n \"0.48063964\",\n \"0.47929338\",\n \"0.47929338\",\n \"0.47929338\",\n \"0.47831923\",\n \"0.47831923\",\n \"0.47831923\",\n \"0.47831923\",\n \"0.47703186\",\n \"0.47703186\",\n \"0.4763168\",\n \"0.47569236\",\n \"0.47543854\",\n \"0.47542846\",\n \"0.47515187\",\n \"0.47500414\",\n \"0.47491306\",\n \"0.47465616\",\n \"0.47442567\",\n \"0.4743497\",\n \"0.4743248\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.79986495"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13077,"cells":{"query":{"kind":"string","value":"returns teh version of the passed object"},"document":{"kind":"string","value":"def get_revision_of_object(obj):\n return getattr(obj, get_version_fieldname(obj))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_object ( self, object ):\n return object","def get(self, obj):","def obj(self) -> object:\n pass","def object(self):","def __invert__(self):\n return self.obj","def get(self, obj):\n raise NotImplementedError","def serialize(self, obj):\n return obj","def to_base(self, obj):\n if hasattr(obj, \"to_base\"):\n return obj.to_base()\n return obj","def obj(self):\r\n return self._obj","def object_for(objectid):","def restore(self, obj):\n return obj","def obj(self):\n return self._obj","def _object2string(self,param_name,obj,replace=True):\n self.debug(\"object2string(%s,%s)\"%(param_name,obj))\n translator = self.translators[param_name]\n\n if not replace:\n translator=copy.copy(translator)\n\n return translator.object2string(obj)","def obj(self):\n if not self._obj:\n self._get()\n return self._obj","def get_object(id):","def transform_one(self, obj: Any):\n return obj","def __call__(obj):","def object_hook(self, obj: Any) -> Any:\n if '__type__' in obj:\n if obj['__type__'] == 'complex':\n val = obj['__value__']\n return val[0] + 1j * val[1]\n if obj['__type__'] == 'array':\n return np.array(obj['__value__'])\n if obj['__type__'] == 'result':\n return Result.from_dict(obj['__value__'])\n if obj['__type__'] == 'to_json':\n return obj['__value__']\n if obj['__type__'] == 'dill':\n decoded = base64.standard_b64decode(obj['__value__'])\n return dill.loads(decoded)\n return obj","def __self__(self):\n if self._ob is not None:\n return self._ob()","def orig_obj(self):\n return self._orig_obj","def orig_obj(self):\n return self._orig_obj","def orig_obj(self):\n return self._orig_obj","def _from_other(cls, obj):","def default(self, obj):\r\n if hasattr(obj, 'to_python'):\r\n return obj.to_python()\r\n return super(CLIJSONEncoder, self).default(obj)","def get_result(self, obj):\n return str(obj)","def get_result(self, obj):\n return str(obj)","def build(self, obj):\n if isinstance(obj, self.art_type):\n return obj\n elif isinstance(obj, (tuple, list, dict, set)):\n if obj.__class__ is tuple:\n return self.build_tuple(obj)\n elif obj.__class__ is dict:\n return self.build_dict(obj)\n elif obj.__class__ is list:\n return self.build_list(obj)\n else:\n return self.build_set(obj)\n elif isinstance(obj, SageObject):\n return self.build_from_magic_method(obj)\n else:\n return self.build_from_string(obj)","def get(self, obj, default):\n pass","def default(self, obj): # pylint: disable=method-hidden\n if isinstance(obj, (ArmCalcInput, ArmCalcOutput)):\n return obj.__dict__\n elif isinstance(obj, (datetime, date)):\n return to_wcf_date(obj)\n return super(ArmCalcJsonEncoder, self).default(obj)","def __get__(self, obj, objtype=None):\n print('Hello from __get__')\n # print(self, obj, objtype)\n # print(type(self), type(obj), type(objtype))\n return self.val","def Value(self) -> object:","def Value(self) -> object:","def id(obj):\n return obj","def to_legacy(self) -> object:\n pass","def get(cls, obj: Model):\n return cache.get(cls._construct_key(obj))","def identity( self, obj ):\n raise NotImplementedError(\"identity\")","def get_representative_data_object(self, obj):\n if self.dim == 0:\n # In this way, obj can be a data object and this class can be\n # used even if the assignment is not between \"flattened components\"\n return obj\n else:\n nominal_index = self.nominal_index\n return obj[nominal_index]","def __itruediv__(self, obj):\n # calls __truediv__\n tmp = self / obj\n self.data = tmp.data\n return self","def __get__(self, obj, cls):\n if obj is None:\n return self\n\n value = self.fget(obj)\n setattr(obj, self.fget.__name__, value)\n return value","def get(self, objectclass, **kwargs):\n raise NotImplementedError","def default(self, o):\n return o.__dict__","def copy(obj):\n return loads(dumps(obj))","def get_object(self, pool_name, object_name):\n return self.get_object_and_version(pool_name, object_name)[0]","def getObject(self):\n return self.base.get(\"object\", [])","def GetDataAsObject(self):","def format(self, obj):\n pass","def format(self, obj):\n pass","def serialize_forstorage(cls, obj):\n return misc.serialize_forstorage(obj)","def __int__(self):\n return int(self.obj)","def __get__(self, obj, objtype=None):\n try:\n return getattr(obj, self.cache_attr)\n except AttributeError:\n # Call the wrapped function with the obj instance as argument\n setattr(obj, self.cache_attr, self.fget(obj))\n return getattr(obj, self.cache_attr)","def getObjByPath(self, path):\n return getObjByPath(self, path)","def get(self, obj):\n obj = self._to_obj_tuple(obj)\n rows = self.query(object=obj)\n if rows:\n return rows[0]","def getZopeObj(self, path):\n return self.getObjByPath(path)","def get_object(self, id, **args):\n return self.request(id, args)","def serialize(self, obj):\n pass","def _get_instance(self):","def _get_instance(self):","def _get_py_obj(self, ctx, obj, route=[]):\n def access(obj, key):\n if key in obj:\n return obj[key]\n return None\n\n cloned = None\n if isinstance(obj, (list, tuple, PyV8.JSArray)):\n cloned = []\n num_elements = len(obj)\n for index in range(num_elements):\n elem = obj[index]\n cloned.append(self._get_py_obj(ctx, elem, route + [index]))\n elif isinstance(obj, (dict, PyV8.JSObject)):\n cloned = {}\n for key in obj.keys():\n cloned_val = None\n if type(key) == int:\n val = None\n try:\n val = access(obj, str(key))\n except KeyError:\n pass\n if val is None:\n val = access(obj, key)\n cloned_val = self._get_py_obj(ctx, val, route + [key])\n else:\n cloned_val = self._get_py_obj(\n ctx, access(obj, key), route + [key])\n cloned[key] = cloned_val\n elif isinstance(obj, (str, bytes)):\n cloned = obj.decode('utf-8')\n else:\n cloned = obj\n return cloned","def default(self, obj):\n \n if isinstance(obj, np.ndarray):\n return list(obj)\n\n if isinstance(obj, uuid.UUID):\n return str(obj)\n\n if isinstance(obj, datetime.datetime):\n return obj.isoformat()\n \n if isinstance(obj,TPC):\n return obj._so()\n \n # No special handling called for; pass through\n return json.JSONEncoder.default(self, obj)","def get_object(self):\n return self._object","def do(self, obj):\n if isinstance(obj, str):\n return 'st__' + obj\n\n if type(obj) in literals:\n return obj\n\n # Now check for list, set, and tuple, and skip if they don't contain\n # any non-literals\n if type(obj) in builtin_iterables:\n if all(isinstance(x, literals) for x in flattened(obj)):\n return as_nested_lists(obj)\n\n oid = id(obj)\n if oid in self._working:\n raise GlueSerializeError(\"Circular reference detected\")\n self._working.add(oid)\n\n fun, version = self._dispatch(obj)\n logging.debug(\"Serializing %s with %s\", obj, fun)\n result = fun(obj, self)\n\n if isinstance(obj, types.FunctionType):\n result['_type'] = 'types.FunctionType'\n elif isinstance(obj, types.MethodType):\n result['_type'] = 'types.MethodType'\n else:\n result['_type'] = \"%s.%s\" % (type(obj).__module__,\n type(obj).__name__)\n if version > 1:\n result['_protocol'] = version\n\n self._working.remove(oid)\n return result","def get_object(self):\n if getattr(self, 'current_instance', None):\n ret = self.current_instance\n else:\n ret = super().get_object()\n return ret","def __str__(self):\n return str(self.obj)","def _finishConstruction(self, obj):\n return obj","def _finishConstruction(self, obj):\n return obj","def __call__(self):\n return self.referee()","def lookup_obj(self,):\n return self._lookup_obj","def get_raw_value ( self, object ):\n try:\n return xgetattr( self.get_object( object ), self.name )\n except:\n return None","def fobj(self):\n return self._fobj","def simplify(self, obj):\n\n result = self.process_object(obj, False)\n return result","def intern(self, obj):\n try:\n return self._cache[obj]\n except KeyError:\n self._cache[obj] = obj\n return obj","def get_object(self, id, **args):\n return self.request(\"{0}/{1}\".format(self.version, id), args)","def __getattribute__(self, name):\n return object.__getattribute__(object.__getattribute__(self, 'orig'),\n name)","def default(self, o):\n try:\n return o.as_dict()\n except Exception:\n pass\n\n try:\n return o.__dict__\n except Exception:\n pass\n\n try:\n return str(o)\n except Exception:\n pass\n\n return None","def default(self, obj):\n\n if hasattr(obj, 'to_dict'):\n return getattr(obj, 'to_dict')()\n\n if isinstance(obj, query.Query):\n return list(obj)\n\n elif isinstance(obj, datetime.datetime):\n return obj.isoformat()\n\n elif isinstance(obj, time.struct_time):\n return list(obj)\n\n elif isinstance(obj, users.User):\n output = {}\n methods = ['nickname', 'email', 'auth_domain']\n for method in methods:\n output[method] = getattr(obj, method)()\n return output\n\n elif isinstance(obj, model.Key):\n return obj.get()\n\n return simplejson.JSONEncoder.default(self, obj)","def get_o(self):\n return self.o","def rv(self, **kw):\n return rv(self, **kw)","def object(self):\n return self._object","def getObjectGuard(o):\n\n # XXX haha what\n return anyGuard","def _retrieve_object(obj: Union[\"Base\", str], method: Callable) -> Union[\"Base\"]:\n # Check whether the part_model is uuid type or class `Part`\n from pykechain.models import Part, Property, Service, Team\n\n if isinstance(obj, (Part, Property, Service, Team)):\n return obj\n elif isinstance(obj, str) and is_uuid(obj):\n obj_id = obj\n obj = method(id=obj_id)\n return obj\n else:\n raise IllegalArgumentError(\n \"When adding the widget, obj must be a Part, Property, Service, Team, \"\n \" Part id, Property id, Service id or Team id. Type is: {}\".format(\n type(obj)\n )\n )","def __current_object__(self):\n return self.__lookup()","def Item(self) -> object:","def Item(self) -> object:","def copy_value(obj):\n c = obj.GetDynamicValue(obj.GetPreferDynamicValue())\n return c","def get_obj(self):\n assert self._obj is not None, \"Object XML tree has not been generated yet!\"\n return self._obj","def updated_object(self):\n o = deepcopy(self.object)\n o[\"name\"] += \"-copy\"\n return o","def __str__(self):\n return str(self.__dict__['_obj'])","def _get(self, name):\n return object.__getattribute__(self, name)","def _get(self, name):\n return object.__getattribute__(self, name)","def make_object():\n return object()","def get_obj(self, idx):\n if idx >= self.object_dataset.get_nb_obj():\n raise ValueError(\"idx is greater than the number of objects\")\n return self.object_dataset.get_obj(idx)","def jsonDefault(object):\n return object.__dict__","def mos_object(self):\n return self._restore_fn(*self._restore_args)","def __call__(object):","def get_for_object(self, content_object, **kwargs):\r\n return self.get(**self._generate_object_kwarg_dict(content_object, **kwargs))","def get_object(self, id=None):\n if id is None and self.kwargs.get('field') == 'id':\n id = self.kwargs.get('constraint')\n self.object = self.get_model_obj().objects.get(pk=id)\n return self.object","def getObject(language=None):","def processObject(self, x):\n pickled = self.objToPickle(x)\n if pickled:\n return pickled\n return self.objToFQN(x)","def __getattr__(self, name):\n self.assert_valid()\n\n value = _swig_getattr(self, self.__class__, name)\n\n # If we got back a different object than we have, we need to copy all our\n # metadata into it, so that it looks identical\n members = self.__dict__.get(\"_members\")\n if members is not None:\n _copy_metadata_deep(value, members.get(name))\n\n # Verify that the new object is good\n _assert_valid_deep(value)\n\n return value","def __getattr__(self, name):\n self.assert_valid()\n\n value = _swig_getattr(self, self.__class__, name)\n\n # If we got back a different object than we have, we need to copy all our\n # metadata into it, so that it looks identical\n members = self.__dict__.get(\"_members\")\n if members is not None:\n _copy_metadata_deep(value, members.get(name))\n\n # Verify that the new object is good\n _assert_valid_deep(value)\n\n return value"],"string":"[\n \"def get_object ( self, object ):\\n return object\",\n \"def get(self, obj):\",\n \"def obj(self) -> object:\\n pass\",\n \"def object(self):\",\n \"def __invert__(self):\\n return self.obj\",\n \"def get(self, obj):\\n raise NotImplementedError\",\n \"def serialize(self, obj):\\n return obj\",\n \"def to_base(self, obj):\\n if hasattr(obj, \\\"to_base\\\"):\\n return obj.to_base()\\n return obj\",\n \"def obj(self):\\r\\n return self._obj\",\n \"def object_for(objectid):\",\n \"def restore(self, obj):\\n return obj\",\n \"def obj(self):\\n return self._obj\",\n \"def _object2string(self,param_name,obj,replace=True):\\n self.debug(\\\"object2string(%s,%s)\\\"%(param_name,obj))\\n translator = self.translators[param_name]\\n\\n if not replace:\\n translator=copy.copy(translator)\\n\\n return translator.object2string(obj)\",\n \"def obj(self):\\n if not self._obj:\\n self._get()\\n return self._obj\",\n \"def get_object(id):\",\n \"def transform_one(self, obj: Any):\\n return obj\",\n \"def __call__(obj):\",\n \"def object_hook(self, obj: Any) -> Any:\\n if '__type__' in obj:\\n if obj['__type__'] == 'complex':\\n val = obj['__value__']\\n return val[0] + 1j * val[1]\\n if obj['__type__'] == 'array':\\n return np.array(obj['__value__'])\\n if obj['__type__'] == 'result':\\n return Result.from_dict(obj['__value__'])\\n if obj['__type__'] == 'to_json':\\n return obj['__value__']\\n if obj['__type__'] == 'dill':\\n decoded = base64.standard_b64decode(obj['__value__'])\\n return dill.loads(decoded)\\n return obj\",\n \"def __self__(self):\\n if self._ob is not None:\\n return self._ob()\",\n \"def orig_obj(self):\\n return self._orig_obj\",\n \"def orig_obj(self):\\n return self._orig_obj\",\n \"def orig_obj(self):\\n return self._orig_obj\",\n \"def _from_other(cls, obj):\",\n \"def default(self, obj):\\r\\n if hasattr(obj, 'to_python'):\\r\\n return obj.to_python()\\r\\n return super(CLIJSONEncoder, self).default(obj)\",\n \"def get_result(self, obj):\\n return str(obj)\",\n \"def get_result(self, obj):\\n return str(obj)\",\n \"def build(self, obj):\\n if isinstance(obj, self.art_type):\\n return obj\\n elif isinstance(obj, (tuple, list, dict, set)):\\n if obj.__class__ is tuple:\\n return self.build_tuple(obj)\\n elif obj.__class__ is dict:\\n return self.build_dict(obj)\\n elif obj.__class__ is list:\\n return self.build_list(obj)\\n else:\\n return self.build_set(obj)\\n elif isinstance(obj, SageObject):\\n return self.build_from_magic_method(obj)\\n else:\\n return self.build_from_string(obj)\",\n \"def get(self, obj, default):\\n pass\",\n \"def default(self, obj): # pylint: disable=method-hidden\\n if isinstance(obj, (ArmCalcInput, ArmCalcOutput)):\\n return obj.__dict__\\n elif isinstance(obj, (datetime, date)):\\n return to_wcf_date(obj)\\n return super(ArmCalcJsonEncoder, self).default(obj)\",\n \"def __get__(self, obj, objtype=None):\\n print('Hello from __get__')\\n # print(self, obj, objtype)\\n # print(type(self), type(obj), type(objtype))\\n return self.val\",\n \"def Value(self) -> object:\",\n \"def Value(self) -> object:\",\n \"def id(obj):\\n return obj\",\n \"def to_legacy(self) -> object:\\n pass\",\n \"def get(cls, obj: Model):\\n return cache.get(cls._construct_key(obj))\",\n \"def identity( self, obj ):\\n raise NotImplementedError(\\\"identity\\\")\",\n \"def get_representative_data_object(self, obj):\\n if self.dim == 0:\\n # In this way, obj can be a data object and this class can be\\n # used even if the assignment is not between \\\"flattened components\\\"\\n return obj\\n else:\\n nominal_index = self.nominal_index\\n return obj[nominal_index]\",\n \"def __itruediv__(self, obj):\\n # calls __truediv__\\n tmp = self / obj\\n self.data = tmp.data\\n return self\",\n \"def __get__(self, obj, cls):\\n if obj is None:\\n return self\\n\\n value = self.fget(obj)\\n setattr(obj, self.fget.__name__, value)\\n return value\",\n \"def get(self, objectclass, **kwargs):\\n raise NotImplementedError\",\n \"def default(self, o):\\n return o.__dict__\",\n \"def copy(obj):\\n return loads(dumps(obj))\",\n \"def get_object(self, pool_name, object_name):\\n return self.get_object_and_version(pool_name, object_name)[0]\",\n \"def getObject(self):\\n return self.base.get(\\\"object\\\", [])\",\n \"def GetDataAsObject(self):\",\n \"def format(self, obj):\\n pass\",\n \"def format(self, obj):\\n pass\",\n \"def serialize_forstorage(cls, obj):\\n return misc.serialize_forstorage(obj)\",\n \"def __int__(self):\\n return int(self.obj)\",\n \"def __get__(self, obj, objtype=None):\\n try:\\n return getattr(obj, self.cache_attr)\\n except AttributeError:\\n # Call the wrapped function with the obj instance as argument\\n setattr(obj, self.cache_attr, self.fget(obj))\\n return getattr(obj, self.cache_attr)\",\n \"def getObjByPath(self, path):\\n return getObjByPath(self, path)\",\n \"def get(self, obj):\\n obj = self._to_obj_tuple(obj)\\n rows = self.query(object=obj)\\n if rows:\\n return rows[0]\",\n \"def getZopeObj(self, path):\\n return self.getObjByPath(path)\",\n \"def get_object(self, id, **args):\\n return self.request(id, args)\",\n \"def serialize(self, obj):\\n pass\",\n \"def _get_instance(self):\",\n \"def _get_instance(self):\",\n \"def _get_py_obj(self, ctx, obj, route=[]):\\n def access(obj, key):\\n if key in obj:\\n return obj[key]\\n return None\\n\\n cloned = None\\n if isinstance(obj, (list, tuple, PyV8.JSArray)):\\n cloned = []\\n num_elements = len(obj)\\n for index in range(num_elements):\\n elem = obj[index]\\n cloned.append(self._get_py_obj(ctx, elem, route + [index]))\\n elif isinstance(obj, (dict, PyV8.JSObject)):\\n cloned = {}\\n for key in obj.keys():\\n cloned_val = None\\n if type(key) == int:\\n val = None\\n try:\\n val = access(obj, str(key))\\n except KeyError:\\n pass\\n if val is None:\\n val = access(obj, key)\\n cloned_val = self._get_py_obj(ctx, val, route + [key])\\n else:\\n cloned_val = self._get_py_obj(\\n ctx, access(obj, key), route + [key])\\n cloned[key] = cloned_val\\n elif isinstance(obj, (str, bytes)):\\n cloned = obj.decode('utf-8')\\n else:\\n cloned = obj\\n return cloned\",\n \"def default(self, obj):\\n \\n if isinstance(obj, np.ndarray):\\n return list(obj)\\n\\n if isinstance(obj, uuid.UUID):\\n return str(obj)\\n\\n if isinstance(obj, datetime.datetime):\\n return obj.isoformat()\\n \\n if isinstance(obj,TPC):\\n return obj._so()\\n \\n # No special handling called for; pass through\\n return json.JSONEncoder.default(self, obj)\",\n \"def get_object(self):\\n return self._object\",\n \"def do(self, obj):\\n if isinstance(obj, str):\\n return 'st__' + obj\\n\\n if type(obj) in literals:\\n return obj\\n\\n # Now check for list, set, and tuple, and skip if they don't contain\\n # any non-literals\\n if type(obj) in builtin_iterables:\\n if all(isinstance(x, literals) for x in flattened(obj)):\\n return as_nested_lists(obj)\\n\\n oid = id(obj)\\n if oid in self._working:\\n raise GlueSerializeError(\\\"Circular reference detected\\\")\\n self._working.add(oid)\\n\\n fun, version = self._dispatch(obj)\\n logging.debug(\\\"Serializing %s with %s\\\", obj, fun)\\n result = fun(obj, self)\\n\\n if isinstance(obj, types.FunctionType):\\n result['_type'] = 'types.FunctionType'\\n elif isinstance(obj, types.MethodType):\\n result['_type'] = 'types.MethodType'\\n else:\\n result['_type'] = \\\"%s.%s\\\" % (type(obj).__module__,\\n type(obj).__name__)\\n if version > 1:\\n result['_protocol'] = version\\n\\n self._working.remove(oid)\\n return result\",\n \"def get_object(self):\\n if getattr(self, 'current_instance', None):\\n ret = self.current_instance\\n else:\\n ret = super().get_object()\\n return ret\",\n \"def __str__(self):\\n return str(self.obj)\",\n \"def _finishConstruction(self, obj):\\n return obj\",\n \"def _finishConstruction(self, obj):\\n return obj\",\n \"def __call__(self):\\n return self.referee()\",\n \"def lookup_obj(self,):\\n return self._lookup_obj\",\n \"def get_raw_value ( self, object ):\\n try:\\n return xgetattr( self.get_object( object ), self.name )\\n except:\\n return None\",\n \"def fobj(self):\\n return self._fobj\",\n \"def simplify(self, obj):\\n\\n result = self.process_object(obj, False)\\n return result\",\n \"def intern(self, obj):\\n try:\\n return self._cache[obj]\\n except KeyError:\\n self._cache[obj] = obj\\n return obj\",\n \"def get_object(self, id, **args):\\n return self.request(\\\"{0}/{1}\\\".format(self.version, id), args)\",\n \"def __getattribute__(self, name):\\n return object.__getattribute__(object.__getattribute__(self, 'orig'),\\n name)\",\n \"def default(self, o):\\n try:\\n return o.as_dict()\\n except Exception:\\n pass\\n\\n try:\\n return o.__dict__\\n except Exception:\\n pass\\n\\n try:\\n return str(o)\\n except Exception:\\n pass\\n\\n return None\",\n \"def default(self, obj):\\n\\n if hasattr(obj, 'to_dict'):\\n return getattr(obj, 'to_dict')()\\n\\n if isinstance(obj, query.Query):\\n return list(obj)\\n\\n elif isinstance(obj, datetime.datetime):\\n return obj.isoformat()\\n\\n elif isinstance(obj, time.struct_time):\\n return list(obj)\\n\\n elif isinstance(obj, users.User):\\n output = {}\\n methods = ['nickname', 'email', 'auth_domain']\\n for method in methods:\\n output[method] = getattr(obj, method)()\\n return output\\n\\n elif isinstance(obj, model.Key):\\n return obj.get()\\n\\n return simplejson.JSONEncoder.default(self, obj)\",\n \"def get_o(self):\\n return self.o\",\n \"def rv(self, **kw):\\n return rv(self, **kw)\",\n \"def object(self):\\n return self._object\",\n \"def getObjectGuard(o):\\n\\n # XXX haha what\\n return anyGuard\",\n \"def _retrieve_object(obj: Union[\\\"Base\\\", str], method: Callable) -> Union[\\\"Base\\\"]:\\n # Check whether the part_model is uuid type or class `Part`\\n from pykechain.models import Part, Property, Service, Team\\n\\n if isinstance(obj, (Part, Property, Service, Team)):\\n return obj\\n elif isinstance(obj, str) and is_uuid(obj):\\n obj_id = obj\\n obj = method(id=obj_id)\\n return obj\\n else:\\n raise IllegalArgumentError(\\n \\\"When adding the widget, obj must be a Part, Property, Service, Team, \\\"\\n \\\" Part id, Property id, Service id or Team id. Type is: {}\\\".format(\\n type(obj)\\n )\\n )\",\n \"def __current_object__(self):\\n return self.__lookup()\",\n \"def Item(self) -> object:\",\n \"def Item(self) -> object:\",\n \"def copy_value(obj):\\n c = obj.GetDynamicValue(obj.GetPreferDynamicValue())\\n return c\",\n \"def get_obj(self):\\n assert self._obj is not None, \\\"Object XML tree has not been generated yet!\\\"\\n return self._obj\",\n \"def updated_object(self):\\n o = deepcopy(self.object)\\n o[\\\"name\\\"] += \\\"-copy\\\"\\n return o\",\n \"def __str__(self):\\n return str(self.__dict__['_obj'])\",\n \"def _get(self, name):\\n return object.__getattribute__(self, name)\",\n \"def _get(self, name):\\n return object.__getattribute__(self, name)\",\n \"def make_object():\\n return object()\",\n \"def get_obj(self, idx):\\n if idx >= self.object_dataset.get_nb_obj():\\n raise ValueError(\\\"idx is greater than the number of objects\\\")\\n return self.object_dataset.get_obj(idx)\",\n \"def jsonDefault(object):\\n return object.__dict__\",\n \"def mos_object(self):\\n return self._restore_fn(*self._restore_args)\",\n \"def __call__(object):\",\n \"def get_for_object(self, content_object, **kwargs):\\r\\n return self.get(**self._generate_object_kwarg_dict(content_object, **kwargs))\",\n \"def get_object(self, id=None):\\n if id is None and self.kwargs.get('field') == 'id':\\n id = self.kwargs.get('constraint')\\n self.object = self.get_model_obj().objects.get(pk=id)\\n return self.object\",\n \"def getObject(language=None):\",\n \"def processObject(self, x):\\n pickled = self.objToPickle(x)\\n if pickled:\\n return pickled\\n return self.objToFQN(x)\",\n \"def __getattr__(self, name):\\n self.assert_valid()\\n\\n value = _swig_getattr(self, self.__class__, name)\\n\\n # If we got back a different object than we have, we need to copy all our\\n # metadata into it, so that it looks identical\\n members = self.__dict__.get(\\\"_members\\\")\\n if members is not None:\\n _copy_metadata_deep(value, members.get(name))\\n\\n # Verify that the new object is good\\n _assert_valid_deep(value)\\n\\n return value\",\n \"def __getattr__(self, name):\\n self.assert_valid()\\n\\n value = _swig_getattr(self, self.__class__, name)\\n\\n # If we got back a different object than we have, we need to copy all our\\n # metadata into it, so that it looks identical\\n members = self.__dict__.get(\\\"_members\\\")\\n if members is not None:\\n _copy_metadata_deep(value, members.get(name))\\n\\n # Verify that the new object is good\\n _assert_valid_deep(value)\\n\\n return value\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.70676875","0.7010541","0.6859093","0.68377954","0.6828108","0.66855097","0.662894","0.6485851","0.63837457","0.6309126","0.6275122","0.62676996","0.62326336","0.6201213","0.61918557","0.6187754","0.61847454","0.6175625","0.61751205","0.61347693","0.61347693","0.61347693","0.6112775","0.60842973","0.60826755","0.60826755","0.60592544","0.60532016","0.6031729","0.60188323","0.6004504","0.6004504","0.5969842","0.5964996","0.5945397","0.59391344","0.59169483","0.5861124","0.58314186","0.58312416","0.5820502","0.58092743","0.58048517","0.579337","0.5791004","0.57799107","0.57799107","0.5767823","0.5763721","0.57605314","0.57580924","0.5757915","0.5756091","0.57330084","0.57211804","0.57153314","0.57153314","0.5706981","0.57049614","0.5702177","0.57018334","0.5686194","0.5674248","0.56724966","0.56724966","0.56692976","0.5669074","0.56690174","0.56641114","0.56631917","0.56513035","0.56499195","0.563894","0.56321335","0.5627411","0.5618765","0.5614927","0.5614012","0.5602761","0.5598336","0.55968726","0.559072","0.559072","0.5583993","0.5575114","0.55749035","0.5568773","0.55677575","0.55677575","0.55665416","0.55577606","0.55552715","0.55437773","0.55318063","0.55290455","0.55129683","0.55051845","0.549932","0.54938984","0.54938984"],"string":"[\n \"0.70676875\",\n \"0.7010541\",\n \"0.6859093\",\n \"0.68377954\",\n \"0.6828108\",\n \"0.66855097\",\n \"0.662894\",\n \"0.6485851\",\n \"0.63837457\",\n \"0.6309126\",\n \"0.6275122\",\n \"0.62676996\",\n \"0.62326336\",\n \"0.6201213\",\n \"0.61918557\",\n \"0.6187754\",\n \"0.61847454\",\n \"0.6175625\",\n \"0.61751205\",\n \"0.61347693\",\n \"0.61347693\",\n \"0.61347693\",\n \"0.6112775\",\n \"0.60842973\",\n \"0.60826755\",\n \"0.60826755\",\n \"0.60592544\",\n \"0.60532016\",\n \"0.6031729\",\n \"0.60188323\",\n \"0.6004504\",\n \"0.6004504\",\n \"0.5969842\",\n \"0.5964996\",\n \"0.5945397\",\n \"0.59391344\",\n \"0.59169483\",\n \"0.5861124\",\n \"0.58314186\",\n \"0.58312416\",\n \"0.5820502\",\n \"0.58092743\",\n \"0.58048517\",\n \"0.579337\",\n \"0.5791004\",\n \"0.57799107\",\n \"0.57799107\",\n \"0.5767823\",\n \"0.5763721\",\n \"0.57605314\",\n \"0.57580924\",\n \"0.5757915\",\n \"0.5756091\",\n \"0.57330084\",\n \"0.57211804\",\n \"0.57153314\",\n \"0.57153314\",\n \"0.5706981\",\n \"0.57049614\",\n \"0.5702177\",\n \"0.57018334\",\n \"0.5686194\",\n \"0.5674248\",\n \"0.56724966\",\n \"0.56724966\",\n \"0.56692976\",\n \"0.5669074\",\n \"0.56690174\",\n \"0.56641114\",\n \"0.56631917\",\n \"0.56513035\",\n \"0.56499195\",\n \"0.563894\",\n \"0.56321335\",\n \"0.5627411\",\n \"0.5618765\",\n \"0.5614927\",\n \"0.5614012\",\n \"0.5602761\",\n \"0.5598336\",\n \"0.55968726\",\n \"0.559072\",\n \"0.559072\",\n \"0.5583993\",\n \"0.5575114\",\n \"0.55749035\",\n \"0.5568773\",\n \"0.55677575\",\n \"0.55677575\",\n \"0.55665416\",\n \"0.55577606\",\n \"0.55552715\",\n \"0.55437773\",\n \"0.55318063\",\n \"0.55290455\",\n \"0.55129683\",\n \"0.55051845\",\n \"0.549932\",\n \"0.54938984\",\n \"0.54938984\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.63562226"},"document_rank":{"kind":"string","value":"9"}}},{"rowIdx":13078,"cells":{"query":{"kind":"string","value":"returns True if `obj` is changed or deleted on the database"},"document":{"kind":"string","value":"def is_changed(obj):\n revision_field = get_version_fieldname(obj)\n version = get_revision_of_object(obj)\n return not obj.__class__.objects.filter(**{obj._meta.pk.name: obj.pk,\n revision_field: version}).exists()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def is_live(self, obj):\n most_appropriate_object = get_appropriate_object_from_model(self.model)\n if most_appropriate_object == obj:\n return True\n return False","def has_change_permission(self, request, obj=None):\n if obj is not None:\n return False\n return super().has_change_permission(request, obj)","def isModelDirty(self):\n \n pass","def exists(self, obj):\n return False","def hasChanged(self):\r\n if self.is_updated:\r\n self.is_updated = False\r\n return True\r\n else:\r\n return False\r\n\r\n # if not self.hasBeenUpdatedOnce:\r\n # self.hasBeenUpdatedOnce = True\r\n # return True\r\n # else:\r\n # if BLENDER_MODE == 'BPY':\r\n # # for e in dir(self.obj): print(e)\r\n # # print(self.obj, self.obj.name, self.obj.is_updated, self.obj.is_updated_data)\r\n # # return self.obj.is_updated # DOESN't UPDATE A THING!\r\n # # return True\r\n # return self.is_updated\r\n\r\n # return False # no update in BGE mode\r","def bool(self, obj):\n return True","def bool(self, obj):\n return True","def has_update_permissions(self, obj):\n return True","def has_object_permission(self, request, view, obj):\n if request.method == \"GET\":\n return self.model_admin_config.has_view_permission(self, request, obj=obj)\n if request.method == \"PUT\":\n return self.model_admin_config.has_change_permission(self, request, obj=obj)\n if request.method == \"DELETE\":\n return self.model_admin_config.has_delete_permission(self, request, obj=obj)","def _is_sqlalchemy_object(obj):\n # TODO: better way?\n return hasattr(obj, \"_sa_instance_state\")","def equals(self, obj: object) -> bool:\n ...","def update_if_not_modified(self, obj, fields, upsert=False):\n spec = state(obj).original_document\n self.update(obj.__class__, spec, fields, upsert=upsert)\n err = self.impl.db.command(dict(getlasterror=1))\n return bool(err['n'] and err['updatedExisting'])","def has_change_permission(self, request, obj=None):\n has_class_permission = super(EntryAdmin, self).has_change_permission(request, obj)\n if not has_class_permission:\n return False\n if obj is not None and not request.user.is_superuser and request.user.id != obj.author.id:\n return False\n return True","def is_editable(obj, request):\n if hasattr(obj, \"is_editable\"):\n return obj.is_editable(request)\n else:\n perm = obj._meta.app_label + \".\" + obj._meta.get_change_permission()\n return request.user.is_authenticated() and request.user.has_perm(perm)","def has_change_permission(self, request, obj=None):\n return False","def _changeable_fields(self, request, obj):\n return not obj or not self.is_readonly(request, obj)","def has_object_permission(self, request, view, obj):\n usuario_request = request.user\n usuario_a_modificar = obj\n\n return usuario_request != usuario_a_modificar","def _objectDeleted(self, obj):\n pass","def has_change_permission(self, request, obj=None) -> bool:\n permission = super().has_change_permission(request, obj)\n\n if obj is not None:\n permission &= (obj.owner == request.user) or request.user.is_superuser\n\n return permission","def isDirty(*args, connection: bool=True, datablock: bool=True, **kwargs)->bool:\n pass","def _can_update(self):\r\n if not self._is_persisted: return False\r\n pks = self._primary_keys.keys()\r\n return all([not self._values[k].changed for k in self._primary_keys])","def isDirty(self):\n\t#@DEBUG christophe have to fix denoising optionnal issue prior to set isDirty() to True\n return False","def has_object_permission(self, request, view, obj):\n if request.method in permissions.SAFE_METHODS:\n return True\n # When the user make a request It will check that is on Safe methods, so it return true if the user is \n # trying to update is own profile or return false. And also it will return the obj.id == request.user.id\n return obj.id == request.user.id","def is_dirty(self):\n return self.dirty","def is_dirty(self):\n return self.dirty","def is_deleted(self):\n if self.deleted:\n return True\n return False","def __contains__(self, obj):\n if isinstance(obj, self):\n query = self.where(**obj.data).select()\n result = query.execute()\n if result.count:\n return True\n return False","def changed(self):\n if self.exists():\n return self.current_content != self.content\n else:\n return True","def should_save(self):\n return self.modified","def isdirty(self):\n\n return not not self._olddata","def __bool__(self):\n return bool(self.obj)","def has_object_update_permission(self, request):\n user = request.user\n if self == user:\n return True\n return user.is_superuser","def exists(self):\n return self.obj is not None","def __is_hard_match(self, obj):\n for attr in self.list:\n try:\n if getattr(obj, attr) != getattr(self, attr):\n return False\n except AttributeError:\n pass\n return True","def has_change_permission(self, request, obj=None):\n\n if type(obj) is Client:\n return obj.is_user_in_main_sales_contacts_of_client(request.user)\n return False","def has_change_permission(self, request, obj=None):\n opts = self.opts\n codename = get_permission_codename('change', opts)\n return any([\n request.user.has_perm(\"%s.%s\" % (opts.app_label, codename)),\n request.user.has_perm(\"%s.%s\" % (opts.app_label, codename), obj)])","def has_changed(self):\n return bool(self.changed_data)","def has_object_permission(self, request, view, obj):\n\n return obj.active","def is_modified(self):\n return len(self.modified_fields) > 0","def delete(self):\n ret = False\n q = self.query\n pk = self.pk\n if pk:\n pk_name = self.schema.pk.name\n self.query.is_field(pk_name, pk).delete()\n setattr(self, pk_name, None)\n\n # mark all the fields that still exist as modified\n self.reset_modified()\n for field_name in self.schema.fields:\n if getattr(self, field_name, None) != None:\n self.modified_fields.add(field_name)\n\n ret = True\n\n return ret","def is_dirty(self):\n return self._is_dirty","def is_dirty(self):\n return self._is_dirty","def has_object_permission(self, request, view, obj):\n if request.user.is_superuser:\n return True\n if request.user.profile.role == UserRole.CLIENT and obj.owner != request.user:\n return False\n if request.user.profile.role == UserRole.EXECUTOR and obj.executor != request.user:\n return False\n return True","def has_change_permission(self, request, obj=None):\n has_perm = super(ShortURLAdmin, self).has_change_permission(request, obj)\n if not has_perm:\n return False\n if obj is not None and not request.user.has_perm('deflect.list_all') and request.user.id != obj.creator.id:\n return False\n return True","def has_object_permission(self, request, view, obj):\n\n return request.user == obj","def has_object_permission(self, request, view, obj):\n return request.user == obj","def save(self, orm, obj):\n try:\n ref = orm.ORM.store(self.table, obj.FIELDS)\n return ref\n except:\n raise MchCriticalError(Exception('Death cannot be saved'))\n return False","def has_object_permission(self, request, view, obj):\n if request.method in permissions.SAFE_METHODS:\n return True\n \n \"\"\"Check if the user has the permission to edit their profile. If True it will allow PUT, PATCH & DELETE operations\"\"\"\n return obj.id == request.user.id # returns True or False","def __eq__(self, obj):\n if not obj:\n return False\n\n return str(self.key()) == str(obj.key())","def in_(self, obj):\r\n return assert_(self.obj in obj, '%r not in %r' % (self.obj, obj))","def isChanged(self, p_int): # real signature unknown; restored from __doc__\n return False","def is_change(self) -> bool:\n return self._change","def get_changed() -> bool:\n return g.ledger.changed()","def __eq__(self, obj):\r\n return assert_(self.obj == obj, '%r != %r' % (self.obj, obj))","def _object_exists(name):\n conn = sqlite3.connect('/dev/input')\n try:\n cur = conn.cursor()\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\n cur.execute(sql, (name, ))\n result = cur.fetchall()\n return len(result) > 0\n finally:\n conn.close()","def has_object_permission(self, request, view, obj):\n\n \"\"\" Check the HTTP method being used for the request\"\"\"\n \"\"\" 'SAFE' methods are those methods that don't make any change to the object e.g. PUT\"\"\"\n \"\"\" users should only be able to make changes to their own profile - being checked below -> whether object ID = user id\"\"\"\n if request.method in permissions.SAFE_METHODS:\n return True\n\n return obj.id == request.user.id","def has_object_permission(self, request, view, obj):\n if request.user.is_authenticated:\n return obj.author != request.user\n return False","def get_changes(model_object):\n\n # Grab the current state of the model_object\n state = db.inspect(model_object)\n changes = False\n\n for attr in state.attrs:\n\n # We skip checking if the password_hash has changed for security reasons.\n # Even if it is being updated, we will not create a notification for this.\n if attr.key == \"password_hash\":\n continue\n\n # Check if attribute has changed. Continue to next attribute if it has not.\n hist = state.get_history(attr.key, True)\n if not hist.has_changes():\n continue\n\n else: # Found changes, so set changes to True and break from loop\n changes = True\n break\n\n return changes","def _is_valid_update_operation(session, row):\n # Check if there are older updates in the queue\n if db.check_for_older_ops(session, row):\n return False\n\n # Check for a pending or processing create operation on this uuid\n if db.check_for_pending_or_processing_ops(\n session, row.object_uuid, operation=odl_const.ODL_CREATE):\n return False\n return True","def check_modified(self) -> bool:\n return bool(self._modified)","def unsaved_changes(self) -> bool:\n return self.db.db_unsaved_changes()","def is_deleted(self):\n return self._is_record_status(self.DELETED)","def is_updated(self):\n return self.timestamp > 0","def _is_dirty(self):\n if self._get_dirty_fields():\n return True\n\n return False","def __contains__(self, obj):\n\n if isinstance(obj, str):\n return obj in FileStorage.__objects\n return key(type(obj), obj.id) in FileStorage.__objects","def isDirty( self ):\n return self._dirty","def is_modified(\n self, instance: object, include_collections: bool = True\n ) -> bool:\n state = object_state(instance)\n\n if not state.modified:\n return False\n\n dict_ = state.dict\n\n for attr in state.manager.attributes:\n if (\n not include_collections\n and hasattr(attr.impl, \"get_collection\")\n ) or not hasattr(attr.impl, \"get_history\"):\n continue\n\n (added, unchanged, deleted) = attr.impl.get_history(\n state, dict_, passive=PassiveFlag.NO_CHANGE\n )\n\n if added or deleted:\n return True\n else:\n return False","def has_object_permission(self, request, view, obj):\n return request.user.id == obj.user_id","def has_delete_permission(self, request, obj=None):\n\n if obj and obj.cwr:\n return False\n return super().has_delete_permission(request, obj)","def is_deleted(self):\n return 'deleted_at' in self._dict and bool(self._dict['deleted_at'])","def is_editable ( self, object ):\n return self.editable","def is_editable ( self, object ):\n return self.editable","def is_update(self) -> bool:\n return self.statement.is_dml and self.statement.is_update","def dirty(self) -> bool:\n return self.__dirty","def isDirty(self):\n return self._dirty","def has_object_permission(self,request,view,obj):\n\n\t\tif request.method in permissions.SAFE_METHODS:\n\t\t\treturn True\n\n\t\treturn obj.id == request.user.id","def post_migrate_function_new_only(obj):\n if obj.was_migrated:\n return post_migrate_function(obj)\n return False","def has_object_permission(self, request, view, obj):\n if request.method in permissions.SAFE_METHODS:\n return True\n \n \"\"\"Check if the user has the permission to edit their profile. If True it will allow PUT, PATCH & DELETE operations\"\"\"\n return obj.user_profile.id == request.user.id # returns True or False","def is_savable(self, request, obj):\n return not self.is_readonly(request, obj)","def __contains__(self, obj):\r\n return assert_(obj in self.obj, '%r not in %r' % (obj, self.obj))","def has_object_permission(self, request, view, obj):\n if request.method in permissions.SAFE_METHODS or request.user.is_admin:\n return True\n\n # Compare instance to the user in request\n return obj.user == request.user","def has_change_permission(self, request, instance=None):\n return False","def check_consistency(object) -> bool:\n time = np.array(list(object.keys()))\n time_diff = time[1:] - time[0:-1]\n return np.all(time_diff == 1)","def __eq__(self, obj: \"Property\") -> bool:\n return self.name == obj.name and self.property_type == obj.property_type","def dirty(self):\n return not self.consistent","def has_object_permission(self, request, view, obj):\n usuario_loggeado = request.user\n perfil_usuario = obj\n return usuario_loggeado == perfil_usuario","def has_object_permission(self , request , view , obj):\n if request.method in permissions.SAFE_METHODS:\n return True\n \n return obj.id == request.user.id","def updated(self):\n return self._dict_hash != self.gen_model_hash(self.json(sort_keys=True))","def exists(self):\n try:\n key = self.key\n except DoesNotExist:\n \"\"\"\n If the object doesn't exists anymore, its PK is deleted, so the\n \"self.key\" call will raise a DoesnotExist exception. We catch it\n to return False, as the field doesn't exists too.\n \"\"\"\n return False\n else:\n return self.connection.exists(key)","def is_object(obj):\n return (isinstance(obj, object) and\n type(obj) is not type and\n type(obj) is not types.FunctionType)","def is_updated_after(self, bucket, object, ts):\n service = self.get_conn()\n try:\n response = (service\n .objects()\n .get(bucket=bucket, object=object)\n .execute())\n\n if 'updated' in response:\n import dateutil.parser\n import dateutil.tz\n\n if not ts.tzinfo:\n ts = ts.replace(tzinfo=dateutil.tz.tzutc())\n\n updated = dateutil.parser.parse(response['updated'])\n self.log.info(\"Verify object date: %s > %s\", updated, ts)\n\n if updated > ts:\n return True\n\n except errors.HttpError as ex:\n if ex.resp['status'] != '404':\n raise\n\n return False","def attempted_change(self):\n return any(self._get_field_data())","def update_or_save_object(command, new_object, recorded_objects,\n fields_to_compare, alternate_pk=False):\n try:\n if alternate_pk:\n recorded_object = recorded_objects.get(**alternate_pk)\n else:\n recorded_object = recorded_objects.get(pk=new_object.pk)\n\n if fields_to_compare:\n return compare_fields(command, recorded_object, new_object,\n fields_to_compare, update=True)\n else:\n return True\n\n except ObjectDoesNotExist:\n new_object.save()\n command.stderr.write('Added new record {} to the database\\n'\n .format(str(new_object)))\n return False","def has_object_permission(self, request, view, obj):\n return not obj.permission == \"author\"","def allow_relation(self, obj1, obj2, **hints):\n\n if obj1._state.db == obj2._state.db:\n return True\n return False","def should_update(self, instance, **kwargs):\n return True","def changed(self) -> bool:\n for chunk_location, chunk in self._chunk_cache.items():\n if chunk is None:\n # if the chunk is None and the saved record is not None, the chunk has changed.\n if chunk_location not in self._chunk_index:\n return True\n _, save_chunk_index = self._chunk_index[chunk_location]\n chunk_storage = self._chunk_history[chunk_location]\n if chunk_storage[save_chunk_index] is not None:\n return True\n elif chunk.changed:\n return True\n for chunk_index, save_chunk_index in self._chunk_index.values():\n if chunk_index != save_chunk_index:\n return True\n return False","def contains(self, obj):\n self._not_support_combined_queries(\"contains\")\n if self._fields is not None:\n raise TypeError(\n \"Cannot call QuerySet.contains() after .values() or .values_list().\"\n )\n try:\n if obj._meta.concrete_model != self.model._meta.concrete_model:\n return False\n except AttributeError:\n raise TypeError(\"'obj' must be a model instance.\")\n if obj.pk is None:\n raise ValueError(\"QuerySet.contains() cannot be used on unsaved objects.\")\n if self._result_cache is not None:\n return obj in self._result_cache\n return self.filter(pk=obj.pk).exists()","def hasChanged(self):\n return ((self.mtime != getmtime(self.path)) or\n (self.size != os.path.getsize(self.path)) )","def has_object_permission(self, request, view, obj):\n if request.method in SAFE_METHODS:\n return True\n return obj.author == request.user"],"string":"[\n \"def is_live(self, obj):\\n most_appropriate_object = get_appropriate_object_from_model(self.model)\\n if most_appropriate_object == obj:\\n return True\\n return False\",\n \"def has_change_permission(self, request, obj=None):\\n if obj is not None:\\n return False\\n return super().has_change_permission(request, obj)\",\n \"def isModelDirty(self):\\n \\n pass\",\n \"def exists(self, obj):\\n return False\",\n \"def hasChanged(self):\\r\\n if self.is_updated:\\r\\n self.is_updated = False\\r\\n return True\\r\\n else:\\r\\n return False\\r\\n\\r\\n # if not self.hasBeenUpdatedOnce:\\r\\n # self.hasBeenUpdatedOnce = True\\r\\n # return True\\r\\n # else:\\r\\n # if BLENDER_MODE == 'BPY':\\r\\n # # for e in dir(self.obj): print(e)\\r\\n # # print(self.obj, self.obj.name, self.obj.is_updated, self.obj.is_updated_data)\\r\\n # # return self.obj.is_updated # DOESN't UPDATE A THING!\\r\\n # # return True\\r\\n # return self.is_updated\\r\\n\\r\\n # return False # no update in BGE mode\\r\",\n \"def bool(self, obj):\\n return True\",\n \"def bool(self, obj):\\n return True\",\n \"def has_update_permissions(self, obj):\\n return True\",\n \"def has_object_permission(self, request, view, obj):\\n if request.method == \\\"GET\\\":\\n return self.model_admin_config.has_view_permission(self, request, obj=obj)\\n if request.method == \\\"PUT\\\":\\n return self.model_admin_config.has_change_permission(self, request, obj=obj)\\n if request.method == \\\"DELETE\\\":\\n return self.model_admin_config.has_delete_permission(self, request, obj=obj)\",\n \"def _is_sqlalchemy_object(obj):\\n # TODO: better way?\\n return hasattr(obj, \\\"_sa_instance_state\\\")\",\n \"def equals(self, obj: object) -> bool:\\n ...\",\n \"def update_if_not_modified(self, obj, fields, upsert=False):\\n spec = state(obj).original_document\\n self.update(obj.__class__, spec, fields, upsert=upsert)\\n err = self.impl.db.command(dict(getlasterror=1))\\n return bool(err['n'] and err['updatedExisting'])\",\n \"def has_change_permission(self, request, obj=None):\\n has_class_permission = super(EntryAdmin, self).has_change_permission(request, obj)\\n if not has_class_permission:\\n return False\\n if obj is not None and not request.user.is_superuser and request.user.id != obj.author.id:\\n return False\\n return True\",\n \"def is_editable(obj, request):\\n if hasattr(obj, \\\"is_editable\\\"):\\n return obj.is_editable(request)\\n else:\\n perm = obj._meta.app_label + \\\".\\\" + obj._meta.get_change_permission()\\n return request.user.is_authenticated() and request.user.has_perm(perm)\",\n \"def has_change_permission(self, request, obj=None):\\n return False\",\n \"def _changeable_fields(self, request, obj):\\n return not obj or not self.is_readonly(request, obj)\",\n \"def has_object_permission(self, request, view, obj):\\n usuario_request = request.user\\n usuario_a_modificar = obj\\n\\n return usuario_request != usuario_a_modificar\",\n \"def _objectDeleted(self, obj):\\n pass\",\n \"def has_change_permission(self, request, obj=None) -> bool:\\n permission = super().has_change_permission(request, obj)\\n\\n if obj is not None:\\n permission &= (obj.owner == request.user) or request.user.is_superuser\\n\\n return permission\",\n \"def isDirty(*args, connection: bool=True, datablock: bool=True, **kwargs)->bool:\\n pass\",\n \"def _can_update(self):\\r\\n if not self._is_persisted: return False\\r\\n pks = self._primary_keys.keys()\\r\\n return all([not self._values[k].changed for k in self._primary_keys])\",\n \"def isDirty(self):\\n\\t#@DEBUG christophe have to fix denoising optionnal issue prior to set isDirty() to True\\n return False\",\n \"def has_object_permission(self, request, view, obj):\\n if request.method in permissions.SAFE_METHODS:\\n return True\\n # When the user make a request It will check that is on Safe methods, so it return true if the user is \\n # trying to update is own profile or return false. And also it will return the obj.id == request.user.id\\n return obj.id == request.user.id\",\n \"def is_dirty(self):\\n return self.dirty\",\n \"def is_dirty(self):\\n return self.dirty\",\n \"def is_deleted(self):\\n if self.deleted:\\n return True\\n return False\",\n \"def __contains__(self, obj):\\n if isinstance(obj, self):\\n query = self.where(**obj.data).select()\\n result = query.execute()\\n if result.count:\\n return True\\n return False\",\n \"def changed(self):\\n if self.exists():\\n return self.current_content != self.content\\n else:\\n return True\",\n \"def should_save(self):\\n return self.modified\",\n \"def isdirty(self):\\n\\n return not not self._olddata\",\n \"def __bool__(self):\\n return bool(self.obj)\",\n \"def has_object_update_permission(self, request):\\n user = request.user\\n if self == user:\\n return True\\n return user.is_superuser\",\n \"def exists(self):\\n return self.obj is not None\",\n \"def __is_hard_match(self, obj):\\n for attr in self.list:\\n try:\\n if getattr(obj, attr) != getattr(self, attr):\\n return False\\n except AttributeError:\\n pass\\n return True\",\n \"def has_change_permission(self, request, obj=None):\\n\\n if type(obj) is Client:\\n return obj.is_user_in_main_sales_contacts_of_client(request.user)\\n return False\",\n \"def has_change_permission(self, request, obj=None):\\n opts = self.opts\\n codename = get_permission_codename('change', opts)\\n return any([\\n request.user.has_perm(\\\"%s.%s\\\" % (opts.app_label, codename)),\\n request.user.has_perm(\\\"%s.%s\\\" % (opts.app_label, codename), obj)])\",\n \"def has_changed(self):\\n return bool(self.changed_data)\",\n \"def has_object_permission(self, request, view, obj):\\n\\n return obj.active\",\n \"def is_modified(self):\\n return len(self.modified_fields) > 0\",\n \"def delete(self):\\n ret = False\\n q = self.query\\n pk = self.pk\\n if pk:\\n pk_name = self.schema.pk.name\\n self.query.is_field(pk_name, pk).delete()\\n setattr(self, pk_name, None)\\n\\n # mark all the fields that still exist as modified\\n self.reset_modified()\\n for field_name in self.schema.fields:\\n if getattr(self, field_name, None) != None:\\n self.modified_fields.add(field_name)\\n\\n ret = True\\n\\n return ret\",\n \"def is_dirty(self):\\n return self._is_dirty\",\n \"def is_dirty(self):\\n return self._is_dirty\",\n \"def has_object_permission(self, request, view, obj):\\n if request.user.is_superuser:\\n return True\\n if request.user.profile.role == UserRole.CLIENT and obj.owner != request.user:\\n return False\\n if request.user.profile.role == UserRole.EXECUTOR and obj.executor != request.user:\\n return False\\n return True\",\n \"def has_change_permission(self, request, obj=None):\\n has_perm = super(ShortURLAdmin, self).has_change_permission(request, obj)\\n if not has_perm:\\n return False\\n if obj is not None and not request.user.has_perm('deflect.list_all') and request.user.id != obj.creator.id:\\n return False\\n return True\",\n \"def has_object_permission(self, request, view, obj):\\n\\n return request.user == obj\",\n \"def has_object_permission(self, request, view, obj):\\n return request.user == obj\",\n \"def save(self, orm, obj):\\n try:\\n ref = orm.ORM.store(self.table, obj.FIELDS)\\n return ref\\n except:\\n raise MchCriticalError(Exception('Death cannot be saved'))\\n return False\",\n \"def has_object_permission(self, request, view, obj):\\n if request.method in permissions.SAFE_METHODS:\\n return True\\n \\n \\\"\\\"\\\"Check if the user has the permission to edit their profile. If True it will allow PUT, PATCH & DELETE operations\\\"\\\"\\\"\\n return obj.id == request.user.id # returns True or False\",\n \"def __eq__(self, obj):\\n if not obj:\\n return False\\n\\n return str(self.key()) == str(obj.key())\",\n \"def in_(self, obj):\\r\\n return assert_(self.obj in obj, '%r not in %r' % (self.obj, obj))\",\n \"def isChanged(self, p_int): # real signature unknown; restored from __doc__\\n return False\",\n \"def is_change(self) -> bool:\\n return self._change\",\n \"def get_changed() -> bool:\\n return g.ledger.changed()\",\n \"def __eq__(self, obj):\\r\\n return assert_(self.obj == obj, '%r != %r' % (self.obj, obj))\",\n \"def _object_exists(name):\\n conn = sqlite3.connect('/dev/input')\\n try:\\n cur = conn.cursor()\\n sql = 'SELECT ROWID FROM object WHERE name=? AND deleted=0'\\n cur.execute(sql, (name, ))\\n result = cur.fetchall()\\n return len(result) > 0\\n finally:\\n conn.close()\",\n \"def has_object_permission(self, request, view, obj):\\n\\n \\\"\\\"\\\" Check the HTTP method being used for the request\\\"\\\"\\\"\\n \\\"\\\"\\\" 'SAFE' methods are those methods that don't make any change to the object e.g. PUT\\\"\\\"\\\"\\n \\\"\\\"\\\" users should only be able to make changes to their own profile - being checked below -> whether object ID = user id\\\"\\\"\\\"\\n if request.method in permissions.SAFE_METHODS:\\n return True\\n\\n return obj.id == request.user.id\",\n \"def has_object_permission(self, request, view, obj):\\n if request.user.is_authenticated:\\n return obj.author != request.user\\n return False\",\n \"def get_changes(model_object):\\n\\n # Grab the current state of the model_object\\n state = db.inspect(model_object)\\n changes = False\\n\\n for attr in state.attrs:\\n\\n # We skip checking if the password_hash has changed for security reasons.\\n # Even if it is being updated, we will not create a notification for this.\\n if attr.key == \\\"password_hash\\\":\\n continue\\n\\n # Check if attribute has changed. Continue to next attribute if it has not.\\n hist = state.get_history(attr.key, True)\\n if not hist.has_changes():\\n continue\\n\\n else: # Found changes, so set changes to True and break from loop\\n changes = True\\n break\\n\\n return changes\",\n \"def _is_valid_update_operation(session, row):\\n # Check if there are older updates in the queue\\n if db.check_for_older_ops(session, row):\\n return False\\n\\n # Check for a pending or processing create operation on this uuid\\n if db.check_for_pending_or_processing_ops(\\n session, row.object_uuid, operation=odl_const.ODL_CREATE):\\n return False\\n return True\",\n \"def check_modified(self) -> bool:\\n return bool(self._modified)\",\n \"def unsaved_changes(self) -> bool:\\n return self.db.db_unsaved_changes()\",\n \"def is_deleted(self):\\n return self._is_record_status(self.DELETED)\",\n \"def is_updated(self):\\n return self.timestamp > 0\",\n \"def _is_dirty(self):\\n if self._get_dirty_fields():\\n return True\\n\\n return False\",\n \"def __contains__(self, obj):\\n\\n if isinstance(obj, str):\\n return obj in FileStorage.__objects\\n return key(type(obj), obj.id) in FileStorage.__objects\",\n \"def isDirty( self ):\\n return self._dirty\",\n \"def is_modified(\\n self, instance: object, include_collections: bool = True\\n ) -> bool:\\n state = object_state(instance)\\n\\n if not state.modified:\\n return False\\n\\n dict_ = state.dict\\n\\n for attr in state.manager.attributes:\\n if (\\n not include_collections\\n and hasattr(attr.impl, \\\"get_collection\\\")\\n ) or not hasattr(attr.impl, \\\"get_history\\\"):\\n continue\\n\\n (added, unchanged, deleted) = attr.impl.get_history(\\n state, dict_, passive=PassiveFlag.NO_CHANGE\\n )\\n\\n if added or deleted:\\n return True\\n else:\\n return False\",\n \"def has_object_permission(self, request, view, obj):\\n return request.user.id == obj.user_id\",\n \"def has_delete_permission(self, request, obj=None):\\n\\n if obj and obj.cwr:\\n return False\\n return super().has_delete_permission(request, obj)\",\n \"def is_deleted(self):\\n return 'deleted_at' in self._dict and bool(self._dict['deleted_at'])\",\n \"def is_editable ( self, object ):\\n return self.editable\",\n \"def is_editable ( self, object ):\\n return self.editable\",\n \"def is_update(self) -> bool:\\n return self.statement.is_dml and self.statement.is_update\",\n \"def dirty(self) -> bool:\\n return self.__dirty\",\n \"def isDirty(self):\\n return self._dirty\",\n \"def has_object_permission(self,request,view,obj):\\n\\n\\t\\tif request.method in permissions.SAFE_METHODS:\\n\\t\\t\\treturn True\\n\\n\\t\\treturn obj.id == request.user.id\",\n \"def post_migrate_function_new_only(obj):\\n if obj.was_migrated:\\n return post_migrate_function(obj)\\n return False\",\n \"def has_object_permission(self, request, view, obj):\\n if request.method in permissions.SAFE_METHODS:\\n return True\\n \\n \\\"\\\"\\\"Check if the user has the permission to edit their profile. If True it will allow PUT, PATCH & DELETE operations\\\"\\\"\\\"\\n return obj.user_profile.id == request.user.id # returns True or False\",\n \"def is_savable(self, request, obj):\\n return not self.is_readonly(request, obj)\",\n \"def __contains__(self, obj):\\r\\n return assert_(obj in self.obj, '%r not in %r' % (obj, self.obj))\",\n \"def has_object_permission(self, request, view, obj):\\n if request.method in permissions.SAFE_METHODS or request.user.is_admin:\\n return True\\n\\n # Compare instance to the user in request\\n return obj.user == request.user\",\n \"def has_change_permission(self, request, instance=None):\\n return False\",\n \"def check_consistency(object) -> bool:\\n time = np.array(list(object.keys()))\\n time_diff = time[1:] - time[0:-1]\\n return np.all(time_diff == 1)\",\n \"def __eq__(self, obj: \\\"Property\\\") -> bool:\\n return self.name == obj.name and self.property_type == obj.property_type\",\n \"def dirty(self):\\n return not self.consistent\",\n \"def has_object_permission(self, request, view, obj):\\n usuario_loggeado = request.user\\n perfil_usuario = obj\\n return usuario_loggeado == perfil_usuario\",\n \"def has_object_permission(self , request , view , obj):\\n if request.method in permissions.SAFE_METHODS:\\n return True\\n \\n return obj.id == request.user.id\",\n \"def updated(self):\\n return self._dict_hash != self.gen_model_hash(self.json(sort_keys=True))\",\n \"def exists(self):\\n try:\\n key = self.key\\n except DoesNotExist:\\n \\\"\\\"\\\"\\n If the object doesn't exists anymore, its PK is deleted, so the\\n \\\"self.key\\\" call will raise a DoesnotExist exception. We catch it\\n to return False, as the field doesn't exists too.\\n \\\"\\\"\\\"\\n return False\\n else:\\n return self.connection.exists(key)\",\n \"def is_object(obj):\\n return (isinstance(obj, object) and\\n type(obj) is not type and\\n type(obj) is not types.FunctionType)\",\n \"def is_updated_after(self, bucket, object, ts):\\n service = self.get_conn()\\n try:\\n response = (service\\n .objects()\\n .get(bucket=bucket, object=object)\\n .execute())\\n\\n if 'updated' in response:\\n import dateutil.parser\\n import dateutil.tz\\n\\n if not ts.tzinfo:\\n ts = ts.replace(tzinfo=dateutil.tz.tzutc())\\n\\n updated = dateutil.parser.parse(response['updated'])\\n self.log.info(\\\"Verify object date: %s > %s\\\", updated, ts)\\n\\n if updated > ts:\\n return True\\n\\n except errors.HttpError as ex:\\n if ex.resp['status'] != '404':\\n raise\\n\\n return False\",\n \"def attempted_change(self):\\n return any(self._get_field_data())\",\n \"def update_or_save_object(command, new_object, recorded_objects,\\n fields_to_compare, alternate_pk=False):\\n try:\\n if alternate_pk:\\n recorded_object = recorded_objects.get(**alternate_pk)\\n else:\\n recorded_object = recorded_objects.get(pk=new_object.pk)\\n\\n if fields_to_compare:\\n return compare_fields(command, recorded_object, new_object,\\n fields_to_compare, update=True)\\n else:\\n return True\\n\\n except ObjectDoesNotExist:\\n new_object.save()\\n command.stderr.write('Added new record {} to the database\\\\n'\\n .format(str(new_object)))\\n return False\",\n \"def has_object_permission(self, request, view, obj):\\n return not obj.permission == \\\"author\\\"\",\n \"def allow_relation(self, obj1, obj2, **hints):\\n\\n if obj1._state.db == obj2._state.db:\\n return True\\n return False\",\n \"def should_update(self, instance, **kwargs):\\n return True\",\n \"def changed(self) -> bool:\\n for chunk_location, chunk in self._chunk_cache.items():\\n if chunk is None:\\n # if the chunk is None and the saved record is not None, the chunk has changed.\\n if chunk_location not in self._chunk_index:\\n return True\\n _, save_chunk_index = self._chunk_index[chunk_location]\\n chunk_storage = self._chunk_history[chunk_location]\\n if chunk_storage[save_chunk_index] is not None:\\n return True\\n elif chunk.changed:\\n return True\\n for chunk_index, save_chunk_index in self._chunk_index.values():\\n if chunk_index != save_chunk_index:\\n return True\\n return False\",\n \"def contains(self, obj):\\n self._not_support_combined_queries(\\\"contains\\\")\\n if self._fields is not None:\\n raise TypeError(\\n \\\"Cannot call QuerySet.contains() after .values() or .values_list().\\\"\\n )\\n try:\\n if obj._meta.concrete_model != self.model._meta.concrete_model:\\n return False\\n except AttributeError:\\n raise TypeError(\\\"'obj' must be a model instance.\\\")\\n if obj.pk is None:\\n raise ValueError(\\\"QuerySet.contains() cannot be used on unsaved objects.\\\")\\n if self._result_cache is not None:\\n return obj in self._result_cache\\n return self.filter(pk=obj.pk).exists()\",\n \"def hasChanged(self):\\n return ((self.mtime != getmtime(self.path)) or\\n (self.size != os.path.getsize(self.path)) )\",\n \"def has_object_permission(self, request, view, obj):\\n if request.method in SAFE_METHODS:\\n return True\\n return obj.author == request.user\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6930333","0.6525286","0.64501333","0.64336836","0.6431397","0.64131296","0.64131296","0.6349598","0.63452303","0.63142246","0.63139683","0.6300048","0.62984204","0.62824523","0.6207841","0.616058","0.61573696","0.6101484","0.60884404","0.60836864","0.6051057","0.6023432","0.6001744","0.5986488","0.5986488","0.59842175","0.59692633","0.59689844","0.5959626","0.59452575","0.59358084","0.5922295","0.59022397","0.589851","0.58866554","0.58798796","0.5864371","0.5863982","0.58525425","0.5849543","0.5843442","0.5843442","0.5838732","0.5811839","0.58113563","0.5800632","0.57960975","0.5777404","0.57722986","0.5758505","0.57570976","0.5752548","0.57524234","0.57512593","0.57435745","0.57411677","0.57359314","0.572392","0.5723495","0.5720765","0.5704566","0.5701341","0.56979704","0.5697498","0.5697388","0.56931716","0.5691153","0.56910807","0.5689933","0.5677068","0.56628364","0.56628364","0.56486696","0.5637596","0.5627355","0.56249845","0.5601547","0.56007755","0.559993","0.55975825","0.5596868","0.5596015","0.55953085","0.5591741","0.5585224","0.5580464","0.5579313","0.557259","0.55706465","0.55612946","0.5561081","0.5555388","0.55509436","0.5545681","0.55185133","0.5516522","0.5512816","0.55126","0.5512522","0.5509139"],"string":"[\n \"0.6930333\",\n \"0.6525286\",\n \"0.64501333\",\n \"0.64336836\",\n \"0.6431397\",\n \"0.64131296\",\n \"0.64131296\",\n \"0.6349598\",\n \"0.63452303\",\n \"0.63142246\",\n \"0.63139683\",\n \"0.6300048\",\n \"0.62984204\",\n \"0.62824523\",\n \"0.6207841\",\n \"0.616058\",\n \"0.61573696\",\n \"0.6101484\",\n \"0.60884404\",\n \"0.60836864\",\n \"0.6051057\",\n \"0.6023432\",\n \"0.6001744\",\n \"0.5986488\",\n \"0.5986488\",\n \"0.59842175\",\n \"0.59692633\",\n \"0.59689844\",\n \"0.5959626\",\n \"0.59452575\",\n \"0.59358084\",\n \"0.5922295\",\n \"0.59022397\",\n \"0.589851\",\n \"0.58866554\",\n \"0.58798796\",\n \"0.5864371\",\n \"0.5863982\",\n \"0.58525425\",\n \"0.5849543\",\n \"0.5843442\",\n \"0.5843442\",\n \"0.5838732\",\n \"0.5811839\",\n \"0.58113563\",\n \"0.5800632\",\n \"0.57960975\",\n \"0.5777404\",\n \"0.57722986\",\n \"0.5758505\",\n \"0.57570976\",\n \"0.5752548\",\n \"0.57524234\",\n \"0.57512593\",\n \"0.57435745\",\n \"0.57411677\",\n \"0.57359314\",\n \"0.572392\",\n \"0.5723495\",\n \"0.5720765\",\n \"0.5704566\",\n \"0.5701341\",\n \"0.56979704\",\n \"0.5697498\",\n \"0.5697388\",\n \"0.56931716\",\n \"0.5691153\",\n \"0.56910807\",\n \"0.5689933\",\n \"0.5677068\",\n \"0.56628364\",\n \"0.56628364\",\n \"0.56486696\",\n \"0.5637596\",\n \"0.5627355\",\n \"0.56249845\",\n \"0.5601547\",\n \"0.56007755\",\n \"0.559993\",\n \"0.55975825\",\n \"0.5596868\",\n \"0.5596015\",\n \"0.55953085\",\n \"0.5591741\",\n \"0.5585224\",\n \"0.5580464\",\n \"0.5579313\",\n \"0.557259\",\n \"0.55706465\",\n \"0.55612946\",\n \"0.5561081\",\n \"0.5555388\",\n \"0.55509436\",\n \"0.5545681\",\n \"0.55185133\",\n \"0.5516522\",\n \"0.5512816\",\n \"0.55126\",\n \"0.5512522\",\n \"0.5509139\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.80351144"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13079,"cells":{"query":{"kind":"string","value":"try go load from the database one object with specific version"},"document":{"kind":"string","value":"def get_version(model_instance, version):\n version_field = get_version_fieldname(model_instance)\n kwargs = {'pk': model_instance.pk, version_field: version}\n return model_instance.__class__.objects.get(**kwargs)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _load_version(cls, unpickler, version):\n model = unpickler.load()\n if version == 0:\n feature = model._state['features']\n model._state['output_column_name'] = 'extracted.' + feature\n return model","def _load_version():\n version = session.get('version')\n\n if version is None:\n g.version = None\n else:\n g.version = version","def load(cls, backend, path, obj):\n b = backend\n id = obj['id']\n name = obj['name']\n desc = obj['description']\n url = obj['url']\n path = os.path.join(path, id)\n\n # Load the index.json file.\n idx = b.read_json(os.path.join(path, 'index.json'))\n if idx['ApiVersion'] != 0:\n return None\n\n versions = []\n for vsn_obj in idx['Versions']:\n # TODO: Maybe check if the version file exists?\n versions.append(dict(\n id=vsn_obj['Id'],\n name=vsn_obj['Name'],\n ))\n\n return cls(b, id, name, desc, url, path, versions)","def retrieve_from_db(self):\n pass","def _load_vdb_with_mode(cls, vdb, mode): \n # {{\n db = anydbm.open(vdb.filename, mode)\n try:\n if db[\"--Reserved--type\"] != vdb.type:\n raise ValueError(\"Not a %s database\" % (vdb.type,))\n except KeyError:\n raise ValueError(\"Not a recognized database\")\n vdb.db = db\n # }}","def test_quest_load_version_fail(testing_quest_page):\n testing_quest_page.save()\n\n # fetch the data\n doc = testing_quest_page.doc_ref.get()\n data = testing_quest_page.storage_model.parse_obj(doc.to_dict())\n\n # mess with the version\n data.version = str(VersionInfo.parse(data.version).bump_major())\n testing_quest_page.doc_ref.set(data.dict())\n\n # try to load with the bad version\n with pytest.raises(QuestLoadError):\n testing_quest_page.load()\n\n # cleanup\n testing_quest_page.delete()","def checkVersions():\n item = Item(fromScene=True)\n\n for ns, componentMData in item.components.iteritems():\n if ns == 'cam':\n # todo tratar versoes da camera\n continue\n\n if componentMData['assembleMode'] == 'reference':\n refComponent = ReferenceComponent(ns, componentMData, parent=item)\n refComponent.checkDBForNewVersion()\n\n elif componentMData['assembleMode'] == 'xlo':\n xloComponent = XloComponent(ns, componentMData, parent=item)\n xloComponent.checkDBForNewVersion()\n xloComponent.checkDBForNewCacheVersion()\n\n elif componentMData['assembleMode'] == 'cache':\n cacheComponent = CacheComponent(ns, componentMData, parent=item)\n cacheComponent.checkDBForNewVersion()\n\n item.putDataToDB()","def test_model_by_version_get(self):\n\n # Firstly, find existing version - latest\n response = self.client().get('/model')\n latest_model = Model.from_json(response.data.decode())\n latest_version = latest_model.version\n\n # Accesses latest model\n response = self.client().get('/models/'+str(latest_version))\n self.assertEqual(response.status_code, 200)\n loaded_model = Model.from_json(response.data.decode())\n self.assertEqual(loaded_model.version, latest_version)\n self.assertEqual(loaded_model, latest_model)\n\n # Accesses random model version\n random_version = random.choice(list(self.data_manipulation.versions.keys()))\n random_model = self.data_manipulation.versions[random_version]\n response = self.client().get('/models/'+str(random_version))\n self.assertEqual(response.status_code, 200)\n loaded_model = Model.from_json(response.data.decode())\n self.assertEqual(loaded_model.version, random_version)\n self.assertEqual(loaded_model, random_model)\n\n # Random version is removed\n del self.data_manipulation.versions[random_version]\n response = self.client().get('/models/'+str(random_version))\n self.assertEqual(response.status_code, 404)","def test_get_entity_version(self):\n self.metadata.create_or_update(data=self.create)\n\n # Find by name\n res_name = self.metadata.get_by_name(\n entity=Dashboard, fqn=self.entity.fullyQualifiedName\n )\n res = self.metadata.get_entity_version(\n entity=Dashboard, entity_id=res_name.id.__root__, version=0.1\n )\n\n # check we get the correct version requested and the correct entity ID\n assert res.version.__root__ == 0.1\n assert res.id == res_name.id","def load(cls, id):\n key = cls.get_key_prefix()+\"#\"+str(id)\n src = dal_get(key)\n logger.debug( \"LOAD %s %s %s\", str(key), str(id), str(src))\n if src == None:\n raise cls.NotExist(\"No instance could be found with ID: \"+str(id))\n result = dal_retrieve(src)\n result = cls._from_dict(result)\n return result","def upgrade_to_1():\n config.db.singletons.insert_one({'_id': 'version', 'database': 1})","def load_pkl(self, name, file_object=None):\n if file_object:\n f = file_object\n else:\n f = gzip.open(name, 'rb')\n temp = pickle.load(f)\n if temp.ht_version < HT_OLD_COMPAT_VERSION:\n raise ValueError('Version of ' + name + ' is ' + str(temp.ht_version)\n + ' which is not at least ' +\n str(HT_OLD_COMPAT_VERSION))\n # assert temp.ht_version >= HT_COMPAT_VERSION\n params = temp.params\n self.hashbits = temp.hashbits\n self.depth = temp.depth\n if hasattr(temp, 'maxtimebits'):\n self.maxtimebits = temp.maxtimebits\n else:\n self.maxtimebits = _bitsfor(temp.maxtime)\n if temp.ht_version < HT_COMPAT_VERSION:\n # Need to upgrade the database.\n print(\"Loading database version\", temp.ht_version,\n \"in compatibility mode.\")\n # Offset all the nonzero bins with one ID count.\n temp.table += np.array(1 << self.maxtimebits).astype(np.uint32) * (\n temp.table != 0)\n temp.ht_version = HT_VERSION\n self.table = temp.table\n self.ht_version = temp.ht_version\n self.counts = temp.counts\n self.names = temp.names\n self.hashesperid = np.array(temp.hashesperid).astype(np.uint32)\n self.dirty = False\n self.params = params","def _internal_load(self, modelcls, key, result=None):\n assert result is None\n riak_object = self.riak_object(modelcls, key)\n yield riak_object.reload()\n was_migrated = False\n\n # Run migrators until we have the correct version of the data.\n while riak_object.get_data() is not None:\n data_version = riak_object.get_data().get('$VERSION', None)\n if data_version == modelcls.VERSION:\n obj = modelcls(self, key, _riak_object=riak_object)\n obj.was_migrated = was_migrated\n returnValue(obj)\n migrator = modelcls.MIGRATOR(modelcls, self, data_version)\n riak_object = migrator(riak_object).get_riak_object()\n was_migrated = True\n returnValue(None)","def test_fetch(self):\n pkg = make_package(factory=SQLPackage)\n self.sql.add(pkg)\n saved_pkg = self.db.fetch(pkg.filename)\n self.assertEqual(saved_pkg, pkg)","def load(self):\n db = CrawlDBI.DBI(dbtype='crawler')\n if self.rowid is not None:\n rows = db.select(table='checkables',\n fields=['rowid',\n 'path',\n 'type',\n 'cos',\n 'cart',\n 'ttypes',\n 'checksum',\n 'last_check',\n 'fails',\n 'reported'],\n where=\"rowid = ?\",\n data=(self.rowid,))\n else:\n rows = db.select(table='checkables',\n fields=['rowid',\n 'path',\n 'type',\n 'cos',\n 'cart',\n 'ttypes',\n 'checksum',\n 'last_check',\n 'fails',\n 'reported'],\n where=\"path = ?\",\n data=(self.path,))\n if 0 == len(rows):\n self.in_db = False\n elif 1 == len(rows):\n self.in_db = True\n rz = list(rows[0])\n self.rowid = rz.pop(0)\n self.path = rz.pop(0)\n self.type = rz.pop(0)\n self.cos = rz.pop(0)\n self.cart = rz.pop(0)\n self.ttypes = rz.pop(0)\n self.checksum = rz.pop(0)\n self.last_check = rz.pop(0)\n try:\n self.fails = rz.pop(0)\n except IndexError:\n self.fails = 0\n try:\n self.reported = rz.pop(0)\n except IndexError:\n self.reported = 0\n self.dirty = False\n else:\n raise StandardError(\"There appears to be more than one copy \" +\n \"of %s in the database\" % self)\n\n db.close()","def load_model(self) -> Any:","def get_object(id):","def on_get_version(self, req, resp, version, **kwargs):\n instance = self.get_object(**kwargs)\n version = instance.load_version(version)\n if not version:\n raise falcon.HTTPNotFound()\n resp.json(**version.as_resource)","def _fetch_old_version(self) -> None:\n if self.version is None:\n try:\n r = fetch(self.api + '?version&format=json')\n try:\n d = r.json()\n except JSONDecodeError:\n # Fallback for old versions which didn't wrap help in json\n d = {'error': {'*': r.text}}\n\n self.version = list(filter(\n lambda x: x.startswith('MediaWiki'),\n (line.strip()\n for line in d['error']['*'].split('\\n'))))[0].split()[1]\n except Exception:\n pass\n else:\n self.version = MediaWikiVersion(self.version)","def load_or_create_db(self):\n try:\n with open(self._filename, 'rb') as f:\n self.db = pickle.load(f)\n except FileNotFoundError:\n pass","def from_db_value(self, value, *args):\n if value is not None:\n try:\n value = dbsafe_decode(value, self.compress)\n except Exception:\n # If the value is a definite pickle; and an error is raised in\n # de-pickling it should be allowed to propogate.\n if isinstance(value, PickledObject):\n raise\n else:\n if isinstance(value, _ObjectWrapper):\n return value._obj\n return value","def test_load(self):\n kwargs = {\"url\": \"my.url\", \"expire\": 7237}\n pkg = make_package(**kwargs)\n # Due to some rounding weirdness in old Py3 versions, we need to remove\n # the microseconds to avoid a flappy test.\n # See: https://bugs.python.org/issue23517\n pkg.last_modified = pkg.last_modified.replace(microsecond=0)\n self.db.save(pkg)\n\n loaded = self.db.fetch(pkg.filename)\n self.assertEqual(loaded.name, pkg.name)\n self.assertEqual(loaded.version, pkg.version)\n self.assertEqual(loaded.filename, pkg.filename)\n self.assertEqual(loaded.last_modified, pkg.last_modified)\n self.assertEqual(loaded.summary, pkg.summary)\n self.assertEqual(loaded.data, kwargs)","def _from_catalog(self):\n if self.dbconn.version < 90100:\n return\n for ext in self.fetch():\n self[ext.key()] = ext","def api_db_load(vend, buy, db_compare=False, compressed=True):\r\n #находим последнюю сжатую базу\r\n if compressed:\r\n db_conv_time = last_db_time_get()\r\n if not db_compare:\r\n if convert_time(db_conv_time, 'm') > 9: #9\r\n print(\"Old database...\")\r\n #собираем ссылку\r\n link = 'https://api.originsro.org/api/v1/market/list?api_key='\r\n api_key = ''\r\n #делаем вызов и сохраняем получаемое в переменной\r\n response = rq.get('{}{}'.format(link, api_key))\r\n #создаем путь/имя для нашей новой базы\r\n latest_file = '{}\\\\jsons\\\\DB_{}.json.gz'.format(db_folder_path, now.strftime(\"%d-%m-%Y_%H-%M-%S\"))\r\n #сохраняем нашу новую базу\r\n compress_json.dump(response.text, latest_file)\r\n print('compressed db saved')\r\n #и сразу же загружаем\r\n #actual_db = compress_json.local_load(latest_file)\r\n #находим 2 по старости дб (то есть ту, которая была перед нашей только что выкачанной)\r\n previous_db = sorted(glob.iglob('{}\\\\jsons\\\\DB_*.json.gz'.format(db_folder_path)), key=os.path.getctime)[-2]\r\n #распаковываем его\r\n #previous_db_uncompressed = compress_json.local_load(previous_db)\r\n #создаем временные листы с данными\r\n #из прошлой бд\r\n pre_vendor_shops = []\r\n pre_buy_shops = []\r\n get_vend_data(previous_db, pre_vendor_shops, pre_buy_shops)\r\n #из новой бд\r\n print(latest_file)\r\n get_vend_data(latest_file, vend, buy)\r\n #fill demand file\r\n compare_data(pre_vendor_shops, vend)\r\n compare_data(pre_buy_shops, buy)\r\n print('demand refreshed')\r\n else:\r\n print('Database ok...')\r\n latest_file = max(glob.glob('{}\\\\jsons\\\\DB_*.json.gz'.format(db_folder_path)), key=os.path.getctime)\r\n get_vend_data(latest_file, vend, buy)\r\n else:\r\n compare_db()\r\n else:\r\n #находим самую свежую базу из имеющихся\r\n latest_file = max(glob.glob('{}\\\\jsons\\\\DB_*.json'.format(db_folder_path)), key=os.path.getctime)\r\n #Загрузка БД и ее обновление\r\n with open(latest_file, encoding=\"utf8\") as json_file:\r\n #делаем удобное обозначение той же базы\r\n api_db = json.load(json_file)['generation_timestamp']\r\n db_time = datetime.datetime.strptime(api_db, \"%Y-%m-%dT%H:%M:%S.%fZ\")\r\n if not db_compare:\r\n #если базе больше 10 минут, надо обновить\r\n if convert_time(db_time, 'm') > 10: #9\r\n print(\"Old database...\")\r\n link = 'https://api.originsro.org/api/v1/market/list?api_key='\r\n api_key = 'r3bkd0q8umxhuj75ahtvwpgkd3yzi3rm'\r\n response = rq.get('{}{}'.format(link, api_key))\r\n latest_file = '{}\\\\jsons\\\\DB_{}.json'.format(db_folder_path, now.strftime(\"%d-%m-%Y_%H-%M-%S\"))\r\n #создаем новую бд с названием из latest_file\r\n with open(latest_file, \"w+\", encoding=\"utf8\") as new_file:\r\n new_file.write(response.text)\r\n #создаем новую, сжатую, бд\r\n #compress_json.dump(response.text, latest_file)\r\n #находим второй по новости файл, то есть прошлую бд\r\n previous_db = sorted(glob.iglob('{}\\\\jsons\\\\DB_*.json'.format(db_folder_path)), key=os.path.getctime)[-2]\r\n #создаем временные листы с данными\r\n #из прошлой бд\r\n pre_vendor_shops = []\r\n pre_buy_shops = []\r\n get_vend_data(previous_db, pre_vendor_shops, pre_buy_shops)\r\n #из новой бд\r\n get_vend_data(latest_file, vend, buy)\r\n #fill demand file\r\n compare_data(pre_vendor_shops, vend)\r\n compare_data(pre_buy_shops, buy)\r\n else:\r\n print('Database ok...')\r\n get_vend_data(latest_file, vend, buy)\r\n else:\r\n compare_db()","def test_fetch(self):\n pkg = make_package()\n self.db.save(pkg)\n saved_pkg = self.db.fetch(pkg.filename)\n self.assertEqual(saved_pkg, pkg)","def get(self, bento_name, bento_version):","def _get_version(self):","def load_obj(name):\n with open('../../data/' + name + '.pkl', 'rb') as f:\n return pickle.load(f)","def load_obj(name):\n with open('../../data/' + name + '.pkl', 'rb') as f:\n return pickle.load(f)","def db_version():\n return IMPL.db_version()","def _load(self, create):\n if not self.db.has_key('size'):\n if create:\n # It's a new database, initialize the special keys\n self.db['head'] = 0\n self.db['count'] = 0\n self.db['size'] = self.newSize\n\n # Cache the special keys\n self.head = self.db['head']\n self.count = self.db['count']\n self.size = self.db['size']\n self._loaded = True","def load(self):","def test_version_upgrade_nonpersistent(self):\n\n db_file = self.mktemp()\n\n db = Database.TestDB(db_file)\n yield db.open()\n yield db.execute(\"INSERT into TESTTYPE (KEY, VALUE) values (:1, :2)\", (\"FOO\", \"BAR\",))\n items = (yield db.query(\"SELECT * from TESTTYPE\"))\n self.assertEqual(items, ((\"FOO\", \"BAR\"),))\n db.close()\n db = None\n\n db = Database.TestDBRecreateUpgrade(db_file)\n yield self.inlineCallbackRaises(Database.TestDBRecreateUpgrade.RecreateDBException, db.open)\n items = (yield db.query(\"SELECT * from TESTTYPE\"))\n self.assertEqual(items, ())\n db.close()","def reconstruct(self):\n if os.path.exists(self.dbname):\n with open(self.dbname, mode='rb') as db:\n self.cache = pickle.load(db)","def load():\n pr = PLAPIResource()\n pr.name = 'Programming Languages'\n pr.uri = 'programming-languages'\n db.session.add(pr)\n db.session.commit()\n\n pd = PLAPIResource()\n pd.name = 'Paradigms'\n pd.uri = 'paradigms'\n db.session.add(pd)\n db.session.commit()\n\n \"\"\"\n pt = PLAPIResource()\n pt.name = 'Tutorials'\n pt.uri = 'tutorials'\n db.session.add(pt)\n db.session.commit()\n \"\"\"\n\n\n pl = ProgrammingLanguageModel()\n pl.name = 'Python'\n pl.slug = 'python'\n pl.homepage_url = 'https://www.python.org/'\n pl.is_visible = True\n db.session.add(pl)\n db.session.commit()\n\n pl2 = ProgrammingLanguageModel()\n pl2.name = 'Swift'\n pl2.slug = 'swift'\n pl2.homepage_url = 'https://developer.apple.com/swift/'\n pl2.is_visible = True\n db.session.add(pl2)\n db.session.commit()\n\n pl3 = ProgrammingLanguageModel()\n pl3.name = 'Ruby'\n pl3.slug = 'ruby'\n pl3.homepage_url = 'https://www.ruby-lang.org/'\n pl3.is_visible = True\n db.session.add(pl3)\n db.session.commit()\n\n prdgm1 = ParadigmModel()\n prdgm1.name = 'Imperative'\n prdgm1.slug = 'imperative'\n prdgm1.is_visible = True\n db.session.add(prdgm1)\n db.session.commit()\n\n prdgm2 = ParadigmModel()\n prdgm2.name = 'Functional'\n prdgm2.slug = 'functional'\n prdgm2.is_visible = True\n db.session.add(prdgm2)\n db.session.commit()\n\n lib = LibraryModel()\n lib.name = 'Django'\n lib.slug = 'django'\n lib.is_visible = True\n lib.language = pl.id\n lib.homepage_url = 'https://www.djangoproject.com/'\n lib.source_code_url = 'https://github.com/django/django'\n db.session.add(lib)\n db.session.commit()\n\n lib2 = LibraryModel()\n lib2.name = 'Flask'\n lib2.slug = 'flask'\n lib2.is_visible = True\n lib2.language = pl.id\n lib2.homepage_url = 'http://flask.pocoo.org/'\n lib2.source_code_url = 'https://github.com/mitsuhiko/flask'\n db.session.add(lib)\n db.session.commit()\n\n tut = TutorialModel()\n tut.name = 'Choose Your Own Adventure Presentations'\n tut.slug = 'choose-your-own-adventure-presentations'\n tut.is_visible = True\n tut.language = pl.id\n tut.tutorial_url = 'https://www.twilio.com/blog/2014/11/choose-your-own-adventure-presentations-with-reveal-js-python-and-websockets.html'\n db.session.add(tut)\n db.session.commit()\n\n tut2 = TutorialModel()\n tut2.name = 'Full Stack Python'\n tut2.slug = 'full-stack-python'\n tut2.is_visible = True\n tut2.language = pl.id\n tut2.tutorial_url = 'http://www.fullstackpython.com/'\n db.session.add(tut2)\n db.session.commit()","def load(self, id):\n return self.getTable().get(id).run(self.r)","def test_database_object_can_be_created(self):\n database = generate_database_object()","def get_revision_of_object(obj):\n return getattr(obj, get_version_fieldname(obj))","def _load_obj(name):\n with open('/bigdisk/pickles/' + name, 'r') as f:\n return pickle.load(f)","def get_version(self, id):\n if id in self.loaded_vsns:\n return self.loaded_vsns[id]\n for v in self.versions:\n if v['id'] == id:\n vsn = Version.load(self.backend, self.path, v['id'], v['name'])\n self.loaded_vsns[v['id']] = vsn\n return vsn","def test_version_control_specified(self):\n # Establish version control on this database\n version = 0\n dbcontrol = ControlledSchema.create(self.engine, self.repos, version)\n self.assertEqual(dbcontrol.version, version)\n\n # Correct when we load it, too\n dbcontrol = ControlledSchema(self.engine, self.repos)\n self.assertEqual(dbcontrol.version, version)\n\n dbcontrol.drop()\n\n # Now try it with a nonzero value\n version = 10\n for i in range(version):\n self.repos.create_script('')\n self.assertEqual(self.repos.latest, version)\n\n # Test with some mid-range value\n dbcontrol = ControlledSchema.create(self.engine,self.repos, 5)\n self.assertEqual(dbcontrol.version, 5)\n dbcontrol.drop()\n\n # Test with max value\n dbcontrol = ControlledSchema.create(self.engine, self.repos, version)\n self.assertEqual(dbcontrol.version, version)\n dbcontrol.drop()","async def load(self, connection=None, reload=False, fields=None):\n skip = self.__restored__ and not reload and not fields\n if skip or self._id is None:\n return # Already loaded or won't do anything\n db = self.objects\n t = db.table\n if fields is not None:\n renamed = self.__renamed_fields__\n columns = (t.c[renamed.get(f, f)] for f in fields)\n q = sa.select(columns).select_from(t)\n else:\n q = t.select()\n q = q.where(t.c[self.__pk__] == self._id)\n state = await db.fetchone(q, connection=connection)\n await self.__restorestate__(state)","def test_version_upgrade_persistent(self):\n db_file = self.mktemp()\n db = Database.TestDB(db_file, persistent=True)\n yield db.open()\n yield db.execute(\"INSERT into TESTTYPE (KEY, VALUE) values (:1, :2)\", (\"FOO\", \"BAR\",))\n items = (yield db.query(\"SELECT * from TESTTYPE\"))\n self.assertEqual(items, ((\"FOO\", \"BAR\"),))\n db.close()\n db = None\n\n db = Database.TestDBRecreateUpgrade(db_file, persistent=True)\n yield self.inlineCallbackRaises(NotImplementedError, db.open)\n self.assertTrue(os.path.exists(db_file))\n db.close()\n db = None\n\n db = Database.TestDB(db_file, persistent=True)\n yield db.open()\n items = (yield db.query(\"SELECT * from TESTTYPE\"))\n self.assertEqual(items, ((\"FOO\", \"BAR\"),))\n db.close()","def load_database(database_type):\n f = open(\"database.p\", \"rb\")\n database = pickle.load(f)\n f.close()\n\n if database_type is \"dict\":\n return database\n elif database_type is \"list\":\n return database.values()","def load_player(player: Player) -> bool:\n with engine.connect() as conn:\n\n result = conn.execute(\n select([player_table]).where(player_table.c.steamid==player.steamid)\n )\n player_data = result.first()\n if player_data is None:\n return False\n player._level = player_data.level\n player._xp = player_data.xp\n player.credits = player_data.credits\n\n result = conn.execute(\n select([skill_table]).where(skill_table.c.steamid==player.steamid)\n )\n for skill_data in result:\n skill = player.get_skill(skill_data.key)\n if skill is not None:\n skill.level = skill_data.level\n skill._db_id = skill_data.id\n\n return True","def db_for_read(self, model, **hints):\n if model._meta.app_label == 'compras':\n return 'db2'\n return None","def load_db(file):\n if os.path.isfile(file):\n try:\n start = time.time()\n db = []\n with open(file, 'r') as f:\n for item in json_lines.reader(f):\n db.append(item)\n stop = time.time() - start\n print(\"load_db time: \", stop, 'sec')\n return db\n except Exception as e:\n print(file, \"is probably corrupted. Creating empty db now...\")\n DbManager.erase_db(file)\n raise e\n\n else:\n # corrupt...\n print(\"database not found. creating new\")\n DbManager.new_db(file)","def get(**kwargs):\n try:\n object = ObjectDB.objects.get(**kwargs)\n except ObjectDB.DoesNotExist:\n object = None\n\n return object","def test_reload_if_needed(self):\n self.db.storage = MagicMock()\n self.db.storage.list.return_value = [make_package(factory=SQLPackage)]\n self.db.reload_if_needed()\n count = self.sql.query(SQLPackage).count()\n self.assertEqual(count, 1)","def load_variant(self, variant_obj):\n # LOG.debug(\"Loading variant %s\", variant_obj['_id'])\n try:\n result = self.variant_collection.insert_one(variant_obj)\n except DuplicateKeyError as err:\n raise IntegrityError(\"Variant %s already exists in database\", variant_obj[\"_id\"])\n return result","def _get_obj(model_class, obj_id, creating=False):\n try:\n obj = ImportedObjects.get_object_from_old_pk(\n model_class, obj_id\n )\n return obj, False\n except ImportedObjectDoesNotExist:\n obj = None\n if creating:\n obj = model_class()\n logger.info(\n '{} class ({}) not found'.format(\n model_class, obj_id\n )\n )\n return obj, True","def loadObj(name):\n\n with open(name + '.pkl', 'rb') as f:\n return pickle.load(f)","def __getitem__(self, dbname):\n return Database(dbname=dbname, connection=self)","def test_fetch_one_version():\n sample_uuid = get_sample_id()\n version = 1\n response = requests.get(f'http://localhost:5000/api/persons/{sample_uuid}/{version}')\n data = response.json()\n\n assert response.status_code == 200\n for field in FIELDS:\n assert field in data","def __init__(self, url=None, version=\"1.0\"):\n dalquery.DALResults.__init__(self, url, \"vaoreg\", version)","def test_save_reload(self):\n base = BaseModel()\n idd = base.id\n base.name = \"betty\"\n base.save()\n storage.reload()\n key = \"BaseModel.{}\".format(idd)\n objs = storage.all()[key]\n self.assertTrue(hasattr(objs, \"name\"))\n self.assertTrue(objs.name == \"betty\")\n self.assertTrue(os.path.exists('file.json'))","def fetch_obj(type, id, error=404, new_id=False):\n if id is None:\n abort(error)\n obj_q = Session.query(type)\n obj = obj_q.get(int(id))\n #else:\n # obj = obj_q.filter(type.ID==int(id)).first()\n\n if obj is None:\n abort(error)\n return obj","def test_load_database_after_pickling(tmp_path):\n path = tmp_path / \"test.db\"\n database = load_database(path_or_database=path, fast_logging=False)\n database = pickle.loads(pickle.dumps(database))\n assert hasattr(database.engine, \"connect\")","def test_load_model(base_bertopic):\n base_bertopic.save(\"test\")\n loaded_bertopic = BERTopic.load(\"test\")\n assert type(base_bertopic) == type(loaded_bertopic)","def test_reloading_from_disk_has_same_value_id(dbdiskrepo):\n original = fit_model()\n loaded = p.load_proxy(original.artifact.id)\n\n assert loaded.artifact.value_id == p.hash(loaded.artifact.value)\n assert loaded.artifact.value_id == original.artifact.value_id\n assert loaded.artifact.id == original.artifact.id","def load_model():\n logger.info('load_model called')\n return 1","def load_obj(name):\r\n with open('../pickle/' + name + '.pkl', 'rb') as fout:\r\n return pickle.load(fout)\r\n # end with\r","def test4ValidEntity(id):\n object = None\n try:\n object = ndb.Key(urlsafe=id).get()\n except Exception, e:\n if e.__class__.__name__ == ProtocolBufferDecodeError:\n object = None\n return object","def test_model_get(self):\n response = self.client().get('/model')\n self.assertEqual(response.status_code, 200)\n loaded_model = Model.from_json(response.data.decode())\n self.assertEqual(loaded_model, self.data_manipulation.get_latest_model())\n\n # All versions are removed\n self.data_manipulation.versions = {}\n\n other_response = self.client().get('/model')\n self.assertEqual(other_response.status_code, 404)","def test_persistence_old_model(self):\n loaded = PoincareModel.load(datapath('poincare_test_3.4.0'))\n self.assertEqual(loaded.kv.syn0.shape, (239, 2))\n self.assertEqual(len(loaded.kv.vocab), 239)\n self.assertEqual(loaded.size, 2)\n self.assertEqual(len(loaded.all_relations), 200)","def db_version(engine):\n return IMPL.db_version(engine)","def test_fetch(self):\n pkg = make_package(factory=DynamoPackage)\n self._save_pkgs(pkg)\n saved_pkg = self.db.fetch(pkg.filename)\n self.assertEqual(saved_pkg, pkg)","def dbRead(dbPoint):\n raise NotImplementedError('dbRead in simu mode')","def load_model(self, **params):\n \t# file_name = params['name']\n # return pickle.load(gzip.open(file_name, 'rb'))","def import_datamodel(database: Database) -> None:\n # The coverage measurement of the behave feature tests is unstable. Most of the time it reports the last two lines\n # as covered, sometimes not. It's unclear why. To prevent needless checking of the coverage report coverage\n # measurement of the last two lines and the if-statement has been turned off.\n data_model_path = pathlib.Path(__file__).resolve().parent.parent / \"data\" / \"datamodel.json\"\n with data_model_path.open() as json_data_model:\n data_model = json.load(json_data_model)\n if latest := latest_datamodel(database): # pragma: no-cover behave\n del latest[\"timestamp\"]\n del latest[\"_id\"]\n if data_model == latest: # pragma: no cover-behave\n logging.info(\"Skipping loading the data model; it is unchanged\")\n return\n insert_new_datamodel(database, data_model) # pragma: no-cover behave\n logging.info(\"Data model loaded\") # pragma: no-cover behave","def get_object(self, pool_name, object_name):\n return self.get_object_and_version(pool_name, object_name)[0]","def get(entity, name=None, version=None, lineage=None):","def test_new_style_with_version(self):\n self.assertIsNotNone(parse_arxiv_id('1202.1234v1'))\n self.assertIsNotNone(parse_arxiv_id('1203.12345v1'))\n self.assertIsNotNone(parse_arxiv_id('1203.12345v12'))","def _database(self):\n ...","def load_index(self, fn):\n name = fn.split('.pkl')[0]\n return utils.load_obj(name)","def test_min_version(self):\n properties_to_set = {\"version\": \"1.0.1\"}\n properties_serialized = {\"version\": \"1.0.1\"}\n\n instance = ClassWithMinVersion()\n instance.version = properties_to_set[\"version\"]\n instance_serialized = instance.to_dict()\n\n instance2 = ClassWithMinVersion()\n # assign from dictionary\n instance2.from_dict(properties_serialized)\n instance2_serialized = instance2.to_dict()\n self.assertEqual(instance_serialized, instance2_serialized)","def _load_version(cls, unpickler, version):\n obj = unpickler.load()\n return TransformerChain(obj._state[\"steps\"])","def get_document(self, docid):\n try:\n return self.sql_session.query(Document).get(docid)\n except OperationalError:\n raise IOError(\"Sorry, this database is incompatible with the \"\n \"current version of Luminoso. If you want, you can \"\n \"delete the model directory and start again.\")","def load(self):\n\n raise NotImplementedError","def _load (self):\n\n cursor = self._exec (self.select)\n rows = cursor.fetchall ()\n if not rows:\n return None\n\n expires, pickled_data = rows[0]\n data = pickle.loads (pickled_data)\n return data, expires","def test_model_save_and_load(self):\r\n tm0 = TestModel.create(count=8, text='123456789')\r\n tm1 = TestModel.create(count=9, text='456789')\r\n tms = TestModel.all([tm0.vid, tm1.vid])\r\n\r\n assert len(tms) == 2\r\n \r\n for cname in tm0._columns.keys():\r\n self.assertEquals(getattr(tm0, cname), getattr(tms[0], cname))\r\n \r\n tms = TestModel.all([tm1.vid, tm0.vid])\r\n assert tms[0].vid == tm1.vid \r\n assert tms[1].vid == tm0.vid","def _object_type(self, path):\n query = self.session.query(Collection).filter(Collection.name == path)\n if query.first():\n return Collection\n try:\n self.session.data_objects.get(path)\n return DataObject\n except DataObjectDoesNotExist:\n return None","def load(self, rec, validate=True, results=None, id=None):\n if not results:\n results = self._mkloadlog()\n errs = []\n\n # the input is a versioned Resource record; convert it into its three parts for the three\n # collections (record, versions, releaseSets)\n try:\n parts = self.tormm.convert(rec, validate=False)\n except (ValueError, ValidationError) as ex:\n return results.add(id or json.dumps({'@id': rec.get('@id','?')}), ex)\n\n for prop in \"record version releaseSet\".split():\n if prop not in parts or not isinstance(parts[prop], Mapping):\n errs.append(\n ValidationError(\"Failed to extract %s record from input NERDm Resource\" % prop)\n )\n if errs:\n if id is None:\n id = json.dumps({'@id': rec.get('@id','?')})\n return results.add(id, errs)\n \n # now load the versioned record first; if that's successful, we'll load the others\n\n # determine the versions udpate key\n try:\n key = self._get_upd_key(parts['version'])\n id = json.dumps(key)\n except KeyError as ex:\n if id is None:\n id = json.dumps({'@id': '?'})\n return results.add(id, RecordIngestError(\"Data is missing input key value, @id\"))\n\n if id is None:\n id = key\n\n # validate the versions record (if requested)\n errs = None\n if validate:\n schemauri = parts['version'].get(\"_schema\")\n if not schemauri:\n schemauri = self._schema\n\n errs = self.validate(parts['version'], schemauri)\n if errs:\n return results.add(id, errs)\n\n # load the version record\n try:\n if self.load_data(parts['version'], key, self._get_onupdate(parts['version'])):\n results.add(id, None)\n except Exception as ex:\n errs = [ex]\n return results.add(id, errs)\n \n\n # now (conditionally) load the other parts. (These will not get loaded if the version is not\n # new enough)\n self.lateloadr.load(parts['record'], validate, results, key)\n self.relloadr.load(parts['releaseSet'], validate, results, key)\n return results","def test_load_from_v4(self) -> None:\n self.save_new_valid_exploration(\n 'Exp1', 'user@example.com', end_state_name='End')\n collection = collection_domain.Collection.from_yaml(\n 'cid', self.YAML_CONTENT_V4)\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)","def load(self):\n pass","def load(self):\n pass","def load(self):\n pass","def load(self):\n pass","def get_original_version(self, reebill):\n result = Session().query(ReeBill).filter_by(\n reebill_customer_id=reebill.reebill_customer_id,\n sequence=reebill.sequence, version=0).one()\n if reebill.version == 0:\n assert result is reebill\n return result","def read(self, key: str):\n if self._json_to_dict():\n curr_time = datetime.now().timestamp()\n if(self.db_data[key][1]['expiration_time'] == -1) or \\\n (curr_time < self.db_data[key][1]['expiration_time']):\n if key in self.db_data.keys():\n return(self.db_data[key])\n else:\n print(\"Object with\", key, \"does not exist.\")\n return False\n else:\n print(\"Object Life Expired\")\n return False\n else:\n return False","def load_object(self, name: str):\r\n with open_(self._path_for_pickle(name), \"rb\") as f:\r\n return dill.load(f)","def test_load_from_v1(self) -> None:\n self.save_new_valid_exploration(\n 'Exp1', 'user@example.com', end_state_name='End')\n collection = collection_domain.Collection.from_yaml(\n 'cid', self.YAML_CONTENT_V1)\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)","def get_or_create(self, orm, obj):\n try:\n dth = self.get()\n if dth:\n obj.FIELDS.update({'indexcol': dth.indexcol})\n self.save(orm, obj)\n return self.get()\n except:\n raise MchCriticalError(Exception('Death cannot be saved and fetched'))\n return False","def test_min_client(self):\n for version in Version.objects.filter(pk__gte=self.version_1_2_0):\n appversion = version.apps.all()[0]\n appversion.min = AppVersion.objects.get(pk=325) # 3.7a5\n appversion.save()\n\n version, file = self.get('', '3070000005000', # 3.7a5pre\n self.app, self.platform)\n assert version == self.version_1_1_3","def test_loqusdb_wrong_version(loqus_exe):\n # GIVEN a loqusdb version < 2.5\n loqus_extension = LoqusDB(loqusdb_binary=loqus_exe, version=1.0)\n # WHEN instantiating an adapter\n with pytest.raises(SyntaxError):\n # THEN assert a syntax error is raised since version is wrong\n loqus_extension.version_check()","def get_revision_heaviest_tenant_one(database_file_path):\n # remove the line below in case you have implemented the query.\n raise NotImplementedError\n\n query = \"\"\"\n \"\"\"\n\n return _fetch_result_from_database(query, database_file_path)","def _set_version(self, version):\n with self.db.atomic():\n JambiModel.delete().execute()\n JambiModel.create(ref=str(version))\n self.logger.debug('Set jambi version to {}'.format(version))","def load_vets():\n\n print(\"Vets\")\n\n Vet.query.delete()\n\n with open(\"seed_data/vet_seed.psv\") as vets:\n for row in vets:\n user_id, grad_year, specialty = row.strip().split(\"|\")\n\n vet = Vet(\n user_id = user_id,\n grad_year = datetime.datetime.strptime(grad_year, \"%d-%b-%Y\"),\n specialty = specialty\n )\n\n db.session.add(vet)\n\n db.session.commit()","def inspect(self):\n self.db.connect()\n result = None\n try:\n jambi_versions = JambiModel.select().limit(1)\n if any(jambi_versions):\n field = jambi_versions[0].ref\n try:\n result = int(field)\n except ValueError:\n self.logger.error('Database current version \"{}\" is not '\n 'valid'.format(jambi_versions[0].ref))\n self.logger.info('Your database is at version '\n '{}'.format(field))\n else:\n self.logger.info('This database hasn\\'t been migrated yet')\n except ProgrammingError:\n self.logger.info('Run \"init\" to create a jambi version table')\n finally:\n self.db.close()\n return result","def object_for(objectid):"],"string":"[\n \"def _load_version(cls, unpickler, version):\\n model = unpickler.load()\\n if version == 0:\\n feature = model._state['features']\\n model._state['output_column_name'] = 'extracted.' + feature\\n return model\",\n \"def _load_version():\\n version = session.get('version')\\n\\n if version is None:\\n g.version = None\\n else:\\n g.version = version\",\n \"def load(cls, backend, path, obj):\\n b = backend\\n id = obj['id']\\n name = obj['name']\\n desc = obj['description']\\n url = obj['url']\\n path = os.path.join(path, id)\\n\\n # Load the index.json file.\\n idx = b.read_json(os.path.join(path, 'index.json'))\\n if idx['ApiVersion'] != 0:\\n return None\\n\\n versions = []\\n for vsn_obj in idx['Versions']:\\n # TODO: Maybe check if the version file exists?\\n versions.append(dict(\\n id=vsn_obj['Id'],\\n name=vsn_obj['Name'],\\n ))\\n\\n return cls(b, id, name, desc, url, path, versions)\",\n \"def retrieve_from_db(self):\\n pass\",\n \"def _load_vdb_with_mode(cls, vdb, mode): \\n # {{\\n db = anydbm.open(vdb.filename, mode)\\n try:\\n if db[\\\"--Reserved--type\\\"] != vdb.type:\\n raise ValueError(\\\"Not a %s database\\\" % (vdb.type,))\\n except KeyError:\\n raise ValueError(\\\"Not a recognized database\\\")\\n vdb.db = db\\n # }}\",\n \"def test_quest_load_version_fail(testing_quest_page):\\n testing_quest_page.save()\\n\\n # fetch the data\\n doc = testing_quest_page.doc_ref.get()\\n data = testing_quest_page.storage_model.parse_obj(doc.to_dict())\\n\\n # mess with the version\\n data.version = str(VersionInfo.parse(data.version).bump_major())\\n testing_quest_page.doc_ref.set(data.dict())\\n\\n # try to load with the bad version\\n with pytest.raises(QuestLoadError):\\n testing_quest_page.load()\\n\\n # cleanup\\n testing_quest_page.delete()\",\n \"def checkVersions():\\n item = Item(fromScene=True)\\n\\n for ns, componentMData in item.components.iteritems():\\n if ns == 'cam':\\n # todo tratar versoes da camera\\n continue\\n\\n if componentMData['assembleMode'] == 'reference':\\n refComponent = ReferenceComponent(ns, componentMData, parent=item)\\n refComponent.checkDBForNewVersion()\\n\\n elif componentMData['assembleMode'] == 'xlo':\\n xloComponent = XloComponent(ns, componentMData, parent=item)\\n xloComponent.checkDBForNewVersion()\\n xloComponent.checkDBForNewCacheVersion()\\n\\n elif componentMData['assembleMode'] == 'cache':\\n cacheComponent = CacheComponent(ns, componentMData, parent=item)\\n cacheComponent.checkDBForNewVersion()\\n\\n item.putDataToDB()\",\n \"def test_model_by_version_get(self):\\n\\n # Firstly, find existing version - latest\\n response = self.client().get('/model')\\n latest_model = Model.from_json(response.data.decode())\\n latest_version = latest_model.version\\n\\n # Accesses latest model\\n response = self.client().get('/models/'+str(latest_version))\\n self.assertEqual(response.status_code, 200)\\n loaded_model = Model.from_json(response.data.decode())\\n self.assertEqual(loaded_model.version, latest_version)\\n self.assertEqual(loaded_model, latest_model)\\n\\n # Accesses random model version\\n random_version = random.choice(list(self.data_manipulation.versions.keys()))\\n random_model = self.data_manipulation.versions[random_version]\\n response = self.client().get('/models/'+str(random_version))\\n self.assertEqual(response.status_code, 200)\\n loaded_model = Model.from_json(response.data.decode())\\n self.assertEqual(loaded_model.version, random_version)\\n self.assertEqual(loaded_model, random_model)\\n\\n # Random version is removed\\n del self.data_manipulation.versions[random_version]\\n response = self.client().get('/models/'+str(random_version))\\n self.assertEqual(response.status_code, 404)\",\n \"def test_get_entity_version(self):\\n self.metadata.create_or_update(data=self.create)\\n\\n # Find by name\\n res_name = self.metadata.get_by_name(\\n entity=Dashboard, fqn=self.entity.fullyQualifiedName\\n )\\n res = self.metadata.get_entity_version(\\n entity=Dashboard, entity_id=res_name.id.__root__, version=0.1\\n )\\n\\n # check we get the correct version requested and the correct entity ID\\n assert res.version.__root__ == 0.1\\n assert res.id == res_name.id\",\n \"def load(cls, id):\\n key = cls.get_key_prefix()+\\\"#\\\"+str(id)\\n src = dal_get(key)\\n logger.debug( \\\"LOAD %s %s %s\\\", str(key), str(id), str(src))\\n if src == None:\\n raise cls.NotExist(\\\"No instance could be found with ID: \\\"+str(id))\\n result = dal_retrieve(src)\\n result = cls._from_dict(result)\\n return result\",\n \"def upgrade_to_1():\\n config.db.singletons.insert_one({'_id': 'version', 'database': 1})\",\n \"def load_pkl(self, name, file_object=None):\\n if file_object:\\n f = file_object\\n else:\\n f = gzip.open(name, 'rb')\\n temp = pickle.load(f)\\n if temp.ht_version < HT_OLD_COMPAT_VERSION:\\n raise ValueError('Version of ' + name + ' is ' + str(temp.ht_version)\\n + ' which is not at least ' +\\n str(HT_OLD_COMPAT_VERSION))\\n # assert temp.ht_version >= HT_COMPAT_VERSION\\n params = temp.params\\n self.hashbits = temp.hashbits\\n self.depth = temp.depth\\n if hasattr(temp, 'maxtimebits'):\\n self.maxtimebits = temp.maxtimebits\\n else:\\n self.maxtimebits = _bitsfor(temp.maxtime)\\n if temp.ht_version < HT_COMPAT_VERSION:\\n # Need to upgrade the database.\\n print(\\\"Loading database version\\\", temp.ht_version,\\n \\\"in compatibility mode.\\\")\\n # Offset all the nonzero bins with one ID count.\\n temp.table += np.array(1 << self.maxtimebits).astype(np.uint32) * (\\n temp.table != 0)\\n temp.ht_version = HT_VERSION\\n self.table = temp.table\\n self.ht_version = temp.ht_version\\n self.counts = temp.counts\\n self.names = temp.names\\n self.hashesperid = np.array(temp.hashesperid).astype(np.uint32)\\n self.dirty = False\\n self.params = params\",\n \"def _internal_load(self, modelcls, key, result=None):\\n assert result is None\\n riak_object = self.riak_object(modelcls, key)\\n yield riak_object.reload()\\n was_migrated = False\\n\\n # Run migrators until we have the correct version of the data.\\n while riak_object.get_data() is not None:\\n data_version = riak_object.get_data().get('$VERSION', None)\\n if data_version == modelcls.VERSION:\\n obj = modelcls(self, key, _riak_object=riak_object)\\n obj.was_migrated = was_migrated\\n returnValue(obj)\\n migrator = modelcls.MIGRATOR(modelcls, self, data_version)\\n riak_object = migrator(riak_object).get_riak_object()\\n was_migrated = True\\n returnValue(None)\",\n \"def test_fetch(self):\\n pkg = make_package(factory=SQLPackage)\\n self.sql.add(pkg)\\n saved_pkg = self.db.fetch(pkg.filename)\\n self.assertEqual(saved_pkg, pkg)\",\n \"def load(self):\\n db = CrawlDBI.DBI(dbtype='crawler')\\n if self.rowid is not None:\\n rows = db.select(table='checkables',\\n fields=['rowid',\\n 'path',\\n 'type',\\n 'cos',\\n 'cart',\\n 'ttypes',\\n 'checksum',\\n 'last_check',\\n 'fails',\\n 'reported'],\\n where=\\\"rowid = ?\\\",\\n data=(self.rowid,))\\n else:\\n rows = db.select(table='checkables',\\n fields=['rowid',\\n 'path',\\n 'type',\\n 'cos',\\n 'cart',\\n 'ttypes',\\n 'checksum',\\n 'last_check',\\n 'fails',\\n 'reported'],\\n where=\\\"path = ?\\\",\\n data=(self.path,))\\n if 0 == len(rows):\\n self.in_db = False\\n elif 1 == len(rows):\\n self.in_db = True\\n rz = list(rows[0])\\n self.rowid = rz.pop(0)\\n self.path = rz.pop(0)\\n self.type = rz.pop(0)\\n self.cos = rz.pop(0)\\n self.cart = rz.pop(0)\\n self.ttypes = rz.pop(0)\\n self.checksum = rz.pop(0)\\n self.last_check = rz.pop(0)\\n try:\\n self.fails = rz.pop(0)\\n except IndexError:\\n self.fails = 0\\n try:\\n self.reported = rz.pop(0)\\n except IndexError:\\n self.reported = 0\\n self.dirty = False\\n else:\\n raise StandardError(\\\"There appears to be more than one copy \\\" +\\n \\\"of %s in the database\\\" % self)\\n\\n db.close()\",\n \"def load_model(self) -> Any:\",\n \"def get_object(id):\",\n \"def on_get_version(self, req, resp, version, **kwargs):\\n instance = self.get_object(**kwargs)\\n version = instance.load_version(version)\\n if not version:\\n raise falcon.HTTPNotFound()\\n resp.json(**version.as_resource)\",\n \"def _fetch_old_version(self) -> None:\\n if self.version is None:\\n try:\\n r = fetch(self.api + '?version&format=json')\\n try:\\n d = r.json()\\n except JSONDecodeError:\\n # Fallback for old versions which didn't wrap help in json\\n d = {'error': {'*': r.text}}\\n\\n self.version = list(filter(\\n lambda x: x.startswith('MediaWiki'),\\n (line.strip()\\n for line in d['error']['*'].split('\\\\n'))))[0].split()[1]\\n except Exception:\\n pass\\n else:\\n self.version = MediaWikiVersion(self.version)\",\n \"def load_or_create_db(self):\\n try:\\n with open(self._filename, 'rb') as f:\\n self.db = pickle.load(f)\\n except FileNotFoundError:\\n pass\",\n \"def from_db_value(self, value, *args):\\n if value is not None:\\n try:\\n value = dbsafe_decode(value, self.compress)\\n except Exception:\\n # If the value is a definite pickle; and an error is raised in\\n # de-pickling it should be allowed to propogate.\\n if isinstance(value, PickledObject):\\n raise\\n else:\\n if isinstance(value, _ObjectWrapper):\\n return value._obj\\n return value\",\n \"def test_load(self):\\n kwargs = {\\\"url\\\": \\\"my.url\\\", \\\"expire\\\": 7237}\\n pkg = make_package(**kwargs)\\n # Due to some rounding weirdness in old Py3 versions, we need to remove\\n # the microseconds to avoid a flappy test.\\n # See: https://bugs.python.org/issue23517\\n pkg.last_modified = pkg.last_modified.replace(microsecond=0)\\n self.db.save(pkg)\\n\\n loaded = self.db.fetch(pkg.filename)\\n self.assertEqual(loaded.name, pkg.name)\\n self.assertEqual(loaded.version, pkg.version)\\n self.assertEqual(loaded.filename, pkg.filename)\\n self.assertEqual(loaded.last_modified, pkg.last_modified)\\n self.assertEqual(loaded.summary, pkg.summary)\\n self.assertEqual(loaded.data, kwargs)\",\n \"def _from_catalog(self):\\n if self.dbconn.version < 90100:\\n return\\n for ext in self.fetch():\\n self[ext.key()] = ext\",\n \"def api_db_load(vend, buy, db_compare=False, compressed=True):\\r\\n #находим последнюю сжатую базу\\r\\n if compressed:\\r\\n db_conv_time = last_db_time_get()\\r\\n if not db_compare:\\r\\n if convert_time(db_conv_time, 'm') > 9: #9\\r\\n print(\\\"Old database...\\\")\\r\\n #собираем ссылку\\r\\n link = 'https://api.originsro.org/api/v1/market/list?api_key='\\r\\n api_key = ''\\r\\n #делаем вызов и сохраняем получаемое в переменной\\r\\n response = rq.get('{}{}'.format(link, api_key))\\r\\n #создаем путь/имя для нашей новой базы\\r\\n latest_file = '{}\\\\\\\\jsons\\\\\\\\DB_{}.json.gz'.format(db_folder_path, now.strftime(\\\"%d-%m-%Y_%H-%M-%S\\\"))\\r\\n #сохраняем нашу новую базу\\r\\n compress_json.dump(response.text, latest_file)\\r\\n print('compressed db saved')\\r\\n #и сразу же загружаем\\r\\n #actual_db = compress_json.local_load(latest_file)\\r\\n #находим 2 по старости дб (то есть ту, которая была перед нашей только что выкачанной)\\r\\n previous_db = sorted(glob.iglob('{}\\\\\\\\jsons\\\\\\\\DB_*.json.gz'.format(db_folder_path)), key=os.path.getctime)[-2]\\r\\n #распаковываем его\\r\\n #previous_db_uncompressed = compress_json.local_load(previous_db)\\r\\n #создаем временные листы с данными\\r\\n #из прошлой бд\\r\\n pre_vendor_shops = []\\r\\n pre_buy_shops = []\\r\\n get_vend_data(previous_db, pre_vendor_shops, pre_buy_shops)\\r\\n #из новой бд\\r\\n print(latest_file)\\r\\n get_vend_data(latest_file, vend, buy)\\r\\n #fill demand file\\r\\n compare_data(pre_vendor_shops, vend)\\r\\n compare_data(pre_buy_shops, buy)\\r\\n print('demand refreshed')\\r\\n else:\\r\\n print('Database ok...')\\r\\n latest_file = max(glob.glob('{}\\\\\\\\jsons\\\\\\\\DB_*.json.gz'.format(db_folder_path)), key=os.path.getctime)\\r\\n get_vend_data(latest_file, vend, buy)\\r\\n else:\\r\\n compare_db()\\r\\n else:\\r\\n #находим самую свежую базу из имеющихся\\r\\n latest_file = max(glob.glob('{}\\\\\\\\jsons\\\\\\\\DB_*.json'.format(db_folder_path)), key=os.path.getctime)\\r\\n #Загрузка БД и ее обновление\\r\\n with open(latest_file, encoding=\\\"utf8\\\") as json_file:\\r\\n #делаем удобное обозначение той же базы\\r\\n api_db = json.load(json_file)['generation_timestamp']\\r\\n db_time = datetime.datetime.strptime(api_db, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\r\\n if not db_compare:\\r\\n #если базе больше 10 минут, надо обновить\\r\\n if convert_time(db_time, 'm') > 10: #9\\r\\n print(\\\"Old database...\\\")\\r\\n link = 'https://api.originsro.org/api/v1/market/list?api_key='\\r\\n api_key = 'r3bkd0q8umxhuj75ahtvwpgkd3yzi3rm'\\r\\n response = rq.get('{}{}'.format(link, api_key))\\r\\n latest_file = '{}\\\\\\\\jsons\\\\\\\\DB_{}.json'.format(db_folder_path, now.strftime(\\\"%d-%m-%Y_%H-%M-%S\\\"))\\r\\n #создаем новую бд с названием из latest_file\\r\\n with open(latest_file, \\\"w+\\\", encoding=\\\"utf8\\\") as new_file:\\r\\n new_file.write(response.text)\\r\\n #создаем новую, сжатую, бд\\r\\n #compress_json.dump(response.text, latest_file)\\r\\n #находим второй по новости файл, то есть прошлую бд\\r\\n previous_db = sorted(glob.iglob('{}\\\\\\\\jsons\\\\\\\\DB_*.json'.format(db_folder_path)), key=os.path.getctime)[-2]\\r\\n #создаем временные листы с данными\\r\\n #из прошлой бд\\r\\n pre_vendor_shops = []\\r\\n pre_buy_shops = []\\r\\n get_vend_data(previous_db, pre_vendor_shops, pre_buy_shops)\\r\\n #из новой бд\\r\\n get_vend_data(latest_file, vend, buy)\\r\\n #fill demand file\\r\\n compare_data(pre_vendor_shops, vend)\\r\\n compare_data(pre_buy_shops, buy)\\r\\n else:\\r\\n print('Database ok...')\\r\\n get_vend_data(latest_file, vend, buy)\\r\\n else:\\r\\n compare_db()\",\n \"def test_fetch(self):\\n pkg = make_package()\\n self.db.save(pkg)\\n saved_pkg = self.db.fetch(pkg.filename)\\n self.assertEqual(saved_pkg, pkg)\",\n \"def get(self, bento_name, bento_version):\",\n \"def _get_version(self):\",\n \"def load_obj(name):\\n with open('../../data/' + name + '.pkl', 'rb') as f:\\n return pickle.load(f)\",\n \"def load_obj(name):\\n with open('../../data/' + name + '.pkl', 'rb') as f:\\n return pickle.load(f)\",\n \"def db_version():\\n return IMPL.db_version()\",\n \"def _load(self, create):\\n if not self.db.has_key('size'):\\n if create:\\n # It's a new database, initialize the special keys\\n self.db['head'] = 0\\n self.db['count'] = 0\\n self.db['size'] = self.newSize\\n\\n # Cache the special keys\\n self.head = self.db['head']\\n self.count = self.db['count']\\n self.size = self.db['size']\\n self._loaded = True\",\n \"def load(self):\",\n \"def test_version_upgrade_nonpersistent(self):\\n\\n db_file = self.mktemp()\\n\\n db = Database.TestDB(db_file)\\n yield db.open()\\n yield db.execute(\\\"INSERT into TESTTYPE (KEY, VALUE) values (:1, :2)\\\", (\\\"FOO\\\", \\\"BAR\\\",))\\n items = (yield db.query(\\\"SELECT * from TESTTYPE\\\"))\\n self.assertEqual(items, ((\\\"FOO\\\", \\\"BAR\\\"),))\\n db.close()\\n db = None\\n\\n db = Database.TestDBRecreateUpgrade(db_file)\\n yield self.inlineCallbackRaises(Database.TestDBRecreateUpgrade.RecreateDBException, db.open)\\n items = (yield db.query(\\\"SELECT * from TESTTYPE\\\"))\\n self.assertEqual(items, ())\\n db.close()\",\n \"def reconstruct(self):\\n if os.path.exists(self.dbname):\\n with open(self.dbname, mode='rb') as db:\\n self.cache = pickle.load(db)\",\n \"def load():\\n pr = PLAPIResource()\\n pr.name = 'Programming Languages'\\n pr.uri = 'programming-languages'\\n db.session.add(pr)\\n db.session.commit()\\n\\n pd = PLAPIResource()\\n pd.name = 'Paradigms'\\n pd.uri = 'paradigms'\\n db.session.add(pd)\\n db.session.commit()\\n\\n \\\"\\\"\\\"\\n pt = PLAPIResource()\\n pt.name = 'Tutorials'\\n pt.uri = 'tutorials'\\n db.session.add(pt)\\n db.session.commit()\\n \\\"\\\"\\\"\\n\\n\\n pl = ProgrammingLanguageModel()\\n pl.name = 'Python'\\n pl.slug = 'python'\\n pl.homepage_url = 'https://www.python.org/'\\n pl.is_visible = True\\n db.session.add(pl)\\n db.session.commit()\\n\\n pl2 = ProgrammingLanguageModel()\\n pl2.name = 'Swift'\\n pl2.slug = 'swift'\\n pl2.homepage_url = 'https://developer.apple.com/swift/'\\n pl2.is_visible = True\\n db.session.add(pl2)\\n db.session.commit()\\n\\n pl3 = ProgrammingLanguageModel()\\n pl3.name = 'Ruby'\\n pl3.slug = 'ruby'\\n pl3.homepage_url = 'https://www.ruby-lang.org/'\\n pl3.is_visible = True\\n db.session.add(pl3)\\n db.session.commit()\\n\\n prdgm1 = ParadigmModel()\\n prdgm1.name = 'Imperative'\\n prdgm1.slug = 'imperative'\\n prdgm1.is_visible = True\\n db.session.add(prdgm1)\\n db.session.commit()\\n\\n prdgm2 = ParadigmModel()\\n prdgm2.name = 'Functional'\\n prdgm2.slug = 'functional'\\n prdgm2.is_visible = True\\n db.session.add(prdgm2)\\n db.session.commit()\\n\\n lib = LibraryModel()\\n lib.name = 'Django'\\n lib.slug = 'django'\\n lib.is_visible = True\\n lib.language = pl.id\\n lib.homepage_url = 'https://www.djangoproject.com/'\\n lib.source_code_url = 'https://github.com/django/django'\\n db.session.add(lib)\\n db.session.commit()\\n\\n lib2 = LibraryModel()\\n lib2.name = 'Flask'\\n lib2.slug = 'flask'\\n lib2.is_visible = True\\n lib2.language = pl.id\\n lib2.homepage_url = 'http://flask.pocoo.org/'\\n lib2.source_code_url = 'https://github.com/mitsuhiko/flask'\\n db.session.add(lib)\\n db.session.commit()\\n\\n tut = TutorialModel()\\n tut.name = 'Choose Your Own Adventure Presentations'\\n tut.slug = 'choose-your-own-adventure-presentations'\\n tut.is_visible = True\\n tut.language = pl.id\\n tut.tutorial_url = 'https://www.twilio.com/blog/2014/11/choose-your-own-adventure-presentations-with-reveal-js-python-and-websockets.html'\\n db.session.add(tut)\\n db.session.commit()\\n\\n tut2 = TutorialModel()\\n tut2.name = 'Full Stack Python'\\n tut2.slug = 'full-stack-python'\\n tut2.is_visible = True\\n tut2.language = pl.id\\n tut2.tutorial_url = 'http://www.fullstackpython.com/'\\n db.session.add(tut2)\\n db.session.commit()\",\n \"def load(self, id):\\n return self.getTable().get(id).run(self.r)\",\n \"def test_database_object_can_be_created(self):\\n database = generate_database_object()\",\n \"def get_revision_of_object(obj):\\n return getattr(obj, get_version_fieldname(obj))\",\n \"def _load_obj(name):\\n with open('/bigdisk/pickles/' + name, 'r') as f:\\n return pickle.load(f)\",\n \"def get_version(self, id):\\n if id in self.loaded_vsns:\\n return self.loaded_vsns[id]\\n for v in self.versions:\\n if v['id'] == id:\\n vsn = Version.load(self.backend, self.path, v['id'], v['name'])\\n self.loaded_vsns[v['id']] = vsn\\n return vsn\",\n \"def test_version_control_specified(self):\\n # Establish version control on this database\\n version = 0\\n dbcontrol = ControlledSchema.create(self.engine, self.repos, version)\\n self.assertEqual(dbcontrol.version, version)\\n\\n # Correct when we load it, too\\n dbcontrol = ControlledSchema(self.engine, self.repos)\\n self.assertEqual(dbcontrol.version, version)\\n\\n dbcontrol.drop()\\n\\n # Now try it with a nonzero value\\n version = 10\\n for i in range(version):\\n self.repos.create_script('')\\n self.assertEqual(self.repos.latest, version)\\n\\n # Test with some mid-range value\\n dbcontrol = ControlledSchema.create(self.engine,self.repos, 5)\\n self.assertEqual(dbcontrol.version, 5)\\n dbcontrol.drop()\\n\\n # Test with max value\\n dbcontrol = ControlledSchema.create(self.engine, self.repos, version)\\n self.assertEqual(dbcontrol.version, version)\\n dbcontrol.drop()\",\n \"async def load(self, connection=None, reload=False, fields=None):\\n skip = self.__restored__ and not reload and not fields\\n if skip or self._id is None:\\n return # Already loaded or won't do anything\\n db = self.objects\\n t = db.table\\n if fields is not None:\\n renamed = self.__renamed_fields__\\n columns = (t.c[renamed.get(f, f)] for f in fields)\\n q = sa.select(columns).select_from(t)\\n else:\\n q = t.select()\\n q = q.where(t.c[self.__pk__] == self._id)\\n state = await db.fetchone(q, connection=connection)\\n await self.__restorestate__(state)\",\n \"def test_version_upgrade_persistent(self):\\n db_file = self.mktemp()\\n db = Database.TestDB(db_file, persistent=True)\\n yield db.open()\\n yield db.execute(\\\"INSERT into TESTTYPE (KEY, VALUE) values (:1, :2)\\\", (\\\"FOO\\\", \\\"BAR\\\",))\\n items = (yield db.query(\\\"SELECT * from TESTTYPE\\\"))\\n self.assertEqual(items, ((\\\"FOO\\\", \\\"BAR\\\"),))\\n db.close()\\n db = None\\n\\n db = Database.TestDBRecreateUpgrade(db_file, persistent=True)\\n yield self.inlineCallbackRaises(NotImplementedError, db.open)\\n self.assertTrue(os.path.exists(db_file))\\n db.close()\\n db = None\\n\\n db = Database.TestDB(db_file, persistent=True)\\n yield db.open()\\n items = (yield db.query(\\\"SELECT * from TESTTYPE\\\"))\\n self.assertEqual(items, ((\\\"FOO\\\", \\\"BAR\\\"),))\\n db.close()\",\n \"def load_database(database_type):\\n f = open(\\\"database.p\\\", \\\"rb\\\")\\n database = pickle.load(f)\\n f.close()\\n\\n if database_type is \\\"dict\\\":\\n return database\\n elif database_type is \\\"list\\\":\\n return database.values()\",\n \"def load_player(player: Player) -> bool:\\n with engine.connect() as conn:\\n\\n result = conn.execute(\\n select([player_table]).where(player_table.c.steamid==player.steamid)\\n )\\n player_data = result.first()\\n if player_data is None:\\n return False\\n player._level = player_data.level\\n player._xp = player_data.xp\\n player.credits = player_data.credits\\n\\n result = conn.execute(\\n select([skill_table]).where(skill_table.c.steamid==player.steamid)\\n )\\n for skill_data in result:\\n skill = player.get_skill(skill_data.key)\\n if skill is not None:\\n skill.level = skill_data.level\\n skill._db_id = skill_data.id\\n\\n return True\",\n \"def db_for_read(self, model, **hints):\\n if model._meta.app_label == 'compras':\\n return 'db2'\\n return None\",\n \"def load_db(file):\\n if os.path.isfile(file):\\n try:\\n start = time.time()\\n db = []\\n with open(file, 'r') as f:\\n for item in json_lines.reader(f):\\n db.append(item)\\n stop = time.time() - start\\n print(\\\"load_db time: \\\", stop, 'sec')\\n return db\\n except Exception as e:\\n print(file, \\\"is probably corrupted. Creating empty db now...\\\")\\n DbManager.erase_db(file)\\n raise e\\n\\n else:\\n # corrupt...\\n print(\\\"database not found. creating new\\\")\\n DbManager.new_db(file)\",\n \"def get(**kwargs):\\n try:\\n object = ObjectDB.objects.get(**kwargs)\\n except ObjectDB.DoesNotExist:\\n object = None\\n\\n return object\",\n \"def test_reload_if_needed(self):\\n self.db.storage = MagicMock()\\n self.db.storage.list.return_value = [make_package(factory=SQLPackage)]\\n self.db.reload_if_needed()\\n count = self.sql.query(SQLPackage).count()\\n self.assertEqual(count, 1)\",\n \"def load_variant(self, variant_obj):\\n # LOG.debug(\\\"Loading variant %s\\\", variant_obj['_id'])\\n try:\\n result = self.variant_collection.insert_one(variant_obj)\\n except DuplicateKeyError as err:\\n raise IntegrityError(\\\"Variant %s already exists in database\\\", variant_obj[\\\"_id\\\"])\\n return result\",\n \"def _get_obj(model_class, obj_id, creating=False):\\n try:\\n obj = ImportedObjects.get_object_from_old_pk(\\n model_class, obj_id\\n )\\n return obj, False\\n except ImportedObjectDoesNotExist:\\n obj = None\\n if creating:\\n obj = model_class()\\n logger.info(\\n '{} class ({}) not found'.format(\\n model_class, obj_id\\n )\\n )\\n return obj, True\",\n \"def loadObj(name):\\n\\n with open(name + '.pkl', 'rb') as f:\\n return pickle.load(f)\",\n \"def __getitem__(self, dbname):\\n return Database(dbname=dbname, connection=self)\",\n \"def test_fetch_one_version():\\n sample_uuid = get_sample_id()\\n version = 1\\n response = requests.get(f'http://localhost:5000/api/persons/{sample_uuid}/{version}')\\n data = response.json()\\n\\n assert response.status_code == 200\\n for field in FIELDS:\\n assert field in data\",\n \"def __init__(self, url=None, version=\\\"1.0\\\"):\\n dalquery.DALResults.__init__(self, url, \\\"vaoreg\\\", version)\",\n \"def test_save_reload(self):\\n base = BaseModel()\\n idd = base.id\\n base.name = \\\"betty\\\"\\n base.save()\\n storage.reload()\\n key = \\\"BaseModel.{}\\\".format(idd)\\n objs = storage.all()[key]\\n self.assertTrue(hasattr(objs, \\\"name\\\"))\\n self.assertTrue(objs.name == \\\"betty\\\")\\n self.assertTrue(os.path.exists('file.json'))\",\n \"def fetch_obj(type, id, error=404, new_id=False):\\n if id is None:\\n abort(error)\\n obj_q = Session.query(type)\\n obj = obj_q.get(int(id))\\n #else:\\n # obj = obj_q.filter(type.ID==int(id)).first()\\n\\n if obj is None:\\n abort(error)\\n return obj\",\n \"def test_load_database_after_pickling(tmp_path):\\n path = tmp_path / \\\"test.db\\\"\\n database = load_database(path_or_database=path, fast_logging=False)\\n database = pickle.loads(pickle.dumps(database))\\n assert hasattr(database.engine, \\\"connect\\\")\",\n \"def test_load_model(base_bertopic):\\n base_bertopic.save(\\\"test\\\")\\n loaded_bertopic = BERTopic.load(\\\"test\\\")\\n assert type(base_bertopic) == type(loaded_bertopic)\",\n \"def test_reloading_from_disk_has_same_value_id(dbdiskrepo):\\n original = fit_model()\\n loaded = p.load_proxy(original.artifact.id)\\n\\n assert loaded.artifact.value_id == p.hash(loaded.artifact.value)\\n assert loaded.artifact.value_id == original.artifact.value_id\\n assert loaded.artifact.id == original.artifact.id\",\n \"def load_model():\\n logger.info('load_model called')\\n return 1\",\n \"def load_obj(name):\\r\\n with open('../pickle/' + name + '.pkl', 'rb') as fout:\\r\\n return pickle.load(fout)\\r\\n # end with\\r\",\n \"def test4ValidEntity(id):\\n object = None\\n try:\\n object = ndb.Key(urlsafe=id).get()\\n except Exception, e:\\n if e.__class__.__name__ == ProtocolBufferDecodeError:\\n object = None\\n return object\",\n \"def test_model_get(self):\\n response = self.client().get('/model')\\n self.assertEqual(response.status_code, 200)\\n loaded_model = Model.from_json(response.data.decode())\\n self.assertEqual(loaded_model, self.data_manipulation.get_latest_model())\\n\\n # All versions are removed\\n self.data_manipulation.versions = {}\\n\\n other_response = self.client().get('/model')\\n self.assertEqual(other_response.status_code, 404)\",\n \"def test_persistence_old_model(self):\\n loaded = PoincareModel.load(datapath('poincare_test_3.4.0'))\\n self.assertEqual(loaded.kv.syn0.shape, (239, 2))\\n self.assertEqual(len(loaded.kv.vocab), 239)\\n self.assertEqual(loaded.size, 2)\\n self.assertEqual(len(loaded.all_relations), 200)\",\n \"def db_version(engine):\\n return IMPL.db_version(engine)\",\n \"def test_fetch(self):\\n pkg = make_package(factory=DynamoPackage)\\n self._save_pkgs(pkg)\\n saved_pkg = self.db.fetch(pkg.filename)\\n self.assertEqual(saved_pkg, pkg)\",\n \"def dbRead(dbPoint):\\n raise NotImplementedError('dbRead in simu mode')\",\n \"def load_model(self, **params):\\n \\t# file_name = params['name']\\n # return pickle.load(gzip.open(file_name, 'rb'))\",\n \"def import_datamodel(database: Database) -> None:\\n # The coverage measurement of the behave feature tests is unstable. Most of the time it reports the last two lines\\n # as covered, sometimes not. It's unclear why. To prevent needless checking of the coverage report coverage\\n # measurement of the last two lines and the if-statement has been turned off.\\n data_model_path = pathlib.Path(__file__).resolve().parent.parent / \\\"data\\\" / \\\"datamodel.json\\\"\\n with data_model_path.open() as json_data_model:\\n data_model = json.load(json_data_model)\\n if latest := latest_datamodel(database): # pragma: no-cover behave\\n del latest[\\\"timestamp\\\"]\\n del latest[\\\"_id\\\"]\\n if data_model == latest: # pragma: no cover-behave\\n logging.info(\\\"Skipping loading the data model; it is unchanged\\\")\\n return\\n insert_new_datamodel(database, data_model) # pragma: no-cover behave\\n logging.info(\\\"Data model loaded\\\") # pragma: no-cover behave\",\n \"def get_object(self, pool_name, object_name):\\n return self.get_object_and_version(pool_name, object_name)[0]\",\n \"def get(entity, name=None, version=None, lineage=None):\",\n \"def test_new_style_with_version(self):\\n self.assertIsNotNone(parse_arxiv_id('1202.1234v1'))\\n self.assertIsNotNone(parse_arxiv_id('1203.12345v1'))\\n self.assertIsNotNone(parse_arxiv_id('1203.12345v12'))\",\n \"def _database(self):\\n ...\",\n \"def load_index(self, fn):\\n name = fn.split('.pkl')[0]\\n return utils.load_obj(name)\",\n \"def test_min_version(self):\\n properties_to_set = {\\\"version\\\": \\\"1.0.1\\\"}\\n properties_serialized = {\\\"version\\\": \\\"1.0.1\\\"}\\n\\n instance = ClassWithMinVersion()\\n instance.version = properties_to_set[\\\"version\\\"]\\n instance_serialized = instance.to_dict()\\n\\n instance2 = ClassWithMinVersion()\\n # assign from dictionary\\n instance2.from_dict(properties_serialized)\\n instance2_serialized = instance2.to_dict()\\n self.assertEqual(instance_serialized, instance2_serialized)\",\n \"def _load_version(cls, unpickler, version):\\n obj = unpickler.load()\\n return TransformerChain(obj._state[\\\"steps\\\"])\",\n \"def get_document(self, docid):\\n try:\\n return self.sql_session.query(Document).get(docid)\\n except OperationalError:\\n raise IOError(\\\"Sorry, this database is incompatible with the \\\"\\n \\\"current version of Luminoso. If you want, you can \\\"\\n \\\"delete the model directory and start again.\\\")\",\n \"def load(self):\\n\\n raise NotImplementedError\",\n \"def _load (self):\\n\\n cursor = self._exec (self.select)\\n rows = cursor.fetchall ()\\n if not rows:\\n return None\\n\\n expires, pickled_data = rows[0]\\n data = pickle.loads (pickled_data)\\n return data, expires\",\n \"def test_model_save_and_load(self):\\r\\n tm0 = TestModel.create(count=8, text='123456789')\\r\\n tm1 = TestModel.create(count=9, text='456789')\\r\\n tms = TestModel.all([tm0.vid, tm1.vid])\\r\\n\\r\\n assert len(tms) == 2\\r\\n \\r\\n for cname in tm0._columns.keys():\\r\\n self.assertEquals(getattr(tm0, cname), getattr(tms[0], cname))\\r\\n \\r\\n tms = TestModel.all([tm1.vid, tm0.vid])\\r\\n assert tms[0].vid == tm1.vid \\r\\n assert tms[1].vid == tm0.vid\",\n \"def _object_type(self, path):\\n query = self.session.query(Collection).filter(Collection.name == path)\\n if query.first():\\n return Collection\\n try:\\n self.session.data_objects.get(path)\\n return DataObject\\n except DataObjectDoesNotExist:\\n return None\",\n \"def load(self, rec, validate=True, results=None, id=None):\\n if not results:\\n results = self._mkloadlog()\\n errs = []\\n\\n # the input is a versioned Resource record; convert it into its three parts for the three\\n # collections (record, versions, releaseSets)\\n try:\\n parts = self.tormm.convert(rec, validate=False)\\n except (ValueError, ValidationError) as ex:\\n return results.add(id or json.dumps({'@id': rec.get('@id','?')}), ex)\\n\\n for prop in \\\"record version releaseSet\\\".split():\\n if prop not in parts or not isinstance(parts[prop], Mapping):\\n errs.append(\\n ValidationError(\\\"Failed to extract %s record from input NERDm Resource\\\" % prop)\\n )\\n if errs:\\n if id is None:\\n id = json.dumps({'@id': rec.get('@id','?')})\\n return results.add(id, errs)\\n \\n # now load the versioned record first; if that's successful, we'll load the others\\n\\n # determine the versions udpate key\\n try:\\n key = self._get_upd_key(parts['version'])\\n id = json.dumps(key)\\n except KeyError as ex:\\n if id is None:\\n id = json.dumps({'@id': '?'})\\n return results.add(id, RecordIngestError(\\\"Data is missing input key value, @id\\\"))\\n\\n if id is None:\\n id = key\\n\\n # validate the versions record (if requested)\\n errs = None\\n if validate:\\n schemauri = parts['version'].get(\\\"_schema\\\")\\n if not schemauri:\\n schemauri = self._schema\\n\\n errs = self.validate(parts['version'], schemauri)\\n if errs:\\n return results.add(id, errs)\\n\\n # load the version record\\n try:\\n if self.load_data(parts['version'], key, self._get_onupdate(parts['version'])):\\n results.add(id, None)\\n except Exception as ex:\\n errs = [ex]\\n return results.add(id, errs)\\n \\n\\n # now (conditionally) load the other parts. (These will not get loaded if the version is not\\n # new enough)\\n self.lateloadr.load(parts['record'], validate, results, key)\\n self.relloadr.load(parts['releaseSet'], validate, results, key)\\n return results\",\n \"def test_load_from_v4(self) -> None:\\n self.save_new_valid_exploration(\\n 'Exp1', 'user@example.com', end_state_name='End')\\n collection = collection_domain.Collection.from_yaml(\\n 'cid', self.YAML_CONTENT_V4)\\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)\",\n \"def load(self):\\n pass\",\n \"def load(self):\\n pass\",\n \"def load(self):\\n pass\",\n \"def load(self):\\n pass\",\n \"def get_original_version(self, reebill):\\n result = Session().query(ReeBill).filter_by(\\n reebill_customer_id=reebill.reebill_customer_id,\\n sequence=reebill.sequence, version=0).one()\\n if reebill.version == 0:\\n assert result is reebill\\n return result\",\n \"def read(self, key: str):\\n if self._json_to_dict():\\n curr_time = datetime.now().timestamp()\\n if(self.db_data[key][1]['expiration_time'] == -1) or \\\\\\n (curr_time < self.db_data[key][1]['expiration_time']):\\n if key in self.db_data.keys():\\n return(self.db_data[key])\\n else:\\n print(\\\"Object with\\\", key, \\\"does not exist.\\\")\\n return False\\n else:\\n print(\\\"Object Life Expired\\\")\\n return False\\n else:\\n return False\",\n \"def load_object(self, name: str):\\r\\n with open_(self._path_for_pickle(name), \\\"rb\\\") as f:\\r\\n return dill.load(f)\",\n \"def test_load_from_v1(self) -> None:\\n self.save_new_valid_exploration(\\n 'Exp1', 'user@example.com', end_state_name='End')\\n collection = collection_domain.Collection.from_yaml(\\n 'cid', self.YAML_CONTENT_V1)\\n self.assertEqual(collection.to_yaml(), self._LATEST_YAML_CONTENT)\",\n \"def get_or_create(self, orm, obj):\\n try:\\n dth = self.get()\\n if dth:\\n obj.FIELDS.update({'indexcol': dth.indexcol})\\n self.save(orm, obj)\\n return self.get()\\n except:\\n raise MchCriticalError(Exception('Death cannot be saved and fetched'))\\n return False\",\n \"def test_min_client(self):\\n for version in Version.objects.filter(pk__gte=self.version_1_2_0):\\n appversion = version.apps.all()[0]\\n appversion.min = AppVersion.objects.get(pk=325) # 3.7a5\\n appversion.save()\\n\\n version, file = self.get('', '3070000005000', # 3.7a5pre\\n self.app, self.platform)\\n assert version == self.version_1_1_3\",\n \"def test_loqusdb_wrong_version(loqus_exe):\\n # GIVEN a loqusdb version < 2.5\\n loqus_extension = LoqusDB(loqusdb_binary=loqus_exe, version=1.0)\\n # WHEN instantiating an adapter\\n with pytest.raises(SyntaxError):\\n # THEN assert a syntax error is raised since version is wrong\\n loqus_extension.version_check()\",\n \"def get_revision_heaviest_tenant_one(database_file_path):\\n # remove the line below in case you have implemented the query.\\n raise NotImplementedError\\n\\n query = \\\"\\\"\\\"\\n \\\"\\\"\\\"\\n\\n return _fetch_result_from_database(query, database_file_path)\",\n \"def _set_version(self, version):\\n with self.db.atomic():\\n JambiModel.delete().execute()\\n JambiModel.create(ref=str(version))\\n self.logger.debug('Set jambi version to {}'.format(version))\",\n \"def load_vets():\\n\\n print(\\\"Vets\\\")\\n\\n Vet.query.delete()\\n\\n with open(\\\"seed_data/vet_seed.psv\\\") as vets:\\n for row in vets:\\n user_id, grad_year, specialty = row.strip().split(\\\"|\\\")\\n\\n vet = Vet(\\n user_id = user_id,\\n grad_year = datetime.datetime.strptime(grad_year, \\\"%d-%b-%Y\\\"),\\n specialty = specialty\\n )\\n\\n db.session.add(vet)\\n\\n db.session.commit()\",\n \"def inspect(self):\\n self.db.connect()\\n result = None\\n try:\\n jambi_versions = JambiModel.select().limit(1)\\n if any(jambi_versions):\\n field = jambi_versions[0].ref\\n try:\\n result = int(field)\\n except ValueError:\\n self.logger.error('Database current version \\\"{}\\\" is not '\\n 'valid'.format(jambi_versions[0].ref))\\n self.logger.info('Your database is at version '\\n '{}'.format(field))\\n else:\\n self.logger.info('This database hasn\\\\'t been migrated yet')\\n except ProgrammingError:\\n self.logger.info('Run \\\"init\\\" to create a jambi version table')\\n finally:\\n self.db.close()\\n return result\",\n \"def object_for(objectid):\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.61055326","0.60126936","0.59640944","0.58599895","0.5854756","0.58120066","0.5810105","0.5798865","0.5735602","0.57199824","0.57042235","0.56773525","0.56663936","0.55917364","0.55864733","0.55482763","0.552244","0.55130196","0.54902387","0.54607445","0.54526514","0.54473156","0.5446195","0.54199004","0.5410973","0.5374291","0.53653705","0.53418607","0.53418607","0.53378165","0.53376967","0.53067464","0.5289473","0.52847195","0.5270394","0.52609","0.5245796","0.5244108","0.523982","0.5227349","0.52249587","0.5224289","0.5223484","0.52165717","0.52095985","0.52014","0.52008694","0.51922685","0.5191517","0.51851547","0.5184676","0.51765704","0.5162571","0.5161674","0.5156429","0.5154919","0.51534665","0.5146707","0.5136271","0.51362157","0.5132179","0.5129278","0.51283246","0.512776","0.5107042","0.5101906","0.50999886","0.509651","0.5092806","0.50744295","0.50671077","0.5066572","0.5064821","0.50578535","0.5056061","0.50541425","0.5051618","0.50498796","0.50480026","0.50466204","0.5043536","0.50432575","0.50426304","0.50417364","0.50392663","0.50392663","0.50392663","0.50392663","0.50360304","0.50344974","0.503439","0.50319546","0.50305873","0.50286186","0.5027971","0.502384","0.5021597","0.5016479","0.5016088","0.5012112"],"string":"[\n \"0.61055326\",\n \"0.60126936\",\n \"0.59640944\",\n \"0.58599895\",\n \"0.5854756\",\n \"0.58120066\",\n \"0.5810105\",\n \"0.5798865\",\n \"0.5735602\",\n \"0.57199824\",\n \"0.57042235\",\n \"0.56773525\",\n \"0.56663936\",\n \"0.55917364\",\n \"0.55864733\",\n \"0.55482763\",\n \"0.552244\",\n \"0.55130196\",\n \"0.54902387\",\n \"0.54607445\",\n \"0.54526514\",\n \"0.54473156\",\n \"0.5446195\",\n \"0.54199004\",\n \"0.5410973\",\n \"0.5374291\",\n \"0.53653705\",\n \"0.53418607\",\n \"0.53418607\",\n \"0.53378165\",\n \"0.53376967\",\n \"0.53067464\",\n \"0.5289473\",\n \"0.52847195\",\n \"0.5270394\",\n \"0.52609\",\n \"0.5245796\",\n \"0.5244108\",\n \"0.523982\",\n \"0.5227349\",\n \"0.52249587\",\n \"0.5224289\",\n \"0.5223484\",\n \"0.52165717\",\n \"0.52095985\",\n \"0.52014\",\n \"0.52008694\",\n \"0.51922685\",\n \"0.5191517\",\n \"0.51851547\",\n \"0.5184676\",\n \"0.51765704\",\n \"0.5162571\",\n \"0.5161674\",\n \"0.5156429\",\n \"0.5154919\",\n \"0.51534665\",\n \"0.5146707\",\n \"0.5136271\",\n \"0.51362157\",\n \"0.5132179\",\n \"0.5129278\",\n \"0.51283246\",\n \"0.512776\",\n \"0.5107042\",\n \"0.5101906\",\n \"0.50999886\",\n \"0.509651\",\n \"0.5092806\",\n \"0.50744295\",\n \"0.50671077\",\n \"0.5066572\",\n \"0.5064821\",\n \"0.50578535\",\n \"0.5056061\",\n \"0.50541425\",\n \"0.5051618\",\n \"0.50498796\",\n \"0.50480026\",\n \"0.50466204\",\n \"0.5043536\",\n \"0.50432575\",\n \"0.50426304\",\n \"0.50417364\",\n \"0.50392663\",\n \"0.50392663\",\n \"0.50392663\",\n \"0.50392663\",\n \"0.50360304\",\n \"0.50344974\",\n \"0.503439\",\n \"0.50319546\",\n \"0.50305873\",\n \"0.50286186\",\n \"0.5027971\",\n \"0.502384\",\n \"0.5021597\",\n \"0.5016479\",\n \"0.5016088\",\n \"0.5012112\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5590578"},"document_rank":{"kind":"string","value":"14"}}},{"rowIdx":13080,"cells":{"query":{"kind":"string","value":"A loop to test movement showing in the terminal"},"document":{"kind":"string","value":"def test_movement(self):\n running = True\n\n self.refresh_tile_maps()\n\n self.data = self.board.data\n self.board_objects = self.board.board_objects\n self.weapons = self.board.weapons\n self.rooms = self.board.rooms\n self.players = self.board.players\n self.player_cards = self.board.player_cards\n self.combined_tiles = self.board.combined_tiles\n self.weapon_tokens = self.board.weapon_tokens\n self.player_tokens = self.board.player_tokens\n self.dice = self.board.dice\n\n cont = True\n movements = {'W': [0, -1], 'S': [0, 1], 'A': [-1, 0], 'D': [1, 0]}\n misc_options_one = ['E', 'D']\n misc_options_two = ['E']\n correct = False\n key = ''\n\n # self.move_players_testing()\n # self.remove_players_testing()\n\n while cont:\n for player_char in self.players: \n player_token = self.player_tokens[player_char]\n player_object = self.players[player_char]\n\n out_count = 0\n for p in self.players:\n if self.players[p].out:\n out_count += 1\n\n if out_count == len(self.players):\n cards = self.board.solution.get_solution()\n print('You all lost!')\n print('The solution was:')\n for card in cards:\n sym, a_card = list(card.items())[0]\n print('%s : %s' % (sym, a_card.name))\n input('Press enter to quit')\n cont = False\n break\n\n if not player_object.out:\n if key == 'P':\n cont = False\n break\n \n roll_one, roll_two = self.dice.roll()\n steps = roll_one + roll_two\n player_not_stopped = True\n \n while player_not_stopped and steps > 0 and not correct:\n if key == 'P':\n cont = False\n player_not_stopped = False\n break\n\n\n key_incorrect = True\n while key_incorrect:\n key, option = self.menu_refresh(player_token, player_char, steps)\n\n if key == 'P':\n cont = False\n player_not_stopped = False\n key_incorrect = False\n break\n \n if key =='/':\n cards = self.board.solution.get_solution()\n for card in cards:\n sym, a_card = list(card.items())[0]\n print('%s : %s' % (sym, a_card.name))\n input()\n\n elif key == 'H':\n for s, pl in player_object.hand.deck.items():\n print('%s : %s' % (s, pl.name))\n input('Continue?')\n\n elif key == '!':\n player_not_stopped = False\n key_incorrect = False\n player_token.reset_has_entered()\n \n elif key == '£' or (key == '\"' and (option == 1 or option == 3)):\n player_not_stopped = False\n # options order: player_cards, rooms, weapons\n if key == '£':\n options = self.board.get_card_options(False)\n if key == '\"' and (option == 1 or option == 3):\n options = self.board.get_card_options(True)\n \n \"\"\" temp for debugging \"\"\"\n # player_token_list = list(self.player_tokens.items())\n\n # for i, p in enumerate(player_token_list):\n # if p[0] == player_char:\n # p_pos = i\n\n # print(player_token_list[p_pos - 1 % len(player_token_list)][1].player.hand.deck)\n \"\"\" \"\"\"\n\n \"\"\" Also temp for debugging \"\"\"\n # cards = self.board.solution.get_solution()\n # print('cards: ', cards)\n \"\"\" \"\"\"\n\n selection = []\n for option_type in options:\n for i, card_details in enumerate(option_type):\n print('%s : %s - %s' % (i, card_details[1], card_details[3]))\n \n cont_three = True\n while cont_three:\n inp = input('Select from above: ')\n\n try: \n inp = int(inp)\n is_int = True\n except ValueError:\n is_int = False\n\n if is_int and inp < len(option_type) and inp >= 0:\n selection.append(option_type[inp])\n cont_three = False\n else:\n print('incorrect number')\n \n if key == '\"' and (option == 1 or option == 3):\n # Room for suggest doesn't need to be selected, is derrived from current room of the current player\n steps = 0\n key_incorrect = False\n player_not_stopped = False\n player_token_list = list(self.player_tokens.items())\n player_token.reset_has_entered()\n\n for i, p in enumerate(player_token_list):\n if p[0] == player_char:\n p_pos = i\n \n left_player = player_token_list[p_pos - 1 % len(player_token_list)]\n result = player_object.suggest(selection[0], {selection[0][1]: self.player_cards[selection[0][1]]}, {player_token.current_room: self.rooms[player_token.current_room]}, selection[1], left_player, self.board)\n if result != False:\n input('Card: %s, Enter to continue.' % result.name)\n else:\n input('Incorrect, Enter to continue.')\n\n elif key == '£':\n correct = player_object.accuse(selection[0][2], selection[1][2], selection[2][2], self.board.solution)\n steps = 0\n if correct:\n print('Yay you won :3')\n cont = False\n\n key = 'P'\n else:\n # print(player_object.out)\n player_object.make_out()\n # print(player_object.out)\n # input()\n print('Oof, you are out')\n \n key_incorrect = False\n player_not_stopped = False\n input()\n else:\n print('wut')\n input()\n\n elif key in movements or key in misc_options_one or key in misc_options_two:\n if option == 0 and key in movements:\n cont_two = True\n switch = True\n while cont_two:\n if switch:\n switch = False\n else:\n key, temp_option = self.menu_refresh(player_token, player_char, steps)\n\n if key == 'P':\n cont_two = False\n cont = False\n steps -= 1\n key_incorrect = False\n elif key in movements:\n off_x, off_y = movements[key] \n cont_two, has_entered = player_token.move_by_direction(off_x, off_y)\n cont_two = not cont_two\n\n if has_entered:\n steps = 1\n else:\n if not cont_two:\n steps -= 1\n key_incorrect = False\n elif option in [1, 2] and key in misc_options_one:\n if key == 'D':\n player_token.reset_has_entered()\n player_token.enter_secret_door()\n steps = 1\n else:\n player_token.exit_door()\n player_token.reset_has_entered()\n steps -= 1\n \n key_incorrect = False\n elif option in [3, 4] and key in misc_options_two:\n player_token.exit_door()\n player_token.reset_has_entered()\n steps -= 1\n key_incorrect = False\n player_token.reset_has_entered()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def main_loop(self):\n center_point = self.mot.center_point\n\n screen_width = center_point[0] * 2\n screen_height = center_point[1] * 2\n\n time.sleep(1)\n pretty_progress_bar(\n 3,\n )\n\n # while int(time.time()) - start <= 10:\n while not self.mot.abort:\n object1_position = self.mot.position(self.color1)[0]\n object2_velocity = self.mot.speed(self.color2)\n # print(object2_velocity)\n\n self.compare(object1_position[0] < 0.25 * screen_width, 'left')\n self.compare(object1_position[0] > 0.75 * screen_width, 'right')\n self.compare(object1_position[1] < 0.25 * screen_height, 'jump')\n self.burst_compare(object2_velocity > 150, 'fire')\n\n # print('KEYBOARD ABORT')","def tray_game():\r\n\r\n print(term.home + term.on_green + term.clear)\r\n\r\n print(term.black + term.move_xy(0,0) + (\"┏\"), end='')\r\n i = 0\r\n while i < 20:\r\n i = i + 1 \r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"┳\"), end='')\r\n print(term.move_xy(80,0) + (\"┓\"), end='')\r\n \r\n y = 0\r\n print(term.black + term.home + term.move_down(y) + (\"┃\"), end='')\r\n i = 0\r\n while i < 20 :\r\n i = i + 1 \r\n print(term.black + term.move_right(3) + (\"┃\"), end='')\r\n \r\n x, y, j = 0, 1, 0\r\n while j < 19: \r\n \r\n y = y + 1\r\n print(term.black + term.home + term.move_y(y) + (\"┣\"), end='')\r\n \r\n i = 0\r\n while i < 20 :\r\n i = i + 1 \r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"╋\"), end='')\r\n print(term.black + term.home + term.move_xy(80,y) + (\"┫\"), end='')\r\n \r\n y = y + 1\r\n print(term.black + term.home + term.move_down(y) + (\"┃\"), end='')\r\n i = 0\r\n while i < 20 :\r\n i = i + 1 \r\n print(term.black + term.move_right(3) + (\"┃\"), end='')\r\n j = j + 1\r\n \r\n print(term.black + term.move_xy(0,40) + (\"┗\"), end='')\r\n i = 0\r\n while i < 20:\r\n i = i + 1 \r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"━\"), end='')\r\n print(term.black + term.move_right(-1) + (\"┻\"), end='')\r\n print(term.move_xy(80,40) + (\"┛\"), end='')","def timer():\r\n\r\n T = 0\r\n while True:\r\n print (term.white + term.move_xy(82,1) + 'TIMER : ', end='')\r\n print(T, end='\\r')\r\n time.sleep(1)\r\n T = T + 1","def console():\r\n while True:\r\n interpret_command(input(\"POM> \"))","def move_repeatedly():\n check = check50.run(run_command)\n check.stdin(\"WEST\").stdout(room_2_description)\n check.stdin(\"EAST\").stdout(room_1_name)\n check.stdin(\"WEST\").stdout(room_2_name)","def run(self):\n move_cmd = Twist()\n move_cmd.linear.x = 0\n move_cmd.angular.z = 0\n\n while not rospy.is_shutdown():\n # bump logic as previous psets\n if self.bump:\n self.bump = False\n # move backwards\n move_cmd.linear.x = LIN_SPEED * -1\n for i in range(5):\n self.cmd_vel.publish(move_cmd)\n self.rate.sleep()\n rospy.sleep(1)\n\n # turn randomly in a random direction\n move_cmd.linear.x = 0\n move_cmd.angular.z = ROT_SPEED * ((-1)**random.randint(1,2))\n\n if self.bump == 0:\n move_cmd.angular.z = ROT_SPEED * (-1)\n elif self.bump == 2:\n move_cmd.angular.z = ROT_SPEED\n\n for i in range(random.randint(5,15)):\n self.cmd_vel.publish(move_cmd)\n self.rate.sleep()\n rospy.sleep(1)\n\n move_cmd.angular.z = 0\n # if somethin in the screen is really close\n elif self.min_val < MIN_THRESHOLD:\n # make sure it's not the sock/leg warmer, and is actually an obstacle\n if self.obstacle_x <= self.x or self.obstacle_x >= self.x + self.w or abs(self.min_val - self.dist) > 0.1:\n move_cmd.linear.x = 0\n # turn away\n if self.obstacle_x > 320:\n move_cmd.angular.z = ROT_SPEED / 2\n else:\n move_cmd.angular.z = -ROT_SPEED / 2\n # self.min_val = 100\n for i in range(10):\n self.cmd_vel.publish(move_cmd)\n self.rate.sleep()\n self.last_move = rospy.Time.now()\n else:\n rospy.loginfo(\"Perimeter \" + str(self.perimeter_size))\n rospy.loginfo(\"Distance is \" + str(self.dist))\n\n # normalize angle error to rot speed\n ang_error_norm = -float(self.ang_error) / 100\n\n # set min and max rot speed\n if ang_error_norm < -ROT_SPEED:\n ang_error_norm = -ROT_SPEED\n elif ang_error_norm > ROT_SPEED:\n ang_error_norm = ROT_SPEED\n\n move_cmd.angular.z = ang_error_norm\n\n if RACE == False:\n # normalize dist error to lin speed\n self.dist_error = self.dist - 0.5\n dist_error_norm = float(self.dist_error) / 2\n\n if dist_error_norm < 0:\n # if NaN (self.dist gets set to -1)\n if dist_error_norm > -0.7:\n self.lost = 0\n # if too close\n else:\n self.lost += 1\n # if it's been more than 2 seconds\n if rospy.Time.now() > self.last_move + rospy.Duration(2):\n dist_error_norm = 0\n # if been lost for a while rotate and beep\n if self.lost > 20:\n move_cmd.angular.z = ROT_SPEED / 4\n self.beep.publish(4)\n else:\n # continue as previous\n dist_error_norm = self.last_speed\n else:\n # set max lin speed\n if dist_error_norm > LIN_SPEED:\n dist_error_norm = LIN_SPEED\n\n # reset lost stats\n self.lost = 0\n self.last_speed = dist_error_norm\n self.last_move = rospy.Time.now()\n\n move_cmd.linear.x = dist_error_norm\n else:\n move_cmd.linear.x = LIN_SPEED\n\n self.cmd_vel.publish(move_cmd)","def main(scr):\n mtr = KST101()\n mtr.en_update_msg(True)\n\n step_size = 1\n old_step_size = -1\n null_point = 0\n curses.curs_set(False)\n scr.nodelay(True)\n while True:\n pos = mtr.get_pos()\n in_key = scr.getch()\n if in_key == 49: step_size = 1 # 1\n elif in_key == 50: step_size = 1e1 # 2\n elif in_key == 51: step_size = 1e2 # 3\n elif in_key == 52: step_size = 1e3 # 4\n elif in_key == 53: step_size = 1e4 # 5\n elif in_key == 54: step_size = 1e5 # 6\n elif in_key == 55: step_size = 1e6 # 7\n elif in_key == 56: step_size = 1e7 # 8\n elif in_key == 57: step_size = 1e8 # 9\n elif in_key == 114: # r\n step_size *= -1\n elif in_key == 32: # space\n mtr.do_move()\n elif in_key == 104: # h\n mtr.home()\n elif in_key == 110: # n\n null_point = pos\n elif in_key == 122: # z\n null_point = 0\n elif in_key == 48: # 0\n mtr.set_move(null_point, False)\n mtr.do_move(False)\n mtr.set_move(step_size)\n elif in_key == 113 or in_key == 27: # q / escape\n break # Quit\n \n if step_size != old_step_size:\n mtr.set_move(step_size)\n old_step_size = step_size\n\n scr.clear()\n scr.addstr(1, 2, \" Steps: %u\" % (pos - null_point))\n scr.addstr(2, 2, \" mm: %0.4f\" % mtr.step2mm(pos - null_point))\n scr.addstr(3, 2, \" Size: %u\" % step_size)\n scr.addstr(4, 2, \" Null: %u\" % null_point)\n home_state = mtr.get_home_state()\n if home_state == 2:\n scr.addstr(6, 2, \" *** Motor homing, please wait... ***\")\n elif home_state == 1:\n scr.addstr(6, 2, \" *** Motor needs homing (press h) ***\")\n elif mtr.is_lower_limit():\n scr.addstr(6, 2, \" *** Motor is at lower limit. ***\")\n elif mtr.is_upper_limit():\n scr.addstr(6, 2, \" *** Motor is at upper limit. ***\")\n elif mtr.is_moving():\n scr.addstr(6, 2, \" *** Motor is moving to position. ***\")\n \n # Lower status\n scr.addstr(16, 2, \" Controls: 1-9 - set step size to 10^(n-1),\" \\\n \" <spc> - move\")\n scr.addstr(17, 2, \" r - reverse, h - home, 0 - go to null\")\n scr.addstr(18, 2, \" n - set null, z - zero null\")\n scr.addstr(21, 2, \" Status: %08X\" % mtr.get_raw_status())\n scr.addstr(20, 2, \" Key: %u\" % int(in_key))\n scr.refresh()\n time.sleep(0.1)","def tmux_move(direction):\n pyautogui.hotkey('ctrl', 'B')\n pyautogui.press(direction)\n time.sleep(0.5)","def nod():\n while True:\n MOVEMENTS.set_raw_angle(7, 52)\n sleep(2)\n MOVEMENTS.set_raw_angle(7, 0)\n sleep(2)","def my_code():\n i = 0\n j = 0\n while True:\n print(\" \"*50, \"\\r\", end=\"\")\n if i in [0, 4, 11, 19]:\n print(\"\\t\\t\\t{} {}\".format(TEXT[j], i - JJ[j]), \"\\a\", end=\"\")\n else:\n print(\"\\t\\t\\t{} {}\".format(TEXT[j], i - JJ[j]), end=\"\")\n time.sleep(1)\n i = i+1\n if i > 4:\n j = 1\n if i > 11:\n j = 2\n if i >= 19:\n i = 0\n j = 0","def step(self, screen):\n max_y, _ = screen.getmaxyx()\n allowed_y = range(0, max_y)\n def is_on_screen(y):\n return y in allowed_y\n still_visible = False\n y, x = -1, -1\n for char in self.characters:\n y, x = int(char.y), char.x\n char.y += self.min_falling_speed\n if not is_on_screen(y):\n continue\n still_visible = True\n screen.addstr(y, x, char.symbol, char.color)\n # Clear trail of characters after column\n y -= 1\n while is_on_screen(y):\n screen.addstr(y, x, ' '*self.width)\n y -= 1\n return still_visible","def checkMotion(self):\n res = 0\n while(self.ser.inWaiting() > 0):\n res = self.ser.readline().strip()\n\n try:\n if self.state == 1 and time.time() - self.last_move > self.config[\"keep_on_time\"]:\n self.execOff()\n\n if res == \"1\":\n self.last_move = time.time()\n\n if res == \"1\" and self.state == 0:\n self.execOn()\n except Exception as e:\n self.logger.error(e)","def run_terminal():\n playing = True\n while playing:\n print(\"$\", end='')\n command = input()\n list_of_inputs = command.split(\" \")\n if list_of_inputs[0] == \"exit\":\n playing = False\n break\n handle_command(list_of_inputs)","def run(self):\n for _ in range(self.num_iteration):\n self.move()\n time.sleep(self.speed)\n if not self.is_running:\n break","def _display_loop(self):\n # Get & handle user input\n self._handle_input(self.screen.getch())\n\n # Only update if there's something to do - Improves performance drastically\n if self.updated:\n # Reset screen\n self.screen.clear()\n self.updated = False\n\n # Commands header & highlight current command\n self.screen.addstr('Every {:.1f}/{:.1f}s: | '.format(self.interval, self.cycle_interval), self.base_color)\n for i, command in enumerate(self.commands_str):\n self.screen.addstr(command, self.highlight_color if i == self.current_idx else self.base_color)\n self.screen.addstr(' | ', self.base_color) # Pad between commands\n\n # Add current date & time to header, pad to end of the line based on current position\n pad = self.max_col - self.screen.getyx()[-1] - self.time_pad\n self.screen.addstr(' '*pad + self.time_str + '\\n', self.base_color)\n\n # Display the current command's output\n self._display_command()\n\n self.screen.refresh() # Refresh must go before delay!\n time.sleep(self.DELAY) # Small delay to avoid stuttering but allow for smooth scrolling","def loop(self):\n while True:\n self._print_field()\n try:\n cmd = input(PROMPT)\n self._invoke_cmd(cmd)\n except EOFError: # Allows to exit by pressing ⌃D without error\n break","def start(self):\n self.print_separator()\n self.stdscr.box()\n\n box = curses.newwin(4, self.maxx-8, self.pad, self.pad)\n box.addstr(1,1,\"hello\")\n while self.running:\n # Enter the main program loop\n key = self.stdscr.getkey()\n for fn in [self.stdscr.clear,\n lambda: self.handle_key(key),\n self.update_xy,\n self.print_pattern,\n self.print_separator,\n self.stdscr.box,\n self.generate_menu_items,\n self.print_menu_items,\n self.print_current_selection,\n self.stdscr.refresh]:\n fn()","def run_prank():\n d = display.Display()\n num_screens = d.screen_count()\n s = d.screen(random.randrange(0, num_screens) )\n root = s.root\n root.warp_pointer(random.randrange(0, s.width_in_pixels), random.randrange(0, s.height_in_pixels) )\n d.sync()\n return (True, 'It looks like you are using a mouse. Let me help you move it')","def run(self):\n while self.direction != \"\":\n if self.direction == \"decrease\":\n if self.position > 200:\n self.position -= 15\n elif self.direction == \"increase\":\n if self.position < 800:\n self.position += 15\n if self.direction != \"neutral\":\n self.move_joint(self.position, 900)\n time.sleep(0.1)","def listenMove(s):\n debugPrint(\"FUNCTION AcornClient.listenMove()\")\n print(grid)\n loop = True\n while loop:\n move = input(\">>> \").lower()\n if move in ['w']:\n loop = False\n sendMove(s, 'up')\n elif move in ['s']:\n loop = False\n sendMove(s, 'down')\n elif move in ['d']:\n loop = False\n sendMove(s, 'right')\n elif move in ['a']:\n loop = False\n sendMove(s, 'left')\n else:\n print(\"Please choose either: 'up', 'down', 'left', or 'right'. Thank you.\") # In case the user is trying to break the system :(\n debugPrint(\"User input an unknown direction: %s\" % move, 1)","def run(self):\n while self.is_connected():\n self.__ticker.tick() # Tick (sleep)\n\n if self.process and self.process.is_alive():\n self.update()\n continue\n\n c = getkey() \n if c:\n if c == 'w':\n print \"Moving forward\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"forward\")\n elif c == 'a':\n print \"Turning left\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"left\")\n elif c == 'd':\n print \"Turning right\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"right\")\n elif c == 's':\n print \"Moving backward\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"backward\")\n elif c == 'q':\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"stop\")\n elif c == 'r':\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"terminate\")\n elif c == 't':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"make_scan\")\n elif c == 'm':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"save_map\")\n elif c == 'l':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"load_map\")\n elif c == 'c':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"match_map\")\n elif c == 'x':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"make_map\")\n elif c == 'z':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"discard_map\")\n elif c == 'p':\n self.save_pose()\n elif c == 'g':\n self.add_property(\"name\", \"map_command\")\n self.add_property(\"map_command\", \"toggle_autoscan\")\n elif c == 'h':\n print \"[w] = forward [a] = left [s] = backward [d] = right\"\n print \"[q] = stop [t] = take scan [c] = matching mode [x] = mapping mode\"\n print \"[m] = save map [l] = load map [p] = save current pose [g] = Toggle autoscanning\"\n \n ############################\n # Send data\n self.update()","def display_loop(self):\n from time import sleep\n self.displaying = True\n while self.displaying:\n print self\n sleep(.083)\n print loc(self.y, self.x) + ' '*self.size","def move_debug(self, environment):\n\n ch2 = sys.stdin.read(1)\n\n if ch2 == \"w\":\n # the up arrow key was pressed\n print(\"up key pressed\")\n\n elif ch2 == \"s\":\n # the down arrow key was pressed\n print(\"down key pressed\")\n\n elif ch2 == \"a\":\n # the left arrow key was pressed\n print(\"left key pressed\")\n\n elif ch2 == \"d\":\n # the right arrow key was pressed\n print(\"right key pressed\")","def all():\n lab = test_loading()\n\n for _ in range(1):\n print('🦅🐀🐙')\n\n test_spawn(lab)\n\n pc = test_spawn_player(lab)\n\n while True:\n pc.store_move(PlayerMove(random.choice(['walk left', 'walk up', 'walk down', 'walk right'])))\n test_turn_ai_and_players(lab)\n if input() == '0':\n break","def strut(self):\n self.fwd(left=50, right=50)\n for x in range(2):\n self.servo(1000)\n time.sleep(.1) \n self.servo(1500) # Look Straight\n time.sleep(1)\n self.servo(2000)\n time.sleep(.1)\n self.servo(1500)","def run(self):\n while self.is_connected():\n self.__ticker.tick() # Tick (sleep)\n\n if self.process and self.process.is_alive():\n self.update()\n continue\n\n c = getkey() \n if c:\n if c == 'w':\n print \"Moving forward\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"mmove\")\n elif c == 'a':\n print \"Turning left\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"mleft\")\n elif c == 'd':\n print \"Turning right\"\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"mright\")\n elif c == 'f':\n self.add_property(\"name\", \"pioneer_command\")\n self.add_property(\"pioneer_command\", \"finish\")\n elif c == 'p':\n self.add_property(\"name\", \"remote_command\")\n self.add_property(\"pioneer_command\", \"record\")\n elif c == 'h':\n print \"[w] = forward [a] = left [d] = right [f] = finish\"\n\n \n ############################\n # Send data\n self.update()","def main():\n move()\n move()\n pick_beeper()\n move()\n turn_left()\n for i in range(2):\n move()\n put_beeper()\n turn_around()\n move_to_wall()\n turn_right()\n move_to_wall()\n turn_around()","def Loop(self):\n self.coshell.SetModesCallback(self.SetModes)\n while True:\n try:\n text = self.Prompt()\n if text is None:\n break\n self.Run(text) # paradoxically ignored - coshell maintains $?\n except EOFError:\n # ctrl-d\n if not self.coshell.ignore_eof:\n break\n except KeyboardInterrupt:\n # ignore ctrl-c\n pass\n except interactive_coshell.CoshellExitError:\n break","def example(self):\n while self.check_end() == False:\n plt.pause(0.25)\n end = self.update_board(random.choice(self.get_actions()), True)","def main():\r\n\r\n movetwotimes()\r\n pick_beeper()\r\n move()\r\n turn_left()\r\n movetwotimes()\r\n put_beeper()\r\n turn_left()\r\n turn_left()\r\n movetwotimes()\r\n rotatethreetimes()\r\n movetwotimes()\r\n move()\r\n turn_left()\r\n turn_left()","def main():\n print(\"Mouse mover\")\n print(\"Press Ctrl + c to terminate the script.\")\n try:\n while True:\n move_the_mouse()\n sleep(2)\n\n except KeyboardInterrupt:\n print(\"Finished.\")","def run():\r\n \r\n match = a4_acc.Game() # Instantiate a Game object \r\n setup(match)\r\n\r\n if constants.SHOW_GRAPHICS:\r\n axes= startGraphics(match.board) #step 0\r\n \r\n \r\n for k in range(constants.STEPS):\r\n update(match)\r\n updateGraphics(board, k, caxes)\r\n \r\n ########\r\n # TO DO: \r\n # Simulate game given the intial state for constants.STEPS iterations\r\n \r\n # Example code to call the updateGraphics function; the second argument\r\n # needs to be replaced:\r\n # if constants.SHOW_GRAPHICS:\r\n # updateGraphics(match.board, None, axes) \r\n \r\n # Do not change or add code below here for function run\r\n endNow= raw_input('Press ENTER to continue.')","def loop():\n global loop_idx\n sys.stdout.write('loop index %d/%d\\r\\n' % (loop_idx, _LOOPS))\n time.sleep(0.5)\n loop_idx += 1\n return loop_idx > _LOOPS","def timed_move(self, direction, duration):\n print(\"Timed move \", end='')\n if direction == MOV_FORWARD:\n print(\"forward\")\n elif direction == MOV_BACK:\n print(\"back\")\n else:\n print(\"?\")\n print(\"Duration:\", duration)\n\n self.moving_delay(duration)\n self.move_stop()","def move(self, direction, step):\n for i in range(1, step + 1):\n y, x = self.robot_position\n if direction == \"N\" and y > 0:\n if self.carte[y - 1][x] in [\" \", \".\", \"U\"]:\n self.robot_position = (y - 1, x)\n elif direction == \"S\" and y <= self.height:\n if self.carte[y + 1][x] in [\" \", \".\", \"U\"]:\n self.robot_position = (y + 1, x)\n elif direction == \"E\" and x <= self.width+1:\n if self.carte[y][x + 1] in [\" \", \".\", \"U\"]:\n self.robot_position = (y, x + 1)\n elif direction == \"O\" and x > 0:\n if self.carte[y][x - 1] in [\" \", \".\", \"U\"]:\n self.robot_position = (y, x - 1)\n\n if self.robot_position == self.out_position:\n print(\"Bravo vous avez fini\")\n return True\n\n return False","def movement(self):","def mainloops(stdscr):\n def signal_handler(sig, frame):\n \"\"\"\n What to do in case of KeyboardInterrupt\n\n Writes times to session file\n (saving file interaction to the end saves time during frames.)\n \"\"\"\n raise ExitException()\n\n signal.signal(signal.SIGINT, signal_handler)\n\n try:\n curses.curs_set(0) # hide cursor (I have my own)\n except Exception:\n pass\n stdscr.nodelay(True) # makes stdscr.getch() non-blocking\n\n canvas = Canvas(curses.LINES - 1, curses.COLS - 1)\n cursor = Cursor(canvas)\n\n display_text(stdscr, TITLE_ART)\n\n # sessions are groups of solves, stored in files in ~/.cl-timer\n # if this is a new session, create a new file, if not, use an existing one.\n\n session_name_input = InputLine(canvas, 'session name: ')\n session = MutableString(ask_for_input(stdscr, canvas, session_name_input, cursor))\n \n times = []\n ao5s = []\n ao12s = []\n scrambles = []\n session_file = \"\"\n\n session_file = MutableString(f'{HOME}/.cl-timer/{session.string}')\n if not isfile(session_file.string):\n with open(session_file.string, 'w+') as f:\n pass\n \n with open(session_file.string, 'r') as f:\n time_lines = [line.split('\\t') for line in f.read().split('\\n')]\n\n if [''] in time_lines:\n time_lines.remove([''])\n\n for line in time_lines:\n times.append(line[0])\n ao5s.append(line[1])\n ao12s.append(line[2])\n scrambles.append(line[3])\n\n settings_file = MutableString(f'{session_file.string}-settings.json')\n if not isfile(settings_file.string):\n with open(settings_file.string, 'w+') as f:\n json.dump(settings, f)\n \n with open(settings_file.string, 'r') as f:\n for key, value in json.load(f).items():\n settings[key] = value\n\n display_text(stdscr, DISCLAIMER)\n\n def add_time(t):\n \"\"\"\n Add new solve with time of `t`\n \"\"\"\n\n times.append(t)\n\n # update number display to show real time\n number_display.time = t\n number_display.update()\n\n # generate new scramble and update scramble_image\n new_scramble = generate_scramble(int(settings['puzzle']),\n int(settings['scramble-length']))\n scrambles.append(new_scramble)\n scramble_image.clear()\n scramble_image.chars = char(new_scramble)\n\n ao5, ao12 = update_stats()\n\n with open(session_file.string, 'a') as f:\n if len(times) == 1:\n f.write(f'{add_zero(t)}\\t{ao5}\\t{ao12}\\t{new_scramble}')\n else:\n f.write(f'\\n{add_zero(t)}\\t{ao5}\\t{ao12}\\t{new_scramble}')\n \n def calculate_average(solve, length):\n \"\"\"\n Returns average of `length` during `solve`\n\n Looks through times list and finds last `length` solves before `solve`\n Excludes best and worst times, and returns average of the rest.\n \"\"\"\n if len(times[:solve]) < length:\n # `length` solves haven't been done yet.\n return ''\n else:\n latest_average = times[solve - length:] # list of last `length` solves\n latest_average, _ = convert_to_float(latest_average, \"average\")\n if len(latest_average) < (length - 1):\n return 'DNF'\n if len(latest_average) == length:\n latest_average.remove(max(latest_average))\n latest_average.remove(min(latest_average))\n\n # calculate average and add zero if it doesn't go to 100ths place.\n \n return add_zero(round(sum(latest_average) / len(latest_average), 2))\n\n def get_session_mean():\n \"\"\"\n Returns mean of all solves in session\n \"\"\"\n try:\n float_times, len_times = convert_to_float(times, 'average')\n return add_zero(round(sum(float_times) / len_times, 2))\n except ZeroDivisionError:\n return \"\"\n\n def get_best_average(length):\n \"\"\"\n Returns best average of `length` in session\n \"\"\"\n try:\n if length == 5:\n best = add_zero(min([i for i in ao5s if i != '']))\n elif length == 12:\n best = add_zero(min([i for i in ao12s if i != '']))\n except ValueError:\n return \"\"\n return best\n\n def get_best_time():\n try:\n converted_times, _ = convert_to_float(times, 'single')\n float_times = [float(t[:-1]) if isinstance(t, str) else t for t in converted_times]\n best = converted_times[float_times.index(min(float_times))]\n if isinstance(best, float):\n return add_zero(best)\n except ValueError as e:\n return \"\"\n return best\n\n def get_worst_time():\n try:\n converted_times, _ = convert_to_float(times, 'single')\n float_times = [float(t[:-1]) if isinstance(t, str) else t for t in converted_times]\n worst = converted_times[float_times.index(max(float_times))]\n if isinstance(worst, float):\n return add_zero(worst)\n except ValueError as e:\n return \"\"\n return worst\n\n def update_stats():\n ao5 = calculate_average(len(times), 5)\n ao5s.append(ao5)\n ao5_image.chars = char(f'AO5: {ao5}')\n ao12 = calculate_average(len(times), 12)\n ao12s.append(ao12)\n ao12_image.chars = char(f'AO12: {ao12}')\n best_ao5 = get_best_average(5)\n best_ao5_image.chars = char(f'Best AO5: {best_ao5}')\n best_ao12 = get_best_average(12)\n best_ao12_image.chars = char(f'Best AO12: {best_ao12}')\n best_time = get_best_time()\n best_time_image.chars = char(f'Best time: {best_time}')\n worst_time = get_worst_time()\n worst_time_image.chars = char(f'Worst time: {worst_time}')\n\n len_successes = 0\n for t in times:\n if not ((isinstance(t, str)) and (t[:3] == 'DNF')):\n len_successes += 1\n\n number_of_times_image.chars = char(f'Number of Times: {len_successes}/{len(times)}')\n session_mean = get_session_mean()\n session_mean_image.chars = char(f'Session Mean: {session_mean}')\n\n return ao5, ao12\n \n session_name_image = Image(canvas, 0, 0, char(session.string))\n scramble_image = Scramble(canvas, 0, 2, char(\n generate_scramble(int(settings['puzzle']),\n int(settings['scramble-length']))))\n scramble_image.render()\n\n number_display = NumberDisplay(canvas, 15, 7)\n timer_background = Image(canvas, 0, 5, char(TIMER_BACKGROUND))\n\n ao5_image = CoverUpImage(canvas, 51, 6, char(f'AO5: {calculate_average(len(times), 5)}'))\n ao12_image = CoverUpImage(canvas, 51, 7, char(f'AO12: {calculate_average(len(times), 12)}'))\n best_ao5_image = CoverUpImage(canvas, 51, 8, char(f'Best AO5: {get_best_average(5)}'))\n best_ao12_image = CoverUpImage(canvas, 51, 9, char(f'Best AO12: {get_best_average(12)}'))\n best_time_image = CoverUpImage(canvas, 51, 10, char(f'Best time: {get_best_time()}'))\n worst_time_image = CoverUpImage(canvas, 51, 11, char(f'Worst time: {get_worst_time()}'))\n\n len_successes = 0\n for t in times:\n if not ((isinstance(t, str)) and (t[:3] == 'DNF')):\n len_successes += 1\n number_of_times_image = CoverUpImage(canvas, 51, 12, char(f'Number of Times: {len_successes}/{len(times)}'))\n \n session_mean_image = CoverUpImage(canvas, 51, 13, char(f'Session Mean: {get_session_mean()}'))\n\n if isfile(f'{HOME}/.cl-timer_rc'):\n with open(f'{HOME}/.cl-timer_rc', 'r') as f:\n rc_commands = f.read().strip().split('\\n')\n if '' in rc_commands:\n rc_commands.remove('')\n for command in rc_commands:\n try:\n command_line(canvas, stdscr, settings, scramble_image, settings_file, session_file, times, ao5s, ao12s,\n scrambles, session, session_name_image, update_stats, add_time, calculate_average, aliases,\n True, command)\n except CommandSyntaxError:\n pass\n else:\n with open(f'{HOME}/.cl-timer_rc', 'w+') as f:\n pass\n \n ao5_image.render()\n ao12_image.render()\n best_ao5_image.render()\n best_ao12_image.render()\n best_time_image.render()\n worst_time_image.render()\n number_of_times_image.render()\n session_mean_image.render()\n\n timer_running = False\n delay = 0 # how far behind the program is\n spacebar_pressed = False\n last_25_keys = [-1 for _ in range(25)]\n\n solve_start_time = 0\n frame = 0\n while True:\n\n # to make sure each frame is exactly 0.01 secs\n start_time = time.time()\n\n key = stdscr.getch()\n\n if key == 58: # :\n try:\n command_line(canvas, stdscr, settings, scramble_image,\n settings_file, session_file, times, ao5s,\n ao12s, scrambles, session, session_name_image,\n update_stats, add_time, calculate_average, aliases)\n except CommandSyntaxError:\n pass\n continue\n\n if not timer_running:\n if key == 32:\n solve_start_time = time.time()\n last_25_keys.append(key)\n last_25_keys.pop(0)\n\n if not timer_running:\n\n if spacebar_pressed:\n if 32 in last_25_keys:\n time.sleep(0.01)\n continue\n else:\n spacebar_pressed = False\n\n timer_running = True\n number_display.reset()\n\n else:\n if key == 32: # spacebar\n spacebar_pressed = True\n\n else:\n if key == 32:\n frame = 0\n timer_running = False\n\n t = round(time.time() - solve_start_time, 2)\n\n add_time(t)\n \n\n session_name_image.render()\n \n timer_background.render()\n number_display.render()\n\n stdscr.clear()\n stdscr.addstr(canvas.display)\n stdscr.refresh()\n\n if timer_running:\n number_display.time = time.time() - solve_start_time\n number_display.update()\n\n # take away from sleep time the amount that will get us back on track\n duration = time.time() - start_time\n if (duration + delay) > 0.01:\n # can't make it back to on-time right now\n # by not sleeping, we have saved (0.01 - duration) seconds\n delay -= 0.01 - duration\n else:\n time.sleep(0.01 - (duration + delay))\n \n frame += 1","def control_loop():\n global rate, regions, speed\n rospy.init_node('ebot_controller')\n rate = rospy.Rate(10)\n rospy.Subscriber('/ebot/laser/scan', LaserScan, laser_callback)\n rospy.Subscriber('/odom', Odometry, odom_callback)\n speed = Twist()\n speed.linear.x = 0\n speed.angular.z = 0\n pub.publish(speed)\n while not rospy.is_shutdown():\n if x <= 6.28:\n user_x, user_y = waypoints(15)\n go_to_x_y(user_x, user_y, 1)\n go_to_x_y(user_x, user_y, 0.25)\n else:\n go_to_x_y(12.5, 0, 3)\n go_to_x_y(12.5, 0, 1)\n go_to_x_y(12.5, 0, 0.2)\n exit()\n speed.linear.x = 0\n speed.angular.z = 0\n pub.publish(speed)\n rate.sleep()","def run(self):\n for i in range(self.nreps):\n print self.ch,","def run(self):\n while True:\n display(self.world.draw())\n self.read_and_process_input()","def waiting_animation():\n animation = [\"[■□□□□□□□□□]\",\"[■■□□□□□□□□]\", \"[■■■□□□□□□□]\", \"[■■■■□□□□□□]\", \n \"[■■■■■□□□□□]\", \"[■■■■■■□□□□]\", \"[■■■■■■■□□□]\", \"[■■■■■■■■□□]\", \n \"[■■■■■■■■■□]\", \"[■■■■■■■■■■]\", \"[□■■■■■■■■■]\", \"[□□■■■■■■■■]\",\n \"[□□□■■■■■■■]\", \"[□□□□■■■■■■]\", \"[□□□□□■■■■■]\", \"[□□□□□□■■■■]\",\n \"[□□□□□□□■■■]\", \"[□□□□□□□□■■]\", \"[□□□□□□□□□■]\", \"[□□□□□□□□□□]\"\n ]\n for i in range(len(animation)):\n time.sleep(0.2)\n sys.stdout.write(\"\\r\" + animation[i % len(animation)])\n sys.stdout.flush()","def run_mouse_notifs(self):\n time.sleep(10)\n try:\n if not pynput_status:\n self.get_by_mice()\n else:\n while 1:\n # Starting mouse event listner\n with mouse.Listener(on_move=self.on_move) as listener:\n listener.join()\n except Exception as e:\n self.logger.log(\n \"Something went wrong: \" + str(e) + \" End of program\",\n logtype=\"error\"\n )\n except KeyboardInterrupt as e:\n self.logger.log(\n \"You pressed Ctrl+C!, Bye\")\n exit()","def step(self, move):","def run(self, verbose=False):\n step_num = 0\n while self.won == 0:\n if len(self.board.valid_moves) == 0:\n return\n status = self.step()\n if verbose and step_num % 2 == 1:\n print(self.board.table())\n if status != board.Board.INVALID_MOVE:\n step_num += 1\n print(f'Player {board.remap_char(self.won)} won!')","def return_to_center(): #ignore this for now, use move_to_position_(0,0)\n current_pos = '\\xAA\\xBB\\xCC\\xDD'\n #run command until back to center (0,0)\n while True: #change the byte locations\n current_pos = to_center()\n print(current_pos)\n time.sleep(0.2) #check timing\n if((current_pos[1] == 0) and (current_pos[1] == 0)):\n break\n print('At center')","def run_until_stop(self):\n while self.commands[self.pointer] != END:\n # Get the cmd\n cmd = self.commands[self.pointer]\n opcode = cmd % 100\n modes = cmd // 100\n \n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\n \n if opcode == ADD:\n self.commands[locs[2]] = vals[0] + vals[1]\n elif opcode == MUL:\n self.commands[locs[2]] = vals[0] * vals[1]\n elif opcode == INP:\n if self.inputs:\n self.commands[locs[0]] = self.inputs.pop(0)\n else:\n # Put the pointer back, so we run this opcode again\n self.pointer -= 2\n return False\n elif opcode == OUT:\n self.outputs.append(vals[0])\n elif opcode == JIT:\n if vals[0] != 0:\n self.pointer = vals[1]\n elif opcode == JIF:\n if vals[0] == 0:\n self.pointer = vals[1]\n elif opcode == LT:\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\n elif opcode == EQ:\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\n else:\n print(\"FAIL????\")\n\n return True","def Run(self):\n while not rospy.is_shutdown():\n # get input of destination\n if (self.target_x is None) or (self.target_y is None):\n self.target_x, self.target_y = self.GetTarget()\n # if the destination is not in x >= 0 and y <= 11, ask user to re-input\n # till the right values found\n if (self.target_x < 0 or self.target_x > 10) or (self.target_y < -10 or self.target_y > 10):\n print(\"-------------------------------------------------------\") \n print(\"WARNING: Invalid Input, please reinput the destination.\")\n print(\"-------------------------------------------------------\") \n self.target_x = None\n self.target_y = None\n else:\n print(\"Current Destination: [{}, {}]\".format(self.target_x, self.target_y))\n else:\n ################################################################################################\n # get all necessary parameters\n goal = np.array([self.target_x, self.target_y])\n robot_pos = self.GetRobotInfo()\n ranges, angles = self.GetObstaclePos()\n\n if (ranges is not None) and (angles is not None):\n ctrl = TangentBug(self.Lidar.range_max)\n # obsts = ctrl.Continuity(ranges, angles, robot_pos[:2])\n # print(len(obsts))\n linear, omega = ctrl.MotionToGo(ranges, angles, goal, robot_pos)\n print(\"=======================================\")\n # print([linear, omega])\n else:\n linear = 0.\n omega = 0.\n print(\"---------------------------------------\")\n print(\"NO OBSTACLE DETECTED.\")\n print(\"---------------------------------------\")\n\n ################################################################################################\n self.vel.linear.x = linear \n self.vel.angular.z = omega\n self.pub.publish(self.vel)\n\n # sleep till the next commend sent\n self.rate.sleep()","def getMove(player,first_move=False):\n while True: \n move = raw_input(\"MAKE YOUR MOVE: \").upper()\n\n # handle special commands\n if move == \"QUIT\" or move == \"Q\":\n wannaQuit()\n continue\n elif move == \"QUIT!\" or move == \"Q!\":\n if SAY_PROC:\n SAY_PROC.terminate()\n sys.exit()\n continue\n elif move == \"HELP\" or move == \"H\":\n help()\n continue\n elif move == \"HELP!\" or move == \"H!\":\n say(helpString())\n continue\n elif move == \"SHUTUP!\" or move == \"S!\":\n shutUp(fuck=True)\n continue\n elif move == \"SHUTUP\" or move == \"S\":\n shutUp()\n continue\n elif move == \"BOARD\" or move == \"B\":\n printBoard()\n continue\n elif move == \"CLEAR\" or move == \"C\": \n clearTerminal()\n printBoard()\n continue\n elif move == \"CLEAR!\" or move == \"C!\": # TODO board -> clear, you end up with a half drawn new board. clear again fixes this\n clearTerminalAndBuffer()\n printBoard()\n continue\n elif move == \"PASS\" or move == \"P\": \n if wannaPass():\n break\n else:\n continue\n elif move == \"PASS!\" or move == \"P!\": \n break\n \n # mostly used to catch blank lines or me typing ASFADS like an asshole\n if len(move) < 7:\n print \"That's too short to be a command.\"\n continue\n\n parts=move.split(\":\")\n if len(parts) != 3:\n print \"Can't find all the parts of the move command. Maybe you're missing/have too many \\\":\\\"?\"\n continue\n\n for item in parts:\n if len(item) == 0:\n print \"Found a blank command. Maybe you left in an extra \\\":\\\"?\"\n continue\n\n coords = parts[0].replace(\" \",\"\") # incase of space inbetween file and rank\n direction = parts[1].strip()\n word = parts[2].strip()\n\n if not coords[0].isalpha():\n print \"I don't know where to put your word (Bad file coord).\"\n continue\n\n if not coords[1:].isdigit():\n print \"I don't know where to put your word (Bad rank coord).\"\n continue\n\n x = gridCharToInt(coords[0])\n y = int(coords[1:]) - 1\n if 14 < x < 0 or 14 < y < 0:\n print \"Those aren't coords on the board. Valid Files are from A-O, valid Ranks are 1-15.\"\n continue\n\n if first_move:\n if x != 7 or y != 7:\n print \"The first move must start from the center (H8).\"\n continue\n\n #compact that command\n if direction == \"ACROSS\":\n direction = \"A\"\n elif direction == \"DOWN\":\n direction = \"D\"\n if direction != \"A\" and direction !=\"D\":\n print \"I don't know where to put your word (Across or Down?).\"\n continue\n \n score,placed_tiles = checkWords(x,y,direction,word,first_move)\n if not score: #error reporting is handling in check words\n continue\n else:\n for tile in placed_tiles:\n if not tile in player.rack:\n print \"You don't have the tiles to play that!\"\n continue\n player.rack.remove(tile)\n print player.name+\" scored \"+str(score)+\" on that last play!\"\n player.score+=score\n for tile in placed_tiles:\n player.rack.remove(tile)\n break #YAY","def run(self):\n terminal.open()\n self.terminal_init()\n terminal.refresh()\n\n try:\n self.loop_until_terminal_exits()\n except KeyboardInterrupt:\n pass\n finally:\n terminal.close()","def main():\r\n robot = ROBOT()\r\n print(\"COMMANDS AVAILABLE:\", commands_avail)\r\n print(\"'PLACE' must be used in the form: PLACE x,y,direction\")\r\n print(\"VALID DIRECTIONS:\", direction_tuple)\r\n print(\"MOVE: moves the robot one unit in the direction its facing, unless it would fall of the tabletop\")\r\n print(\"LEFT and RIGHT: rotates the robot 90 degrees anti-clockwise or clockwise respectively\")\r\n print(\"REPORT: prints the position on the tabletop and which direction the robot is facing\")\r\n print(\"NOTE: position 0,0 is south-west corner and 4,4 is north-east corner. Size can be changed in source code\")\r\n print(\"NOTE: if REPORT in input, all previous commands processed and reported. Option to enter more input given.\")\r\n while True:\r\n commands = robot.input_discard()\r\n try:\r\n for i in commands:\r\n if commands_avail[0] in i:\r\n xyd = i.split(' ')\r\n xy = xyd[1].split(',')\r\n x = int(xy[0])\r\n y = int(xy[1])\r\n d = xy[2]\r\n robot.place(x, y, d)\r\n elif i == commands_avail[1]:\r\n robot.move()\r\n elif i == commands_avail[2]:\r\n robot.left()\r\n elif i == commands_avail[3]:\r\n robot.right()\r\n elif i == commands_avail[4]:\r\n robot.report()\r\n except TypeError:\r\n print(\"NO VALID PLACE OR EXISTING ROBOT POSITION\")\r\n print(\"Would you like to enter more input: 'Y' for yes or 'N' to quit\")\r\n cont = input()\r\n while cont != 'N' and cont != 'Y':\r\n print(\"INVALID COMMAND!\\nWould you like to enter more input: 'Y' for yes or 'N' to quit\")\r\n cont = input()\r\n if cont == 'N':\r\n break\r\n print(\"Exiting Program\")","def main():\n\tcolorama.init()\n\n\n\n\tgrid = get_start_grid(*map(int,sys.argv[1:]))\n\tprint_grid(grid)\n\n\twhile True:\n\t\tgrid_copy = copy.deepcopy(grid)\n\t\tget_input = getch(\"Enter direction (w/a/s/d/n/r/q): \")\n\t\tif get_input in functions:\t\n\t\t\tfunctions[get_input](grid)\n\t\telif get_input == \"n\":\n\t\t\tif get_next_action(grid) == '':\n\t\t\t\tprint(\"Checkmate!\")\n\t\t\t\tbreak\n\t\t\tfunctions[get_next_action(grid)](grid)\n\t\telif get_input == \"r\":\n\t\t\tbreak\n\t\telif get_input == \"q\":\n\t\t\tbreak\n\t\telse:\n\t\t\tprint(\"\\nInvalid choice.\")\n\t\t\tcontinue\n\t\tif grid != grid_copy:\n\t\t\tif not prepare_next_turn(grid):\n\t\t\t\tprint_grid(grid)\n\t\t\t\tprint(\"Well played!\")\n\t\t\t\tbreak\n\t\tprint_grid(grid)\n\t\n\tif get_input == \"r\":\n\t\twhile True:\n\t\t\tgrid_copy = copy.deepcopy(grid)\n\n\t\t\tnext_action = get_next_action(grid)\n\t\t\tif next_action == '':\n\t\t\t\tprint(\"Checkmate!\")\n\t\t\t\tbreak\n\t\t\t\n\t\t\tfunctions[next_action](grid)\n\t\t\tif grid != grid_copy:\n\t\t\t\tif not prepare_next_turn(grid):\n\t\t\t\t\tprint_grid(grid)\n\t\t\t\t\tprint(\"Well played!\")\n\t\t\t\t\tbreak\n\t\t\tprint_grid(grid)\n\n\tprint(\"Thanks for playing.\")","def idle_loop(self):\n sleep(0.1)\n self.scroll()","def run(self):\n global key\n getch = _GetchUnix()\n key = getch()\n while key != \"e\":\n key = getch()\n #time.sleep(0.1)","def chacha(self):\n self.right()\n time.sleep(2)\n self.stop()\n self.back()\n time.sleep(1)\n self.servo(1000)\n time.sleep(1)\n self.stop()\n self.fwd()\n time.sleep(1)\n self.stop()\n self.servo(2000)\n time.sleep(1)\n self.stop()\n self.left()\n time.sleep(2)\n self.stop()","def gameloop(self):\r\n\r\n # What you see above (\"\"\" some text \"\"\") is called a docstring.\r\n # It explains the purpose of the method/function.\r\n # There should generally be one for every function.\r\n\r\n\r\n # Below is the main loop\r\n while True: \r\n # One cycle in the loop is equivalent to one frame.\r\n\r\n self.event()\r\n\r\n self.draw_objects()\r\n self.move_objects()\r\n\r\n self.update_display()","def run(self):\n\t\twhile 1:\n\t\t\tif self._driveSystem.port_open == True and self._parent.aborted==False:\n\n\t\t\t\tself._driveSystem.check_encoder_pos()\n\t\t\t\tpos=self._driveSystem.positions\n\t\t\t\tif self._parent.printRequest==True: #Print positions when print Button was pressed\n\t\t\t\t\toutput=\"Axis 1: \"+str(pos[0])+\"\\nAxis 2: \"+str(pos[1])+\"\\nAxis 3: \"+str(pos[2])+\"\\nAxis 4: \"+str(pos[3])\n\t\t\t\t\tprint(output)\n\t\t\t\t\tself._parent.printRequest=False\n\t\t\t\tevent = PosUpdateEvent(myEVT_POSUPDATE, -1, pos)\n\t\t\t\twx.PostEvent(self._parent.matplotpanel, event)\n\n\t\t\t\tt=0\n\t\t\t\twhile t<UPDATE_TIME:\n\t\t\t\t\tself.checkQ()\n\t\t\t\t\ttime.sleep(REAC_TIME)\n\t\t\t\t\tt=t+REAC_TIME\n\t\t\telse:\n\t\t\t\ttime.sleep(1)","def pause_handler(term):\n inp = None\n while inp not in (\"p\", \"P\", \"q\", \"Q\"):\n print(term.home + term.clear + term.move_y(term.height // 2))\n print(term.black_on_white(term.center(\"press P to continue.\")))\n\n inp = term.inkey(timeout=10)","def start():\n display_board()\n print(\"\\n\")\n y_n_prompt()","def main():\n\n r = np.arange(-90, 90, 2)\n tilt = 22.5\n\n with ptcmd.PTCMD(baud=57600) as controller:\n\n controller.home()\n\n for pan_angle in r:\n\n current_position = controller.get_position()\n pan_steps, tilt_steps, pan_rate, tilt_rate = system.move_to_angle(pan_angle, tilt, current_position[0], current_position[1], base_rate = 1000)\n controller.sync(pan_rate, pan_steps, tilt_rate, tilt_steps)\n controller.wait('all')\n\n time.sleep(2)\n\n distances = []\n for i in range(0,12):\n time.sleep(1)\n distances.append(controller.get_analog_sensor(1))\n\n distances.sort()\n distance = sum(distances[1:-1]) / len(distances[1:-1])\n\n x = math.sin(pan_angle*math.pi/180) * distance\n y = math.cos(pan_angle*math.pi/180) * distance\n\n print(distances, distance, pan_angle, x, y)\n\n plt.plot(x, y, 'b+')\n\n plt.show()","def do_simulation_loop(self) -> tuple[bool, bool]:\n running, reset = True, False\n for event in pygame.event.get():\n if check_for_quit(event):\n running = False\n elif check_for_reset(event):\n running = False\n reset = True\n self.simulation.do_step()\n self.update_visualization()\n self.simple_pygame.loop()\n return running, reset","def move():\n print(\" ------ Execution -----\\n\")\n pyautogui.moveRel(0, 10)\n pyautogui.moveRel(0, -10)\n pyautogui.click()","def example_move(self):\n self.right() # start rotating right\n time.sleep(1) # turn for a second\n self.stop() # stop\n self.servo(1000) # look right\n time.sleep(.25) # give your head time to move\n self.servo(2000) # look left","def example_move(self):\n self.right() # start rotating right\n time.sleep(1) # turn for a second\n self.stop() # stop\n self.servo(1000) # look right\n time.sleep(.25) # give your head time to move\n self.servo(2000) # look left","def run_cli_game():\n # Set up game\n view = ConsoleView()\n game = GameEngine(view)\n\n # Game loop\n while not game.game_over:\n view.turn_started()\n\n # Get move to make from user and execute it\n move = input()\n print()\n \n execute_move(move, game, view)","def run(self):\n \n t = 0\n while t < 10:\n self.reset()\n self.start_simulation()\n while not self.done:\n raw_input(\"Press Enter to continue...\")\n action = self.action_space.sample()\n print(action)\n state, reward, self.done, _ = self.step(action)\n print('Current state:\\n angles: {}'.format(state))\n print('Reward: {}'.format(reward))\n\n self.stop_simulation()\n t += 1","def robot_start():\n \n global history\n\n global position_x, position_y, current_direction_index\n \n robot_name = get_robot_name()\n output(robot_name, \"Hello kiddo!\")\n\n position_x = 0\n position_y = 0\n current_direction_index = 0\n\n command = get_command(robot_name)\n keep_history(command) \n while handle_command(robot_name, command):\n command = get_command(robot_name)\n keep_history(command)\n output(robot_name, \"Shutting down..\")\n\n history = []","def loop(self):\n rospy.loginfo(\"Hexapod entering main loop...\")\n rospy.loginfo(\" Waiting for initial velocity command on /hexapod/cmd_vel/ ...\")\n while self.last_vel_cmd is None:\n self._loop_rate.sleep()\n\n # start main loop\n while not rospy.is_shutdown():\n\n chassis_pos_delta = None\n if self.last_vel_cmd is not None:\n dt = 1 # FIXME: Temporary for debugging\n lin_disp_lmt = self.linear_displacement_limit\n ang_disp_lmt = self.angular_displacement_limit\n chassis_pos_delta = Twist()\n chassis_pos_delta.linear.x = clamp(self.last_vel_cmd.linear.x*dt, -lin_disp_lmt, lin_disp_lmt)\n chassis_pos_delta.linear.y = clamp(self.last_vel_cmd.linear.y*dt, -lin_disp_lmt, lin_disp_lmt)\n chassis_pos_delta.linear.z = clamp(self.last_vel_cmd.linear.z*dt, -lin_disp_lmt, lin_disp_lmt)\n chassis_pos_delta.angular.x = clamp(self.last_vel_cmd.angular.x*dt, -ang_disp_lmt, ang_disp_lmt)\n chassis_pos_delta.angular.y = clamp(self.last_vel_cmd.angular.y*dt, -ang_disp_lmt, ang_disp_lmt)\n chassis_pos_delta.angular.z = clamp(self.last_vel_cmd.angular.z*dt, -ang_disp_lmt, ang_disp_lmt)\n self.last_vel_cmd = None\n\n if chassis_pos_delta is not None \\\n and not self._check_if_twist_msg_is_zero(chassis_pos_delta, linear_threshold=0.005, angular_threshold=0.01):\n # Get chassis position transformation\n chassis_pos_rot = transforms.euler_matrix(chassis_pos_delta.angular.x,\n chassis_pos_delta.angular.y,\n chassis_pos_delta.angular.z)[:3,:3]\n\n rospy.loginfo(\"chassis_pos_rot: %s\", chassis_pos_rot)\n chassis_pos_trans = np.zeros([3])\n chassis_pos_trans[0] = chassis_pos_delta.linear.x\n chassis_pos_trans[1] = chassis_pos_delta.linear.y\n chassis_pos_trans[2] = chassis_pos_delta.linear.z\n chassis_translation = np.dot(chassis_pos_trans, chassis_pos_rot)\n rospy.loginfo(\"chassis_translation: %s\", chassis_translation)\n\n leg_target_eff_translation = [[]]*LEGS\n # Get leg base positions relative to chassis\n leg_base_positions = self._get_base_to_leg_base_fk()\n for i, leg_base_pos in enumerate(leg_base_positions):\n leg_base_pos_arr = np.array(leg_base_pos).reshape(3,1)\n leg_base_pos_arr_new = np.dot(chassis_pos_rot, leg_base_pos_arr)\n leg_base_pos_trans_4 = np.ones(4).reshape(4,1)\n leg_base_pos_trans_4[:3,:] = leg_base_pos_arr_new\n # get leg base translations relative to leg_base coordinate frame\n relative_trans = np.dot(np.linalg.inv(self.kdl_fk_base_to_leg_base[i].forward([])), leg_base_pos_trans_4)\n relative_trans = relative_trans.reshape(1,4).tolist()[0][:3]\n leg_target_eff_translation[i] = relative_trans\n\n # Get leg target end-effector translations\n for i, q in enumerate(self.leg_jt_home_pos):\n base_to_leg_base_rot = self.kdl_fk_base_to_leg_base[i].forward([])[:3,:3]\n leg_target_eff_trans = np.dot(np.linalg.inv(base_to_leg_base_rot),chassis_translation).tolist()[0]\n leg_target_eff_translation[i] = [x+y for x,y in zip(leg_target_eff_translation[i], leg_target_eff_trans)] # TODO: FIXME: Technically incorrect\n\n # 1: side_alpha legs lift, plant to +transformation\n rospy.loginfo(\"1: side_alpha legs lift, plant to +transformation\")\n if self._odd_starts:\n active_legs = [1,2,5]\n else: # even starts\n active_legs = [0,3,4]\n\n init_wp = WaypointMsg()\n lift_wp = WaypointMsg()\n end_wp = WaypointMsg()\n\n legs_jt_init_pos = self._get_joint_angles()\n leg_eff_cur_pos = self._get_leg_base_to_eff_fk(legs_jt_init_pos)\n for i in range(LEGS):\n motor_names = [name for name in self.hebi_mapping[i]]\n # INITIAL POSITION\n init_wp.names.extend(motor_names)\n init_wp.positions.extend(legs_jt_init_pos[i])\n init_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n init_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n # LIFT\n lift_wp.names.extend(motor_names)\n if i in active_legs:\n # apply translation\n leg_lift_eff_target_pos = [(x + y + z) / 2.0 for x, y, z in zip(leg_eff_cur_pos[i], self.leg_eff_home_pos[i], leg_target_eff_translation[i])]\n leg_lift_eff_target_pos = [x + y for x,y in zip(leg_lift_eff_target_pos, self.leg_eff_step_height[i])]\n # get ik\n leg_lift_jt_target_pos = self._get_pos_ik(self.trac_ik_leg_base_to_end[i], legs_jt_init_pos[i],\n leg_lift_eff_target_pos, seed_xyz=self.leg_eff_home_pos[i])\n lift_wp.positions.extend(leg_lift_jt_target_pos)\n lift_wp.velocities.extend([NAN]*ACTUATORS_PER_LEG)\n lift_wp.accelerations.extend([NAN]*ACTUATORS_PER_LEG)\n else:\n lift_wp.positions.extend(legs_jt_init_pos[i])\n lift_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n lift_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n # PLANT\n end_wp.names.extend(motor_names)\n if i in active_legs:\n # apply translation\n leg_plant_eff_target_pos = [x + y for x,y in zip(self.leg_eff_home_pos[i], leg_target_eff_translation[i])]\n leg_plant_eff_target_pos[2] = self.leg_eff_home_pos[i][2] # end eff z-position should match home z-position\n # get ik\n leg_plant_jt_target_pos = self._get_pos_ik(self.trac_ik_leg_base_to_end[i], leg_lift_jt_target_pos,\n leg_plant_eff_target_pos, seed_xyz=leg_lift_eff_target_pos)\n end_wp.positions.extend(leg_plant_jt_target_pos)\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n else:\n end_wp.positions.extend(legs_jt_init_pos[i])\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n\n goal = TrajectoryGoal()\n goal.waypoints.append(init_wp)\n goal.waypoints.append(lift_wp)\n goal.waypoints.append(end_wp)\n goal.times.extend([0.0, 0.4, 0.8])\n\n self.release_pos([1,2,3,4,5,6])\n self.trajectory_action_client.send_goal(goal)\n self.trajectory_action_client.wait_for_result()\n self.hold_pos([1,2,3,4,5,6])\n\n # 2: side_alpha legs push to new home positions; side_beta legs push to -transformation\n rospy.loginfo(\"2: side_alpha legs push to new home positions; side_beta legs push to -transformation\")\n if self._odd_starts:\n active_legs = [0,3,4]\n else: # even starts\n active_legs = [1,2,5]\n\n init_wp = WaypointMsg()\n end_wp = WaypointMsg()\n\n legs_jt_init_pos = self._get_joint_angles()\n for i in range(LEGS):\n motor_names = [name for name in self.hebi_mapping[i]]\n # INITIAL POSITION\n init_wp.names.extend(motor_names)\n init_wp.positions.extend(legs_jt_init_pos[i])\n init_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n init_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n # PUSH\n end_wp.names.extend(motor_names)\n if i in active_legs:\n # apply -translation\n leg_plant_eff_target_pos = [x + y for x,y in zip(self.leg_eff_home_pos[i], [-val for val in leg_target_eff_translation[i]])]\n leg_plant_eff_target_pos[2] = self.leg_eff_home_pos[i][2] # end eff z-position should match home z-position\n # get ik\n leg_plant_jt_target_pos = self._get_pos_ik(self.trac_ik_leg_base_to_end[i], legs_jt_init_pos[i],\n leg_plant_eff_target_pos, seed_xyz=self.leg_eff_home_pos[i])\n end_wp.positions.extend(leg_plant_jt_target_pos)\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n else:\n end_wp.positions.extend(self.leg_jt_home_pos[i])\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\n\n goal = TrajectoryGoal()\n goal.waypoints.append(init_wp)\n goal.waypoints.append(end_wp)\n goal.times.extend([0.0, 0.4])\n\n self.release_pos([1,2,3,4,5,6])\n self.trajectory_action_client.send_goal(goal)\n self.trajectory_action_client.wait_for_result()\n self.hold_pos([1,2,3,4,5,6])\n\n self._odd_starts = not self._odd_starts\n\n self._loop_rate.sleep() # FIXME: Doesn't make sense to use this unless re-planning trajectories\n # end main loop","def bye_bye():\n\n os.system(\"clear\")\n print(\"Your opponent was too strong...\")\n time.sleep(1)\n print(\"You've should be better prepared...\")\n time.sleep(2)\n print()\n print()\n for i in range(20):\n os.system(\"clear\")\n print(\"\"\"\n * ) ( \n ( ( ( ` ( /( )\\ ) \n )\\ ) )\\ )\\))( ( )\\())( ( ( (()/( \n (()/( ((((_)( ((_)()\\ )\\ ((_)\\ )\\ )\\ )\\ /(_)) \n /(_))_)\\ _ )\\(_()((_|(_) ((_|(_)((_|(_)(_)) \n (_)) __(_)_\\(_) \\/ | __| / _ \\ \\ / /| __| _ \\ \n | (_ |/ _ \\ | |\\/| | _| | (_) \\ V / | _|| / \n \\___/_/ \\_\\|_| |_|___| \\___/ \\_/ |___|_|_\\ \"\"\")\n time.sleep(0.05)\n os.system(\"clear\")\n print(\"\"\"\n * ) ( \n ( ( ( ` ( /( )\\ ) \n )\\ ) )\\ )\\))( ( )\\())( ( ( (()/( \n (()/( ((((_)( ((_)()\\ )\\ ((_)\\ )\\ )\\ )\\ /(_)) \n /(_))_)\\ _ )\\(_()((_|(_) ((_|(_)((_|(_)(_)) \n (_)) __(_)_\\(_) \\/ | __| / _ \\ \\ / /| __| _ \\ \n | (_ |/ _ \\ | |\\/| | _| | (_) \\ V / | _|| / \n \\___/_/ \\_\\|_| |_|___| \\___/ \\_/ |___|_|_\\ \"\"\")\n time.sleep(0.05)\n os.system(\"clear\")\n print(\"\"\"\n * ) ( \n ( ( ( ` ( /( )\\ ) \n )\\ ) )\\ )\\))( ( )\\())( ( ( (()/( \n (()/( ((((_)( ((_)()\\ )\\ ((_)\\ )\\ )\\ )\\ /(_)) \n /(_))_)\\ _ )\\(_()((_|(_) ((_|(_)((_|(_)(_)) \n (_)) __(_)_\\(_) \\/ | __| / _ \\ \\ / /| __| _ \\ \n | (_ |/ _ \\ | |\\/| | _| | (_) \\ V / | _|| / \n \\___/_/ \\_\\|_| |_|___| \\___/ \\_/ |___|_|_\\ \"\"\")\n os.system(\"clear\")\n time.sleep(0.05)\n print(\"\"\"\n * ) ( \n ( ( ( ` ( /( )\\ ) \n )\\ ) )\\ )\\))( ( )\\())( ( ( (()/( \n (()/( ((((_)( ((_)()\\ )\\ ((_)\\ )\\ )\\ )\\ /(_)) \n /(_))_)\\ _ )\\(_()((_|(_) ((_|(_)((_|(_)(_)) \n (_)) __(_)_\\(_) \\/ | __| / _ \\ \\ / /| __| _ \\ \n | (_ |/ _ \\ | |\\/| | _| | (_) \\ V / | _|| / \n \\___/_/ \\_\\|_| |_|___| \\___/ \\_/ |___|_|_\\ \"\"\")\n os.system(\"clear\")\n time.sleep(0.05)\n print(\"\"\"\n * ) ( \n ( ( ( ` ( /( )\\ ) \n )\\ ) )\\ )\\))( ( )\\())( ( ( (()/( \n (()/( ((((_)( ((_)()\\ )\\ ((_)\\ )\\ )\\ )\\ /(_)) \n /(_))_)\\ _ )\\(_()((_|(_) ((_|(_)((_|(_)(_)) \n (_)) __(_)_\\(_) \\/ | __| / _ \\ \\ / /| __| _ \\ \n | (_ |/ _ \\ | |\\/| | _| | (_) \\ V / | _|| / \n \\___/_/ \\_\\|_| |_|___| \\___/ \\_/ |___|_|_\\ \"\"\")\n time.sleep(0.05)","def run():\n step = 0\n while traci.simulation.getMinExpectedNumber() > 0:\n traci.simulationStep()\n step+=1\n traci.close()\n sys.stdout.flush()","async def loop():\n # ArmDevice.storage.joints_pos = await get_positions() # Use this if encoders are wired up.\n # ArmDevice.storage.joints_pos = simulate_positions() # Use this for testing without position feedback.\n log.debug(\"command: {}\".format(ArmDevice.storage.command))\n ArmDevice.storage.controller.user_command(ArmDevice.storage.mode, *ArmDevice.storage.command)\n ArmDevice.storage.speeds = ArmDevice.storage.controller.update_duties(ArmDevice.storage.joints_pos)\n\n # publish speeds/duty cycles here\n log.debug(\"joints_pos: {}\".format(ArmDevice.storage.joints_pos))\n log.debug(\"speeds: {}\".format(ArmDevice.storage.speeds))\n await send_duties()","def GAMEOVER_LOOP():\n pass","def run_game():\n set_locations()\n while True:\n draw_dungeon()\n valid_moves = get_moves('player')\n print(\"You're currently in room {}.\".format(STATUS['locations']['player']))\n print(\"You are currently {}.\".format(STATUS['weapon']))\n print(\"{}\".format(monster_check()))\n print(\"You can move {} (w/a/s/d)\"\n .format(', '.join(parse_moves(valid_moves))))\n move = input(\"> \").upper()\n while move not in valid_moves:\n clear_screen()\n print(\"There's no door that way... \")\n draw_dungeon()\n move = input(\"> \").upper()\n clear_screen()\n else:\n clear_screen()\n move_player(move)\n weapon_check()","def move():\n Robot.move()","def runemelt(n):\n\n print (\"place mouse at bank position, will document in 5s\") #Determine bank position\n rt.wait(5)\n bank_position = gui.position()\n (xbank, ybank) = bank_position #assign seperate paramaters to positions so we can randomize them\n print (\"Bank position = \", bank_position)\n \n print (\"place mouse at last ore position, will document in 5s\") #Determine 3rd ore position\n rt.wait(5)\n ore_position = gui.position()\n (xore,yore) = ore_position\n print( \"last ore position = \", ore_position)\n\n print (\"get ready, melting will begin in 5s\")\n rt.wait(5)\n\n for i in range(int(n/3)+1):\n randxbank = int(random.gauss(xbank,15))\n randybank = int(random.gauss(ybank,15))\n randxore = int(random.gauss(xore,5))\n randyore = int(random.gauss(yore,5))\n \n process = float(i+1)/float(n/3)*100 #calculate percentage till done\n eta = (n/3)*11 - i*11 \n\n mv.randmove(randxore,randyore,randxbank,randybank,10,0.5) #Move to bank\n rt.wait(0.1)\n \n mouse.click() #click mouse\n rt.wait(0.5)\n\n kb.press(\"2\",0.2) #press 2\n\n mv.randmove(randxbank,randybank,randxore,randyore,10,0.5) #move to ore position\n rt.wait(0.7)\n \n for i in range(3): #three times\n\n kb.press(\"2\",0.2) #press 2\n rt.wait(0.3)\n\n mouse.click() #click mouse\n rt.wait(1)\n\n #USER update on progress:\n #Process: 0.00% ETA: 00hour 00min 00s\n\n print (\"PROCESS: \", '%.2f' % process,\"% \", \"ETA: \", int(int(eta)/3600), \"hour\",int(int(eta)/60-((int(eta)/3600)*60)),\"min\",int(eta)%60,\"sec\")","def run_test_move_arm_to_position():\r\n print()\r\n print(\"-----------------------------------------=-\")\r\n print(\"Testing the move_arm_to_position method\")\r\n print(\" of the ArmAndClaw class.\")\r\n print(\"-------------------------------------------\")\r\n print()\r\n\r\n # Start with a fresh (uncalibrated) ArmAndClaw.\r\n robot = rb.RoseBot()\r\n\r\n # Positions to which to move the Arm, one at a time.\r\n positions = [1200, 200, 1000, 2000, 1000, 500, 14 * 360, 0]\r\n print()\r\n print(\"READ the above tests to know what movement to expect\")\r\n print(\"in the following tests.\")\r\n\r\n try:\r\n for k in range(len(positions)):\r\n print()\r\n print(\"Press the ENTER key when ready for the robot\")\r\n print(\"to move to position {}.\".format(positions[k]))\r\n print(\"Since it has not yet been calibrated, it will first\")\r\n print(\"go UP, then DOWN, to calibrate, then to the above position.\")\r\n print(\" If it does NOT do that and seems to be stuck,\")\r\n input(\" press Control-C to force this test to stop.\")\r\n\r\n # -----------------------------------------------------------------\r\n #: 8. Replace the pass statement below with a call to\r\n # the move_arm_to_position method on the arm_and_claw\r\n # of the given RoseBot, sending it positions[k].\r\n # -----------------------------------------------------------------\r\n robot.arm_and_claw.move_arm_to_position(positions[k])\r\n\r\n except KeyboardInterrupt:\r\n print()\r\n print(\"OK, you just did a keyboard interrupt (Control-C).\")\r\n print(\"No worries. The program will keep running from here.\")","def test(self):\n while True: \n gyX, gyY, gyZ = self.getGyro()\n accX, accY, accZ = self.getAcc()\n print(\"Gyroscope: X: %.2f Y: %.2f Z: %.2f\" %(gyX,gyY,gyZ))\n print(\"Accelerom: X: %.2f Y: %.2f Z: %.2f\" %(accX,accY,accZ))\n \n time.sleep(0.5)","def postloop() -> None:\n print(\"\\n\")","def do_motion_detection():\n current_count = get_last_counter()\n if not imageNumOn:\n print(\"%s INFO : File Naming by Date Time Sequence\" % get_now())\n while True:\n x_pos, y_pos = scan_motion()\n file_name = get_file_name(imagePath, imageNamePrefix, current_count)\n take_day_image(file_name)\n if imageNumOn:\n current_count += 1\n # Convert xy movement location for full size image\n mo_x = x_pos * X_MO_CONV\n mo_y = y_pos * Y_MO_CONV\n if verbose:\n print(\"%s INFO : Motion xy(%d,%d) Saved %s (%ix%i)\"\n % (get_now(), mo_x, mo_y, file_name,\n imageWidth, imageHeight,))","def main():\r\n turn_left()\r\n move_three_times()\r\n turn_right()\r\n move_three_times()\r\n turn_right()\r\n move_three_times()\r\n turn_left()","def play_one_move(self):\n self.print(\"top of move\")\n # 1) grab three cups\n c1 = self.take_cup_after(self.current_cup_idx())\n c2 = self.take_cup_after(self.current_cup_idx())\n c3 = self.take_cup_after(self.current_cup_idx())\n print(f\"pick up: {c1}, {c2}, {c3}\")\n self.print(\"after pickup\")\n\n # 2) find a destination cup\n destination_idx = self.find_next_destination(self.current_cup)\n print(\n f\"destination index is {destination_idx}, cup is {self.cups[destination_idx]}\"\n )\n\n # 3) insert cups back into the circle\n self.add_cups(destination_idx, [c1, c2, c3])\n self.print(\"after adding cups..\")\n\n # 4) select the next cup\n self.select_next_cup()\n\n self.print(\"post move\")","def _main_loop(scr):\n\tglobal curr_player\n\tbob = Player()\n\tbob.name = 'Bob'\n\tcurr_player = bob\n\n\twhile 1:\n\t\t# Keep player in bounds (should actually change maps)\n\t\tif bob.map_coords[0] > 79:\n\t\t\tbob.map_coords[0] = 0\n\t\tif bob.map_coords[0] < 0:\n\t\t\tbob.map_coords[0] = 79\n\t\tif bob.map_coords[1] > 19:\n\t\t\tbob.map_coords[1] = 0\n\t\tif bob.map_coords[1] < 0:\n\t\t\tbob.map_coords[1] = 19\n\t\ttime.sleep(0.01)\n\n\t\tscr.erase()\n\t\tscr.addstr(bob.map_coords[1], bob.map_coords[0], '@')\n\n\t\t_draw_info_area(scr)\n\t\t_handle_input(scr)","def loop(self):\n pass","def step(self, action):\n\n action[1] = 0 if action[1] < 0 else 1\n\n if not self.moving:\n self.agent_host.sendCommand(\"move 0.5\")\n time.sleep(.2)\n self.moving = True\n\n # Get Action\n command = \"strafe \" + str(action[0])\n if ((action[0] < 0 and self.allow_left) or (action[0] > 0 and self.allow_right)):\n self.agent_host.sendCommand(command)\n time.sleep(.2)\n self.agent_host.sendCommand(\"strafe 0\")\n time.sleep(.1)\n\n if action[1]:\n if self.checkCommand:\n self.jumpsOverDitches += 1\n self.checkCommand = False\n self.agent_host.sendCommand(\"jump 1\")\n time.sleep(.2)\n self.agent_host.sendCommand(\"jump 0\")\n\n # if (command == \"crouch 1\"):\n # self.agent_host.sendCommand(command)\n # time.sleep(.3)\n # self.agent_host.sendCommand(\"crouch 0\")\n # time.sleep(.2)\n\n self.episode_step += 1\n\n # Get Observation\n world_state = self.agent_host.getWorldState()\n for error in world_state.errors:\n print(\"Error:\", error.text)\n self.obs, self.allow_left, self.allow_right, curZPos, curXPos = self.get_observation(world_state)\n if curZPos:\n self.curZPos = curZPos\n if curXPos:\n if self.obs[3 + int(curXPos)]:\n self.checkCommand = True\n self.numDitchesEncountered += 1\n\n # Get Done\n done = not world_state.is_mission_running \n\n # Get Reward\n reward = 0\n for r in world_state.rewards:\n reward += r.getValue()\n self.episode_return += reward\n\n return self.obs, reward, done, dict()","def run(self):\n while not self.turn_over:\n self.go()","def intro_instructions():\n print(\"The board will be updated after each move.\")\n print(\"Watch both the board and the python prompt after each move.\")\n print(\"Player 1 is white and player 2 is orange\")\n print(\"Green boxes are snakes and yellow boxes are ladders.\")\n print(\"If you hit any part of the snake(not just the head), you will slide down to the snakes tail\")\n print(\"If you hit any part of the ladder(not just the bottom), you will climb to the ladder's top\")\n print(\"May the luckiest player win\")","def loop1(self, move, new_state, i):\n if move == i[0]:\n # analyze another cell\n if new_state.letters[i[1]].isalpha():\n new_state.claim[i[2]] \\\n = new_state.get_current_player_name()[1]\n # analyze the other 3 cells\n if (new_state.get_current_player_name()[1]\n == new_state.letters[i[3]]\n or new_state.get_current_player_name()[1]\n == new_state.letters[i[4]]\n or new_state.get_current_player_name()[1]\n == new_state.letters[i[5]]) \\\n and new_state.claim[i[6]] == \"@\":\n new_state.claim[i[6]] \\\n = new_state.get_current_player_name()[1]\n # analyze the other 4 cells\n count = 0\n for x in [new_state.letters[i[7]],\n new_state.letters[i[8]],\n new_state.letters[i[9]],\n new_state.letters[i[10]]]:\n if new_state.get_current_player_name()[1] == x:\n count += 1\n if count == 2 and new_state.claim[i[11]] == \"@\":\n new_state.claim[i[11]] = \\\n new_state.get_current_player_name()[1]\n new_state.letters = [self.get_current_player_name()[1]\n if i == move else i for i in self.letters]\n return new_state","def win():\n try:\n color.write(\"=============================================\\n\",\"BUILTIN\")\n print(\"Ctrl + C to skip!\")\n slow_print(\"Finally\")\n intro_dots()\n slow_print(\"I am here at the Star of Tangaroa~\")\n time.sleep(0.5)\n slow_print(\"I wield the fishing rod of legends, and it is now time for the greatest catch~\")\n time.sleep(0.5)\n slow_print(\"Time to fish.~~\",\"ERROR\")\n except:\n pass\n fishing = True\n while fishing:\n command = input(\"Enter a command: \").lower()\n if command == 'fish' or command == 'f' or command == 'fishing':\n fishing = False\n else:\n color.write(\"The time for the greatest catch is here. You wouldn't miss this for the world would you?\\n\\n\",\"ERROR\")\n\n try:\n color.write(\"=============================================\\n\",\"BUILTIN\")\n print(\"Ctrl + C to skip!\")\n slow_print(\"Nnngh!~\")\n time.sleep(0.5)\n slow_print(\"This is a big one!~\")\n time.sleep(0.5)\n slow_print(\"BUT I AM MĀUI-POTIKI, AND NO CATCH WILL BEST ME!~\")\n time.sleep(0.5)\n slow_print(\"THIS~\",\"ERROR\")\n time.sleep(0.2)\n slow_print(\"IS~\",\"ERROR\")\n time.sleep(0.2)\n slow_print(\"MY~\",\"ERROR\")\n time.sleep(0.2)\n slow_print(\"LEGEND!~\",\"ERROR\")\n time.sleep(2)\n \n except:\n pass\n ending(\"win\")","def execute_pause(self):\n print(self.empty_lines + self.double_tab + \"to continue press any key..\\r\")\n self.getch()","def move_player(direction):\n global ZERO_BASE_PLYR_POS\n if direction == \"north\":\n ZERO_BASE_PLYR_POS -= 10\n elif direction == \"south\":\n ZERO_BASE_PLYR_POS += 10\n elif direction == \"west\":\n ZERO_BASE_PLYR_POS -= 1\n elif direction == \"east\":\n ZERO_BASE_PLYR_POS += 1\n \n sleep(0.5) # all moves have a 0.5 second delay\n \n show_ground_feature()","def loop(self):\r\n while True:\r\n for event in pygame.event.get():\r\n if event.type == pygame.QUIT:\r\n return\r\n if not self.done:\r\n self.update_path()\r\n self.algorithm()\r\n\r\n self.screen.fill(self.LINE_COLOR)\r\n self.draw_board()\r\n pygame.display.flip()\r\n self.clock.tick(self.FPS)","def interact():\n env = SnakeEnv()\n done = False\n r = 0\n action = random.randrange(4)\n delay_time = 0.2\n\n # After the first run of the method env.render()\n # env.renderer.viewer obtains an attribute 'window'\n # which is a pyglet.window.Window object\n env.render(mode='human')\n # Use the arrows to control the snake's movement direction\n @env.renderer.viewer.window.event\n def on_text_motion(motion):\n \"\"\"\n Events to actions mapping\n \"\"\"\n\n nonlocal action\n if motion == MOTION_UP:\n action = 0\n elif motion == MOTION_DOWN:\n action = 2\n elif motion == MOTION_LEFT:\n action = 3\n elif motion == MOTION_RIGHT:\n action = 1\n\n while not done:\n time.sleep(delay_time)\n obs, reward, done, info = env.step(action)\n env.render(mode='human')\n if reward:\n r += reward\n # Speeding up snake after eating food\n delay_time -= 1/6 * delay_time\n\n return r","def print_position(self):\n\n while True:\n lat = self.vehicle.location.global_relative_frame.lat\n lon = self.vehicle.location.global_relative_frame.lon\n try:\n self.pathFile.write('{0},{1}'.format(lat, lon))\n time.sleep(1)\n except:\n break\n #print ('{0},{1}'.format(lat, lon))","def main():\n while True:\n # Get envrionment data\n env_text = (\"{temperature:0.1f}°F {humidity:0.1f}% {pressure:0.1f}mb\"\n \"\".format(\n temperature=fahrenheit(sense.get_temperature()),\n humidity=sense.get_humidity(),\n pressure=sense.get_pressure(),\n ))\n \n # Display on stdout\n os.system('clear')\n print(env_text)\n\n # Display on sense-hat\n sense.set_rotation(0)\n sense.show_message(\n env_text,\n scroll_speed=0.05,\n text_colour=random_color(),\n back_colour=e,\n )","def loop(self):\n running = True\n while running:\n key_input = pygame.key.get_pressed()\n for event in pygame.event.get():\n if event.type is pygame.QUIT:\n running = False\n if key_input[pygame.K_ESCAPE]:\n running = False\n\n # Player horizonal\n if key_input[pygame.K_LEFT] and key_input[pygame.K_RIGHT]:\n self.player.stop_moving()\n elif key_input[pygame.K_LEFT]:\n self.player.start_moving_left()\n elif key_input[pygame.K_RIGHT]:\n self.player.start_moving_right()\n else:\n self.player.stop_moving()\n\n # Player jump\n if key_input[pygame.K_z]:\n self.player.start_jump()\n else:\n # released?\n self.player.stop_jump()\n\n self.clock.tick(self.fps)\n \n self.update(self.clock.get_time())\n\n self.draw()","def main_loop(self):\n dt = 0.3\n self.clock.tick(self.fps)\n while not self.done:\n self.event_loop()\n self.update(dt)\n self.render()\n dt = self.clock.tick(self.fps)/1000.0 # create delta time variable to multiply with movement and rotation\n self.display_fps()\n self.health_bar()\n self.enemy_health()\n self.energy_bar()","def camonitor(self):\n\n try:\n self._mov_ev.clear()\n while not self._mov_ev.is_set():\n print(\"\\r {0:4f}\".format(self.wm()), end=\" \")\n self._mov_ev.wait(0.1)\n except KeyboardInterrupt:\n pass\n finally:\n self._mov_ev.clear()","def intro_dots():\n i = 0\n time.sleep(0.6)\n while i != 3:\n color.write(\".\")\n time.sleep(0.3)\n i += 1\n print(\"\")","def move(self, direction):\n command = self.DIRECTIONS[direction][\"command\"]\n mem, out = self.cpu.run_program(inputs=[command])\n status = out.pop()\n if status in (1, 2):\n self.position = Point(\n self.position.x + self.DIRECTIONS[direction][\"mask\"][0],\n self.position.y + self.DIRECTIONS[direction][\"mask\"][1]\n )\n if self.display:\n self.draw_grid()\n sleep(self.delay)\n return status","def printMovement(fltXCurrent, fltYCurrent, fltXNew, fltYNew):\r\n \r\n print(\"Moving from (\" + str(fltXCurrent) + \", \" +\r\n str(fltYCurrent) + \")\")\r\n \r\n print(\"to\" + \" \" * 10 + \"(\" + str(fltXNew) + \", \" +\r\n str(fltYNew) + \").\")","def run(self):\n while not self.done:\n time_delta = self.clock.tick(self.fps)\n self.event_loop()\n self.update(time_delta)\n pg.display.update()\n if self.show_fps:\n fps = self.clock.get_fps()\n with_fps = \"{} - {:.2f} FPS\".format(self.caption, fps)\n pg.display.set_caption(with_fps)"],"string":"[\n \"def main_loop(self):\\n center_point = self.mot.center_point\\n\\n screen_width = center_point[0] * 2\\n screen_height = center_point[1] * 2\\n\\n time.sleep(1)\\n pretty_progress_bar(\\n 3,\\n )\\n\\n # while int(time.time()) - start <= 10:\\n while not self.mot.abort:\\n object1_position = self.mot.position(self.color1)[0]\\n object2_velocity = self.mot.speed(self.color2)\\n # print(object2_velocity)\\n\\n self.compare(object1_position[0] < 0.25 * screen_width, 'left')\\n self.compare(object1_position[0] > 0.75 * screen_width, 'right')\\n self.compare(object1_position[1] < 0.25 * screen_height, 'jump')\\n self.burst_compare(object2_velocity > 150, 'fire')\\n\\n # print('KEYBOARD ABORT')\",\n \"def tray_game():\\r\\n\\r\\n print(term.home + term.on_green + term.clear)\\r\\n\\r\\n print(term.black + term.move_xy(0,0) + (\\\"┏\\\"), end='')\\r\\n i = 0\\r\\n while i < 20:\\r\\n i = i + 1 \\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"┳\\\"), end='')\\r\\n print(term.move_xy(80,0) + (\\\"┓\\\"), end='')\\r\\n \\r\\n y = 0\\r\\n print(term.black + term.home + term.move_down(y) + (\\\"┃\\\"), end='')\\r\\n i = 0\\r\\n while i < 20 :\\r\\n i = i + 1 \\r\\n print(term.black + term.move_right(3) + (\\\"┃\\\"), end='')\\r\\n \\r\\n x, y, j = 0, 1, 0\\r\\n while j < 19: \\r\\n \\r\\n y = y + 1\\r\\n print(term.black + term.home + term.move_y(y) + (\\\"┣\\\"), end='')\\r\\n \\r\\n i = 0\\r\\n while i < 20 :\\r\\n i = i + 1 \\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"╋\\\"), end='')\\r\\n print(term.black + term.home + term.move_xy(80,y) + (\\\"┫\\\"), end='')\\r\\n \\r\\n y = y + 1\\r\\n print(term.black + term.home + term.move_down(y) + (\\\"┃\\\"), end='')\\r\\n i = 0\\r\\n while i < 20 :\\r\\n i = i + 1 \\r\\n print(term.black + term.move_right(3) + (\\\"┃\\\"), end='')\\r\\n j = j + 1\\r\\n \\r\\n print(term.black + term.move_xy(0,40) + (\\\"┗\\\"), end='')\\r\\n i = 0\\r\\n while i < 20:\\r\\n i = i + 1 \\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"━\\\"), end='')\\r\\n print(term.black + term.move_right(-1) + (\\\"┻\\\"), end='')\\r\\n print(term.move_xy(80,40) + (\\\"┛\\\"), end='')\",\n \"def timer():\\r\\n\\r\\n T = 0\\r\\n while True:\\r\\n print (term.white + term.move_xy(82,1) + 'TIMER : ', end='')\\r\\n print(T, end='\\\\r')\\r\\n time.sleep(1)\\r\\n T = T + 1\",\n \"def console():\\r\\n while True:\\r\\n interpret_command(input(\\\"POM> \\\"))\",\n \"def move_repeatedly():\\n check = check50.run(run_command)\\n check.stdin(\\\"WEST\\\").stdout(room_2_description)\\n check.stdin(\\\"EAST\\\").stdout(room_1_name)\\n check.stdin(\\\"WEST\\\").stdout(room_2_name)\",\n \"def run(self):\\n move_cmd = Twist()\\n move_cmd.linear.x = 0\\n move_cmd.angular.z = 0\\n\\n while not rospy.is_shutdown():\\n # bump logic as previous psets\\n if self.bump:\\n self.bump = False\\n # move backwards\\n move_cmd.linear.x = LIN_SPEED * -1\\n for i in range(5):\\n self.cmd_vel.publish(move_cmd)\\n self.rate.sleep()\\n rospy.sleep(1)\\n\\n # turn randomly in a random direction\\n move_cmd.linear.x = 0\\n move_cmd.angular.z = ROT_SPEED * ((-1)**random.randint(1,2))\\n\\n if self.bump == 0:\\n move_cmd.angular.z = ROT_SPEED * (-1)\\n elif self.bump == 2:\\n move_cmd.angular.z = ROT_SPEED\\n\\n for i in range(random.randint(5,15)):\\n self.cmd_vel.publish(move_cmd)\\n self.rate.sleep()\\n rospy.sleep(1)\\n\\n move_cmd.angular.z = 0\\n # if somethin in the screen is really close\\n elif self.min_val < MIN_THRESHOLD:\\n # make sure it's not the sock/leg warmer, and is actually an obstacle\\n if self.obstacle_x <= self.x or self.obstacle_x >= self.x + self.w or abs(self.min_val - self.dist) > 0.1:\\n move_cmd.linear.x = 0\\n # turn away\\n if self.obstacle_x > 320:\\n move_cmd.angular.z = ROT_SPEED / 2\\n else:\\n move_cmd.angular.z = -ROT_SPEED / 2\\n # self.min_val = 100\\n for i in range(10):\\n self.cmd_vel.publish(move_cmd)\\n self.rate.sleep()\\n self.last_move = rospy.Time.now()\\n else:\\n rospy.loginfo(\\\"Perimeter \\\" + str(self.perimeter_size))\\n rospy.loginfo(\\\"Distance is \\\" + str(self.dist))\\n\\n # normalize angle error to rot speed\\n ang_error_norm = -float(self.ang_error) / 100\\n\\n # set min and max rot speed\\n if ang_error_norm < -ROT_SPEED:\\n ang_error_norm = -ROT_SPEED\\n elif ang_error_norm > ROT_SPEED:\\n ang_error_norm = ROT_SPEED\\n\\n move_cmd.angular.z = ang_error_norm\\n\\n if RACE == False:\\n # normalize dist error to lin speed\\n self.dist_error = self.dist - 0.5\\n dist_error_norm = float(self.dist_error) / 2\\n\\n if dist_error_norm < 0:\\n # if NaN (self.dist gets set to -1)\\n if dist_error_norm > -0.7:\\n self.lost = 0\\n # if too close\\n else:\\n self.lost += 1\\n # if it's been more than 2 seconds\\n if rospy.Time.now() > self.last_move + rospy.Duration(2):\\n dist_error_norm = 0\\n # if been lost for a while rotate and beep\\n if self.lost > 20:\\n move_cmd.angular.z = ROT_SPEED / 4\\n self.beep.publish(4)\\n else:\\n # continue as previous\\n dist_error_norm = self.last_speed\\n else:\\n # set max lin speed\\n if dist_error_norm > LIN_SPEED:\\n dist_error_norm = LIN_SPEED\\n\\n # reset lost stats\\n self.lost = 0\\n self.last_speed = dist_error_norm\\n self.last_move = rospy.Time.now()\\n\\n move_cmd.linear.x = dist_error_norm\\n else:\\n move_cmd.linear.x = LIN_SPEED\\n\\n self.cmd_vel.publish(move_cmd)\",\n \"def main(scr):\\n mtr = KST101()\\n mtr.en_update_msg(True)\\n\\n step_size = 1\\n old_step_size = -1\\n null_point = 0\\n curses.curs_set(False)\\n scr.nodelay(True)\\n while True:\\n pos = mtr.get_pos()\\n in_key = scr.getch()\\n if in_key == 49: step_size = 1 # 1\\n elif in_key == 50: step_size = 1e1 # 2\\n elif in_key == 51: step_size = 1e2 # 3\\n elif in_key == 52: step_size = 1e3 # 4\\n elif in_key == 53: step_size = 1e4 # 5\\n elif in_key == 54: step_size = 1e5 # 6\\n elif in_key == 55: step_size = 1e6 # 7\\n elif in_key == 56: step_size = 1e7 # 8\\n elif in_key == 57: step_size = 1e8 # 9\\n elif in_key == 114: # r\\n step_size *= -1\\n elif in_key == 32: # space\\n mtr.do_move()\\n elif in_key == 104: # h\\n mtr.home()\\n elif in_key == 110: # n\\n null_point = pos\\n elif in_key == 122: # z\\n null_point = 0\\n elif in_key == 48: # 0\\n mtr.set_move(null_point, False)\\n mtr.do_move(False)\\n mtr.set_move(step_size)\\n elif in_key == 113 or in_key == 27: # q / escape\\n break # Quit\\n \\n if step_size != old_step_size:\\n mtr.set_move(step_size)\\n old_step_size = step_size\\n\\n scr.clear()\\n scr.addstr(1, 2, \\\" Steps: %u\\\" % (pos - null_point))\\n scr.addstr(2, 2, \\\" mm: %0.4f\\\" % mtr.step2mm(pos - null_point))\\n scr.addstr(3, 2, \\\" Size: %u\\\" % step_size)\\n scr.addstr(4, 2, \\\" Null: %u\\\" % null_point)\\n home_state = mtr.get_home_state()\\n if home_state == 2:\\n scr.addstr(6, 2, \\\" *** Motor homing, please wait... ***\\\")\\n elif home_state == 1:\\n scr.addstr(6, 2, \\\" *** Motor needs homing (press h) ***\\\")\\n elif mtr.is_lower_limit():\\n scr.addstr(6, 2, \\\" *** Motor is at lower limit. ***\\\")\\n elif mtr.is_upper_limit():\\n scr.addstr(6, 2, \\\" *** Motor is at upper limit. ***\\\")\\n elif mtr.is_moving():\\n scr.addstr(6, 2, \\\" *** Motor is moving to position. ***\\\")\\n \\n # Lower status\\n scr.addstr(16, 2, \\\" Controls: 1-9 - set step size to 10^(n-1),\\\" \\\\\\n \\\" <spc> - move\\\")\\n scr.addstr(17, 2, \\\" r - reverse, h - home, 0 - go to null\\\")\\n scr.addstr(18, 2, \\\" n - set null, z - zero null\\\")\\n scr.addstr(21, 2, \\\" Status: %08X\\\" % mtr.get_raw_status())\\n scr.addstr(20, 2, \\\" Key: %u\\\" % int(in_key))\\n scr.refresh()\\n time.sleep(0.1)\",\n \"def tmux_move(direction):\\n pyautogui.hotkey('ctrl', 'B')\\n pyautogui.press(direction)\\n time.sleep(0.5)\",\n \"def nod():\\n while True:\\n MOVEMENTS.set_raw_angle(7, 52)\\n sleep(2)\\n MOVEMENTS.set_raw_angle(7, 0)\\n sleep(2)\",\n \"def my_code():\\n i = 0\\n j = 0\\n while True:\\n print(\\\" \\\"*50, \\\"\\\\r\\\", end=\\\"\\\")\\n if i in [0, 4, 11, 19]:\\n print(\\\"\\\\t\\\\t\\\\t{} {}\\\".format(TEXT[j], i - JJ[j]), \\\"\\\\a\\\", end=\\\"\\\")\\n else:\\n print(\\\"\\\\t\\\\t\\\\t{} {}\\\".format(TEXT[j], i - JJ[j]), end=\\\"\\\")\\n time.sleep(1)\\n i = i+1\\n if i > 4:\\n j = 1\\n if i > 11:\\n j = 2\\n if i >= 19:\\n i = 0\\n j = 0\",\n \"def step(self, screen):\\n max_y, _ = screen.getmaxyx()\\n allowed_y = range(0, max_y)\\n def is_on_screen(y):\\n return y in allowed_y\\n still_visible = False\\n y, x = -1, -1\\n for char in self.characters:\\n y, x = int(char.y), char.x\\n char.y += self.min_falling_speed\\n if not is_on_screen(y):\\n continue\\n still_visible = True\\n screen.addstr(y, x, char.symbol, char.color)\\n # Clear trail of characters after column\\n y -= 1\\n while is_on_screen(y):\\n screen.addstr(y, x, ' '*self.width)\\n y -= 1\\n return still_visible\",\n \"def checkMotion(self):\\n res = 0\\n while(self.ser.inWaiting() > 0):\\n res = self.ser.readline().strip()\\n\\n try:\\n if self.state == 1 and time.time() - self.last_move > self.config[\\\"keep_on_time\\\"]:\\n self.execOff()\\n\\n if res == \\\"1\\\":\\n self.last_move = time.time()\\n\\n if res == \\\"1\\\" and self.state == 0:\\n self.execOn()\\n except Exception as e:\\n self.logger.error(e)\",\n \"def run_terminal():\\n playing = True\\n while playing:\\n print(\\\"$\\\", end='')\\n command = input()\\n list_of_inputs = command.split(\\\" \\\")\\n if list_of_inputs[0] == \\\"exit\\\":\\n playing = False\\n break\\n handle_command(list_of_inputs)\",\n \"def run(self):\\n for _ in range(self.num_iteration):\\n self.move()\\n time.sleep(self.speed)\\n if not self.is_running:\\n break\",\n \"def _display_loop(self):\\n # Get & handle user input\\n self._handle_input(self.screen.getch())\\n\\n # Only update if there's something to do - Improves performance drastically\\n if self.updated:\\n # Reset screen\\n self.screen.clear()\\n self.updated = False\\n\\n # Commands header & highlight current command\\n self.screen.addstr('Every {:.1f}/{:.1f}s: | '.format(self.interval, self.cycle_interval), self.base_color)\\n for i, command in enumerate(self.commands_str):\\n self.screen.addstr(command, self.highlight_color if i == self.current_idx else self.base_color)\\n self.screen.addstr(' | ', self.base_color) # Pad between commands\\n\\n # Add current date & time to header, pad to end of the line based on current position\\n pad = self.max_col - self.screen.getyx()[-1] - self.time_pad\\n self.screen.addstr(' '*pad + self.time_str + '\\\\n', self.base_color)\\n\\n # Display the current command's output\\n self._display_command()\\n\\n self.screen.refresh() # Refresh must go before delay!\\n time.sleep(self.DELAY) # Small delay to avoid stuttering but allow for smooth scrolling\",\n \"def loop(self):\\n while True:\\n self._print_field()\\n try:\\n cmd = input(PROMPT)\\n self._invoke_cmd(cmd)\\n except EOFError: # Allows to exit by pressing ⌃D without error\\n break\",\n \"def start(self):\\n self.print_separator()\\n self.stdscr.box()\\n\\n box = curses.newwin(4, self.maxx-8, self.pad, self.pad)\\n box.addstr(1,1,\\\"hello\\\")\\n while self.running:\\n # Enter the main program loop\\n key = self.stdscr.getkey()\\n for fn in [self.stdscr.clear,\\n lambda: self.handle_key(key),\\n self.update_xy,\\n self.print_pattern,\\n self.print_separator,\\n self.stdscr.box,\\n self.generate_menu_items,\\n self.print_menu_items,\\n self.print_current_selection,\\n self.stdscr.refresh]:\\n fn()\",\n \"def run_prank():\\n d = display.Display()\\n num_screens = d.screen_count()\\n s = d.screen(random.randrange(0, num_screens) )\\n root = s.root\\n root.warp_pointer(random.randrange(0, s.width_in_pixels), random.randrange(0, s.height_in_pixels) )\\n d.sync()\\n return (True, 'It looks like you are using a mouse. Let me help you move it')\",\n \"def run(self):\\n while self.direction != \\\"\\\":\\n if self.direction == \\\"decrease\\\":\\n if self.position > 200:\\n self.position -= 15\\n elif self.direction == \\\"increase\\\":\\n if self.position < 800:\\n self.position += 15\\n if self.direction != \\\"neutral\\\":\\n self.move_joint(self.position, 900)\\n time.sleep(0.1)\",\n \"def listenMove(s):\\n debugPrint(\\\"FUNCTION AcornClient.listenMove()\\\")\\n print(grid)\\n loop = True\\n while loop:\\n move = input(\\\">>> \\\").lower()\\n if move in ['w']:\\n loop = False\\n sendMove(s, 'up')\\n elif move in ['s']:\\n loop = False\\n sendMove(s, 'down')\\n elif move in ['d']:\\n loop = False\\n sendMove(s, 'right')\\n elif move in ['a']:\\n loop = False\\n sendMove(s, 'left')\\n else:\\n print(\\\"Please choose either: 'up', 'down', 'left', or 'right'. Thank you.\\\") # In case the user is trying to break the system :(\\n debugPrint(\\\"User input an unknown direction: %s\\\" % move, 1)\",\n \"def run(self):\\n while self.is_connected():\\n self.__ticker.tick() # Tick (sleep)\\n\\n if self.process and self.process.is_alive():\\n self.update()\\n continue\\n\\n c = getkey() \\n if c:\\n if c == 'w':\\n print \\\"Moving forward\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"forward\\\")\\n elif c == 'a':\\n print \\\"Turning left\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"left\\\")\\n elif c == 'd':\\n print \\\"Turning right\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"right\\\")\\n elif c == 's':\\n print \\\"Moving backward\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"backward\\\")\\n elif c == 'q':\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"stop\\\")\\n elif c == 'r':\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"terminate\\\")\\n elif c == 't':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"make_scan\\\")\\n elif c == 'm':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"save_map\\\")\\n elif c == 'l':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"load_map\\\")\\n elif c == 'c':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"match_map\\\")\\n elif c == 'x':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"make_map\\\")\\n elif c == 'z':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"discard_map\\\")\\n elif c == 'p':\\n self.save_pose()\\n elif c == 'g':\\n self.add_property(\\\"name\\\", \\\"map_command\\\")\\n self.add_property(\\\"map_command\\\", \\\"toggle_autoscan\\\")\\n elif c == 'h':\\n print \\\"[w] = forward [a] = left [s] = backward [d] = right\\\"\\n print \\\"[q] = stop [t] = take scan [c] = matching mode [x] = mapping mode\\\"\\n print \\\"[m] = save map [l] = load map [p] = save current pose [g] = Toggle autoscanning\\\"\\n \\n ############################\\n # Send data\\n self.update()\",\n \"def display_loop(self):\\n from time import sleep\\n self.displaying = True\\n while self.displaying:\\n print self\\n sleep(.083)\\n print loc(self.y, self.x) + ' '*self.size\",\n \"def move_debug(self, environment):\\n\\n ch2 = sys.stdin.read(1)\\n\\n if ch2 == \\\"w\\\":\\n # the up arrow key was pressed\\n print(\\\"up key pressed\\\")\\n\\n elif ch2 == \\\"s\\\":\\n # the down arrow key was pressed\\n print(\\\"down key pressed\\\")\\n\\n elif ch2 == \\\"a\\\":\\n # the left arrow key was pressed\\n print(\\\"left key pressed\\\")\\n\\n elif ch2 == \\\"d\\\":\\n # the right arrow key was pressed\\n print(\\\"right key pressed\\\")\",\n \"def all():\\n lab = test_loading()\\n\\n for _ in range(1):\\n print('🦅🐀🐙')\\n\\n test_spawn(lab)\\n\\n pc = test_spawn_player(lab)\\n\\n while True:\\n pc.store_move(PlayerMove(random.choice(['walk left', 'walk up', 'walk down', 'walk right'])))\\n test_turn_ai_and_players(lab)\\n if input() == '0':\\n break\",\n \"def strut(self):\\n self.fwd(left=50, right=50)\\n for x in range(2):\\n self.servo(1000)\\n time.sleep(.1) \\n self.servo(1500) # Look Straight\\n time.sleep(1)\\n self.servo(2000)\\n time.sleep(.1)\\n self.servo(1500)\",\n \"def run(self):\\n while self.is_connected():\\n self.__ticker.tick() # Tick (sleep)\\n\\n if self.process and self.process.is_alive():\\n self.update()\\n continue\\n\\n c = getkey() \\n if c:\\n if c == 'w':\\n print \\\"Moving forward\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"mmove\\\")\\n elif c == 'a':\\n print \\\"Turning left\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"mleft\\\")\\n elif c == 'd':\\n print \\\"Turning right\\\"\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"mright\\\")\\n elif c == 'f':\\n self.add_property(\\\"name\\\", \\\"pioneer_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"finish\\\")\\n elif c == 'p':\\n self.add_property(\\\"name\\\", \\\"remote_command\\\")\\n self.add_property(\\\"pioneer_command\\\", \\\"record\\\")\\n elif c == 'h':\\n print \\\"[w] = forward [a] = left [d] = right [f] = finish\\\"\\n\\n \\n ############################\\n # Send data\\n self.update()\",\n \"def main():\\n move()\\n move()\\n pick_beeper()\\n move()\\n turn_left()\\n for i in range(2):\\n move()\\n put_beeper()\\n turn_around()\\n move_to_wall()\\n turn_right()\\n move_to_wall()\\n turn_around()\",\n \"def Loop(self):\\n self.coshell.SetModesCallback(self.SetModes)\\n while True:\\n try:\\n text = self.Prompt()\\n if text is None:\\n break\\n self.Run(text) # paradoxically ignored - coshell maintains $?\\n except EOFError:\\n # ctrl-d\\n if not self.coshell.ignore_eof:\\n break\\n except KeyboardInterrupt:\\n # ignore ctrl-c\\n pass\\n except interactive_coshell.CoshellExitError:\\n break\",\n \"def example(self):\\n while self.check_end() == False:\\n plt.pause(0.25)\\n end = self.update_board(random.choice(self.get_actions()), True)\",\n \"def main():\\r\\n\\r\\n movetwotimes()\\r\\n pick_beeper()\\r\\n move()\\r\\n turn_left()\\r\\n movetwotimes()\\r\\n put_beeper()\\r\\n turn_left()\\r\\n turn_left()\\r\\n movetwotimes()\\r\\n rotatethreetimes()\\r\\n movetwotimes()\\r\\n move()\\r\\n turn_left()\\r\\n turn_left()\",\n \"def main():\\n print(\\\"Mouse mover\\\")\\n print(\\\"Press Ctrl + c to terminate the script.\\\")\\n try:\\n while True:\\n move_the_mouse()\\n sleep(2)\\n\\n except KeyboardInterrupt:\\n print(\\\"Finished.\\\")\",\n \"def run():\\r\\n \\r\\n match = a4_acc.Game() # Instantiate a Game object \\r\\n setup(match)\\r\\n\\r\\n if constants.SHOW_GRAPHICS:\\r\\n axes= startGraphics(match.board) #step 0\\r\\n \\r\\n \\r\\n for k in range(constants.STEPS):\\r\\n update(match)\\r\\n updateGraphics(board, k, caxes)\\r\\n \\r\\n ########\\r\\n # TO DO: \\r\\n # Simulate game given the intial state for constants.STEPS iterations\\r\\n \\r\\n # Example code to call the updateGraphics function; the second argument\\r\\n # needs to be replaced:\\r\\n # if constants.SHOW_GRAPHICS:\\r\\n # updateGraphics(match.board, None, axes) \\r\\n \\r\\n # Do not change or add code below here for function run\\r\\n endNow= raw_input('Press ENTER to continue.')\",\n \"def loop():\\n global loop_idx\\n sys.stdout.write('loop index %d/%d\\\\r\\\\n' % (loop_idx, _LOOPS))\\n time.sleep(0.5)\\n loop_idx += 1\\n return loop_idx > _LOOPS\",\n \"def timed_move(self, direction, duration):\\n print(\\\"Timed move \\\", end='')\\n if direction == MOV_FORWARD:\\n print(\\\"forward\\\")\\n elif direction == MOV_BACK:\\n print(\\\"back\\\")\\n else:\\n print(\\\"?\\\")\\n print(\\\"Duration:\\\", duration)\\n\\n self.moving_delay(duration)\\n self.move_stop()\",\n \"def move(self, direction, step):\\n for i in range(1, step + 1):\\n y, x = self.robot_position\\n if direction == \\\"N\\\" and y > 0:\\n if self.carte[y - 1][x] in [\\\" \\\", \\\".\\\", \\\"U\\\"]:\\n self.robot_position = (y - 1, x)\\n elif direction == \\\"S\\\" and y <= self.height:\\n if self.carte[y + 1][x] in [\\\" \\\", \\\".\\\", \\\"U\\\"]:\\n self.robot_position = (y + 1, x)\\n elif direction == \\\"E\\\" and x <= self.width+1:\\n if self.carte[y][x + 1] in [\\\" \\\", \\\".\\\", \\\"U\\\"]:\\n self.robot_position = (y, x + 1)\\n elif direction == \\\"O\\\" and x > 0:\\n if self.carte[y][x - 1] in [\\\" \\\", \\\".\\\", \\\"U\\\"]:\\n self.robot_position = (y, x - 1)\\n\\n if self.robot_position == self.out_position:\\n print(\\\"Bravo vous avez fini\\\")\\n return True\\n\\n return False\",\n \"def movement(self):\",\n \"def mainloops(stdscr):\\n def signal_handler(sig, frame):\\n \\\"\\\"\\\"\\n What to do in case of KeyboardInterrupt\\n\\n Writes times to session file\\n (saving file interaction to the end saves time during frames.)\\n \\\"\\\"\\\"\\n raise ExitException()\\n\\n signal.signal(signal.SIGINT, signal_handler)\\n\\n try:\\n curses.curs_set(0) # hide cursor (I have my own)\\n except Exception:\\n pass\\n stdscr.nodelay(True) # makes stdscr.getch() non-blocking\\n\\n canvas = Canvas(curses.LINES - 1, curses.COLS - 1)\\n cursor = Cursor(canvas)\\n\\n display_text(stdscr, TITLE_ART)\\n\\n # sessions are groups of solves, stored in files in ~/.cl-timer\\n # if this is a new session, create a new file, if not, use an existing one.\\n\\n session_name_input = InputLine(canvas, 'session name: ')\\n session = MutableString(ask_for_input(stdscr, canvas, session_name_input, cursor))\\n \\n times = []\\n ao5s = []\\n ao12s = []\\n scrambles = []\\n session_file = \\\"\\\"\\n\\n session_file = MutableString(f'{HOME}/.cl-timer/{session.string}')\\n if not isfile(session_file.string):\\n with open(session_file.string, 'w+') as f:\\n pass\\n \\n with open(session_file.string, 'r') as f:\\n time_lines = [line.split('\\\\t') for line in f.read().split('\\\\n')]\\n\\n if [''] in time_lines:\\n time_lines.remove([''])\\n\\n for line in time_lines:\\n times.append(line[0])\\n ao5s.append(line[1])\\n ao12s.append(line[2])\\n scrambles.append(line[3])\\n\\n settings_file = MutableString(f'{session_file.string}-settings.json')\\n if not isfile(settings_file.string):\\n with open(settings_file.string, 'w+') as f:\\n json.dump(settings, f)\\n \\n with open(settings_file.string, 'r') as f:\\n for key, value in json.load(f).items():\\n settings[key] = value\\n\\n display_text(stdscr, DISCLAIMER)\\n\\n def add_time(t):\\n \\\"\\\"\\\"\\n Add new solve with time of `t`\\n \\\"\\\"\\\"\\n\\n times.append(t)\\n\\n # update number display to show real time\\n number_display.time = t\\n number_display.update()\\n\\n # generate new scramble and update scramble_image\\n new_scramble = generate_scramble(int(settings['puzzle']),\\n int(settings['scramble-length']))\\n scrambles.append(new_scramble)\\n scramble_image.clear()\\n scramble_image.chars = char(new_scramble)\\n\\n ao5, ao12 = update_stats()\\n\\n with open(session_file.string, 'a') as f:\\n if len(times) == 1:\\n f.write(f'{add_zero(t)}\\\\t{ao5}\\\\t{ao12}\\\\t{new_scramble}')\\n else:\\n f.write(f'\\\\n{add_zero(t)}\\\\t{ao5}\\\\t{ao12}\\\\t{new_scramble}')\\n \\n def calculate_average(solve, length):\\n \\\"\\\"\\\"\\n Returns average of `length` during `solve`\\n\\n Looks through times list and finds last `length` solves before `solve`\\n Excludes best and worst times, and returns average of the rest.\\n \\\"\\\"\\\"\\n if len(times[:solve]) < length:\\n # `length` solves haven't been done yet.\\n return ''\\n else:\\n latest_average = times[solve - length:] # list of last `length` solves\\n latest_average, _ = convert_to_float(latest_average, \\\"average\\\")\\n if len(latest_average) < (length - 1):\\n return 'DNF'\\n if len(latest_average) == length:\\n latest_average.remove(max(latest_average))\\n latest_average.remove(min(latest_average))\\n\\n # calculate average and add zero if it doesn't go to 100ths place.\\n \\n return add_zero(round(sum(latest_average) / len(latest_average), 2))\\n\\n def get_session_mean():\\n \\\"\\\"\\\"\\n Returns mean of all solves in session\\n \\\"\\\"\\\"\\n try:\\n float_times, len_times = convert_to_float(times, 'average')\\n return add_zero(round(sum(float_times) / len_times, 2))\\n except ZeroDivisionError:\\n return \\\"\\\"\\n\\n def get_best_average(length):\\n \\\"\\\"\\\"\\n Returns best average of `length` in session\\n \\\"\\\"\\\"\\n try:\\n if length == 5:\\n best = add_zero(min([i for i in ao5s if i != '']))\\n elif length == 12:\\n best = add_zero(min([i for i in ao12s if i != '']))\\n except ValueError:\\n return \\\"\\\"\\n return best\\n\\n def get_best_time():\\n try:\\n converted_times, _ = convert_to_float(times, 'single')\\n float_times = [float(t[:-1]) if isinstance(t, str) else t for t in converted_times]\\n best = converted_times[float_times.index(min(float_times))]\\n if isinstance(best, float):\\n return add_zero(best)\\n except ValueError as e:\\n return \\\"\\\"\\n return best\\n\\n def get_worst_time():\\n try:\\n converted_times, _ = convert_to_float(times, 'single')\\n float_times = [float(t[:-1]) if isinstance(t, str) else t for t in converted_times]\\n worst = converted_times[float_times.index(max(float_times))]\\n if isinstance(worst, float):\\n return add_zero(worst)\\n except ValueError as e:\\n return \\\"\\\"\\n return worst\\n\\n def update_stats():\\n ao5 = calculate_average(len(times), 5)\\n ao5s.append(ao5)\\n ao5_image.chars = char(f'AO5: {ao5}')\\n ao12 = calculate_average(len(times), 12)\\n ao12s.append(ao12)\\n ao12_image.chars = char(f'AO12: {ao12}')\\n best_ao5 = get_best_average(5)\\n best_ao5_image.chars = char(f'Best AO5: {best_ao5}')\\n best_ao12 = get_best_average(12)\\n best_ao12_image.chars = char(f'Best AO12: {best_ao12}')\\n best_time = get_best_time()\\n best_time_image.chars = char(f'Best time: {best_time}')\\n worst_time = get_worst_time()\\n worst_time_image.chars = char(f'Worst time: {worst_time}')\\n\\n len_successes = 0\\n for t in times:\\n if not ((isinstance(t, str)) and (t[:3] == 'DNF')):\\n len_successes += 1\\n\\n number_of_times_image.chars = char(f'Number of Times: {len_successes}/{len(times)}')\\n session_mean = get_session_mean()\\n session_mean_image.chars = char(f'Session Mean: {session_mean}')\\n\\n return ao5, ao12\\n \\n session_name_image = Image(canvas, 0, 0, char(session.string))\\n scramble_image = Scramble(canvas, 0, 2, char(\\n generate_scramble(int(settings['puzzle']),\\n int(settings['scramble-length']))))\\n scramble_image.render()\\n\\n number_display = NumberDisplay(canvas, 15, 7)\\n timer_background = Image(canvas, 0, 5, char(TIMER_BACKGROUND))\\n\\n ao5_image = CoverUpImage(canvas, 51, 6, char(f'AO5: {calculate_average(len(times), 5)}'))\\n ao12_image = CoverUpImage(canvas, 51, 7, char(f'AO12: {calculate_average(len(times), 12)}'))\\n best_ao5_image = CoverUpImage(canvas, 51, 8, char(f'Best AO5: {get_best_average(5)}'))\\n best_ao12_image = CoverUpImage(canvas, 51, 9, char(f'Best AO12: {get_best_average(12)}'))\\n best_time_image = CoverUpImage(canvas, 51, 10, char(f'Best time: {get_best_time()}'))\\n worst_time_image = CoverUpImage(canvas, 51, 11, char(f'Worst time: {get_worst_time()}'))\\n\\n len_successes = 0\\n for t in times:\\n if not ((isinstance(t, str)) and (t[:3] == 'DNF')):\\n len_successes += 1\\n number_of_times_image = CoverUpImage(canvas, 51, 12, char(f'Number of Times: {len_successes}/{len(times)}'))\\n \\n session_mean_image = CoverUpImage(canvas, 51, 13, char(f'Session Mean: {get_session_mean()}'))\\n\\n if isfile(f'{HOME}/.cl-timer_rc'):\\n with open(f'{HOME}/.cl-timer_rc', 'r') as f:\\n rc_commands = f.read().strip().split('\\\\n')\\n if '' in rc_commands:\\n rc_commands.remove('')\\n for command in rc_commands:\\n try:\\n command_line(canvas, stdscr, settings, scramble_image, settings_file, session_file, times, ao5s, ao12s,\\n scrambles, session, session_name_image, update_stats, add_time, calculate_average, aliases,\\n True, command)\\n except CommandSyntaxError:\\n pass\\n else:\\n with open(f'{HOME}/.cl-timer_rc', 'w+') as f:\\n pass\\n \\n ao5_image.render()\\n ao12_image.render()\\n best_ao5_image.render()\\n best_ao12_image.render()\\n best_time_image.render()\\n worst_time_image.render()\\n number_of_times_image.render()\\n session_mean_image.render()\\n\\n timer_running = False\\n delay = 0 # how far behind the program is\\n spacebar_pressed = False\\n last_25_keys = [-1 for _ in range(25)]\\n\\n solve_start_time = 0\\n frame = 0\\n while True:\\n\\n # to make sure each frame is exactly 0.01 secs\\n start_time = time.time()\\n\\n key = stdscr.getch()\\n\\n if key == 58: # :\\n try:\\n command_line(canvas, stdscr, settings, scramble_image,\\n settings_file, session_file, times, ao5s,\\n ao12s, scrambles, session, session_name_image,\\n update_stats, add_time, calculate_average, aliases)\\n except CommandSyntaxError:\\n pass\\n continue\\n\\n if not timer_running:\\n if key == 32:\\n solve_start_time = time.time()\\n last_25_keys.append(key)\\n last_25_keys.pop(0)\\n\\n if not timer_running:\\n\\n if spacebar_pressed:\\n if 32 in last_25_keys:\\n time.sleep(0.01)\\n continue\\n else:\\n spacebar_pressed = False\\n\\n timer_running = True\\n number_display.reset()\\n\\n else:\\n if key == 32: # spacebar\\n spacebar_pressed = True\\n\\n else:\\n if key == 32:\\n frame = 0\\n timer_running = False\\n\\n t = round(time.time() - solve_start_time, 2)\\n\\n add_time(t)\\n \\n\\n session_name_image.render()\\n \\n timer_background.render()\\n number_display.render()\\n\\n stdscr.clear()\\n stdscr.addstr(canvas.display)\\n stdscr.refresh()\\n\\n if timer_running:\\n number_display.time = time.time() - solve_start_time\\n number_display.update()\\n\\n # take away from sleep time the amount that will get us back on track\\n duration = time.time() - start_time\\n if (duration + delay) > 0.01:\\n # can't make it back to on-time right now\\n # by not sleeping, we have saved (0.01 - duration) seconds\\n delay -= 0.01 - duration\\n else:\\n time.sleep(0.01 - (duration + delay))\\n \\n frame += 1\",\n \"def control_loop():\\n global rate, regions, speed\\n rospy.init_node('ebot_controller')\\n rate = rospy.Rate(10)\\n rospy.Subscriber('/ebot/laser/scan', LaserScan, laser_callback)\\n rospy.Subscriber('/odom', Odometry, odom_callback)\\n speed = Twist()\\n speed.linear.x = 0\\n speed.angular.z = 0\\n pub.publish(speed)\\n while not rospy.is_shutdown():\\n if x <= 6.28:\\n user_x, user_y = waypoints(15)\\n go_to_x_y(user_x, user_y, 1)\\n go_to_x_y(user_x, user_y, 0.25)\\n else:\\n go_to_x_y(12.5, 0, 3)\\n go_to_x_y(12.5, 0, 1)\\n go_to_x_y(12.5, 0, 0.2)\\n exit()\\n speed.linear.x = 0\\n speed.angular.z = 0\\n pub.publish(speed)\\n rate.sleep()\",\n \"def run(self):\\n for i in range(self.nreps):\\n print self.ch,\",\n \"def run(self):\\n while True:\\n display(self.world.draw())\\n self.read_and_process_input()\",\n \"def waiting_animation():\\n animation = [\\\"[■□□□□□□□□□]\\\",\\\"[■■□□□□□□□□]\\\", \\\"[■■■□□□□□□□]\\\", \\\"[■■■■□□□□□□]\\\", \\n \\\"[■■■■■□□□□□]\\\", \\\"[■■■■■■□□□□]\\\", \\\"[■■■■■■■□□□]\\\", \\\"[■■■■■■■■□□]\\\", \\n \\\"[■■■■■■■■■□]\\\", \\\"[■■■■■■■■■■]\\\", \\\"[□■■■■■■■■■]\\\", \\\"[□□■■■■■■■■]\\\",\\n \\\"[□□□■■■■■■■]\\\", \\\"[□□□□■■■■■■]\\\", \\\"[□□□□□■■■■■]\\\", \\\"[□□□□□□■■■■]\\\",\\n \\\"[□□□□□□□■■■]\\\", \\\"[□□□□□□□□■■]\\\", \\\"[□□□□□□□□□■]\\\", \\\"[□□□□□□□□□□]\\\"\\n ]\\n for i in range(len(animation)):\\n time.sleep(0.2)\\n sys.stdout.write(\\\"\\\\r\\\" + animation[i % len(animation)])\\n sys.stdout.flush()\",\n \"def run_mouse_notifs(self):\\n time.sleep(10)\\n try:\\n if not pynput_status:\\n self.get_by_mice()\\n else:\\n while 1:\\n # Starting mouse event listner\\n with mouse.Listener(on_move=self.on_move) as listener:\\n listener.join()\\n except Exception as e:\\n self.logger.log(\\n \\\"Something went wrong: \\\" + str(e) + \\\" End of program\\\",\\n logtype=\\\"error\\\"\\n )\\n except KeyboardInterrupt as e:\\n self.logger.log(\\n \\\"You pressed Ctrl+C!, Bye\\\")\\n exit()\",\n \"def step(self, move):\",\n \"def run(self, verbose=False):\\n step_num = 0\\n while self.won == 0:\\n if len(self.board.valid_moves) == 0:\\n return\\n status = self.step()\\n if verbose and step_num % 2 == 1:\\n print(self.board.table())\\n if status != board.Board.INVALID_MOVE:\\n step_num += 1\\n print(f'Player {board.remap_char(self.won)} won!')\",\n \"def return_to_center(): #ignore this for now, use move_to_position_(0,0)\\n current_pos = '\\\\xAA\\\\xBB\\\\xCC\\\\xDD'\\n #run command until back to center (0,0)\\n while True: #change the byte locations\\n current_pos = to_center()\\n print(current_pos)\\n time.sleep(0.2) #check timing\\n if((current_pos[1] == 0) and (current_pos[1] == 0)):\\n break\\n print('At center')\",\n \"def run_until_stop(self):\\n while self.commands[self.pointer] != END:\\n # Get the cmd\\n cmd = self.commands[self.pointer]\\n opcode = cmd % 100\\n modes = cmd // 100\\n \\n vals, locs, self.pointer = get_vals_and_locs(opcode, modes, self.pointer, self.commands)\\n \\n if opcode == ADD:\\n self.commands[locs[2]] = vals[0] + vals[1]\\n elif opcode == MUL:\\n self.commands[locs[2]] = vals[0] * vals[1]\\n elif opcode == INP:\\n if self.inputs:\\n self.commands[locs[0]] = self.inputs.pop(0)\\n else:\\n # Put the pointer back, so we run this opcode again\\n self.pointer -= 2\\n return False\\n elif opcode == OUT:\\n self.outputs.append(vals[0])\\n elif opcode == JIT:\\n if vals[0] != 0:\\n self.pointer = vals[1]\\n elif opcode == JIF:\\n if vals[0] == 0:\\n self.pointer = vals[1]\\n elif opcode == LT:\\n self.commands[locs[2]] = 1 if vals[0] < vals[1] else 0\\n elif opcode == EQ:\\n self.commands[locs[2]] = 1 if vals[0] == vals[1] else 0\\n else:\\n print(\\\"FAIL????\\\")\\n\\n return True\",\n \"def Run(self):\\n while not rospy.is_shutdown():\\n # get input of destination\\n if (self.target_x is None) or (self.target_y is None):\\n self.target_x, self.target_y = self.GetTarget()\\n # if the destination is not in x >= 0 and y <= 11, ask user to re-input\\n # till the right values found\\n if (self.target_x < 0 or self.target_x > 10) or (self.target_y < -10 or self.target_y > 10):\\n print(\\\"-------------------------------------------------------\\\") \\n print(\\\"WARNING: Invalid Input, please reinput the destination.\\\")\\n print(\\\"-------------------------------------------------------\\\") \\n self.target_x = None\\n self.target_y = None\\n else:\\n print(\\\"Current Destination: [{}, {}]\\\".format(self.target_x, self.target_y))\\n else:\\n ################################################################################################\\n # get all necessary parameters\\n goal = np.array([self.target_x, self.target_y])\\n robot_pos = self.GetRobotInfo()\\n ranges, angles = self.GetObstaclePos()\\n\\n if (ranges is not None) and (angles is not None):\\n ctrl = TangentBug(self.Lidar.range_max)\\n # obsts = ctrl.Continuity(ranges, angles, robot_pos[:2])\\n # print(len(obsts))\\n linear, omega = ctrl.MotionToGo(ranges, angles, goal, robot_pos)\\n print(\\\"=======================================\\\")\\n # print([linear, omega])\\n else:\\n linear = 0.\\n omega = 0.\\n print(\\\"---------------------------------------\\\")\\n print(\\\"NO OBSTACLE DETECTED.\\\")\\n print(\\\"---------------------------------------\\\")\\n\\n ################################################################################################\\n self.vel.linear.x = linear \\n self.vel.angular.z = omega\\n self.pub.publish(self.vel)\\n\\n # sleep till the next commend sent\\n self.rate.sleep()\",\n \"def getMove(player,first_move=False):\\n while True: \\n move = raw_input(\\\"MAKE YOUR MOVE: \\\").upper()\\n\\n # handle special commands\\n if move == \\\"QUIT\\\" or move == \\\"Q\\\":\\n wannaQuit()\\n continue\\n elif move == \\\"QUIT!\\\" or move == \\\"Q!\\\":\\n if SAY_PROC:\\n SAY_PROC.terminate()\\n sys.exit()\\n continue\\n elif move == \\\"HELP\\\" or move == \\\"H\\\":\\n help()\\n continue\\n elif move == \\\"HELP!\\\" or move == \\\"H!\\\":\\n say(helpString())\\n continue\\n elif move == \\\"SHUTUP!\\\" or move == \\\"S!\\\":\\n shutUp(fuck=True)\\n continue\\n elif move == \\\"SHUTUP\\\" or move == \\\"S\\\":\\n shutUp()\\n continue\\n elif move == \\\"BOARD\\\" or move == \\\"B\\\":\\n printBoard()\\n continue\\n elif move == \\\"CLEAR\\\" or move == \\\"C\\\": \\n clearTerminal()\\n printBoard()\\n continue\\n elif move == \\\"CLEAR!\\\" or move == \\\"C!\\\": # TODO board -> clear, you end up with a half drawn new board. clear again fixes this\\n clearTerminalAndBuffer()\\n printBoard()\\n continue\\n elif move == \\\"PASS\\\" or move == \\\"P\\\": \\n if wannaPass():\\n break\\n else:\\n continue\\n elif move == \\\"PASS!\\\" or move == \\\"P!\\\": \\n break\\n \\n # mostly used to catch blank lines or me typing ASFADS like an asshole\\n if len(move) < 7:\\n print \\\"That's too short to be a command.\\\"\\n continue\\n\\n parts=move.split(\\\":\\\")\\n if len(parts) != 3:\\n print \\\"Can't find all the parts of the move command. Maybe you're missing/have too many \\\\\\\":\\\\\\\"?\\\"\\n continue\\n\\n for item in parts:\\n if len(item) == 0:\\n print \\\"Found a blank command. Maybe you left in an extra \\\\\\\":\\\\\\\"?\\\"\\n continue\\n\\n coords = parts[0].replace(\\\" \\\",\\\"\\\") # incase of space inbetween file and rank\\n direction = parts[1].strip()\\n word = parts[2].strip()\\n\\n if not coords[0].isalpha():\\n print \\\"I don't know where to put your word (Bad file coord).\\\"\\n continue\\n\\n if not coords[1:].isdigit():\\n print \\\"I don't know where to put your word (Bad rank coord).\\\"\\n continue\\n\\n x = gridCharToInt(coords[0])\\n y = int(coords[1:]) - 1\\n if 14 < x < 0 or 14 < y < 0:\\n print \\\"Those aren't coords on the board. Valid Files are from A-O, valid Ranks are 1-15.\\\"\\n continue\\n\\n if first_move:\\n if x != 7 or y != 7:\\n print \\\"The first move must start from the center (H8).\\\"\\n continue\\n\\n #compact that command\\n if direction == \\\"ACROSS\\\":\\n direction = \\\"A\\\"\\n elif direction == \\\"DOWN\\\":\\n direction = \\\"D\\\"\\n if direction != \\\"A\\\" and direction !=\\\"D\\\":\\n print \\\"I don't know where to put your word (Across or Down?).\\\"\\n continue\\n \\n score,placed_tiles = checkWords(x,y,direction,word,first_move)\\n if not score: #error reporting is handling in check words\\n continue\\n else:\\n for tile in placed_tiles:\\n if not tile in player.rack:\\n print \\\"You don't have the tiles to play that!\\\"\\n continue\\n player.rack.remove(tile)\\n print player.name+\\\" scored \\\"+str(score)+\\\" on that last play!\\\"\\n player.score+=score\\n for tile in placed_tiles:\\n player.rack.remove(tile)\\n break #YAY\",\n \"def run(self):\\n terminal.open()\\n self.terminal_init()\\n terminal.refresh()\\n\\n try:\\n self.loop_until_terminal_exits()\\n except KeyboardInterrupt:\\n pass\\n finally:\\n terminal.close()\",\n \"def main():\\r\\n robot = ROBOT()\\r\\n print(\\\"COMMANDS AVAILABLE:\\\", commands_avail)\\r\\n print(\\\"'PLACE' must be used in the form: PLACE x,y,direction\\\")\\r\\n print(\\\"VALID DIRECTIONS:\\\", direction_tuple)\\r\\n print(\\\"MOVE: moves the robot one unit in the direction its facing, unless it would fall of the tabletop\\\")\\r\\n print(\\\"LEFT and RIGHT: rotates the robot 90 degrees anti-clockwise or clockwise respectively\\\")\\r\\n print(\\\"REPORT: prints the position on the tabletop and which direction the robot is facing\\\")\\r\\n print(\\\"NOTE: position 0,0 is south-west corner and 4,4 is north-east corner. Size can be changed in source code\\\")\\r\\n print(\\\"NOTE: if REPORT in input, all previous commands processed and reported. Option to enter more input given.\\\")\\r\\n while True:\\r\\n commands = robot.input_discard()\\r\\n try:\\r\\n for i in commands:\\r\\n if commands_avail[0] in i:\\r\\n xyd = i.split(' ')\\r\\n xy = xyd[1].split(',')\\r\\n x = int(xy[0])\\r\\n y = int(xy[1])\\r\\n d = xy[2]\\r\\n robot.place(x, y, d)\\r\\n elif i == commands_avail[1]:\\r\\n robot.move()\\r\\n elif i == commands_avail[2]:\\r\\n robot.left()\\r\\n elif i == commands_avail[3]:\\r\\n robot.right()\\r\\n elif i == commands_avail[4]:\\r\\n robot.report()\\r\\n except TypeError:\\r\\n print(\\\"NO VALID PLACE OR EXISTING ROBOT POSITION\\\")\\r\\n print(\\\"Would you like to enter more input: 'Y' for yes or 'N' to quit\\\")\\r\\n cont = input()\\r\\n while cont != 'N' and cont != 'Y':\\r\\n print(\\\"INVALID COMMAND!\\\\nWould you like to enter more input: 'Y' for yes or 'N' to quit\\\")\\r\\n cont = input()\\r\\n if cont == 'N':\\r\\n break\\r\\n print(\\\"Exiting Program\\\")\",\n \"def main():\\n\\tcolorama.init()\\n\\n\\n\\n\\tgrid = get_start_grid(*map(int,sys.argv[1:]))\\n\\tprint_grid(grid)\\n\\n\\twhile True:\\n\\t\\tgrid_copy = copy.deepcopy(grid)\\n\\t\\tget_input = getch(\\\"Enter direction (w/a/s/d/n/r/q): \\\")\\n\\t\\tif get_input in functions:\\t\\n\\t\\t\\tfunctions[get_input](grid)\\n\\t\\telif get_input == \\\"n\\\":\\n\\t\\t\\tif get_next_action(grid) == '':\\n\\t\\t\\t\\tprint(\\\"Checkmate!\\\")\\n\\t\\t\\t\\tbreak\\n\\t\\t\\tfunctions[get_next_action(grid)](grid)\\n\\t\\telif get_input == \\\"r\\\":\\n\\t\\t\\tbreak\\n\\t\\telif get_input == \\\"q\\\":\\n\\t\\t\\tbreak\\n\\t\\telse:\\n\\t\\t\\tprint(\\\"\\\\nInvalid choice.\\\")\\n\\t\\t\\tcontinue\\n\\t\\tif grid != grid_copy:\\n\\t\\t\\tif not prepare_next_turn(grid):\\n\\t\\t\\t\\tprint_grid(grid)\\n\\t\\t\\t\\tprint(\\\"Well played!\\\")\\n\\t\\t\\t\\tbreak\\n\\t\\tprint_grid(grid)\\n\\t\\n\\tif get_input == \\\"r\\\":\\n\\t\\twhile True:\\n\\t\\t\\tgrid_copy = copy.deepcopy(grid)\\n\\n\\t\\t\\tnext_action = get_next_action(grid)\\n\\t\\t\\tif next_action == '':\\n\\t\\t\\t\\tprint(\\\"Checkmate!\\\")\\n\\t\\t\\t\\tbreak\\n\\t\\t\\t\\n\\t\\t\\tfunctions[next_action](grid)\\n\\t\\t\\tif grid != grid_copy:\\n\\t\\t\\t\\tif not prepare_next_turn(grid):\\n\\t\\t\\t\\t\\tprint_grid(grid)\\n\\t\\t\\t\\t\\tprint(\\\"Well played!\\\")\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\tprint_grid(grid)\\n\\n\\tprint(\\\"Thanks for playing.\\\")\",\n \"def idle_loop(self):\\n sleep(0.1)\\n self.scroll()\",\n \"def run(self):\\n global key\\n getch = _GetchUnix()\\n key = getch()\\n while key != \\\"e\\\":\\n key = getch()\\n #time.sleep(0.1)\",\n \"def chacha(self):\\n self.right()\\n time.sleep(2)\\n self.stop()\\n self.back()\\n time.sleep(1)\\n self.servo(1000)\\n time.sleep(1)\\n self.stop()\\n self.fwd()\\n time.sleep(1)\\n self.stop()\\n self.servo(2000)\\n time.sleep(1)\\n self.stop()\\n self.left()\\n time.sleep(2)\\n self.stop()\",\n \"def gameloop(self):\\r\\n\\r\\n # What you see above (\\\"\\\"\\\" some text \\\"\\\"\\\") is called a docstring.\\r\\n # It explains the purpose of the method/function.\\r\\n # There should generally be one for every function.\\r\\n\\r\\n\\r\\n # Below is the main loop\\r\\n while True: \\r\\n # One cycle in the loop is equivalent to one frame.\\r\\n\\r\\n self.event()\\r\\n\\r\\n self.draw_objects()\\r\\n self.move_objects()\\r\\n\\r\\n self.update_display()\",\n \"def run(self):\\n\\t\\twhile 1:\\n\\t\\t\\tif self._driveSystem.port_open == True and self._parent.aborted==False:\\n\\n\\t\\t\\t\\tself._driveSystem.check_encoder_pos()\\n\\t\\t\\t\\tpos=self._driveSystem.positions\\n\\t\\t\\t\\tif self._parent.printRequest==True: #Print positions when print Button was pressed\\n\\t\\t\\t\\t\\toutput=\\\"Axis 1: \\\"+str(pos[0])+\\\"\\\\nAxis 2: \\\"+str(pos[1])+\\\"\\\\nAxis 3: \\\"+str(pos[2])+\\\"\\\\nAxis 4: \\\"+str(pos[3])\\n\\t\\t\\t\\t\\tprint(output)\\n\\t\\t\\t\\t\\tself._parent.printRequest=False\\n\\t\\t\\t\\tevent = PosUpdateEvent(myEVT_POSUPDATE, -1, pos)\\n\\t\\t\\t\\twx.PostEvent(self._parent.matplotpanel, event)\\n\\n\\t\\t\\t\\tt=0\\n\\t\\t\\t\\twhile t<UPDATE_TIME:\\n\\t\\t\\t\\t\\tself.checkQ()\\n\\t\\t\\t\\t\\ttime.sleep(REAC_TIME)\\n\\t\\t\\t\\t\\tt=t+REAC_TIME\\n\\t\\t\\telse:\\n\\t\\t\\t\\ttime.sleep(1)\",\n \"def pause_handler(term):\\n inp = None\\n while inp not in (\\\"p\\\", \\\"P\\\", \\\"q\\\", \\\"Q\\\"):\\n print(term.home + term.clear + term.move_y(term.height // 2))\\n print(term.black_on_white(term.center(\\\"press P to continue.\\\")))\\n\\n inp = term.inkey(timeout=10)\",\n \"def start():\\n display_board()\\n print(\\\"\\\\n\\\")\\n y_n_prompt()\",\n \"def main():\\n\\n r = np.arange(-90, 90, 2)\\n tilt = 22.5\\n\\n with ptcmd.PTCMD(baud=57600) as controller:\\n\\n controller.home()\\n\\n for pan_angle in r:\\n\\n current_position = controller.get_position()\\n pan_steps, tilt_steps, pan_rate, tilt_rate = system.move_to_angle(pan_angle, tilt, current_position[0], current_position[1], base_rate = 1000)\\n controller.sync(pan_rate, pan_steps, tilt_rate, tilt_steps)\\n controller.wait('all')\\n\\n time.sleep(2)\\n\\n distances = []\\n for i in range(0,12):\\n time.sleep(1)\\n distances.append(controller.get_analog_sensor(1))\\n\\n distances.sort()\\n distance = sum(distances[1:-1]) / len(distances[1:-1])\\n\\n x = math.sin(pan_angle*math.pi/180) * distance\\n y = math.cos(pan_angle*math.pi/180) * distance\\n\\n print(distances, distance, pan_angle, x, y)\\n\\n plt.plot(x, y, 'b+')\\n\\n plt.show()\",\n \"def do_simulation_loop(self) -> tuple[bool, bool]:\\n running, reset = True, False\\n for event in pygame.event.get():\\n if check_for_quit(event):\\n running = False\\n elif check_for_reset(event):\\n running = False\\n reset = True\\n self.simulation.do_step()\\n self.update_visualization()\\n self.simple_pygame.loop()\\n return running, reset\",\n \"def move():\\n print(\\\" ------ Execution -----\\\\n\\\")\\n pyautogui.moveRel(0, 10)\\n pyautogui.moveRel(0, -10)\\n pyautogui.click()\",\n \"def example_move(self):\\n self.right() # start rotating right\\n time.sleep(1) # turn for a second\\n self.stop() # stop\\n self.servo(1000) # look right\\n time.sleep(.25) # give your head time to move\\n self.servo(2000) # look left\",\n \"def example_move(self):\\n self.right() # start rotating right\\n time.sleep(1) # turn for a second\\n self.stop() # stop\\n self.servo(1000) # look right\\n time.sleep(.25) # give your head time to move\\n self.servo(2000) # look left\",\n \"def run_cli_game():\\n # Set up game\\n view = ConsoleView()\\n game = GameEngine(view)\\n\\n # Game loop\\n while not game.game_over:\\n view.turn_started()\\n\\n # Get move to make from user and execute it\\n move = input()\\n print()\\n \\n execute_move(move, game, view)\",\n \"def run(self):\\n \\n t = 0\\n while t < 10:\\n self.reset()\\n self.start_simulation()\\n while not self.done:\\n raw_input(\\\"Press Enter to continue...\\\")\\n action = self.action_space.sample()\\n print(action)\\n state, reward, self.done, _ = self.step(action)\\n print('Current state:\\\\n angles: {}'.format(state))\\n print('Reward: {}'.format(reward))\\n\\n self.stop_simulation()\\n t += 1\",\n \"def robot_start():\\n \\n global history\\n\\n global position_x, position_y, current_direction_index\\n \\n robot_name = get_robot_name()\\n output(robot_name, \\\"Hello kiddo!\\\")\\n\\n position_x = 0\\n position_y = 0\\n current_direction_index = 0\\n\\n command = get_command(robot_name)\\n keep_history(command) \\n while handle_command(robot_name, command):\\n command = get_command(robot_name)\\n keep_history(command)\\n output(robot_name, \\\"Shutting down..\\\")\\n\\n history = []\",\n \"def loop(self):\\n rospy.loginfo(\\\"Hexapod entering main loop...\\\")\\n rospy.loginfo(\\\" Waiting for initial velocity command on /hexapod/cmd_vel/ ...\\\")\\n while self.last_vel_cmd is None:\\n self._loop_rate.sleep()\\n\\n # start main loop\\n while not rospy.is_shutdown():\\n\\n chassis_pos_delta = None\\n if self.last_vel_cmd is not None:\\n dt = 1 # FIXME: Temporary for debugging\\n lin_disp_lmt = self.linear_displacement_limit\\n ang_disp_lmt = self.angular_displacement_limit\\n chassis_pos_delta = Twist()\\n chassis_pos_delta.linear.x = clamp(self.last_vel_cmd.linear.x*dt, -lin_disp_lmt, lin_disp_lmt)\\n chassis_pos_delta.linear.y = clamp(self.last_vel_cmd.linear.y*dt, -lin_disp_lmt, lin_disp_lmt)\\n chassis_pos_delta.linear.z = clamp(self.last_vel_cmd.linear.z*dt, -lin_disp_lmt, lin_disp_lmt)\\n chassis_pos_delta.angular.x = clamp(self.last_vel_cmd.angular.x*dt, -ang_disp_lmt, ang_disp_lmt)\\n chassis_pos_delta.angular.y = clamp(self.last_vel_cmd.angular.y*dt, -ang_disp_lmt, ang_disp_lmt)\\n chassis_pos_delta.angular.z = clamp(self.last_vel_cmd.angular.z*dt, -ang_disp_lmt, ang_disp_lmt)\\n self.last_vel_cmd = None\\n\\n if chassis_pos_delta is not None \\\\\\n and not self._check_if_twist_msg_is_zero(chassis_pos_delta, linear_threshold=0.005, angular_threshold=0.01):\\n # Get chassis position transformation\\n chassis_pos_rot = transforms.euler_matrix(chassis_pos_delta.angular.x,\\n chassis_pos_delta.angular.y,\\n chassis_pos_delta.angular.z)[:3,:3]\\n\\n rospy.loginfo(\\\"chassis_pos_rot: %s\\\", chassis_pos_rot)\\n chassis_pos_trans = np.zeros([3])\\n chassis_pos_trans[0] = chassis_pos_delta.linear.x\\n chassis_pos_trans[1] = chassis_pos_delta.linear.y\\n chassis_pos_trans[2] = chassis_pos_delta.linear.z\\n chassis_translation = np.dot(chassis_pos_trans, chassis_pos_rot)\\n rospy.loginfo(\\\"chassis_translation: %s\\\", chassis_translation)\\n\\n leg_target_eff_translation = [[]]*LEGS\\n # Get leg base positions relative to chassis\\n leg_base_positions = self._get_base_to_leg_base_fk()\\n for i, leg_base_pos in enumerate(leg_base_positions):\\n leg_base_pos_arr = np.array(leg_base_pos).reshape(3,1)\\n leg_base_pos_arr_new = np.dot(chassis_pos_rot, leg_base_pos_arr)\\n leg_base_pos_trans_4 = np.ones(4).reshape(4,1)\\n leg_base_pos_trans_4[:3,:] = leg_base_pos_arr_new\\n # get leg base translations relative to leg_base coordinate frame\\n relative_trans = np.dot(np.linalg.inv(self.kdl_fk_base_to_leg_base[i].forward([])), leg_base_pos_trans_4)\\n relative_trans = relative_trans.reshape(1,4).tolist()[0][:3]\\n leg_target_eff_translation[i] = relative_trans\\n\\n # Get leg target end-effector translations\\n for i, q in enumerate(self.leg_jt_home_pos):\\n base_to_leg_base_rot = self.kdl_fk_base_to_leg_base[i].forward([])[:3,:3]\\n leg_target_eff_trans = np.dot(np.linalg.inv(base_to_leg_base_rot),chassis_translation).tolist()[0]\\n leg_target_eff_translation[i] = [x+y for x,y in zip(leg_target_eff_translation[i], leg_target_eff_trans)] # TODO: FIXME: Technically incorrect\\n\\n # 1: side_alpha legs lift, plant to +transformation\\n rospy.loginfo(\\\"1: side_alpha legs lift, plant to +transformation\\\")\\n if self._odd_starts:\\n active_legs = [1,2,5]\\n else: # even starts\\n active_legs = [0,3,4]\\n\\n init_wp = WaypointMsg()\\n lift_wp = WaypointMsg()\\n end_wp = WaypointMsg()\\n\\n legs_jt_init_pos = self._get_joint_angles()\\n leg_eff_cur_pos = self._get_leg_base_to_eff_fk(legs_jt_init_pos)\\n for i in range(LEGS):\\n motor_names = [name for name in self.hebi_mapping[i]]\\n # INITIAL POSITION\\n init_wp.names.extend(motor_names)\\n init_wp.positions.extend(legs_jt_init_pos[i])\\n init_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n init_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n # LIFT\\n lift_wp.names.extend(motor_names)\\n if i in active_legs:\\n # apply translation\\n leg_lift_eff_target_pos = [(x + y + z) / 2.0 for x, y, z in zip(leg_eff_cur_pos[i], self.leg_eff_home_pos[i], leg_target_eff_translation[i])]\\n leg_lift_eff_target_pos = [x + y for x,y in zip(leg_lift_eff_target_pos, self.leg_eff_step_height[i])]\\n # get ik\\n leg_lift_jt_target_pos = self._get_pos_ik(self.trac_ik_leg_base_to_end[i], legs_jt_init_pos[i],\\n leg_lift_eff_target_pos, seed_xyz=self.leg_eff_home_pos[i])\\n lift_wp.positions.extend(leg_lift_jt_target_pos)\\n lift_wp.velocities.extend([NAN]*ACTUATORS_PER_LEG)\\n lift_wp.accelerations.extend([NAN]*ACTUATORS_PER_LEG)\\n else:\\n lift_wp.positions.extend(legs_jt_init_pos[i])\\n lift_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n lift_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n # PLANT\\n end_wp.names.extend(motor_names)\\n if i in active_legs:\\n # apply translation\\n leg_plant_eff_target_pos = [x + y for x,y in zip(self.leg_eff_home_pos[i], leg_target_eff_translation[i])]\\n leg_plant_eff_target_pos[2] = self.leg_eff_home_pos[i][2] # end eff z-position should match home z-position\\n # get ik\\n leg_plant_jt_target_pos = self._get_pos_ik(self.trac_ik_leg_base_to_end[i], leg_lift_jt_target_pos,\\n leg_plant_eff_target_pos, seed_xyz=leg_lift_eff_target_pos)\\n end_wp.positions.extend(leg_plant_jt_target_pos)\\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n else:\\n end_wp.positions.extend(legs_jt_init_pos[i])\\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n\\n goal = TrajectoryGoal()\\n goal.waypoints.append(init_wp)\\n goal.waypoints.append(lift_wp)\\n goal.waypoints.append(end_wp)\\n goal.times.extend([0.0, 0.4, 0.8])\\n\\n self.release_pos([1,2,3,4,5,6])\\n self.trajectory_action_client.send_goal(goal)\\n self.trajectory_action_client.wait_for_result()\\n self.hold_pos([1,2,3,4,5,6])\\n\\n # 2: side_alpha legs push to new home positions; side_beta legs push to -transformation\\n rospy.loginfo(\\\"2: side_alpha legs push to new home positions; side_beta legs push to -transformation\\\")\\n if self._odd_starts:\\n active_legs = [0,3,4]\\n else: # even starts\\n active_legs = [1,2,5]\\n\\n init_wp = WaypointMsg()\\n end_wp = WaypointMsg()\\n\\n legs_jt_init_pos = self._get_joint_angles()\\n for i in range(LEGS):\\n motor_names = [name for name in self.hebi_mapping[i]]\\n # INITIAL POSITION\\n init_wp.names.extend(motor_names)\\n init_wp.positions.extend(legs_jt_init_pos[i])\\n init_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n init_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n # PUSH\\n end_wp.names.extend(motor_names)\\n if i in active_legs:\\n # apply -translation\\n leg_plant_eff_target_pos = [x + y for x,y in zip(self.leg_eff_home_pos[i], [-val for val in leg_target_eff_translation[i]])]\\n leg_plant_eff_target_pos[2] = self.leg_eff_home_pos[i][2] # end eff z-position should match home z-position\\n # get ik\\n leg_plant_jt_target_pos = self._get_pos_ik(self.trac_ik_leg_base_to_end[i], legs_jt_init_pos[i],\\n leg_plant_eff_target_pos, seed_xyz=self.leg_eff_home_pos[i])\\n end_wp.positions.extend(leg_plant_jt_target_pos)\\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n else:\\n end_wp.positions.extend(self.leg_jt_home_pos[i])\\n end_wp.velocities.extend([0.0]*ACTUATORS_PER_LEG)\\n end_wp.accelerations.extend([0.0]*ACTUATORS_PER_LEG)\\n\\n goal = TrajectoryGoal()\\n goal.waypoints.append(init_wp)\\n goal.waypoints.append(end_wp)\\n goal.times.extend([0.0, 0.4])\\n\\n self.release_pos([1,2,3,4,5,6])\\n self.trajectory_action_client.send_goal(goal)\\n self.trajectory_action_client.wait_for_result()\\n self.hold_pos([1,2,3,4,5,6])\\n\\n self._odd_starts = not self._odd_starts\\n\\n self._loop_rate.sleep() # FIXME: Doesn't make sense to use this unless re-planning trajectories\\n # end main loop\",\n \"def bye_bye():\\n\\n os.system(\\\"clear\\\")\\n print(\\\"Your opponent was too strong...\\\")\\n time.sleep(1)\\n print(\\\"You've should be better prepared...\\\")\\n time.sleep(2)\\n print()\\n print()\\n for i in range(20):\\n os.system(\\\"clear\\\")\\n print(\\\"\\\"\\\"\\n * ) ( \\n ( ( ( ` ( /( )\\\\ ) \\n )\\\\ ) )\\\\ )\\\\))( ( )\\\\())( ( ( (()/( \\n (()/( ((((_)( ((_)()\\\\ )\\\\ ((_)\\\\ )\\\\ )\\\\ )\\\\ /(_)) \\n /(_))_)\\\\ _ )\\\\(_()((_|(_) ((_|(_)((_|(_)(_)) \\n (_)) __(_)_\\\\(_) \\\\/ | __| / _ \\\\ \\\\ / /| __| _ \\\\ \\n | (_ |/ _ \\\\ | |\\\\/| | _| | (_) \\\\ V / | _|| / \\n \\\\___/_/ \\\\_\\\\|_| |_|___| \\\\___/ \\\\_/ |___|_|_\\\\ \\\"\\\"\\\")\\n time.sleep(0.05)\\n os.system(\\\"clear\\\")\\n print(\\\"\\\"\\\"\\n * ) ( \\n ( ( ( ` ( /( )\\\\ ) \\n )\\\\ ) )\\\\ )\\\\))( ( )\\\\())( ( ( (()/( \\n (()/( ((((_)( ((_)()\\\\ )\\\\ ((_)\\\\ )\\\\ )\\\\ )\\\\ /(_)) \\n /(_))_)\\\\ _ )\\\\(_()((_|(_) ((_|(_)((_|(_)(_)) \\n (_)) __(_)_\\\\(_) \\\\/ | __| / _ \\\\ \\\\ / /| __| _ \\\\ \\n | (_ |/ _ \\\\ | |\\\\/| | _| | (_) \\\\ V / | _|| / \\n \\\\___/_/ \\\\_\\\\|_| |_|___| \\\\___/ \\\\_/ |___|_|_\\\\ \\\"\\\"\\\")\\n time.sleep(0.05)\\n os.system(\\\"clear\\\")\\n print(\\\"\\\"\\\"\\n * ) ( \\n ( ( ( ` ( /( )\\\\ ) \\n )\\\\ ) )\\\\ )\\\\))( ( )\\\\())( ( ( (()/( \\n (()/( ((((_)( ((_)()\\\\ )\\\\ ((_)\\\\ )\\\\ )\\\\ )\\\\ /(_)) \\n /(_))_)\\\\ _ )\\\\(_()((_|(_) ((_|(_)((_|(_)(_)) \\n (_)) __(_)_\\\\(_) \\\\/ | __| / _ \\\\ \\\\ / /| __| _ \\\\ \\n | (_ |/ _ \\\\ | |\\\\/| | _| | (_) \\\\ V / | _|| / \\n \\\\___/_/ \\\\_\\\\|_| |_|___| \\\\___/ \\\\_/ |___|_|_\\\\ \\\"\\\"\\\")\\n os.system(\\\"clear\\\")\\n time.sleep(0.05)\\n print(\\\"\\\"\\\"\\n * ) ( \\n ( ( ( ` ( /( )\\\\ ) \\n )\\\\ ) )\\\\ )\\\\))( ( )\\\\())( ( ( (()/( \\n (()/( ((((_)( ((_)()\\\\ )\\\\ ((_)\\\\ )\\\\ )\\\\ )\\\\ /(_)) \\n /(_))_)\\\\ _ )\\\\(_()((_|(_) ((_|(_)((_|(_)(_)) \\n (_)) __(_)_\\\\(_) \\\\/ | __| / _ \\\\ \\\\ / /| __| _ \\\\ \\n | (_ |/ _ \\\\ | |\\\\/| | _| | (_) \\\\ V / | _|| / \\n \\\\___/_/ \\\\_\\\\|_| |_|___| \\\\___/ \\\\_/ |___|_|_\\\\ \\\"\\\"\\\")\\n os.system(\\\"clear\\\")\\n time.sleep(0.05)\\n print(\\\"\\\"\\\"\\n * ) ( \\n ( ( ( ` ( /( )\\\\ ) \\n )\\\\ ) )\\\\ )\\\\))( ( )\\\\())( ( ( (()/( \\n (()/( ((((_)( ((_)()\\\\ )\\\\ ((_)\\\\ )\\\\ )\\\\ )\\\\ /(_)) \\n /(_))_)\\\\ _ )\\\\(_()((_|(_) ((_|(_)((_|(_)(_)) \\n (_)) __(_)_\\\\(_) \\\\/ | __| / _ \\\\ \\\\ / /| __| _ \\\\ \\n | (_ |/ _ \\\\ | |\\\\/| | _| | (_) \\\\ V / | _|| / \\n \\\\___/_/ \\\\_\\\\|_| |_|___| \\\\___/ \\\\_/ |___|_|_\\\\ \\\"\\\"\\\")\\n time.sleep(0.05)\",\n \"def run():\\n step = 0\\n while traci.simulation.getMinExpectedNumber() > 0:\\n traci.simulationStep()\\n step+=1\\n traci.close()\\n sys.stdout.flush()\",\n \"async def loop():\\n # ArmDevice.storage.joints_pos = await get_positions() # Use this if encoders are wired up.\\n # ArmDevice.storage.joints_pos = simulate_positions() # Use this for testing without position feedback.\\n log.debug(\\\"command: {}\\\".format(ArmDevice.storage.command))\\n ArmDevice.storage.controller.user_command(ArmDevice.storage.mode, *ArmDevice.storage.command)\\n ArmDevice.storage.speeds = ArmDevice.storage.controller.update_duties(ArmDevice.storage.joints_pos)\\n\\n # publish speeds/duty cycles here\\n log.debug(\\\"joints_pos: {}\\\".format(ArmDevice.storage.joints_pos))\\n log.debug(\\\"speeds: {}\\\".format(ArmDevice.storage.speeds))\\n await send_duties()\",\n \"def GAMEOVER_LOOP():\\n pass\",\n \"def run_game():\\n set_locations()\\n while True:\\n draw_dungeon()\\n valid_moves = get_moves('player')\\n print(\\\"You're currently in room {}.\\\".format(STATUS['locations']['player']))\\n print(\\\"You are currently {}.\\\".format(STATUS['weapon']))\\n print(\\\"{}\\\".format(monster_check()))\\n print(\\\"You can move {} (w/a/s/d)\\\"\\n .format(', '.join(parse_moves(valid_moves))))\\n move = input(\\\"> \\\").upper()\\n while move not in valid_moves:\\n clear_screen()\\n print(\\\"There's no door that way... \\\")\\n draw_dungeon()\\n move = input(\\\"> \\\").upper()\\n clear_screen()\\n else:\\n clear_screen()\\n move_player(move)\\n weapon_check()\",\n \"def move():\\n Robot.move()\",\n \"def runemelt(n):\\n\\n print (\\\"place mouse at bank position, will document in 5s\\\") #Determine bank position\\n rt.wait(5)\\n bank_position = gui.position()\\n (xbank, ybank) = bank_position #assign seperate paramaters to positions so we can randomize them\\n print (\\\"Bank position = \\\", bank_position)\\n \\n print (\\\"place mouse at last ore position, will document in 5s\\\") #Determine 3rd ore position\\n rt.wait(5)\\n ore_position = gui.position()\\n (xore,yore) = ore_position\\n print( \\\"last ore position = \\\", ore_position)\\n\\n print (\\\"get ready, melting will begin in 5s\\\")\\n rt.wait(5)\\n\\n for i in range(int(n/3)+1):\\n randxbank = int(random.gauss(xbank,15))\\n randybank = int(random.gauss(ybank,15))\\n randxore = int(random.gauss(xore,5))\\n randyore = int(random.gauss(yore,5))\\n \\n process = float(i+1)/float(n/3)*100 #calculate percentage till done\\n eta = (n/3)*11 - i*11 \\n\\n mv.randmove(randxore,randyore,randxbank,randybank,10,0.5) #Move to bank\\n rt.wait(0.1)\\n \\n mouse.click() #click mouse\\n rt.wait(0.5)\\n\\n kb.press(\\\"2\\\",0.2) #press 2\\n\\n mv.randmove(randxbank,randybank,randxore,randyore,10,0.5) #move to ore position\\n rt.wait(0.7)\\n \\n for i in range(3): #three times\\n\\n kb.press(\\\"2\\\",0.2) #press 2\\n rt.wait(0.3)\\n\\n mouse.click() #click mouse\\n rt.wait(1)\\n\\n #USER update on progress:\\n #Process: 0.00% ETA: 00hour 00min 00s\\n\\n print (\\\"PROCESS: \\\", '%.2f' % process,\\\"% \\\", \\\"ETA: \\\", int(int(eta)/3600), \\\"hour\\\",int(int(eta)/60-((int(eta)/3600)*60)),\\\"min\\\",int(eta)%60,\\\"sec\\\")\",\n \"def run_test_move_arm_to_position():\\r\\n print()\\r\\n print(\\\"-----------------------------------------=-\\\")\\r\\n print(\\\"Testing the move_arm_to_position method\\\")\\r\\n print(\\\" of the ArmAndClaw class.\\\")\\r\\n print(\\\"-------------------------------------------\\\")\\r\\n print()\\r\\n\\r\\n # Start with a fresh (uncalibrated) ArmAndClaw.\\r\\n robot = rb.RoseBot()\\r\\n\\r\\n # Positions to which to move the Arm, one at a time.\\r\\n positions = [1200, 200, 1000, 2000, 1000, 500, 14 * 360, 0]\\r\\n print()\\r\\n print(\\\"READ the above tests to know what movement to expect\\\")\\r\\n print(\\\"in the following tests.\\\")\\r\\n\\r\\n try:\\r\\n for k in range(len(positions)):\\r\\n print()\\r\\n print(\\\"Press the ENTER key when ready for the robot\\\")\\r\\n print(\\\"to move to position {}.\\\".format(positions[k]))\\r\\n print(\\\"Since it has not yet been calibrated, it will first\\\")\\r\\n print(\\\"go UP, then DOWN, to calibrate, then to the above position.\\\")\\r\\n print(\\\" If it does NOT do that and seems to be stuck,\\\")\\r\\n input(\\\" press Control-C to force this test to stop.\\\")\\r\\n\\r\\n # -----------------------------------------------------------------\\r\\n #: 8. Replace the pass statement below with a call to\\r\\n # the move_arm_to_position method on the arm_and_claw\\r\\n # of the given RoseBot, sending it positions[k].\\r\\n # -----------------------------------------------------------------\\r\\n robot.arm_and_claw.move_arm_to_position(positions[k])\\r\\n\\r\\n except KeyboardInterrupt:\\r\\n print()\\r\\n print(\\\"OK, you just did a keyboard interrupt (Control-C).\\\")\\r\\n print(\\\"No worries. The program will keep running from here.\\\")\",\n \"def test(self):\\n while True: \\n gyX, gyY, gyZ = self.getGyro()\\n accX, accY, accZ = self.getAcc()\\n print(\\\"Gyroscope: X: %.2f Y: %.2f Z: %.2f\\\" %(gyX,gyY,gyZ))\\n print(\\\"Accelerom: X: %.2f Y: %.2f Z: %.2f\\\" %(accX,accY,accZ))\\n \\n time.sleep(0.5)\",\n \"def postloop() -> None:\\n print(\\\"\\\\n\\\")\",\n \"def do_motion_detection():\\n current_count = get_last_counter()\\n if not imageNumOn:\\n print(\\\"%s INFO : File Naming by Date Time Sequence\\\" % get_now())\\n while True:\\n x_pos, y_pos = scan_motion()\\n file_name = get_file_name(imagePath, imageNamePrefix, current_count)\\n take_day_image(file_name)\\n if imageNumOn:\\n current_count += 1\\n # Convert xy movement location for full size image\\n mo_x = x_pos * X_MO_CONV\\n mo_y = y_pos * Y_MO_CONV\\n if verbose:\\n print(\\\"%s INFO : Motion xy(%d,%d) Saved %s (%ix%i)\\\"\\n % (get_now(), mo_x, mo_y, file_name,\\n imageWidth, imageHeight,))\",\n \"def main():\\r\\n turn_left()\\r\\n move_three_times()\\r\\n turn_right()\\r\\n move_three_times()\\r\\n turn_right()\\r\\n move_three_times()\\r\\n turn_left()\",\n \"def play_one_move(self):\\n self.print(\\\"top of move\\\")\\n # 1) grab three cups\\n c1 = self.take_cup_after(self.current_cup_idx())\\n c2 = self.take_cup_after(self.current_cup_idx())\\n c3 = self.take_cup_after(self.current_cup_idx())\\n print(f\\\"pick up: {c1}, {c2}, {c3}\\\")\\n self.print(\\\"after pickup\\\")\\n\\n # 2) find a destination cup\\n destination_idx = self.find_next_destination(self.current_cup)\\n print(\\n f\\\"destination index is {destination_idx}, cup is {self.cups[destination_idx]}\\\"\\n )\\n\\n # 3) insert cups back into the circle\\n self.add_cups(destination_idx, [c1, c2, c3])\\n self.print(\\\"after adding cups..\\\")\\n\\n # 4) select the next cup\\n self.select_next_cup()\\n\\n self.print(\\\"post move\\\")\",\n \"def _main_loop(scr):\\n\\tglobal curr_player\\n\\tbob = Player()\\n\\tbob.name = 'Bob'\\n\\tcurr_player = bob\\n\\n\\twhile 1:\\n\\t\\t# Keep player in bounds (should actually change maps)\\n\\t\\tif bob.map_coords[0] > 79:\\n\\t\\t\\tbob.map_coords[0] = 0\\n\\t\\tif bob.map_coords[0] < 0:\\n\\t\\t\\tbob.map_coords[0] = 79\\n\\t\\tif bob.map_coords[1] > 19:\\n\\t\\t\\tbob.map_coords[1] = 0\\n\\t\\tif bob.map_coords[1] < 0:\\n\\t\\t\\tbob.map_coords[1] = 19\\n\\t\\ttime.sleep(0.01)\\n\\n\\t\\tscr.erase()\\n\\t\\tscr.addstr(bob.map_coords[1], bob.map_coords[0], '@')\\n\\n\\t\\t_draw_info_area(scr)\\n\\t\\t_handle_input(scr)\",\n \"def loop(self):\\n pass\",\n \"def step(self, action):\\n\\n action[1] = 0 if action[1] < 0 else 1\\n\\n if not self.moving:\\n self.agent_host.sendCommand(\\\"move 0.5\\\")\\n time.sleep(.2)\\n self.moving = True\\n\\n # Get Action\\n command = \\\"strafe \\\" + str(action[0])\\n if ((action[0] < 0 and self.allow_left) or (action[0] > 0 and self.allow_right)):\\n self.agent_host.sendCommand(command)\\n time.sleep(.2)\\n self.agent_host.sendCommand(\\\"strafe 0\\\")\\n time.sleep(.1)\\n\\n if action[1]:\\n if self.checkCommand:\\n self.jumpsOverDitches += 1\\n self.checkCommand = False\\n self.agent_host.sendCommand(\\\"jump 1\\\")\\n time.sleep(.2)\\n self.agent_host.sendCommand(\\\"jump 0\\\")\\n\\n # if (command == \\\"crouch 1\\\"):\\n # self.agent_host.sendCommand(command)\\n # time.sleep(.3)\\n # self.agent_host.sendCommand(\\\"crouch 0\\\")\\n # time.sleep(.2)\\n\\n self.episode_step += 1\\n\\n # Get Observation\\n world_state = self.agent_host.getWorldState()\\n for error in world_state.errors:\\n print(\\\"Error:\\\", error.text)\\n self.obs, self.allow_left, self.allow_right, curZPos, curXPos = self.get_observation(world_state)\\n if curZPos:\\n self.curZPos = curZPos\\n if curXPos:\\n if self.obs[3 + int(curXPos)]:\\n self.checkCommand = True\\n self.numDitchesEncountered += 1\\n\\n # Get Done\\n done = not world_state.is_mission_running \\n\\n # Get Reward\\n reward = 0\\n for r in world_state.rewards:\\n reward += r.getValue()\\n self.episode_return += reward\\n\\n return self.obs, reward, done, dict()\",\n \"def run(self):\\n while not self.turn_over:\\n self.go()\",\n \"def intro_instructions():\\n print(\\\"The board will be updated after each move.\\\")\\n print(\\\"Watch both the board and the python prompt after each move.\\\")\\n print(\\\"Player 1 is white and player 2 is orange\\\")\\n print(\\\"Green boxes are snakes and yellow boxes are ladders.\\\")\\n print(\\\"If you hit any part of the snake(not just the head), you will slide down to the snakes tail\\\")\\n print(\\\"If you hit any part of the ladder(not just the bottom), you will climb to the ladder's top\\\")\\n print(\\\"May the luckiest player win\\\")\",\n \"def loop1(self, move, new_state, i):\\n if move == i[0]:\\n # analyze another cell\\n if new_state.letters[i[1]].isalpha():\\n new_state.claim[i[2]] \\\\\\n = new_state.get_current_player_name()[1]\\n # analyze the other 3 cells\\n if (new_state.get_current_player_name()[1]\\n == new_state.letters[i[3]]\\n or new_state.get_current_player_name()[1]\\n == new_state.letters[i[4]]\\n or new_state.get_current_player_name()[1]\\n == new_state.letters[i[5]]) \\\\\\n and new_state.claim[i[6]] == \\\"@\\\":\\n new_state.claim[i[6]] \\\\\\n = new_state.get_current_player_name()[1]\\n # analyze the other 4 cells\\n count = 0\\n for x in [new_state.letters[i[7]],\\n new_state.letters[i[8]],\\n new_state.letters[i[9]],\\n new_state.letters[i[10]]]:\\n if new_state.get_current_player_name()[1] == x:\\n count += 1\\n if count == 2 and new_state.claim[i[11]] == \\\"@\\\":\\n new_state.claim[i[11]] = \\\\\\n new_state.get_current_player_name()[1]\\n new_state.letters = [self.get_current_player_name()[1]\\n if i == move else i for i in self.letters]\\n return new_state\",\n \"def win():\\n try:\\n color.write(\\\"=============================================\\\\n\\\",\\\"BUILTIN\\\")\\n print(\\\"Ctrl + C to skip!\\\")\\n slow_print(\\\"Finally\\\")\\n intro_dots()\\n slow_print(\\\"I am here at the Star of Tangaroa~\\\")\\n time.sleep(0.5)\\n slow_print(\\\"I wield the fishing rod of legends, and it is now time for the greatest catch~\\\")\\n time.sleep(0.5)\\n slow_print(\\\"Time to fish.~~\\\",\\\"ERROR\\\")\\n except:\\n pass\\n fishing = True\\n while fishing:\\n command = input(\\\"Enter a command: \\\").lower()\\n if command == 'fish' or command == 'f' or command == 'fishing':\\n fishing = False\\n else:\\n color.write(\\\"The time for the greatest catch is here. You wouldn't miss this for the world would you?\\\\n\\\\n\\\",\\\"ERROR\\\")\\n\\n try:\\n color.write(\\\"=============================================\\\\n\\\",\\\"BUILTIN\\\")\\n print(\\\"Ctrl + C to skip!\\\")\\n slow_print(\\\"Nnngh!~\\\")\\n time.sleep(0.5)\\n slow_print(\\\"This is a big one!~\\\")\\n time.sleep(0.5)\\n slow_print(\\\"BUT I AM MĀUI-POTIKI, AND NO CATCH WILL BEST ME!~\\\")\\n time.sleep(0.5)\\n slow_print(\\\"THIS~\\\",\\\"ERROR\\\")\\n time.sleep(0.2)\\n slow_print(\\\"IS~\\\",\\\"ERROR\\\")\\n time.sleep(0.2)\\n slow_print(\\\"MY~\\\",\\\"ERROR\\\")\\n time.sleep(0.2)\\n slow_print(\\\"LEGEND!~\\\",\\\"ERROR\\\")\\n time.sleep(2)\\n \\n except:\\n pass\\n ending(\\\"win\\\")\",\n \"def execute_pause(self):\\n print(self.empty_lines + self.double_tab + \\\"to continue press any key..\\\\r\\\")\\n self.getch()\",\n \"def move_player(direction):\\n global ZERO_BASE_PLYR_POS\\n if direction == \\\"north\\\":\\n ZERO_BASE_PLYR_POS -= 10\\n elif direction == \\\"south\\\":\\n ZERO_BASE_PLYR_POS += 10\\n elif direction == \\\"west\\\":\\n ZERO_BASE_PLYR_POS -= 1\\n elif direction == \\\"east\\\":\\n ZERO_BASE_PLYR_POS += 1\\n \\n sleep(0.5) # all moves have a 0.5 second delay\\n \\n show_ground_feature()\",\n \"def loop(self):\\r\\n while True:\\r\\n for event in pygame.event.get():\\r\\n if event.type == pygame.QUIT:\\r\\n return\\r\\n if not self.done:\\r\\n self.update_path()\\r\\n self.algorithm()\\r\\n\\r\\n self.screen.fill(self.LINE_COLOR)\\r\\n self.draw_board()\\r\\n pygame.display.flip()\\r\\n self.clock.tick(self.FPS)\",\n \"def interact():\\n env = SnakeEnv()\\n done = False\\n r = 0\\n action = random.randrange(4)\\n delay_time = 0.2\\n\\n # After the first run of the method env.render()\\n # env.renderer.viewer obtains an attribute 'window'\\n # which is a pyglet.window.Window object\\n env.render(mode='human')\\n # Use the arrows to control the snake's movement direction\\n @env.renderer.viewer.window.event\\n def on_text_motion(motion):\\n \\\"\\\"\\\"\\n Events to actions mapping\\n \\\"\\\"\\\"\\n\\n nonlocal action\\n if motion == MOTION_UP:\\n action = 0\\n elif motion == MOTION_DOWN:\\n action = 2\\n elif motion == MOTION_LEFT:\\n action = 3\\n elif motion == MOTION_RIGHT:\\n action = 1\\n\\n while not done:\\n time.sleep(delay_time)\\n obs, reward, done, info = env.step(action)\\n env.render(mode='human')\\n if reward:\\n r += reward\\n # Speeding up snake after eating food\\n delay_time -= 1/6 * delay_time\\n\\n return r\",\n \"def print_position(self):\\n\\n while True:\\n lat = self.vehicle.location.global_relative_frame.lat\\n lon = self.vehicle.location.global_relative_frame.lon\\n try:\\n self.pathFile.write('{0},{1}'.format(lat, lon))\\n time.sleep(1)\\n except:\\n break\\n #print ('{0},{1}'.format(lat, lon))\",\n \"def main():\\n while True:\\n # Get envrionment data\\n env_text = (\\\"{temperature:0.1f}°F {humidity:0.1f}% {pressure:0.1f}mb\\\"\\n \\\"\\\".format(\\n temperature=fahrenheit(sense.get_temperature()),\\n humidity=sense.get_humidity(),\\n pressure=sense.get_pressure(),\\n ))\\n \\n # Display on stdout\\n os.system('clear')\\n print(env_text)\\n\\n # Display on sense-hat\\n sense.set_rotation(0)\\n sense.show_message(\\n env_text,\\n scroll_speed=0.05,\\n text_colour=random_color(),\\n back_colour=e,\\n )\",\n \"def loop(self):\\n running = True\\n while running:\\n key_input = pygame.key.get_pressed()\\n for event in pygame.event.get():\\n if event.type is pygame.QUIT:\\n running = False\\n if key_input[pygame.K_ESCAPE]:\\n running = False\\n\\n # Player horizonal\\n if key_input[pygame.K_LEFT] and key_input[pygame.K_RIGHT]:\\n self.player.stop_moving()\\n elif key_input[pygame.K_LEFT]:\\n self.player.start_moving_left()\\n elif key_input[pygame.K_RIGHT]:\\n self.player.start_moving_right()\\n else:\\n self.player.stop_moving()\\n\\n # Player jump\\n if key_input[pygame.K_z]:\\n self.player.start_jump()\\n else:\\n # released?\\n self.player.stop_jump()\\n\\n self.clock.tick(self.fps)\\n \\n self.update(self.clock.get_time())\\n\\n self.draw()\",\n \"def main_loop(self):\\n dt = 0.3\\n self.clock.tick(self.fps)\\n while not self.done:\\n self.event_loop()\\n self.update(dt)\\n self.render()\\n dt = self.clock.tick(self.fps)/1000.0 # create delta time variable to multiply with movement and rotation\\n self.display_fps()\\n self.health_bar()\\n self.enemy_health()\\n self.energy_bar()\",\n \"def camonitor(self):\\n\\n try:\\n self._mov_ev.clear()\\n while not self._mov_ev.is_set():\\n print(\\\"\\\\r {0:4f}\\\".format(self.wm()), end=\\\" \\\")\\n self._mov_ev.wait(0.1)\\n except KeyboardInterrupt:\\n pass\\n finally:\\n self._mov_ev.clear()\",\n \"def intro_dots():\\n i = 0\\n time.sleep(0.6)\\n while i != 3:\\n color.write(\\\".\\\")\\n time.sleep(0.3)\\n i += 1\\n print(\\\"\\\")\",\n \"def move(self, direction):\\n command = self.DIRECTIONS[direction][\\\"command\\\"]\\n mem, out = self.cpu.run_program(inputs=[command])\\n status = out.pop()\\n if status in (1, 2):\\n self.position = Point(\\n self.position.x + self.DIRECTIONS[direction][\\\"mask\\\"][0],\\n self.position.y + self.DIRECTIONS[direction][\\\"mask\\\"][1]\\n )\\n if self.display:\\n self.draw_grid()\\n sleep(self.delay)\\n return status\",\n \"def printMovement(fltXCurrent, fltYCurrent, fltXNew, fltYNew):\\r\\n \\r\\n print(\\\"Moving from (\\\" + str(fltXCurrent) + \\\", \\\" +\\r\\n str(fltYCurrent) + \\\")\\\")\\r\\n \\r\\n print(\\\"to\\\" + \\\" \\\" * 10 + \\\"(\\\" + str(fltXNew) + \\\", \\\" +\\r\\n str(fltYNew) + \\\").\\\")\",\n \"def run(self):\\n while not self.done:\\n time_delta = self.clock.tick(self.fps)\\n self.event_loop()\\n self.update(time_delta)\\n pg.display.update()\\n if self.show_fps:\\n fps = self.clock.get_fps()\\n with_fps = \\\"{} - {:.2f} FPS\\\".format(self.caption, fps)\\n pg.display.set_caption(with_fps)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67542243","0.6601597","0.6516112","0.6261025","0.62314874","0.62044203","0.61881465","0.6146819","0.61307657","0.60168695","0.5986854","0.5973035","0.5970921","0.59660184","0.5957132","0.59444493","0.5920678","0.59130436","0.5904488","0.59033316","0.59018147","0.5882993","0.58811426","0.58779204","0.5844774","0.5831792","0.58108556","0.58025396","0.5793954","0.57893527","0.5782776","0.5760757","0.57575786","0.5755594","0.57524306","0.57467204","0.57432383","0.57429355","0.57252866","0.57213086","0.5716231","0.57143885","0.5707452","0.56950504","0.5689574","0.56869334","0.5686861","0.56827086","0.5681669","0.5674532","0.5673272","0.5670559","0.56606704","0.56477016","0.5641157","0.5640202","0.5634035","0.56272393","0.56239915","0.5617116","0.5605959","0.55904996","0.55904996","0.55895895","0.55869156","0.55861664","0.5566417","0.5561288","0.5557808","0.55527043","0.5552273","0.55516946","0.5551052","0.55499864","0.5547785","0.5535076","0.552237","0.5515199","0.5513816","0.5502567","0.5496421","0.5496402","0.54823714","0.54791516","0.54772234","0.54749936","0.54642487","0.54639876","0.54624414","0.54594535","0.54574853","0.5457439","0.5451171","0.5444927","0.5431182","0.5431039","0.5425972","0.54253906","0.541994","0.5419151"],"string":"[\n \"0.67542243\",\n \"0.6601597\",\n \"0.6516112\",\n \"0.6261025\",\n \"0.62314874\",\n \"0.62044203\",\n \"0.61881465\",\n \"0.6146819\",\n \"0.61307657\",\n \"0.60168695\",\n \"0.5986854\",\n \"0.5973035\",\n \"0.5970921\",\n \"0.59660184\",\n \"0.5957132\",\n \"0.59444493\",\n \"0.5920678\",\n \"0.59130436\",\n \"0.5904488\",\n \"0.59033316\",\n \"0.59018147\",\n \"0.5882993\",\n \"0.58811426\",\n \"0.58779204\",\n \"0.5844774\",\n \"0.5831792\",\n \"0.58108556\",\n \"0.58025396\",\n \"0.5793954\",\n \"0.57893527\",\n \"0.5782776\",\n \"0.5760757\",\n \"0.57575786\",\n \"0.5755594\",\n \"0.57524306\",\n \"0.57467204\",\n \"0.57432383\",\n \"0.57429355\",\n \"0.57252866\",\n \"0.57213086\",\n \"0.5716231\",\n \"0.57143885\",\n \"0.5707452\",\n \"0.56950504\",\n \"0.5689574\",\n \"0.56869334\",\n \"0.5686861\",\n \"0.56827086\",\n \"0.5681669\",\n \"0.5674532\",\n \"0.5673272\",\n \"0.5670559\",\n \"0.56606704\",\n \"0.56477016\",\n \"0.5641157\",\n \"0.5640202\",\n \"0.5634035\",\n \"0.56272393\",\n \"0.56239915\",\n \"0.5617116\",\n \"0.5605959\",\n \"0.55904996\",\n \"0.55904996\",\n \"0.55895895\",\n \"0.55869156\",\n \"0.55861664\",\n \"0.5566417\",\n \"0.5561288\",\n \"0.5557808\",\n \"0.55527043\",\n \"0.5552273\",\n \"0.55516946\",\n \"0.5551052\",\n \"0.55499864\",\n \"0.5547785\",\n \"0.5535076\",\n \"0.552237\",\n \"0.5515199\",\n \"0.5513816\",\n \"0.5502567\",\n \"0.5496421\",\n \"0.5496402\",\n \"0.54823714\",\n \"0.54791516\",\n \"0.54772234\",\n \"0.54749936\",\n \"0.54642487\",\n \"0.54639876\",\n \"0.54624414\",\n \"0.54594535\",\n \"0.54574853\",\n \"0.5457439\",\n \"0.5451171\",\n \"0.5444927\",\n \"0.5431182\",\n \"0.5431039\",\n \"0.5425972\",\n \"0.54253906\",\n \"0.541994\",\n \"0.5419151\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5588828"},"document_rank":{"kind":"string","value":"64"}}},{"rowIdx":13081,"cells":{"query":{"kind":"string","value":"Initialize relation as a set of nodes and edges. Edges are added onebyone as to assure the integrity of a structure. root_graphs is a subgraph of universe that does not have \"dead ends\""},"document":{"kind":"string","value":"def __init__(self, nodes: Set[Node], edges: Set[Edge]):\n super().__init__()\n self.nodes = nodes\n for edge in edges:\n self.add_edge(edge)\n self.leaves = {node for node in self.nodes if self.degree_out(node) == 0}\n root_nodes = self.nodes - self.leaves\n root_edges = {edge for edge in self.edges if edge.node_to not in self.leaves}\n self.root_graph = Mask(root_nodes, root_edges, self)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def initialize_graph(compound_relations, relation_types):\n graph = nx.DiGraph()\n for compound, targets in compound_relations.items():\n for target, relation in targets.items():\n if relation in relation_types:\n graph.add_edge(compound, target)\n return graph","def populate_graph(self):\n if self.edges and self.vertices:\n graph = Graph()\n for edge in self.edges:\n graph.add_edge(edge)\n self.graph = graph\n else:\n print(\"Populate edges & vertices first, then populate graph!\")","def complete_graph(self):\n root_nodes = set()\n\n for name, a_block in self.wf['action'].items():\n\n a_block['name'] = name\n\n for n in a_block.get('needs', []):\n if not self.wf['action'][n].get('next', None):\n self.wf['action'][n]['next'] = set()\n self.wf['action'][n]['next'].add(name)\n\n if not a_block.get('needs', None):\n root_nodes.add(name)\n\n self.wf['root'] = root_nodes","def populate_graph(self):","def _setup_graph(self):\n pass","def _setup_graph(self):\n pass","def legalize_graph(gm: pippy.fx.GraphModule) -> pippy.fx.GraphModule:\n indeg = {node: 0 for node in gm.graph.nodes}\n new_graph = pippy.fx.Graph()\n # Track how many unfulfilled dependencies each node has\n for node in gm.graph.nodes:\n for user in node.users:\n indeg[user] += 1\n queue: collections.deque = collections.deque()\n # Add all nodes with no dependencies to the queue\n for node in gm.graph.nodes:\n if indeg[node] == 0:\n queue.append(node)\n env: Dict[pippy.fx.Node, pippy.fx.Node] = {}\n # Pop nodes from the queue, and add nodes that have had all their\n # dependencies fulfilled\n while len(queue) > 0:\n cur = queue.popleft()\n env[cur] = new_graph.node_copy(cur, lambda x: env[x])\n for user in cur.users:\n indeg[user] -= 1\n if indeg[user] == 0:\n queue.append(user)\n # If the new graph's size is not as large as the old one, then there must be\n # a cycle (i.e. some node's dependencies were not satisfied.)\n if len(new_graph.nodes) < len(gm.graph.nodes):\n raise RuntimeError(f\"Input graph has cycles, unable to add {[node for node in indeg if indeg[node] != 0]}\")\n gm.graph = new_graph\n return gm","def _init_graph(self):\n self.G = nx.Graph()\n self.G.add_nodes_from([1,2,3,4,5])\n self.G.add_edges_from([(1,2),(2,3),(2,4)\\\n ,(2,5),(3,4),(4,5)])","def _build_graph(self):\n pass","def initialize_connection(self, branch_iterable: Iterable, root_iterable: Iterable) -> None:\n for root in root_iterable:\n for branch in branch_iterable:\n if root.group.intersection(branch.group):\n self._add_graph_edges(root, branch)\n return","def __init__(self, root):\r\n self.root = root\r\n self.nodes = [root]\r\n self.nodes.extend(Node.all_descendants(self.root))\r\n self.node_ids = [ n.id for n in self.nodes ]","def build_graph(self):\n pass","def __init__(self, vertices=[], edges=[]):\n for vertex in vertices:\n self.add_vertex(vertex)\n for edge in edges:\n self.add_edge(edge)","def __init__(self, nodes):\n\t\t\n\t\tself.variables = dict([(n.name, n) for n in nodes])\n\t\tself.roots = [n for n in nodes if not n.parents]\n\t\tself.nodes = nodes","def initGraphs(self):\n \n self.graph = ConjunctiveGraph()\n # Create a separate graph for annotations\n self.annotationGraph = ConjunctiveGraph()\n \n self.log.debug('Adding namespaces to graphs')\n # Bind namespaces to graphs\n for namespace in self.namespaces:\n self.graph.namespace_manager.bind(namespace, self.namespaces[namespace])\n\n # Same for annotation graph\n for namespace in self.annotationNamespaces:\n self.annotationGraph.namespace_manager.bind(namespace, self.annotationNamespaces[namespace])\n \n # Add schema information\n self.log.debug('Adding some schema information (dimension and measure properties) ')\n self.addDataCellProperty()\n\n # Add dimensions \n self.graph.add((self.namespaces['tablink']['dimension'], RDF.type, self.namespaces['qb']['DimensionProperty']))\n \n #self.graph.add((self.namespaces['tablink']['label'], RDF.type, RDF['Property']))","def _build_dependency_graph(self):\n\n #\n # Find the binary roles\n #\n nodes, roles = self._find_roles()\n\n #\n # Build the graph\n #\n working_list = list(set(nodes.keys()))\n\n setters = [b for b, r in roles.items() if Role.SETTER in r or Role.SETTER_GETTER in r]\n\n while working_list:\n b = working_list[0]\n working_list = working_list[1:]\n\n if nodes[b] not in self._graph:\n self._graph[nodes[b]] = []\n\n # it's a root node\n if Role.GETTER not in roles[b] and Role.SETTER_GETTER not in roles[b]:\n nodes[b].set_root()\n\n # takes params from some other binary\n else:\n is_orphan = True\n for setter in setters:\n setter_strings_set = set(nodes[setter].role_strings)\n node_strings_set = set(nodes[b].role_strings)\n if setter_strings_set.intersection(node_strings_set):\n if nodes[setter] not in self._graph:\n self._graph[nodes[setter]] = []\n self._graph[nodes[setter]].append(nodes[b])\n is_orphan = False\n\n # mark orphans\n if is_orphan:\n nodes[b].set_orphan()\n\n # Clean up\n for k, childs in self._graph.iteritems():\n self._graph[k] = list(set(childs))\n\n # set leaves\n for k, c in self._graph.iteritems():\n if not c:\n k.set_leaf()\n\n # post processing:\n # remove those nodes that are not orphans\n # and are not network parsers\n\n nodes = self.nodes\n children = [c for x in self._graph.values() for c in x if x]\n leafs_non_orphan = [n for n in nodes if n.leaf and not n.orphan]\n seed_names = [x.split('/')[-1] for x in self._seed_bins]\n spurious_nodes = [n for n in leafs_non_orphan if n not in children and n.bin.split('/')[-1] not in seed_names]\n for to_rem in spurious_nodes:\n del self._graph[to_rem]","def create_initial_graph(self):\n # Initialise weights\n for link in self.gene_links:\n link.weight = random.uniform(weight_init_min, weight_init_max)\n # Initialise biases\n for node in self.gene_nodes:\n node.bias = random.uniform(bias_init_min, bias_init_max)\n if node.can_modify:\n node.act_func = self.act_set.get_random_activation_func()\n if node.act_func in [activations.gaussian, activations.sin]:\n if node.act_func.__name__[0] == \"g\":\n node.freq += random.uniform(-guass_freq_adjust, guass_freq_adjust)\n elif node.act_func.__name__[0] == \"s\":\n node.freq += random.uniform(-sin_freq_adjust, sin_freq_adjust)\n node.amp += random.uniform(-func_amp_adjust, func_amp_adjust)\n node.vshift += random.uniform(-func_vshift_adjust, func_vshift_adjust)","def _setup_graph_def(self):\n raise NotImplementedError","def setUp(self):\n self.complete = nx.Graph()\n self.complete.add_edge(1, 2)\n self.complete.add_edge(2, 3)\n self.complete.add_edge(1, 3)\n\n self.small_tree = nx.Graph()\n self.small_tree.add_edge(1, 2)\n self.small_tree.add_edge(2, 3)\n self.small_tree.add_edge(3, 4)\n self.small_tree.add_edge(1, 4)\n self.small_tree.add_edge(2, 4)\n self.small_tree.add_edge(4, 5)\n self.small_tree.add_edge(5, 6)\n self.small_tree.add_edge(5, 7)\n self.small_tree.add_edge(6, 7)\n\n self.deterministic_graph = nx.Graph()\n self.deterministic_graph.add_edge(1, 2)\n self.deterministic_graph.add_edge(1, 3)\n self.deterministic_graph.add_edge(3, 4)\n self.deterministic_graph.add_edge(2, 4)\n self.deterministic_graph.add_edge(3, 5)\n self.deterministic_graph.add_edge(4, 5)\n self.deterministic_graph.add_edge(3, 6)\n self.deterministic_graph.add_edge(5, 6)","def __init__(self, nodeset):\n self.nodeset = nodeset # initialize all necessary fields\n\n self.__check_validity() # check if graph is valid - throws exception if not","def __init__(self):\n\n self.nodes = set()","def __init__(self, directed=True):\n self.nodes = set()\n self.edges = []\n self.directed = directed","def build_graph(self, objects_: Union[Dict[str, List[Union[str, dict, int]]], NamedTuple],\n root_name: str, *branch_names: str) -> list:\n\n all_nodes = []\n for key, value in objects_.items():\n for index, items in enumerate(value):\n if isinstance(items, dict):\n vertices = self.initialize_vertices(objects_=items,\n root_name=root_name,\n independent=False,\n group=index)\n all_nodes.extend(vertices)\n continue\n\n root = set()\n\n for vertex in all_nodes:\n if vertex[root_name]:\n root.add(vertex[root_name])\n\n for branch in branch_names:\n if not isinstance(branch, str):\n raise TypeError(f\"Expected a string, got {type(branch)}\")\n\n try:\n if vertex[branch]:\n branches = self.locate_graph_link(vertex_list=all_nodes,\n branch_name=branch)\n except KeyError:\n continue\n\n share = self.initialize_connection(branch_iterable=branches, root_iterable=root)\n\n return self.find_nodes_subtype(root_name)","def _construct_graph(self):\n raise NotImplementedError","def setgraphs(self, graphs):\n\n self.__graphs = graphs\n # Create table_graph objects\n rgraph = re.compile(r\":([^:]+):([^:]+):([^:]+):\")\n for graph in rgraph.findall(graphs):\n new_graph = self.addgraph(graph[0])\n new_graph.setscaling(graph[1])\n new_graph.setcolumns(graph[2])\n self.__nonzero = True","def init_graph(self):\n import dgl\n\n adj_list = []\n for rel_type in range(1, self.n_relations, 1):\n edge_idxs = self.ckg.filter_edges(\n lambda edge: edge.data[\"relation_id\"] == rel_type\n )\n sub_graph = (\n dgl.edge_subgraph(self.ckg, edge_idxs, preserve_nodes=True)\n .adjacency_matrix(transpose=False, scipy_fmt=\"coo\")\n .astype(\"float\")\n )\n rowsum = np.array(sub_graph.sum(1))\n d_inv = np.power(rowsum, -1).flatten()\n d_inv[np.isinf(d_inv)] = 0.0\n d_mat_inv = sp.diags(d_inv)\n norm_adj = d_mat_inv.dot(sub_graph).tocoo()\n adj_list.append(norm_adj)\n\n final_adj_matrix = sum(adj_list).tocoo()\n indices = torch.LongTensor([final_adj_matrix.row, final_adj_matrix.col])\n values = torch.FloatTensor(final_adj_matrix.data)\n adj_matrix_tensor = torch.sparse.FloatTensor(indices, values, self.matrix_size)\n return adj_matrix_tensor.to(self.device)","def __init__(self):\n self.graph = {}\n self.edges = 0\n self.vertices = 0","def build_graph(self):\n self.import_tree(ZOO_PATH, self.import_zoo, self.verify_zoos)\n self.import_tree(WILD_PATH, self.import_wild, self.verify_wilds)\n self.import_tree(PANDA_PATH, self.import_redpanda, self.verify_pandas)\n self.import_tree(MEDIA_PATH, self.import_media, self.verify_media)","def isValidCompatible(cls,root):\n valid = True\n # the order of node types in chains is restricted\n # (this would be easier if the data was in a Corpus-instance)\n allowed = NX.XDiGraph(selfloops=True)\n\n # continue from here!\n allowed.add_edge('Physical','Physical')\n allowed.add_edge('Property','Physical')\n allowed.add_edge('Process','Physical')\n allowed.add_edge('Regulation','Physical')\n\n allowed.add_edge('Property','Property')\n allowed.add_edge('Process','Property')\n allowed.add_edge('Regulation','Property')\n\n allowed.add_edge('Property','Process')\n# allowed.add_edge('Process','Process')\n allowed.add_edge('Regulation','Process')\n\n allowed.add_edge('Property','Regulation')\n# allowed.add_edge('Process','Regulation')\n allowed.add_edge('Regulation','Regulation')\n\n mapping = {}\n for a in root.find(\"ontologies\").findall(\"ontology\"):\n if a.attrib['id']=='interaction':\n for x in a.getiterator(\"ontnode\"):\n if x.attrib.has_key('effect') and x.attrib['effect'].endswith('regulation'):\n t = 'Regulation'\n else:\n t = x.attrib['onttype']\n mapping[x.attrib['id']] = t\n \n for a in root.getiterator(\"relannotation\"):\n t2type = dict( [(x.attrib['id'],x.attrib['type'])\n for x in a.findall(\"reltoken\")] )\n n2t = dict( [(x.attrib['id'],x.attrib['token'])\n for x in a.findall(\"relnode\")] )\n for x in a.findall(\"reledge\"):\n bt = t2type[n2t[x.attrib['bgn']]]\n et = t2type[n2t[x.attrib['end']]]\n bgn = mapping[bt]\n end = mapping[et]\n if not allowed.has_edge(bgn,end):\n printError(cls,inspect.stack()[1][3],\n \"%s -- %s (%s) -> %s (%s) is not a valid edge\"%\n (x.attrib['id'].split('.')[1],bgn,bt,end,et))\n valid = False\n \n return(valid)","def build_graph(self):\n raise NotImplementedError","def __init__(self):\n self.graph = None","def __init__(self, edges=None, nodes=None, graph=None):\n self.edges = edges\n self.nodes = nodes\n self.graph = graph","def init_vertices(self):\n self.vertices = []\n for key in self.graph:\n self.vertices.append(self.Vertex(key, self.graph[key]))","def make_complete_graph(num_nodes):\n xgraph = {} #Create a Blank Dict\n if num_nodes - 1 < 0: # checks to see if the num_nodes is less then 0 (negative number) if it is return empty graph (dict). Could probably combine the If statments for negative nodes and 1 node together\n return xgraph\n if num_nodes - 1 == 0: # If the number of nodes is 1 or returns a one node dict because there are no edges to compute\n xgraph[0] = set([]) # creates a dict that represents a single node graph as per the requirement\n return xgraph # the empty Graph\n else:\n for base_node in range(num_nodes): # This portion starts the build phase. for each node it will compute the theretical maximum amount of edges\n xlist = set([]) # defines an empty list. We first build a list for each node and the append to a dict. This list is erased with each iteration\n #print base_node # testing - REMOVE\n for edge_node in range(num_nodes):\n #print edge_node # testing - REMOVE\n if edge_node != base_node: #No Looping is allowed for this project. Therefor we check to insure the we are not counting a self node connection (edge_node NOT equal base_node)\n xlist.add(edge_node) # Populating list that will be added to dict\n\n xgraph[base_node] = xlist # Appending created list to the dict\n\n return xgraph # returning populated dict","def make_complete_graph(num_nodes):\n xgraph = {} #Create a Blank Dict\n if num_nodes - 1 < 0: # checks to see if the num_nodes is less then 0 (negative number) if it is return empty graph (dict). Could probably combine the If statments for negative nodes and 1 node together\n return xgraph\n if num_nodes - 1 == 0: # If the number of nodes is 1 or returns a one node dict because there are no edges to compute\n xgraph[0] = set([]) # creates a dict that represents a single node graph as per the requirement\n return xgraph # the empty Graph\n else:\n for base_node in range(num_nodes): # This portion starts the build phase. for each node it will compute the theretical maximum amount of edges\n xlist = set([]) # defines an empty list. We first build a list for each node and the append to a dict. This list is erased with each iteration\n #print base_node # testing - REMOVE\n for edge_node in range(num_nodes):\n #print edge_node # testing - REMOVE\n if edge_node != base_node: #No Looping is allowed for this project. Therefor we check to insure the we are not counting a self node connection (edge_node NOT equal base_node)\n xlist.add(edge_node) # Populating list that will be added to dict\n\n xgraph[base_node] = xlist # Appending created list to the dict\n\n return xgraph # returning populated dict","def build_graph(self):\n for each_list in self.lab.look():\n vertice = self._add_vertice(each_list)\n if vertice:\n self.unvisited.add(vertice)\n self.graph.addEdge((self.current, vertice))\n \n self.unvisited -= self.visited\n self._connect_neighbours()","def direct_network(self):\n #print list(self.get_subgraphs())\n graphs = [self._depth_first_directed(g) for g in self.get_subgraphs()]\n self._network = reduce(lambda a, b: nx.union(a, b), graphs)","def _internal_build(self):\n self.nodes = self.__tree.Nodes()\n self.edges = self.__tree.Edges()\n self.augmentedEdges = {}\n for key, val in self.__tree.AugmentedEdges().items():\n self.augmentedEdges[key] = list(val)\n self.root = self.__tree.Root()\n\n seen = set()\n self.branches = set()\n\n # Find all of the branching nodes in the tree, degree > 1\n # That is, they appear in more than one edge\n for e1, e2 in self.edges:\n if e1 not in seen:\n seen.add(e1)\n else:\n self.branches.add(e1)\n\n if e2 not in seen:\n seen.add(e2)\n else:\n self.branches.add(e2)\n\n # The nodes that are not branches are leaves\n self.leaves = set(self.nodes.keys()) - self.branches\n self.leaves.remove(self.root)","def __init__(self):\n self._graph = DirectedGraph()\n self._graph_copies = []","def _get_full_graph(self):","def set_root(self, root):\n self.root = root\n self.sites = [root]","def reset_graph(self):\n self.graph = OrderedDict()","def graphing_setup(self):\n pass","def _CreateGraph(self):\n self.nodes = []\n self.edges = []\n for i, r in self.airports.set_index('airport_id').iterrows():\n self.nodes.append((i,r.to_dict()))\n for i, r in self.routes.set_index(['src_id','dst_id']).iterrows():\n self.edges.append((i[0],i[1],r.to_dict()))\n # print('node ex: {}'.format(self.nodes[0]))\n # print('edge ex: {}'.format(self.edges[0]))\n\n self.graph = self._CreateAdjacencyListGraph()","def __initilization(self,node_set):\n \n print \"*********************************\"\n \n for x in node_set:\n x.node_vol=np.transpose(np.matrix([cmath.exp(0), cmath.exp(complex(0,math.pi*2/3)), cmath.exp(complex(0,-math.pi*2/3))]))\n \n print \"Forward/Backward Algorithm Initialization Done!\"","def __init__(self, start_edges=None):\n self.adj_list = dict()\n\n # populate graph with initial vertices and edges (if provided)\n # before using, implement add_vertex() and add_edge() methods\n if start_edges is not None:\n for u, v in start_edges:\n self.add_edge(u, v)","def _build_graph_general(self): \n\n #Find a canonical coloring scheme\n #Each node has a color that is determined by the non-mapped aspects\n nodecolors=set()\n for nl in self.net.iter_node_layers():\n nodecolors.add(self._slice_node_layer_not_allowed(nl))\n nodecolors_sorted=sorted(list(nodecolors))\n del nodecolors\n self._assert_full_order(nodecolors_sorted)\n self.colormap=dict( ((color,colorid) for colorid,color in enumerate(nodecolors_sorted) ))\n\n #each aux node has a color that is determined by the aspect\n self.auxcolormap=dict( ((auxcolor, auxcolorid+len(self.colormap)) for auxcolorid,auxcolor in enumerate(sorted(self.asp)) ) )\n\n\n #Add the underlying network\n #node-layers:\n for nl in self.net.iter_node_layers():\n nlid=self._get_node_id(nl)\n color=self._slice_node_layer_not_allowed(nl)\n colorid=self.colormap[color]\n self.add_node(nlid,colorid)\n\n #edges between node-layers:\n for nl1 in self.net.iter_node_layers():\n for nl2 in self.net[nl1]:\n nl1id=self._get_node_id(nl1)\n nl2id=self._get_node_id(nl2)\n self.add_link(nl1id,nl2id)\n\n\n #Add the auxiliary nodes and edges\n #add the aux nodes\n for a in self.asp:\n for elayer in self.net.slices[a]:\n auxid=self._get_auxnode_id( (a,elayer) )\n auxcolorid=self.auxcolormap[a]\n self.add_node(auxid,auxcolorid)\n \n #add the aux edges\n for nl in self.net.iter_node_layers():\n for a in self.asp:\n nlid=self._get_node_id(nl)\n auxid=self._get_auxnode_id( (a,nl[a]) )\n self.add_link(nlid,auxid)","def graph_root_setter(server, graph):\n if graph:\n if isinstance(graph, dict):\n kind = graph.get(\"kind\")\n elif hasattr(graph, \"kind\"):\n kind = graph.kind\n else:\n raise MLRunInvalidArgumentError(\"graph must be a dict or a valid object\")\n if kind == StepKinds.router:\n server._graph = server._verify_dict(graph, \"graph\", RouterStep)\n elif not kind or kind == StepKinds.root:\n server._graph = server._verify_dict(graph, \"graph\", RootFlowStep)\n else:\n raise GraphError(f\"illegal root step {kind}\")","def __init__(self, prefix, downstream, upstream, root):\n super(SubGraph, self).__init__(prefix, downstream, upstream, root)","def initialize_graph(self, V, edge_list):\n # ---------- INSERT CODE BELOW ----------\n for _ in range(V):\n self.add_vertex()\n \n for node in edge_list:\n self.add_edge(node[0],node[1],node[2])\n\n # ---------- INSERT CODE ABOVE ----------","def sub_graph_merging(self):","def __init__(self):\n self.data_graph = self._initialise_data()\n\n self.messages_sent = []\n self.messages_received = []\n\n self.answered_true = set()\n self.implied_true = set()\n\n self.current_subgraph = set()","def _initilise_graph_db(self):\n for collector in self.collectors:\n collector.init_graph_db()","def __init__(self):\n\t\tself.edges = defaultdict(list)\n\t\tself.weights = {}\n\t\tself.connections = {}","def buildGraph(self):\n return None","def _generate_vertexes(self):\n # generate list of sets for each vms\n self._graph = [set() for _ in range(self._vm_count)]","def build_3_node_line_root_articulation_graph(directed=False):\n if directed:\n graph = DirectedGraph()\n else:\n graph = UndirectedGraph()\n\n graph.new_node()\n graph.new_node()\n graph.new_node()\n\n graph.new_edge(1, 2)\n graph.new_edge(1, 3)\n\n return graph","def __init__(self, graph=None):\n\n self.graph = graph if graph else nx.Graph()","def _create_graph(self, pools: List[Pool]):\n for pool in pools:\n self._add_nodes(pool.tokens)\n\n for pool in pools: # noqa: WPS440,WPS441\n self._add_edges(pool) # noqa: WPS441","def __init__(self, subnodes, optionals=None):\n self.subnodes = subnodes\n self.optionals = optionals or []","def __init__(self, nodes=None, edges=None):\n self._nodes = []\n self.nodes = nodes\n self._edges = []\n self.edges = edges\n self._create_connections()\n self._sorted_nodes = None\n self._node_wip = []","def multi_edge():\n from networkx.readwrite import json_graph\n import networkx as nx\n import autonetkit\n # returns a house graph\n data = {'directed': False,\n 'graph': [],\n 'links': [{'_ports': {'r4': 2, 'r5': 1},\n 'raw_interfaces': {},\n 'source': 0,\n 'target': 1},\n {'_ports': {'r2': 3, 'r4': 1},\n 'raw_interfaces': {},\n 'source': 0,\n 'target': 3},\n {'_ports': {'r2': 4, 'r4': 3},\n 'raw_interfaces': {},\n 'source': 0,\n 'target': 3},\n {'_ports': {'r3': 3, 'r5': 2},\n 'raw_interfaces': {},\n 'source': 1,\n 'target': 4},\n {'_ports': {'r1': 1, 'r2': 1},\n 'raw_interfaces': {},\n 'source': 2,\n 'target': 3},\n {'_ports': {'r1': 3, 'r2': 5},\n 'raw_interfaces': {},\n 'source': 2,\n 'target': 3},\n {'_ports': {'r1': 2, 'r3': 1},\n 'raw_interfaces': {},\n 'source': 2,\n 'target': 4},\n {'_ports': {'r1': 4, 'r3': 4},\n 'raw_interfaces': {},\n 'source': 2,\n 'target': 4},\n {'_ports': {'r1': 5, 'r3': 5},\n 'raw_interfaces': {},\n 'source': 2,\n 'target': 4},\n {'_ports': {'r2': 2, 'r3': 2},\n 'raw_interfaces': {},\n 'source': 3,\n 'target': 4}],\n 'multigraph': True,\n 'nodes': [{'_ports': {0: {'category': 'physical', 'description': None},\n 1: {'category': 'physical', 'description': 'r4 to r2', 'id': 'eth0'},\n 2: {'category': 'physical', 'description': 'r4 to r5', 'id': 'eth1'},\n 3: {'category': 'physical', 'description': 'r4 to r2', 'id': 'eth2'}},\n 'asn': 2,\n 'device_type': 'router',\n 'id': 'r4',\n 'label': 'r4',\n 'x': 675,\n 'y': 300},\n {'_ports': {0: {'category': 'physical', 'description': None},\n 1: {'category': 'physical', 'description': 'r5 to r4', 'id': 'eth0'},\n 2: {'category': 'physical', 'description': 'r5 to r3', 'id': 'eth1'}},\n 'asn': 2,\n 'device_type': 'router',\n 'id': 'r5',\n 'label': 'r5',\n 'x': 675,\n 'y': 500},\n {'_ports': {0: {'category': 'physical', 'description': None},\n 1: {'category': 'physical', 'description': 'r1 to r2', 'id': 'eth0'},\n 2: {'category': 'physical', 'description': 'r1 to r3', 'id': 'eth1'},\n 3: {'category': 'physical', 'description': 'r1 to r2', 'id': 'eth2'},\n 4: {'category': 'physical', 'description': 'r1 to r3', 'id': 'eth3'},\n 5: {'category': 'physical', 'description': 'r1 to r3', 'id': 'eth4'}},\n 'asn': 1,\n 'device_type': 'router',\n 'id': 'r1',\n 'label': 'r1',\n 'x': 350,\n 'y': 400},\n {'_ports': {0: {'category': 'physical', 'description': None},\n 1: {'category': 'physical', 'description': 'r2 to r1', 'id': 'eth0'},\n 2: {'category': 'physical', 'description': 'r2 to r3', 'id': 'eth1'},\n 3: {'category': 'physical', 'description': 'r2 to r4', 'id': 'eth2'},\n 4: {'category': 'physical', 'description': 'r2 to r4', 'id': 'eth3'},\n 5: {'category': 'physical', 'description': 'r2 to r1', 'id': 'eth4'}},\n 'asn': 1,\n 'device_type': 'router',\n 'id': 'r2',\n 'label': 'r2',\n 'x': 500,\n 'y': 300},\n {'_ports': {0: {'category': 'physical', 'description': None},\n 1: {'category': 'physical', 'description': 'r3 to r1', 'id': 'eth0'},\n 2: {'category': 'physical', 'description': 'r3 to r2', 'id': 'eth1'},\n 3: {'category': 'physical', 'description': 'r3 to r5', 'id': 'eth2'},\n 4: {'category': 'physical', 'description': 'r3 to r1', 'id': 'eth3'},\n 5: {'category': 'physical', 'description': 'r3 to r1', 'id': 'eth4'}},\n 'asn': 1,\n 'device_type': 'router',\n 'id': 'r3',\n 'label': 'r3',\n 'x': 500,\n 'y': 500}]}\n graph = json_graph.node_link_graph(data)\n anm = autonetkit.anm.NetworkModel()\n g_in = anm.add_overlay(\"input\")\n g_in._replace_graph(nx.MultiGraph(graph))\n # TODO: check if should build overlays here rather than clone in?\n g_phy = anm[\"phy\"]\n g_phy._replace_graph(graph)\n return anm","def connect_all(graph, nodeset):\n for element in nodeset:\n graph.add_node(element)\n for element1 in nodeset:\n for element2 in nodeset:\n if not element1 == element2:\n graph.add_edge(element1, element2)\n return graph","def _build_graphs(self):\n g1 = self._build_graph1()\n g2 = self._build_graph2(g1)\n return g1, g2","def __init__(self, nodes=None, connections=None):\r\n\r\n super(Graph, self).__init__()\r\n self.nodes = OrderedDict()\r\n self.connections = set()\r\n\r\n self.logger = get_logger()\r\n\r\n self._name_sequence = 1\r\n\r\n if nodes:\r\n try:\r\n for name, node in nodes.items():\r\n self.add(node, name)\r\n except:\r\n raise ValueError(\"Nodes should be a dictionary, is %s\" % type(nodes))\r\n\r\n if connections:\r\n for connection in connections:\r\n self.connect(connection[0], connection[1])","def build_graph(self):\n self._reset_iterator_memory()\n self._construct_graph_handler()\n assert self.graph_handler\n for rxn_id in self.graph_handler.get_valid_reaction_ids():\n rxn = db.Reaction(rxn_id, self._reactions)\n self.graph_handler.add_rxn(rxn)","def create_graph(self,root_path):\n graph = self.graph\n\n #get the path lists recursively from the root directory \n path_list = sorted(Path(root_path).rglob('*'))\n # create the necessary amount of vertices \n graph.add_vertices(len(path_list)+1)\n \n # these list will be used for inserting to sqlite database\n vertices = []\n edges = []\n\n # now the edges have to be created, and the vertices need the file informations\n # first is the root vertex\n temp=graph.vs[0]\n temp[\"name\"]=root_path\n temp[\"parent\"]=\"\"\n temp[\"size\"]=os.stat(root_path).st_size\n temp[\"last_modified\"]=os.stat(root_path).st_mtime\n temp[\"last_accessed\"]=os.stat(root_path).st_atime\n \n vertices.append((0,temp[\"name\"],temp[\"parent\"],temp[\"size\"],temp[\"last_modified\"],temp[\"last_accessed\"]))\n\n # walking through the paths, the vertices get the informations, and the egdes will be created\n for i, file in enumerate(path_list):\n temp=graph.vs[i+1]\n temp[\"name\"]=file.as_posix()\n temp[\"parent\"]=file.parent.as_posix()\n temp[\"size\"]=os.stat(file).st_size\n temp[\"last_modified\"]=os.stat(file).st_mtime\n temp[\"last_accessed\"]=os.stat(file).st_atime\n vertices.append((temp.index,temp[\"name\"],temp[\"parent\"],temp[\"size\"],temp[\"last_modified\"],temp[\"last_accessed\"]))\n \n parent_id=graph.vs.find(name=temp[\"parent\"]).index\n # Egde is defined beetween the current vertex and its parent\n graph.add_edges([(i+1,parent_id)])\n edges.append((i+1,parent_id))\n\n # save the created Graph object into the connected redis database as JSON\n cache= get_redis()\n cache.execute_command('JSON.SET', 'vertices_name','.',json.dumps(self.graph.vs[\"name\"]))\n cache.execute_command('JSON.SET', 'vertices_parent','.',json.dumps(self.graph.vs[\"parent\"]))\n cache.execute_command('JSON.SET', 'vertices_size','.',json.dumps(self.graph.vs[\"size\"]))\n cache.execute_command('JSON.SET', 'vertices_last_modified','.',json.dumps(self.graph.vs[\"last_modified\"]))\n cache.execute_command('JSON.SET', 'vertices_last_accessed','.',json.dumps(self.graph.vs[\"last_accessed\"]))\n cache.execute_command('JSON.SET', 'edges','.',json.dumps(self.graph.get_edgelist()))\n\n # save the created Graph object into the connected sqlite database \n conn = get_sqlite()\n c = conn.cursor()\n c.execute('DROP TABLE IF EXISTS vertices')\n c.execute('DROP TABLE IF EXISTS edges')\n c.execute('CREATE TABLE vertices (id, name, parent, size, last_modified, last_accessed)')\n c.execute('CREATE TABLE edges (start, end)')\n c.executemany('INSERT INTO vertices VALUES (?,?,?,?,?,?)', vertices)\n c.executemany('INSERT INTO edges VALUES (?,?)', edges)\n conn.commit()\n\n # optionally create image from the Graph object\n # unfortunatelly this feature not working correctly now\n plot(graph,\"plot.png\", layout=\"tree\")","def __init__(self, vertices=None):\n\n self._vertices = dict() \n if vertices is not None:\n for label in vertices.keys():\n self.add_vertex(label)\n for label, heads in vertices.items():\n for head in heads:\n self.add_edge(label, head)","def build_graph(edges):\n \n G = nx.MultiGraph()\n G.add_edges_from(edges)\n return G","def to_undirected_graph(self):\n visited = set() \n G = Graph.Graph()\n \n for node in self.node_set:\n \n if node not in visited:\n visited.add(node)\n for i in self.suffix[node]:\n G.add_edge(node, i)\n \n return G","def __init__(self, graph: ghidra.graph.GImplicitDirectedGraph):\n ...","def test_build_graph():\r\n assert valid_graph.get_graph() is not None\r\n assert invalid_graph.get_graph() != collections.defaultdict(list)","def build_drop_fullgraphs(self, do_subgraph=False, graph_lib='pygraphviz'):\n if 'pygraphviz' == graph_lib:\n G = pgv.AGraph(strict=True, directed=True)\n else:\n G = nx.Graph()\n do_subgraph = False\n subgraph_dict = defaultdict(list) # k - node-ip, v - a list of graph nodes\n oid_gnid_dict = dict()\n\n for i, oid in enumerate(self.pg_spec.keys()):\n oid_gnid_dict[oid] = str(i)\n logger.info(\"oid to gid mapping done\")\n\n for dropspec in self.pg_spec.itervalues():\n gid = oid_gnid_dict[dropspec['oid']]\n ip = dropspec['node']\n subgraph_dict[ip].append(gid)\n if (dropspec['type'] == 'app'):\n G.add_node(gid, shape='rect', label='')#, fixedsize=True, hight=.05, width=.05)\n elif (dropspec['type'] == 'plain'): #parallelogram\n G.add_node(gid, shape='circle', label='')#, fixedsize=True, hight=.05, width=.05)\n logger.info(\"Graph nodes added\")\n\n for dropspec in self.pg_spec.itervalues():\n gid = oid_gnid_dict[dropspec['oid']]\n if (dropspec['type'] == 'app'):\n ds_kw = 'outputs' #down stream key word\n elif (dropspec['type'] == 'plain'):\n ds_kw = 'consumers'\n else:\n ds_kw = 'None'\n if (ds_kw in dropspec):\n for doid in dropspec[ds_kw]:\n G.add_edge(gid, oid_gnid_dict[doid])\n logger.info(\"Graph edges added\")\n\n if (do_subgraph):\n for i, subgraph_nodes in enumerate(subgraph_dict.values()):\n # we don't care about the subgraph label or rank\n subgraph = G.add_subgraph(subgraph_nodes, label='%d' % i, name=\"cluster_%d\" % i, rank=\"same\")\n subgraph.graph_attr['rank']='same'\n logger.info(\"Subgraph added\")\n\n return G","def _make_graph(nodes, ways):\n graph = networkx.MultiDiGraph(crs=\"EPSG:4326\")\n ways_proj = ways.set_crs(\"EPSG:4326\").to_crs(\"EPSG:3395\")\n\n for node_id, node_attr in nodes.rename(columns={'longitude': 'x', 'latitude': 'y'}).iterrows():\n graph.add_node(node_id, **node_attr)\n\n for _, way in ways_proj.iterrows():\n\n osm_oneway_values = [\"yes\", \"true\", \"1\", \"-1\", \"T\", \"F\"]\n if \"oneway\" in way and way.oneway in osm_oneway_values:\n if way[\"oneway\"] == \"-1\" or way[\"oneway\"] == \"T\":\n # paths with a one-way value of -1 or T are one-way, but in the\n # reverse direction of the nodes' order, see osm documentation\n path_nodes = list(reversed(way.nodes))\n else:\n path_nodes = way.nodes\n # add this path (in only one direction) to the graph\n one_way = True\n\n elif \"junction\" in way and way.junction == \"roundabout\":\n # roundabout are also oneway but not tagged as is\n path_nodes = way.nodes\n one_way = True\n\n # else, this path is not tagged as one-way or it is a walking network\n # (you can walk both directions on a one-way street)\n else:\n # add this path (in both directions) to the graph and set its\n # 'oneway' attribute to False. if this is a walking network, this\n # may very well be a one-way street (as cars/bikes go), but in a\n # walking-only network it is a bi-directional edge\n path_nodes = way.nodes\n one_way = False\n\n # zip together the path nodes so you get tuples like (0,1), (1,2), (2,3)\n # and so on\n path_edges = list(zip(path_nodes[:-1], path_nodes[1:]))\n graph.add_edges_from(path_edges, **way[['id']])\n if not one_way:\n path_edges_reverse = [(v, u) for u, v in path_edges]\n graph.add_edges_from(path_edges_reverse, **way[['id']])\n\n graph = osmnx.utils_graph.add_edge_lengths(graph)\n return graph","def __init__(self,graph,legal_edges=None,starting_point=(0,0),exits=None):\n\t\tself.graph = graph\n\t\tself.legal_edges = legal_edges\n\t\tself.starting_point = starting_point\n\t\tself.exits = exits","def clear(self):\r\n self.nodes = collections.defaultdict(list)\r\n self.nodes_mapping = collections.defaultdict(list)\r\n self.edges = 0\r\n #self.children_length={}\r\n self.parents_length = collections.defaultdict(lambda : collections.defaultdict(int))","def reset_graph(self):\n self.nodes = {}\n self.add_node(self.initial_state)\n self.add_node(self.final_state)","def relations(self):\n\n def functions_helper(returned_set: set()):\n if is_relation(self.root): # Populate self.root and self.arguments\n returned_set.add((self.root, len(self.arguments)))\n\n elif is_equality(self.root): # Populate self.first and self.second\n return\n elif is_quantifier(self.root): # Populate self.variable and self.predicate\n returned_set.update(self.predicate.relations())\n\n elif is_unary(self.root): # Populate self.first\n returned_set.update(self.first.relations())\n\n else: # Populate self.first and self.second\n returned_set.update(self.first.relations())\n returned_set.update(self.second.relations())\n return\n\n \"\"\" Return a set of pairs (function_name, arity) for all function names\n that appear in this formula \"\"\"\n returned_set = set()\n functions_helper(returned_set)\n return returned_set\n\n # Ex12","def setUp(self):\n self.complete = nx.Graph()\n self.complete.add_edge(1, 2)\n self.complete.add_edge(2, 3)\n self.complete.add_edge(1, 3)\n\n self.small_tree = nx.Graph()\n self.small_tree.add_edge(1, 3)\n self.small_tree.add_edge(4, 3)\n self.small_tree.add_edge(2, 3)\n self.small_tree.add_edge(3, 5)\n self.small_tree.add_edge(5, 6)\n self.small_tree.add_edge(5, 7)\n self.small_tree.add_edge(6, 7)\n\n self.deterministic_graph = nx.Graph()\n self.deterministic_graph.add_edge(0, 1) # deg(0) = 1\n\n self.deterministic_graph.add_edge(1, 2) # deg(1) = 2\n\n self.deterministic_graph.add_edge(2, 3)\n self.deterministic_graph.add_edge(2, 4) # deg(2) = 3\n\n self.deterministic_graph.add_edge(3, 4)\n self.deterministic_graph.add_edge(3, 5)\n self.deterministic_graph.add_edge(3, 6) # deg(3) = 4\n\n self.deterministic_graph.add_edge(4, 5)\n self.deterministic_graph.add_edge(4, 6)\n self.deterministic_graph.add_edge(4, 7) # deg(4) = 5\n\n self.deterministic_graph.add_edge(5, 6)\n self.deterministic_graph.add_edge(5, 7)\n self.deterministic_graph.add_edge(5, 8)\n self.deterministic_graph.add_edge(5, 9) # deg(5) = 6\n\n self.deterministic_graph.add_edge(6, 7)\n self.deterministic_graph.add_edge(6, 8)\n self.deterministic_graph.add_edge(6, 9) # deg(6) = 6\n\n self.deterministic_graph.add_edge(7, 8)\n self.deterministic_graph.add_edge(7, 9) # deg(7) = 5\n\n self.deterministic_graph.add_edge(8, 9) # deg(8) = 4","def rootSetOrder (self):\n order = []\n nodes = set(self.__nodes)\n edge_map = {}\n for (d, srcs) in six.iteritems(self.__edgeMap):\n edge_map[d] = srcs.copy()\n while nodes:\n freeset = set()\n for n in nodes:\n if not (n in edge_map):\n freeset.add(n)\n if 0 == len(freeset):\n _log.error('dependency cycle in named components')\n return None\n order.append(freeset)\n nodes.difference_update(freeset)\n new_edge_map = {}\n for (d, srcs) in six.iteritems(edge_map):\n srcs.difference_update(freeset)\n if 0 != len(srcs):\n new_edge_map[d] = srcs\n edge_map = new_edge_map\n return order","def gen_graph(self):","def build(self):\n self.logger.info('Rebuilding adjacency information')\n self.edges = collections.defaultdict(list)\n\n topic_to_publisher = collections.defaultdict(list)\n topic_to_subscribers = collections.defaultdict(list)\n node_to_missing_deps = collections.defaultdict(list)\n\n result = True\n\n for node in self.nodes.values():\n for topic in node.provided_topics.keys():\n topic_to_publisher[topic].append(node)\n\n for topic in node.required_topics:\n topic_to_subscribers[topic].append(node)\n\n for dep in node.additional_dependencies:\n if dep not in self.nodes:\n node_to_missing_deps[node].append(dep)\n\n if len(node_to_missing_deps) > 0:\n result = False\n msg = io.StringIO()\n print('Found [{}] managed processes with missing dependencies'.format(len(node_to_missing_deps)), file=msg)\n fmt = ' Managed process [{}] is missing [{}]'\n\n for (node, missing) in node_to_missing_deps.items():\n print(fmt.format(node.name, ', '.join(missing)), file=msg)\n self.logger.error(msg.getvalue())\n\n missing_publishers = []\n for topic in topic_to_subscribers.keys():\n if topic not in topic_to_publisher:\n missing_publishers.append(topic)\n\n if len(missing_publishers) > 0:\n result = False\n msg = io.StringIO()\n print('Found [{}] topics that do not have publishers'.format(len(missing_publishers)), file=msg)\n fmt = ' Topic [{}] with subscribers [{}]'\n\n for topic in missing_publishers:\n print(fmt.format(topic, ', '.join([x.name for x in topic_to_subscribers[topic]])), file=msg)\n self.logger.error(msg.getvalue())\n\n if not result:\n self.logger.error('Found errors when building adjacency information')\n raise GraphBuildError(\n 'Found errors when building adjacency information / graph edges. Check log for details')\n\n # Now we have enough information to build our edges. Phase 1: pub/sub stuff\n for (topic, subscribers) in topic_to_subscribers.items():\n publishers = topic_to_publisher[topic]\n\n for p in publishers:\n for s in subscribers:\n self.edges[p].append(s)\n\n # Phase 2: additional dependencies\n for node in self.nodes.values():\n for dep in node.additional_dependencies:\n src = self.nodes[dep]\n self.edges[src].append(node)","def __init__(self):\n self._graph = GenericGraph()\n self._atom_index = {}\n self._next_locant = 1\n self._brutto_formula = ''\n self.modified = True","def initialize_vertices(self, objects_: Union[Dict[str, List[Union[str, int]]], NamedTuple],\n root_name: str, independent: bool, group: int,\n vertices_list: list = None) -> list:\n if vertices_list is None:\n vertices_list = []\n if not isinstance(vertices_list, list):\n raise TypeError(f\"Expected List, got {type(vertices_list)}\")\n\n group_store = {}\n for key, values in objects_.items():\n if key == root_name:\n if type(values) == int or type(values) == str:\n node = Graph_Node(subtype_name=key, value=values,\n independent=True, level=\"root\")\n node.group.add(group)\n group_store[key] = node\n\n # add root nodes to the class node list\n self._add_node(node)\n else:\n raise TypeError(\"Expected value of 'root_name' key to be a str or int\")\n else:\n node = Graph_Node(subtype_name=key, value=values,\n independent=independent)\n node.group.add(group)\n group_store[key] = node\n vertices_list.append(group_store)\n\n return vertices_list","def build_empty_graph(input_dim, output_dim, num_intermediate):\n from .models import DAG\n num_emit, num_rec = num_intermediate + input_dim, num_intermediate + output_dim\n activations = torch.zeros(num_rec, dtype=torch.long)\n connections = torch.zeros(num_rec, num_emit, dtype=torch.long)\n\n return DAG(input_dim, output_dim, num_intermediate, connections, activations, check_valid=True)","def _produce_none_relations(self):\n print \"Producing NONE-relations\"\n relations = self.relations\n events = self.events\n none_relations = []\n\n for source in events:\n for target in events:\n new_relation = Relation(\"NONE\", self.text_obj, source, target, RelationType.NONE)\n print new_relation\n\n if new_relation in relations:\n continue\n else:\n none_relations.append(new_relation)\n\n self.relations = self.relations + none_relations\n\n print \"Finished producing NONE-relations\"","def build_graph(self):\n for node in self.graph.nodes():\n self.c2py[node] = PyNode(node)\n for _input in node.inputs():\n if _input not in self.c2py:\n self.c2py[_input] = PyNode(_input, True)\n if _input in self.forward_edge:\n self.forward_edge[_input].append(node)\n else:\n self.forward_edge[_input] = [node]\n for output in node.outputs():\n if output not in self.c2py:\n self.c2py[output] = PyNode(output, True)\n if node in self.forward_edge:\n self.forward_edge[node].append(output)\n else:\n self.forward_edge[node] = [output]","def load(toks):\r\n graph = nx.Graph()\r\n\r\n for tok in toks:\r\n graph.add_node(tok['id'])\r\n\r\n for tok in toks:\r\n if 'governor' in tok:\r\n governor = tok['governor']\r\n dependant = tok['id']\r\n graph.add_edge(governor, dependant)\r\n return graph","def setUp(self):\n self.G = nx.DiGraph()","def _get_and_create_relation_objects(self, root_node):\n relations = []\n\n for relation in root_node.iterdescendants(\"TLINK\"):\n lid = relation.get(\"lid\")\n\n # Get relation type as a string\n relation_type = relation.get(\"relType\")\n\n # Get relation_type_id\n relation_type_id = RelationType.get_id(relation_type)\n\n if not relation.get(\"timeID\") and not relation.get(\"relatedToTime\"):\n # This is event-event\n source_eiid = relation.get(\"eventInstanceID\")\n target_eiid = relation.get(\"relatedToEventInstance\")\n\n # Find source event\n source_obj = self.find_event_by_eiid(self.events, source_eiid)\n # Find target event\n target_obj = self.find_event_by_eiid(self.events, target_eiid)\n\n else:\n # This must be event-timex or timex-event or timex-timex\n target_tid = relation.get(\"relatedToTime\")\n target_eiid = relation.get(\"relatedToEventInstance\")\n\n source_tid = relation.get(\"timeID\")\n source_eiid = relation.get(\"eventInstanceID\")\n\n\n if source_tid and target_eiid:\n # timex-event\n source_obj = self.find_timex_by_tid(source_tid)\n target_obj = self.find_event_by_eiid(self.events, target_eiid)\n elif source_eiid and target_tid:\n # event-timex\n source_obj = self.find_event_by_eiid(self.events, source_eiid)\n target_obj = self.find_timex_by_tid(target_tid)\n elif source_tid and target_tid:\n # timex-timex\n source_obj = self.find_timex_by_tid(source_tid)\n target_obj = self.find_timex_by_tid(target_tid)\n\n relation_obj = Relation(lid, self.text_obj, source_obj, target_obj, relation_type_id)\n\n # So we don't run into problems with helper.output\n if relation_obj.is_timex_timex(): relation_obj.predicted_class = relation_type_id\n\n # There are sometimes duplicates which we do not want to have\n if relation_obj not in relations:\n relations.append(relation_obj)\n\n return relations","def make_set(node):\n node.parent = node\n node.rank = 0","def __init__(self, edges=None, directed=False):\n self._graph = defaultdict(dict)\n self._directed = directed\n if edges:\n self.add_edges(edges)","def graph(self):\n graph = nx.DiGraph()\n for name, joint in self.joints.items():\n graph.add_edge(*joint.connects, joint=name)\n return graph","def __init__(self, name=None):\n self.id = id # Unique identifier for the set\n self._next_id = 0 # Holds unique ids for graphs\n self._graphs = {} # Holds graphs, keyed by unique id\n self.name = name # Holds description of graph","def __init__(self, root):\n self._root = root\n self._leaves = [root]","def __init__(self, nodes=[], edges=[], connections=[], directed=False, isNetwork=False):\n Node.count=0\n Edge.count=0\n self.nodes = [n for n in nodes]\n self.edges = [e for e in edges]\n self.connections = [(a, b) for (a, b) in connections]\n self.isDirected = directed\n self.isNetwork = isNetwork","def ResetGraph(self):\n self.nodes = []\n self.edges = []\n self.connections = []\n Node.resetNodeCount()\n Edge.resetEdgesCount()","def __create_graph(self):\n # create the nodes\n for h in range(self.height):\n row: List[JuncNode] = list()\n for w in range(self.width):\n jnodes: List[Node] = [self.add_node() for _ in range(4)]\n jn = JuncNode(jnodes, (h, w))\n row.append(jn)\n self.__juncs.append(row)\n # create all connections\n self.__create_connections()","def relations_to(self, end_node):","def build(self, graph):\n self.results = None\n\n self.graph = graph\n\n self.__build_nodes()\n self.__build_edges()"],"string":"[\n \"def initialize_graph(compound_relations, relation_types):\\n graph = nx.DiGraph()\\n for compound, targets in compound_relations.items():\\n for target, relation in targets.items():\\n if relation in relation_types:\\n graph.add_edge(compound, target)\\n return graph\",\n \"def populate_graph(self):\\n if self.edges and self.vertices:\\n graph = Graph()\\n for edge in self.edges:\\n graph.add_edge(edge)\\n self.graph = graph\\n else:\\n print(\\\"Populate edges & vertices first, then populate graph!\\\")\",\n \"def complete_graph(self):\\n root_nodes = set()\\n\\n for name, a_block in self.wf['action'].items():\\n\\n a_block['name'] = name\\n\\n for n in a_block.get('needs', []):\\n if not self.wf['action'][n].get('next', None):\\n self.wf['action'][n]['next'] = set()\\n self.wf['action'][n]['next'].add(name)\\n\\n if not a_block.get('needs', None):\\n root_nodes.add(name)\\n\\n self.wf['root'] = root_nodes\",\n \"def populate_graph(self):\",\n \"def _setup_graph(self):\\n pass\",\n \"def _setup_graph(self):\\n pass\",\n \"def legalize_graph(gm: pippy.fx.GraphModule) -> pippy.fx.GraphModule:\\n indeg = {node: 0 for node in gm.graph.nodes}\\n new_graph = pippy.fx.Graph()\\n # Track how many unfulfilled dependencies each node has\\n for node in gm.graph.nodes:\\n for user in node.users:\\n indeg[user] += 1\\n queue: collections.deque = collections.deque()\\n # Add all nodes with no dependencies to the queue\\n for node in gm.graph.nodes:\\n if indeg[node] == 0:\\n queue.append(node)\\n env: Dict[pippy.fx.Node, pippy.fx.Node] = {}\\n # Pop nodes from the queue, and add nodes that have had all their\\n # dependencies fulfilled\\n while len(queue) > 0:\\n cur = queue.popleft()\\n env[cur] = new_graph.node_copy(cur, lambda x: env[x])\\n for user in cur.users:\\n indeg[user] -= 1\\n if indeg[user] == 0:\\n queue.append(user)\\n # If the new graph's size is not as large as the old one, then there must be\\n # a cycle (i.e. some node's dependencies were not satisfied.)\\n if len(new_graph.nodes) < len(gm.graph.nodes):\\n raise RuntimeError(f\\\"Input graph has cycles, unable to add {[node for node in indeg if indeg[node] != 0]}\\\")\\n gm.graph = new_graph\\n return gm\",\n \"def _init_graph(self):\\n self.G = nx.Graph()\\n self.G.add_nodes_from([1,2,3,4,5])\\n self.G.add_edges_from([(1,2),(2,3),(2,4)\\\\\\n ,(2,5),(3,4),(4,5)])\",\n \"def _build_graph(self):\\n pass\",\n \"def initialize_connection(self, branch_iterable: Iterable, root_iterable: Iterable) -> None:\\n for root in root_iterable:\\n for branch in branch_iterable:\\n if root.group.intersection(branch.group):\\n self._add_graph_edges(root, branch)\\n return\",\n \"def __init__(self, root):\\r\\n self.root = root\\r\\n self.nodes = [root]\\r\\n self.nodes.extend(Node.all_descendants(self.root))\\r\\n self.node_ids = [ n.id for n in self.nodes ]\",\n \"def build_graph(self):\\n pass\",\n \"def __init__(self, vertices=[], edges=[]):\\n for vertex in vertices:\\n self.add_vertex(vertex)\\n for edge in edges:\\n self.add_edge(edge)\",\n \"def __init__(self, nodes):\\n\\t\\t\\n\\t\\tself.variables = dict([(n.name, n) for n in nodes])\\n\\t\\tself.roots = [n for n in nodes if not n.parents]\\n\\t\\tself.nodes = nodes\",\n \"def initGraphs(self):\\n \\n self.graph = ConjunctiveGraph()\\n # Create a separate graph for annotations\\n self.annotationGraph = ConjunctiveGraph()\\n \\n self.log.debug('Adding namespaces to graphs')\\n # Bind namespaces to graphs\\n for namespace in self.namespaces:\\n self.graph.namespace_manager.bind(namespace, self.namespaces[namespace])\\n\\n # Same for annotation graph\\n for namespace in self.annotationNamespaces:\\n self.annotationGraph.namespace_manager.bind(namespace, self.annotationNamespaces[namespace])\\n \\n # Add schema information\\n self.log.debug('Adding some schema information (dimension and measure properties) ')\\n self.addDataCellProperty()\\n\\n # Add dimensions \\n self.graph.add((self.namespaces['tablink']['dimension'], RDF.type, self.namespaces['qb']['DimensionProperty']))\\n \\n #self.graph.add((self.namespaces['tablink']['label'], RDF.type, RDF['Property']))\",\n \"def _build_dependency_graph(self):\\n\\n #\\n # Find the binary roles\\n #\\n nodes, roles = self._find_roles()\\n\\n #\\n # Build the graph\\n #\\n working_list = list(set(nodes.keys()))\\n\\n setters = [b for b, r in roles.items() if Role.SETTER in r or Role.SETTER_GETTER in r]\\n\\n while working_list:\\n b = working_list[0]\\n working_list = working_list[1:]\\n\\n if nodes[b] not in self._graph:\\n self._graph[nodes[b]] = []\\n\\n # it's a root node\\n if Role.GETTER not in roles[b] and Role.SETTER_GETTER not in roles[b]:\\n nodes[b].set_root()\\n\\n # takes params from some other binary\\n else:\\n is_orphan = True\\n for setter in setters:\\n setter_strings_set = set(nodes[setter].role_strings)\\n node_strings_set = set(nodes[b].role_strings)\\n if setter_strings_set.intersection(node_strings_set):\\n if nodes[setter] not in self._graph:\\n self._graph[nodes[setter]] = []\\n self._graph[nodes[setter]].append(nodes[b])\\n is_orphan = False\\n\\n # mark orphans\\n if is_orphan:\\n nodes[b].set_orphan()\\n\\n # Clean up\\n for k, childs in self._graph.iteritems():\\n self._graph[k] = list(set(childs))\\n\\n # set leaves\\n for k, c in self._graph.iteritems():\\n if not c:\\n k.set_leaf()\\n\\n # post processing:\\n # remove those nodes that are not orphans\\n # and are not network parsers\\n\\n nodes = self.nodes\\n children = [c for x in self._graph.values() for c in x if x]\\n leafs_non_orphan = [n for n in nodes if n.leaf and not n.orphan]\\n seed_names = [x.split('/')[-1] for x in self._seed_bins]\\n spurious_nodes = [n for n in leafs_non_orphan if n not in children and n.bin.split('/')[-1] not in seed_names]\\n for to_rem in spurious_nodes:\\n del self._graph[to_rem]\",\n \"def create_initial_graph(self):\\n # Initialise weights\\n for link in self.gene_links:\\n link.weight = random.uniform(weight_init_min, weight_init_max)\\n # Initialise biases\\n for node in self.gene_nodes:\\n node.bias = random.uniform(bias_init_min, bias_init_max)\\n if node.can_modify:\\n node.act_func = self.act_set.get_random_activation_func()\\n if node.act_func in [activations.gaussian, activations.sin]:\\n if node.act_func.__name__[0] == \\\"g\\\":\\n node.freq += random.uniform(-guass_freq_adjust, guass_freq_adjust)\\n elif node.act_func.__name__[0] == \\\"s\\\":\\n node.freq += random.uniform(-sin_freq_adjust, sin_freq_adjust)\\n node.amp += random.uniform(-func_amp_adjust, func_amp_adjust)\\n node.vshift += random.uniform(-func_vshift_adjust, func_vshift_adjust)\",\n \"def _setup_graph_def(self):\\n raise NotImplementedError\",\n \"def setUp(self):\\n self.complete = nx.Graph()\\n self.complete.add_edge(1, 2)\\n self.complete.add_edge(2, 3)\\n self.complete.add_edge(1, 3)\\n\\n self.small_tree = nx.Graph()\\n self.small_tree.add_edge(1, 2)\\n self.small_tree.add_edge(2, 3)\\n self.small_tree.add_edge(3, 4)\\n self.small_tree.add_edge(1, 4)\\n self.small_tree.add_edge(2, 4)\\n self.small_tree.add_edge(4, 5)\\n self.small_tree.add_edge(5, 6)\\n self.small_tree.add_edge(5, 7)\\n self.small_tree.add_edge(6, 7)\\n\\n self.deterministic_graph = nx.Graph()\\n self.deterministic_graph.add_edge(1, 2)\\n self.deterministic_graph.add_edge(1, 3)\\n self.deterministic_graph.add_edge(3, 4)\\n self.deterministic_graph.add_edge(2, 4)\\n self.deterministic_graph.add_edge(3, 5)\\n self.deterministic_graph.add_edge(4, 5)\\n self.deterministic_graph.add_edge(3, 6)\\n self.deterministic_graph.add_edge(5, 6)\",\n \"def __init__(self, nodeset):\\n self.nodeset = nodeset # initialize all necessary fields\\n\\n self.__check_validity() # check if graph is valid - throws exception if not\",\n \"def __init__(self):\\n\\n self.nodes = set()\",\n \"def __init__(self, directed=True):\\n self.nodes = set()\\n self.edges = []\\n self.directed = directed\",\n \"def build_graph(self, objects_: Union[Dict[str, List[Union[str, dict, int]]], NamedTuple],\\n root_name: str, *branch_names: str) -> list:\\n\\n all_nodes = []\\n for key, value in objects_.items():\\n for index, items in enumerate(value):\\n if isinstance(items, dict):\\n vertices = self.initialize_vertices(objects_=items,\\n root_name=root_name,\\n independent=False,\\n group=index)\\n all_nodes.extend(vertices)\\n continue\\n\\n root = set()\\n\\n for vertex in all_nodes:\\n if vertex[root_name]:\\n root.add(vertex[root_name])\\n\\n for branch in branch_names:\\n if not isinstance(branch, str):\\n raise TypeError(f\\\"Expected a string, got {type(branch)}\\\")\\n\\n try:\\n if vertex[branch]:\\n branches = self.locate_graph_link(vertex_list=all_nodes,\\n branch_name=branch)\\n except KeyError:\\n continue\\n\\n share = self.initialize_connection(branch_iterable=branches, root_iterable=root)\\n\\n return self.find_nodes_subtype(root_name)\",\n \"def _construct_graph(self):\\n raise NotImplementedError\",\n \"def setgraphs(self, graphs):\\n\\n self.__graphs = graphs\\n # Create table_graph objects\\n rgraph = re.compile(r\\\":([^:]+):([^:]+):([^:]+):\\\")\\n for graph in rgraph.findall(graphs):\\n new_graph = self.addgraph(graph[0])\\n new_graph.setscaling(graph[1])\\n new_graph.setcolumns(graph[2])\\n self.__nonzero = True\",\n \"def init_graph(self):\\n import dgl\\n\\n adj_list = []\\n for rel_type in range(1, self.n_relations, 1):\\n edge_idxs = self.ckg.filter_edges(\\n lambda edge: edge.data[\\\"relation_id\\\"] == rel_type\\n )\\n sub_graph = (\\n dgl.edge_subgraph(self.ckg, edge_idxs, preserve_nodes=True)\\n .adjacency_matrix(transpose=False, scipy_fmt=\\\"coo\\\")\\n .astype(\\\"float\\\")\\n )\\n rowsum = np.array(sub_graph.sum(1))\\n d_inv = np.power(rowsum, -1).flatten()\\n d_inv[np.isinf(d_inv)] = 0.0\\n d_mat_inv = sp.diags(d_inv)\\n norm_adj = d_mat_inv.dot(sub_graph).tocoo()\\n adj_list.append(norm_adj)\\n\\n final_adj_matrix = sum(adj_list).tocoo()\\n indices = torch.LongTensor([final_adj_matrix.row, final_adj_matrix.col])\\n values = torch.FloatTensor(final_adj_matrix.data)\\n adj_matrix_tensor = torch.sparse.FloatTensor(indices, values, self.matrix_size)\\n return adj_matrix_tensor.to(self.device)\",\n \"def __init__(self):\\n self.graph = {}\\n self.edges = 0\\n self.vertices = 0\",\n \"def build_graph(self):\\n self.import_tree(ZOO_PATH, self.import_zoo, self.verify_zoos)\\n self.import_tree(WILD_PATH, self.import_wild, self.verify_wilds)\\n self.import_tree(PANDA_PATH, self.import_redpanda, self.verify_pandas)\\n self.import_tree(MEDIA_PATH, self.import_media, self.verify_media)\",\n \"def isValidCompatible(cls,root):\\n valid = True\\n # the order of node types in chains is restricted\\n # (this would be easier if the data was in a Corpus-instance)\\n allowed = NX.XDiGraph(selfloops=True)\\n\\n # continue from here!\\n allowed.add_edge('Physical','Physical')\\n allowed.add_edge('Property','Physical')\\n allowed.add_edge('Process','Physical')\\n allowed.add_edge('Regulation','Physical')\\n\\n allowed.add_edge('Property','Property')\\n allowed.add_edge('Process','Property')\\n allowed.add_edge('Regulation','Property')\\n\\n allowed.add_edge('Property','Process')\\n# allowed.add_edge('Process','Process')\\n allowed.add_edge('Regulation','Process')\\n\\n allowed.add_edge('Property','Regulation')\\n# allowed.add_edge('Process','Regulation')\\n allowed.add_edge('Regulation','Regulation')\\n\\n mapping = {}\\n for a in root.find(\\\"ontologies\\\").findall(\\\"ontology\\\"):\\n if a.attrib['id']=='interaction':\\n for x in a.getiterator(\\\"ontnode\\\"):\\n if x.attrib.has_key('effect') and x.attrib['effect'].endswith('regulation'):\\n t = 'Regulation'\\n else:\\n t = x.attrib['onttype']\\n mapping[x.attrib['id']] = t\\n \\n for a in root.getiterator(\\\"relannotation\\\"):\\n t2type = dict( [(x.attrib['id'],x.attrib['type'])\\n for x in a.findall(\\\"reltoken\\\")] )\\n n2t = dict( [(x.attrib['id'],x.attrib['token'])\\n for x in a.findall(\\\"relnode\\\")] )\\n for x in a.findall(\\\"reledge\\\"):\\n bt = t2type[n2t[x.attrib['bgn']]]\\n et = t2type[n2t[x.attrib['end']]]\\n bgn = mapping[bt]\\n end = mapping[et]\\n if not allowed.has_edge(bgn,end):\\n printError(cls,inspect.stack()[1][3],\\n \\\"%s -- %s (%s) -> %s (%s) is not a valid edge\\\"%\\n (x.attrib['id'].split('.')[1],bgn,bt,end,et))\\n valid = False\\n \\n return(valid)\",\n \"def build_graph(self):\\n raise NotImplementedError\",\n \"def __init__(self):\\n self.graph = None\",\n \"def __init__(self, edges=None, nodes=None, graph=None):\\n self.edges = edges\\n self.nodes = nodes\\n self.graph = graph\",\n \"def init_vertices(self):\\n self.vertices = []\\n for key in self.graph:\\n self.vertices.append(self.Vertex(key, self.graph[key]))\",\n \"def make_complete_graph(num_nodes):\\n xgraph = {} #Create a Blank Dict\\n if num_nodes - 1 < 0: # checks to see if the num_nodes is less then 0 (negative number) if it is return empty graph (dict). Could probably combine the If statments for negative nodes and 1 node together\\n return xgraph\\n if num_nodes - 1 == 0: # If the number of nodes is 1 or returns a one node dict because there are no edges to compute\\n xgraph[0] = set([]) # creates a dict that represents a single node graph as per the requirement\\n return xgraph # the empty Graph\\n else:\\n for base_node in range(num_nodes): # This portion starts the build phase. for each node it will compute the theretical maximum amount of edges\\n xlist = set([]) # defines an empty list. We first build a list for each node and the append to a dict. This list is erased with each iteration\\n #print base_node # testing - REMOVE\\n for edge_node in range(num_nodes):\\n #print edge_node # testing - REMOVE\\n if edge_node != base_node: #No Looping is allowed for this project. Therefor we check to insure the we are not counting a self node connection (edge_node NOT equal base_node)\\n xlist.add(edge_node) # Populating list that will be added to dict\\n\\n xgraph[base_node] = xlist # Appending created list to the dict\\n\\n return xgraph # returning populated dict\",\n \"def make_complete_graph(num_nodes):\\n xgraph = {} #Create a Blank Dict\\n if num_nodes - 1 < 0: # checks to see if the num_nodes is less then 0 (negative number) if it is return empty graph (dict). Could probably combine the If statments for negative nodes and 1 node together\\n return xgraph\\n if num_nodes - 1 == 0: # If the number of nodes is 1 or returns a one node dict because there are no edges to compute\\n xgraph[0] = set([]) # creates a dict that represents a single node graph as per the requirement\\n return xgraph # the empty Graph\\n else:\\n for base_node in range(num_nodes): # This portion starts the build phase. for each node it will compute the theretical maximum amount of edges\\n xlist = set([]) # defines an empty list. We first build a list for each node and the append to a dict. This list is erased with each iteration\\n #print base_node # testing - REMOVE\\n for edge_node in range(num_nodes):\\n #print edge_node # testing - REMOVE\\n if edge_node != base_node: #No Looping is allowed for this project. Therefor we check to insure the we are not counting a self node connection (edge_node NOT equal base_node)\\n xlist.add(edge_node) # Populating list that will be added to dict\\n\\n xgraph[base_node] = xlist # Appending created list to the dict\\n\\n return xgraph # returning populated dict\",\n \"def build_graph(self):\\n for each_list in self.lab.look():\\n vertice = self._add_vertice(each_list)\\n if vertice:\\n self.unvisited.add(vertice)\\n self.graph.addEdge((self.current, vertice))\\n \\n self.unvisited -= self.visited\\n self._connect_neighbours()\",\n \"def direct_network(self):\\n #print list(self.get_subgraphs())\\n graphs = [self._depth_first_directed(g) for g in self.get_subgraphs()]\\n self._network = reduce(lambda a, b: nx.union(a, b), graphs)\",\n \"def _internal_build(self):\\n self.nodes = self.__tree.Nodes()\\n self.edges = self.__tree.Edges()\\n self.augmentedEdges = {}\\n for key, val in self.__tree.AugmentedEdges().items():\\n self.augmentedEdges[key] = list(val)\\n self.root = self.__tree.Root()\\n\\n seen = set()\\n self.branches = set()\\n\\n # Find all of the branching nodes in the tree, degree > 1\\n # That is, they appear in more than one edge\\n for e1, e2 in self.edges:\\n if e1 not in seen:\\n seen.add(e1)\\n else:\\n self.branches.add(e1)\\n\\n if e2 not in seen:\\n seen.add(e2)\\n else:\\n self.branches.add(e2)\\n\\n # The nodes that are not branches are leaves\\n self.leaves = set(self.nodes.keys()) - self.branches\\n self.leaves.remove(self.root)\",\n \"def __init__(self):\\n self._graph = DirectedGraph()\\n self._graph_copies = []\",\n \"def _get_full_graph(self):\",\n \"def set_root(self, root):\\n self.root = root\\n self.sites = [root]\",\n \"def reset_graph(self):\\n self.graph = OrderedDict()\",\n \"def graphing_setup(self):\\n pass\",\n \"def _CreateGraph(self):\\n self.nodes = []\\n self.edges = []\\n for i, r in self.airports.set_index('airport_id').iterrows():\\n self.nodes.append((i,r.to_dict()))\\n for i, r in self.routes.set_index(['src_id','dst_id']).iterrows():\\n self.edges.append((i[0],i[1],r.to_dict()))\\n # print('node ex: {}'.format(self.nodes[0]))\\n # print('edge ex: {}'.format(self.edges[0]))\\n\\n self.graph = self._CreateAdjacencyListGraph()\",\n \"def __initilization(self,node_set):\\n \\n print \\\"*********************************\\\"\\n \\n for x in node_set:\\n x.node_vol=np.transpose(np.matrix([cmath.exp(0), cmath.exp(complex(0,math.pi*2/3)), cmath.exp(complex(0,-math.pi*2/3))]))\\n \\n print \\\"Forward/Backward Algorithm Initialization Done!\\\"\",\n \"def __init__(self, start_edges=None):\\n self.adj_list = dict()\\n\\n # populate graph with initial vertices and edges (if provided)\\n # before using, implement add_vertex() and add_edge() methods\\n if start_edges is not None:\\n for u, v in start_edges:\\n self.add_edge(u, v)\",\n \"def _build_graph_general(self): \\n\\n #Find a canonical coloring scheme\\n #Each node has a color that is determined by the non-mapped aspects\\n nodecolors=set()\\n for nl in self.net.iter_node_layers():\\n nodecolors.add(self._slice_node_layer_not_allowed(nl))\\n nodecolors_sorted=sorted(list(nodecolors))\\n del nodecolors\\n self._assert_full_order(nodecolors_sorted)\\n self.colormap=dict( ((color,colorid) for colorid,color in enumerate(nodecolors_sorted) ))\\n\\n #each aux node has a color that is determined by the aspect\\n self.auxcolormap=dict( ((auxcolor, auxcolorid+len(self.colormap)) for auxcolorid,auxcolor in enumerate(sorted(self.asp)) ) )\\n\\n\\n #Add the underlying network\\n #node-layers:\\n for nl in self.net.iter_node_layers():\\n nlid=self._get_node_id(nl)\\n color=self._slice_node_layer_not_allowed(nl)\\n colorid=self.colormap[color]\\n self.add_node(nlid,colorid)\\n\\n #edges between node-layers:\\n for nl1 in self.net.iter_node_layers():\\n for nl2 in self.net[nl1]:\\n nl1id=self._get_node_id(nl1)\\n nl2id=self._get_node_id(nl2)\\n self.add_link(nl1id,nl2id)\\n\\n\\n #Add the auxiliary nodes and edges\\n #add the aux nodes\\n for a in self.asp:\\n for elayer in self.net.slices[a]:\\n auxid=self._get_auxnode_id( (a,elayer) )\\n auxcolorid=self.auxcolormap[a]\\n self.add_node(auxid,auxcolorid)\\n \\n #add the aux edges\\n for nl in self.net.iter_node_layers():\\n for a in self.asp:\\n nlid=self._get_node_id(nl)\\n auxid=self._get_auxnode_id( (a,nl[a]) )\\n self.add_link(nlid,auxid)\",\n \"def graph_root_setter(server, graph):\\n if graph:\\n if isinstance(graph, dict):\\n kind = graph.get(\\\"kind\\\")\\n elif hasattr(graph, \\\"kind\\\"):\\n kind = graph.kind\\n else:\\n raise MLRunInvalidArgumentError(\\\"graph must be a dict or a valid object\\\")\\n if kind == StepKinds.router:\\n server._graph = server._verify_dict(graph, \\\"graph\\\", RouterStep)\\n elif not kind or kind == StepKinds.root:\\n server._graph = server._verify_dict(graph, \\\"graph\\\", RootFlowStep)\\n else:\\n raise GraphError(f\\\"illegal root step {kind}\\\")\",\n \"def __init__(self, prefix, downstream, upstream, root):\\n super(SubGraph, self).__init__(prefix, downstream, upstream, root)\",\n \"def initialize_graph(self, V, edge_list):\\n # ---------- INSERT CODE BELOW ----------\\n for _ in range(V):\\n self.add_vertex()\\n \\n for node in edge_list:\\n self.add_edge(node[0],node[1],node[2])\\n\\n # ---------- INSERT CODE ABOVE ----------\",\n \"def sub_graph_merging(self):\",\n \"def __init__(self):\\n self.data_graph = self._initialise_data()\\n\\n self.messages_sent = []\\n self.messages_received = []\\n\\n self.answered_true = set()\\n self.implied_true = set()\\n\\n self.current_subgraph = set()\",\n \"def _initilise_graph_db(self):\\n for collector in self.collectors:\\n collector.init_graph_db()\",\n \"def __init__(self):\\n\\t\\tself.edges = defaultdict(list)\\n\\t\\tself.weights = {}\\n\\t\\tself.connections = {}\",\n \"def buildGraph(self):\\n return None\",\n \"def _generate_vertexes(self):\\n # generate list of sets for each vms\\n self._graph = [set() for _ in range(self._vm_count)]\",\n \"def build_3_node_line_root_articulation_graph(directed=False):\\n if directed:\\n graph = DirectedGraph()\\n else:\\n graph = UndirectedGraph()\\n\\n graph.new_node()\\n graph.new_node()\\n graph.new_node()\\n\\n graph.new_edge(1, 2)\\n graph.new_edge(1, 3)\\n\\n return graph\",\n \"def __init__(self, graph=None):\\n\\n self.graph = graph if graph else nx.Graph()\",\n \"def _create_graph(self, pools: List[Pool]):\\n for pool in pools:\\n self._add_nodes(pool.tokens)\\n\\n for pool in pools: # noqa: WPS440,WPS441\\n self._add_edges(pool) # noqa: WPS441\",\n \"def __init__(self, subnodes, optionals=None):\\n self.subnodes = subnodes\\n self.optionals = optionals or []\",\n \"def __init__(self, nodes=None, edges=None):\\n self._nodes = []\\n self.nodes = nodes\\n self._edges = []\\n self.edges = edges\\n self._create_connections()\\n self._sorted_nodes = None\\n self._node_wip = []\",\n \"def multi_edge():\\n from networkx.readwrite import json_graph\\n import networkx as nx\\n import autonetkit\\n # returns a house graph\\n data = {'directed': False,\\n 'graph': [],\\n 'links': [{'_ports': {'r4': 2, 'r5': 1},\\n 'raw_interfaces': {},\\n 'source': 0,\\n 'target': 1},\\n {'_ports': {'r2': 3, 'r4': 1},\\n 'raw_interfaces': {},\\n 'source': 0,\\n 'target': 3},\\n {'_ports': {'r2': 4, 'r4': 3},\\n 'raw_interfaces': {},\\n 'source': 0,\\n 'target': 3},\\n {'_ports': {'r3': 3, 'r5': 2},\\n 'raw_interfaces': {},\\n 'source': 1,\\n 'target': 4},\\n {'_ports': {'r1': 1, 'r2': 1},\\n 'raw_interfaces': {},\\n 'source': 2,\\n 'target': 3},\\n {'_ports': {'r1': 3, 'r2': 5},\\n 'raw_interfaces': {},\\n 'source': 2,\\n 'target': 3},\\n {'_ports': {'r1': 2, 'r3': 1},\\n 'raw_interfaces': {},\\n 'source': 2,\\n 'target': 4},\\n {'_ports': {'r1': 4, 'r3': 4},\\n 'raw_interfaces': {},\\n 'source': 2,\\n 'target': 4},\\n {'_ports': {'r1': 5, 'r3': 5},\\n 'raw_interfaces': {},\\n 'source': 2,\\n 'target': 4},\\n {'_ports': {'r2': 2, 'r3': 2},\\n 'raw_interfaces': {},\\n 'source': 3,\\n 'target': 4}],\\n 'multigraph': True,\\n 'nodes': [{'_ports': {0: {'category': 'physical', 'description': None},\\n 1: {'category': 'physical', 'description': 'r4 to r2', 'id': 'eth0'},\\n 2: {'category': 'physical', 'description': 'r4 to r5', 'id': 'eth1'},\\n 3: {'category': 'physical', 'description': 'r4 to r2', 'id': 'eth2'}},\\n 'asn': 2,\\n 'device_type': 'router',\\n 'id': 'r4',\\n 'label': 'r4',\\n 'x': 675,\\n 'y': 300},\\n {'_ports': {0: {'category': 'physical', 'description': None},\\n 1: {'category': 'physical', 'description': 'r5 to r4', 'id': 'eth0'},\\n 2: {'category': 'physical', 'description': 'r5 to r3', 'id': 'eth1'}},\\n 'asn': 2,\\n 'device_type': 'router',\\n 'id': 'r5',\\n 'label': 'r5',\\n 'x': 675,\\n 'y': 500},\\n {'_ports': {0: {'category': 'physical', 'description': None},\\n 1: {'category': 'physical', 'description': 'r1 to r2', 'id': 'eth0'},\\n 2: {'category': 'physical', 'description': 'r1 to r3', 'id': 'eth1'},\\n 3: {'category': 'physical', 'description': 'r1 to r2', 'id': 'eth2'},\\n 4: {'category': 'physical', 'description': 'r1 to r3', 'id': 'eth3'},\\n 5: {'category': 'physical', 'description': 'r1 to r3', 'id': 'eth4'}},\\n 'asn': 1,\\n 'device_type': 'router',\\n 'id': 'r1',\\n 'label': 'r1',\\n 'x': 350,\\n 'y': 400},\\n {'_ports': {0: {'category': 'physical', 'description': None},\\n 1: {'category': 'physical', 'description': 'r2 to r1', 'id': 'eth0'},\\n 2: {'category': 'physical', 'description': 'r2 to r3', 'id': 'eth1'},\\n 3: {'category': 'physical', 'description': 'r2 to r4', 'id': 'eth2'},\\n 4: {'category': 'physical', 'description': 'r2 to r4', 'id': 'eth3'},\\n 5: {'category': 'physical', 'description': 'r2 to r1', 'id': 'eth4'}},\\n 'asn': 1,\\n 'device_type': 'router',\\n 'id': 'r2',\\n 'label': 'r2',\\n 'x': 500,\\n 'y': 300},\\n {'_ports': {0: {'category': 'physical', 'description': None},\\n 1: {'category': 'physical', 'description': 'r3 to r1', 'id': 'eth0'},\\n 2: {'category': 'physical', 'description': 'r3 to r2', 'id': 'eth1'},\\n 3: {'category': 'physical', 'description': 'r3 to r5', 'id': 'eth2'},\\n 4: {'category': 'physical', 'description': 'r3 to r1', 'id': 'eth3'},\\n 5: {'category': 'physical', 'description': 'r3 to r1', 'id': 'eth4'}},\\n 'asn': 1,\\n 'device_type': 'router',\\n 'id': 'r3',\\n 'label': 'r3',\\n 'x': 500,\\n 'y': 500}]}\\n graph = json_graph.node_link_graph(data)\\n anm = autonetkit.anm.NetworkModel()\\n g_in = anm.add_overlay(\\\"input\\\")\\n g_in._replace_graph(nx.MultiGraph(graph))\\n # TODO: check if should build overlays here rather than clone in?\\n g_phy = anm[\\\"phy\\\"]\\n g_phy._replace_graph(graph)\\n return anm\",\n \"def connect_all(graph, nodeset):\\n for element in nodeset:\\n graph.add_node(element)\\n for element1 in nodeset:\\n for element2 in nodeset:\\n if not element1 == element2:\\n graph.add_edge(element1, element2)\\n return graph\",\n \"def _build_graphs(self):\\n g1 = self._build_graph1()\\n g2 = self._build_graph2(g1)\\n return g1, g2\",\n \"def __init__(self, nodes=None, connections=None):\\r\\n\\r\\n super(Graph, self).__init__()\\r\\n self.nodes = OrderedDict()\\r\\n self.connections = set()\\r\\n\\r\\n self.logger = get_logger()\\r\\n\\r\\n self._name_sequence = 1\\r\\n\\r\\n if nodes:\\r\\n try:\\r\\n for name, node in nodes.items():\\r\\n self.add(node, name)\\r\\n except:\\r\\n raise ValueError(\\\"Nodes should be a dictionary, is %s\\\" % type(nodes))\\r\\n\\r\\n if connections:\\r\\n for connection in connections:\\r\\n self.connect(connection[0], connection[1])\",\n \"def build_graph(self):\\n self._reset_iterator_memory()\\n self._construct_graph_handler()\\n assert self.graph_handler\\n for rxn_id in self.graph_handler.get_valid_reaction_ids():\\n rxn = db.Reaction(rxn_id, self._reactions)\\n self.graph_handler.add_rxn(rxn)\",\n \"def create_graph(self,root_path):\\n graph = self.graph\\n\\n #get the path lists recursively from the root directory \\n path_list = sorted(Path(root_path).rglob('*'))\\n # create the necessary amount of vertices \\n graph.add_vertices(len(path_list)+1)\\n \\n # these list will be used for inserting to sqlite database\\n vertices = []\\n edges = []\\n\\n # now the edges have to be created, and the vertices need the file informations\\n # first is the root vertex\\n temp=graph.vs[0]\\n temp[\\\"name\\\"]=root_path\\n temp[\\\"parent\\\"]=\\\"\\\"\\n temp[\\\"size\\\"]=os.stat(root_path).st_size\\n temp[\\\"last_modified\\\"]=os.stat(root_path).st_mtime\\n temp[\\\"last_accessed\\\"]=os.stat(root_path).st_atime\\n \\n vertices.append((0,temp[\\\"name\\\"],temp[\\\"parent\\\"],temp[\\\"size\\\"],temp[\\\"last_modified\\\"],temp[\\\"last_accessed\\\"]))\\n\\n # walking through the paths, the vertices get the informations, and the egdes will be created\\n for i, file in enumerate(path_list):\\n temp=graph.vs[i+1]\\n temp[\\\"name\\\"]=file.as_posix()\\n temp[\\\"parent\\\"]=file.parent.as_posix()\\n temp[\\\"size\\\"]=os.stat(file).st_size\\n temp[\\\"last_modified\\\"]=os.stat(file).st_mtime\\n temp[\\\"last_accessed\\\"]=os.stat(file).st_atime\\n vertices.append((temp.index,temp[\\\"name\\\"],temp[\\\"parent\\\"],temp[\\\"size\\\"],temp[\\\"last_modified\\\"],temp[\\\"last_accessed\\\"]))\\n \\n parent_id=graph.vs.find(name=temp[\\\"parent\\\"]).index\\n # Egde is defined beetween the current vertex and its parent\\n graph.add_edges([(i+1,parent_id)])\\n edges.append((i+1,parent_id))\\n\\n # save the created Graph object into the connected redis database as JSON\\n cache= get_redis()\\n cache.execute_command('JSON.SET', 'vertices_name','.',json.dumps(self.graph.vs[\\\"name\\\"]))\\n cache.execute_command('JSON.SET', 'vertices_parent','.',json.dumps(self.graph.vs[\\\"parent\\\"]))\\n cache.execute_command('JSON.SET', 'vertices_size','.',json.dumps(self.graph.vs[\\\"size\\\"]))\\n cache.execute_command('JSON.SET', 'vertices_last_modified','.',json.dumps(self.graph.vs[\\\"last_modified\\\"]))\\n cache.execute_command('JSON.SET', 'vertices_last_accessed','.',json.dumps(self.graph.vs[\\\"last_accessed\\\"]))\\n cache.execute_command('JSON.SET', 'edges','.',json.dumps(self.graph.get_edgelist()))\\n\\n # save the created Graph object into the connected sqlite database \\n conn = get_sqlite()\\n c = conn.cursor()\\n c.execute('DROP TABLE IF EXISTS vertices')\\n c.execute('DROP TABLE IF EXISTS edges')\\n c.execute('CREATE TABLE vertices (id, name, parent, size, last_modified, last_accessed)')\\n c.execute('CREATE TABLE edges (start, end)')\\n c.executemany('INSERT INTO vertices VALUES (?,?,?,?,?,?)', vertices)\\n c.executemany('INSERT INTO edges VALUES (?,?)', edges)\\n conn.commit()\\n\\n # optionally create image from the Graph object\\n # unfortunatelly this feature not working correctly now\\n plot(graph,\\\"plot.png\\\", layout=\\\"tree\\\")\",\n \"def __init__(self, vertices=None):\\n\\n self._vertices = dict() \\n if vertices is not None:\\n for label in vertices.keys():\\n self.add_vertex(label)\\n for label, heads in vertices.items():\\n for head in heads:\\n self.add_edge(label, head)\",\n \"def build_graph(edges):\\n \\n G = nx.MultiGraph()\\n G.add_edges_from(edges)\\n return G\",\n \"def to_undirected_graph(self):\\n visited = set() \\n G = Graph.Graph()\\n \\n for node in self.node_set:\\n \\n if node not in visited:\\n visited.add(node)\\n for i in self.suffix[node]:\\n G.add_edge(node, i)\\n \\n return G\",\n \"def __init__(self, graph: ghidra.graph.GImplicitDirectedGraph):\\n ...\",\n \"def test_build_graph():\\r\\n assert valid_graph.get_graph() is not None\\r\\n assert invalid_graph.get_graph() != collections.defaultdict(list)\",\n \"def build_drop_fullgraphs(self, do_subgraph=False, graph_lib='pygraphviz'):\\n if 'pygraphviz' == graph_lib:\\n G = pgv.AGraph(strict=True, directed=True)\\n else:\\n G = nx.Graph()\\n do_subgraph = False\\n subgraph_dict = defaultdict(list) # k - node-ip, v - a list of graph nodes\\n oid_gnid_dict = dict()\\n\\n for i, oid in enumerate(self.pg_spec.keys()):\\n oid_gnid_dict[oid] = str(i)\\n logger.info(\\\"oid to gid mapping done\\\")\\n\\n for dropspec in self.pg_spec.itervalues():\\n gid = oid_gnid_dict[dropspec['oid']]\\n ip = dropspec['node']\\n subgraph_dict[ip].append(gid)\\n if (dropspec['type'] == 'app'):\\n G.add_node(gid, shape='rect', label='')#, fixedsize=True, hight=.05, width=.05)\\n elif (dropspec['type'] == 'plain'): #parallelogram\\n G.add_node(gid, shape='circle', label='')#, fixedsize=True, hight=.05, width=.05)\\n logger.info(\\\"Graph nodes added\\\")\\n\\n for dropspec in self.pg_spec.itervalues():\\n gid = oid_gnid_dict[dropspec['oid']]\\n if (dropspec['type'] == 'app'):\\n ds_kw = 'outputs' #down stream key word\\n elif (dropspec['type'] == 'plain'):\\n ds_kw = 'consumers'\\n else:\\n ds_kw = 'None'\\n if (ds_kw in dropspec):\\n for doid in dropspec[ds_kw]:\\n G.add_edge(gid, oid_gnid_dict[doid])\\n logger.info(\\\"Graph edges added\\\")\\n\\n if (do_subgraph):\\n for i, subgraph_nodes in enumerate(subgraph_dict.values()):\\n # we don't care about the subgraph label or rank\\n subgraph = G.add_subgraph(subgraph_nodes, label='%d' % i, name=\\\"cluster_%d\\\" % i, rank=\\\"same\\\")\\n subgraph.graph_attr['rank']='same'\\n logger.info(\\\"Subgraph added\\\")\\n\\n return G\",\n \"def _make_graph(nodes, ways):\\n graph = networkx.MultiDiGraph(crs=\\\"EPSG:4326\\\")\\n ways_proj = ways.set_crs(\\\"EPSG:4326\\\").to_crs(\\\"EPSG:3395\\\")\\n\\n for node_id, node_attr in nodes.rename(columns={'longitude': 'x', 'latitude': 'y'}).iterrows():\\n graph.add_node(node_id, **node_attr)\\n\\n for _, way in ways_proj.iterrows():\\n\\n osm_oneway_values = [\\\"yes\\\", \\\"true\\\", \\\"1\\\", \\\"-1\\\", \\\"T\\\", \\\"F\\\"]\\n if \\\"oneway\\\" in way and way.oneway in osm_oneway_values:\\n if way[\\\"oneway\\\"] == \\\"-1\\\" or way[\\\"oneway\\\"] == \\\"T\\\":\\n # paths with a one-way value of -1 or T are one-way, but in the\\n # reverse direction of the nodes' order, see osm documentation\\n path_nodes = list(reversed(way.nodes))\\n else:\\n path_nodes = way.nodes\\n # add this path (in only one direction) to the graph\\n one_way = True\\n\\n elif \\\"junction\\\" in way and way.junction == \\\"roundabout\\\":\\n # roundabout are also oneway but not tagged as is\\n path_nodes = way.nodes\\n one_way = True\\n\\n # else, this path is not tagged as one-way or it is a walking network\\n # (you can walk both directions on a one-way street)\\n else:\\n # add this path (in both directions) to the graph and set its\\n # 'oneway' attribute to False. if this is a walking network, this\\n # may very well be a one-way street (as cars/bikes go), but in a\\n # walking-only network it is a bi-directional edge\\n path_nodes = way.nodes\\n one_way = False\\n\\n # zip together the path nodes so you get tuples like (0,1), (1,2), (2,3)\\n # and so on\\n path_edges = list(zip(path_nodes[:-1], path_nodes[1:]))\\n graph.add_edges_from(path_edges, **way[['id']])\\n if not one_way:\\n path_edges_reverse = [(v, u) for u, v in path_edges]\\n graph.add_edges_from(path_edges_reverse, **way[['id']])\\n\\n graph = osmnx.utils_graph.add_edge_lengths(graph)\\n return graph\",\n \"def __init__(self,graph,legal_edges=None,starting_point=(0,0),exits=None):\\n\\t\\tself.graph = graph\\n\\t\\tself.legal_edges = legal_edges\\n\\t\\tself.starting_point = starting_point\\n\\t\\tself.exits = exits\",\n \"def clear(self):\\r\\n self.nodes = collections.defaultdict(list)\\r\\n self.nodes_mapping = collections.defaultdict(list)\\r\\n self.edges = 0\\r\\n #self.children_length={}\\r\\n self.parents_length = collections.defaultdict(lambda : collections.defaultdict(int))\",\n \"def reset_graph(self):\\n self.nodes = {}\\n self.add_node(self.initial_state)\\n self.add_node(self.final_state)\",\n \"def relations(self):\\n\\n def functions_helper(returned_set: set()):\\n if is_relation(self.root): # Populate self.root and self.arguments\\n returned_set.add((self.root, len(self.arguments)))\\n\\n elif is_equality(self.root): # Populate self.first and self.second\\n return\\n elif is_quantifier(self.root): # Populate self.variable and self.predicate\\n returned_set.update(self.predicate.relations())\\n\\n elif is_unary(self.root): # Populate self.first\\n returned_set.update(self.first.relations())\\n\\n else: # Populate self.first and self.second\\n returned_set.update(self.first.relations())\\n returned_set.update(self.second.relations())\\n return\\n\\n \\\"\\\"\\\" Return a set of pairs (function_name, arity) for all function names\\n that appear in this formula \\\"\\\"\\\"\\n returned_set = set()\\n functions_helper(returned_set)\\n return returned_set\\n\\n # Ex12\",\n \"def setUp(self):\\n self.complete = nx.Graph()\\n self.complete.add_edge(1, 2)\\n self.complete.add_edge(2, 3)\\n self.complete.add_edge(1, 3)\\n\\n self.small_tree = nx.Graph()\\n self.small_tree.add_edge(1, 3)\\n self.small_tree.add_edge(4, 3)\\n self.small_tree.add_edge(2, 3)\\n self.small_tree.add_edge(3, 5)\\n self.small_tree.add_edge(5, 6)\\n self.small_tree.add_edge(5, 7)\\n self.small_tree.add_edge(6, 7)\\n\\n self.deterministic_graph = nx.Graph()\\n self.deterministic_graph.add_edge(0, 1) # deg(0) = 1\\n\\n self.deterministic_graph.add_edge(1, 2) # deg(1) = 2\\n\\n self.deterministic_graph.add_edge(2, 3)\\n self.deterministic_graph.add_edge(2, 4) # deg(2) = 3\\n\\n self.deterministic_graph.add_edge(3, 4)\\n self.deterministic_graph.add_edge(3, 5)\\n self.deterministic_graph.add_edge(3, 6) # deg(3) = 4\\n\\n self.deterministic_graph.add_edge(4, 5)\\n self.deterministic_graph.add_edge(4, 6)\\n self.deterministic_graph.add_edge(4, 7) # deg(4) = 5\\n\\n self.deterministic_graph.add_edge(5, 6)\\n self.deterministic_graph.add_edge(5, 7)\\n self.deterministic_graph.add_edge(5, 8)\\n self.deterministic_graph.add_edge(5, 9) # deg(5) = 6\\n\\n self.deterministic_graph.add_edge(6, 7)\\n self.deterministic_graph.add_edge(6, 8)\\n self.deterministic_graph.add_edge(6, 9) # deg(6) = 6\\n\\n self.deterministic_graph.add_edge(7, 8)\\n self.deterministic_graph.add_edge(7, 9) # deg(7) = 5\\n\\n self.deterministic_graph.add_edge(8, 9) # deg(8) = 4\",\n \"def rootSetOrder (self):\\n order = []\\n nodes = set(self.__nodes)\\n edge_map = {}\\n for (d, srcs) in six.iteritems(self.__edgeMap):\\n edge_map[d] = srcs.copy()\\n while nodes:\\n freeset = set()\\n for n in nodes:\\n if not (n in edge_map):\\n freeset.add(n)\\n if 0 == len(freeset):\\n _log.error('dependency cycle in named components')\\n return None\\n order.append(freeset)\\n nodes.difference_update(freeset)\\n new_edge_map = {}\\n for (d, srcs) in six.iteritems(edge_map):\\n srcs.difference_update(freeset)\\n if 0 != len(srcs):\\n new_edge_map[d] = srcs\\n edge_map = new_edge_map\\n return order\",\n \"def gen_graph(self):\",\n \"def build(self):\\n self.logger.info('Rebuilding adjacency information')\\n self.edges = collections.defaultdict(list)\\n\\n topic_to_publisher = collections.defaultdict(list)\\n topic_to_subscribers = collections.defaultdict(list)\\n node_to_missing_deps = collections.defaultdict(list)\\n\\n result = True\\n\\n for node in self.nodes.values():\\n for topic in node.provided_topics.keys():\\n topic_to_publisher[topic].append(node)\\n\\n for topic in node.required_topics:\\n topic_to_subscribers[topic].append(node)\\n\\n for dep in node.additional_dependencies:\\n if dep not in self.nodes:\\n node_to_missing_deps[node].append(dep)\\n\\n if len(node_to_missing_deps) > 0:\\n result = False\\n msg = io.StringIO()\\n print('Found [{}] managed processes with missing dependencies'.format(len(node_to_missing_deps)), file=msg)\\n fmt = ' Managed process [{}] is missing [{}]'\\n\\n for (node, missing) in node_to_missing_deps.items():\\n print(fmt.format(node.name, ', '.join(missing)), file=msg)\\n self.logger.error(msg.getvalue())\\n\\n missing_publishers = []\\n for topic in topic_to_subscribers.keys():\\n if topic not in topic_to_publisher:\\n missing_publishers.append(topic)\\n\\n if len(missing_publishers) > 0:\\n result = False\\n msg = io.StringIO()\\n print('Found [{}] topics that do not have publishers'.format(len(missing_publishers)), file=msg)\\n fmt = ' Topic [{}] with subscribers [{}]'\\n\\n for topic in missing_publishers:\\n print(fmt.format(topic, ', '.join([x.name for x in topic_to_subscribers[topic]])), file=msg)\\n self.logger.error(msg.getvalue())\\n\\n if not result:\\n self.logger.error('Found errors when building adjacency information')\\n raise GraphBuildError(\\n 'Found errors when building adjacency information / graph edges. Check log for details')\\n\\n # Now we have enough information to build our edges. Phase 1: pub/sub stuff\\n for (topic, subscribers) in topic_to_subscribers.items():\\n publishers = topic_to_publisher[topic]\\n\\n for p in publishers:\\n for s in subscribers:\\n self.edges[p].append(s)\\n\\n # Phase 2: additional dependencies\\n for node in self.nodes.values():\\n for dep in node.additional_dependencies:\\n src = self.nodes[dep]\\n self.edges[src].append(node)\",\n \"def __init__(self):\\n self._graph = GenericGraph()\\n self._atom_index = {}\\n self._next_locant = 1\\n self._brutto_formula = ''\\n self.modified = True\",\n \"def initialize_vertices(self, objects_: Union[Dict[str, List[Union[str, int]]], NamedTuple],\\n root_name: str, independent: bool, group: int,\\n vertices_list: list = None) -> list:\\n if vertices_list is None:\\n vertices_list = []\\n if not isinstance(vertices_list, list):\\n raise TypeError(f\\\"Expected List, got {type(vertices_list)}\\\")\\n\\n group_store = {}\\n for key, values in objects_.items():\\n if key == root_name:\\n if type(values) == int or type(values) == str:\\n node = Graph_Node(subtype_name=key, value=values,\\n independent=True, level=\\\"root\\\")\\n node.group.add(group)\\n group_store[key] = node\\n\\n # add root nodes to the class node list\\n self._add_node(node)\\n else:\\n raise TypeError(\\\"Expected value of 'root_name' key to be a str or int\\\")\\n else:\\n node = Graph_Node(subtype_name=key, value=values,\\n independent=independent)\\n node.group.add(group)\\n group_store[key] = node\\n vertices_list.append(group_store)\\n\\n return vertices_list\",\n \"def build_empty_graph(input_dim, output_dim, num_intermediate):\\n from .models import DAG\\n num_emit, num_rec = num_intermediate + input_dim, num_intermediate + output_dim\\n activations = torch.zeros(num_rec, dtype=torch.long)\\n connections = torch.zeros(num_rec, num_emit, dtype=torch.long)\\n\\n return DAG(input_dim, output_dim, num_intermediate, connections, activations, check_valid=True)\",\n \"def _produce_none_relations(self):\\n print \\\"Producing NONE-relations\\\"\\n relations = self.relations\\n events = self.events\\n none_relations = []\\n\\n for source in events:\\n for target in events:\\n new_relation = Relation(\\\"NONE\\\", self.text_obj, source, target, RelationType.NONE)\\n print new_relation\\n\\n if new_relation in relations:\\n continue\\n else:\\n none_relations.append(new_relation)\\n\\n self.relations = self.relations + none_relations\\n\\n print \\\"Finished producing NONE-relations\\\"\",\n \"def build_graph(self):\\n for node in self.graph.nodes():\\n self.c2py[node] = PyNode(node)\\n for _input in node.inputs():\\n if _input not in self.c2py:\\n self.c2py[_input] = PyNode(_input, True)\\n if _input in self.forward_edge:\\n self.forward_edge[_input].append(node)\\n else:\\n self.forward_edge[_input] = [node]\\n for output in node.outputs():\\n if output not in self.c2py:\\n self.c2py[output] = PyNode(output, True)\\n if node in self.forward_edge:\\n self.forward_edge[node].append(output)\\n else:\\n self.forward_edge[node] = [output]\",\n \"def load(toks):\\r\\n graph = nx.Graph()\\r\\n\\r\\n for tok in toks:\\r\\n graph.add_node(tok['id'])\\r\\n\\r\\n for tok in toks:\\r\\n if 'governor' in tok:\\r\\n governor = tok['governor']\\r\\n dependant = tok['id']\\r\\n graph.add_edge(governor, dependant)\\r\\n return graph\",\n \"def setUp(self):\\n self.G = nx.DiGraph()\",\n \"def _get_and_create_relation_objects(self, root_node):\\n relations = []\\n\\n for relation in root_node.iterdescendants(\\\"TLINK\\\"):\\n lid = relation.get(\\\"lid\\\")\\n\\n # Get relation type as a string\\n relation_type = relation.get(\\\"relType\\\")\\n\\n # Get relation_type_id\\n relation_type_id = RelationType.get_id(relation_type)\\n\\n if not relation.get(\\\"timeID\\\") and not relation.get(\\\"relatedToTime\\\"):\\n # This is event-event\\n source_eiid = relation.get(\\\"eventInstanceID\\\")\\n target_eiid = relation.get(\\\"relatedToEventInstance\\\")\\n\\n # Find source event\\n source_obj = self.find_event_by_eiid(self.events, source_eiid)\\n # Find target event\\n target_obj = self.find_event_by_eiid(self.events, target_eiid)\\n\\n else:\\n # This must be event-timex or timex-event or timex-timex\\n target_tid = relation.get(\\\"relatedToTime\\\")\\n target_eiid = relation.get(\\\"relatedToEventInstance\\\")\\n\\n source_tid = relation.get(\\\"timeID\\\")\\n source_eiid = relation.get(\\\"eventInstanceID\\\")\\n\\n\\n if source_tid and target_eiid:\\n # timex-event\\n source_obj = self.find_timex_by_tid(source_tid)\\n target_obj = self.find_event_by_eiid(self.events, target_eiid)\\n elif source_eiid and target_tid:\\n # event-timex\\n source_obj = self.find_event_by_eiid(self.events, source_eiid)\\n target_obj = self.find_timex_by_tid(target_tid)\\n elif source_tid and target_tid:\\n # timex-timex\\n source_obj = self.find_timex_by_tid(source_tid)\\n target_obj = self.find_timex_by_tid(target_tid)\\n\\n relation_obj = Relation(lid, self.text_obj, source_obj, target_obj, relation_type_id)\\n\\n # So we don't run into problems with helper.output\\n if relation_obj.is_timex_timex(): relation_obj.predicted_class = relation_type_id\\n\\n # There are sometimes duplicates which we do not want to have\\n if relation_obj not in relations:\\n relations.append(relation_obj)\\n\\n return relations\",\n \"def make_set(node):\\n node.parent = node\\n node.rank = 0\",\n \"def __init__(self, edges=None, directed=False):\\n self._graph = defaultdict(dict)\\n self._directed = directed\\n if edges:\\n self.add_edges(edges)\",\n \"def graph(self):\\n graph = nx.DiGraph()\\n for name, joint in self.joints.items():\\n graph.add_edge(*joint.connects, joint=name)\\n return graph\",\n \"def __init__(self, name=None):\\n self.id = id # Unique identifier for the set\\n self._next_id = 0 # Holds unique ids for graphs\\n self._graphs = {} # Holds graphs, keyed by unique id\\n self.name = name # Holds description of graph\",\n \"def __init__(self, root):\\n self._root = root\\n self._leaves = [root]\",\n \"def __init__(self, nodes=[], edges=[], connections=[], directed=False, isNetwork=False):\\n Node.count=0\\n Edge.count=0\\n self.nodes = [n for n in nodes]\\n self.edges = [e for e in edges]\\n self.connections = [(a, b) for (a, b) in connections]\\n self.isDirected = directed\\n self.isNetwork = isNetwork\",\n \"def ResetGraph(self):\\n self.nodes = []\\n self.edges = []\\n self.connections = []\\n Node.resetNodeCount()\\n Edge.resetEdgesCount()\",\n \"def __create_graph(self):\\n # create the nodes\\n for h in range(self.height):\\n row: List[JuncNode] = list()\\n for w in range(self.width):\\n jnodes: List[Node] = [self.add_node() for _ in range(4)]\\n jn = JuncNode(jnodes, (h, w))\\n row.append(jn)\\n self.__juncs.append(row)\\n # create all connections\\n self.__create_connections()\",\n \"def relations_to(self, end_node):\",\n \"def build(self, graph):\\n self.results = None\\n\\n self.graph = graph\\n\\n self.__build_nodes()\\n self.__build_edges()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6473229","0.61222476","0.6110643","0.6073983","0.5881061","0.5881061","0.57006747","0.5691904","0.5682234","0.5674344","0.5652","0.5635029","0.5594031","0.55848473","0.557185","0.55271906","0.5522342","0.5512572","0.54549974","0.54519945","0.54198855","0.5416138","0.5388613","0.53863686","0.5386153","0.53385955","0.53324","0.5321737","0.5307942","0.5303616","0.53012156","0.52870905","0.5280214","0.5277893","0.5277893","0.52760565","0.527569","0.5269703","0.526791","0.5242439","0.52410996","0.5240479","0.5228421","0.5220272","0.51967937","0.5187742","0.5180311","0.51798564","0.5174119","0.5172296","0.5168658","0.516706","0.51591086","0.5155143","0.51545477","0.5145498","0.5113691","0.5107165","0.5098735","0.50973284","0.5095642","0.5094398","0.50894445","0.50884104","0.5088052","0.50823","0.5081537","0.50806","0.50776017","0.5073736","0.50694185","0.5067299","0.50670564","0.50642765","0.50628316","0.50589794","0.5056638","0.5055692","0.5055618","0.5054535","0.5052857","0.5049215","0.5045585","0.5044283","0.50436","0.50413364","0.50388944","0.50369024","0.50348455","0.5034178","0.5028868","0.50269467","0.5016761","0.5014933","0.5014532","0.5013411","0.5011065","0.5010733","0.5002421","0.50013876"],"string":"[\n \"0.6473229\",\n \"0.61222476\",\n \"0.6110643\",\n \"0.6073983\",\n \"0.5881061\",\n \"0.5881061\",\n \"0.57006747\",\n \"0.5691904\",\n \"0.5682234\",\n \"0.5674344\",\n \"0.5652\",\n \"0.5635029\",\n \"0.5594031\",\n \"0.55848473\",\n \"0.557185\",\n \"0.55271906\",\n \"0.5522342\",\n \"0.5512572\",\n \"0.54549974\",\n \"0.54519945\",\n \"0.54198855\",\n \"0.5416138\",\n \"0.5388613\",\n \"0.53863686\",\n \"0.5386153\",\n \"0.53385955\",\n \"0.53324\",\n \"0.5321737\",\n \"0.5307942\",\n \"0.5303616\",\n \"0.53012156\",\n \"0.52870905\",\n \"0.5280214\",\n \"0.5277893\",\n \"0.5277893\",\n \"0.52760565\",\n \"0.527569\",\n \"0.5269703\",\n \"0.526791\",\n \"0.5242439\",\n \"0.52410996\",\n \"0.5240479\",\n \"0.5228421\",\n \"0.5220272\",\n \"0.51967937\",\n \"0.5187742\",\n \"0.5180311\",\n \"0.51798564\",\n \"0.5174119\",\n \"0.5172296\",\n \"0.5168658\",\n \"0.516706\",\n \"0.51591086\",\n \"0.5155143\",\n \"0.51545477\",\n \"0.5145498\",\n \"0.5113691\",\n \"0.5107165\",\n \"0.5098735\",\n \"0.50973284\",\n \"0.5095642\",\n \"0.5094398\",\n \"0.50894445\",\n \"0.50884104\",\n \"0.5088052\",\n \"0.50823\",\n \"0.5081537\",\n \"0.50806\",\n \"0.50776017\",\n \"0.5073736\",\n \"0.50694185\",\n \"0.5067299\",\n \"0.50670564\",\n \"0.50642765\",\n \"0.50628316\",\n \"0.50589794\",\n \"0.5056638\",\n \"0.5055692\",\n \"0.5055618\",\n \"0.5054535\",\n \"0.5052857\",\n \"0.5049215\",\n \"0.5045585\",\n \"0.5044283\",\n \"0.50436\",\n \"0.50413364\",\n \"0.50388944\",\n \"0.50369024\",\n \"0.50348455\",\n \"0.5034178\",\n \"0.5028868\",\n \"0.50269467\",\n \"0.5016761\",\n \"0.5014933\",\n \"0.5014532\",\n \"0.5013411\",\n \"0.5011065\",\n \"0.5010733\",\n \"0.5002421\",\n \"0.50013876\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.58929604"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":13082,"cells":{"query":{"kind":"string","value":"Redefine the root graph for universe. It omits edges whose labels are in omit_edge_labels and also does not store references for nodes they point at. This is used mostly to get rid of uniquely identifying nodes."},"document":{"kind":"string","value":"def re_root(self, omit_edge_label: List[str]):\n self.leaves = {node for node in self.nodes\n if any([edge.label in omit_edge_label for edge in self.edges_to(node)])}\n root_nodes = self.nodes - self.leaves\n root_edges = {edge for edge in self.edges if edge.node_to in root_nodes and edge.node_from in root_nodes}\n self.root_graph = Mask(root_nodes, root_edges, self)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def reset_graph(self):\n self.nodes = {}\n self.add_node(self.initial_state)\n self.add_node(self.final_state)","def reset_graph(self):\n raise NotImplementedError","def reset_graph(self):\n self.graph = OrderedDict()","def _restoreGraph(self):\n\n # self.tempG = self.g.copy()\n\n if nx.is_directed(self.g):\n self.tempG = nx.DiGraph(self.g)\n else:\n self.tempG = nx.Graph(self.g)\n self.deletedEdges = []\n self.deletedNodes = []","def strip_useless_attributes(self):\n graph_dict = self.graph.graph\n if \"node\" in graph_dict and \"label\" in graph_dict[\"node\"]:\n graph_dict[\"node\"].pop(\"label\")\n if \"graph\" in graph_dict:\n graph_dict.pop(\"graph\")","def ResetGraph(self):\n self.nodes = []\n self.edges = []\n self.connections = []\n Node.resetNodeCount()\n Edge.resetEdgesCount()","def clear(self):\n \n self.node_set.clear()\n self.prefix.clear()\n self.suffix.clear()\n self.num_node = 0\n self.edges = 0","def unifyPreviewNodes(self):\n\n self.leaves.update(self.forced)\n self.forced = set()","def restore(self):\n self.nodes.restore()","def __init__(self, nodes: Set[Node], edges: Set[Edge]):\n super().__init__()\n self.nodes = nodes\n for edge in edges:\n self.add_edge(edge)\n self.leaves = {node for node in self.nodes if self.degree_out(node) == 0}\n root_nodes = self.nodes - self.leaves\n root_edges = {edge for edge in self.edges if edge.node_to not in self.leaves}\n self.root_graph = Mask(root_nodes, root_edges, self)","def clear_registered_nodes(self):\n self.__nodes.clear()\n self.__names.clear()\n self.__aliases.clear()","def reset():\n\n globals()[\"currentGraph\"] = CompositionGraph()","def clear(self):\r\n self.nodes = collections.defaultdict(list)\r\n self.nodes_mapping = collections.defaultdict(list)\r\n self.edges = 0\r\n #self.children_length={}\r\n self.parents_length = collections.defaultdict(lambda : collections.defaultdict(int))","def _Restore(self) -> None:\n self._SetNodes(self._nodes)","def root_replace(self,node):\r\n self.feature_index = node.feature_index\r\n self.threshold = node.threshold\r\n self.label = node.label\r\n self.left = node.left\r\n self.right = node.right\r\n self.substitute = node.substitute\r\n if node.left is not None and node.right is not None:\r\n node.left.parents.remove(node) if node in node.left.parents else node.left.parents\r\n node.left.parents.append(self) if self not in node.left.parents else node.left.parents\r\n node.right.parents.remove(node) if node in node.right.parents else node.right.parents\r\n node.right.parents.append(self) if self not in node.right.parents else node.right.parents","def reset(self):\n self.G = nx.Graph()\n self.form.plot_canvas.plot(self.G)","def complete_graph(self):\n root_nodes = set()\n\n for name, a_block in self.wf['action'].items():\n\n a_block['name'] = name\n\n for n in a_block.get('needs', []):\n if not self.wf['action'][n].get('next', None):\n self.wf['action'][n]['next'] = set()\n self.wf['action'][n]['next'].add(name)\n\n if not a_block.get('needs', None):\n root_nodes.add(name)\n\n self.wf['root'] = root_nodes","def reset_edges(self):\n\n # Ensure original edges are stored in cache, otherwise nothing to do.\n if self._modified_edges is None or self._weighted_modified_edges is None:\n return\n\n # Restore the former value from cache\n self.adj_matrices = {**self.adj_matrices, **self._modified_edges}\n self.degree_weighted_matrices = {**self.degree_weighted_matrices, **self._weighted_modified_edges}\n self.in_degree = {**self.in_degree, **self._orig_in_degree}\n self.out_degree = {**self.out_degree, **self._orig_out_degree}\n\n # Reset the edge and degree cache\n self._modified_edges = None\n self._weighted_modified_edges = None\n self._orig_in_degree = dict()\n self._orig_out_degree = dict()","def update_node2edge(self):\n self.node2edge = {e.child : e for e in self.edge}\n childrenset = set(self.node2edge.keys())\n rootset = set(e.parent for e in self.edge).difference(childrenset)\n if len(rootset) > 1:\n raise Warning(\"there should be a single root: \" + str(rootset))\n if len(rootset) == 0:\n raise Exception(\"there should be at least one root!\")\n self.root = rootset.pop()","def reset_edges(self):\n super().reset_edges()\n\n # If we're in default state, notheing to rest\n if self._modified_weighted_adj_matrices is None:\n return\n\n # Degrees are reset, so we need to reset the original weight scaling\n if self.scale_weights and not self.scaling_skipped:\n self._scale_weights_to_degree()\n self._generate_weighted_adj_matrices()\n else:\n # No weight scaling so just load prev values from cache\n self.weighted_adj_matrices = {**self.weighted_adj_matrices, **self._modified_weighted_adj_matrices}\n self._modified_weighted_adj_matrices = None","def start_new_graph(self):\n self.nodes = {}\n self.reset_graph()","def reset_tree(self):\n self.root = None\n self.action = None\n self.dist_probability = None","def disown(self):\r\n for apply_node in self.apply_nodes:\r\n del apply_node.fgraph\r\n del apply_node.deps\r\n for variable in self.variables:\r\n del variable.fgraph\r\n del variable.clients\r\n self.apply_nodes = set()\r\n self.variables = set()\r\n self.inputs = None\r\n self.outputs = None","def to_undirected_graph(self):\n visited = set() \n G = Graph.Graph()\n \n for node in self.node_set:\n \n if node not in visited:\n visited.add(node)\n for i in self.suffix[node]:\n G.add_edge(node, i)\n \n return G","def reset(self):\n\t\tself.graph = OrderedDict()\n\t\tself.bottoms = OrderedDict()\n\t\tself.output_shape = OrderedDict()\n\t\tself.cur_tensor = None\n\t\tself.cur_id = None\n\t\tself.tmp_list = []\n\t\tself.log_init()","def clear(self):\n self._nodes = { }\n self._arcs = set()","def __root(T: \"Graph\"):\n T_copy = T.copy()\n\n # Leaves are removed from the copy untill 1 or 2 vertices remain\n while len(T_copy.vertices) > 2:\n vertices_to_remove = []\n for v in T_copy.vertices:\n if v.degree == 1:\n vertices_to_remove.append(v)\n for v in vertices_to_remove:\n T_copy.del_vertex(v)\n\n root_labels = []\n for v in T_copy.vertices:\n root_labels.append(v.label)\n\n # From the original tree, the roots are returned\n T_root = []\n for v in T.vertices:\n if v.label in root_labels:\n T_root.append(v)\n\n return T_root","def reset(self):\n self.edges = None\n self.chi = None\n self.k = None\n self.n_bins = None\n self.classes = None\n self.n_params = None","def clear_nastran(self):\n self.eid_map = {}\n self.nid_map = {}\n self.eid_to_nid_map = {}\n self.element_ids = None\n self.node_ids = None","def clear(self):\n self.root = _NGramMapNode()\n self.size_freqs = dict()\n self.ele_freqs = dict()","def reset(self):\n self.visited = set()\n del self.targets[0]","def relabel_nodes(graph: BaseGraph, mapping: Dict) -> None:\n relabel_nodes(graph.graph, mapping, copy=False)","def clear(self):\n self.nodes = list()\n self.inputs = list()\n self.nodes += [self]","def clean_edges(self):","def clear_edges(infr):\n for graph in infr.review_graphs.values():\n graph.remove_edges_from(list(graph.edges()))\n infr.graph.remove_edges_from(list(infr.graph.edges()))\n infr.pos_redun_nids.clear()\n infr.neg_redun_metagraph.clear()\n infr.nid_to_errors.clear()","def _reset_traversal_state(self):\n for n in self.nodes.values():\n n.reset_traversal_state()","def reset_nn(self): # Clear current network\n self.weights = np.zeros((p.num_rovers, self.n_weights))\n self.in_layer = np.zeros((p.num_rovers, self.n_inputs))\n self.hid_layer = np.zeros((p.num_rovers, self.n_nodes))\n self.out_layer = np.zeros((p.num_rovers, self.n_outputs))","def add_resets_edges(graph, start):\n for node in graph.nodes:\n neighbors = list(graph[node])\n if neighbors == [node]:\n graph.add_edge(node, start, label=\"RESET / \")","def clear_node_id_terms(self):\n pass","def reset(self):\n self.dims.clear()\n self.xlabels.clear()\n self.annotators.clear()\n self._figTitle = None\n self.tbmTitle = None\n self._isSubplot = False\n self._universal_xlabel = False\n self._plotter = None\n self.Nsp = 0","def edge_subgraph(self, edges, relabel_nodes=False, output_device=None):\n raise NotImplementedError(\"edge_subgraph is not implemented yet\")","def create_unlabeled_subgraph(graph):\n unlabeled_nodes = []\n for (p, d) in graph.nodes(data=True):\n if (d['leaning'] == 'Unknown'):\n unlabeled_nodes.append(p)\n return nx.subgraph(graph, unlabeled_nodes)","def _clean_graph(self):\n for entry_node in self._entry_nodes:\n self._clean_graph_visit(entry_node.get_func_first_node(), {})","def clear(self) -> None:\n self.graph.clear()","def reset(self):\r\n self.tree = KDTree()\r\n self.paint()","def reset(cls):\r\n cls._ROOTS_BY_TYPE = {}\r\n cls._TYPES_BY_ROOT = {}\r\n cls._SEARCHED = set()","def clean_local_memory(self):\n self.namespaces = self._rdf_builder.namespaces\n self.dataset = self._rdf_builder.dataset\n\n self.ontology_graph = self._rdf_builder.ontology_graph\n self.instance_graph = self._rdf_builder.instance_graph\n self.claim_graph = self._rdf_builder.claim_graph\n self.perspective_graph = self._rdf_builder.perspective_graph\n self.interaction_graph = self._rdf_builder.interaction_graph","def clone_as_root(self) :\n clone = deepcopy(self)\n clone.parent = None\n clone.path_length = 0\n clone.previous_action = None\n return clone","def reset(self):\n self._clusters = {}\n self._clusters_val = {}\n self._centroids = {}\n self.store()","def subgraph(self, nodes, relabel_nodes=False, output_device=None):\n raise NotImplementedError(\"subgraph is not implemented yet\")","def strip(self):\n self.graph = None\n self.session = None\n\n return self","def restore_graph_ui(self):\n if len(self._graph_copies) == 0:\n print('No copies to restore!')\n return\n # the last made copy is restored in graph\n self._graph = self._graph_copies.pop(-1)","def reset_graph():\n sess = tf.get_default_session()\n if sess:\n sess.close()\n tf.reset_default_graph()","def reset_graph():\n sess = tf.get_default_session()\n if sess:\n sess.close()\n tf.reset_default_graph()","def reset_weights(self):\n self.head.reset_weights()","def clear(self):\n self.root = None","def _reset_topological_order(self):\n self._topological_order = self._input_nodes[:]\n self.sorted = False","def clear_network(self):\n\n return self.alter_network(remove=list(self.network.edges))","def refresh_metadata(self):\n #self.node_index = None\n #self.edge_index = None\n #self._calc_edge_centers = False\n #self._calc_cell_centers = False\n #self._calc_vcenters = False\n self._node_to_edges = None\n self._node_to_cells = None","def onnx_remove_node_unused(onnx_model, recursive=True, debug_info=None, **options):\r\n if debug_info is None:\r\n debug_info = [str(type(onnx_model)).rsplit(\r\n '.', maxsplit=1)[-1].strip(\"'>\")]\r\n else:\r\n debug_info = (debug_info +\r\n [str(type(onnx_model)).rsplit('.', maxsplit=1)[-1].strip(\"'>\")])\r\n\r\n if hasattr(onnx_model, 'graph'):\r\n return _apply_optimisation_on_graph(\r\n onnx_remove_node_unused, onnx_model,\r\n recursive=recursive, debug_info=debug_info,\r\n **options)\r\n\r\n graph = onnx_model\r\n data = {}\r\n valid = {}\r\n edges = {}\r\n\r\n for init in graph.initializer:\r\n data[init.name, 0] = init\r\n\r\n for node in graph.node:\r\n data[node.name, 1] = node\r\n for inp in node.input:\r\n data[inp, 0] = node\r\n edges[(inp, 0), (node.name, 1)] = node\r\n for out in node.output:\r\n data[out, 0] = node\r\n edges[(node.name, 1), (out, 0)] = node\r\n\r\n for out in graph.output:\r\n valid[out.name, 0] = True\r\n\r\n modif = 1\r\n while modif > 0:\r\n modif = 0\r\n for e1, e2 in edges: # pylint: disable=E1141\r\n if valid.get(e2, False) and not valid.get(e1, False):\r\n valid[e1] = True\r\n modif += 1\r\n\r\n new_nodes = [n for n in graph.node if (n.name, 1) in valid]\r\n new_inits = [n for n in graph.initializer if (n.name, 0) in valid]\r\n\r\n if recursive:\r\n # Handles subgraphs.\r\n for i in range(len(new_nodes)): # pylint: disable=C0200\r\n node = new_nodes[i]\r\n if node is None or not (node.attribute): # pylint: disable=C0325\r\n continue\r\n new_nodes[i] = _apply_remove_node_fct_node(\r\n onnx_remove_node_unused,\r\n node, recursive=True, debug_info=debug_info + [node.name])\r\n\r\n # Finally create the new graph.\r\n nodes = list(filter(lambda n: n is not None, new_nodes))\r\n graph = make_graph(nodes, onnx_model.name,\r\n onnx_model.input, onnx_model.output,\r\n new_inits)\r\n\r\n graph.value_info.extend(onnx_model.value_info) # pylint: disable=E1101\r\n return graph","def reset(self):\r\n self.key = None\r\n self.value = None\r\n self.parent = None\r\n self.left_child = None\r\n self.right_child = None\r\n self.color = BLACK\r\n self.size_tree = 0","def __deepcopy__(self):\n return UndirectedGraph.extract_edge_induced_subgraph(self, lambda edge: True) # copy all edges","def reset_equivalencies(self):\n self._equivalencies = self._default_equivalencies","def clear_name_labels(infr):\n infr.print('clear_name_labels()', 1)\n # make distinct names for all nodes\n distinct_names = {node: -aid for node, aid in infr.get_node_attrs('aid').items()}\n infr.set_node_attrs('name_label', distinct_names)","def remove_identity_nodes(self):\n nodes_to_remove = []\n for node in self.model.nodes():\n if node.op_type == \"Identity\":\n if node.output[0] not in self.model.get_graphs_output_names():\n self.model.replace_input_of_all_nodes(node.output[0], node.input[0])\n nodes_to_remove.append(node)\n\n if nodes_to_remove:\n self.model.remove_nodes(nodes_to_remove)\n logger.info(f\"Removed {len(nodes_to_remove)} Identity nodes\")","def reset_visited(self):\n self.__visited = False","def generate(self):\n self.graph_repl = self.master.graph_repl","def reinitialize(self):\n if self.is_leaf():\n self.__hash__(reinit=True)\n return {self}, {self}\n else:\n children_leaves = set()\n children_nodes = {self}\n # iterating over the children\n for child in self.child_nodes:\n cur_child_leaves, cur_child_nodes = self.child_nodes[child].reinitialize()\n children_leaves = children_leaves.union(cur_child_leaves)\n children_nodes = children_nodes.union(cur_child_nodes)\n # storing the sets for later use\n self.__hash__(reinit=True)\n self.leaves = children_leaves\n self.nodes = children_nodes\n return children_leaves, children_nodes","def reset_weight_zero(self):\n self.node_embedding = np.random.uniform(low=-0.5, high=0.5, size=(self.vocab_size, self.layer1_size)).astype(\n np.float32)\n self.context_embedding = np.zeros((self.vocab_size, self.layer1_size), dtype=np.float32)\n\n self.centroid = np.zeros((self.k, self.layer1_size), dtype=np.float32)\n self.covariance_mat = np.zeros((self.k, self.layer1_size, self.layer1_size), dtype=np.float32)\n self.inv_covariance_mat = np.zeros((self.k, self.layer1_size, self.layer1_size), dtype=np.float32)\n self.pi = np.zeros((self.vocab_size, self.k), dtype=np.float32)\n log.info(\"reset communities data| k: {}\".format(self.k))","def clear(self):\n self.mismatch_error = None\n self.pt_outs = None\n self._onnx_graph = None\n self.upper_graph_info = None\n self.lower_graph_info = None","def unflatten(self): \n self.assign(self.get_unflattened_circuit())\n self._expr_map = None","def defaultize(self):\n if self.root is None:\n genome.initialize(self)\n self.root.defaultize()","def uproot(self):\n self.__root__ = self\n return self","def untangle_roots(self):\n\n for root in self.all_seed_roots:\n root_queue = [root]\n while root_queue:\n for output_root in self.connect_roots(root_queue.pop(0)):\n root_queue.append(output_root)","def unfinalize(namespace='*'):\n\n utils.set_historical_importance(state=2)\n\n if namespace:\n namespace += ':'\n\n attrs = ['visibility_CTL.jointsVis',\n 'visibility_CTL.modelVis',\n 'visibility_CTL.modelSelectable',\n 'visibility_CTL.jointsSelectable']\n\n attrs += [namespace+'visibility_CTL.jointsVis',\n namespace+'visibility_CTL.modelVis',\n namespace+'visibility_CTL.modelSelectable',\n namespace+'visibility_CTL.jointsSelectable']\n\n for attr in attrs:\n if mc.objExists(attr):\n mc.setAttr(attr, True)\n\n pickWalk.delete_tags()\n mp = utils.ModelPanel()\n\n mp.set_joints_vis(1)\n mp.set_jointXray_vis(1)","def unisolvent_nodes(self):\r\n pass","def _clear_node(self):\n self._element = None\n self._parent = None\n self._leftchild = None\n self._rightchild = None\n self._height = None","def _rewrite_unary_default(self, node: saldag.UnaryOpNode):\n\n par = next(iter(node.parents))\n if node.is_reversible() and node.is_lower_boundary() and not par.is_root():\n print(\"lower boundary\", node)\n node.get_in_rel().stored_with = copy.copy(node.out_rel.stored_with)\n node.is_mpc = False","def reverse_graph(self) -> GraphInterface:\n ans = DiGraph()\n\n nodes = self._graph.get_all_v() # {key: NodeData}\n for key in nodes:\n ans.add_node(key)\n ans.get_node(key).tag = self._graph.get_node(key).tag\n\n for key in nodes:\n out_edges = self._graph.all_out_edges_of_node(key)\n for edge in out_edges:\n e = out_edges.get(edge)\n ans.add_edge(e.dest, e.src, e.weight)\n\n return ans","def reset(self):\n for c in self.children:\n c.reset()\n self.marked = False","def reset(self):\n self.current = self.root\n env = self.env\n obs, infos = env.reset()\n obs = obs[obs.find(\"=\"):] # removes textworld legend\n\n return env, obs, infos","def reset(self):\n self.det_link_map = OrderedDict()\n self.id_link_map = OrderedDict()\n self.declarations_table = None\n self.annotations_table = None\n self.num_frames = 0\n self.num_frames_by_uid = {}\n self.num_frames_by_uid_pre_remove = {}","def make_complete_graph(num_nodes):\n graph = {}\n for dummy_node in range(num_nodes):\n graph[dummy_node] = set([dummy_x for dummy_x in range(num_nodes)])\n graph[dummy_node].remove(dummy_node)\n return graph","def make_complete_graph(num_nodes):\n graph = {}\n for dummy_node in range(num_nodes):\n graph[dummy_node] = set([dummy_x for dummy_x in range(num_nodes)])\n graph[dummy_node].remove(dummy_node)\n return graph","def reset(self):\n\n self.fig.clear()\n self.ax = self.fig.add_subplot(111)\n self.hasLegend.set(False)\n self.title(Graph.default_title)\n # Lines is a list of DataSet objects. The user should take care to make\n # DataSet names unique, as there is no error checking done by Graph. \n # If a DataSet line is deleted by its formal name, Graph will delete the\n # first line in the list that matches the name.\n self.lines = {}\n self.line_counter = 1","def draw_graph(self):\n\t\tif None in self.graph:\n\t\t\tdel self.graph[None]\n\n\t\tfor vs in self.graph.itervalues():\n\t\t\tto_delete = []\n\t\t\tfor i in xrange(len(vs)):\n\t\t\t\tif vs[i] is None:\n\t\t\t\t\tto_delete.append(i)\n\n\t\t\tfor i in reversed(to_delete):\n\t\t\t\tdel vs[i]\n\n\t\tself.G=nx.Graph(self.graph)\n\n\t\tfor k,v in self.labels.iteritems():\n\t\t\tif v[:6] == 'Module':\n\t\t\t\troot = k\n\t\t\t\tbreak\n\n\t\treturn self.__dfs_plot(root)","def deactivate_all_snodes():\n for root_fb in FieldsBuilder._finalized_roots():\n root_fb.deactivate_all()","def forget_labels(labels_to_forget=\"none\"):\n\t\t\tassert labels_to_forget in {\"none\",\"originally unlabelled\",\"all\"}\n\t\t\tif labels_to_forget != \"none\":\n\t\t\t\tif labels_to_forget == \"originally unlabelled\":\n\t\t\t\t\tself.train_labels___0_unlab__neg1_exclud=self.train_orig_labels.copy()\n\t\t\t\telif labels_to_forget == \"all\":\n\t\t\t\t\tself.train_labels___0_unlab__neg1_exclud=np.zeros(self.num_train)\n\t\t\t\telse:\n\t\t\t\t\tassert False\n\t\t\t\tself.bool_train_labelled=(self.train_labels___0_unlab__neg1_exclud>0)\n\t\t\t\tself.bool_train_unlabelled=(self.train_labels___0_unlab__neg1_exclud==0)\n\t\t\t\tself.bool_train_excluded=(self.train_labels___0_unlab__neg1_exclud<0)\n\t\t\t\tself.num_train_labelled=sum(self.bool_train_labelled)\n\t\t\t\tself.num_train_unlabelled=sum(self.bool_train_unlabelled)\n\t\t\t\tself.num_train_excluded=sum(self.bool_train_excluded)","def _internal_build(self):\n self.nodes = self.__tree.Nodes()\n self.edges = self.__tree.Edges()\n self.augmentedEdges = {}\n for key, val in self.__tree.AugmentedEdges().items():\n self.augmentedEdges[key] = list(val)\n self.root = self.__tree.Root()\n\n seen = set()\n self.branches = set()\n\n # Find all of the branching nodes in the tree, degree > 1\n # That is, they appear in more than one edge\n for e1, e2 in self.edges:\n if e1 not in seen:\n seen.add(e1)\n else:\n self.branches.add(e1)\n\n if e2 not in seen:\n seen.add(e2)\n else:\n self.branches.add(e2)\n\n # The nodes that are not branches are leaves\n self.leaves = set(self.nodes.keys()) - self.branches\n self.leaves.remove(self.root)","def reset(self):\n self.children.clear()","def reset_pooling_layer(self):\n self._semantic_decoder.reset_pooling_layer()\n if self._instance_decoder is not None:\n self._instance_decoder.reset_pooling_layer()","def make_complete_graph(num_nodes):\n complete_digraph = {}\n if num_nodes > 0 and type(num_nodes) == int:\n neighbors = set([idx for idx in range(num_nodes)])\n for idx in range(num_nodes):\n complete_digraph[idx] = neighbors.copy() #creates adjacency set\n complete_digraph[idx].remove(idx) # pop out self-loop \n return complete_digraph","def reset (self):\n self.__inScopeNamespaces = self.__initialScopeNamespaces\n self.__inScopePrefixes = self.__initialScopePrefixes\n self.__mutableInScopeNamespaces = False\n self.__namespacePrefixCounter = 0","def _reset(self):\n self._set(\"_n_init_features\", None)\n self._set(\"_n_output_features\", None)\n self._set(\"_n_intervals\", None)\n self._set(\"_mapper\", {})\n self._set(\"_cpp_preprocessor\", None)\n self._set(\"_fitted\", False)","def clear(self):\n while len(self.nodes) > 0:\n self.nodes[0].remove()\n\n self.has_been_modified = False","def _setup_graph_def(self):\n raise NotImplementedError","def destroy(self):\n del self.nodes\n self.nodes = {}","def reset(self):\r\n self._root_dir = None","def tearDown(self):\n data_graph.update(\"CLEAR DEFAULT\")","def upstream_structure(self):\n structure_dict = {'edges': set(),\n 'nodes': set()}\n structure_dict = self._build_structure_dict(structure_dict)\n return structure_dict"],"string":"[\n \"def reset_graph(self):\\n self.nodes = {}\\n self.add_node(self.initial_state)\\n self.add_node(self.final_state)\",\n \"def reset_graph(self):\\n raise NotImplementedError\",\n \"def reset_graph(self):\\n self.graph = OrderedDict()\",\n \"def _restoreGraph(self):\\n\\n # self.tempG = self.g.copy()\\n\\n if nx.is_directed(self.g):\\n self.tempG = nx.DiGraph(self.g)\\n else:\\n self.tempG = nx.Graph(self.g)\\n self.deletedEdges = []\\n self.deletedNodes = []\",\n \"def strip_useless_attributes(self):\\n graph_dict = self.graph.graph\\n if \\\"node\\\" in graph_dict and \\\"label\\\" in graph_dict[\\\"node\\\"]:\\n graph_dict[\\\"node\\\"].pop(\\\"label\\\")\\n if \\\"graph\\\" in graph_dict:\\n graph_dict.pop(\\\"graph\\\")\",\n \"def ResetGraph(self):\\n self.nodes = []\\n self.edges = []\\n self.connections = []\\n Node.resetNodeCount()\\n Edge.resetEdgesCount()\",\n \"def clear(self):\\n \\n self.node_set.clear()\\n self.prefix.clear()\\n self.suffix.clear()\\n self.num_node = 0\\n self.edges = 0\",\n \"def unifyPreviewNodes(self):\\n\\n self.leaves.update(self.forced)\\n self.forced = set()\",\n \"def restore(self):\\n self.nodes.restore()\",\n \"def __init__(self, nodes: Set[Node], edges: Set[Edge]):\\n super().__init__()\\n self.nodes = nodes\\n for edge in edges:\\n self.add_edge(edge)\\n self.leaves = {node for node in self.nodes if self.degree_out(node) == 0}\\n root_nodes = self.nodes - self.leaves\\n root_edges = {edge for edge in self.edges if edge.node_to not in self.leaves}\\n self.root_graph = Mask(root_nodes, root_edges, self)\",\n \"def clear_registered_nodes(self):\\n self.__nodes.clear()\\n self.__names.clear()\\n self.__aliases.clear()\",\n \"def reset():\\n\\n globals()[\\\"currentGraph\\\"] = CompositionGraph()\",\n \"def clear(self):\\r\\n self.nodes = collections.defaultdict(list)\\r\\n self.nodes_mapping = collections.defaultdict(list)\\r\\n self.edges = 0\\r\\n #self.children_length={}\\r\\n self.parents_length = collections.defaultdict(lambda : collections.defaultdict(int))\",\n \"def _Restore(self) -> None:\\n self._SetNodes(self._nodes)\",\n \"def root_replace(self,node):\\r\\n self.feature_index = node.feature_index\\r\\n self.threshold = node.threshold\\r\\n self.label = node.label\\r\\n self.left = node.left\\r\\n self.right = node.right\\r\\n self.substitute = node.substitute\\r\\n if node.left is not None and node.right is not None:\\r\\n node.left.parents.remove(node) if node in node.left.parents else node.left.parents\\r\\n node.left.parents.append(self) if self not in node.left.parents else node.left.parents\\r\\n node.right.parents.remove(node) if node in node.right.parents else node.right.parents\\r\\n node.right.parents.append(self) if self not in node.right.parents else node.right.parents\",\n \"def reset(self):\\n self.G = nx.Graph()\\n self.form.plot_canvas.plot(self.G)\",\n \"def complete_graph(self):\\n root_nodes = set()\\n\\n for name, a_block in self.wf['action'].items():\\n\\n a_block['name'] = name\\n\\n for n in a_block.get('needs', []):\\n if not self.wf['action'][n].get('next', None):\\n self.wf['action'][n]['next'] = set()\\n self.wf['action'][n]['next'].add(name)\\n\\n if not a_block.get('needs', None):\\n root_nodes.add(name)\\n\\n self.wf['root'] = root_nodes\",\n \"def reset_edges(self):\\n\\n # Ensure original edges are stored in cache, otherwise nothing to do.\\n if self._modified_edges is None or self._weighted_modified_edges is None:\\n return\\n\\n # Restore the former value from cache\\n self.adj_matrices = {**self.adj_matrices, **self._modified_edges}\\n self.degree_weighted_matrices = {**self.degree_weighted_matrices, **self._weighted_modified_edges}\\n self.in_degree = {**self.in_degree, **self._orig_in_degree}\\n self.out_degree = {**self.out_degree, **self._orig_out_degree}\\n\\n # Reset the edge and degree cache\\n self._modified_edges = None\\n self._weighted_modified_edges = None\\n self._orig_in_degree = dict()\\n self._orig_out_degree = dict()\",\n \"def update_node2edge(self):\\n self.node2edge = {e.child : e for e in self.edge}\\n childrenset = set(self.node2edge.keys())\\n rootset = set(e.parent for e in self.edge).difference(childrenset)\\n if len(rootset) > 1:\\n raise Warning(\\\"there should be a single root: \\\" + str(rootset))\\n if len(rootset) == 0:\\n raise Exception(\\\"there should be at least one root!\\\")\\n self.root = rootset.pop()\",\n \"def reset_edges(self):\\n super().reset_edges()\\n\\n # If we're in default state, notheing to rest\\n if self._modified_weighted_adj_matrices is None:\\n return\\n\\n # Degrees are reset, so we need to reset the original weight scaling\\n if self.scale_weights and not self.scaling_skipped:\\n self._scale_weights_to_degree()\\n self._generate_weighted_adj_matrices()\\n else:\\n # No weight scaling so just load prev values from cache\\n self.weighted_adj_matrices = {**self.weighted_adj_matrices, **self._modified_weighted_adj_matrices}\\n self._modified_weighted_adj_matrices = None\",\n \"def start_new_graph(self):\\n self.nodes = {}\\n self.reset_graph()\",\n \"def reset_tree(self):\\n self.root = None\\n self.action = None\\n self.dist_probability = None\",\n \"def disown(self):\\r\\n for apply_node in self.apply_nodes:\\r\\n del apply_node.fgraph\\r\\n del apply_node.deps\\r\\n for variable in self.variables:\\r\\n del variable.fgraph\\r\\n del variable.clients\\r\\n self.apply_nodes = set()\\r\\n self.variables = set()\\r\\n self.inputs = None\\r\\n self.outputs = None\",\n \"def to_undirected_graph(self):\\n visited = set() \\n G = Graph.Graph()\\n \\n for node in self.node_set:\\n \\n if node not in visited:\\n visited.add(node)\\n for i in self.suffix[node]:\\n G.add_edge(node, i)\\n \\n return G\",\n \"def reset(self):\\n\\t\\tself.graph = OrderedDict()\\n\\t\\tself.bottoms = OrderedDict()\\n\\t\\tself.output_shape = OrderedDict()\\n\\t\\tself.cur_tensor = None\\n\\t\\tself.cur_id = None\\n\\t\\tself.tmp_list = []\\n\\t\\tself.log_init()\",\n \"def clear(self):\\n self._nodes = { }\\n self._arcs = set()\",\n \"def __root(T: \\\"Graph\\\"):\\n T_copy = T.copy()\\n\\n # Leaves are removed from the copy untill 1 or 2 vertices remain\\n while len(T_copy.vertices) > 2:\\n vertices_to_remove = []\\n for v in T_copy.vertices:\\n if v.degree == 1:\\n vertices_to_remove.append(v)\\n for v in vertices_to_remove:\\n T_copy.del_vertex(v)\\n\\n root_labels = []\\n for v in T_copy.vertices:\\n root_labels.append(v.label)\\n\\n # From the original tree, the roots are returned\\n T_root = []\\n for v in T.vertices:\\n if v.label in root_labels:\\n T_root.append(v)\\n\\n return T_root\",\n \"def reset(self):\\n self.edges = None\\n self.chi = None\\n self.k = None\\n self.n_bins = None\\n self.classes = None\\n self.n_params = None\",\n \"def clear_nastran(self):\\n self.eid_map = {}\\n self.nid_map = {}\\n self.eid_to_nid_map = {}\\n self.element_ids = None\\n self.node_ids = None\",\n \"def clear(self):\\n self.root = _NGramMapNode()\\n self.size_freqs = dict()\\n self.ele_freqs = dict()\",\n \"def reset(self):\\n self.visited = set()\\n del self.targets[0]\",\n \"def relabel_nodes(graph: BaseGraph, mapping: Dict) -> None:\\n relabel_nodes(graph.graph, mapping, copy=False)\",\n \"def clear(self):\\n self.nodes = list()\\n self.inputs = list()\\n self.nodes += [self]\",\n \"def clean_edges(self):\",\n \"def clear_edges(infr):\\n for graph in infr.review_graphs.values():\\n graph.remove_edges_from(list(graph.edges()))\\n infr.graph.remove_edges_from(list(infr.graph.edges()))\\n infr.pos_redun_nids.clear()\\n infr.neg_redun_metagraph.clear()\\n infr.nid_to_errors.clear()\",\n \"def _reset_traversal_state(self):\\n for n in self.nodes.values():\\n n.reset_traversal_state()\",\n \"def reset_nn(self): # Clear current network\\n self.weights = np.zeros((p.num_rovers, self.n_weights))\\n self.in_layer = np.zeros((p.num_rovers, self.n_inputs))\\n self.hid_layer = np.zeros((p.num_rovers, self.n_nodes))\\n self.out_layer = np.zeros((p.num_rovers, self.n_outputs))\",\n \"def add_resets_edges(graph, start):\\n for node in graph.nodes:\\n neighbors = list(graph[node])\\n if neighbors == [node]:\\n graph.add_edge(node, start, label=\\\"RESET / \\\")\",\n \"def clear_node_id_terms(self):\\n pass\",\n \"def reset(self):\\n self.dims.clear()\\n self.xlabels.clear()\\n self.annotators.clear()\\n self._figTitle = None\\n self.tbmTitle = None\\n self._isSubplot = False\\n self._universal_xlabel = False\\n self._plotter = None\\n self.Nsp = 0\",\n \"def edge_subgraph(self, edges, relabel_nodes=False, output_device=None):\\n raise NotImplementedError(\\\"edge_subgraph is not implemented yet\\\")\",\n \"def create_unlabeled_subgraph(graph):\\n unlabeled_nodes = []\\n for (p, d) in graph.nodes(data=True):\\n if (d['leaning'] == 'Unknown'):\\n unlabeled_nodes.append(p)\\n return nx.subgraph(graph, unlabeled_nodes)\",\n \"def _clean_graph(self):\\n for entry_node in self._entry_nodes:\\n self._clean_graph_visit(entry_node.get_func_first_node(), {})\",\n \"def clear(self) -> None:\\n self.graph.clear()\",\n \"def reset(self):\\r\\n self.tree = KDTree()\\r\\n self.paint()\",\n \"def reset(cls):\\r\\n cls._ROOTS_BY_TYPE = {}\\r\\n cls._TYPES_BY_ROOT = {}\\r\\n cls._SEARCHED = set()\",\n \"def clean_local_memory(self):\\n self.namespaces = self._rdf_builder.namespaces\\n self.dataset = self._rdf_builder.dataset\\n\\n self.ontology_graph = self._rdf_builder.ontology_graph\\n self.instance_graph = self._rdf_builder.instance_graph\\n self.claim_graph = self._rdf_builder.claim_graph\\n self.perspective_graph = self._rdf_builder.perspective_graph\\n self.interaction_graph = self._rdf_builder.interaction_graph\",\n \"def clone_as_root(self) :\\n clone = deepcopy(self)\\n clone.parent = None\\n clone.path_length = 0\\n clone.previous_action = None\\n return clone\",\n \"def reset(self):\\n self._clusters = {}\\n self._clusters_val = {}\\n self._centroids = {}\\n self.store()\",\n \"def subgraph(self, nodes, relabel_nodes=False, output_device=None):\\n raise NotImplementedError(\\\"subgraph is not implemented yet\\\")\",\n \"def strip(self):\\n self.graph = None\\n self.session = None\\n\\n return self\",\n \"def restore_graph_ui(self):\\n if len(self._graph_copies) == 0:\\n print('No copies to restore!')\\n return\\n # the last made copy is restored in graph\\n self._graph = self._graph_copies.pop(-1)\",\n \"def reset_graph():\\n sess = tf.get_default_session()\\n if sess:\\n sess.close()\\n tf.reset_default_graph()\",\n \"def reset_graph():\\n sess = tf.get_default_session()\\n if sess:\\n sess.close()\\n tf.reset_default_graph()\",\n \"def reset_weights(self):\\n self.head.reset_weights()\",\n \"def clear(self):\\n self.root = None\",\n \"def _reset_topological_order(self):\\n self._topological_order = self._input_nodes[:]\\n self.sorted = False\",\n \"def clear_network(self):\\n\\n return self.alter_network(remove=list(self.network.edges))\",\n \"def refresh_metadata(self):\\n #self.node_index = None\\n #self.edge_index = None\\n #self._calc_edge_centers = False\\n #self._calc_cell_centers = False\\n #self._calc_vcenters = False\\n self._node_to_edges = None\\n self._node_to_cells = None\",\n \"def onnx_remove_node_unused(onnx_model, recursive=True, debug_info=None, **options):\\r\\n if debug_info is None:\\r\\n debug_info = [str(type(onnx_model)).rsplit(\\r\\n '.', maxsplit=1)[-1].strip(\\\"'>\\\")]\\r\\n else:\\r\\n debug_info = (debug_info +\\r\\n [str(type(onnx_model)).rsplit('.', maxsplit=1)[-1].strip(\\\"'>\\\")])\\r\\n\\r\\n if hasattr(onnx_model, 'graph'):\\r\\n return _apply_optimisation_on_graph(\\r\\n onnx_remove_node_unused, onnx_model,\\r\\n recursive=recursive, debug_info=debug_info,\\r\\n **options)\\r\\n\\r\\n graph = onnx_model\\r\\n data = {}\\r\\n valid = {}\\r\\n edges = {}\\r\\n\\r\\n for init in graph.initializer:\\r\\n data[init.name, 0] = init\\r\\n\\r\\n for node in graph.node:\\r\\n data[node.name, 1] = node\\r\\n for inp in node.input:\\r\\n data[inp, 0] = node\\r\\n edges[(inp, 0), (node.name, 1)] = node\\r\\n for out in node.output:\\r\\n data[out, 0] = node\\r\\n edges[(node.name, 1), (out, 0)] = node\\r\\n\\r\\n for out in graph.output:\\r\\n valid[out.name, 0] = True\\r\\n\\r\\n modif = 1\\r\\n while modif > 0:\\r\\n modif = 0\\r\\n for e1, e2 in edges: # pylint: disable=E1141\\r\\n if valid.get(e2, False) and not valid.get(e1, False):\\r\\n valid[e1] = True\\r\\n modif += 1\\r\\n\\r\\n new_nodes = [n for n in graph.node if (n.name, 1) in valid]\\r\\n new_inits = [n for n in graph.initializer if (n.name, 0) in valid]\\r\\n\\r\\n if recursive:\\r\\n # Handles subgraphs.\\r\\n for i in range(len(new_nodes)): # pylint: disable=C0200\\r\\n node = new_nodes[i]\\r\\n if node is None or not (node.attribute): # pylint: disable=C0325\\r\\n continue\\r\\n new_nodes[i] = _apply_remove_node_fct_node(\\r\\n onnx_remove_node_unused,\\r\\n node, recursive=True, debug_info=debug_info + [node.name])\\r\\n\\r\\n # Finally create the new graph.\\r\\n nodes = list(filter(lambda n: n is not None, new_nodes))\\r\\n graph = make_graph(nodes, onnx_model.name,\\r\\n onnx_model.input, onnx_model.output,\\r\\n new_inits)\\r\\n\\r\\n graph.value_info.extend(onnx_model.value_info) # pylint: disable=E1101\\r\\n return graph\",\n \"def reset(self):\\r\\n self.key = None\\r\\n self.value = None\\r\\n self.parent = None\\r\\n self.left_child = None\\r\\n self.right_child = None\\r\\n self.color = BLACK\\r\\n self.size_tree = 0\",\n \"def __deepcopy__(self):\\n return UndirectedGraph.extract_edge_induced_subgraph(self, lambda edge: True) # copy all edges\",\n \"def reset_equivalencies(self):\\n self._equivalencies = self._default_equivalencies\",\n \"def clear_name_labels(infr):\\n infr.print('clear_name_labels()', 1)\\n # make distinct names for all nodes\\n distinct_names = {node: -aid for node, aid in infr.get_node_attrs('aid').items()}\\n infr.set_node_attrs('name_label', distinct_names)\",\n \"def remove_identity_nodes(self):\\n nodes_to_remove = []\\n for node in self.model.nodes():\\n if node.op_type == \\\"Identity\\\":\\n if node.output[0] not in self.model.get_graphs_output_names():\\n self.model.replace_input_of_all_nodes(node.output[0], node.input[0])\\n nodes_to_remove.append(node)\\n\\n if nodes_to_remove:\\n self.model.remove_nodes(nodes_to_remove)\\n logger.info(f\\\"Removed {len(nodes_to_remove)} Identity nodes\\\")\",\n \"def reset_visited(self):\\n self.__visited = False\",\n \"def generate(self):\\n self.graph_repl = self.master.graph_repl\",\n \"def reinitialize(self):\\n if self.is_leaf():\\n self.__hash__(reinit=True)\\n return {self}, {self}\\n else:\\n children_leaves = set()\\n children_nodes = {self}\\n # iterating over the children\\n for child in self.child_nodes:\\n cur_child_leaves, cur_child_nodes = self.child_nodes[child].reinitialize()\\n children_leaves = children_leaves.union(cur_child_leaves)\\n children_nodes = children_nodes.union(cur_child_nodes)\\n # storing the sets for later use\\n self.__hash__(reinit=True)\\n self.leaves = children_leaves\\n self.nodes = children_nodes\\n return children_leaves, children_nodes\",\n \"def reset_weight_zero(self):\\n self.node_embedding = np.random.uniform(low=-0.5, high=0.5, size=(self.vocab_size, self.layer1_size)).astype(\\n np.float32)\\n self.context_embedding = np.zeros((self.vocab_size, self.layer1_size), dtype=np.float32)\\n\\n self.centroid = np.zeros((self.k, self.layer1_size), dtype=np.float32)\\n self.covariance_mat = np.zeros((self.k, self.layer1_size, self.layer1_size), dtype=np.float32)\\n self.inv_covariance_mat = np.zeros((self.k, self.layer1_size, self.layer1_size), dtype=np.float32)\\n self.pi = np.zeros((self.vocab_size, self.k), dtype=np.float32)\\n log.info(\\\"reset communities data| k: {}\\\".format(self.k))\",\n \"def clear(self):\\n self.mismatch_error = None\\n self.pt_outs = None\\n self._onnx_graph = None\\n self.upper_graph_info = None\\n self.lower_graph_info = None\",\n \"def unflatten(self): \\n self.assign(self.get_unflattened_circuit())\\n self._expr_map = None\",\n \"def defaultize(self):\\n if self.root is None:\\n genome.initialize(self)\\n self.root.defaultize()\",\n \"def uproot(self):\\n self.__root__ = self\\n return self\",\n \"def untangle_roots(self):\\n\\n for root in self.all_seed_roots:\\n root_queue = [root]\\n while root_queue:\\n for output_root in self.connect_roots(root_queue.pop(0)):\\n root_queue.append(output_root)\",\n \"def unfinalize(namespace='*'):\\n\\n utils.set_historical_importance(state=2)\\n\\n if namespace:\\n namespace += ':'\\n\\n attrs = ['visibility_CTL.jointsVis',\\n 'visibility_CTL.modelVis',\\n 'visibility_CTL.modelSelectable',\\n 'visibility_CTL.jointsSelectable']\\n\\n attrs += [namespace+'visibility_CTL.jointsVis',\\n namespace+'visibility_CTL.modelVis',\\n namespace+'visibility_CTL.modelSelectable',\\n namespace+'visibility_CTL.jointsSelectable']\\n\\n for attr in attrs:\\n if mc.objExists(attr):\\n mc.setAttr(attr, True)\\n\\n pickWalk.delete_tags()\\n mp = utils.ModelPanel()\\n\\n mp.set_joints_vis(1)\\n mp.set_jointXray_vis(1)\",\n \"def unisolvent_nodes(self):\\r\\n pass\",\n \"def _clear_node(self):\\n self._element = None\\n self._parent = None\\n self._leftchild = None\\n self._rightchild = None\\n self._height = None\",\n \"def _rewrite_unary_default(self, node: saldag.UnaryOpNode):\\n\\n par = next(iter(node.parents))\\n if node.is_reversible() and node.is_lower_boundary() and not par.is_root():\\n print(\\\"lower boundary\\\", node)\\n node.get_in_rel().stored_with = copy.copy(node.out_rel.stored_with)\\n node.is_mpc = False\",\n \"def reverse_graph(self) -> GraphInterface:\\n ans = DiGraph()\\n\\n nodes = self._graph.get_all_v() # {key: NodeData}\\n for key in nodes:\\n ans.add_node(key)\\n ans.get_node(key).tag = self._graph.get_node(key).tag\\n\\n for key in nodes:\\n out_edges = self._graph.all_out_edges_of_node(key)\\n for edge in out_edges:\\n e = out_edges.get(edge)\\n ans.add_edge(e.dest, e.src, e.weight)\\n\\n return ans\",\n \"def reset(self):\\n for c in self.children:\\n c.reset()\\n self.marked = False\",\n \"def reset(self):\\n self.current = self.root\\n env = self.env\\n obs, infos = env.reset()\\n obs = obs[obs.find(\\\"=\\\"):] # removes textworld legend\\n\\n return env, obs, infos\",\n \"def reset(self):\\n self.det_link_map = OrderedDict()\\n self.id_link_map = OrderedDict()\\n self.declarations_table = None\\n self.annotations_table = None\\n self.num_frames = 0\\n self.num_frames_by_uid = {}\\n self.num_frames_by_uid_pre_remove = {}\",\n \"def make_complete_graph(num_nodes):\\n graph = {}\\n for dummy_node in range(num_nodes):\\n graph[dummy_node] = set([dummy_x for dummy_x in range(num_nodes)])\\n graph[dummy_node].remove(dummy_node)\\n return graph\",\n \"def make_complete_graph(num_nodes):\\n graph = {}\\n for dummy_node in range(num_nodes):\\n graph[dummy_node] = set([dummy_x for dummy_x in range(num_nodes)])\\n graph[dummy_node].remove(dummy_node)\\n return graph\",\n \"def reset(self):\\n\\n self.fig.clear()\\n self.ax = self.fig.add_subplot(111)\\n self.hasLegend.set(False)\\n self.title(Graph.default_title)\\n # Lines is a list of DataSet objects. The user should take care to make\\n # DataSet names unique, as there is no error checking done by Graph. \\n # If a DataSet line is deleted by its formal name, Graph will delete the\\n # first line in the list that matches the name.\\n self.lines = {}\\n self.line_counter = 1\",\n \"def draw_graph(self):\\n\\t\\tif None in self.graph:\\n\\t\\t\\tdel self.graph[None]\\n\\n\\t\\tfor vs in self.graph.itervalues():\\n\\t\\t\\tto_delete = []\\n\\t\\t\\tfor i in xrange(len(vs)):\\n\\t\\t\\t\\tif vs[i] is None:\\n\\t\\t\\t\\t\\tto_delete.append(i)\\n\\n\\t\\t\\tfor i in reversed(to_delete):\\n\\t\\t\\t\\tdel vs[i]\\n\\n\\t\\tself.G=nx.Graph(self.graph)\\n\\n\\t\\tfor k,v in self.labels.iteritems():\\n\\t\\t\\tif v[:6] == 'Module':\\n\\t\\t\\t\\troot = k\\n\\t\\t\\t\\tbreak\\n\\n\\t\\treturn self.__dfs_plot(root)\",\n \"def deactivate_all_snodes():\\n for root_fb in FieldsBuilder._finalized_roots():\\n root_fb.deactivate_all()\",\n \"def forget_labels(labels_to_forget=\\\"none\\\"):\\n\\t\\t\\tassert labels_to_forget in {\\\"none\\\",\\\"originally unlabelled\\\",\\\"all\\\"}\\n\\t\\t\\tif labels_to_forget != \\\"none\\\":\\n\\t\\t\\t\\tif labels_to_forget == \\\"originally unlabelled\\\":\\n\\t\\t\\t\\t\\tself.train_labels___0_unlab__neg1_exclud=self.train_orig_labels.copy()\\n\\t\\t\\t\\telif labels_to_forget == \\\"all\\\":\\n\\t\\t\\t\\t\\tself.train_labels___0_unlab__neg1_exclud=np.zeros(self.num_train)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tassert False\\n\\t\\t\\t\\tself.bool_train_labelled=(self.train_labels___0_unlab__neg1_exclud>0)\\n\\t\\t\\t\\tself.bool_train_unlabelled=(self.train_labels___0_unlab__neg1_exclud==0)\\n\\t\\t\\t\\tself.bool_train_excluded=(self.train_labels___0_unlab__neg1_exclud<0)\\n\\t\\t\\t\\tself.num_train_labelled=sum(self.bool_train_labelled)\\n\\t\\t\\t\\tself.num_train_unlabelled=sum(self.bool_train_unlabelled)\\n\\t\\t\\t\\tself.num_train_excluded=sum(self.bool_train_excluded)\",\n \"def _internal_build(self):\\n self.nodes = self.__tree.Nodes()\\n self.edges = self.__tree.Edges()\\n self.augmentedEdges = {}\\n for key, val in self.__tree.AugmentedEdges().items():\\n self.augmentedEdges[key] = list(val)\\n self.root = self.__tree.Root()\\n\\n seen = set()\\n self.branches = set()\\n\\n # Find all of the branching nodes in the tree, degree > 1\\n # That is, they appear in more than one edge\\n for e1, e2 in self.edges:\\n if e1 not in seen:\\n seen.add(e1)\\n else:\\n self.branches.add(e1)\\n\\n if e2 not in seen:\\n seen.add(e2)\\n else:\\n self.branches.add(e2)\\n\\n # The nodes that are not branches are leaves\\n self.leaves = set(self.nodes.keys()) - self.branches\\n self.leaves.remove(self.root)\",\n \"def reset(self):\\n self.children.clear()\",\n \"def reset_pooling_layer(self):\\n self._semantic_decoder.reset_pooling_layer()\\n if self._instance_decoder is not None:\\n self._instance_decoder.reset_pooling_layer()\",\n \"def make_complete_graph(num_nodes):\\n complete_digraph = {}\\n if num_nodes > 0 and type(num_nodes) == int:\\n neighbors = set([idx for idx in range(num_nodes)])\\n for idx in range(num_nodes):\\n complete_digraph[idx] = neighbors.copy() #creates adjacency set\\n complete_digraph[idx].remove(idx) # pop out self-loop \\n return complete_digraph\",\n \"def reset (self):\\n self.__inScopeNamespaces = self.__initialScopeNamespaces\\n self.__inScopePrefixes = self.__initialScopePrefixes\\n self.__mutableInScopeNamespaces = False\\n self.__namespacePrefixCounter = 0\",\n \"def _reset(self):\\n self._set(\\\"_n_init_features\\\", None)\\n self._set(\\\"_n_output_features\\\", None)\\n self._set(\\\"_n_intervals\\\", None)\\n self._set(\\\"_mapper\\\", {})\\n self._set(\\\"_cpp_preprocessor\\\", None)\\n self._set(\\\"_fitted\\\", False)\",\n \"def clear(self):\\n while len(self.nodes) > 0:\\n self.nodes[0].remove()\\n\\n self.has_been_modified = False\",\n \"def _setup_graph_def(self):\\n raise NotImplementedError\",\n \"def destroy(self):\\n del self.nodes\\n self.nodes = {}\",\n \"def reset(self):\\r\\n self._root_dir = None\",\n \"def tearDown(self):\\n data_graph.update(\\\"CLEAR DEFAULT\\\")\",\n \"def upstream_structure(self):\\n structure_dict = {'edges': set(),\\n 'nodes': set()}\\n structure_dict = self._build_structure_dict(structure_dict)\\n return structure_dict\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.66198105","0.6407392","0.61415255","0.61093223","0.6048665","0.60347766","0.60298306","0.5988843","0.5949874","0.5943684","0.5910985","0.5874265","0.58275336","0.57994217","0.5747671","0.57045126","0.57044613","0.565234","0.56324726","0.5624728","0.56222004","0.56187963","0.5585501","0.55618304","0.5561007","0.55475235","0.5544825","0.55439115","0.55436563","0.54859316","0.5475382","0.5463628","0.5459803","0.5437075","0.5400913","0.5388431","0.53737456","0.5356454","0.53357154","0.5331465","0.5299187","0.52930355","0.5279607","0.52739865","0.5265378","0.5253438","0.5250912","0.5246694","0.522379","0.52145404","0.5212589","0.520542","0.5196414","0.5196414","0.5187049","0.51842666","0.51572734","0.5149203","0.51287454","0.5126616","0.5125969","0.51245004","0.5116785","0.5086907","0.5083947","0.50638825","0.50622916","0.50587225","0.50568914","0.5053218","0.5048021","0.5046479","0.50461334","0.50410587","0.5040982","0.50265765","0.5021406","0.50179535","0.5012174","0.501044","0.5005797","0.50015557","0.50005084","0.50005084","0.5000456","0.49955833","0.49905273","0.4988526","0.49869448","0.49859056","0.49823874","0.4979418","0.49766904","0.49745286","0.49657574","0.4964277","0.4962585","0.49579638","0.495575","0.49549565"],"string":"[\n \"0.66198105\",\n \"0.6407392\",\n \"0.61415255\",\n \"0.61093223\",\n \"0.6048665\",\n \"0.60347766\",\n \"0.60298306\",\n \"0.5988843\",\n \"0.5949874\",\n \"0.5943684\",\n \"0.5910985\",\n \"0.5874265\",\n \"0.58275336\",\n \"0.57994217\",\n \"0.5747671\",\n \"0.57045126\",\n \"0.57044613\",\n \"0.565234\",\n \"0.56324726\",\n \"0.5624728\",\n \"0.56222004\",\n \"0.56187963\",\n \"0.5585501\",\n \"0.55618304\",\n \"0.5561007\",\n \"0.55475235\",\n \"0.5544825\",\n \"0.55439115\",\n \"0.55436563\",\n \"0.54859316\",\n \"0.5475382\",\n \"0.5463628\",\n \"0.5459803\",\n \"0.5437075\",\n \"0.5400913\",\n \"0.5388431\",\n \"0.53737456\",\n \"0.5356454\",\n \"0.53357154\",\n \"0.5331465\",\n \"0.5299187\",\n \"0.52930355\",\n \"0.5279607\",\n \"0.52739865\",\n \"0.5265378\",\n \"0.5253438\",\n \"0.5250912\",\n \"0.5246694\",\n \"0.522379\",\n \"0.52145404\",\n \"0.5212589\",\n \"0.520542\",\n \"0.5196414\",\n \"0.5196414\",\n \"0.5187049\",\n \"0.51842666\",\n \"0.51572734\",\n \"0.5149203\",\n \"0.51287454\",\n \"0.5126616\",\n \"0.5125969\",\n \"0.51245004\",\n \"0.5116785\",\n \"0.5086907\",\n \"0.5083947\",\n \"0.50638825\",\n \"0.50622916\",\n \"0.50587225\",\n \"0.50568914\",\n \"0.5053218\",\n \"0.5048021\",\n \"0.5046479\",\n \"0.50461334\",\n \"0.50410587\",\n \"0.5040982\",\n \"0.50265765\",\n \"0.5021406\",\n \"0.50179535\",\n \"0.5012174\",\n \"0.501044\",\n \"0.5005797\",\n \"0.50015557\",\n \"0.50005084\",\n \"0.50005084\",\n \"0.5000456\",\n \"0.49955833\",\n \"0.49905273\",\n \"0.4988526\",\n \"0.49869448\",\n \"0.49859056\",\n \"0.49823874\",\n \"0.4979418\",\n \"0.49766904\",\n \"0.49745286\",\n \"0.49657574\",\n \"0.4964277\",\n \"0.4962585\",\n \"0.49579638\",\n \"0.495575\",\n \"0.49549565\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7510522"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13083,"cells":{"query":{"kind":"string","value":"Create a mask, that is a graphlike structure which can be thought of as a subgraph of universe. It holds only the references for known nodes and edges. This method create subgraph induced by its nodes."},"document":{"kind":"string","value":"def get_random_full_mask(self, size: int, breadth_first_preference: float = 0.5, from_root: bool = True) -> Mask:\n if from_root:\n g = self.root_graph\n else:\n g = self\n nodes = set(random.sample(g.nodes, 1))\n while len(nodes) < size:\n to_extend = {edge.node_to for node in nodes\n for edge in g.edges_from(node)\n if random.random() < breadth_first_preference}\n to_extend.update({edge.node_from for node in nodes\n for edge in g.edges_to(node)\n if random.random() < breadth_first_preference})\n if len(to_extend) > size - len(nodes):\n to_extend = set(random.sample(to_extend, k=size - len(nodes)))\n nodes.update(to_extend)\n edges = {edge for edge in g.edges if edge.node_from in nodes and edge.node_to in nodes}\n return Mask(nodes, edges, g)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def subgraph_mask(self, size):\n init_matrix = np.random.randn(size,size)\n Tcs = csgraph.minimum_spanning_tree(init_matrix)\n mask_matrix = Tcs.toarray()\n return mask_matrix","def __init__(self, nodes: Set[Node], edges: Set[Edge]):\n super().__init__()\n self.nodes = nodes\n for edge in edges:\n self.add_edge(edge)\n self.leaves = {node for node in self.nodes if self.degree_out(node) == 0}\n root_nodes = self.nodes - self.leaves\n root_edges = {edge for edge in self.edges if edge.node_to not in self.leaves}\n self.root_graph = Mask(root_nodes, root_edges, self)","def _build_mask(self, xg, yg):\n\n # 1. create mask based on meshes\n points = np.vstack((xg.flatten(), yg.flatten())).T\n\n # 2. extract edge points using el_pos\n edge_points = self.node[np.arange(16)]\n path = Path(edge_points, closed=False)\n mask = path.contains_points(points)\n\n return mask","def create_unlabeled_subgraph(graph):\n unlabeled_nodes = []\n for (p, d) in graph.nodes(data=True):\n if (d['leaning'] == 'Unknown'):\n unlabeled_nodes.append(p)\n return nx.subgraph(graph, unlabeled_nodes)","def create_labeled_subgraph(graph):\n labeled_nodes = []\n for (p, d) in graph.nodes(data=True):\n if (d['leaning'] == 'R') or (d['leaning'] == 'D'):\n labeled_nodes.append(p)\n return nx.subgraph(graph, labeled_nodes)","def create_sub_graph_copy(graph: nx.MultiDiGraph, nodes_to_extract: list):\n return graph.subgraph(nodes_to_extract).copy()","def __deepcopy__(self):\n return UndirectedGraph.extract_edge_induced_subgraph(self, lambda edge: True) # copy all edges","def islands(\n self,\n corners=False\n ):\n\n if self.linked_mask == None:\n print \"Island assignment requires a mask.\"\n return\n \n structure = (Struct(\n \"simple\", \n ndim=self.linked_mask.data.ndim, \n corners=corners)).struct\n\n labels, nlabels = ndimage.label(self.linked_mask.data,\n structure=structure)\n \n self.data = labels\n self.nclouds = nlabels\n self.slices = ndimage.find_objects(self.data)","def _create_reference_connectivity_graph(self):\n #take the self._residue_graph and create a replicate (without the misc attributes) with the atoms_with_positions\n _reference_connectivity_graph = nx.Graph()\n atoms_with_positions = set(self._atoms_with_positions)\n\n #iterate over all the bonds\n for bond in self._residue_graph.edges():\n if set(bond).issubset(atoms_with_positions):\n #if both of the atoms in the bond are in atoms_with_positions, we can add the atoms/bonds to the reference\n _reference_connectivity_graph.add_edge(*bond)\n\n return _reference_connectivity_graph","def build_fpn_mask_graph(rois, feature_maps, image_meta,\n pool_size, num_classes, train_bn=True):\n # ROI Pooling\n # Shape: [batch, boxes, pool_height, pool_width, channels]\n x = PyramidROIAlign([pool_size, pool_size],\n name=\"roi_align_mask\")([rois, image_meta] + feature_maps)\n\n # Conv layers\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv1\")(x)\n x = KL.TimeDistributed(BatchNorm(),\n name='mrcnn_mask_bn1')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv2\")(x)\n x = KL.TimeDistributed(BatchNorm(),\n name='mrcnn_mask_bn2')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv3\")(x)\n x = KL.TimeDistributed(BatchNorm(),\n name='mrcnn_mask_bn3')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv4\")(x)\n x = KL.TimeDistributed(BatchNorm(),\n name='mrcnn_mask_bn4')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2DTranspose(256, (2, 2), strides=2, activation=\"relu\"),\n name=\"mrcnn_mask_deconv\")(x)\n x = KL.TimeDistributed(KL.Conv2D(num_classes, (1, 1), strides=1, activation=\"sigmoid\"),\n name=\"mrcnn_mask\")(x)\n return x","def re_root(self, omit_edge_label: List[str]):\n self.leaves = {node for node in self.nodes\n if any([edge.label in omit_edge_label for edge in self.edges_to(node)])}\n root_nodes = self.nodes - self.leaves\n root_edges = {edge for edge in self.edges if edge.node_to in root_nodes and edge.node_from in root_nodes}\n self.root_graph = Mask(root_nodes, root_edges, self)","def subgraph(self, nodes, relabel_nodes=False, output_device=None):\n raise NotImplementedError(\"subgraph is not implemented yet\")","def get_contest_mask():\n return createmaskdf(\"data/fcstrodeo_nctemplates/fcstrodeo_mask.nc\")","def test(shape=(1000,2000)):\n mask = Mask()\n mask.addCircle(400,300,250)\n mask.subtractCircle(400,300,150)\n mask.addRectangle(350,250,1500,700)\n plt.imshow( mask.getMask(shape) )\n return mask","def test_differentiable__mask_connectivity(self):\n data = random_graph_data(5, 4, 3)\n print(data.size)","def subgraph(self, subset_dict: Dict[NodeType, Tensor]) -> 'HeteroData':\n data = copy.copy(self)\n subset_dict = copy.copy(subset_dict)\n\n for node_type, subset in subset_dict.items():\n for key, value in self[node_type].items():\n if key == 'num_nodes':\n if subset.dtype == torch.bool:\n data[node_type].num_nodes = int(subset.sum())\n else:\n data[node_type].num_nodes = subset.size(0)\n elif self[node_type].is_node_attr(key):\n data[node_type][key] = value[subset]\n else:\n data[node_type][key] = value\n\n for edge_type in self.edge_types:\n src, _, dst = edge_type\n\n src_subset = subset_dict.get(src)\n if src_subset is None:\n src_subset = torch.arange(data[src].num_nodes)\n dst_subset = subset_dict.get(dst)\n if dst_subset is None:\n dst_subset = torch.arange(data[dst].num_nodes)\n\n edge_index, _, edge_mask = bipartite_subgraph(\n (src_subset, dst_subset),\n self[edge_type].edge_index,\n relabel_nodes=True,\n size=(self[src].num_nodes, self[dst].num_nodes),\n return_edge_mask=True,\n )\n\n for key, value in self[edge_type].items():\n if key == 'edge_index':\n data[edge_type].edge_index = edge_index\n elif self[edge_type].is_edge_attr(key):\n data[edge_type][key] = value[edge_mask]\n else:\n data[edge_type][key] = value\n\n return data","def fpn_mask_graph(rois, feature_maps, image_meta,\n pool_size, num_classes, train_bn=True):\n # ROI Pooling\n # Shape: [batch, boxes, pool_height, pool_width, channels]\n x = modellib.PyramidROIAlign([pool_size, pool_size],\n name=\"roi_align_mask\")([rois, image_meta] + feature_maps)\n\n # Conv layers\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv1\")(x)\n x = KL.TimeDistributed(modellib.BatchNorm(),\n name='mrcnn_mask_bn1')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv2\")(x)\n x = KL.TimeDistributed(modellib.BatchNorm(),\n name='mrcnn_mask_bn2')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv3\")(x)\n x = KL.TimeDistributed(modellib.BatchNorm(),\n name='mrcnn_mask_bn3')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\"same\"),\n name=\"mrcnn_mask_conv4\")(x)\n x = KL.TimeDistributed(modellib.BatchNorm(),\n name='mrcnn_mask_bn4')(x, training=train_bn)\n x = KL.Activation('relu')(x)\n\n x = KL.TimeDistributed(KL.Conv2DTranspose(256, (2, 2), strides=2, activation=\"relu\"),\n name=\"mrcnn_mask_deconv\")(x)\n x = KL.TimeDistributed(KL.Conv2D(1, (1, 1), strides=1, activation=\"sigmoid\"),\n name=\"mrcnn_mask\")(x)\n # Duplicate output for fg/bg detections\n x = KL.Concatenate(axis=-1)([x for i in range(num_classes)])\n return x","def generate(self, subset=False, indices=[]):\n\n F = self.faces\n n = F.max()+1\n\n rows = np.concatenate([F[:, 0], F[:, 0],\n F[:, 1], F[:, 1], \n F[:, 2], F[:, 2]])\n\n cols = np.concatenate([F[:, 1], F[:, 2], \n F[:, 0], F[:, 2], \n F[:, 0], F[:, 1]])\n\n combos = np.column_stack([rows, cols])\n\n [_, idx] = np.unique(combos, axis=0, return_index=True)\n A = sparse.csr_matrix((np.ones(len(idx)), (combos[idx, 0], combos[idx, 1])), shape=(n, n))\n\n\n G = nx.from_scipy_sparse_matrix(A)\n\n if subset:\n nodes = indices\n else:\n nodes = G.nodes\n\n adj = {node: [] for node in nodes}\n for node in nodes:\n for j in G.neighbors(n=node):\n adj[node].append(j)\n adj[node].sort()\n \n self.adj = adj","def mask_neighbors(self, mask, rad=9, ptrn='r'):\n return um.mask_neighbors(mask, rad, ptrn)","def __generate_mask(self):\n mask = np.concatenate([np.ones(len(self.fixed[0])),\n np.zeros(self.num_points),\n np.ones(len(self.fixed[1]))])\n return mask","def _build_graph_general(self): \n\n #Find a canonical coloring scheme\n #Each node has a color that is determined by the non-mapped aspects\n nodecolors=set()\n for nl in self.net.iter_node_layers():\n nodecolors.add(self._slice_node_layer_not_allowed(nl))\n nodecolors_sorted=sorted(list(nodecolors))\n del nodecolors\n self._assert_full_order(nodecolors_sorted)\n self.colormap=dict( ((color,colorid) for colorid,color in enumerate(nodecolors_sorted) ))\n\n #each aux node has a color that is determined by the aspect\n self.auxcolormap=dict( ((auxcolor, auxcolorid+len(self.colormap)) for auxcolorid,auxcolor in enumerate(sorted(self.asp)) ) )\n\n\n #Add the underlying network\n #node-layers:\n for nl in self.net.iter_node_layers():\n nlid=self._get_node_id(nl)\n color=self._slice_node_layer_not_allowed(nl)\n colorid=self.colormap[color]\n self.add_node(nlid,colorid)\n\n #edges between node-layers:\n for nl1 in self.net.iter_node_layers():\n for nl2 in self.net[nl1]:\n nl1id=self._get_node_id(nl1)\n nl2id=self._get_node_id(nl2)\n self.add_link(nl1id,nl2id)\n\n\n #Add the auxiliary nodes and edges\n #add the aux nodes\n for a in self.asp:\n for elayer in self.net.slices[a]:\n auxid=self._get_auxnode_id( (a,elayer) )\n auxcolorid=self.auxcolormap[a]\n self.add_node(auxid,auxcolorid)\n \n #add the aux edges\n for nl in self.net.iter_node_layers():\n for a in self.asp:\n nlid=self._get_node_id(nl)\n auxid=self._get_auxnode_id( (a,nl[a]) )\n self.add_link(nlid,auxid)","def copy(self):\n \n \n G = DiGraph()\n G.node_set = copy.deepcopy(self.node_set)\n G.prefix = copy.deepcopy(self.prefix)\n G.suffix = copy.deepcopy(self.suffix)\n G.num_node = copy.deepcopy(self.num_node)\n G.edges = copy.deepcopy(self.edges)\n \n return G","def mask(self):","def create_mask(shape):\n return np.zeros(shape).astype(bool)","def _create_mask_part(\n self,\n shape: List[int],\n overlap: List[int],\n device: torch.device,\n dtype: torch.dtype = torch.float,\n ) -> torch.Tensor:\n assert len(shape) == 4\n zeros_size, lin_size = overlap[0:2]\n ones_size = shape[3] - (zeros_size + lin_size)\n sizes = (zeros_size, lin_size, ones_size)\n mask_parts = [\n torch.zeros(sizes[0], device=device, dtype=dtype),\n torch.linspace(0, 1, sizes[1], device=device, dtype=dtype),\n torch.ones(sizes[2], device=device, dtype=dtype),\n ]\n return (\n torch.cat(mask_parts, 0)\n .repeat(shape[2], 1)\n .repeat(shape[1], 1, 1)\n .unsqueeze(0)\n )","def createMaskDictionary(self):\n try:\n self.maskMap = dict(list(zip(self.inds,list(range(len(self.inds))))))\n self.maskSet = set(self.inds)\n except Exception as error:\n print(\"failed in createMaskDictionary\", error)","def create_mask(frame):\n \n # detect ridges\n ridges = enhance_ridges(frame)\n\n # threshold ridge image\n thresh = filters.threshold_otsu(ridges)\n thresh_factor = 1.1\n prominent_ridges = ridges > thresh_factor*thresh\n prominent_ridges = morphology.remove_small_objects(prominent_ridges, min_size=128)\n\n # the mask contains the prominent ridges\n mask = morphology.convex_hull_image(prominent_ridges)\n mask = morphology.binary_erosion(mask, disk(10))\n return mask","def subgraph(self, name):\n\n self._compiled = None\n sub = Graph()\n self.graph[name] = sub\n return sub","def mask(self, mask):\n ds_out = self._obj\n for var in self.vars:\n ds_out[var] = ds_out[var].raster.mask(mask)\n return ds_out","def generate_effective_mask(self, mask_size: tuple, polygons_ignore):\n mask = np.ones(mask_size, dtype=np.uint8)\n\n for poly in polygons_ignore:\n instance = poly.astype(np.int32).reshape(1, -1, 2)\n cv2.fillPoly(mask, instance, 0)\n\n return mask","def mask(self, mask):\n return MaskedDistribution(self, mask)","def clone(self):\n cloned = Graph()\n for v in self.vertices:\n cloned.vertices[v] = self.vertices[v].clone()\n return cloned","def mask_nodata(self):\n ds_out = self._obj\n for var in self.vars:\n ds_out[var] = ds_out[var].raster.mask_nodata()\n return ds_out","def copy(self):\n cls = self.__class__\n new_graph = cls.__new__(cls)\n new_graph._nodes = self._nodes[:]\n new_graph._node_wip = self._node_wip[:]\n new_graph._edges = self._edges[:]\n if self._sorted_nodes:\n new_graph._sorted_nodes = self._sorted_nodes[:]\n else:\n new_graph._sorted_nodes = None\n new_graph.predecessors = {}\n for key, val in self.predecessors.items():\n new_graph.predecessors[key] = self.predecessors[key][:]\n new_graph.successors = {}\n for key, val in self.successors.items():\n new_graph.successors[key] = self.successors[key][:]\n return new_graph","def to_undirected_graph(self):\n visited = set() \n G = Graph.Graph()\n \n for node in self.node_set:\n \n if node not in visited:\n visited.add(node)\n for i in self.suffix[node]:\n G.add_edge(node, i)\n \n return G","def identity_mask_propagation(nx_node, nx_graph):\n input_masks = get_input_masks(nx_node, nx_graph)\n assert len(input_masks) == 1\n nx_node[\"input_masks\"] = input_masks\n nx_node[\"output_mask\"] = input_masks[0]","def check_subgraph_for_data_mask_optimization(args: dict) -> bool:\n whitelist = {\n \"drop_dimension\",\n \"filter_bands\",\n \"filter_bbox\",\n \"filter_spatial\",\n \"filter_temporal\",\n \"load_collection\",\n }\n\n children_node_types = flatten_children_node_types(args[\"data\"])\n # If children_node_types exists only out of whitelisted nodes, an intersection should have no effect.\n if len(children_node_types.intersection(whitelist)) != len(children_node_types):\n return False\n\n data_children_node_names = flatten_children_node_names(args[\"data\"])\n mask_children_node_names = flatten_children_node_names(args[\"mask\"])\n if not data_children_node_names.isdisjoint(mask_children_node_names):\n # To avoid an issue in integration tests:\n _log.info(\"Overlap between data and mask node. Will not pre-apply mask on load_collections.\")\n return False\n\n return True","def identity_mask_propagation(nx_node, nx_graph):\n input_masks = get_input_masks(nx_node, nx_graph)\n assert len(input_masks) == 1\n nx_node['input_masks'] = input_masks\n nx_node['output_mask'] = input_masks[0]","def project(B,nodes,create_using=None):\n\n if create_using==None:\n create_using=networkx.Graph()\n\n G=networkx.empty_graph(0,create_using)\n\n for v in nodes:\n G.add_node(v)\n for nbr in B[v]:\n G.add_edges_from([(v,u) for u in B[nbr] if u!=v])\n return G","def build_mask(mask, unused_features_positions):\n\tfinal_mask = mask.tolist()\n\n\tfor i in range(len(unused_features_positions)):\n\t\tif not unused_features_positions[i]:\n\t\t\tfinal_mask.insert(i, False)\n\n\treturn final_mask","def make_initial_mask(model):\n mask = Mask()\n prunable_layers = utils.prunable_layers(model)\n for module in prunable_layers:\n mask[module] = torch.ones(list(model.state_dict()[module].shape))\n return mask","def edge_subgraph(self, edges, relabel_nodes=False, output_device=None):\n raise NotImplementedError(\"edge_subgraph is not implemented yet\")","def create_pathway_mask(feature_list, dict_pathway, add_missing=True, fully_connected=True, to_tensor=False):\n assert type(dict_pathway) == OrderedDict\n p_mask = np.zeros((len(feature_list), len(dict_pathway)))\n for j, k in enumerate(dict_pathway.keys()):\n for i in range(p_mask.shape[0]):\n if feature_list[i] in dict_pathway[k]:\n p_mask[i,j] = 1.\n if add_missing:\n n = 1 if type(add_missing)==bool else add_missing\n # Get non connected genes\n if not fully_connected:\n idx_0 = np.where(np.sum(p_mask, axis=1)==0)\n vec = np.zeros((p_mask.shape[0],n))\n vec[idx_0,:] = 1.\n else:\n vec = np.ones((p_mask.shape[0], n))\n p_mask = np.hstack((p_mask, vec))\n if to_tensor:\n p_mask = torch.Tensor(p_mask)\n return p_mask","def atlas6():\n\n Atlas = graph_atlas_g()[0:208] # 208\n # remove isolated nodes, only connected graphs are left\n U = nx.Graph() # graph for union of all graphs in atlas\n for G in Atlas:\n zerodegree = [n for n in G if G.degree(n) == 0]\n for n in zerodegree:\n G.remove_node(n)\n U = nx.disjoint_union(U, G)\n\n # iterator of graphs of all connected components\n C = (U.subgraph(c) for c in nx.connected_components(U))\n\n UU = nx.Graph()\n # do quick isomorphic-like check, not a true isomorphism checker\n nlist = [] # list of nonisomorphic graphs\n for G in C:\n # check against all nonisomorphic graphs so far\n if not iso(G, nlist):\n nlist.append(G)\n UU = nx.disjoint_union(UU, G) # union the nonisomorphic graphs\n return UU","def di_subgraph(self, nbunch):\n\t\t\n\t\t# create new subgraph.\n\t\tg = nx.DiGraph()\n\t\t\n\t\t# add edges and nodes.\n\t\tg.add_edges_from( self.edges(nbunch=nbunch) )\n\t\t\n\t\treturn g","def create_subbasin_graph():\n subbasin_to_downstream = pd.read_csv(module_dir + '/../data/simulations_shervan/test.rvh', sep='\\s+', skiprows=7, nrows=724, names=['subbasin', 'downstream_subbasin'], usecols=[1,2])\n subbasin_to_downstream['subbasin'] = subbasin_to_downstream['subbasin']\n subbasin_to_downstream['downstream_subbasin'] = 'sub' + subbasin_to_downstream['downstream_subbasin'].astype(str)\n subbasin_to_downstream['edge'] = 1\n\n for subbasin in subbasin_to_downstream['subbasin'].unique():\n is_sink = 1 if len(subbasin_to_downstream[(subbasin_to_downstream['subbasin'] == subbasin) & subbasin_to_downstream['edge'] == 1]) == 0 else 0\n subbasin_to_downstream = subbasin_to_downstream.append({'subbasin': subbasin, 'downstream_subbasin': subbasin, 'edge': is_sink}, ignore_index=True)\n subbasin_to_downstream = subbasin_to_downstream.append({'subbasin': 'sub-1', 'downstream_subbasin': 'sub-1', 'edge': 1}, ignore_index=True)\n \n adj = subbasin_to_downstream.pivot(index='subbasin', columns='downstream_subbasin', values='edge').fillna(0) \n adj = adj.sort_index(axis=0).sort_index(axis=1)\n \n G = nx.from_numpy_matrix(adj.values, parallel_edges=False, create_using=nx.DiGraph())\n label_mapping = dict(zip(range(len(adj.values)), adj.index))\n G = nx.relabel_nodes(G, label_mapping)\n \n return G","def build_drop_fullgraphs(self, do_subgraph=False, graph_lib='pygraphviz'):\n if 'pygraphviz' == graph_lib:\n G = pgv.AGraph(strict=True, directed=True)\n else:\n G = nx.Graph()\n do_subgraph = False\n subgraph_dict = defaultdict(list) # k - node-ip, v - a list of graph nodes\n oid_gnid_dict = dict()\n\n for i, oid in enumerate(self.pg_spec.keys()):\n oid_gnid_dict[oid] = str(i)\n logger.info(\"oid to gid mapping done\")\n\n for dropspec in self.pg_spec.itervalues():\n gid = oid_gnid_dict[dropspec['oid']]\n ip = dropspec['node']\n subgraph_dict[ip].append(gid)\n if (dropspec['type'] == 'app'):\n G.add_node(gid, shape='rect', label='')#, fixedsize=True, hight=.05, width=.05)\n elif (dropspec['type'] == 'plain'): #parallelogram\n G.add_node(gid, shape='circle', label='')#, fixedsize=True, hight=.05, width=.05)\n logger.info(\"Graph nodes added\")\n\n for dropspec in self.pg_spec.itervalues():\n gid = oid_gnid_dict[dropspec['oid']]\n if (dropspec['type'] == 'app'):\n ds_kw = 'outputs' #down stream key word\n elif (dropspec['type'] == 'plain'):\n ds_kw = 'consumers'\n else:\n ds_kw = 'None'\n if (ds_kw in dropspec):\n for doid in dropspec[ds_kw]:\n G.add_edge(gid, oid_gnid_dict[doid])\n logger.info(\"Graph edges added\")\n\n if (do_subgraph):\n for i, subgraph_nodes in enumerate(subgraph_dict.values()):\n # we don't care about the subgraph label or rank\n subgraph = G.add_subgraph(subgraph_nodes, label='%d' % i, name=\"cluster_%d\" % i, rank=\"same\")\n subgraph.graph_attr['rank']='same'\n logger.info(\"Subgraph added\")\n\n return G","def create_logits_mask_by_first_edge_graph(edge_indexes, num_edge, nvec):\n # find first edge\n # adj matrix of graphs\n # adj_mat = nx.to_numpy_matrix(graph, nodelist=range(nvec))[None]\n\n # bs = adj_mats.shape[0]\n # total_mask = []\n max_edge = edge_indexes.shape[0]\n total_mask = np.zeros(shape=(1, max_edge), dtype=np.int8)\n\n\n # edges = edge_indexes[:num_edge]\n # edges = np.where(adj_mats[i, :, :] > 0)\n\n # max_edge = max(max_edge, num_edges)\n # mask = np.zeros(shape=(1, max_edge), dtype=np.int8)\n all_half_edges = edge_indexes[:num_edge // 2] # only use the directed edge (a->b), not (b->a) # location[np.where(location[:, 0] < location[:, 1])[0]]\n all_valid_edges = edge_indexes[:num_edge] # only use the directed edge (a->b), not (b->a) # location[np.where(location[:, 0] < location[:, 1])[0]]\n\n # restore adj matrix\n rawobs = np.zeros(shape=(nvec, nvec), dtype=np.int8)\n for edge in all_valid_edges:\n rawobs[edge[0], edge[1]] = 1 # edge is an ndarray (2,), we cannot index using rawobs[edge] (is array with shape (2, 15))\n#\n for idx_1, edge_1 in enumerate(all_half_edges):\n encoded_edge_1 = idx_1\n # check if they are one-hop connected\n\n mask = np.zeros(shape=(max_edge,), dtype=np.int8)\n for idx_2, edge_2 in enumerate(all_valid_edges):\n\n fail_cond = edge_2[0] in edge_1 or edge_2[1] in edge_1 or\\\n int(rawobs[edge_2[0], edge_1[0]]) + int(rawobs[edge_2[0], edge_1[1]]) + \\\n int(rawobs[edge_2[1], edge_1[0]]) + int(rawobs[edge_2[1], edge_1[1]]) > 0\n\n mask[idx_2] = not fail_cond\n\n total_mask[0, encoded_edge_1] = mask.any()\n\n\n return total_mask","def generate_subclass_mask(mask_image,\n subclasses=(1, 3)):\n mask_shape = mask_image.shape\n sub_mask = generate_image(mask_shape[0], mask_shape[1], color=0)\n if mask_image.ndim == 2:\n gray_mask_image = mask_image[:, :]\n else:\n gray_mask_image = mask_image[:, :, 0]\n \n if isinstance(subclasses, (list, tuple)):\n if len(subclasses) == 2:\n keep_bool = np.logical_or(gray_mask_image == subclasses[0], gray_mask_image == subclasses[1])\n else:\n keep = []\n for subclass in subclasses:\n keep.append(gray_mask_image == subclass)\n\n keep_bool = np.logical_or.reduce(tuple(keep))\n else:\n keep_bool = (gray_mask_image == subclasses)\n\n sub_mask[keep_bool] = 1\n\n return sub_mask","def create_mask(neurons: list):\n\n return np.zeros_like(neurons[0])","def extract_node_induced_subgraph(self, predicate):\n # construct the filtered nodeset\n nodeset = {node.produce_duplicate_disconnected_node() for node in self.get_nodeset() if predicate(node)}\n\n G_prime = UndirectedGraph(nodeset) # create a new subgraph\n\n for edge in self.get_edges(): # for every edge in the original graph\n # if the first incident node is in the graph\n if edge.get_first_incident_node().get_name() in G_prime.get_node_names():\n # if the second incident node is also in the graph\n if edge.get_second_incident_node().get_name() in G_prime.get_node_names():\n # add the edge to the subgraph\n G_prime = UndirectedGraph.__induced_subgraph_helper(G_prime, edge)\n return G_prime # return the subgraph","def get_mask(self, shape):\n h, w = shape[0:2]\n y, x = np.mgrid[:h, :w]\n points = np.transpose((x.ravel(), y.ravel()))\n\n mask = _nxutils_points_inside_poly(points, self.verts)\n #mask = nxutils.points_inside_poly(points, self.verts)\n return mask.reshape(h, w)","def compute_masks_for_splits(\n graph):\n masks = {}\n num_nodes = graph.num_nodes()\n for split, split_nodes in zip(\n ['train', 'validation', 'test'],\n [graph.train_nodes, graph.validation_nodes, graph.test_nodes]):\n split_mask = np.zeros(num_nodes, dtype=bool)\n split_mask[split_nodes] = True\n masks[split] = split_mask\n return masks","def from_analysis(cls, analysis, from_node=None):\n obj = cls()\n if not from_node:\n from_node = analysis.best_node()\n\n obj._stock = from_node.state.stock\n actions, nodes = analysis.search_tree.route_to_node(from_node)\n unique_mols = {}\n\n root_mol = nodes[0].state.mols[0]\n obj.root = root_mol.make_unique()\n unique_mols[id(root_mol)] = obj.root\n obj.graph.add_node(obj.root)\n\n for child, action in zip(nodes[1:], actions):\n obj._add_bipartite(child, action, unique_mols)\n\n obj._find_repeating_patterns()\n return obj","def extract_edge_induced_subgraph(self, predicate):\n # initialize the new nodeset as sets containing disconnected copies of the original nodes\n nodeset = {node.produce_duplicate_disconnected_node() for node in self.get_nodeset()}\n\n # create a null graph using the nodeset constructed above\n G_prime = UndirectedGraph(nodeset)\n\n # for every edge in the original graph\n for edge in self.get_edges():\n if predicate(edge): # if the edge is not filtered out\n G_prime = UndirectedGraph.__induced_subgraph_helper(G_prime, edge)\n\n return G_prime # return the subgraph","def subnetwork(self, node_list):\n return Network(adjacency=self.internal_adjacency(node_list),\n directed=self.directed,\n node_weights=self.node_weights[node_list],\n silence_level=self.silence_level)","def copy(self, new=True):\n return UndirectedGraph(self._nodes, self._edges)","def copy(self):\n return AncestralGraph(self.nodes, self.directed, self.bidirected, self.undirected)","def createMaskVariable(self, product, variable_name):\r\n\r\n mask_variable_dict = {'name': variable_name,\r\n 'dtype': None,\r\n 'vtype': 'mask',\r\n 'units': None,\r\n 'ndims': None,\r\n 'shape': None}\r\n\r\n mask_variable = Variable(mask_variable_dict)\r\n\r\n return mask_variable","def mkNetCDF_mask4CVAO_African_nest(res='2x2.5', invert_mask=False,\n regrid21x1=True):\n import cartopy.crs as ccrs\n import matplotlib.pyplot as plt\n import xesmf as xe\n ds = AC.get_LWI_map(res=res, rtn_ds=True)\n ds = ds.transpose('lon', 'lat')\n var2use = 'LWI'\n # Get mask\n m = AC.get_CVAO_Africa_nest_Masked(res=res)\n # Name to save as\n if regrid21x1:\n res = '1x1'\n savename = 'ARNA_CVAO_African_nest_{}'.format(res)\n vals = ds[var2use].values\n # Change mask values\n if invert_mask:\n vals = np.where(m, vals, 0)\n vals = np.where(~m, vals, 1)\n ds[var2use].values = vals\n savename += '_inverted'\n ExtraStr = ' inverted'\n else:\n vals = np.where(~m, vals, 0)\n vals = np.where(m, vals, 1)\n ds[var2use].values = vals\n ExtraStr = ''\n # Only consider variable of interest\n ds = ds[[var2use]]\n\n # Plot up without mask present\n AC.quick_map_plot(ds, var2plot=var2use, savename=savename)\n plt.title(savename)\n\n # --- Add time to ds\n # Include a time dimension to meet COARDS\n try:\n ds = ds.expand_dims('time', axis=0)\n except ValueError:\n pass\n # Update Namings\n Var2SaveAs = 'MASK'\n ds = ds.rename({var2use: Var2SaveAs})\n var2use = Var2SaveAs\n # make sure ordering meets COARDS\n ds = ds.transpose('time', 'lat', 'lon')\n # --- Regrid\n if regrid21x1:\n # Regrid to use the same grid as the EMEP data (if the 2x2.5 fails)\n Fstr = get_local_folder('HEMCO_data')\n Fstr += '/MASKS/v2018-09/EMEP_mask.geos.1x1.20151222.nc'\n dsREF = xr.open_dataset(Fstr)\n # Create a dataset to re-grid into\n ds_out = xr.Dataset({\n 'lat': (['lat'], dsREF['lat']),\n 'lon': (['lon'], dsREF['lon']),\n })\n # Create a regidder (to be reused )\n regridder = xe.Regridder(ds, ds_out, 'bilinear', reuse_weights=True)\n # Loop and regrid variables\n ds_l = []\n for var_ in [var2use]:\n # Create a dataset to re-grid into\n ds_out = xr.Dataset({\n 'lat': (['lat'], dsREF['lat']),\n 'lon': (['lon'], dsREF['lon']),\n })\n # Get a DataArray\n dr = ds[var_] # .to_array()\n # build regridder\n dr_out = regridder(dr)\n # Important note: Extra dimensions must be on the left, i.e. (time, lev, lat, lon) is correct but (lat, lon, time, lev) would not work. Most data sets should have (lat, lon) on the right (being the fastest changing dimension in the memory). If not, use DataArray.transpose or numpy.transpose to preprocess the data.\n # exactly the same as input\n# xr.testing.assert_identical(dr_out['time'], dr['time'])\n # Save variable\n ds_l += [dr_out]\n # Combine variables\n dsN = xr.Dataset()\n for n, var2use in enumerate([var2use]):\n dsN[var2use] = ds_l[n]\n dsN[var2use].attrs = ds[var2use].attrs\n # Clean up\n regridder.clean_weight_file()\n # Parse the lat and lon attrs from original array\n dsN['lat'].attrs = ds['lat'].attrs\n dsN['lon'].attrs = ds['lon'].attrs\n # Now use re-gridded file\n del ds\n ds = dsN\n\n # - Plot up\n # Select data to plot\n a = ds[var2use].mean(dim='time')\n # Plot up map with mask present\n fig = plt.figure(figsize=(10, 6))\n ax = fig.add_subplot(111, projection=ccrs.Robinson(), aspect='auto')\n a.plot.imshow(x='lon', y='lat', ax=ax, transform=ccrs.PlateCarree())\n plt.title(savename)\n plt.savefig(savename+'.png')\n plt.close()\n\n # - Update attrs etc\n try:\n ds = ds.expand_dims('time', axis=0)\n except ValueError:\n pass\n ds = ds.assign_coords(time=[0])\n attrs = ds['time'].attrs\n attrs['standard_name'] = 'Time'\n attrs['long_name'] = attrs['standard_name']\n attrs['axis'] = 'T'\n attrs['units'] = 'hours since 2000-01-01 00:00:00'\n attrs['calendar'] = 'standard'\n ds['time'].attrs = attrs\n # Save array as float32 instead of float 64\n ds[Var2SaveAs].values = ds[Var2SaveAs].astype(np.float32).values\n # Update MASK attributes\n MainVarTitle = 'MASK of African high-res model nest '+ExtraStr\n attrs = ds[var2use].attrs\n attrs['standard_name'] = Var2SaveAs\n attrs['long_name'] = MainVarTitle\n# attrs['units'] = int(1)\n attrs['units'] = 'unitless'\n attrs['add_offset'] = int(0)\n attrs['scale_factor'] = int(1)\n attrs['missing_value'] = float(-1e-32)\n attrs['_FillValue'] = float(-1e-32)\n # Remove the vestigial ctm_units attribute\n try:\n del attrs['ctm_units']\n except:\n pass\n ds[var2use].attrs = attrs\n # Global attributes\n attrs = ds.attrs\n attrs['conventions'] = 'COARDS'\n attrs['contact'] = 'tomas.sherwen@york.ac.uk'\n attrs['title'] = MainVarTitle\n attrs['history'] = 'Created {}'.format(time.ctime(time.time()))\n# attrs['format'] = 'NetCDF-4'\n attrs['format'] = 'NETCDF3_CLASSIC'\n ds.attrs = attrs\n # Save as NetCDF\n# ds.to_netcdf( savename+'.nc', engine='scipy' )\n ds.to_netcdf(savename+'.nc', format='NETCDF3_CLASSIC')","def make_auxiliar_network(edges):\n\n s = S;t = T;na = {}\n fl = deque([s]) # fathers layer\n cl = deque([]) # childrens layer\n level = 0\n vl = {s:level} # vertex : level\n while len(fl) > 0:\n key = fl.popleft()\n for e in edges:\n if e['used']: continue\n \n r = e['capacity'] - e['flow']\n if key == e['first'] and r > 0:\n v = {'id':e['last'], 'direction':'F'}\n elif key == e['last'] and e['flow'] > 0:\n v = {'id':e['first'], 'direction':'B'}\n else: continue\n \n if v['id'] not in cl: \n cl.append(v['id'])\n if key not in na:\n na[key] = []\n\n if v['id'] not in vl:\n vl[v['id']] = level\n if vl[v['id']] == level:\n na[key].append(v)\n e['used'] = True\n\n \n if len(fl) == 0: fl = cl; cl = deque([]); level += 1\n if len(fl) == 0 or t in fl: break\n\n complete = False\n # remove all vertex except t from last layer\n for n in [k for k in vl if vl[k] == level-1]: \n if n == t:\n complete = True\n continue\n for k in na:\n na[k] = [v for v in na[k] if v['id'] != n]\n\n \n return {'na':na, 'complete':complete}","def _internal_build(self):\n self.nodes = self.__tree.Nodes()\n self.edges = self.__tree.Edges()\n self.augmentedEdges = {}\n for key, val in self.__tree.AugmentedEdges().items():\n self.augmentedEdges[key] = list(val)\n self.root = self.__tree.Root()\n\n seen = set()\n self.branches = set()\n\n # Find all of the branching nodes in the tree, degree > 1\n # That is, they appear in more than one edge\n for e1, e2 in self.edges:\n if e1 not in seen:\n seen.add(e1)\n else:\n self.branches.add(e1)\n\n if e2 not in seen:\n seen.add(e2)\n else:\n self.branches.add(e2)\n\n # The nodes that are not branches are leaves\n self.leaves = set(self.nodes.keys()) - self.branches\n self.leaves.remove(self.root)","def Expand_Mask(mask, feature_dict):\n new_mask = np.zeros(mask.shape + (len(feature_dict),))\n for i in feature_dict.keys():\n ni = int(i)\n new_mask[mask == ni,ni] = 1 \n return new_mask","def get_subgraphs(graph):\n nodes_powerset = get_nodes_combinations(graph)\n #print(\"Doing\")\n #draw_graph(graph)\n subgraphs = []\n for nodes in nodes_powerset:\n subg = graph.subgraph(nodes)\n nodes = subg.nodes(data=True)\n if nx.is_weakly_connected(subg):\n subgraphs.append(subg)\n return subgraphs","def _select_masks_to_boundaries(self, select_masks):\n\n def _merge(node_covers, select_idx):\n \"\"\"\n node_covers [[s1, e1], [s2, e2], ..., [sn, en]]\n \"\"\"\n new_node_covers = []\n for i in range(len(node_covers) - 1):\n if i == select_idx:\n merge_node_boundary = [node_covers[select_idx][0], node_covers[select_idx + 1][1]]\n new_node_covers.append(merge_node_boundary)\n elif i < select_idx:\n new_node_covers.append(node_covers[i])\n else:\n new_node_covers.append(node_covers[i + 1])\n return new_node_covers, merge_node_boundary\n batch_size = select_masks[0].size()[0]\n max_length = select_masks[0].size()[1] + 1\n combine_matrix = torch.rand(batch_size, max_length, 2).long()\n for j in range(max_length):\n combine_matrix[:, j, :] = j\n results = []\n for batch_idx in range(batch_size):\n node_covers = combine_matrix[batch_idx, :, :].numpy().tolist()\n result = []\n for node_idx in range(max_length - 2):\n select = select_masks[node_idx][batch_idx, :]\n select_idx = torch.nonzero(select).data[0][0]\n node_covers, merge_boundary = _merge(node_covers, select_idx)\n result.append(merge_boundary)\n results.append(result)\n results = torch.LongTensor(results)\n return results","def get_induced_subgraph(graph, subset):\n\t\n\tgraph_edges = graph.E\n\tvertices = list(graph.V)\n\n\t# construct the induced subgraph\n\n\tnew_graph_edge = {}\n\tnew_graph_vertices = subset\n\n\tfor start in graph_edges.keys():\n\t\tif start in new_graph_vertices:\n\t\t\tfor stop in graph_edges[start]:\n\t\t\t\tif stop in new_graph_vertices:\n\t\t\t\t\t# add it to new_graph_edge\n\t\t\t\t\tif start in new_graph_edge:\n\t\t\t\t\t\tnew_graph_edge[start].append(stop)\n\t\t\t\t\telse:\n\t\t\t\t\t\tnew_graph_edge[start] = [stop]\n\n\t#print new_graph_vertices\t\t\t\t\t\n\t#print new_graph_edge\n\treturn UndirectedGraph(new_graph_vertices, new_graph_edge)","def via_mask_from(self, mask: Mask2D) -> Visuals2D:\r\n origin = self.origin_via_mask_from(mask=mask)\r\n mask_visuals = self.get(\"mask\", mask)\r\n border = self.get(\"border\", mask.derive_grid.border_sub_1.binned)\r\n\r\n return self.visuals + self.visuals.__class__(\r\n origin=origin, mask=mask_visuals, border=border\r\n )","def getMoreComplexInLayerGraph(self):\n makeLayers = self.makeLayers\n addNodesToLayer = self.addNodesToLayer\n addNodeToLayer = self.addNodeToLayer\n eastWestEdgeFromTo = self.eastWestEdgeFromTo\n addInLayerEdge = self.addInLayerEdge\n setFixedOrderConstraint = self.setFixedOrderConstraint\n\n layers = makeLayers(3)\n leftNodes = addNodesToLayer(4, layers[0])\n middleNodes = addNodesToLayer(3, layers[1])\n rightNode = addNodeToLayer(layers[2])\n setFixedOrderConstraint(middleNodes[0])\n setFixedOrderConstraint(middleNodes[1])\n\n eastWestEdgeFromTo(leftNodes[1], middleNodes[0])\n\n eastWestEdgeFromTo(leftNodes[3], middleNodes[1])\n eastWestEdgeFromTo(leftNodes[2], middleNodes[1])\n addInLayerEdge(middleNodes[0], middleNodes[1], PortSide.WEST)\n eastWestEdgeFromTo(leftNodes[0], middleNodes[0])\n addInLayerEdge(middleNodes[0], middleNodes[2], PortSide.WEST)\n\n addInLayerEdge(middleNodes[0], middleNodes[1], PortSide.EAST)\n eastWestEdgeFromTo(middleNodes[0], rightNode)\n\n return self.graph","def getMask(label, scribble, class_id, class_ids):\n # Dense Mask\n fg_mask = torch.where(label == class_id,\n torch.ones_like(label), torch.zeros_like(label))\n bg_mask = torch.where(label != class_id,\n torch.ones_like(label), torch.zeros_like(label))\n for class_id in class_ids:\n bg_mask[label == class_id] = 0\n\n # Scribble Mask\n bg_scribble = scribble == 0\n fg_scribble = torch.where((fg_mask == 1)\n & (scribble != 0)\n & (scribble != 255),\n scribble, torch.zeros_like(fg_mask))\n scribble_cls_list = list(set(np.unique(fg_scribble)) - set([0,]))\n if scribble_cls_list: # Still need investigation\n fg_scribble = fg_scribble == random.choice(scribble_cls_list).item()\n else:\n fg_scribble[:] = 0\n\n return {'fg_mask': fg_mask,\n 'bg_mask': bg_mask,\n 'fg_scribble': fg_scribble.long(),\n 'bg_scribble': bg_scribble.long()}","def mask(self):\n mask = np.zeros((self.height, self.width))\n pts = [\n np.array(anno).reshape(-1, 2).round().astype(int)\n for anno in self.segmentation\n ]\n mask = cv2.fillPoly(mask, pts, 1)\n return mask","def model_masks(self, prunable=None):\n # TODO Also accept a dataloader\n pass\n # return masks","def sub_graph_merging(self):","def mask_infeasible(self):\n ns = len(self)-1\n # mask entries with i+j+k > ns\n for ii in range(len(self)):\n for jj in range(len(self)):\n for kk in range(len(self)):\n if ii+jj+kk > ns:\n self.mask[ii,jj,kk] = True\n \n return self","def build_graph(edges):\n \n G = nx.MultiGraph()\n G.add_edges_from(edges)\n return G","def get_induced_subgraph(graph: Graph, nodes: Nodes):\n return {node: graph[node].intersection(nodes) for node in nodes}","def mask_border(self, left=3, right=3, top=3, bottom=3):\n self.MaskPrefix = 'b' + self.MaskPrefix #prepend 'b' for border\n print('Masking edge pixels: left={0}, right={1}, top={2}, bottom={3}'.format(left,right,top,bottom))\n for ig in self.Set:\n igram = self.load_ma(ig)\n igram[:top,:] = ma.masked\n igram[-bottom:,:] = ma.masked\n igram[:,:left] = ma.masked\n igram[:,-right:] = ma.masked\n mskFile = self.MaskPrefix + 'Mask_' + ig.Name[:-4]\n np.save(os.path.join(self.ProcDir, mskFile), igram.mask)\n print(mskFile)\n print('mask_border() complete: {0} interferograms'.format(self.Set.Nig))","def fill_input_masks(nx_node, nx_graph):\n input_edges = sorted(list(nx_graph.in_edges(nx_node['key'])), key=lambda edge: nx_graph.edges[edge]['in_port'])\n input_masks = [nx_graph.nodes[input_node]['output_mask'] for input_node, _ in input_edges]\n\n filled_input_masks = []\n for i, mask in enumerate(input_masks):\n if mask is None:\n mask = torch.ones(nx_graph.edges[input_edges[i]]['activation_shape'][1])\n filled_input_masks.append(mask)\n return input_masks, filled_input_masks","def __init__(self, nodes, infimum=1e-8):\n self.nodes, (self.nn, self.dim) = nodes, nodes.shape\n\n # generate anisotropic simplices\n delaunay = Delaunay(self.nodes)\n simplices = delaunay.simplices\n volumes = np.linalg.det(self.nodes[simplices[:, :-1]] - self.nodes[simplices[:, [-1]]])\n valid_indices = [i for i, v in enumerate(volumes) if np.abs(v) > infimum]\n simplices = simplices[valid_indices, :]\n volumes = volumes[valid_indices]\n\n # generate mask of convex hull\n mask = np.expand_dims(self.nodes[delaunay.convex_hull], axis=1) - np.expand_dims(self.nodes, axis=(0, 2))\n self.mask = np.min(np.abs(np.linalg.det(mask)), axis=0) == 0\n\n # generate isotropic simplices\n def reverse(spx): return spx[[0, 2, 1] + list(range(3, spx.__len__()))]\n self.simplices = np.array([spx if flag else reverse(spx) for spx, flag in zip(simplices, volumes > 0)])\n self.nt = self.simplices.shape[0]\n\n # generate isotropic surfaces of simplices.\n self.surfaces = np.stack([np.roll(self.simplices, -k, 1) if k * self.dim % 2 else reverse(np.roll(self.simplices, -k, 1).T).T for k in range(self.dim + 1)], axis=1)[:, :, 1:]\n\n # generate minors and determinants of `tensor` in isotropic mode.\n # +- x_{t,0,0} & \\cdots & x_{t,0,ND-1} & 1 -+\n # tensor[t, :, :] = | \\vdots & \\ddots & \\vdots & \\vdots |\n # +- x_{t,ND,0} & \\cdots & x_{t,ND,ND-1} & 1 -+\n tensor = np.concatenate([self.nodes[self.simplices, :], np.ones(shape=(self.simplices.__len__(), self.dim + 1, 1))], axis=-1)\n self.determinants = np.abs(volumes)\n self.minors = np.einsum(\"tij,t->tji\", np.linalg.inv(tensor), self.determinants)","def edge_subgraph(\n self,\n subset_dict: Dict[EdgeType, Tensor],\n ) -> 'HeteroData':\n data = copy.copy(self)\n\n for edge_type, subset in subset_dict.items():\n edge_store, new_edge_store = self[edge_type], data[edge_type]\n for key, value in edge_store.items():\n if edge_store.is_edge_attr(key):\n dim = self.__cat_dim__(key, value, edge_store)\n if subset.dtype == torch.bool:\n new_edge_store[key] = mask_select(value, dim, subset)\n else:\n new_edge_store[key] = value.index_select(dim, subset)\n\n return data","def get_input_masks(nx_node, nx_graph):\n input_edges = list(nx_graph.in_edges(nx_node[\"key\"]))\n input_masks = [nx_graph.nodes[input_node][\"output_mask\"] for input_node, _ in input_edges]\n return input_masks","def __deepcopy__(self, memodict={}):\n nodes = [deepcopy(n) for n in self.nodes]\n return Network(nodes)","def get_mask(self, nodetype):\n print(\"Deprecation warning: Do it yourself.\")\n assert nodetype in [PAPER_TYPE, SUBJECT_TYPE, AUTHOR_TYPE], \"Unknown node type\"\n return (self.ndata.type == nodetype).values","def get_input_masks(nx_node, nx_graph):\n input_edges = list(nx_graph.in_edges(nx_node['key']))\n input_masks = [nx_graph.nodes[input_node]['output_mask'] for input_node, _ in input_edges]\n return input_masks","def mask(self):\n\n mask = np.zeros(shape=(self._info.height, self._info.width), dtype=np.uint8)\n\n self.draw(image=mask, color=constants.COLOR_WHITE_MONO)\n\n mask_with_border = np.pad(mask, 1, 'constant', constant_values=255)\n\n cv2.floodFill(image=mask,\n mask=mask_with_border,\n seedPoint=(int(self.middle_point[0]), int(self.middle_point[1])),\n newVal=constants.COLOR_WHITE_MONO)\n\n return mask","def get_mask(self, base_mask, contribution, num_prune):\n prune_indices = torch.argsort(contribution)[:num_prune]\n for idx in prune_indices:\n base_mask['weight_mask'][idx] = 0.\n if base_mask['bias_mask'] is not None:\n base_mask['bias_mask'][idx] = 0.\n return base_mask","def map_edges(clone):\n \n pcr.setglobaloption('unittrue')\n xmin, xmax, ymin, ymax, nr_rows, nr_cols, cell_size = clone_attributes()\n clone = pcr.ifthenelse(pcr.defined(clone), pcr.boolean(1), pcr.boolean(1))\n x_coor = pcr.xcoordinate(clone)\n y_coor = pcr.ycoordinate(clone)\n north = y_coor > (ymax - cell_size)\n south = y_coor < (ymin + cell_size)\n west = x_coor < (xmin + cell_size)\n east = x_coor > (xmax - cell_size)\n edges = north | south | west | east\n return edges","def get_copy_of_graph(self):\r\n return deepcopy(self)","def build_auxiliary_node_connectivity(G):\n directed = G.is_directed()\n\n mapping = {}\n H = nx.DiGraph()\n\n for i, node in enumerate(G):\n mapping[node] = i\n H.add_node('%dA' % i, id=node)\n H.add_node('%dB' % i, id=node)\n H.add_edge('%dA' % i, '%dB' % i, capacity=1)\n\n edges = []\n for (source, target) in G.edges():\n edges.append(('%sB' % mapping[source], '%sA' % mapping[target]))\n if not directed:\n edges.append(('%sB' % mapping[target], '%sA' % mapping[source]))\n H.add_edges_from(edges, capacity=1)\n\n # Store mapping as graph attribute\n H.graph['mapping'] = mapping\n return H","def generate_mask(self):\n\n polymer_length = len(self.sequence)\n protein_length = len(self.particle_order) - polymer_length\n\n if self.filter_specification == 'type':\n mask = np.in1d(self.particle_order, self.monomer_id)\n elif self.filter_specification == 'id':\n if self.molecule == 'polymer':\n offset = protein_length\n else:\n offset = 0\n mask = np.array([False] * (polymer_length + protein_length))\n absolute_id = [x+offset for x in self.monomer_id]\n mask[absolute_id] = True\n else:\n raise NotImplementedError(\"Filter is unknown. Use 'type' or 'id'!\")\n\n # if molecule == 'full', nothing needs to be done\n if self.molecule == 'polymer':\n mask[:protein_length] = [False] * protein_length\n elif self.molecule == 'protein':\n mask[protein_length:] = [False] * polymer_length\n\n return mask","def nonconnected():\n nonconnected = nx.MultiDiGraph()\n nonconnected.add_nodes_from(range(6))\n nonconnected.add_edges_from([\n (0, 1),\n (1, 2),\n (2, 3),\n (3, 0),\n (1, 0),\n (1, 0),\n (3, 2),\n (3, 3),\n (4, 4),\n (4, 4)\n ])\n return nonconnected","def mask(self):\n return type(self)(self.data.mask, self.bset)","def _source_mask(self, ilens):\n x_masks = make_non_pad_mask(ilens)\n return x_masks.unsqueeze(-2)","def _initalize_mask(dataSubStack):\n # Initalize an array to store the output mask values\n outMask = np.zeros(dataSubStack.shape, dtype=bool)\n\n # Start by masking out NaNs or Infs\n NaNsOrInfs = np.logical_not(np.isfinite(dataSubStack.data))\n dataSubStack.mask = NaNsOrInfs\n\n return outMask, dataSubStack","def load_mask(self, image_id):\n # If not homeobject dataset, delegate to parent class.\n image_info = self.image_info[image_id]\n if image_info[\"source\"] != 'homeobject':\n print(\n \"Warn: \\'{}\\' label not found. Processing with parent load_mask.\".format(image_info[\"source\"]))\n return super(self.__class__, self).load_mask(image_id)\n\n # Convert polygons to a bitmap mask of shape\n class_ids = image_info['class_ids']\n info = self.image_info[image_id]\n mask = np.zeros([info[\"height\"], info[\"width\"], len(info[\"polygons\"])], dtype=np.uint8)\n for i, p in enumerate(info[\"polygons\"]):\n # Get indexes of pixels inside the polygon and set them to 1\n rr, cc = skimage.draw.polygon(p['all_points_y'], p['all_points_x'])\n\n # modify dirt mask if it resides outside of image boundary\n rr[rr > mask.shape[0] - 1] = mask.shape[0] - 1\n cc[cc > mask.shape[1] - 1] = mask.shape[1] - 1\n\n mask[rr, cc, i] = 1\n # Return mask, and array of class IDs of each instance. Since we have\n # one class ID only, we return an array of 1s\n class_ids = np.array(class_ids, dtype=np.int32)\n # return mask.astype(np.bool), np.ones([mask.shape[-1]], dtype=np.int32)\n return mask, class_ids","def make_mask(data, pad):\n def subsequent_mask(size):\n \"\"\" helper function for creating the masks. \"\"\"\n attn_shape = (1, size, size)\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\n\n mask = (data != pad).unsqueeze(-2)\n mask = mask & Variable(\n subsequent_mask(data.size(-1)).type_as(mask.data))\n return mask","def infer_reuse_pattern(fgraph, outputs_to_disown):\r\n rval = set()\r\n for o in outputs_to_disown:\r\n view_tree_set(alias_root(o), rval)\r\n # remove from rval all of the inputs, constants, values.\r\n rval = set(r for r in rval if r.owner is not None)\r\n\r\n return rval","def subgraph(self, nodes_to_include=None, edges_to_include=None,\n nodes_to_exclude=None, edges_to_exclude=None):\n if nodes_to_include is None:\n node_filter_prop = self.graph.new_vertex_property(\n \"bool\", val=True)\n if nodes_to_exclude is not None:\n indices_to_exclude = [\n _get_vertex_obj(self.graph, n)\n for n in nodes_to_exclude\n ]\n for i in indices_to_exclude:\n node_filter_prop[i] = False\n else:\n node_filter_prop = self.graph.new_vertex_property(\n \"bool\", val=False)\n indices_to_include = [\n _get_vertex_obj(self.graph, n)\n for n in nodes_to_include\n ]\n for i in indices_to_include:\n node_filter_prop[i] = True\n\n if edges_to_include is None:\n edge_filter_prop = self.graph.new_edge_property(\n \"bool\", val=True)\n if edges_to_exclude is not None:\n sources = [\n _get_vertex_obj(self.graph, s)\n for s, _ in edges_to_exclude\n ]\n targets = [\n _get_vertex_obj(self.graph, t)\n for _, t in edges_to_exclude\n ]\n for s, t in zip(sources, targets):\n edge_filter_prop[self.graph.edge(s, t)] = False\n else:\n edge_filter_prop = self.graph.new_edge_property(\n \"bool\", val=False)\n sources = [\n _get_vertex_obj(self.graph, s)\n for s, _ in edges_to_include\n ]\n targets = [\n _get_vertex_obj(self.graph, t)\n for _, t in edges_to_include\n ]\n for s, t in zip(sources, targets):\n edge_filter_prop[self.graph.edge(s, t)] = True\n\n return GraphView(\n self.graph,\n vfilt=node_filter_prop,\n efilt=edge_filter_prop)","def _build_dependency_graph(self):\n\n #\n # Find the binary roles\n #\n nodes, roles = self._find_roles()\n\n #\n # Build the graph\n #\n working_list = list(set(nodes.keys()))\n\n setters = [b for b, r in roles.items() if Role.SETTER in r or Role.SETTER_GETTER in r]\n\n while working_list:\n b = working_list[0]\n working_list = working_list[1:]\n\n if nodes[b] not in self._graph:\n self._graph[nodes[b]] = []\n\n # it's a root node\n if Role.GETTER not in roles[b] and Role.SETTER_GETTER not in roles[b]:\n nodes[b].set_root()\n\n # takes params from some other binary\n else:\n is_orphan = True\n for setter in setters:\n setter_strings_set = set(nodes[setter].role_strings)\n node_strings_set = set(nodes[b].role_strings)\n if setter_strings_set.intersection(node_strings_set):\n if nodes[setter] not in self._graph:\n self._graph[nodes[setter]] = []\n self._graph[nodes[setter]].append(nodes[b])\n is_orphan = False\n\n # mark orphans\n if is_orphan:\n nodes[b].set_orphan()\n\n # Clean up\n for k, childs in self._graph.iteritems():\n self._graph[k] = list(set(childs))\n\n # set leaves\n for k, c in self._graph.iteritems():\n if not c:\n k.set_leaf()\n\n # post processing:\n # remove those nodes that are not orphans\n # and are not network parsers\n\n nodes = self.nodes\n children = [c for x in self._graph.values() for c in x if x]\n leafs_non_orphan = [n for n in nodes if n.leaf and not n.orphan]\n seed_names = [x.split('/')[-1] for x in self._seed_bins]\n spurious_nodes = [n for n in leafs_non_orphan if n not in children and n.bin.split('/')[-1] not in seed_names]\n for to_rem in spurious_nodes:\n del self._graph[to_rem]","def make_mask(data, pad):\n\n def subsequent_mask(size):\n \"\"\" helper function for creating the masks. \"\"\"\n attn_shape = (1, size, size)\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\n return torch.from_numpy(subsequent_mask) == 0\n\n mask = (data != pad).unsqueeze(-2)\n mask = mask & Variable(\n subsequent_mask(data.size(-1)).type_as(mask.data))\n return mask","def randomize_graph(graph, nodePositions, mask, planar=0, iterations=1000):\n nodeNumber = graph.number_of_nodes()\n edgeNumber = graph.number_of_edges()\n randomizedGraph = nx.empty_graph(nodeNumber, nx.MultiGraph())\n edgeLengths = np.array([property['edist'] for node1, node2, property in graph.edges(data=True)])\n bins = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 9999]\n binNumber = len(bins) - 1\n edgeBins = np.zeros(edgeNumber).astype('int')\n for index, (bin1, bin2) in enumerate(zip(bins[:-1], bins[1:])):\n edgesInBin = (edgeLengths >= bin1) * (edgeLengths < bin2)\n edgeBins[edgesInBin] = index\n edgeWeights = np.array([property['weight'] for node1, node2, property in graph.edges(data=True)])\n edgeCapacities = np.array([property['capa'] for node1, node2, property in graph.edges(data=True)])\n redoRandomization = 1\n iterationNumber = 0\n while (redoRandomization == 1 and iterationNumber < iterations):\n iterationNumber += 1\n nodePositionsRandom = cell_sample(mask, nodeNumber)[:, ::-1].astype('int')\n distanceMatrix = sp.spatial.distance_matrix(nodePositionsRandom, nodePositionsRandom)\n edgeBinsRandom = np.zeros((nodeNumber, nodeNumber)).astype('int')\n for index, (bin1, bin2) in enumerate(zip(bins[:-1], bins[1:])):\n edgesInBin = (distanceMatrix >= bin1) * (distanceMatrix < bin2)\n edgeBinsRandom[edgesInBin] = index\n edgeBinsRandom[np.tri(nodeNumber) > 0] =- 9999\n redoRandomization = 1 * np.max([(edgeBinsRandom == bins).sum() < (edgeBins == bins).sum() for bins in range(binNumber)])\n if (iterationNumber < iterations):\n sortBins = np.argsort(edgeLengths)[::-1]\n edgeBinsSort = edgeBins[sortBins]\n edgeWeightsSort = edgeWeights[sortBins]\n edgeCapacitiesSort = edgeCapacities[sortBins]\n addedEdges = []\n for edge in range(edgeNumber):\n candidateNodes = np.where(edgeBinsRandom == edgeBinsSort[edge])\n candidateNumber = len(candidateNodes[0])\n edgeCrossings = 9999\n selectedCandidates = random.sample(range(candidateNumber), min(50, candidateNumber))\n for candidate in selectedCandidates:\n node1 = candidateNodes[0][candidate]\n node2 = candidateNodes[1][candidate]\n edgeBetweenNodes = np.array([[nodePositionsRandom[node1][0], nodePositionsRandom[node2][0]], [nodePositionsRandom[node1][1], nodePositions[node2][1]]]).T\n crossingsOfEdges = planar * multi_line_intersect(np.array(edgeBetweenNodes), np.array(addedEdges)).sum()\n if (crossingsOfEdges < edgeCrossings and edgeBinsRandom[node1, node2] >= 0):\n edgeCrossings = crossingsOfEdges\n selectedEdge = edgeBetweenNodes\n selectedNode1, selectedNode2 = node1, node2\n addedEdges.append(selectedEdge)\n nodeDistanceRandom = distanceMatrix[selectedNode1, selectedNode2]\n filamentLengthRandom = 1.0 * np.ceil(nodeDistanceRandom)\n edgeWeightRandom = edgeWeightsSort[edge]\n edgeCapacityRandom = edgeCapacitiesSort[edge]\n edgeLengthRandom = 1.0 * filamentLengthRandom / edgeWeightRandom\n edgeConnectivityRandom = 0\n edgeJumpRandom = 0\n edgeMultiplicity = 1\n randomizedGraph.add_edge(selectedNode1, selectedNode2, edist=nodeDistanceRandom, fdist=filamentLengthRandom, weight=edgeWeightRandom, capa=edgeCapacityRandom, lgth=edgeLengthRandom, conn=edgeConnectivityRandom, jump=edgeJumpRandom, multi=edgeMultiplicity)\n edgeBinsRandom[selectedNode1, selectedNode2] =- 9999\n edgeBinsRandom[selectedNode2, selectedNode1] =- 9999\n else:\n edgeProperties = np.array([property for node1, node2, property in graph.edges(data=True)])\n random.shuffle(edgeProperties)\n randomizedGraph = graph.copy()\n for index, (node1, node2, properties) in enumerate(randomizedGraph.edges(data=True)):\n for key in properties.keys():\n properties[key] = edgeProperties[index][key]\n nodePositionsRandom = nodePositions\n return(randomizedGraph, nodePositionsRandom)"],"string":"[\n \"def subgraph_mask(self, size):\\n init_matrix = np.random.randn(size,size)\\n Tcs = csgraph.minimum_spanning_tree(init_matrix)\\n mask_matrix = Tcs.toarray()\\n return mask_matrix\",\n \"def __init__(self, nodes: Set[Node], edges: Set[Edge]):\\n super().__init__()\\n self.nodes = nodes\\n for edge in edges:\\n self.add_edge(edge)\\n self.leaves = {node for node in self.nodes if self.degree_out(node) == 0}\\n root_nodes = self.nodes - self.leaves\\n root_edges = {edge for edge in self.edges if edge.node_to not in self.leaves}\\n self.root_graph = Mask(root_nodes, root_edges, self)\",\n \"def _build_mask(self, xg, yg):\\n\\n # 1. create mask based on meshes\\n points = np.vstack((xg.flatten(), yg.flatten())).T\\n\\n # 2. extract edge points using el_pos\\n edge_points = self.node[np.arange(16)]\\n path = Path(edge_points, closed=False)\\n mask = path.contains_points(points)\\n\\n return mask\",\n \"def create_unlabeled_subgraph(graph):\\n unlabeled_nodes = []\\n for (p, d) in graph.nodes(data=True):\\n if (d['leaning'] == 'Unknown'):\\n unlabeled_nodes.append(p)\\n return nx.subgraph(graph, unlabeled_nodes)\",\n \"def create_labeled_subgraph(graph):\\n labeled_nodes = []\\n for (p, d) in graph.nodes(data=True):\\n if (d['leaning'] == 'R') or (d['leaning'] == 'D'):\\n labeled_nodes.append(p)\\n return nx.subgraph(graph, labeled_nodes)\",\n \"def create_sub_graph_copy(graph: nx.MultiDiGraph, nodes_to_extract: list):\\n return graph.subgraph(nodes_to_extract).copy()\",\n \"def __deepcopy__(self):\\n return UndirectedGraph.extract_edge_induced_subgraph(self, lambda edge: True) # copy all edges\",\n \"def islands(\\n self,\\n corners=False\\n ):\\n\\n if self.linked_mask == None:\\n print \\\"Island assignment requires a mask.\\\"\\n return\\n \\n structure = (Struct(\\n \\\"simple\\\", \\n ndim=self.linked_mask.data.ndim, \\n corners=corners)).struct\\n\\n labels, nlabels = ndimage.label(self.linked_mask.data,\\n structure=structure)\\n \\n self.data = labels\\n self.nclouds = nlabels\\n self.slices = ndimage.find_objects(self.data)\",\n \"def _create_reference_connectivity_graph(self):\\n #take the self._residue_graph and create a replicate (without the misc attributes) with the atoms_with_positions\\n _reference_connectivity_graph = nx.Graph()\\n atoms_with_positions = set(self._atoms_with_positions)\\n\\n #iterate over all the bonds\\n for bond in self._residue_graph.edges():\\n if set(bond).issubset(atoms_with_positions):\\n #if both of the atoms in the bond are in atoms_with_positions, we can add the atoms/bonds to the reference\\n _reference_connectivity_graph.add_edge(*bond)\\n\\n return _reference_connectivity_graph\",\n \"def build_fpn_mask_graph(rois, feature_maps, image_meta,\\n pool_size, num_classes, train_bn=True):\\n # ROI Pooling\\n # Shape: [batch, boxes, pool_height, pool_width, channels]\\n x = PyramidROIAlign([pool_size, pool_size],\\n name=\\\"roi_align_mask\\\")([rois, image_meta] + feature_maps)\\n\\n # Conv layers\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv1\\\")(x)\\n x = KL.TimeDistributed(BatchNorm(),\\n name='mrcnn_mask_bn1')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv2\\\")(x)\\n x = KL.TimeDistributed(BatchNorm(),\\n name='mrcnn_mask_bn2')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv3\\\")(x)\\n x = KL.TimeDistributed(BatchNorm(),\\n name='mrcnn_mask_bn3')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv4\\\")(x)\\n x = KL.TimeDistributed(BatchNorm(),\\n name='mrcnn_mask_bn4')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2DTranspose(256, (2, 2), strides=2, activation=\\\"relu\\\"),\\n name=\\\"mrcnn_mask_deconv\\\")(x)\\n x = KL.TimeDistributed(KL.Conv2D(num_classes, (1, 1), strides=1, activation=\\\"sigmoid\\\"),\\n name=\\\"mrcnn_mask\\\")(x)\\n return x\",\n \"def re_root(self, omit_edge_label: List[str]):\\n self.leaves = {node for node in self.nodes\\n if any([edge.label in omit_edge_label for edge in self.edges_to(node)])}\\n root_nodes = self.nodes - self.leaves\\n root_edges = {edge for edge in self.edges if edge.node_to in root_nodes and edge.node_from in root_nodes}\\n self.root_graph = Mask(root_nodes, root_edges, self)\",\n \"def subgraph(self, nodes, relabel_nodes=False, output_device=None):\\n raise NotImplementedError(\\\"subgraph is not implemented yet\\\")\",\n \"def get_contest_mask():\\n return createmaskdf(\\\"data/fcstrodeo_nctemplates/fcstrodeo_mask.nc\\\")\",\n \"def test(shape=(1000,2000)):\\n mask = Mask()\\n mask.addCircle(400,300,250)\\n mask.subtractCircle(400,300,150)\\n mask.addRectangle(350,250,1500,700)\\n plt.imshow( mask.getMask(shape) )\\n return mask\",\n \"def test_differentiable__mask_connectivity(self):\\n data = random_graph_data(5, 4, 3)\\n print(data.size)\",\n \"def subgraph(self, subset_dict: Dict[NodeType, Tensor]) -> 'HeteroData':\\n data = copy.copy(self)\\n subset_dict = copy.copy(subset_dict)\\n\\n for node_type, subset in subset_dict.items():\\n for key, value in self[node_type].items():\\n if key == 'num_nodes':\\n if subset.dtype == torch.bool:\\n data[node_type].num_nodes = int(subset.sum())\\n else:\\n data[node_type].num_nodes = subset.size(0)\\n elif self[node_type].is_node_attr(key):\\n data[node_type][key] = value[subset]\\n else:\\n data[node_type][key] = value\\n\\n for edge_type in self.edge_types:\\n src, _, dst = edge_type\\n\\n src_subset = subset_dict.get(src)\\n if src_subset is None:\\n src_subset = torch.arange(data[src].num_nodes)\\n dst_subset = subset_dict.get(dst)\\n if dst_subset is None:\\n dst_subset = torch.arange(data[dst].num_nodes)\\n\\n edge_index, _, edge_mask = bipartite_subgraph(\\n (src_subset, dst_subset),\\n self[edge_type].edge_index,\\n relabel_nodes=True,\\n size=(self[src].num_nodes, self[dst].num_nodes),\\n return_edge_mask=True,\\n )\\n\\n for key, value in self[edge_type].items():\\n if key == 'edge_index':\\n data[edge_type].edge_index = edge_index\\n elif self[edge_type].is_edge_attr(key):\\n data[edge_type][key] = value[edge_mask]\\n else:\\n data[edge_type][key] = value\\n\\n return data\",\n \"def fpn_mask_graph(rois, feature_maps, image_meta,\\n pool_size, num_classes, train_bn=True):\\n # ROI Pooling\\n # Shape: [batch, boxes, pool_height, pool_width, channels]\\n x = modellib.PyramidROIAlign([pool_size, pool_size],\\n name=\\\"roi_align_mask\\\")([rois, image_meta] + feature_maps)\\n\\n # Conv layers\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv1\\\")(x)\\n x = KL.TimeDistributed(modellib.BatchNorm(),\\n name='mrcnn_mask_bn1')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv2\\\")(x)\\n x = KL.TimeDistributed(modellib.BatchNorm(),\\n name='mrcnn_mask_bn2')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv3\\\")(x)\\n x = KL.TimeDistributed(modellib.BatchNorm(),\\n name='mrcnn_mask_bn3')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2D(256, (3, 3), padding=\\\"same\\\"),\\n name=\\\"mrcnn_mask_conv4\\\")(x)\\n x = KL.TimeDistributed(modellib.BatchNorm(),\\n name='mrcnn_mask_bn4')(x, training=train_bn)\\n x = KL.Activation('relu')(x)\\n\\n x = KL.TimeDistributed(KL.Conv2DTranspose(256, (2, 2), strides=2, activation=\\\"relu\\\"),\\n name=\\\"mrcnn_mask_deconv\\\")(x)\\n x = KL.TimeDistributed(KL.Conv2D(1, (1, 1), strides=1, activation=\\\"sigmoid\\\"),\\n name=\\\"mrcnn_mask\\\")(x)\\n # Duplicate output for fg/bg detections\\n x = KL.Concatenate(axis=-1)([x for i in range(num_classes)])\\n return x\",\n \"def generate(self, subset=False, indices=[]):\\n\\n F = self.faces\\n n = F.max()+1\\n\\n rows = np.concatenate([F[:, 0], F[:, 0],\\n F[:, 1], F[:, 1], \\n F[:, 2], F[:, 2]])\\n\\n cols = np.concatenate([F[:, 1], F[:, 2], \\n F[:, 0], F[:, 2], \\n F[:, 0], F[:, 1]])\\n\\n combos = np.column_stack([rows, cols])\\n\\n [_, idx] = np.unique(combos, axis=0, return_index=True)\\n A = sparse.csr_matrix((np.ones(len(idx)), (combos[idx, 0], combos[idx, 1])), shape=(n, n))\\n\\n\\n G = nx.from_scipy_sparse_matrix(A)\\n\\n if subset:\\n nodes = indices\\n else:\\n nodes = G.nodes\\n\\n adj = {node: [] for node in nodes}\\n for node in nodes:\\n for j in G.neighbors(n=node):\\n adj[node].append(j)\\n adj[node].sort()\\n \\n self.adj = adj\",\n \"def mask_neighbors(self, mask, rad=9, ptrn='r'):\\n return um.mask_neighbors(mask, rad, ptrn)\",\n \"def __generate_mask(self):\\n mask = np.concatenate([np.ones(len(self.fixed[0])),\\n np.zeros(self.num_points),\\n np.ones(len(self.fixed[1]))])\\n return mask\",\n \"def _build_graph_general(self): \\n\\n #Find a canonical coloring scheme\\n #Each node has a color that is determined by the non-mapped aspects\\n nodecolors=set()\\n for nl in self.net.iter_node_layers():\\n nodecolors.add(self._slice_node_layer_not_allowed(nl))\\n nodecolors_sorted=sorted(list(nodecolors))\\n del nodecolors\\n self._assert_full_order(nodecolors_sorted)\\n self.colormap=dict( ((color,colorid) for colorid,color in enumerate(nodecolors_sorted) ))\\n\\n #each aux node has a color that is determined by the aspect\\n self.auxcolormap=dict( ((auxcolor, auxcolorid+len(self.colormap)) for auxcolorid,auxcolor in enumerate(sorted(self.asp)) ) )\\n\\n\\n #Add the underlying network\\n #node-layers:\\n for nl in self.net.iter_node_layers():\\n nlid=self._get_node_id(nl)\\n color=self._slice_node_layer_not_allowed(nl)\\n colorid=self.colormap[color]\\n self.add_node(nlid,colorid)\\n\\n #edges between node-layers:\\n for nl1 in self.net.iter_node_layers():\\n for nl2 in self.net[nl1]:\\n nl1id=self._get_node_id(nl1)\\n nl2id=self._get_node_id(nl2)\\n self.add_link(nl1id,nl2id)\\n\\n\\n #Add the auxiliary nodes and edges\\n #add the aux nodes\\n for a in self.asp:\\n for elayer in self.net.slices[a]:\\n auxid=self._get_auxnode_id( (a,elayer) )\\n auxcolorid=self.auxcolormap[a]\\n self.add_node(auxid,auxcolorid)\\n \\n #add the aux edges\\n for nl in self.net.iter_node_layers():\\n for a in self.asp:\\n nlid=self._get_node_id(nl)\\n auxid=self._get_auxnode_id( (a,nl[a]) )\\n self.add_link(nlid,auxid)\",\n \"def copy(self):\\n \\n \\n G = DiGraph()\\n G.node_set = copy.deepcopy(self.node_set)\\n G.prefix = copy.deepcopy(self.prefix)\\n G.suffix = copy.deepcopy(self.suffix)\\n G.num_node = copy.deepcopy(self.num_node)\\n G.edges = copy.deepcopy(self.edges)\\n \\n return G\",\n \"def mask(self):\",\n \"def create_mask(shape):\\n return np.zeros(shape).astype(bool)\",\n \"def _create_mask_part(\\n self,\\n shape: List[int],\\n overlap: List[int],\\n device: torch.device,\\n dtype: torch.dtype = torch.float,\\n ) -> torch.Tensor:\\n assert len(shape) == 4\\n zeros_size, lin_size = overlap[0:2]\\n ones_size = shape[3] - (zeros_size + lin_size)\\n sizes = (zeros_size, lin_size, ones_size)\\n mask_parts = [\\n torch.zeros(sizes[0], device=device, dtype=dtype),\\n torch.linspace(0, 1, sizes[1], device=device, dtype=dtype),\\n torch.ones(sizes[2], device=device, dtype=dtype),\\n ]\\n return (\\n torch.cat(mask_parts, 0)\\n .repeat(shape[2], 1)\\n .repeat(shape[1], 1, 1)\\n .unsqueeze(0)\\n )\",\n \"def createMaskDictionary(self):\\n try:\\n self.maskMap = dict(list(zip(self.inds,list(range(len(self.inds))))))\\n self.maskSet = set(self.inds)\\n except Exception as error:\\n print(\\\"failed in createMaskDictionary\\\", error)\",\n \"def create_mask(frame):\\n \\n # detect ridges\\n ridges = enhance_ridges(frame)\\n\\n # threshold ridge image\\n thresh = filters.threshold_otsu(ridges)\\n thresh_factor = 1.1\\n prominent_ridges = ridges > thresh_factor*thresh\\n prominent_ridges = morphology.remove_small_objects(prominent_ridges, min_size=128)\\n\\n # the mask contains the prominent ridges\\n mask = morphology.convex_hull_image(prominent_ridges)\\n mask = morphology.binary_erosion(mask, disk(10))\\n return mask\",\n \"def subgraph(self, name):\\n\\n self._compiled = None\\n sub = Graph()\\n self.graph[name] = sub\\n return sub\",\n \"def mask(self, mask):\\n ds_out = self._obj\\n for var in self.vars:\\n ds_out[var] = ds_out[var].raster.mask(mask)\\n return ds_out\",\n \"def generate_effective_mask(self, mask_size: tuple, polygons_ignore):\\n mask = np.ones(mask_size, dtype=np.uint8)\\n\\n for poly in polygons_ignore:\\n instance = poly.astype(np.int32).reshape(1, -1, 2)\\n cv2.fillPoly(mask, instance, 0)\\n\\n return mask\",\n \"def mask(self, mask):\\n return MaskedDistribution(self, mask)\",\n \"def clone(self):\\n cloned = Graph()\\n for v in self.vertices:\\n cloned.vertices[v] = self.vertices[v].clone()\\n return cloned\",\n \"def mask_nodata(self):\\n ds_out = self._obj\\n for var in self.vars:\\n ds_out[var] = ds_out[var].raster.mask_nodata()\\n return ds_out\",\n \"def copy(self):\\n cls = self.__class__\\n new_graph = cls.__new__(cls)\\n new_graph._nodes = self._nodes[:]\\n new_graph._node_wip = self._node_wip[:]\\n new_graph._edges = self._edges[:]\\n if self._sorted_nodes:\\n new_graph._sorted_nodes = self._sorted_nodes[:]\\n else:\\n new_graph._sorted_nodes = None\\n new_graph.predecessors = {}\\n for key, val in self.predecessors.items():\\n new_graph.predecessors[key] = self.predecessors[key][:]\\n new_graph.successors = {}\\n for key, val in self.successors.items():\\n new_graph.successors[key] = self.successors[key][:]\\n return new_graph\",\n \"def to_undirected_graph(self):\\n visited = set() \\n G = Graph.Graph()\\n \\n for node in self.node_set:\\n \\n if node not in visited:\\n visited.add(node)\\n for i in self.suffix[node]:\\n G.add_edge(node, i)\\n \\n return G\",\n \"def identity_mask_propagation(nx_node, nx_graph):\\n input_masks = get_input_masks(nx_node, nx_graph)\\n assert len(input_masks) == 1\\n nx_node[\\\"input_masks\\\"] = input_masks\\n nx_node[\\\"output_mask\\\"] = input_masks[0]\",\n \"def check_subgraph_for_data_mask_optimization(args: dict) -> bool:\\n whitelist = {\\n \\\"drop_dimension\\\",\\n \\\"filter_bands\\\",\\n \\\"filter_bbox\\\",\\n \\\"filter_spatial\\\",\\n \\\"filter_temporal\\\",\\n \\\"load_collection\\\",\\n }\\n\\n children_node_types = flatten_children_node_types(args[\\\"data\\\"])\\n # If children_node_types exists only out of whitelisted nodes, an intersection should have no effect.\\n if len(children_node_types.intersection(whitelist)) != len(children_node_types):\\n return False\\n\\n data_children_node_names = flatten_children_node_names(args[\\\"data\\\"])\\n mask_children_node_names = flatten_children_node_names(args[\\\"mask\\\"])\\n if not data_children_node_names.isdisjoint(mask_children_node_names):\\n # To avoid an issue in integration tests:\\n _log.info(\\\"Overlap between data and mask node. Will not pre-apply mask on load_collections.\\\")\\n return False\\n\\n return True\",\n \"def identity_mask_propagation(nx_node, nx_graph):\\n input_masks = get_input_masks(nx_node, nx_graph)\\n assert len(input_masks) == 1\\n nx_node['input_masks'] = input_masks\\n nx_node['output_mask'] = input_masks[0]\",\n \"def project(B,nodes,create_using=None):\\n\\n if create_using==None:\\n create_using=networkx.Graph()\\n\\n G=networkx.empty_graph(0,create_using)\\n\\n for v in nodes:\\n G.add_node(v)\\n for nbr in B[v]:\\n G.add_edges_from([(v,u) for u in B[nbr] if u!=v])\\n return G\",\n \"def build_mask(mask, unused_features_positions):\\n\\tfinal_mask = mask.tolist()\\n\\n\\tfor i in range(len(unused_features_positions)):\\n\\t\\tif not unused_features_positions[i]:\\n\\t\\t\\tfinal_mask.insert(i, False)\\n\\n\\treturn final_mask\",\n \"def make_initial_mask(model):\\n mask = Mask()\\n prunable_layers = utils.prunable_layers(model)\\n for module in prunable_layers:\\n mask[module] = torch.ones(list(model.state_dict()[module].shape))\\n return mask\",\n \"def edge_subgraph(self, edges, relabel_nodes=False, output_device=None):\\n raise NotImplementedError(\\\"edge_subgraph is not implemented yet\\\")\",\n \"def create_pathway_mask(feature_list, dict_pathway, add_missing=True, fully_connected=True, to_tensor=False):\\n assert type(dict_pathway) == OrderedDict\\n p_mask = np.zeros((len(feature_list), len(dict_pathway)))\\n for j, k in enumerate(dict_pathway.keys()):\\n for i in range(p_mask.shape[0]):\\n if feature_list[i] in dict_pathway[k]:\\n p_mask[i,j] = 1.\\n if add_missing:\\n n = 1 if type(add_missing)==bool else add_missing\\n # Get non connected genes\\n if not fully_connected:\\n idx_0 = np.where(np.sum(p_mask, axis=1)==0)\\n vec = np.zeros((p_mask.shape[0],n))\\n vec[idx_0,:] = 1.\\n else:\\n vec = np.ones((p_mask.shape[0], n))\\n p_mask = np.hstack((p_mask, vec))\\n if to_tensor:\\n p_mask = torch.Tensor(p_mask)\\n return p_mask\",\n \"def atlas6():\\n\\n Atlas = graph_atlas_g()[0:208] # 208\\n # remove isolated nodes, only connected graphs are left\\n U = nx.Graph() # graph for union of all graphs in atlas\\n for G in Atlas:\\n zerodegree = [n for n in G if G.degree(n) == 0]\\n for n in zerodegree:\\n G.remove_node(n)\\n U = nx.disjoint_union(U, G)\\n\\n # iterator of graphs of all connected components\\n C = (U.subgraph(c) for c in nx.connected_components(U))\\n\\n UU = nx.Graph()\\n # do quick isomorphic-like check, not a true isomorphism checker\\n nlist = [] # list of nonisomorphic graphs\\n for G in C:\\n # check against all nonisomorphic graphs so far\\n if not iso(G, nlist):\\n nlist.append(G)\\n UU = nx.disjoint_union(UU, G) # union the nonisomorphic graphs\\n return UU\",\n \"def di_subgraph(self, nbunch):\\n\\t\\t\\n\\t\\t# create new subgraph.\\n\\t\\tg = nx.DiGraph()\\n\\t\\t\\n\\t\\t# add edges and nodes.\\n\\t\\tg.add_edges_from( self.edges(nbunch=nbunch) )\\n\\t\\t\\n\\t\\treturn g\",\n \"def create_subbasin_graph():\\n subbasin_to_downstream = pd.read_csv(module_dir + '/../data/simulations_shervan/test.rvh', sep='\\\\s+', skiprows=7, nrows=724, names=['subbasin', 'downstream_subbasin'], usecols=[1,2])\\n subbasin_to_downstream['subbasin'] = subbasin_to_downstream['subbasin']\\n subbasin_to_downstream['downstream_subbasin'] = 'sub' + subbasin_to_downstream['downstream_subbasin'].astype(str)\\n subbasin_to_downstream['edge'] = 1\\n\\n for subbasin in subbasin_to_downstream['subbasin'].unique():\\n is_sink = 1 if len(subbasin_to_downstream[(subbasin_to_downstream['subbasin'] == subbasin) & subbasin_to_downstream['edge'] == 1]) == 0 else 0\\n subbasin_to_downstream = subbasin_to_downstream.append({'subbasin': subbasin, 'downstream_subbasin': subbasin, 'edge': is_sink}, ignore_index=True)\\n subbasin_to_downstream = subbasin_to_downstream.append({'subbasin': 'sub-1', 'downstream_subbasin': 'sub-1', 'edge': 1}, ignore_index=True)\\n \\n adj = subbasin_to_downstream.pivot(index='subbasin', columns='downstream_subbasin', values='edge').fillna(0) \\n adj = adj.sort_index(axis=0).sort_index(axis=1)\\n \\n G = nx.from_numpy_matrix(adj.values, parallel_edges=False, create_using=nx.DiGraph())\\n label_mapping = dict(zip(range(len(adj.values)), adj.index))\\n G = nx.relabel_nodes(G, label_mapping)\\n \\n return G\",\n \"def build_drop_fullgraphs(self, do_subgraph=False, graph_lib='pygraphviz'):\\n if 'pygraphviz' == graph_lib:\\n G = pgv.AGraph(strict=True, directed=True)\\n else:\\n G = nx.Graph()\\n do_subgraph = False\\n subgraph_dict = defaultdict(list) # k - node-ip, v - a list of graph nodes\\n oid_gnid_dict = dict()\\n\\n for i, oid in enumerate(self.pg_spec.keys()):\\n oid_gnid_dict[oid] = str(i)\\n logger.info(\\\"oid to gid mapping done\\\")\\n\\n for dropspec in self.pg_spec.itervalues():\\n gid = oid_gnid_dict[dropspec['oid']]\\n ip = dropspec['node']\\n subgraph_dict[ip].append(gid)\\n if (dropspec['type'] == 'app'):\\n G.add_node(gid, shape='rect', label='')#, fixedsize=True, hight=.05, width=.05)\\n elif (dropspec['type'] == 'plain'): #parallelogram\\n G.add_node(gid, shape='circle', label='')#, fixedsize=True, hight=.05, width=.05)\\n logger.info(\\\"Graph nodes added\\\")\\n\\n for dropspec in self.pg_spec.itervalues():\\n gid = oid_gnid_dict[dropspec['oid']]\\n if (dropspec['type'] == 'app'):\\n ds_kw = 'outputs' #down stream key word\\n elif (dropspec['type'] == 'plain'):\\n ds_kw = 'consumers'\\n else:\\n ds_kw = 'None'\\n if (ds_kw in dropspec):\\n for doid in dropspec[ds_kw]:\\n G.add_edge(gid, oid_gnid_dict[doid])\\n logger.info(\\\"Graph edges added\\\")\\n\\n if (do_subgraph):\\n for i, subgraph_nodes in enumerate(subgraph_dict.values()):\\n # we don't care about the subgraph label or rank\\n subgraph = G.add_subgraph(subgraph_nodes, label='%d' % i, name=\\\"cluster_%d\\\" % i, rank=\\\"same\\\")\\n subgraph.graph_attr['rank']='same'\\n logger.info(\\\"Subgraph added\\\")\\n\\n return G\",\n \"def create_logits_mask_by_first_edge_graph(edge_indexes, num_edge, nvec):\\n # find first edge\\n # adj matrix of graphs\\n # adj_mat = nx.to_numpy_matrix(graph, nodelist=range(nvec))[None]\\n\\n # bs = adj_mats.shape[0]\\n # total_mask = []\\n max_edge = edge_indexes.shape[0]\\n total_mask = np.zeros(shape=(1, max_edge), dtype=np.int8)\\n\\n\\n # edges = edge_indexes[:num_edge]\\n # edges = np.where(adj_mats[i, :, :] > 0)\\n\\n # max_edge = max(max_edge, num_edges)\\n # mask = np.zeros(shape=(1, max_edge), dtype=np.int8)\\n all_half_edges = edge_indexes[:num_edge // 2] # only use the directed edge (a->b), not (b->a) # location[np.where(location[:, 0] < location[:, 1])[0]]\\n all_valid_edges = edge_indexes[:num_edge] # only use the directed edge (a->b), not (b->a) # location[np.where(location[:, 0] < location[:, 1])[0]]\\n\\n # restore adj matrix\\n rawobs = np.zeros(shape=(nvec, nvec), dtype=np.int8)\\n for edge in all_valid_edges:\\n rawobs[edge[0], edge[1]] = 1 # edge is an ndarray (2,), we cannot index using rawobs[edge] (is array with shape (2, 15))\\n#\\n for idx_1, edge_1 in enumerate(all_half_edges):\\n encoded_edge_1 = idx_1\\n # check if they are one-hop connected\\n\\n mask = np.zeros(shape=(max_edge,), dtype=np.int8)\\n for idx_2, edge_2 in enumerate(all_valid_edges):\\n\\n fail_cond = edge_2[0] in edge_1 or edge_2[1] in edge_1 or\\\\\\n int(rawobs[edge_2[0], edge_1[0]]) + int(rawobs[edge_2[0], edge_1[1]]) + \\\\\\n int(rawobs[edge_2[1], edge_1[0]]) + int(rawobs[edge_2[1], edge_1[1]]) > 0\\n\\n mask[idx_2] = not fail_cond\\n\\n total_mask[0, encoded_edge_1] = mask.any()\\n\\n\\n return total_mask\",\n \"def generate_subclass_mask(mask_image,\\n subclasses=(1, 3)):\\n mask_shape = mask_image.shape\\n sub_mask = generate_image(mask_shape[0], mask_shape[1], color=0)\\n if mask_image.ndim == 2:\\n gray_mask_image = mask_image[:, :]\\n else:\\n gray_mask_image = mask_image[:, :, 0]\\n \\n if isinstance(subclasses, (list, tuple)):\\n if len(subclasses) == 2:\\n keep_bool = np.logical_or(gray_mask_image == subclasses[0], gray_mask_image == subclasses[1])\\n else:\\n keep = []\\n for subclass in subclasses:\\n keep.append(gray_mask_image == subclass)\\n\\n keep_bool = np.logical_or.reduce(tuple(keep))\\n else:\\n keep_bool = (gray_mask_image == subclasses)\\n\\n sub_mask[keep_bool] = 1\\n\\n return sub_mask\",\n \"def create_mask(neurons: list):\\n\\n return np.zeros_like(neurons[0])\",\n \"def extract_node_induced_subgraph(self, predicate):\\n # construct the filtered nodeset\\n nodeset = {node.produce_duplicate_disconnected_node() for node in self.get_nodeset() if predicate(node)}\\n\\n G_prime = UndirectedGraph(nodeset) # create a new subgraph\\n\\n for edge in self.get_edges(): # for every edge in the original graph\\n # if the first incident node is in the graph\\n if edge.get_first_incident_node().get_name() in G_prime.get_node_names():\\n # if the second incident node is also in the graph\\n if edge.get_second_incident_node().get_name() in G_prime.get_node_names():\\n # add the edge to the subgraph\\n G_prime = UndirectedGraph.__induced_subgraph_helper(G_prime, edge)\\n return G_prime # return the subgraph\",\n \"def get_mask(self, shape):\\n h, w = shape[0:2]\\n y, x = np.mgrid[:h, :w]\\n points = np.transpose((x.ravel(), y.ravel()))\\n\\n mask = _nxutils_points_inside_poly(points, self.verts)\\n #mask = nxutils.points_inside_poly(points, self.verts)\\n return mask.reshape(h, w)\",\n \"def compute_masks_for_splits(\\n graph):\\n masks = {}\\n num_nodes = graph.num_nodes()\\n for split, split_nodes in zip(\\n ['train', 'validation', 'test'],\\n [graph.train_nodes, graph.validation_nodes, graph.test_nodes]):\\n split_mask = np.zeros(num_nodes, dtype=bool)\\n split_mask[split_nodes] = True\\n masks[split] = split_mask\\n return masks\",\n \"def from_analysis(cls, analysis, from_node=None):\\n obj = cls()\\n if not from_node:\\n from_node = analysis.best_node()\\n\\n obj._stock = from_node.state.stock\\n actions, nodes = analysis.search_tree.route_to_node(from_node)\\n unique_mols = {}\\n\\n root_mol = nodes[0].state.mols[0]\\n obj.root = root_mol.make_unique()\\n unique_mols[id(root_mol)] = obj.root\\n obj.graph.add_node(obj.root)\\n\\n for child, action in zip(nodes[1:], actions):\\n obj._add_bipartite(child, action, unique_mols)\\n\\n obj._find_repeating_patterns()\\n return obj\",\n \"def extract_edge_induced_subgraph(self, predicate):\\n # initialize the new nodeset as sets containing disconnected copies of the original nodes\\n nodeset = {node.produce_duplicate_disconnected_node() for node in self.get_nodeset()}\\n\\n # create a null graph using the nodeset constructed above\\n G_prime = UndirectedGraph(nodeset)\\n\\n # for every edge in the original graph\\n for edge in self.get_edges():\\n if predicate(edge): # if the edge is not filtered out\\n G_prime = UndirectedGraph.__induced_subgraph_helper(G_prime, edge)\\n\\n return G_prime # return the subgraph\",\n \"def subnetwork(self, node_list):\\n return Network(adjacency=self.internal_adjacency(node_list),\\n directed=self.directed,\\n node_weights=self.node_weights[node_list],\\n silence_level=self.silence_level)\",\n \"def copy(self, new=True):\\n return UndirectedGraph(self._nodes, self._edges)\",\n \"def copy(self):\\n return AncestralGraph(self.nodes, self.directed, self.bidirected, self.undirected)\",\n \"def createMaskVariable(self, product, variable_name):\\r\\n\\r\\n mask_variable_dict = {'name': variable_name,\\r\\n 'dtype': None,\\r\\n 'vtype': 'mask',\\r\\n 'units': None,\\r\\n 'ndims': None,\\r\\n 'shape': None}\\r\\n\\r\\n mask_variable = Variable(mask_variable_dict)\\r\\n\\r\\n return mask_variable\",\n \"def mkNetCDF_mask4CVAO_African_nest(res='2x2.5', invert_mask=False,\\n regrid21x1=True):\\n import cartopy.crs as ccrs\\n import matplotlib.pyplot as plt\\n import xesmf as xe\\n ds = AC.get_LWI_map(res=res, rtn_ds=True)\\n ds = ds.transpose('lon', 'lat')\\n var2use = 'LWI'\\n # Get mask\\n m = AC.get_CVAO_Africa_nest_Masked(res=res)\\n # Name to save as\\n if regrid21x1:\\n res = '1x1'\\n savename = 'ARNA_CVAO_African_nest_{}'.format(res)\\n vals = ds[var2use].values\\n # Change mask values\\n if invert_mask:\\n vals = np.where(m, vals, 0)\\n vals = np.where(~m, vals, 1)\\n ds[var2use].values = vals\\n savename += '_inverted'\\n ExtraStr = ' inverted'\\n else:\\n vals = np.where(~m, vals, 0)\\n vals = np.where(m, vals, 1)\\n ds[var2use].values = vals\\n ExtraStr = ''\\n # Only consider variable of interest\\n ds = ds[[var2use]]\\n\\n # Plot up without mask present\\n AC.quick_map_plot(ds, var2plot=var2use, savename=savename)\\n plt.title(savename)\\n\\n # --- Add time to ds\\n # Include a time dimension to meet COARDS\\n try:\\n ds = ds.expand_dims('time', axis=0)\\n except ValueError:\\n pass\\n # Update Namings\\n Var2SaveAs = 'MASK'\\n ds = ds.rename({var2use: Var2SaveAs})\\n var2use = Var2SaveAs\\n # make sure ordering meets COARDS\\n ds = ds.transpose('time', 'lat', 'lon')\\n # --- Regrid\\n if regrid21x1:\\n # Regrid to use the same grid as the EMEP data (if the 2x2.5 fails)\\n Fstr = get_local_folder('HEMCO_data')\\n Fstr += '/MASKS/v2018-09/EMEP_mask.geos.1x1.20151222.nc'\\n dsREF = xr.open_dataset(Fstr)\\n # Create a dataset to re-grid into\\n ds_out = xr.Dataset({\\n 'lat': (['lat'], dsREF['lat']),\\n 'lon': (['lon'], dsREF['lon']),\\n })\\n # Create a regidder (to be reused )\\n regridder = xe.Regridder(ds, ds_out, 'bilinear', reuse_weights=True)\\n # Loop and regrid variables\\n ds_l = []\\n for var_ in [var2use]:\\n # Create a dataset to re-grid into\\n ds_out = xr.Dataset({\\n 'lat': (['lat'], dsREF['lat']),\\n 'lon': (['lon'], dsREF['lon']),\\n })\\n # Get a DataArray\\n dr = ds[var_] # .to_array()\\n # build regridder\\n dr_out = regridder(dr)\\n # Important note: Extra dimensions must be on the left, i.e. (time, lev, lat, lon) is correct but (lat, lon, time, lev) would not work. Most data sets should have (lat, lon) on the right (being the fastest changing dimension in the memory). If not, use DataArray.transpose or numpy.transpose to preprocess the data.\\n # exactly the same as input\\n# xr.testing.assert_identical(dr_out['time'], dr['time'])\\n # Save variable\\n ds_l += [dr_out]\\n # Combine variables\\n dsN = xr.Dataset()\\n for n, var2use in enumerate([var2use]):\\n dsN[var2use] = ds_l[n]\\n dsN[var2use].attrs = ds[var2use].attrs\\n # Clean up\\n regridder.clean_weight_file()\\n # Parse the lat and lon attrs from original array\\n dsN['lat'].attrs = ds['lat'].attrs\\n dsN['lon'].attrs = ds['lon'].attrs\\n # Now use re-gridded file\\n del ds\\n ds = dsN\\n\\n # - Plot up\\n # Select data to plot\\n a = ds[var2use].mean(dim='time')\\n # Plot up map with mask present\\n fig = plt.figure(figsize=(10, 6))\\n ax = fig.add_subplot(111, projection=ccrs.Robinson(), aspect='auto')\\n a.plot.imshow(x='lon', y='lat', ax=ax, transform=ccrs.PlateCarree())\\n plt.title(savename)\\n plt.savefig(savename+'.png')\\n plt.close()\\n\\n # - Update attrs etc\\n try:\\n ds = ds.expand_dims('time', axis=0)\\n except ValueError:\\n pass\\n ds = ds.assign_coords(time=[0])\\n attrs = ds['time'].attrs\\n attrs['standard_name'] = 'Time'\\n attrs['long_name'] = attrs['standard_name']\\n attrs['axis'] = 'T'\\n attrs['units'] = 'hours since 2000-01-01 00:00:00'\\n attrs['calendar'] = 'standard'\\n ds['time'].attrs = attrs\\n # Save array as float32 instead of float 64\\n ds[Var2SaveAs].values = ds[Var2SaveAs].astype(np.float32).values\\n # Update MASK attributes\\n MainVarTitle = 'MASK of African high-res model nest '+ExtraStr\\n attrs = ds[var2use].attrs\\n attrs['standard_name'] = Var2SaveAs\\n attrs['long_name'] = MainVarTitle\\n# attrs['units'] = int(1)\\n attrs['units'] = 'unitless'\\n attrs['add_offset'] = int(0)\\n attrs['scale_factor'] = int(1)\\n attrs['missing_value'] = float(-1e-32)\\n attrs['_FillValue'] = float(-1e-32)\\n # Remove the vestigial ctm_units attribute\\n try:\\n del attrs['ctm_units']\\n except:\\n pass\\n ds[var2use].attrs = attrs\\n # Global attributes\\n attrs = ds.attrs\\n attrs['conventions'] = 'COARDS'\\n attrs['contact'] = 'tomas.sherwen@york.ac.uk'\\n attrs['title'] = MainVarTitle\\n attrs['history'] = 'Created {}'.format(time.ctime(time.time()))\\n# attrs['format'] = 'NetCDF-4'\\n attrs['format'] = 'NETCDF3_CLASSIC'\\n ds.attrs = attrs\\n # Save as NetCDF\\n# ds.to_netcdf( savename+'.nc', engine='scipy' )\\n ds.to_netcdf(savename+'.nc', format='NETCDF3_CLASSIC')\",\n \"def make_auxiliar_network(edges):\\n\\n s = S;t = T;na = {}\\n fl = deque([s]) # fathers layer\\n cl = deque([]) # childrens layer\\n level = 0\\n vl = {s:level} # vertex : level\\n while len(fl) > 0:\\n key = fl.popleft()\\n for e in edges:\\n if e['used']: continue\\n \\n r = e['capacity'] - e['flow']\\n if key == e['first'] and r > 0:\\n v = {'id':e['last'], 'direction':'F'}\\n elif key == e['last'] and e['flow'] > 0:\\n v = {'id':e['first'], 'direction':'B'}\\n else: continue\\n \\n if v['id'] not in cl: \\n cl.append(v['id'])\\n if key not in na:\\n na[key] = []\\n\\n if v['id'] not in vl:\\n vl[v['id']] = level\\n if vl[v['id']] == level:\\n na[key].append(v)\\n e['used'] = True\\n\\n \\n if len(fl) == 0: fl = cl; cl = deque([]); level += 1\\n if len(fl) == 0 or t in fl: break\\n\\n complete = False\\n # remove all vertex except t from last layer\\n for n in [k for k in vl if vl[k] == level-1]: \\n if n == t:\\n complete = True\\n continue\\n for k in na:\\n na[k] = [v for v in na[k] if v['id'] != n]\\n\\n \\n return {'na':na, 'complete':complete}\",\n \"def _internal_build(self):\\n self.nodes = self.__tree.Nodes()\\n self.edges = self.__tree.Edges()\\n self.augmentedEdges = {}\\n for key, val in self.__tree.AugmentedEdges().items():\\n self.augmentedEdges[key] = list(val)\\n self.root = self.__tree.Root()\\n\\n seen = set()\\n self.branches = set()\\n\\n # Find all of the branching nodes in the tree, degree > 1\\n # That is, they appear in more than one edge\\n for e1, e2 in self.edges:\\n if e1 not in seen:\\n seen.add(e1)\\n else:\\n self.branches.add(e1)\\n\\n if e2 not in seen:\\n seen.add(e2)\\n else:\\n self.branches.add(e2)\\n\\n # The nodes that are not branches are leaves\\n self.leaves = set(self.nodes.keys()) - self.branches\\n self.leaves.remove(self.root)\",\n \"def Expand_Mask(mask, feature_dict):\\n new_mask = np.zeros(mask.shape + (len(feature_dict),))\\n for i in feature_dict.keys():\\n ni = int(i)\\n new_mask[mask == ni,ni] = 1 \\n return new_mask\",\n \"def get_subgraphs(graph):\\n nodes_powerset = get_nodes_combinations(graph)\\n #print(\\\"Doing\\\")\\n #draw_graph(graph)\\n subgraphs = []\\n for nodes in nodes_powerset:\\n subg = graph.subgraph(nodes)\\n nodes = subg.nodes(data=True)\\n if nx.is_weakly_connected(subg):\\n subgraphs.append(subg)\\n return subgraphs\",\n \"def _select_masks_to_boundaries(self, select_masks):\\n\\n def _merge(node_covers, select_idx):\\n \\\"\\\"\\\"\\n node_covers [[s1, e1], [s2, e2], ..., [sn, en]]\\n \\\"\\\"\\\"\\n new_node_covers = []\\n for i in range(len(node_covers) - 1):\\n if i == select_idx:\\n merge_node_boundary = [node_covers[select_idx][0], node_covers[select_idx + 1][1]]\\n new_node_covers.append(merge_node_boundary)\\n elif i < select_idx:\\n new_node_covers.append(node_covers[i])\\n else:\\n new_node_covers.append(node_covers[i + 1])\\n return new_node_covers, merge_node_boundary\\n batch_size = select_masks[0].size()[0]\\n max_length = select_masks[0].size()[1] + 1\\n combine_matrix = torch.rand(batch_size, max_length, 2).long()\\n for j in range(max_length):\\n combine_matrix[:, j, :] = j\\n results = []\\n for batch_idx in range(batch_size):\\n node_covers = combine_matrix[batch_idx, :, :].numpy().tolist()\\n result = []\\n for node_idx in range(max_length - 2):\\n select = select_masks[node_idx][batch_idx, :]\\n select_idx = torch.nonzero(select).data[0][0]\\n node_covers, merge_boundary = _merge(node_covers, select_idx)\\n result.append(merge_boundary)\\n results.append(result)\\n results = torch.LongTensor(results)\\n return results\",\n \"def get_induced_subgraph(graph, subset):\\n\\t\\n\\tgraph_edges = graph.E\\n\\tvertices = list(graph.V)\\n\\n\\t# construct the induced subgraph\\n\\n\\tnew_graph_edge = {}\\n\\tnew_graph_vertices = subset\\n\\n\\tfor start in graph_edges.keys():\\n\\t\\tif start in new_graph_vertices:\\n\\t\\t\\tfor stop in graph_edges[start]:\\n\\t\\t\\t\\tif stop in new_graph_vertices:\\n\\t\\t\\t\\t\\t# add it to new_graph_edge\\n\\t\\t\\t\\t\\tif start in new_graph_edge:\\n\\t\\t\\t\\t\\t\\tnew_graph_edge[start].append(stop)\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\tnew_graph_edge[start] = [stop]\\n\\n\\t#print new_graph_vertices\\t\\t\\t\\t\\t\\n\\t#print new_graph_edge\\n\\treturn UndirectedGraph(new_graph_vertices, new_graph_edge)\",\n \"def via_mask_from(self, mask: Mask2D) -> Visuals2D:\\r\\n origin = self.origin_via_mask_from(mask=mask)\\r\\n mask_visuals = self.get(\\\"mask\\\", mask)\\r\\n border = self.get(\\\"border\\\", mask.derive_grid.border_sub_1.binned)\\r\\n\\r\\n return self.visuals + self.visuals.__class__(\\r\\n origin=origin, mask=mask_visuals, border=border\\r\\n )\",\n \"def getMoreComplexInLayerGraph(self):\\n makeLayers = self.makeLayers\\n addNodesToLayer = self.addNodesToLayer\\n addNodeToLayer = self.addNodeToLayer\\n eastWestEdgeFromTo = self.eastWestEdgeFromTo\\n addInLayerEdge = self.addInLayerEdge\\n setFixedOrderConstraint = self.setFixedOrderConstraint\\n\\n layers = makeLayers(3)\\n leftNodes = addNodesToLayer(4, layers[0])\\n middleNodes = addNodesToLayer(3, layers[1])\\n rightNode = addNodeToLayer(layers[2])\\n setFixedOrderConstraint(middleNodes[0])\\n setFixedOrderConstraint(middleNodes[1])\\n\\n eastWestEdgeFromTo(leftNodes[1], middleNodes[0])\\n\\n eastWestEdgeFromTo(leftNodes[3], middleNodes[1])\\n eastWestEdgeFromTo(leftNodes[2], middleNodes[1])\\n addInLayerEdge(middleNodes[0], middleNodes[1], PortSide.WEST)\\n eastWestEdgeFromTo(leftNodes[0], middleNodes[0])\\n addInLayerEdge(middleNodes[0], middleNodes[2], PortSide.WEST)\\n\\n addInLayerEdge(middleNodes[0], middleNodes[1], PortSide.EAST)\\n eastWestEdgeFromTo(middleNodes[0], rightNode)\\n\\n return self.graph\",\n \"def getMask(label, scribble, class_id, class_ids):\\n # Dense Mask\\n fg_mask = torch.where(label == class_id,\\n torch.ones_like(label), torch.zeros_like(label))\\n bg_mask = torch.where(label != class_id,\\n torch.ones_like(label), torch.zeros_like(label))\\n for class_id in class_ids:\\n bg_mask[label == class_id] = 0\\n\\n # Scribble Mask\\n bg_scribble = scribble == 0\\n fg_scribble = torch.where((fg_mask == 1)\\n & (scribble != 0)\\n & (scribble != 255),\\n scribble, torch.zeros_like(fg_mask))\\n scribble_cls_list = list(set(np.unique(fg_scribble)) - set([0,]))\\n if scribble_cls_list: # Still need investigation\\n fg_scribble = fg_scribble == random.choice(scribble_cls_list).item()\\n else:\\n fg_scribble[:] = 0\\n\\n return {'fg_mask': fg_mask,\\n 'bg_mask': bg_mask,\\n 'fg_scribble': fg_scribble.long(),\\n 'bg_scribble': bg_scribble.long()}\",\n \"def mask(self):\\n mask = np.zeros((self.height, self.width))\\n pts = [\\n np.array(anno).reshape(-1, 2).round().astype(int)\\n for anno in self.segmentation\\n ]\\n mask = cv2.fillPoly(mask, pts, 1)\\n return mask\",\n \"def model_masks(self, prunable=None):\\n # TODO Also accept a dataloader\\n pass\\n # return masks\",\n \"def sub_graph_merging(self):\",\n \"def mask_infeasible(self):\\n ns = len(self)-1\\n # mask entries with i+j+k > ns\\n for ii in range(len(self)):\\n for jj in range(len(self)):\\n for kk in range(len(self)):\\n if ii+jj+kk > ns:\\n self.mask[ii,jj,kk] = True\\n \\n return self\",\n \"def build_graph(edges):\\n \\n G = nx.MultiGraph()\\n G.add_edges_from(edges)\\n return G\",\n \"def get_induced_subgraph(graph: Graph, nodes: Nodes):\\n return {node: graph[node].intersection(nodes) for node in nodes}\",\n \"def mask_border(self, left=3, right=3, top=3, bottom=3):\\n self.MaskPrefix = 'b' + self.MaskPrefix #prepend 'b' for border\\n print('Masking edge pixels: left={0}, right={1}, top={2}, bottom={3}'.format(left,right,top,bottom))\\n for ig in self.Set:\\n igram = self.load_ma(ig)\\n igram[:top,:] = ma.masked\\n igram[-bottom:,:] = ma.masked\\n igram[:,:left] = ma.masked\\n igram[:,-right:] = ma.masked\\n mskFile = self.MaskPrefix + 'Mask_' + ig.Name[:-4]\\n np.save(os.path.join(self.ProcDir, mskFile), igram.mask)\\n print(mskFile)\\n print('mask_border() complete: {0} interferograms'.format(self.Set.Nig))\",\n \"def fill_input_masks(nx_node, nx_graph):\\n input_edges = sorted(list(nx_graph.in_edges(nx_node['key'])), key=lambda edge: nx_graph.edges[edge]['in_port'])\\n input_masks = [nx_graph.nodes[input_node]['output_mask'] for input_node, _ in input_edges]\\n\\n filled_input_masks = []\\n for i, mask in enumerate(input_masks):\\n if mask is None:\\n mask = torch.ones(nx_graph.edges[input_edges[i]]['activation_shape'][1])\\n filled_input_masks.append(mask)\\n return input_masks, filled_input_masks\",\n \"def __init__(self, nodes, infimum=1e-8):\\n self.nodes, (self.nn, self.dim) = nodes, nodes.shape\\n\\n # generate anisotropic simplices\\n delaunay = Delaunay(self.nodes)\\n simplices = delaunay.simplices\\n volumes = np.linalg.det(self.nodes[simplices[:, :-1]] - self.nodes[simplices[:, [-1]]])\\n valid_indices = [i for i, v in enumerate(volumes) if np.abs(v) > infimum]\\n simplices = simplices[valid_indices, :]\\n volumes = volumes[valid_indices]\\n\\n # generate mask of convex hull\\n mask = np.expand_dims(self.nodes[delaunay.convex_hull], axis=1) - np.expand_dims(self.nodes, axis=(0, 2))\\n self.mask = np.min(np.abs(np.linalg.det(mask)), axis=0) == 0\\n\\n # generate isotropic simplices\\n def reverse(spx): return spx[[0, 2, 1] + list(range(3, spx.__len__()))]\\n self.simplices = np.array([spx if flag else reverse(spx) for spx, flag in zip(simplices, volumes > 0)])\\n self.nt = self.simplices.shape[0]\\n\\n # generate isotropic surfaces of simplices.\\n self.surfaces = np.stack([np.roll(self.simplices, -k, 1) if k * self.dim % 2 else reverse(np.roll(self.simplices, -k, 1).T).T for k in range(self.dim + 1)], axis=1)[:, :, 1:]\\n\\n # generate minors and determinants of `tensor` in isotropic mode.\\n # +- x_{t,0,0} & \\\\cdots & x_{t,0,ND-1} & 1 -+\\n # tensor[t, :, :] = | \\\\vdots & \\\\ddots & \\\\vdots & \\\\vdots |\\n # +- x_{t,ND,0} & \\\\cdots & x_{t,ND,ND-1} & 1 -+\\n tensor = np.concatenate([self.nodes[self.simplices, :], np.ones(shape=(self.simplices.__len__(), self.dim + 1, 1))], axis=-1)\\n self.determinants = np.abs(volumes)\\n self.minors = np.einsum(\\\"tij,t->tji\\\", np.linalg.inv(tensor), self.determinants)\",\n \"def edge_subgraph(\\n self,\\n subset_dict: Dict[EdgeType, Tensor],\\n ) -> 'HeteroData':\\n data = copy.copy(self)\\n\\n for edge_type, subset in subset_dict.items():\\n edge_store, new_edge_store = self[edge_type], data[edge_type]\\n for key, value in edge_store.items():\\n if edge_store.is_edge_attr(key):\\n dim = self.__cat_dim__(key, value, edge_store)\\n if subset.dtype == torch.bool:\\n new_edge_store[key] = mask_select(value, dim, subset)\\n else:\\n new_edge_store[key] = value.index_select(dim, subset)\\n\\n return data\",\n \"def get_input_masks(nx_node, nx_graph):\\n input_edges = list(nx_graph.in_edges(nx_node[\\\"key\\\"]))\\n input_masks = [nx_graph.nodes[input_node][\\\"output_mask\\\"] for input_node, _ in input_edges]\\n return input_masks\",\n \"def __deepcopy__(self, memodict={}):\\n nodes = [deepcopy(n) for n in self.nodes]\\n return Network(nodes)\",\n \"def get_mask(self, nodetype):\\n print(\\\"Deprecation warning: Do it yourself.\\\")\\n assert nodetype in [PAPER_TYPE, SUBJECT_TYPE, AUTHOR_TYPE], \\\"Unknown node type\\\"\\n return (self.ndata.type == nodetype).values\",\n \"def get_input_masks(nx_node, nx_graph):\\n input_edges = list(nx_graph.in_edges(nx_node['key']))\\n input_masks = [nx_graph.nodes[input_node]['output_mask'] for input_node, _ in input_edges]\\n return input_masks\",\n \"def mask(self):\\n\\n mask = np.zeros(shape=(self._info.height, self._info.width), dtype=np.uint8)\\n\\n self.draw(image=mask, color=constants.COLOR_WHITE_MONO)\\n\\n mask_with_border = np.pad(mask, 1, 'constant', constant_values=255)\\n\\n cv2.floodFill(image=mask,\\n mask=mask_with_border,\\n seedPoint=(int(self.middle_point[0]), int(self.middle_point[1])),\\n newVal=constants.COLOR_WHITE_MONO)\\n\\n return mask\",\n \"def get_mask(self, base_mask, contribution, num_prune):\\n prune_indices = torch.argsort(contribution)[:num_prune]\\n for idx in prune_indices:\\n base_mask['weight_mask'][idx] = 0.\\n if base_mask['bias_mask'] is not None:\\n base_mask['bias_mask'][idx] = 0.\\n return base_mask\",\n \"def map_edges(clone):\\n \\n pcr.setglobaloption('unittrue')\\n xmin, xmax, ymin, ymax, nr_rows, nr_cols, cell_size = clone_attributes()\\n clone = pcr.ifthenelse(pcr.defined(clone), pcr.boolean(1), pcr.boolean(1))\\n x_coor = pcr.xcoordinate(clone)\\n y_coor = pcr.ycoordinate(clone)\\n north = y_coor > (ymax - cell_size)\\n south = y_coor < (ymin + cell_size)\\n west = x_coor < (xmin + cell_size)\\n east = x_coor > (xmax - cell_size)\\n edges = north | south | west | east\\n return edges\",\n \"def get_copy_of_graph(self):\\r\\n return deepcopy(self)\",\n \"def build_auxiliary_node_connectivity(G):\\n directed = G.is_directed()\\n\\n mapping = {}\\n H = nx.DiGraph()\\n\\n for i, node in enumerate(G):\\n mapping[node] = i\\n H.add_node('%dA' % i, id=node)\\n H.add_node('%dB' % i, id=node)\\n H.add_edge('%dA' % i, '%dB' % i, capacity=1)\\n\\n edges = []\\n for (source, target) in G.edges():\\n edges.append(('%sB' % mapping[source], '%sA' % mapping[target]))\\n if not directed:\\n edges.append(('%sB' % mapping[target], '%sA' % mapping[source]))\\n H.add_edges_from(edges, capacity=1)\\n\\n # Store mapping as graph attribute\\n H.graph['mapping'] = mapping\\n return H\",\n \"def generate_mask(self):\\n\\n polymer_length = len(self.sequence)\\n protein_length = len(self.particle_order) - polymer_length\\n\\n if self.filter_specification == 'type':\\n mask = np.in1d(self.particle_order, self.monomer_id)\\n elif self.filter_specification == 'id':\\n if self.molecule == 'polymer':\\n offset = protein_length\\n else:\\n offset = 0\\n mask = np.array([False] * (polymer_length + protein_length))\\n absolute_id = [x+offset for x in self.monomer_id]\\n mask[absolute_id] = True\\n else:\\n raise NotImplementedError(\\\"Filter is unknown. Use 'type' or 'id'!\\\")\\n\\n # if molecule == 'full', nothing needs to be done\\n if self.molecule == 'polymer':\\n mask[:protein_length] = [False] * protein_length\\n elif self.molecule == 'protein':\\n mask[protein_length:] = [False] * polymer_length\\n\\n return mask\",\n \"def nonconnected():\\n nonconnected = nx.MultiDiGraph()\\n nonconnected.add_nodes_from(range(6))\\n nonconnected.add_edges_from([\\n (0, 1),\\n (1, 2),\\n (2, 3),\\n (3, 0),\\n (1, 0),\\n (1, 0),\\n (3, 2),\\n (3, 3),\\n (4, 4),\\n (4, 4)\\n ])\\n return nonconnected\",\n \"def mask(self):\\n return type(self)(self.data.mask, self.bset)\",\n \"def _source_mask(self, ilens):\\n x_masks = make_non_pad_mask(ilens)\\n return x_masks.unsqueeze(-2)\",\n \"def _initalize_mask(dataSubStack):\\n # Initalize an array to store the output mask values\\n outMask = np.zeros(dataSubStack.shape, dtype=bool)\\n\\n # Start by masking out NaNs or Infs\\n NaNsOrInfs = np.logical_not(np.isfinite(dataSubStack.data))\\n dataSubStack.mask = NaNsOrInfs\\n\\n return outMask, dataSubStack\",\n \"def load_mask(self, image_id):\\n # If not homeobject dataset, delegate to parent class.\\n image_info = self.image_info[image_id]\\n if image_info[\\\"source\\\"] != 'homeobject':\\n print(\\n \\\"Warn: \\\\'{}\\\\' label not found. Processing with parent load_mask.\\\".format(image_info[\\\"source\\\"]))\\n return super(self.__class__, self).load_mask(image_id)\\n\\n # Convert polygons to a bitmap mask of shape\\n class_ids = image_info['class_ids']\\n info = self.image_info[image_id]\\n mask = np.zeros([info[\\\"height\\\"], info[\\\"width\\\"], len(info[\\\"polygons\\\"])], dtype=np.uint8)\\n for i, p in enumerate(info[\\\"polygons\\\"]):\\n # Get indexes of pixels inside the polygon and set them to 1\\n rr, cc = skimage.draw.polygon(p['all_points_y'], p['all_points_x'])\\n\\n # modify dirt mask if it resides outside of image boundary\\n rr[rr > mask.shape[0] - 1] = mask.shape[0] - 1\\n cc[cc > mask.shape[1] - 1] = mask.shape[1] - 1\\n\\n mask[rr, cc, i] = 1\\n # Return mask, and array of class IDs of each instance. Since we have\\n # one class ID only, we return an array of 1s\\n class_ids = np.array(class_ids, dtype=np.int32)\\n # return mask.astype(np.bool), np.ones([mask.shape[-1]], dtype=np.int32)\\n return mask, class_ids\",\n \"def make_mask(data, pad):\\n def subsequent_mask(size):\\n \\\"\\\"\\\" helper function for creating the masks. \\\"\\\"\\\"\\n attn_shape = (1, size, size)\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\n\\n mask = (data != pad).unsqueeze(-2)\\n mask = mask & Variable(\\n subsequent_mask(data.size(-1)).type_as(mask.data))\\n return mask\",\n \"def infer_reuse_pattern(fgraph, outputs_to_disown):\\r\\n rval = set()\\r\\n for o in outputs_to_disown:\\r\\n view_tree_set(alias_root(o), rval)\\r\\n # remove from rval all of the inputs, constants, values.\\r\\n rval = set(r for r in rval if r.owner is not None)\\r\\n\\r\\n return rval\",\n \"def subgraph(self, nodes_to_include=None, edges_to_include=None,\\n nodes_to_exclude=None, edges_to_exclude=None):\\n if nodes_to_include is None:\\n node_filter_prop = self.graph.new_vertex_property(\\n \\\"bool\\\", val=True)\\n if nodes_to_exclude is not None:\\n indices_to_exclude = [\\n _get_vertex_obj(self.graph, n)\\n for n in nodes_to_exclude\\n ]\\n for i in indices_to_exclude:\\n node_filter_prop[i] = False\\n else:\\n node_filter_prop = self.graph.new_vertex_property(\\n \\\"bool\\\", val=False)\\n indices_to_include = [\\n _get_vertex_obj(self.graph, n)\\n for n in nodes_to_include\\n ]\\n for i in indices_to_include:\\n node_filter_prop[i] = True\\n\\n if edges_to_include is None:\\n edge_filter_prop = self.graph.new_edge_property(\\n \\\"bool\\\", val=True)\\n if edges_to_exclude is not None:\\n sources = [\\n _get_vertex_obj(self.graph, s)\\n for s, _ in edges_to_exclude\\n ]\\n targets = [\\n _get_vertex_obj(self.graph, t)\\n for _, t in edges_to_exclude\\n ]\\n for s, t in zip(sources, targets):\\n edge_filter_prop[self.graph.edge(s, t)] = False\\n else:\\n edge_filter_prop = self.graph.new_edge_property(\\n \\\"bool\\\", val=False)\\n sources = [\\n _get_vertex_obj(self.graph, s)\\n for s, _ in edges_to_include\\n ]\\n targets = [\\n _get_vertex_obj(self.graph, t)\\n for _, t in edges_to_include\\n ]\\n for s, t in zip(sources, targets):\\n edge_filter_prop[self.graph.edge(s, t)] = True\\n\\n return GraphView(\\n self.graph,\\n vfilt=node_filter_prop,\\n efilt=edge_filter_prop)\",\n \"def _build_dependency_graph(self):\\n\\n #\\n # Find the binary roles\\n #\\n nodes, roles = self._find_roles()\\n\\n #\\n # Build the graph\\n #\\n working_list = list(set(nodes.keys()))\\n\\n setters = [b for b, r in roles.items() if Role.SETTER in r or Role.SETTER_GETTER in r]\\n\\n while working_list:\\n b = working_list[0]\\n working_list = working_list[1:]\\n\\n if nodes[b] not in self._graph:\\n self._graph[nodes[b]] = []\\n\\n # it's a root node\\n if Role.GETTER not in roles[b] and Role.SETTER_GETTER not in roles[b]:\\n nodes[b].set_root()\\n\\n # takes params from some other binary\\n else:\\n is_orphan = True\\n for setter in setters:\\n setter_strings_set = set(nodes[setter].role_strings)\\n node_strings_set = set(nodes[b].role_strings)\\n if setter_strings_set.intersection(node_strings_set):\\n if nodes[setter] not in self._graph:\\n self._graph[nodes[setter]] = []\\n self._graph[nodes[setter]].append(nodes[b])\\n is_orphan = False\\n\\n # mark orphans\\n if is_orphan:\\n nodes[b].set_orphan()\\n\\n # Clean up\\n for k, childs in self._graph.iteritems():\\n self._graph[k] = list(set(childs))\\n\\n # set leaves\\n for k, c in self._graph.iteritems():\\n if not c:\\n k.set_leaf()\\n\\n # post processing:\\n # remove those nodes that are not orphans\\n # and are not network parsers\\n\\n nodes = self.nodes\\n children = [c for x in self._graph.values() for c in x if x]\\n leafs_non_orphan = [n for n in nodes if n.leaf and not n.orphan]\\n seed_names = [x.split('/')[-1] for x in self._seed_bins]\\n spurious_nodes = [n for n in leafs_non_orphan if n not in children and n.bin.split('/')[-1] not in seed_names]\\n for to_rem in spurious_nodes:\\n del self._graph[to_rem]\",\n \"def make_mask(data, pad):\\n\\n def subsequent_mask(size):\\n \\\"\\\"\\\" helper function for creating the masks. \\\"\\\"\\\"\\n attn_shape = (1, size, size)\\n subsequent_mask = np.triu(np.ones(attn_shape), k=1).astype('uint8')\\n return torch.from_numpy(subsequent_mask) == 0\\n\\n mask = (data != pad).unsqueeze(-2)\\n mask = mask & Variable(\\n subsequent_mask(data.size(-1)).type_as(mask.data))\\n return mask\",\n \"def randomize_graph(graph, nodePositions, mask, planar=0, iterations=1000):\\n nodeNumber = graph.number_of_nodes()\\n edgeNumber = graph.number_of_edges()\\n randomizedGraph = nx.empty_graph(nodeNumber, nx.MultiGraph())\\n edgeLengths = np.array([property['edist'] for node1, node2, property in graph.edges(data=True)])\\n bins = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 9999]\\n binNumber = len(bins) - 1\\n edgeBins = np.zeros(edgeNumber).astype('int')\\n for index, (bin1, bin2) in enumerate(zip(bins[:-1], bins[1:])):\\n edgesInBin = (edgeLengths >= bin1) * (edgeLengths < bin2)\\n edgeBins[edgesInBin] = index\\n edgeWeights = np.array([property['weight'] for node1, node2, property in graph.edges(data=True)])\\n edgeCapacities = np.array([property['capa'] for node1, node2, property in graph.edges(data=True)])\\n redoRandomization = 1\\n iterationNumber = 0\\n while (redoRandomization == 1 and iterationNumber < iterations):\\n iterationNumber += 1\\n nodePositionsRandom = cell_sample(mask, nodeNumber)[:, ::-1].astype('int')\\n distanceMatrix = sp.spatial.distance_matrix(nodePositionsRandom, nodePositionsRandom)\\n edgeBinsRandom = np.zeros((nodeNumber, nodeNumber)).astype('int')\\n for index, (bin1, bin2) in enumerate(zip(bins[:-1], bins[1:])):\\n edgesInBin = (distanceMatrix >= bin1) * (distanceMatrix < bin2)\\n edgeBinsRandom[edgesInBin] = index\\n edgeBinsRandom[np.tri(nodeNumber) > 0] =- 9999\\n redoRandomization = 1 * np.max([(edgeBinsRandom == bins).sum() < (edgeBins == bins).sum() for bins in range(binNumber)])\\n if (iterationNumber < iterations):\\n sortBins = np.argsort(edgeLengths)[::-1]\\n edgeBinsSort = edgeBins[sortBins]\\n edgeWeightsSort = edgeWeights[sortBins]\\n edgeCapacitiesSort = edgeCapacities[sortBins]\\n addedEdges = []\\n for edge in range(edgeNumber):\\n candidateNodes = np.where(edgeBinsRandom == edgeBinsSort[edge])\\n candidateNumber = len(candidateNodes[0])\\n edgeCrossings = 9999\\n selectedCandidates = random.sample(range(candidateNumber), min(50, candidateNumber))\\n for candidate in selectedCandidates:\\n node1 = candidateNodes[0][candidate]\\n node2 = candidateNodes[1][candidate]\\n edgeBetweenNodes = np.array([[nodePositionsRandom[node1][0], nodePositionsRandom[node2][0]], [nodePositionsRandom[node1][1], nodePositions[node2][1]]]).T\\n crossingsOfEdges = planar * multi_line_intersect(np.array(edgeBetweenNodes), np.array(addedEdges)).sum()\\n if (crossingsOfEdges < edgeCrossings and edgeBinsRandom[node1, node2] >= 0):\\n edgeCrossings = crossingsOfEdges\\n selectedEdge = edgeBetweenNodes\\n selectedNode1, selectedNode2 = node1, node2\\n addedEdges.append(selectedEdge)\\n nodeDistanceRandom = distanceMatrix[selectedNode1, selectedNode2]\\n filamentLengthRandom = 1.0 * np.ceil(nodeDistanceRandom)\\n edgeWeightRandom = edgeWeightsSort[edge]\\n edgeCapacityRandom = edgeCapacitiesSort[edge]\\n edgeLengthRandom = 1.0 * filamentLengthRandom / edgeWeightRandom\\n edgeConnectivityRandom = 0\\n edgeJumpRandom = 0\\n edgeMultiplicity = 1\\n randomizedGraph.add_edge(selectedNode1, selectedNode2, edist=nodeDistanceRandom, fdist=filamentLengthRandom, weight=edgeWeightRandom, capa=edgeCapacityRandom, lgth=edgeLengthRandom, conn=edgeConnectivityRandom, jump=edgeJumpRandom, multi=edgeMultiplicity)\\n edgeBinsRandom[selectedNode1, selectedNode2] =- 9999\\n edgeBinsRandom[selectedNode2, selectedNode1] =- 9999\\n else:\\n edgeProperties = np.array([property for node1, node2, property in graph.edges(data=True)])\\n random.shuffle(edgeProperties)\\n randomizedGraph = graph.copy()\\n for index, (node1, node2, properties) in enumerate(randomizedGraph.edges(data=True)):\\n for key in properties.keys():\\n properties[key] = edgeProperties[index][key]\\n nodePositionsRandom = nodePositions\\n return(randomizedGraph, nodePositionsRandom)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69909257","0.6730791","0.6133464","0.60049623","0.5896379","0.5863855","0.5832731","0.57625717","0.5693712","0.5613123","0.55460924","0.553991","0.5532406","0.54798096","0.53914773","0.53446835","0.53339267","0.5312013","0.5276624","0.52759224","0.52489316","0.5247374","0.5239885","0.51817673","0.5179462","0.5137593","0.5126325","0.5114081","0.5093612","0.50912833","0.5071981","0.5059149","0.5047951","0.5047666","0.504139","0.50253934","0.5021002","0.50142753","0.5009846","0.49965286","0.49813023","0.49766016","0.4969476","0.49569052","0.4955974","0.49549916","0.49536768","0.49515906","0.49451947","0.49437675","0.49368095","0.4925801","0.49223018","0.49221873","0.49217403","0.4918265","0.49054056","0.4904672","0.49040496","0.4901798","0.48914984","0.4889013","0.48859397","0.4879795","0.48792607","0.48782805","0.4874577","0.4873906","0.48730704","0.48693138","0.48664227","0.48661616","0.48642987","0.48563915","0.4848582","0.4847957","0.48476005","0.48376667","0.48373228","0.48301318","0.4825252","0.48223746","0.48143378","0.48141214","0.48091683","0.48063016","0.4790591","0.4786188","0.4772961","0.4772278","0.47680286","0.47608942","0.47583485","0.47567213","0.47561935","0.47514257","0.4749913","0.4746324","0.47462437","0.4734964"],"string":"[\n \"0.69909257\",\n \"0.6730791\",\n \"0.6133464\",\n \"0.60049623\",\n \"0.5896379\",\n \"0.5863855\",\n \"0.5832731\",\n \"0.57625717\",\n \"0.5693712\",\n \"0.5613123\",\n \"0.55460924\",\n \"0.553991\",\n \"0.5532406\",\n \"0.54798096\",\n \"0.53914773\",\n \"0.53446835\",\n \"0.53339267\",\n \"0.5312013\",\n \"0.5276624\",\n \"0.52759224\",\n \"0.52489316\",\n \"0.5247374\",\n \"0.5239885\",\n \"0.51817673\",\n \"0.5179462\",\n \"0.5137593\",\n \"0.5126325\",\n \"0.5114081\",\n \"0.5093612\",\n \"0.50912833\",\n \"0.5071981\",\n \"0.5059149\",\n \"0.5047951\",\n \"0.5047666\",\n \"0.504139\",\n \"0.50253934\",\n \"0.5021002\",\n \"0.50142753\",\n \"0.5009846\",\n \"0.49965286\",\n \"0.49813023\",\n \"0.49766016\",\n \"0.4969476\",\n \"0.49569052\",\n \"0.4955974\",\n \"0.49549916\",\n \"0.49536768\",\n \"0.49515906\",\n \"0.49451947\",\n \"0.49437675\",\n \"0.49368095\",\n \"0.4925801\",\n \"0.49223018\",\n \"0.49221873\",\n \"0.49217403\",\n \"0.4918265\",\n \"0.49054056\",\n \"0.4904672\",\n \"0.49040496\",\n \"0.4901798\",\n \"0.48914984\",\n \"0.4889013\",\n \"0.48859397\",\n \"0.4879795\",\n \"0.48792607\",\n \"0.48782805\",\n \"0.4874577\",\n \"0.4873906\",\n \"0.48730704\",\n \"0.48693138\",\n \"0.48664227\",\n \"0.48661616\",\n \"0.48642987\",\n \"0.48563915\",\n \"0.4848582\",\n \"0.4847957\",\n \"0.48476005\",\n \"0.48376667\",\n \"0.48373228\",\n \"0.48301318\",\n \"0.4825252\",\n \"0.48223746\",\n \"0.48143378\",\n \"0.48141214\",\n \"0.48091683\",\n \"0.48063016\",\n \"0.4790591\",\n \"0.4786188\",\n \"0.4772961\",\n \"0.4772278\",\n \"0.47680286\",\n \"0.47608942\",\n \"0.47583485\",\n \"0.47567213\",\n \"0.47561935\",\n \"0.47514257\",\n \"0.4749913\",\n \"0.4746324\",\n \"0.47462437\",\n \"0.4734964\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5328217"},"document_rank":{"kind":"string","value":"17"}}},{"rowIdx":13084,"cells":{"query":{"kind":"string","value":"return a cursor to a query"},"document":{"kind":"string","value":"def query_to_cur(dbh, qry, args):\n if args.debug:\n print(datetime.datetime.strftime(datetime.datetime.now(), \"%D %H:%m:%S\"), qry, file=sys.stderr)\n t0 = time.time()\n cur = dbh.cursor()\n cur.execute(qry)\n print(\"query took\", time.time() - t0, \"seconds\")\n return cur"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_cursor(self):\r\n cursor = self.connection.cursor()\r\n return cursor","def cursor():\n dbh = handle()\n return dbh.cursor()","def get_cursor(self, *args, **kwargs):","def _cursor(self):\n cursor = self.conn.cursor()\n\n return cursor","def cursor(self):\n return self._conn.cursor()","def get_cursor():\n cur = conn.cursor(cursor_factory=DictCursor)\n return cur","def cursor(self):\n with self.connection() as conn:\n cursor = conn.cursor(prepared=True)\n try:\n yield cursor\n finally:\n cursor.close()","def cursor(self):\n with self.conn as c:\n yield c.cursor()","def cursor(self):\n with self.conn as c:\n yield c.cursor()","def cursor(self):\n cursor = Cursor(self, self.__aceQLHttpApi)\n return cursor","def oracle_cursor(query):\n conf_file_dir = os.path.dirname(os.path.realpath(__file__))\n conf_file = conf_file_dir + os.sep + '.setup.conf'\n (username, password, host, port, sid) = credential_setup(conf_file)\n dsn_tns = cx_Oracle.makedsn(host, port, sid)\n connection = cx_Oracle.connect(username, password, dsn_tns)\n cursor = connection.cursor()\n cursor.execute(query)\n\n return cursor","def get_cursor(self):\n self.cur = self.dbcon.cursor()\n return self.cur","def cursor(self):\n return self.conn.cursor()","def get_cursor():\n return _thread_local.connection.cursor()","def cursor(self) -> NamedTupleCursor:\n return self.connection.cursor","def _get_cursor(self):\n conn = self._connect()\n conn.autocommit = True\n cursor = conn.cursor()\n return cursor","def get_cursor(self):\n return self.connection.cursor()","def cursor(self):\r\n if self._closed:\r\n raise Error('The connection to the database has been closed.')\r\n return Cursor(self)","def __cursor(cls):\n print('|-- Richiesta cursore da:'+str(cls.__dbCon))\n return cls.__dbCon.cursor( cursor_factory = psycopg2.extras.DictCursor )","def cursorExecute(self, query):\n return self.cursor.execute(query)","def getCursor(self) -> sqlite3:\n return self.cursor","def cursor():\n return get_dbconn(\"nldn\").cursor()","def cursor(self):\n if self.__connection is None:\n self.connect()\n return self.__connection.cursor()","def get_cursor(self):\n return self.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor)","def query(cursor, query):\n out = []\n c = cursor.execute(query)\n out.append(c.fetchall())\n # will return list of tuples for each query\n return out","def cursor(cls) -> Iterator[sqlite3.Cursor]:\n with closing(cls.db.cursor()) as cur:\n yield cur","def query_to_cur(dbh, query, verbose=verbose):\n if verbose : \n print query\n cur = dbh.cursor()\n cur.execute(query)\n\n return cur","def get_cursor(self):\n try:\n self.cursor = self.connection.cursor()\n logging.getLogger(__name__).info(\"Cursor was created.\")\n except Error as er:\n logging.getLogger(__name__).error(\"Something went wrong with cursor creating. %s\" %er)\n finally:\n return self.cursor","def cursor(self):\n return self._adapter.cursor()","def query(self, query, cs_type=None, *parameters, **kwparameters):\n cursor = self._cursor(cs_type)\n try:\n self._execute(cursor, query, parameters, kwparameters)\n if cs_type in [\"SSCursor\", \"SSDictCursor\"]:\n while 1:\n try:\n row = cursor.fetchone()\n except Exception, e:\n cursor.close()\n raise e\n if row:\n yield row\n else:\n break\n else:\n yield [Row(row) if isinstance(row, dict) else row for row in cursor]\n except Exception, e:\n cursor.close()","def get_cursor(file_name):\n con = lite.connect(file_name)\n con.row_factory = lite.Row\n return con.cursor()","def db_create_cursor(self, database_name):\n\n cursor = self.connections[database_name].cursor()\n return cursor","def __enter__(self) -> 'cursor':\n self.conn = cx_Oracle.connect(self.configuration)\n self.cursor = self.conn.cursor()\n return self.cursor","def run_query(query):\n conn = connection.get_db_connection()\n cursor = conn.cursor()\n cursor.execute(query)\n return cursor","def exec_get_cur(self, request, params={}, extra_params = None):\n con = self.create_connection()\n cur = con.cursor()\n cur_exec(cur, request, params)\n return cur","def q(self, sql, return_curs=False):\n curs = self._db.cursor()\n curs.execute(sql)\n\n if return_curs:\n return curs\n else:\n curs.close()","def cur(self):\n return self.conn.cursor()","def cursor(self):\n if not self._active_cursor:\n self._active_cursor = self.model.find(self.query,\n self.projection or None,\n **self.options)\n return self._active_cursor","def _execute(self, *args):\n cursor = self.db.cursor()\n cursor.execute(*args)\n return cursor","def create_cursor(self):\n c = self._dbapi_connection.cursor()\n c.arraysize = 100\n return c","def dbcursor(self):\n return self.__dbcursor","def execute(cls, sql):\n cursor = cls.get_conn().cursor()\n cursor.execute(sql)\n return cursor","def cursor(file_name):\n con = sql.connect(file_name)\n con.row_factory = sql.Row\n return con.cursor()","def _query_mysql(self):\n mysql = MySqlHook(mysql_conn_id=self.mysql_conn_id)\n conn = mysql.get_conn()\n cursor = conn.cursor()\n cursor.execute(self.sql)\n return cursor","def get_cursor():\n db = getattr(g, '_database', None)\n if db is None:\n db = g._database = connect_db()\n return db.cursor()","def cdr_cursor(self):\n\n if not hasattr(self, \"_cdr_cursor\"):\n opts = dict(tier=self.tier, user=\"CdrGuest\")\n self._cdr_cursor = db.connect(**opts).cursor()\n return self._cdr_cursor","def _get_cursor(self, page, page_size=20, **q_options):\n # Check if cursor already exists.\n curs = self._get_cursor_from_cache(page, page_size=20, **q_options)\n if curs:\n return curs\n # Compute new cursor.\n if self.page > 1:\n # Get cursor.\n for page in xrange(1, 10000 / page_size):\n if page == self.page:\n break\n dummy, curs, more = self.query.fetch_page(page_size,\n start_cursor=curs,\n keys_only=True,\n **q_options)\n self._set_cursor_to_cache(curs, page, page_size, **q_options)\n if not more:\n break\n return curs","def __enter__(self) -> 'DBcursor':\n self.conn = connector.connect(**self.dbconfig)\n self.cursor = self.conn.cursor()\n return self.cursor","def get_database_cursor(conn=None):\n\n if not conn:\n conn = get_database_connection()\n\n return conn.cursor()","def get_cursor(self, commit=True):\n\t\tconnection = pg8000.connect(**self._dsn)\n\t\tcursor = RigorCursor(connection.cursor())\n\t\ttry:\n\t\t\tyield cursor\n\t\texcept pg8000.IntegrityError as error:\n\t\t\texc_info = sys.exc_info()\n\t\t\tself.rollback(cursor)\n\t\t\traise rigor.database.IntegrityError, exc_info[1], exc_info[2]\n\t\texcept pg8000.DatabaseError as error:\n\t\t\texc_info = sys.exc_info()\n\t\t\tself.rollback(cursor)\n\t\t\traise rigor.database.DatabaseError, exc_info[1], exc_info[2]\n\t\texcept:\n\t\t\texc_info = sys.exc_info()\n\t\t\tself.rollback(cursor)\n\t\t\traise exc_info[0], exc_info[1], exc_info[2]\n\t\telse:\n\t\t\tif commit:\n\t\t\t\tself.commit(cursor)\n\t\t\telse:\n\t\t\t\tself.rollback(cursor)","def query(self, query, *args, **kwargs):\n # TODO: do not return an sqlite3 Errors\n\n if not self.begin():\n return None\n\n self.execute(query, *args, **kwargs)\n\n # create clever result\n ret = list()\n for row in self.cursor:\n if len(row) == 1: # (2)\n ret.append(row[0])\n else: # (3)\n ret.append(row)\n if len(ret) == 1: # (1)\n ret = ret[0]\n\n self.end()\n\n return ret","def new_cursor(self, db, collection):\n if self._mongo_client == None:\n raise Exception(\"mongo_client is None\")\n cursor = self._mongo_client[db][collection]\n return cursor","def get_cursor(self):\n return self.cursor","def __iter__(self):\n return self._cursor","def cursor(self):\n\t\treturn self._cursor","def _query_and_fetchall(self, query):\n with self._connect() as conn:\n cur = conn.cursor()\n cur.execute(query)\n results = cur.fetchall()\n\n return results","def managed_cursor(self, cursor_factory=None):\n\n self.conn_url = (f'postgresql://{self.user}:{self.password}@{self.host}:{self.port}/{self.db}')\n self.conn = psycopg2.connect(self.conn_url)\n self.conn.autocommit = True\n self.curr = self.conn.cursor(cursor_factory=cursor_factory)\n try:\n yield self.curr\n finally:\n self.curr.close()\n self.conn.close()","def __get_cursor():\n try:\n return mysql_conn.cursor()\n except OperationalError:\n mysql_conn.ping(reconnect=True)\n return mysql_conn.cursor()","def __get_cursor():\n try:\n return mysql_conn.cursor()\n except OperationalError:\n mysql_conn.ping(reconnect=True)\n return mysql_conn.cursor()","def __enter__(self) -> 'cursor':\n self.conn = pymysql.connect(self.configuration)\n #self.conn = pyodbc.connect(self.configuration)\n self.cursor = self.conn.cursor()\n return self.cursor","def get_query_results(self, conn, sql):\n\n cur = conn.cursor()\n cur.execute(sql)\n yield from cur.fetchall()","def _execute_query(self, query, values):\n with self as plasticDB:\n cursor = plasticDB.connection.cursor()\n cursor.execute(query,values)\n if not cursor.description:\n return []\n rs = RecordSet(initialData=cursor.fetchall(), recordType=next(zip(*cursor.description)))\n return rs","def query(self, sql):\n try:\n res_cursor = self.connection.execute(text(sql))\n except Exception as e: \n raise e(\"SQL execution error!\")\n \n rows = (Row(res_cursor.keys(), record) for record in res_cursor)\n results = RowsCollection(rows)\n return results","def __enter__(self):\n return self.cursor","def query(self, query: str, *args, **kwargs):\n cursor = self._cursor()\n try:\n self._execute(cursor, query, args, kwargs)\n column_names = [d[0] for d in cursor.description]\n return [Row(zip(column_names, row)) for row in cursor]\n finally:\n cursor.close()","def cursor(self):\n return self._cursor","def cursor(self):\n return self._cursor","def cursor(self):\n return self._cursor","async def query(self, stmt, *args):\n\n with (await self.application.db.cursor()) as cur:\n await cur.execute(stmt, args)\n return [self.row_to_obj(row, cur)\n for row in await cur.fetchall()]","def get_postgres_cursor(self, dictcursor=False):\n pgcursor = None\n try:\n if dictcursor:\n pgcursor = self._connection.cursor(cursor_factory=DictCursor)\n else:\n pgcursor = self._connection.cursor()\n except PostgresError, e:\n raise RuntimeError(\"Cannot get postgres cursor! %s\" % str(e))\n return pgcursor","def execute(self, qry):\n def internal():\n print 'qry = ', qry\n self._cur = self.get_cursor()\n print 'self._cur = ', self._cur\n self._cur.execute(qry)\n # self.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor).execute(qry)\n rows = self._cur.fetchall()\n return rows\n\n return self._retry(internal)","def yield_db_cursor(connect_params=DB_PARAMS, cursor_type=DictCursor):\n\n with psycopg2.connect(**connect_params) as con:\n with con.cursor(cursor_factory=cursor_type) as cur:\n yield cur","def _cursor_collection(self, cursor):\n ...","def _cursor_collection(self, cursor):\n ...","def _run_query(self, query):\n cursor = self.conn.cursor()\n cursor.execute(query)\n return cursor.fetchall()","def db_execute_query(db_connection, query, query_args):\n cursor = db_connection.cursor()\n #datalab_logger_connections.info(\"reading database[Query. May Take Time]...\")\n cursor.execute(query, query_args)\n #datalab_logger_connections.info(\"finish to query database\")\n return cursor","def execute(self, query):\n try:\n cursor = self._get_cursor()\n cursor.execute(query)\n return cursor\n except pymssql.Error as e:\n raise PluginError('Error during query execution !\\n'\n 'Query: %s' % query, e.message)","def __execute_query(self, query: str, params: Union[None, tuple] = None) -> sqlite3.Cursor:\n if params is None:\n params = ()\n\n with self.conn:\n return self.conn.execute(query, params)","def query(self, sql):\n self.cursor.execute(sql)\n result = self.cursor.fetchall()\n return result","def cursor_with_rows(condition, database, table):\n connection = sqlite3.connect(database)\n connection.row_factory = sqlite3.Row\n cursor = connection.cursor()\n cursor.execute('SELECT * FROM ' + table + ' WHERE ' + condition)\n return cursor, connection","def connectionCursorPair(self, name=None):\n connection = self.connection(name)\n return (connection, connection.cursor())","def cursor(self):\n\n cursor = Cursor(\n self.url,\n self.user,\n self.password,\n self.context,\n self.header,\n self.ssl_verify_cert,\n self.ssl_client_cert,\n self.proxies,\n )\n\n self.cursors.append(cursor)\n\n return cursor","def execute_query(query):\n c.execute(query)\n return c.fetchall()","def query(query, parameters=(), single=False):\n cur = get_db().execute(query, parameters)\n cur.row_factory = dict_factory\n #cur = cur.cursor()\n if single:\n result = cur.fetchone()\n else:\n result = cur.fetchall()\n cur.close()\n return result","def _exec (self, sql, **kwargs):\n\n kwargs['id'] = self.id\n cursor = self.connection.cursor ()\n cursor.execute (sql.replace ('table_name', self.table_name), kwargs)\n return cursor","def conn_curs():\n dbname = \"abcdefgh\"\n password = \"Acka-1jfue4-snYmkall\"\n host = \"db.elephantsql.com\"\n\n connection = psycopg2.connect(dbname=dbname, user=dbname,\n password=password, host=host)\n cursor = connection.cursor()\n return connection, cursor","def query(self, query):\n cursor = self.database.cursor()\n cursor.execute(query)\n # If it's a query that's expected to return a value (EG: SELECT)\n if query.strip().lower().startswith('select'): return cursor.fetchall()","def execute(cursor, query):\n while True:\n try:\n cursor.execute(query)\n break\n except Exception as e:\n print(\"Database query: {} {}\".format(cursor, query))\n print(\"Database retry reason: {}\".format(e))\n return cursor","def execute_sql(self, result_type=MULTI):\r\n try:\r\n sql, params = self.as_sql()\r\n #import pdb; pdb.set_trace()\r\n if not sql:\r\n raise EmptyResultSet\r\n except EmptyResultSet:\r\n if result_type == MULTI:\r\n return iter([])\r\n else:\r\n return\r\n\r\n cursor = self.connection.cursor() \r\n cursor.execute(sql, params)\r\n\r\n if not result_type:\r\n return cursor\r\n if result_type == SINGLE:\r\n if self.query.ordering_aliases:\r\n return cursor.fetchone()[:-len(self.query.ordering_aliases)]\r\n return cursor.fetchone()\r\n\r\n # The MULTI case.\r\n if self.query.ordering_aliases:\r\n result = order_modified_iter(cursor, len(self.query.ordering_aliases),\r\n self.connection.features.empty_fetchmany_value)\r\n else:\r\n result = iter((lambda: cursor.fetchmany(GET_ITERATOR_CHUNK_SIZE)),\r\n self.connection.features.empty_fetchmany_value)\r\n if not self.connection.features.can_use_chunked_reads:\r\n # If we are using non-chunked reads, we return the same data\r\n # structure as normally, but ensure it is all read into memory\r\n # before going any further.\r\n return list(result)\r\n return result","def cursor_for_object_in_connection(data, _object):\n if _object not in data:\n return None\n\n offset = data.index(_object)\n return offset_to_cursor(offset)","def sql_query(self, query, params=(), plain_query=False, dict_cursor=False,\n cursor_class=None, show_table=False, buffsize=1024):\n if not cursor_class:\n if dict_cursor:\n cursor_class = oursql.DictCursor\n else:\n cursor_class = oursql.Cursor\n klass = cursor_class\n\n with self._sql_lock:\n if not self._sql_conn:\n self._sql_connect()\n with self._sql_conn.cursor(klass, show_table=show_table) as cur:\n cur.execute(query, params, plain_query)\n if buffsize:\n while True:\n group = cur.fetchmany(buffsize)\n if not group:\n return\n for result in group:\n yield result\n for result in cur.fetchall():\n yield result","def __iter__(self):\n for r in self.cursor:\n yield r","def query(self, query, *parameters, **kwparameters):\n cursor = self._cursor()\n try:\n cursor.execute(query, kwparameters or parameters)\n result = cursor.fetchall()\n return result\n finally:\n cursor.close()","def iter(self, query: str, *args, **kwargs):\n self._ensure_connected()\n cursor = SSCursor(self._db)\n try:\n self._execute(cursor, query, args, kwargs)\n column_names = [d[0] for d in cursor.description]\n for row in cursor:\n yield Row(zip(column_names, row))\n finally:\n cursor.close()","def query(self, query):\n\n config = {\n 'user' : self.db_user,\n 'password' : self.db_pwd,\n 'database' : self.db_name,\n 'host' : self.db_host,\n 'unix_socket' : self.db_socket,\n 'port' : self.db_port,\n 'charset' : 'utf8'\n }\n\n try: \n cnx = mysql.connector.connect(**config)\n cursor = cnx.cursor(dictionary=True) # To return rows as dictionaries.\n\n cursor.execute(query[0], query[1])\n \n # Putting the result rows in an array.\n result = []\n for row in cursor:\n result.append(row)\n\n except mysql.connector.Error as err:\n return None\n else:\n cursor.close()\n cnx.close()\n return result","def query_fetchall(self, q, param=None):\r\n try:\r\n c = self.connection.cursor()\r\n if param is None:\r\n c.execute(q)\r\n else:\r\n c.execute(q, param)\r\n self.logger.log(logger.LogLevel.DEBUG, 'database.fetchall: %s | %s' % (q, param)) \r\n return c.fetchall()\r\n except Exception as e:\r\n self.logger.log(logger.LogLevel.ERROR, 'database.fetchall: %s. %s | %s' % (e, q, param))\r\n return False","def find(cls, query_args, as_dict=False, as_cursor=False):\n cursor = cls.collection.find(query_args.query,\n query_args.select,\n sort=query_args.order_by,\n limit=query_args.limit)\n\n if as_cursor:\n return cursor\n else:\n return [record for record in cursor] if as_dict else [\n cls(record) for record in cursor\n ]","def __init__(self, cursor):\n self.__cursor = cursor","def iter(self, query, *parameters, **kwparameters):\n self._ensure_connected()\n cursor = cursors.SSCursor(self._db)\n try:\n self._execute(cursor, query, parameters, kwparameters)\n column_names = [d[0] for d in cursor.description]\n for row in cursor:\n yield Row(zip(column_names, row))\n finally:\n cursor.close()","def carto_query(query):\n params = {'q': query, 'api_key': apikey(serv=\"cdb\")}\n d = api_query(api_url=CDB_URL, params=params)['rows']\n logging.info(\"Returned %d rows\" % len(d))\n return d"],"string":"[\n \"def create_cursor(self):\\r\\n cursor = self.connection.cursor()\\r\\n return cursor\",\n \"def cursor():\\n dbh = handle()\\n return dbh.cursor()\",\n \"def get_cursor(self, *args, **kwargs):\",\n \"def _cursor(self):\\n cursor = self.conn.cursor()\\n\\n return cursor\",\n \"def cursor(self):\\n return self._conn.cursor()\",\n \"def get_cursor():\\n cur = conn.cursor(cursor_factory=DictCursor)\\n return cur\",\n \"def cursor(self):\\n with self.connection() as conn:\\n cursor = conn.cursor(prepared=True)\\n try:\\n yield cursor\\n finally:\\n cursor.close()\",\n \"def cursor(self):\\n with self.conn as c:\\n yield c.cursor()\",\n \"def cursor(self):\\n with self.conn as c:\\n yield c.cursor()\",\n \"def cursor(self):\\n cursor = Cursor(self, self.__aceQLHttpApi)\\n return cursor\",\n \"def oracle_cursor(query):\\n conf_file_dir = os.path.dirname(os.path.realpath(__file__))\\n conf_file = conf_file_dir + os.sep + '.setup.conf'\\n (username, password, host, port, sid) = credential_setup(conf_file)\\n dsn_tns = cx_Oracle.makedsn(host, port, sid)\\n connection = cx_Oracle.connect(username, password, dsn_tns)\\n cursor = connection.cursor()\\n cursor.execute(query)\\n\\n return cursor\",\n \"def get_cursor(self):\\n self.cur = self.dbcon.cursor()\\n return self.cur\",\n \"def cursor(self):\\n return self.conn.cursor()\",\n \"def get_cursor():\\n return _thread_local.connection.cursor()\",\n \"def cursor(self) -> NamedTupleCursor:\\n return self.connection.cursor\",\n \"def _get_cursor(self):\\n conn = self._connect()\\n conn.autocommit = True\\n cursor = conn.cursor()\\n return cursor\",\n \"def get_cursor(self):\\n return self.connection.cursor()\",\n \"def cursor(self):\\r\\n if self._closed:\\r\\n raise Error('The connection to the database has been closed.')\\r\\n return Cursor(self)\",\n \"def __cursor(cls):\\n print('|-- Richiesta cursore da:'+str(cls.__dbCon))\\n return cls.__dbCon.cursor( cursor_factory = psycopg2.extras.DictCursor )\",\n \"def cursorExecute(self, query):\\n return self.cursor.execute(query)\",\n \"def getCursor(self) -> sqlite3:\\n return self.cursor\",\n \"def cursor():\\n return get_dbconn(\\\"nldn\\\").cursor()\",\n \"def cursor(self):\\n if self.__connection is None:\\n self.connect()\\n return self.__connection.cursor()\",\n \"def get_cursor(self):\\n return self.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor)\",\n \"def query(cursor, query):\\n out = []\\n c = cursor.execute(query)\\n out.append(c.fetchall())\\n # will return list of tuples for each query\\n return out\",\n \"def cursor(cls) -> Iterator[sqlite3.Cursor]:\\n with closing(cls.db.cursor()) as cur:\\n yield cur\",\n \"def query_to_cur(dbh, query, verbose=verbose):\\n if verbose : \\n print query\\n cur = dbh.cursor()\\n cur.execute(query)\\n\\n return cur\",\n \"def get_cursor(self):\\n try:\\n self.cursor = self.connection.cursor()\\n logging.getLogger(__name__).info(\\\"Cursor was created.\\\")\\n except Error as er:\\n logging.getLogger(__name__).error(\\\"Something went wrong with cursor creating. %s\\\" %er)\\n finally:\\n return self.cursor\",\n \"def cursor(self):\\n return self._adapter.cursor()\",\n \"def query(self, query, cs_type=None, *parameters, **kwparameters):\\n cursor = self._cursor(cs_type)\\n try:\\n self._execute(cursor, query, parameters, kwparameters)\\n if cs_type in [\\\"SSCursor\\\", \\\"SSDictCursor\\\"]:\\n while 1:\\n try:\\n row = cursor.fetchone()\\n except Exception, e:\\n cursor.close()\\n raise e\\n if row:\\n yield row\\n else:\\n break\\n else:\\n yield [Row(row) if isinstance(row, dict) else row for row in cursor]\\n except Exception, e:\\n cursor.close()\",\n \"def get_cursor(file_name):\\n con = lite.connect(file_name)\\n con.row_factory = lite.Row\\n return con.cursor()\",\n \"def db_create_cursor(self, database_name):\\n\\n cursor = self.connections[database_name].cursor()\\n return cursor\",\n \"def __enter__(self) -> 'cursor':\\n self.conn = cx_Oracle.connect(self.configuration)\\n self.cursor = self.conn.cursor()\\n return self.cursor\",\n \"def run_query(query):\\n conn = connection.get_db_connection()\\n cursor = conn.cursor()\\n cursor.execute(query)\\n return cursor\",\n \"def exec_get_cur(self, request, params={}, extra_params = None):\\n con = self.create_connection()\\n cur = con.cursor()\\n cur_exec(cur, request, params)\\n return cur\",\n \"def q(self, sql, return_curs=False):\\n curs = self._db.cursor()\\n curs.execute(sql)\\n\\n if return_curs:\\n return curs\\n else:\\n curs.close()\",\n \"def cur(self):\\n return self.conn.cursor()\",\n \"def cursor(self):\\n if not self._active_cursor:\\n self._active_cursor = self.model.find(self.query,\\n self.projection or None,\\n **self.options)\\n return self._active_cursor\",\n \"def _execute(self, *args):\\n cursor = self.db.cursor()\\n cursor.execute(*args)\\n return cursor\",\n \"def create_cursor(self):\\n c = self._dbapi_connection.cursor()\\n c.arraysize = 100\\n return c\",\n \"def dbcursor(self):\\n return self.__dbcursor\",\n \"def execute(cls, sql):\\n cursor = cls.get_conn().cursor()\\n cursor.execute(sql)\\n return cursor\",\n \"def cursor(file_name):\\n con = sql.connect(file_name)\\n con.row_factory = sql.Row\\n return con.cursor()\",\n \"def _query_mysql(self):\\n mysql = MySqlHook(mysql_conn_id=self.mysql_conn_id)\\n conn = mysql.get_conn()\\n cursor = conn.cursor()\\n cursor.execute(self.sql)\\n return cursor\",\n \"def get_cursor():\\n db = getattr(g, '_database', None)\\n if db is None:\\n db = g._database = connect_db()\\n return db.cursor()\",\n \"def cdr_cursor(self):\\n\\n if not hasattr(self, \\\"_cdr_cursor\\\"):\\n opts = dict(tier=self.tier, user=\\\"CdrGuest\\\")\\n self._cdr_cursor = db.connect(**opts).cursor()\\n return self._cdr_cursor\",\n \"def _get_cursor(self, page, page_size=20, **q_options):\\n # Check if cursor already exists.\\n curs = self._get_cursor_from_cache(page, page_size=20, **q_options)\\n if curs:\\n return curs\\n # Compute new cursor.\\n if self.page > 1:\\n # Get cursor.\\n for page in xrange(1, 10000 / page_size):\\n if page == self.page:\\n break\\n dummy, curs, more = self.query.fetch_page(page_size,\\n start_cursor=curs,\\n keys_only=True,\\n **q_options)\\n self._set_cursor_to_cache(curs, page, page_size, **q_options)\\n if not more:\\n break\\n return curs\",\n \"def __enter__(self) -> 'DBcursor':\\n self.conn = connector.connect(**self.dbconfig)\\n self.cursor = self.conn.cursor()\\n return self.cursor\",\n \"def get_database_cursor(conn=None):\\n\\n if not conn:\\n conn = get_database_connection()\\n\\n return conn.cursor()\",\n \"def get_cursor(self, commit=True):\\n\\t\\tconnection = pg8000.connect(**self._dsn)\\n\\t\\tcursor = RigorCursor(connection.cursor())\\n\\t\\ttry:\\n\\t\\t\\tyield cursor\\n\\t\\texcept pg8000.IntegrityError as error:\\n\\t\\t\\texc_info = sys.exc_info()\\n\\t\\t\\tself.rollback(cursor)\\n\\t\\t\\traise rigor.database.IntegrityError, exc_info[1], exc_info[2]\\n\\t\\texcept pg8000.DatabaseError as error:\\n\\t\\t\\texc_info = sys.exc_info()\\n\\t\\t\\tself.rollback(cursor)\\n\\t\\t\\traise rigor.database.DatabaseError, exc_info[1], exc_info[2]\\n\\t\\texcept:\\n\\t\\t\\texc_info = sys.exc_info()\\n\\t\\t\\tself.rollback(cursor)\\n\\t\\t\\traise exc_info[0], exc_info[1], exc_info[2]\\n\\t\\telse:\\n\\t\\t\\tif commit:\\n\\t\\t\\t\\tself.commit(cursor)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tself.rollback(cursor)\",\n \"def query(self, query, *args, **kwargs):\\n # TODO: do not return an sqlite3 Errors\\n\\n if not self.begin():\\n return None\\n\\n self.execute(query, *args, **kwargs)\\n\\n # create clever result\\n ret = list()\\n for row in self.cursor:\\n if len(row) == 1: # (2)\\n ret.append(row[0])\\n else: # (3)\\n ret.append(row)\\n if len(ret) == 1: # (1)\\n ret = ret[0]\\n\\n self.end()\\n\\n return ret\",\n \"def new_cursor(self, db, collection):\\n if self._mongo_client == None:\\n raise Exception(\\\"mongo_client is None\\\")\\n cursor = self._mongo_client[db][collection]\\n return cursor\",\n \"def get_cursor(self):\\n return self.cursor\",\n \"def __iter__(self):\\n return self._cursor\",\n \"def cursor(self):\\n\\t\\treturn self._cursor\",\n \"def _query_and_fetchall(self, query):\\n with self._connect() as conn:\\n cur = conn.cursor()\\n cur.execute(query)\\n results = cur.fetchall()\\n\\n return results\",\n \"def managed_cursor(self, cursor_factory=None):\\n\\n self.conn_url = (f'postgresql://{self.user}:{self.password}@{self.host}:{self.port}/{self.db}')\\n self.conn = psycopg2.connect(self.conn_url)\\n self.conn.autocommit = True\\n self.curr = self.conn.cursor(cursor_factory=cursor_factory)\\n try:\\n yield self.curr\\n finally:\\n self.curr.close()\\n self.conn.close()\",\n \"def __get_cursor():\\n try:\\n return mysql_conn.cursor()\\n except OperationalError:\\n mysql_conn.ping(reconnect=True)\\n return mysql_conn.cursor()\",\n \"def __get_cursor():\\n try:\\n return mysql_conn.cursor()\\n except OperationalError:\\n mysql_conn.ping(reconnect=True)\\n return mysql_conn.cursor()\",\n \"def __enter__(self) -> 'cursor':\\n self.conn = pymysql.connect(self.configuration)\\n #self.conn = pyodbc.connect(self.configuration)\\n self.cursor = self.conn.cursor()\\n return self.cursor\",\n \"def get_query_results(self, conn, sql):\\n\\n cur = conn.cursor()\\n cur.execute(sql)\\n yield from cur.fetchall()\",\n \"def _execute_query(self, query, values):\\n with self as plasticDB:\\n cursor = plasticDB.connection.cursor()\\n cursor.execute(query,values)\\n if not cursor.description:\\n return []\\n rs = RecordSet(initialData=cursor.fetchall(), recordType=next(zip(*cursor.description)))\\n return rs\",\n \"def query(self, sql):\\n try:\\n res_cursor = self.connection.execute(text(sql))\\n except Exception as e: \\n raise e(\\\"SQL execution error!\\\")\\n \\n rows = (Row(res_cursor.keys(), record) for record in res_cursor)\\n results = RowsCollection(rows)\\n return results\",\n \"def __enter__(self):\\n return self.cursor\",\n \"def query(self, query: str, *args, **kwargs):\\n cursor = self._cursor()\\n try:\\n self._execute(cursor, query, args, kwargs)\\n column_names = [d[0] for d in cursor.description]\\n return [Row(zip(column_names, row)) for row in cursor]\\n finally:\\n cursor.close()\",\n \"def cursor(self):\\n return self._cursor\",\n \"def cursor(self):\\n return self._cursor\",\n \"def cursor(self):\\n return self._cursor\",\n \"async def query(self, stmt, *args):\\n\\n with (await self.application.db.cursor()) as cur:\\n await cur.execute(stmt, args)\\n return [self.row_to_obj(row, cur)\\n for row in await cur.fetchall()]\",\n \"def get_postgres_cursor(self, dictcursor=False):\\n pgcursor = None\\n try:\\n if dictcursor:\\n pgcursor = self._connection.cursor(cursor_factory=DictCursor)\\n else:\\n pgcursor = self._connection.cursor()\\n except PostgresError, e:\\n raise RuntimeError(\\\"Cannot get postgres cursor! %s\\\" % str(e))\\n return pgcursor\",\n \"def execute(self, qry):\\n def internal():\\n print 'qry = ', qry\\n self._cur = self.get_cursor()\\n print 'self._cur = ', self._cur\\n self._cur.execute(qry)\\n # self.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor).execute(qry)\\n rows = self._cur.fetchall()\\n return rows\\n\\n return self._retry(internal)\",\n \"def yield_db_cursor(connect_params=DB_PARAMS, cursor_type=DictCursor):\\n\\n with psycopg2.connect(**connect_params) as con:\\n with con.cursor(cursor_factory=cursor_type) as cur:\\n yield cur\",\n \"def _cursor_collection(self, cursor):\\n ...\",\n \"def _cursor_collection(self, cursor):\\n ...\",\n \"def _run_query(self, query):\\n cursor = self.conn.cursor()\\n cursor.execute(query)\\n return cursor.fetchall()\",\n \"def db_execute_query(db_connection, query, query_args):\\n cursor = db_connection.cursor()\\n #datalab_logger_connections.info(\\\"reading database[Query. May Take Time]...\\\")\\n cursor.execute(query, query_args)\\n #datalab_logger_connections.info(\\\"finish to query database\\\")\\n return cursor\",\n \"def execute(self, query):\\n try:\\n cursor = self._get_cursor()\\n cursor.execute(query)\\n return cursor\\n except pymssql.Error as e:\\n raise PluginError('Error during query execution !\\\\n'\\n 'Query: %s' % query, e.message)\",\n \"def __execute_query(self, query: str, params: Union[None, tuple] = None) -> sqlite3.Cursor:\\n if params is None:\\n params = ()\\n\\n with self.conn:\\n return self.conn.execute(query, params)\",\n \"def query(self, sql):\\n self.cursor.execute(sql)\\n result = self.cursor.fetchall()\\n return result\",\n \"def cursor_with_rows(condition, database, table):\\n connection = sqlite3.connect(database)\\n connection.row_factory = sqlite3.Row\\n cursor = connection.cursor()\\n cursor.execute('SELECT * FROM ' + table + ' WHERE ' + condition)\\n return cursor, connection\",\n \"def connectionCursorPair(self, name=None):\\n connection = self.connection(name)\\n return (connection, connection.cursor())\",\n \"def cursor(self):\\n\\n cursor = Cursor(\\n self.url,\\n self.user,\\n self.password,\\n self.context,\\n self.header,\\n self.ssl_verify_cert,\\n self.ssl_client_cert,\\n self.proxies,\\n )\\n\\n self.cursors.append(cursor)\\n\\n return cursor\",\n \"def execute_query(query):\\n c.execute(query)\\n return c.fetchall()\",\n \"def query(query, parameters=(), single=False):\\n cur = get_db().execute(query, parameters)\\n cur.row_factory = dict_factory\\n #cur = cur.cursor()\\n if single:\\n result = cur.fetchone()\\n else:\\n result = cur.fetchall()\\n cur.close()\\n return result\",\n \"def _exec (self, sql, **kwargs):\\n\\n kwargs['id'] = self.id\\n cursor = self.connection.cursor ()\\n cursor.execute (sql.replace ('table_name', self.table_name), kwargs)\\n return cursor\",\n \"def conn_curs():\\n dbname = \\\"abcdefgh\\\"\\n password = \\\"Acka-1jfue4-snYmkall\\\"\\n host = \\\"db.elephantsql.com\\\"\\n\\n connection = psycopg2.connect(dbname=dbname, user=dbname,\\n password=password, host=host)\\n cursor = connection.cursor()\\n return connection, cursor\",\n \"def query(self, query):\\n cursor = self.database.cursor()\\n cursor.execute(query)\\n # If it's a query that's expected to return a value (EG: SELECT)\\n if query.strip().lower().startswith('select'): return cursor.fetchall()\",\n \"def execute(cursor, query):\\n while True:\\n try:\\n cursor.execute(query)\\n break\\n except Exception as e:\\n print(\\\"Database query: {} {}\\\".format(cursor, query))\\n print(\\\"Database retry reason: {}\\\".format(e))\\n return cursor\",\n \"def execute_sql(self, result_type=MULTI):\\r\\n try:\\r\\n sql, params = self.as_sql()\\r\\n #import pdb; pdb.set_trace()\\r\\n if not sql:\\r\\n raise EmptyResultSet\\r\\n except EmptyResultSet:\\r\\n if result_type == MULTI:\\r\\n return iter([])\\r\\n else:\\r\\n return\\r\\n\\r\\n cursor = self.connection.cursor() \\r\\n cursor.execute(sql, params)\\r\\n\\r\\n if not result_type:\\r\\n return cursor\\r\\n if result_type == SINGLE:\\r\\n if self.query.ordering_aliases:\\r\\n return cursor.fetchone()[:-len(self.query.ordering_aliases)]\\r\\n return cursor.fetchone()\\r\\n\\r\\n # The MULTI case.\\r\\n if self.query.ordering_aliases:\\r\\n result = order_modified_iter(cursor, len(self.query.ordering_aliases),\\r\\n self.connection.features.empty_fetchmany_value)\\r\\n else:\\r\\n result = iter((lambda: cursor.fetchmany(GET_ITERATOR_CHUNK_SIZE)),\\r\\n self.connection.features.empty_fetchmany_value)\\r\\n if not self.connection.features.can_use_chunked_reads:\\r\\n # If we are using non-chunked reads, we return the same data\\r\\n # structure as normally, but ensure it is all read into memory\\r\\n # before going any further.\\r\\n return list(result)\\r\\n return result\",\n \"def cursor_for_object_in_connection(data, _object):\\n if _object not in data:\\n return None\\n\\n offset = data.index(_object)\\n return offset_to_cursor(offset)\",\n \"def sql_query(self, query, params=(), plain_query=False, dict_cursor=False,\\n cursor_class=None, show_table=False, buffsize=1024):\\n if not cursor_class:\\n if dict_cursor:\\n cursor_class = oursql.DictCursor\\n else:\\n cursor_class = oursql.Cursor\\n klass = cursor_class\\n\\n with self._sql_lock:\\n if not self._sql_conn:\\n self._sql_connect()\\n with self._sql_conn.cursor(klass, show_table=show_table) as cur:\\n cur.execute(query, params, plain_query)\\n if buffsize:\\n while True:\\n group = cur.fetchmany(buffsize)\\n if not group:\\n return\\n for result in group:\\n yield result\\n for result in cur.fetchall():\\n yield result\",\n \"def __iter__(self):\\n for r in self.cursor:\\n yield r\",\n \"def query(self, query, *parameters, **kwparameters):\\n cursor = self._cursor()\\n try:\\n cursor.execute(query, kwparameters or parameters)\\n result = cursor.fetchall()\\n return result\\n finally:\\n cursor.close()\",\n \"def iter(self, query: str, *args, **kwargs):\\n self._ensure_connected()\\n cursor = SSCursor(self._db)\\n try:\\n self._execute(cursor, query, args, kwargs)\\n column_names = [d[0] for d in cursor.description]\\n for row in cursor:\\n yield Row(zip(column_names, row))\\n finally:\\n cursor.close()\",\n \"def query(self, query):\\n\\n config = {\\n 'user' : self.db_user,\\n 'password' : self.db_pwd,\\n 'database' : self.db_name,\\n 'host' : self.db_host,\\n 'unix_socket' : self.db_socket,\\n 'port' : self.db_port,\\n 'charset' : 'utf8'\\n }\\n\\n try: \\n cnx = mysql.connector.connect(**config)\\n cursor = cnx.cursor(dictionary=True) # To return rows as dictionaries.\\n\\n cursor.execute(query[0], query[1])\\n \\n # Putting the result rows in an array.\\n result = []\\n for row in cursor:\\n result.append(row)\\n\\n except mysql.connector.Error as err:\\n return None\\n else:\\n cursor.close()\\n cnx.close()\\n return result\",\n \"def query_fetchall(self, q, param=None):\\r\\n try:\\r\\n c = self.connection.cursor()\\r\\n if param is None:\\r\\n c.execute(q)\\r\\n else:\\r\\n c.execute(q, param)\\r\\n self.logger.log(logger.LogLevel.DEBUG, 'database.fetchall: %s | %s' % (q, param)) \\r\\n return c.fetchall()\\r\\n except Exception as e:\\r\\n self.logger.log(logger.LogLevel.ERROR, 'database.fetchall: %s. %s | %s' % (e, q, param))\\r\\n return False\",\n \"def find(cls, query_args, as_dict=False, as_cursor=False):\\n cursor = cls.collection.find(query_args.query,\\n query_args.select,\\n sort=query_args.order_by,\\n limit=query_args.limit)\\n\\n if as_cursor:\\n return cursor\\n else:\\n return [record for record in cursor] if as_dict else [\\n cls(record) for record in cursor\\n ]\",\n \"def __init__(self, cursor):\\n self.__cursor = cursor\",\n \"def iter(self, query, *parameters, **kwparameters):\\n self._ensure_connected()\\n cursor = cursors.SSCursor(self._db)\\n try:\\n self._execute(cursor, query, parameters, kwparameters)\\n column_names = [d[0] for d in cursor.description]\\n for row in cursor:\\n yield Row(zip(column_names, row))\\n finally:\\n cursor.close()\",\n \"def carto_query(query):\\n params = {'q': query, 'api_key': apikey(serv=\\\"cdb\\\")}\\n d = api_query(api_url=CDB_URL, params=params)['rows']\\n logging.info(\\\"Returned %d rows\\\" % len(d))\\n return d\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.77592504","0.7748701","0.7519825","0.7482258","0.7413113","0.7369768","0.7340349","0.731754","0.731754","0.7271211","0.7255303","0.7223003","0.71825427","0.7179095","0.7167863","0.71537787","0.70854706","0.7069509","0.7030988","0.7016853","0.69801897","0.69698113","0.6963466","0.69497156","0.6919799","0.68728334","0.6859818","0.6835457","0.68172336","0.6814817","0.6758031","0.67429864","0.6728755","0.671461","0.6700041","0.6599479","0.65950537","0.6582121","0.65550065","0.65539616","0.65409815","0.65388274","0.6522774","0.6516377","0.6481925","0.6464561","0.6443913","0.64366186","0.6426763","0.64025146","0.6391852","0.63726777","0.6358491","0.6354361","0.63399434","0.63136506","0.6298297","0.62640154","0.62640154","0.6258407","0.62553537","0.62522423","0.6218141","0.621401","0.61866945","0.6183067","0.6183067","0.6183067","0.61814016","0.6177309","0.61739194","0.61666137","0.6150645","0.6150645","0.61358917","0.6129391","0.61275095","0.610244","0.6099064","0.6093722","0.6078968","0.60740715","0.6058623","0.60577464","0.60515773","0.604786","0.60423744","0.6037161","0.5980085","0.5966306","0.5964467","0.5963072","0.5940637","0.59360904","0.59143627","0.59123737","0.5910079","0.5901547","0.5898163","0.5892568"],"string":"[\n \"0.77592504\",\n \"0.7748701\",\n \"0.7519825\",\n \"0.7482258\",\n \"0.7413113\",\n \"0.7369768\",\n \"0.7340349\",\n \"0.731754\",\n \"0.731754\",\n \"0.7271211\",\n \"0.7255303\",\n \"0.7223003\",\n \"0.71825427\",\n \"0.7179095\",\n \"0.7167863\",\n \"0.71537787\",\n \"0.70854706\",\n \"0.7069509\",\n \"0.7030988\",\n \"0.7016853\",\n \"0.69801897\",\n \"0.69698113\",\n \"0.6963466\",\n \"0.69497156\",\n \"0.6919799\",\n \"0.68728334\",\n \"0.6859818\",\n \"0.6835457\",\n \"0.68172336\",\n \"0.6814817\",\n \"0.6758031\",\n \"0.67429864\",\n \"0.6728755\",\n \"0.671461\",\n \"0.6700041\",\n \"0.6599479\",\n \"0.65950537\",\n \"0.6582121\",\n \"0.65550065\",\n \"0.65539616\",\n \"0.65409815\",\n \"0.65388274\",\n \"0.6522774\",\n \"0.6516377\",\n \"0.6481925\",\n \"0.6464561\",\n \"0.6443913\",\n \"0.64366186\",\n \"0.6426763\",\n \"0.64025146\",\n \"0.6391852\",\n \"0.63726777\",\n \"0.6358491\",\n \"0.6354361\",\n \"0.63399434\",\n \"0.63136506\",\n \"0.6298297\",\n \"0.62640154\",\n \"0.62640154\",\n \"0.6258407\",\n \"0.62553537\",\n \"0.62522423\",\n \"0.6218141\",\n \"0.621401\",\n \"0.61866945\",\n \"0.6183067\",\n \"0.6183067\",\n \"0.6183067\",\n \"0.61814016\",\n \"0.6177309\",\n \"0.61739194\",\n \"0.61666137\",\n \"0.6150645\",\n \"0.6150645\",\n \"0.61358917\",\n \"0.6129391\",\n \"0.61275095\",\n \"0.610244\",\n \"0.6099064\",\n \"0.6093722\",\n \"0.6078968\",\n \"0.60740715\",\n \"0.6058623\",\n \"0.60577464\",\n \"0.60515773\",\n \"0.604786\",\n \"0.60423744\",\n \"0.6037161\",\n \"0.5980085\",\n \"0.5966306\",\n \"0.5964467\",\n \"0.5963072\",\n \"0.5940637\",\n \"0.59360904\",\n \"0.59143627\",\n \"0.59123737\",\n \"0.5910079\",\n \"0.5901547\",\n \"0.5898163\",\n \"0.5892568\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6644475"},"document_rank":{"kind":"string","value":"35"}}},{"rowIdx":13085,"cells":{"query":{"kind":"string","value":"print data returned from a query in nice aligned columns"},"document":{"kind":"string","value":"def printPrettyFromCursor(cur, args):\n rows = []\n #get column headers -- not very ergonomic\n # exit if function does nto return things\n if not cur.description:\n return\n if args.header:\n rows.append([item[0] for item in cur.description])\n\n rows = rows + cur.fetchall()\n zipped = zip(*rows)\n widths = []\n for col in zipped:\n width = max([len(stringify(c)) for c in col])\n widths.append(width)\n fmat = ' '.join(['{:<%d}' % width for width in widths])\n for row in rows:\n row = [stringify(r) for r in row]\n print(fmat.format(*row))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def format_bash(self,query_results):\n data=query_results.data\n \n name=\"ddb\"\n\n print (\"{0}_row_length={1}\".format(name,len(data)))\n print (\"{0}_column_length={1}\".format(name,len(query_results.columns)))\n print (\"\")\n\n column_index=0\n for column in query_results.columns:\n print(\"{0}_columns['{1}']='{2}'\".format(name,column_index,column))\n column_index+=1\n\n\n row_index=0\n for row in data:\n for column_index in range(0,len(query_results.columns)):\n print('{0}_data[{1}][{2}]=\"{3}\"'.format(name,row_index,column_index,row['data'][column_index]))\n row_index+=1\n # TODO return output for this\n return \"\"","def prettyprint(self):\n\n import pandas.io.sql as psql\n df = psql.read_sql(\"SELECT * FROM ATOM\",self.conn)\n print(df)","def python_data_printer(cur):\n # Print a header.\n for fieldDesc in cur.description:\n print (fieldDesc[fdb.DESCRIPTION_NAME].ljust(fieldDesc[fdb.DESCRIPTION_DISPLAY_SIZE]),end=' ')\n print('')\n for fieldDesc in cur.description:\n print (\"-\" * max((len(fieldDesc[fdb.DESCRIPTION_NAME]),fieldDesc[fdb.DESCRIPTION_DISPLAY_SIZE])),end=' ')\n print('')\n # For each row, print the value of each field left-justified within\n # the maximum possible width of that field.\n fieldIndices = range(len(cur.description))\n for row in cur:\n for fieldIndex in fieldIndices:\n fieldValue = row[fieldIndex]\n if not isinstance(fieldValue,types.StringTypes):\n fieldValue = str(fieldValue)\n if isinstance(fieldValue,types.UnicodeType):\n fieldValue = fieldValue.encode('utf8')\n fieldMaxWidth = max((len(cur.description[fieldIndex][fdb.DESCRIPTION_NAME]),cur.description[fieldIndex][fdb.DESCRIPTION_DISPLAY_SIZE]))\n print (fieldValue.ljust(fieldMaxWidth),end=' ')\n print('')","def print_results(results):\n print(\"\\033[4m\\033[1m%-75s%s\\033[0m\" % (\"NAME\", \"ADDRESS\"))\n\n for selections in data:\n print(\"%-75s%s\" % (selections['applicant'], selections['location']))\n \n print(\"\\n\\033[1m--- PAGE \", page_num, \"---\\033[0m\\n\")","def pretty_print(conn, cur): # an out dated function. if use update with fortnite_database object\n\n cur.execute(\"\"\"SELECT * FROM CurrentStats \n ORDER BY alive desc\n \"\"\")\n data = cur.fetchall()\n # returns x in the x[0] // header row in the data.descriptions\n # iterates through all the items in the data description\n print(\"\\n{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}\".format(\n \"user_id\", \"username\", \"current_kills\", \"current_weapon\", \"total_wins\", \"total_matches\", \"win_percent\",\n \"total_kills\", \"kd\", \"alive\"))\n\n for d in data:\n print(\n \"{:<20d}{:20s}{:<20d}{:20s}{:<20d}{:<20d}{:<20.2f}{:<20d}{:<20.2f}{:<20d}\".format(d[0], d[1], d[2], d[3], d[4],\n d[5], d[6], d[7], d[8], d[9]))","def print_table(data):\n for key in sorted(data):\n print \"%s: %s\" % (key.rjust(16), data[key])","def pretty_print(self, query_obj):\n assert type(query_obj) == dict\n result = \"\"\n if type(query_obj) == dict and 'message' in query_obj:\n result += query_obj[\"message\"] + \"\\n\"\n if 'data' in query_obj and 'column_labels' in query_obj:\n \"\"\" Pretty-print data table \"\"\"\n pt = prettytable.PrettyTable()\n columns = query_obj['column_labels']\n pt.field_names = columns\n\n # Adjust value width - for now preserve 2 decimal places.\n for row_idx, row_values in enumerate(query_obj['data']):\n if type(row_values) == tuple:\n row_values = list(row_values)\n for col_idx, col_value in enumerate(row_values):\n if type(col_value) == float:\n # Right-align numeric columns.\n if row_idx == 0:\n pt.align[columns[col_idx]] = 'r'\n row_values[col_idx] = \"% .2f\" % col_value\n pt.add_row(row_values)\n result += str(pt)\n\n elif 'list' in query_obj:\n \"\"\" Pretty-print lists \"\"\"\n result += str(query_obj['list'])\n elif 'column_names' in query_obj:\n \"\"\" Pretty-print cctypes \"\"\"\n colnames = query_obj['column_names']\n zmatrix = query_obj['matrix']\n pt = prettytable.PrettyTable(hrules=prettytable.ALL, vrules=prettytable.ALL,\n header=False)\n pt.add_row([''] + list(colnames))\n for row, colname in zip(zmatrix, list(colnames)):\n pt.add_row([colname] + list(row))\n result += str(pt)\n elif 'column_labels' in query_obj:\n \"\"\" Pretty-print column list.\"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = ['column']\n for column in query_obj['column_labels']:\n pt.add_row([column])\n result += str(pt)\n elif 'row_lists' in query_obj:\n \"\"\" Pretty-print multiple row lists, which are just names and row sizes. \"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = ('Row List Name', 'Row Count')\n\n def get_row_list_sorting_key(x):\n \"\"\" To be used as the key function in a sort. Puts cc_2 ahead of cc_10, e.g. \"\"\"\n name, count = x\n if '_' not in name:\n return name\n s = name.split('_')\n end = s[-1]\n start = '_'.join(s[:-1])\n if utils.is_int(end):\n return (start, int(end))\n return name\n\n for name, count in sorted(query_obj['row_lists'], key=get_row_list_sorting_key):\n pt.add_row((name, count))\n result += str(pt)\n elif 'column_lists' in query_obj:\n \"\"\" Pretty-print multiple column lists. \"\"\"\n print\n clists = query_obj['column_lists']\n for name, clist in clists:\n print(\"%s:\" % name)\n pt = prettytable.PrettyTable()\n pt.field_names = clist\n print(pt)\n elif 'models' in query_obj:\n \"\"\" Pretty-print model info. \"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = ('model_id', 'iterations')\n for (id, iterations) in query_obj['models']:\n pt.add_row((id, iterations))\n result += str(pt)\n\n if len(result) >= 1 and result[-1] == '\\n':\n result = result[:-1]\n return result","def print_table(self):\n print(\"%-12s%-12s%-12s%-12s%-12s\" % (\"index\",\"balance\",\"payment\",\"interest\",\"amortization\"))\n print(\"-------------------------------------------------------------\")\n for i in self.table[\"index\"]:\n print(\"%-12i%-12i%-12i%-12i%-12i\" % (self.table[\"index\"][i],self.table[\"balance\"][i]\\\n ,self.table[\"payment\"][i],self.table[\"interest\"][i],\\\n self.table[\"amortization\"][i]))","def uglyprint(self):\n\n ctmp = self.conn.cursor()\n ctmp.execute(\"SELECT * FROM ATOM\")\n print(ctmp.fetchall())","def print_results(results):\n data = []\n for idx in results.index:\n item = results.loc[idx]\n row = (str(item.gid), \n re.sub(r'\\n', ' ', item.creators),\n re.sub(r'[\\n\\r]+', ' ', item.title), \n gut_utf8.format(item.gid))\n data.append(row)\n _ = [print('|'.join(row)) for row in data]\n print('#', len(data), \"items returned\")\n return data","def print_row():\n print('| | |')","def output_columns(self) -> List[str]:","def printData (data):\n print(str(len(data)) + '\\t' + str(data))","def pretty_print(self, query_obj):\n assert type(query_obj) == dict\n result = \"\"\n if type(query_obj) == dict and 'message' in query_obj:\n result += query_obj[\"message\"] + \"\\n\"\n if 'data' in query_obj and 'columns' in query_obj:\n \"\"\" Pretty-print data table \"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = query_obj['columns']\n for row in query_obj['data']:\n pt.add_row(row)\n result += str(pt)\n elif 'list' in query_obj:\n \"\"\" Pretty-print lists \"\"\"\n result += str(query_obj['list'])\n elif 'column_names' in query_obj:\n \"\"\" Pretty-print cctypes \"\"\"\n colnames = query_obj['column_names']\n zmatrix = query_obj['matrix']\n pt = prettytable.PrettyTable(hrules=prettytable.ALL, vrules=prettytable.ALL,\n header=False)\n pt.add_row([''] + list(colnames))\n for row, colname in zip(zmatrix, list(colnames)):\n pt.add_row([colname] + list(row))\n result += str(pt)\n elif 'columns' in query_obj:\n \"\"\" Pretty-print column list.\"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = ['column']\n for column in query_obj['columns']:\n pt.add_row([column])\n result += str(pt)\n elif 'row_lists' in query_obj:\n \"\"\" Pretty-print multiple row lists, which are just names and row sizes. \"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = ('Row List Name', 'Row Count')\n\n def get_row_list_sorting_key(x):\n \"\"\" To be used as the key function in a sort. Puts cc_2 ahead of cc_10, e.g. \"\"\"\n name, count = x\n if '_' not in name:\n return name\n s = name.split('_')\n end = s[-1]\n start = '_'.join(s[:-1])\n if is_int(end):\n return (start, int(end))\n return name\n\n for name, count in sorted(query_obj['row_lists'], key=get_row_list_sorting_key):\n pt.add_row((name, count))\n result += str(pt)\n elif 'column_lists' in query_obj:\n \"\"\" Pretty-print multiple column lists. \"\"\"\n print\n clists = query_obj['column_lists']\n for name, clist in clists:\n print(\"%s:\" % name)\n pt = prettytable.PrettyTable()\n pt.field_names = clist\n print(pt)\n elif 'models' in query_obj:\n \"\"\" Pretty-print model info. \"\"\"\n pt = prettytable.PrettyTable()\n pt.field_names = ('model_id', 'iterations')\n for (id, iterations) in query_obj['models']:\n pt.add_row((id, iterations))\n result += str(pt)\n\n if len(result) >= 1 and result[-1] == '\\n':\n result = result[:-1]\n return result","def print_dataframe(self, df):\n header = [\n '일련번호',\n '학생 id',\n '이름',\n '생년월일',\n '중간고사',\n '기말고사',\n '평균',\n 'Grade'\n ]\n\n header_str = '{:10s}' * len(header)\n print(header_str.format(*header))\n print(df.to_string(header=False, col_space=10))","def print_column():\n print('+----+----+----+----+')","def format_raw(self,query_results,output_stream):\n #print(query_results.data)\n delimiter=query_results.delimiter\n res=[]\n for row in query_results.data:\n if 'data' in row:\n raw=delimiter.join(row['data'])\n if output_stream=='STDIO':\n print(raw)\n else:\n res.append(raw)\n\n if output_stream=='STRING':\n return res","def print_table(hdrs, flag=False, data=[],fmt='psql'):\n\tres = cur.fetchall()\n\tif flag:\n\t\tres = data\n\tprint(tabulate(res, headers=hdrs, tablefmt=fmt))","def print_table(table):\n rest = table[1:]\n fmt = \"%-28s %-9s %-16s %s\"\n for row in rest:\n print(fmt % tuple(row))","def print_table(table):\n for row in table:\n # Header column left justified\n print(\"{:<19}\".format(row[0]), end='')\n # Remaining columns right justified\n for col in row[1:]:\n print(\"{:>4}\".format(col), end='')\n print(\"\", end='\\n')","def print_row():\n print('| | | | |')","def pretty_display(self):\n\t\tpretty_space = PrettyTable()\n\t\tpretty_space.field_names = range(self.space.shape[1])\n\t\tcount = 0\n\t\tpretty_row = []\n\t\tfor cell in self.space.flat:\n\t\t\tcount = count + 1\n\t\t\tpretty_row.append(cell.state)\n\t\t\tif count >= self.space.shape[1]:\n\t\t\t\tpretty_space.add_row(pretty_row)\n\t\t\t\tcount = 0\n\t\t\t\tpretty_row = []\n\t\tprint(pretty_space)","def __print_work_table(table):\n print \"%-5s %-30s %5s %5s %5s %5s %5s\" % ('Act', 'Pred', 'Block', 'Dummy', 'Succ', 'start', 'end')\n for k, col in sorted(table.items()):\n print \"%-5s %-30s %5s %5s %5s %5s %5s\" % tuple(\n [str(k)] + [list(col[0])] + [str(col[i]) for i in range(1, len(col))])","def print_column_names(self):\n counter = 1\n try:\n for col_names in self.cursor.description:\n # print(self.cursor.description[col_names][0])\n print(\"\"\"Attribut{}: {:<5}, Typ: {:<5}, DisplaySize: {} InternalSize: {:<5}, Precision: {},\n \"Scale: {}, Null_Ok: {}\"\"\"\n .format(counter,\n col_names[0],\n col_names[1],\n col_names[2],\n col_names[3],\n col_names[4],\n col_names[5],\n col_names[6]))\n counter += 1\n except p.Error as exception:\n print(exception.pgerror)\n except Exception as general_exception:\n print(general_exception)","def dump(self):\n outputs = [\"View : %s\\n\" % self.name]\n cols = list(self.columns.values())\n cols.sort()\n for column in cols:\n outputs.append(\" %-30s %-12s\" % (column['name'], column['type']))\n outputs.append(\"%7s\" % self.__class__.calc_precision(column['type'],\n column['length'], column['precision'], column['scale']))\n if not column['nullable']:\n outputs.append(\" NOT NULL\")\n outputs.append(\"\\n\")\n outputs.append(\"\\n\")\n outputs.append(self.sql+\"\\n\")\n outputs.append(\"\\n\")\n return \"\".join(outputs)","def __repr__(self):\n output = ''\n for grp_id, col_list in self.data.items():\n output += grp_id + ':\\n'\n for col in col_list:\n output += ' ' * 4 + col + '\\n'\n return output","def display_row(self, row):\n column_sizes = self.get_column_sizes()\n sys.stdout.write('|')\n for size, column in zip(column_sizes, row):\n sys.stdout.write(' ' + str(column).ljust(size) + ' |')\n print","def print_column():\n print('+----+----+')","def pprint_table(out, table):\n\n\tcol_paddings = []\n\n\tfor i in range(len(table[0])):\n\t\tcol_paddings.append(get_max_width(table, i))\n\n\tfor row in table:\n\t\t# left col\n\t\tout.write(str(row[0]).ljust(col_paddings[0] + 1))\n\t\t\n\t\t# rest of the cols\n\t\tfor i in range(1, len(row)):\n\t\t\tout.write(str(row[i]).rjust(col_paddings[i] + 2))\n\t\t\n\t\tout.write('\\n')","def print_full(x):\r\n pd.set_option('display.max_rows', len(x))\r\n pd.set_option('display.max_columns', 1000)\r\n pd.set_option('display.expand_frame_repr', False)\r\n print(x)\r\n pd.reset_option('display.max_rows')\r\n pd.reset_option('display.max_columns')\r\n pd.reset_option('display.expand_frame_repr')","def print_output(blast_results):\n output = ''\n header = ['query ID', 'query length', 'subject ID', 'percent identity',\n 'query coverage']\n line = '\\t'.join(header) + '\\n'\n output += line\n for query in blast_results:\n length = str(query_length(query))\n coverage = query_coverage(query)\n coverage = '{:.2}'.format(coverage)\n identity = '{:.2f}'.format(float(query['% identity']))\n line = '\\t'.join([query['query acc.ver'], length, \n query['subject acc.ver'], identity,\n coverage])\n line += '\\n'\n output += line\n print(output)","def pretty_print(self):\n for dtr in self.dtrs:\n dtr.pretty_print(indent=2)","def print_dataframe_content(dataframe):\n\n dataframe_len = len(dataframe.columns)\n dataframe_columns_index = list(range(0, dataframe_len))\n dataframe_column_index_len = len(dataframe_columns_index)\n\n if dataframe.empty:\n print('Empty dataframe.')\n else:\n should_continue_process = True\n current_process_batch_size = 0\n\n while should_continue_process:\n slide_object = slice(current_process_batch_size,\n current_process_batch_size+MAX_ROWS_TO_PRINT)\n dataframe_index_columns = dataframe_columns_index[slide_object]\n\n current_process_batch_size = current_process_batch_size+MAX_ROWS_TO_PRINT\n\n dataframe_buffer = dataframe.iloc[:,\n dataframe_index_columns].copy()\n print(tabulate(dataframe_buffer, headers='keys', tablefmt='psql'))\n\n if current_process_batch_size >= dataframe_column_index_len:\n should_continue_process = False","def print_results(results):\n print()\n print(\"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\")\n print(\"%% RESULTS %%\")\n print(\"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\")\n print()\n print(\"Route \\t Cells \\t\")\n print(\"Length\\tChecked\\t Time\")\n print(\"--------------------------------\")\n print(\"{0}\\t{1}\\t{2}\".format(*results))\n print()","def print_pretty_result(self):\n\t\tfor row in range(0, len(self.resulting_matrix)):\n\t\t\tfor col in range(0, len(self.resulting_matrix[self.__ROW_INDEX])):\n\t\t\t\tactual_number = self.resulting_matrix[row][col]\n\t\t\t\tif (actual_number != 0):\n\t\t\t\t\tprint (\"A la ciudad \", row+1, \" en la fabrica \", col+1, \" se envía \", actual_number)","def __str__(self):\n txt = ''\n if self.PrintHeader:\n txt = \" |\" + \"|\".join(sorted(self.rows[0].keys())).expandtabs() + \"|\"\n txt += \"\\n\"\n txt += \"|-\"\n for r in self.rows:\n txt += \"\\n|\"\n txt += \"|\".join([str(uround(r[key] , 2) if isinstance(r[key], (int, long, float, complex , Variable,AffineScalarFunc )) else r[key]) for key in sorted(self.rows[0].keys())]) + \"|\"\n txt += \"\\n|-\"\n if self.PrintSum:\n txt += \"\\n\"\n sumRow = self.GetSumRow()\n txt += \"| |\" + \"|\".join( [str(uround(sumRow[key] , 2) if isinstance(sumRow[key], (int, long, float, complex , Variable ,AffineScalarFunc )) else sumRow[key]) for key in sorted(self.rows[0].keys())[1:]] ) + \"|\"\n\n return txt","def print_result(self, header, result, suffix=\"views\"):\n print(header)\n for i in range(len(result)):\n print(' ', i + 1, '.', result[i][0], '--', result[i][1], suffix)\n print(\"\\n\")","def print_pretty(self, data):\n length = max(map(lambda x: len(x), data.keys()))\n print '+-------------------------------------+'\n print '| Company Name | Year | Month | Value |'\n print '+-------------------------------------+'\n for key, value in data.items():\n print '| %s | %s | %s | %s |' % (key, \\\n value['year'], value['month'], value['value'])\n print '+-------------------------------------+'","def __print_row(vol_id, vol_name, used, used_lim, excl, excl_lim):\n print(\"{:s}{:s} | {:s}{:s} | {:s} | {:s}{:s} | {:s} | {:s}{:s}\".format(\n vol_id, \" \"*(__collen[\"id\"]-len(vol_id)),\n vol_name, \" \"*(__collen[\"name\"]-len(vol_name)),\n used, \" \"*(__collen[\"used_lim\"]-len(used_lim)), used_lim,\n excl, \" \"*(__collen[\"excl_lim\"]-len(excl_lim)), excl_lim))","def prettify_output(data, columns):\n return data.filter(columns)","def print_full(df):\n pandas.set_option('display.max_rows', len(df))\n print df\n pandas.reset_option('display.max_rows')","def print_individuals(self):\n pt = PrettyTable()\n pt.field_names = ['ID', 'Name', 'Gender', 'Birthday', 'Age', 'Alive', 'Death', 'Child', 'Spouse']\n for i in self.individuals.values():\n pt.add_row(i.get_values())\n print(pt)","def pprint(self, data):\n self._assert(data)\n data = self._render(data) # make elements ascii\n fmats = self._fmats(data) # get array of padding formats)\n for row in data:\n print(fmats.format(*row))","def __print_header():\n __collen[\"id\"] = max(__collen[\"id\"], 2) # min is \"ID\"\n __collen[\"name\"] = max(__collen[\"name\"], 14) # min is \"Subvolume Name\"\n __collen[\"used_lim\"] = max(__collen[\"used_lim\"], 10) # min is \"Max (Used)\"\n __collen[\"excl_lim\"] = max(__collen[\"excl_lim\"], 11) # min is \"Max (Excl.)\"\n print(\"ID{:s} | Subvolume Name{:s} | {:s}Used | {:s}Max (Used) | {:s}Exclusive | {:s}Max (Excl.)\".format(\n \" \"*(__collen[\"id\"]-2),\n \" \"*(__collen[\"name\"]-14),\n \" \"*(MAX_SIZE-4),\n \" \"*(__collen[\"used_lim\"]-10),\n \" \"*(MAX_SIZE-9),\n \" \"*(__collen[\"excl_lim\"]-11)))","def print_table(table):\n print(\"City \", end='')\n for month in MONTHS:\n print(\"{:>6}\".format(month), end='')\n print(\"\")\n for name, row in table.items():\n # Header column left justified\n print(\"{:<19}\".format(name), end='')\n # Remaining columns right justified\n for month in MONTHS:\n print(\"{:>6}\".format(row[month]), end='')\n print(\"\", end='\\n')","def print_table(table, fieldnames):\n print(\"{:<19}\".format(fieldnames[0]), end='')\n for field in fieldnames[1:]:\n print(\"{:>6}\".format(field), end='')\n print(\"\")\n for name, row in table.items():\n # Header column left justified\n print(\"{:<19}\".format(name), end='')\n # Remaining columns right justified\n for field in fieldnames[1:]:\n print(\"{:>6}\".format(row[field]), end='')\n print(\"\", end='\\n')","def print_table(table, fieldnames):\n print(\"{:<19}\".format(fieldnames[0]), end='')\n for field in fieldnames[1:]:\n print(\"{:>6}\".format(field), end='')\n print(\"\")\n for name, row in table.items():\n # Header column left justified\n print(\"{:<19}\".format(name), end='')\n # Remaining columns right justified\n for field in fieldnames[1:]:\n print(\"{:>6}\".format(row[field]), end='')\n print(\"\", end='\\n')","def sql_display(line, cell=None):\n val = cell if cell is not None else line \n return spark.sql(val).limit(max_show_lines).toPandas()","def __str__(self):\n # make the header\n bigstring = 'Column: '+str(self.colname)\n\n # go over each row\n for index in range(self._nrows):\n # append the string repr. to the output\n bigstring += '\\n'+self.fprint_elem(index)\n\n # return the string\n return bigstring","def print_wrapped(data, ncols=3):\r\n nrows = len(data)\r\n labels = data.index\r\n n_split_rows = int(np.ceil(nrows / ncols))\r\n for r in range(0, nrows, ncols):\r\n for c in range(ncols):\r\n try:\r\n numstr = '{}'.format(data[r + c])\r\n tabs = [' '] * (20 - len(labels[r + c]) - len(numstr))\r\n print(labels[r + c] + \"\".join(tabs) + numstr, end='\\t')\r\n except:\r\n pass\r\n print()","def display_results_line(stats):\n # Line output.\n template = ' %5d |%6.2f |%6.2f %6.2f %6.2f |%3d %3d %3d'\n\n num_bytes = stats['data_size']\n\n P_times = stats['P_times']\n val = [num_bytes]\n for p in P_times:\n val.append(p*1000.)\n\n val.append(stats['count_lost'])\n val.append(stats['count_timeout'])\n val.append(stats['count_corrupt'])\n val = tuple(val)\n\n print(template % val)","def show_data(self, ):\r\n return print('society_name : {}\\n'\r\n 'flat : {}\\n'\r\n 'house_no : {}\\n'\r\n 'no_of_members : {}\\n'\r\n 'income : {}\\n '\r\n .format(self.society_name, self.flat, self.house_no, self.no_of_members, self.income))","def tabular_formatted_printing(data_list):\n n = len(data_list)\n max = 0\n for i in range(0,n):\n if int(len(data_list[i][0])) > max:\n max = len(data_list[i][0])\n for i in range(0,n):\n if int(len(data_list[i][0])) < max:\n space = max - len(data_list[i][0])\n else:\n space = 0\n print(data_list[i][0]+space*' '+' : '+str(data_list[i][1]))\n return","def print_tables(db):\n # connect to the database and create a cursor\n\n # select all columns using SQL command\n # 'SELECT * FROM StatelessCountByCountry'\n\n # print the data from StatelessCountByCountry\n\n # select all columns using SQL command\n # 'SELECT * FROM StatelessCountByRegion'\n\n # print the data from StatelessCountByRegion","def format_aggr_result(self,db_res):\n res_str = []\n res_str.append(TABLE_OPEN)\n res_str.append(THEAD_OPEN)\n res_str.append(ROW_OPEN)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Date')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Total')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Adobe VisIdHighLow')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('McVisIdHigh')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('UUID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(THEAD_ROW_OPEN)\n res_str.append('Auth UUID')\n res_str.append(THEAD_ROW_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(THEAD_CLOSE)\n res_str.append(TBODY_OPEN)\n for row in db_res:\n res_str.append(ROW_OPEN)\n for elem in row:\n res_str.append(COLUMN_OPEN)\n res_str.append(str(elem)) # do this gracefully\n res_str.append(COLUMN_CLOSE)\n res_str.append(ROW_CLOSE)\n res_str.append(TBODY_CLOSE)\n res_str.append(TABLE_CLOSE)\n return \"\".join(res_str)","def print_PQ(q):\n for item in q:\n print(str(item), end=' ')\n print()","def print_tables(self):\n print \"------------------\\nTables\\n------------------\"\n cnt = 0\n for x in self.show_tables():\n cnt += 1\n print (\"{0}.) {1}\".format(cnt, x[0]))","def df_print(p_df):\n l_gr = p_df['Group']\n l_number = p_df['Number']\n l_string = p_df['String']\n\n for i in range(l_gr.count()):\n print(\"=== {} ===\".format(str(l_gr[i])))\n for j in range(len(l_number[i])):\n print('{}. {}'.format(l_number[i][j], l_string[i][j]))","def printdatarow(dat, iteration):\r\n i = np.where(dat.f[:, 0] == iteration)[0][0]\r\n j = np.where(dat.std[:, 0] == iteration)[0][0]\r\n print('%5d' % (int(dat.f[i,0])) + ' %6d' % (int(dat.f[i,1])) + ' %.14e' % (dat.f[i,5]) +\r\n ' %5.1e' % (dat.f[i,3]) +\r\n ' %6.2e' % (max(dat.std[j,5:])) + ' %6.2e' % min(dat.std[j,5:]))","def printdatarow(dat, iteration):\r\n i = np.where(dat.f[:, 0] == iteration)[0][0]\r\n j = np.where(dat.std[:, 0] == iteration)[0][0]\r\n print('%5d' % (int(dat.f[i,0])) + ' %6d' % (int(dat.f[i,1])) + ' %.14e' % (dat.f[i,5]) +\r\n ' %5.1e' % (dat.f[i,3]) +\r\n ' %6.2e' % (max(dat.std[j,5:])) + ' %6.2e' % min(dat.std[j,5:]))","def show(self):\r\n \r\n clear() \r\n print \" \" + \"-\" * self.__width + \" \"\r\n \r\n for row in self.__buffer:\r\n rowData = \"\".join(str(i) for i in row)\r\n print \"|\" + rowData + \"|\"\r\n\r\n print \" \" + \"-\" * self.__width + \" \"\r\n self.clearBuffer()","def print_dataset_schema(outputs, name, columns):\n outputs.stdout.append(TextOutput(name + ' ('))\n for i in range(len(columns)):\n text = ' ' + str(columns[i])\n if i != len(columns) - 1:\n text += ','\n outputs.stdout.append(TextOutput(text))\n outputs.stdout.append(TextOutput(')'))","def print_table(table):\n # transpose the table:\n table = map(list, zip(*table))\n # get the column width:\n col_width = [max(len(str(x)) for x in col) for col in zip(*table)]\n # print it to screen:\n print\n for line in table:\n print \"| \" + \" | \".join(\"{:{}}\".format(x, col_width[i]) for i, x in enumerate(line)) + \" |\"\n print","def displayPokedex(pokedex):\n for col1,col2 in zip(pokedex[::2],pokedex[1::2]):\n\t print(col1+\",\",col2+\",\")","def human(self, query):\n result = self.query(query)\n width = max([len(x) for x in result.keys()])\n fmt = (\" %%-%ds\" % width) + \"\\t%s\\t%s\"\n for key, val in result.iteritems():\n self._log(fmt % (key, val[0], val[1]), deadline=self._deadline)","def print_results(list_object1, list_object2):\n STUDENT_COLUMN = 16\n GENERAL_COLUMN = 14\n\n print()\n print(\"{:>{}}\".format(\"Student ID\",STUDENT_COLUMN),end=\"\")\n\n for i in range(len(list_object1)):\n print(\"{:>{}}\".format(list_object1[i][0],GENERAL_COLUMN),end=\"\")\n \n print(\"{:>{}}\".format(\"Course grade\",GENERAL_COLUMN))\n\n for tuple_element in list_object2:\n\n print(\"{:>{}}\".format(tuple_element[0],STUDENT_COLUMN),end=\"\")\n\n for i, value in enumerate(tuple_element[1]):\n print(\"{:>{}}\".format(value,GENERAL_COLUMN),end=\"\")\n \n print(\"{:>{}}\".format(round(tuple_element[-1],2),GENERAL_COLUMN))","def print_result_r(result, write=True):\n table = ''\n table += '%-6s%6s%6s%6s\\n' % ('#', 'start', 'end', 'score')\n for i in xrange(len(result['end'])):\n table += '%-6s%6s%6s%6s\\n' % (i+1, result['start'][i]+1,\n result['end'][i]+1,\n result['score'][i])\n if write:\n print table\n else:\n return table","def df_print(df):\n with pd.option_context('display.max_rows', None, 'display.max_columns', 3):\n print(df)","def get_formatted_text(self, n_cols):","def prod(): \n query = \"SELECT * FROM ProducedMsg;\"\n tablestr = dbwrapper._query_pretty(query)\n result = string.replace(str(tablestr),'\\n','<br>')\n return result","def dump(self):\n # This is pretty, but we could just return the ddl_string\n outputs = [\"Table : %s\\n\" % self.name]\n # We show the columns in sequence order, using DSU\n # DSU = Decorate, Sort, Undecorate - a.k.a Schwartzian transform\n deco_cols = [ (x['sequence'], x) for x in list(self.columns.values()) ]\n deco_cols.sort()\n cols = [ col for seq, col in deco_cols ]\n for column in cols:\n outputs.append(\" %-30s\" % column['name'])\n if 'length' in column and column['length'] != None:\n if 'precision' in column and column['precision'] != None:\n # This column is a numeric data type\n column_defn = column['type']+self.__class__.calc_precision(column['type'], column['length'], column['precision'], column['scale'])\n else:\n # This column is a text data type\n column_defn = '%s(%d)' % (column['type'], column['length'])\n else:\n # This column is a simple data type such as date or boolean\n column_defn = column['type']\n outputs.append(\" %-15s \" % column_defn)\n if not column['nullable']:\n outputs.append(\" NOT NULL\")\n if 'special' in column:\n # Special case for e.g. 'enum' in MySQL\n outputs.append(' %s' % column['special'])\n outputs.append(\"\\n\")\n # Constraints please\n if len(self.constraints) != 0:\n outputs.append(\" Constraints;\\n\")\n for constraint_name, constraint in list(self.constraints.items()):\n outputs.append(\" %s, \" % constraint_name)\n outputs.append(\"%s \" % (constraint['type']))\n if 'columns' in constraint:\n outputs.append(\": \")\n outputs.append(', '.join(constraint['columns']))\n outputs.append(\"\\n\")\n # Indexes\n if len(self.indexes) > 0:\n outputs.append(\" Indexes:\\n\")\n for index_name, index in list(self.indexes.items()):\n outputs.append(\" %s, \" % index_name)\n outputs.append(\"%s\\n\" % index['type'])\n # Don't check number of columns because there must be at least 1\n outputs.append(\" Columns: \")\n outputs.append(\", \".join(index['columns']))\n outputs.append(\"\\n\")\n # LOG.debug(\"Table Dump output: \" + \"\".join(outputs))\n return \"\".join(outputs)","def _print_results(results, title=''):\n pstr = '[' + title + ']: ' if title else ''\n for k, v in results.items():\n pstr += '\\t{}: {}'.format(k, v)\n print(pstr)","def print_table(response, title):\n print title + ':'\n\n if 'rows' not in response:\n print 'Empty response'\n return\n\n rows = response['rows']\n row_format = '{:<20}' + '{:>20}' * 4\n print row_format.format('Keys', 'Clicks', 'Impressions', 'CTR', 'Position')\n for row in rows:\n keys = ''\n # Keys are returned only if one or more dimensions are requested.\n if 'keys' in row:\n keys = u','.join(row['keys']).encode('utf-8')\n print row_format.format(\n keys, row['clicks'], row['impressions'], row['ctr'], row['position'])","def print_results(self, question, query, desc=\"views\"):\n # get the resuls from the query\n results = self.db_results(query)\n # print out the question\n print(question)\n # go through the rows and format the results\n for row in results:\n print('\\t' + str(row[0]) + ' - ' + str(row[1]) + ' ' + desc)\n print","def __repr__(self):\n\n headers = [\"{}\\n({})\".format(column, dtype)\n for column, dtype in zip(self.columns, self.dtypes)]\n\n preserve = copy.copy(tabulate.MIN_PADDING)\n tabulate.MIN_PADDING = 0\n\n _repr = tabulate.tabulate(tabular_data=self.data,\n headers=headers,\n numalign=\"center\",\n stralign=\"center\",\n tablefmt=\"psql\",\n showindex=\"always\")\n\n tabulate.MIN_PADDING = preserve\n return _repr","def print_columns(outfile):\r\n values = []\r\n for key in Output.R_COLUMNS:\r\n values.append(str(key))\r\n row = '\\t'.join(values)\r\n row = row + '\\n'\r\n outfile.write(row.encode(\"utf8\"))","def display_data(data):\n\n index = 0\n for details in data:\n index += 1\n print(\"{5:1}{0}. {1:10} in {2:15} priority {3:>3}\".format(index, *details))","def formatResult(self, result):\r\n return '\\t'.join(map(str, result))","def print_mistakes_table():\n conn = sq.connect(host='localhost', user='root',\n password='student', database='quiz')\n cursor = conn.cursor()\n\n cursor.execute(\"select * from mistakes\")\n data = cursor.fetchall()\n\n table = PrettyTable()\n table.field_names = ['Question', 'Given Answer','User Given Answer']\n for row in data:\n table.add_row(row)\n conn.close()\n\n return table","def print_table(rows, header=['Operation', 'OPS']):\n if len(rows) == 0:\n return\n col_max = [max([len(str(val[i])) for val in rows]) + 3 for i in range(len(rows[0]))]\n row_format = ''.join([\"{:<\" + str(length) + \"}\" for length in col_max])\n\n if len(header) > 0:\n print(row_format.format(*header))\n print(row_format.format(*['-' * (val - 2) for val in col_max]))\n\n for row in rows:\n print(row_format.format(*row))\n print(row_format.format(*['-' * (val - 3) for val in col_max]))","def print_row(width, items):\n def fmt_item(x):\n if isinstance(x, np.ndarray):\n assert x.ndim == 0\n x = x.item()\n if isinstance(x, float):\n rep = \"%.3f\" % x\n else:\n rep = str(x)\n return rep.ljust(width)\n\n print(\" | \".join(fmt_item(item) for item in items))","def show(self):\n if self.columns is None:\n return\n\n now = time.time()\n if self.columns != [\"default\"]:\n self.ctxt.sort_fields = None\n else:\n self.ctxt.sort_fields = []\n\n df = self._invoke_sqobj(self.sqobj.get,\n hostname=self.hostname, columns=self.columns,\n namespace=self.namespace,\n query_str=self.query_str,\n )\n\n self.ctxt.exec_time = \"{:5.4f}s\".format(time.time() - now)\n\n if not self.format or (self.format == 'text'):\n self.format = 'devconfig'\n return self._gen_output(df)","def print_data_list(self):\n print('\\n{0}'.format(self.webDataFrame))","def sql_pp(cursor, data):\n headers = cursor.description\n names = []\n lengths = []\n dividers = []\n\n if not data:\n return \"Query Error - PersonID does not exist in Database, please try again\"\n\n # Build out our header row, and our column length list\n for header in headers:\n length = len(header[0])\n if not length:\n length = 12\n length = max(length, len(header[0]))\n names.append(header[0])\n lengths.append(length)\n\n # Check to see if any column data is too wide, adjust length if it is\n for counter, length in enumerate(lengths):\n for row in data:\n if row[counter]:\n row_length = len(str(row[counter]))\n lengths[counter] = max(row_length, length)\n # Build out the dividers\n dividers.append(\"-\"*lengths[counter])\n\n # Builds a string output with correct spacing per our length list\n output = \" \".join([\"%%-%ss\" % _ for _ in lengths])\n\n # Header, divider row string building\n result = [output % tuple(names)]\n result.append(output % tuple(dividers))\n\n # Build out the data rows\n for row in data:\n result.append(output % row)\n\n # Return our result string\n return \"\\n\".join(result)","def viewdata(data):\n\n print('_' * 50)\n print('Number of Results: ' + str(data[0]['numResults']))\n print('\\nSearchURL: ' + data[0]['searchURL'])\n print('_' * 50)\n\n i = 1\n for m in data[1]:\n print(str(i) + '. ')\n for n in m:\n print(str(n) + ': ' + str(m[n]))\n i += 1\n print('\\n')","def _print_table(stats):\n max_key_len = max([len(key) for key in stats])\n width_right = 15\n width_left = max(width_right, max_key_len)\n divider = '+-' + '-' * width_left + '-+-' + '-' * width_right + '-+'\n\n def get_format_char(value):\n if isinstance(value, int):\n return 'd'\n elif isinstance(value, float):\n return '.4f'\n else:\n return 's'\n\n print(divider)\n for name, value in stats.items():\n left_format = f':>{width_left}s'\n right_format = f':<{width_right}{get_format_char(value)}'\n line_format = f'| {{{left_format}}} | {{{right_format}}} |'\n line = line_format.format(name, value)\n print(line)\n print(divider)","def print_result(result, label = \"\"):\n\n if isinstance(label, str) and label:\n print(f\"\\n\\n\\t{label}:\")\n\n if not result:\n print(\"\\tNO RESULTS\")\n return\n\n #if result is string\n if isinstance(result, str):\n print(\"\\n\\t\" + result)\n return\n #if result is integer\n elif isinstance(result, int):\n print(\"\\n\\t\" + result)\n return\n\n text = \"\"\n max_length = [] # max length of item for each column\n titles = []\n\n # if its a list of lists\n if isinstance(result, list): \n # if label we received doesnt give as titles for columns\n if not isinstance(label, list):\n for i in range(len(result[0])):\n titles.append(\"\")\n elif len(label) >= len(result[0]):\n for i in range(len(result[0])):\n titles.append(label[i])\n elif len(label) < len(result[0]):\n print_error_message(\"\\n\\n\\tERROR: NUMBER OF TITLES MUST MATCH NUMBER OF COLUMNS\")\n return\n \n if isinstance(result, dict):\n alist = []\n for key in result:\n alist.append([key,result.get(key)])\n print_table(alist, label)\n return\n\n print_table(result, titles)","def _print_summary(results):\n if not len(results) > 0:\n print 'No results to show in summary.'\n return\n\n table = {}\n for res in results:\n for k, v in res.iteritems():\n table.setdefault(k, []).append(v)\n print tabulate(table, headers='keys', tablefmt=\"simple\")","def dataframe_displayer(df):\n\n #On paramètre les options d'affichage du module pandas\n pd.set_option('display.max_rows', None)\n pd.set_option('display.max_columns', None)\n pd.set_option('display.width', None)\n pd.set_option('display.max_colwidth', -1)\n\n print(df)","def print_playing_field(d):\n print()\n print(\"1 2 3 4 5 6 7\")\n for row in d:\n line = \"\"\n for cell in row:\n line += cell + \" \"\n print(line)\n print()","def print_table(table):\n for i in range(len(table)):\n print \"Row \", i, \"\\t\",\n for j in range(len(table[i])):\n print table[i][j],\n print \"\\n\"","def print_rows():\n do_four(print_row)","def print_rows():\n do_four(print_row)","def pretty_print_table(result, heading=False):\n # If the data is not in string, then it is likely a text format\n if type(result) == 'str':\n result = result.split('\\n')\n result = [line.split() for line in result]\n #Remove empty items\n result = [row for row in result if row!=['']]\n\n columns = len(result[0]) #Get the number of columns, this is used for row formatting\n row_format = '' #variable to construct the row formatting\n \n # Calculating the max length for each column\n for i in range(0, columns):\n # picking the length of the longest element\n #Need to convert the elements into string\n MAX_LEN = len(max([str(row[i]) for row in result], key=len))\n # Constructing the string formatting\n row_format += \"{:<\" + str(MAX_LEN) + \"} | \"\n\n pretty_result = ''\n if heading:\n pretty_result = row_format.format(*result[0]) + '\\n'\n pretty_result += len(row_format.format(*result[0])) * \"-\" + '\\n'\n result = result[1:]\n for row in result:\n pretty_result += row_format.format(*row) + '\\n'\n return pretty_result","def show_dataframe(self, df, **kwargs):\n show_index = False\n if 'show_index' in kwargs:\n show_index = kwargs['show_index']\n\n exceed_limit = len(df) > self.max_result\n header_buf = StringIO(\"\")\n if show_index:\n idx_name = str(df.index.name) if df.index.name is not None else \"\"\n header_buf.write(self.normalizeColumn(idx_name) + \"\\t\")\n header_buf.write(self.normalizeColumn(str(df.columns[0])))\n for col in df.columns[1:]:\n header_buf.write(\"\\t\")\n header_buf.write(self.normalizeColumn(str(col)))\n header_buf.write(\"\\n\")\n\n body_buf = StringIO(\"\")\n rows = df.head(self.max_result).values if exceed_limit else df.values\n rowNumber = len(rows)\n index = df.index.values\n for idx, row in zip(index, rows):\n if show_index:\n body_buf.write(\"%html <strong>{}</strong>\".format(idx))\n body_buf.write(\"\\t\")\n body_buf.write(self.normalizeColumn(str(row[0])))\n for cell in row[1:]:\n body_buf.write(\"\\t\")\n body_buf.write(self.normalizeColumn(str(cell)))\n # don't print '\\n' after the last row\n rowNumber -=1\n if rowNumber != 0:\n body_buf.write(\"\\n\")\n body_buf.seek(0)\n header_buf.seek(0)\n print(\"%table \" + header_buf.read() + body_buf.read())\n body_buf.close()\n header_buf.close()\n if exceed_limit:\n print(\"\\n%html <font color=red>Results are limited by {}.</font>\".format(self.max_result))","def _print_header():\n print()\n print(\n \" ┌─────────────────────── Measurements in BPM ─────────────────────┐\"\n )\n print(\n \"ID Date Activity Distance Elevation Start Duration 5s 30s 60s 5m 10m 20m 30m 60m 90m 120m\"\n )\n _print_separator()","def display_columns(self, display_as='table', write=False):\n cols = self.columns\n if display_as == 'table':\n out = _tb(\n [['Column', 'Description', 'Type']] +\\\n [[k, v[1], v[0]] for k, v in cols.items()],\n headers='firstrow', tablefmt='grid'\n )\n elif display_as == 'tab':\n out = '\\n'.join(\n ['\\t'.join(['Column', 'Description', 'Type'])] +\\\n ['\\t'.join([k, v[1], v[0]]) for k, v in cols.items()],\n )\n elif display_as == 'list':\n out = '\\n'.join([i[1] for i in cols.values()])\n else:\n raise Exception(\"'display_as' must be one of {table,tab,list}\")\n if write:\n print(out)\n else:\n return out","def display_columns(self, display_as='table', write=False):\n cols = self.columns\n if display_as == 'table':\n out = _tb(\n [['Column', 'Description', 'Type']] +\\\n [[k, v[1], v[0]] for k, v in cols.items()],\n headers='firstrow', tablefmt='grid'\n )\n elif display_as == 'tab':\n out = '\\n'.join(\n ['\\t'.join(['Column', 'Description', 'Type'])] +\\\n ['\\t'.join([k, v[1], v[0]]) for k, v in cols.items()],\n )\n elif display_as == 'list':\n out = '\\n'.join([i[1] for i in cols.values()])\n else:\n raise Exception(\"'display_as' must be one of {table,tab,list}\")\n if write:\n print(out)\n else:\n return out","def print_report():\n width = 68\n print(\"-\" * width)\n header = (\"Donor Name\", \"Total Given\", \"Num Gifts\", \"Average Gift\")\n print(\"{:20} | {:15} | {:10} | {:12}\".format(*header))\n print(\"-\" * width)\n for index, donor in enumerate(donors_data):\n name = donor[\"name\"]\n total = sum(donor[\"donations\"])\n num_gift = len(donor[\"donations\"])\n average = total/num_gift\n print(\"{:22} ${:12,.2f} {:12d} ${:12,.2f}\".format(name, total, num_gift, average ))\n print(\"-\" * width)","def __str__(self):\n \n result = [\"rows: \" + str(self.rows),\n \"columns: \"+str(self.columns),\n \"data: \"+str(self.data)]\n return \"\\n\".join(result)"],"string":"[\n \"def format_bash(self,query_results):\\n data=query_results.data\\n \\n name=\\\"ddb\\\"\\n\\n print (\\\"{0}_row_length={1}\\\".format(name,len(data)))\\n print (\\\"{0}_column_length={1}\\\".format(name,len(query_results.columns)))\\n print (\\\"\\\")\\n\\n column_index=0\\n for column in query_results.columns:\\n print(\\\"{0}_columns['{1}']='{2}'\\\".format(name,column_index,column))\\n column_index+=1\\n\\n\\n row_index=0\\n for row in data:\\n for column_index in range(0,len(query_results.columns)):\\n print('{0}_data[{1}][{2}]=\\\"{3}\\\"'.format(name,row_index,column_index,row['data'][column_index]))\\n row_index+=1\\n # TODO return output for this\\n return \\\"\\\"\",\n \"def prettyprint(self):\\n\\n import pandas.io.sql as psql\\n df = psql.read_sql(\\\"SELECT * FROM ATOM\\\",self.conn)\\n print(df)\",\n \"def python_data_printer(cur):\\n # Print a header.\\n for fieldDesc in cur.description:\\n print (fieldDesc[fdb.DESCRIPTION_NAME].ljust(fieldDesc[fdb.DESCRIPTION_DISPLAY_SIZE]),end=' ')\\n print('')\\n for fieldDesc in cur.description:\\n print (\\\"-\\\" * max((len(fieldDesc[fdb.DESCRIPTION_NAME]),fieldDesc[fdb.DESCRIPTION_DISPLAY_SIZE])),end=' ')\\n print('')\\n # For each row, print the value of each field left-justified within\\n # the maximum possible width of that field.\\n fieldIndices = range(len(cur.description))\\n for row in cur:\\n for fieldIndex in fieldIndices:\\n fieldValue = row[fieldIndex]\\n if not isinstance(fieldValue,types.StringTypes):\\n fieldValue = str(fieldValue)\\n if isinstance(fieldValue,types.UnicodeType):\\n fieldValue = fieldValue.encode('utf8')\\n fieldMaxWidth = max((len(cur.description[fieldIndex][fdb.DESCRIPTION_NAME]),cur.description[fieldIndex][fdb.DESCRIPTION_DISPLAY_SIZE]))\\n print (fieldValue.ljust(fieldMaxWidth),end=' ')\\n print('')\",\n \"def print_results(results):\\n print(\\\"\\\\033[4m\\\\033[1m%-75s%s\\\\033[0m\\\" % (\\\"NAME\\\", \\\"ADDRESS\\\"))\\n\\n for selections in data:\\n print(\\\"%-75s%s\\\" % (selections['applicant'], selections['location']))\\n \\n print(\\\"\\\\n\\\\033[1m--- PAGE \\\", page_num, \\\"---\\\\033[0m\\\\n\\\")\",\n \"def pretty_print(conn, cur): # an out dated function. if use update with fortnite_database object\\n\\n cur.execute(\\\"\\\"\\\"SELECT * FROM CurrentStats \\n ORDER BY alive desc\\n \\\"\\\"\\\")\\n data = cur.fetchall()\\n # returns x in the x[0] // header row in the data.descriptions\\n # iterates through all the items in the data description\\n print(\\\"\\\\n{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}{:20s}\\\".format(\\n \\\"user_id\\\", \\\"username\\\", \\\"current_kills\\\", \\\"current_weapon\\\", \\\"total_wins\\\", \\\"total_matches\\\", \\\"win_percent\\\",\\n \\\"total_kills\\\", \\\"kd\\\", \\\"alive\\\"))\\n\\n for d in data:\\n print(\\n \\\"{:<20d}{:20s}{:<20d}{:20s}{:<20d}{:<20d}{:<20.2f}{:<20d}{:<20.2f}{:<20d}\\\".format(d[0], d[1], d[2], d[3], d[4],\\n d[5], d[6], d[7], d[8], d[9]))\",\n \"def print_table(data):\\n for key in sorted(data):\\n print \\\"%s: %s\\\" % (key.rjust(16), data[key])\",\n \"def pretty_print(self, query_obj):\\n assert type(query_obj) == dict\\n result = \\\"\\\"\\n if type(query_obj) == dict and 'message' in query_obj:\\n result += query_obj[\\\"message\\\"] + \\\"\\\\n\\\"\\n if 'data' in query_obj and 'column_labels' in query_obj:\\n \\\"\\\"\\\" Pretty-print data table \\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n columns = query_obj['column_labels']\\n pt.field_names = columns\\n\\n # Adjust value width - for now preserve 2 decimal places.\\n for row_idx, row_values in enumerate(query_obj['data']):\\n if type(row_values) == tuple:\\n row_values = list(row_values)\\n for col_idx, col_value in enumerate(row_values):\\n if type(col_value) == float:\\n # Right-align numeric columns.\\n if row_idx == 0:\\n pt.align[columns[col_idx]] = 'r'\\n row_values[col_idx] = \\\"% .2f\\\" % col_value\\n pt.add_row(row_values)\\n result += str(pt)\\n\\n elif 'list' in query_obj:\\n \\\"\\\"\\\" Pretty-print lists \\\"\\\"\\\"\\n result += str(query_obj['list'])\\n elif 'column_names' in query_obj:\\n \\\"\\\"\\\" Pretty-print cctypes \\\"\\\"\\\"\\n colnames = query_obj['column_names']\\n zmatrix = query_obj['matrix']\\n pt = prettytable.PrettyTable(hrules=prettytable.ALL, vrules=prettytable.ALL,\\n header=False)\\n pt.add_row([''] + list(colnames))\\n for row, colname in zip(zmatrix, list(colnames)):\\n pt.add_row([colname] + list(row))\\n result += str(pt)\\n elif 'column_labels' in query_obj:\\n \\\"\\\"\\\" Pretty-print column list.\\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = ['column']\\n for column in query_obj['column_labels']:\\n pt.add_row([column])\\n result += str(pt)\\n elif 'row_lists' in query_obj:\\n \\\"\\\"\\\" Pretty-print multiple row lists, which are just names and row sizes. \\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = ('Row List Name', 'Row Count')\\n\\n def get_row_list_sorting_key(x):\\n \\\"\\\"\\\" To be used as the key function in a sort. Puts cc_2 ahead of cc_10, e.g. \\\"\\\"\\\"\\n name, count = x\\n if '_' not in name:\\n return name\\n s = name.split('_')\\n end = s[-1]\\n start = '_'.join(s[:-1])\\n if utils.is_int(end):\\n return (start, int(end))\\n return name\\n\\n for name, count in sorted(query_obj['row_lists'], key=get_row_list_sorting_key):\\n pt.add_row((name, count))\\n result += str(pt)\\n elif 'column_lists' in query_obj:\\n \\\"\\\"\\\" Pretty-print multiple column lists. \\\"\\\"\\\"\\n print\\n clists = query_obj['column_lists']\\n for name, clist in clists:\\n print(\\\"%s:\\\" % name)\\n pt = prettytable.PrettyTable()\\n pt.field_names = clist\\n print(pt)\\n elif 'models' in query_obj:\\n \\\"\\\"\\\" Pretty-print model info. \\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = ('model_id', 'iterations')\\n for (id, iterations) in query_obj['models']:\\n pt.add_row((id, iterations))\\n result += str(pt)\\n\\n if len(result) >= 1 and result[-1] == '\\\\n':\\n result = result[:-1]\\n return result\",\n \"def print_table(self):\\n print(\\\"%-12s%-12s%-12s%-12s%-12s\\\" % (\\\"index\\\",\\\"balance\\\",\\\"payment\\\",\\\"interest\\\",\\\"amortization\\\"))\\n print(\\\"-------------------------------------------------------------\\\")\\n for i in self.table[\\\"index\\\"]:\\n print(\\\"%-12i%-12i%-12i%-12i%-12i\\\" % (self.table[\\\"index\\\"][i],self.table[\\\"balance\\\"][i]\\\\\\n ,self.table[\\\"payment\\\"][i],self.table[\\\"interest\\\"][i],\\\\\\n self.table[\\\"amortization\\\"][i]))\",\n \"def uglyprint(self):\\n\\n ctmp = self.conn.cursor()\\n ctmp.execute(\\\"SELECT * FROM ATOM\\\")\\n print(ctmp.fetchall())\",\n \"def print_results(results):\\n data = []\\n for idx in results.index:\\n item = results.loc[idx]\\n row = (str(item.gid), \\n re.sub(r'\\\\n', ' ', item.creators),\\n re.sub(r'[\\\\n\\\\r]+', ' ', item.title), \\n gut_utf8.format(item.gid))\\n data.append(row)\\n _ = [print('|'.join(row)) for row in data]\\n print('#', len(data), \\\"items returned\\\")\\n return data\",\n \"def print_row():\\n print('| | |')\",\n \"def output_columns(self) -> List[str]:\",\n \"def printData (data):\\n print(str(len(data)) + '\\\\t' + str(data))\",\n \"def pretty_print(self, query_obj):\\n assert type(query_obj) == dict\\n result = \\\"\\\"\\n if type(query_obj) == dict and 'message' in query_obj:\\n result += query_obj[\\\"message\\\"] + \\\"\\\\n\\\"\\n if 'data' in query_obj and 'columns' in query_obj:\\n \\\"\\\"\\\" Pretty-print data table \\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = query_obj['columns']\\n for row in query_obj['data']:\\n pt.add_row(row)\\n result += str(pt)\\n elif 'list' in query_obj:\\n \\\"\\\"\\\" Pretty-print lists \\\"\\\"\\\"\\n result += str(query_obj['list'])\\n elif 'column_names' in query_obj:\\n \\\"\\\"\\\" Pretty-print cctypes \\\"\\\"\\\"\\n colnames = query_obj['column_names']\\n zmatrix = query_obj['matrix']\\n pt = prettytable.PrettyTable(hrules=prettytable.ALL, vrules=prettytable.ALL,\\n header=False)\\n pt.add_row([''] + list(colnames))\\n for row, colname in zip(zmatrix, list(colnames)):\\n pt.add_row([colname] + list(row))\\n result += str(pt)\\n elif 'columns' in query_obj:\\n \\\"\\\"\\\" Pretty-print column list.\\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = ['column']\\n for column in query_obj['columns']:\\n pt.add_row([column])\\n result += str(pt)\\n elif 'row_lists' in query_obj:\\n \\\"\\\"\\\" Pretty-print multiple row lists, which are just names and row sizes. \\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = ('Row List Name', 'Row Count')\\n\\n def get_row_list_sorting_key(x):\\n \\\"\\\"\\\" To be used as the key function in a sort. Puts cc_2 ahead of cc_10, e.g. \\\"\\\"\\\"\\n name, count = x\\n if '_' not in name:\\n return name\\n s = name.split('_')\\n end = s[-1]\\n start = '_'.join(s[:-1])\\n if is_int(end):\\n return (start, int(end))\\n return name\\n\\n for name, count in sorted(query_obj['row_lists'], key=get_row_list_sorting_key):\\n pt.add_row((name, count))\\n result += str(pt)\\n elif 'column_lists' in query_obj:\\n \\\"\\\"\\\" Pretty-print multiple column lists. \\\"\\\"\\\"\\n print\\n clists = query_obj['column_lists']\\n for name, clist in clists:\\n print(\\\"%s:\\\" % name)\\n pt = prettytable.PrettyTable()\\n pt.field_names = clist\\n print(pt)\\n elif 'models' in query_obj:\\n \\\"\\\"\\\" Pretty-print model info. \\\"\\\"\\\"\\n pt = prettytable.PrettyTable()\\n pt.field_names = ('model_id', 'iterations')\\n for (id, iterations) in query_obj['models']:\\n pt.add_row((id, iterations))\\n result += str(pt)\\n\\n if len(result) >= 1 and result[-1] == '\\\\n':\\n result = result[:-1]\\n return result\",\n \"def print_dataframe(self, df):\\n header = [\\n '일련번호',\\n '학생 id',\\n '이름',\\n '생년월일',\\n '중간고사',\\n '기말고사',\\n '평균',\\n 'Grade'\\n ]\\n\\n header_str = '{:10s}' * len(header)\\n print(header_str.format(*header))\\n print(df.to_string(header=False, col_space=10))\",\n \"def print_column():\\n print('+----+----+----+----+')\",\n \"def format_raw(self,query_results,output_stream):\\n #print(query_results.data)\\n delimiter=query_results.delimiter\\n res=[]\\n for row in query_results.data:\\n if 'data' in row:\\n raw=delimiter.join(row['data'])\\n if output_stream=='STDIO':\\n print(raw)\\n else:\\n res.append(raw)\\n\\n if output_stream=='STRING':\\n return res\",\n \"def print_table(hdrs, flag=False, data=[],fmt='psql'):\\n\\tres = cur.fetchall()\\n\\tif flag:\\n\\t\\tres = data\\n\\tprint(tabulate(res, headers=hdrs, tablefmt=fmt))\",\n \"def print_table(table):\\n rest = table[1:]\\n fmt = \\\"%-28s %-9s %-16s %s\\\"\\n for row in rest:\\n print(fmt % tuple(row))\",\n \"def print_table(table):\\n for row in table:\\n # Header column left justified\\n print(\\\"{:<19}\\\".format(row[0]), end='')\\n # Remaining columns right justified\\n for col in row[1:]:\\n print(\\\"{:>4}\\\".format(col), end='')\\n print(\\\"\\\", end='\\\\n')\",\n \"def print_row():\\n print('| | | | |')\",\n \"def pretty_display(self):\\n\\t\\tpretty_space = PrettyTable()\\n\\t\\tpretty_space.field_names = range(self.space.shape[1])\\n\\t\\tcount = 0\\n\\t\\tpretty_row = []\\n\\t\\tfor cell in self.space.flat:\\n\\t\\t\\tcount = count + 1\\n\\t\\t\\tpretty_row.append(cell.state)\\n\\t\\t\\tif count >= self.space.shape[1]:\\n\\t\\t\\t\\tpretty_space.add_row(pretty_row)\\n\\t\\t\\t\\tcount = 0\\n\\t\\t\\t\\tpretty_row = []\\n\\t\\tprint(pretty_space)\",\n \"def __print_work_table(table):\\n print \\\"%-5s %-30s %5s %5s %5s %5s %5s\\\" % ('Act', 'Pred', 'Block', 'Dummy', 'Succ', 'start', 'end')\\n for k, col in sorted(table.items()):\\n print \\\"%-5s %-30s %5s %5s %5s %5s %5s\\\" % tuple(\\n [str(k)] + [list(col[0])] + [str(col[i]) for i in range(1, len(col))])\",\n \"def print_column_names(self):\\n counter = 1\\n try:\\n for col_names in self.cursor.description:\\n # print(self.cursor.description[col_names][0])\\n print(\\\"\\\"\\\"Attribut{}: {:<5}, Typ: {:<5}, DisplaySize: {} InternalSize: {:<5}, Precision: {},\\n \\\"Scale: {}, Null_Ok: {}\\\"\\\"\\\"\\n .format(counter,\\n col_names[0],\\n col_names[1],\\n col_names[2],\\n col_names[3],\\n col_names[4],\\n col_names[5],\\n col_names[6]))\\n counter += 1\\n except p.Error as exception:\\n print(exception.pgerror)\\n except Exception as general_exception:\\n print(general_exception)\",\n \"def dump(self):\\n outputs = [\\\"View : %s\\\\n\\\" % self.name]\\n cols = list(self.columns.values())\\n cols.sort()\\n for column in cols:\\n outputs.append(\\\" %-30s %-12s\\\" % (column['name'], column['type']))\\n outputs.append(\\\"%7s\\\" % self.__class__.calc_precision(column['type'],\\n column['length'], column['precision'], column['scale']))\\n if not column['nullable']:\\n outputs.append(\\\" NOT NULL\\\")\\n outputs.append(\\\"\\\\n\\\")\\n outputs.append(\\\"\\\\n\\\")\\n outputs.append(self.sql+\\\"\\\\n\\\")\\n outputs.append(\\\"\\\\n\\\")\\n return \\\"\\\".join(outputs)\",\n \"def __repr__(self):\\n output = ''\\n for grp_id, col_list in self.data.items():\\n output += grp_id + ':\\\\n'\\n for col in col_list:\\n output += ' ' * 4 + col + '\\\\n'\\n return output\",\n \"def display_row(self, row):\\n column_sizes = self.get_column_sizes()\\n sys.stdout.write('|')\\n for size, column in zip(column_sizes, row):\\n sys.stdout.write(' ' + str(column).ljust(size) + ' |')\\n print\",\n \"def print_column():\\n print('+----+----+')\",\n \"def pprint_table(out, table):\\n\\n\\tcol_paddings = []\\n\\n\\tfor i in range(len(table[0])):\\n\\t\\tcol_paddings.append(get_max_width(table, i))\\n\\n\\tfor row in table:\\n\\t\\t# left col\\n\\t\\tout.write(str(row[0]).ljust(col_paddings[0] + 1))\\n\\t\\t\\n\\t\\t# rest of the cols\\n\\t\\tfor i in range(1, len(row)):\\n\\t\\t\\tout.write(str(row[i]).rjust(col_paddings[i] + 2))\\n\\t\\t\\n\\t\\tout.write('\\\\n')\",\n \"def print_full(x):\\r\\n pd.set_option('display.max_rows', len(x))\\r\\n pd.set_option('display.max_columns', 1000)\\r\\n pd.set_option('display.expand_frame_repr', False)\\r\\n print(x)\\r\\n pd.reset_option('display.max_rows')\\r\\n pd.reset_option('display.max_columns')\\r\\n pd.reset_option('display.expand_frame_repr')\",\n \"def print_output(blast_results):\\n output = ''\\n header = ['query ID', 'query length', 'subject ID', 'percent identity',\\n 'query coverage']\\n line = '\\\\t'.join(header) + '\\\\n'\\n output += line\\n for query in blast_results:\\n length = str(query_length(query))\\n coverage = query_coverage(query)\\n coverage = '{:.2}'.format(coverage)\\n identity = '{:.2f}'.format(float(query['% identity']))\\n line = '\\\\t'.join([query['query acc.ver'], length, \\n query['subject acc.ver'], identity,\\n coverage])\\n line += '\\\\n'\\n output += line\\n print(output)\",\n \"def pretty_print(self):\\n for dtr in self.dtrs:\\n dtr.pretty_print(indent=2)\",\n \"def print_dataframe_content(dataframe):\\n\\n dataframe_len = len(dataframe.columns)\\n dataframe_columns_index = list(range(0, dataframe_len))\\n dataframe_column_index_len = len(dataframe_columns_index)\\n\\n if dataframe.empty:\\n print('Empty dataframe.')\\n else:\\n should_continue_process = True\\n current_process_batch_size = 0\\n\\n while should_continue_process:\\n slide_object = slice(current_process_batch_size,\\n current_process_batch_size+MAX_ROWS_TO_PRINT)\\n dataframe_index_columns = dataframe_columns_index[slide_object]\\n\\n current_process_batch_size = current_process_batch_size+MAX_ROWS_TO_PRINT\\n\\n dataframe_buffer = dataframe.iloc[:,\\n dataframe_index_columns].copy()\\n print(tabulate(dataframe_buffer, headers='keys', tablefmt='psql'))\\n\\n if current_process_batch_size >= dataframe_column_index_len:\\n should_continue_process = False\",\n \"def print_results(results):\\n print()\\n print(\\\"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\\\")\\n print(\\\"%% RESULTS %%\\\")\\n print(\\\"%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\\\")\\n print()\\n print(\\\"Route \\\\t Cells \\\\t\\\")\\n print(\\\"Length\\\\tChecked\\\\t Time\\\")\\n print(\\\"--------------------------------\\\")\\n print(\\\"{0}\\\\t{1}\\\\t{2}\\\".format(*results))\\n print()\",\n \"def print_pretty_result(self):\\n\\t\\tfor row in range(0, len(self.resulting_matrix)):\\n\\t\\t\\tfor col in range(0, len(self.resulting_matrix[self.__ROW_INDEX])):\\n\\t\\t\\t\\tactual_number = self.resulting_matrix[row][col]\\n\\t\\t\\t\\tif (actual_number != 0):\\n\\t\\t\\t\\t\\tprint (\\\"A la ciudad \\\", row+1, \\\" en la fabrica \\\", col+1, \\\" se envía \\\", actual_number)\",\n \"def __str__(self):\\n txt = ''\\n if self.PrintHeader:\\n txt = \\\" |\\\" + \\\"|\\\".join(sorted(self.rows[0].keys())).expandtabs() + \\\"|\\\"\\n txt += \\\"\\\\n\\\"\\n txt += \\\"|-\\\"\\n for r in self.rows:\\n txt += \\\"\\\\n|\\\"\\n txt += \\\"|\\\".join([str(uround(r[key] , 2) if isinstance(r[key], (int, long, float, complex , Variable,AffineScalarFunc )) else r[key]) for key in sorted(self.rows[0].keys())]) + \\\"|\\\"\\n txt += \\\"\\\\n|-\\\"\\n if self.PrintSum:\\n txt += \\\"\\\\n\\\"\\n sumRow = self.GetSumRow()\\n txt += \\\"| |\\\" + \\\"|\\\".join( [str(uround(sumRow[key] , 2) if isinstance(sumRow[key], (int, long, float, complex , Variable ,AffineScalarFunc )) else sumRow[key]) for key in sorted(self.rows[0].keys())[1:]] ) + \\\"|\\\"\\n\\n return txt\",\n \"def print_result(self, header, result, suffix=\\\"views\\\"):\\n print(header)\\n for i in range(len(result)):\\n print(' ', i + 1, '.', result[i][0], '--', result[i][1], suffix)\\n print(\\\"\\\\n\\\")\",\n \"def print_pretty(self, data):\\n length = max(map(lambda x: len(x), data.keys()))\\n print '+-------------------------------------+'\\n print '| Company Name | Year | Month | Value |'\\n print '+-------------------------------------+'\\n for key, value in data.items():\\n print '| %s | %s | %s | %s |' % (key, \\\\\\n value['year'], value['month'], value['value'])\\n print '+-------------------------------------+'\",\n \"def __print_row(vol_id, vol_name, used, used_lim, excl, excl_lim):\\n print(\\\"{:s}{:s} | {:s}{:s} | {:s} | {:s}{:s} | {:s} | {:s}{:s}\\\".format(\\n vol_id, \\\" \\\"*(__collen[\\\"id\\\"]-len(vol_id)),\\n vol_name, \\\" \\\"*(__collen[\\\"name\\\"]-len(vol_name)),\\n used, \\\" \\\"*(__collen[\\\"used_lim\\\"]-len(used_lim)), used_lim,\\n excl, \\\" \\\"*(__collen[\\\"excl_lim\\\"]-len(excl_lim)), excl_lim))\",\n \"def prettify_output(data, columns):\\n return data.filter(columns)\",\n \"def print_full(df):\\n pandas.set_option('display.max_rows', len(df))\\n print df\\n pandas.reset_option('display.max_rows')\",\n \"def print_individuals(self):\\n pt = PrettyTable()\\n pt.field_names = ['ID', 'Name', 'Gender', 'Birthday', 'Age', 'Alive', 'Death', 'Child', 'Spouse']\\n for i in self.individuals.values():\\n pt.add_row(i.get_values())\\n print(pt)\",\n \"def pprint(self, data):\\n self._assert(data)\\n data = self._render(data) # make elements ascii\\n fmats = self._fmats(data) # get array of padding formats)\\n for row in data:\\n print(fmats.format(*row))\",\n \"def __print_header():\\n __collen[\\\"id\\\"] = max(__collen[\\\"id\\\"], 2) # min is \\\"ID\\\"\\n __collen[\\\"name\\\"] = max(__collen[\\\"name\\\"], 14) # min is \\\"Subvolume Name\\\"\\n __collen[\\\"used_lim\\\"] = max(__collen[\\\"used_lim\\\"], 10) # min is \\\"Max (Used)\\\"\\n __collen[\\\"excl_lim\\\"] = max(__collen[\\\"excl_lim\\\"], 11) # min is \\\"Max (Excl.)\\\"\\n print(\\\"ID{:s} | Subvolume Name{:s} | {:s}Used | {:s}Max (Used) | {:s}Exclusive | {:s}Max (Excl.)\\\".format(\\n \\\" \\\"*(__collen[\\\"id\\\"]-2),\\n \\\" \\\"*(__collen[\\\"name\\\"]-14),\\n \\\" \\\"*(MAX_SIZE-4),\\n \\\" \\\"*(__collen[\\\"used_lim\\\"]-10),\\n \\\" \\\"*(MAX_SIZE-9),\\n \\\" \\\"*(__collen[\\\"excl_lim\\\"]-11)))\",\n \"def print_table(table):\\n print(\\\"City \\\", end='')\\n for month in MONTHS:\\n print(\\\"{:>6}\\\".format(month), end='')\\n print(\\\"\\\")\\n for name, row in table.items():\\n # Header column left justified\\n print(\\\"{:<19}\\\".format(name), end='')\\n # Remaining columns right justified\\n for month in MONTHS:\\n print(\\\"{:>6}\\\".format(row[month]), end='')\\n print(\\\"\\\", end='\\\\n')\",\n \"def print_table(table, fieldnames):\\n print(\\\"{:<19}\\\".format(fieldnames[0]), end='')\\n for field in fieldnames[1:]:\\n print(\\\"{:>6}\\\".format(field), end='')\\n print(\\\"\\\")\\n for name, row in table.items():\\n # Header column left justified\\n print(\\\"{:<19}\\\".format(name), end='')\\n # Remaining columns right justified\\n for field in fieldnames[1:]:\\n print(\\\"{:>6}\\\".format(row[field]), end='')\\n print(\\\"\\\", end='\\\\n')\",\n \"def print_table(table, fieldnames):\\n print(\\\"{:<19}\\\".format(fieldnames[0]), end='')\\n for field in fieldnames[1:]:\\n print(\\\"{:>6}\\\".format(field), end='')\\n print(\\\"\\\")\\n for name, row in table.items():\\n # Header column left justified\\n print(\\\"{:<19}\\\".format(name), end='')\\n # Remaining columns right justified\\n for field in fieldnames[1:]:\\n print(\\\"{:>6}\\\".format(row[field]), end='')\\n print(\\\"\\\", end='\\\\n')\",\n \"def sql_display(line, cell=None):\\n val = cell if cell is not None else line \\n return spark.sql(val).limit(max_show_lines).toPandas()\",\n \"def __str__(self):\\n # make the header\\n bigstring = 'Column: '+str(self.colname)\\n\\n # go over each row\\n for index in range(self._nrows):\\n # append the string repr. to the output\\n bigstring += '\\\\n'+self.fprint_elem(index)\\n\\n # return the string\\n return bigstring\",\n \"def print_wrapped(data, ncols=3):\\r\\n nrows = len(data)\\r\\n labels = data.index\\r\\n n_split_rows = int(np.ceil(nrows / ncols))\\r\\n for r in range(0, nrows, ncols):\\r\\n for c in range(ncols):\\r\\n try:\\r\\n numstr = '{}'.format(data[r + c])\\r\\n tabs = [' '] * (20 - len(labels[r + c]) - len(numstr))\\r\\n print(labels[r + c] + \\\"\\\".join(tabs) + numstr, end='\\\\t')\\r\\n except:\\r\\n pass\\r\\n print()\",\n \"def display_results_line(stats):\\n # Line output.\\n template = ' %5d |%6.2f |%6.2f %6.2f %6.2f |%3d %3d %3d'\\n\\n num_bytes = stats['data_size']\\n\\n P_times = stats['P_times']\\n val = [num_bytes]\\n for p in P_times:\\n val.append(p*1000.)\\n\\n val.append(stats['count_lost'])\\n val.append(stats['count_timeout'])\\n val.append(stats['count_corrupt'])\\n val = tuple(val)\\n\\n print(template % val)\",\n \"def show_data(self, ):\\r\\n return print('society_name : {}\\\\n'\\r\\n 'flat : {}\\\\n'\\r\\n 'house_no : {}\\\\n'\\r\\n 'no_of_members : {}\\\\n'\\r\\n 'income : {}\\\\n '\\r\\n .format(self.society_name, self.flat, self.house_no, self.no_of_members, self.income))\",\n \"def tabular_formatted_printing(data_list):\\n n = len(data_list)\\n max = 0\\n for i in range(0,n):\\n if int(len(data_list[i][0])) > max:\\n max = len(data_list[i][0])\\n for i in range(0,n):\\n if int(len(data_list[i][0])) < max:\\n space = max - len(data_list[i][0])\\n else:\\n space = 0\\n print(data_list[i][0]+space*' '+' : '+str(data_list[i][1]))\\n return\",\n \"def print_tables(db):\\n # connect to the database and create a cursor\\n\\n # select all columns using SQL command\\n # 'SELECT * FROM StatelessCountByCountry'\\n\\n # print the data from StatelessCountByCountry\\n\\n # select all columns using SQL command\\n # 'SELECT * FROM StatelessCountByRegion'\\n\\n # print the data from StatelessCountByRegion\",\n \"def format_aggr_result(self,db_res):\\n res_str = []\\n res_str.append(TABLE_OPEN)\\n res_str.append(THEAD_OPEN)\\n res_str.append(ROW_OPEN)\\n res_str.append(THEAD_ROW_OPEN)\\n res_str.append('Date')\\n res_str.append(THEAD_ROW_CLOSE)\\n res_str.append(THEAD_ROW_OPEN)\\n res_str.append('Total')\\n res_str.append(THEAD_ROW_CLOSE)\\n res_str.append(THEAD_ROW_OPEN)\\n res_str.append('Adobe VisIdHighLow')\\n res_str.append(THEAD_ROW_CLOSE)\\n res_str.append(THEAD_ROW_OPEN)\\n res_str.append('McVisIdHigh')\\n res_str.append(THEAD_ROW_CLOSE)\\n res_str.append(THEAD_ROW_OPEN)\\n res_str.append('UUID')\\n res_str.append(THEAD_ROW_CLOSE)\\n res_str.append(THEAD_ROW_OPEN)\\n res_str.append('Auth UUID')\\n res_str.append(THEAD_ROW_CLOSE)\\n res_str.append(ROW_CLOSE)\\n res_str.append(THEAD_CLOSE)\\n res_str.append(TBODY_OPEN)\\n for row in db_res:\\n res_str.append(ROW_OPEN)\\n for elem in row:\\n res_str.append(COLUMN_OPEN)\\n res_str.append(str(elem)) # do this gracefully\\n res_str.append(COLUMN_CLOSE)\\n res_str.append(ROW_CLOSE)\\n res_str.append(TBODY_CLOSE)\\n res_str.append(TABLE_CLOSE)\\n return \\\"\\\".join(res_str)\",\n \"def print_PQ(q):\\n for item in q:\\n print(str(item), end=' ')\\n print()\",\n \"def print_tables(self):\\n print \\\"------------------\\\\nTables\\\\n------------------\\\"\\n cnt = 0\\n for x in self.show_tables():\\n cnt += 1\\n print (\\\"{0}.) {1}\\\".format(cnt, x[0]))\",\n \"def df_print(p_df):\\n l_gr = p_df['Group']\\n l_number = p_df['Number']\\n l_string = p_df['String']\\n\\n for i in range(l_gr.count()):\\n print(\\\"=== {} ===\\\".format(str(l_gr[i])))\\n for j in range(len(l_number[i])):\\n print('{}. {}'.format(l_number[i][j], l_string[i][j]))\",\n \"def printdatarow(dat, iteration):\\r\\n i = np.where(dat.f[:, 0] == iteration)[0][0]\\r\\n j = np.where(dat.std[:, 0] == iteration)[0][0]\\r\\n print('%5d' % (int(dat.f[i,0])) + ' %6d' % (int(dat.f[i,1])) + ' %.14e' % (dat.f[i,5]) +\\r\\n ' %5.1e' % (dat.f[i,3]) +\\r\\n ' %6.2e' % (max(dat.std[j,5:])) + ' %6.2e' % min(dat.std[j,5:]))\",\n \"def printdatarow(dat, iteration):\\r\\n i = np.where(dat.f[:, 0] == iteration)[0][0]\\r\\n j = np.where(dat.std[:, 0] == iteration)[0][0]\\r\\n print('%5d' % (int(dat.f[i,0])) + ' %6d' % (int(dat.f[i,1])) + ' %.14e' % (dat.f[i,5]) +\\r\\n ' %5.1e' % (dat.f[i,3]) +\\r\\n ' %6.2e' % (max(dat.std[j,5:])) + ' %6.2e' % min(dat.std[j,5:]))\",\n \"def show(self):\\r\\n \\r\\n clear() \\r\\n print \\\" \\\" + \\\"-\\\" * self.__width + \\\" \\\"\\r\\n \\r\\n for row in self.__buffer:\\r\\n rowData = \\\"\\\".join(str(i) for i in row)\\r\\n print \\\"|\\\" + rowData + \\\"|\\\"\\r\\n\\r\\n print \\\" \\\" + \\\"-\\\" * self.__width + \\\" \\\"\\r\\n self.clearBuffer()\",\n \"def print_dataset_schema(outputs, name, columns):\\n outputs.stdout.append(TextOutput(name + ' ('))\\n for i in range(len(columns)):\\n text = ' ' + str(columns[i])\\n if i != len(columns) - 1:\\n text += ','\\n outputs.stdout.append(TextOutput(text))\\n outputs.stdout.append(TextOutput(')'))\",\n \"def print_table(table):\\n # transpose the table:\\n table = map(list, zip(*table))\\n # get the column width:\\n col_width = [max(len(str(x)) for x in col) for col in zip(*table)]\\n # print it to screen:\\n print\\n for line in table:\\n print \\\"| \\\" + \\\" | \\\".join(\\\"{:{}}\\\".format(x, col_width[i]) for i, x in enumerate(line)) + \\\" |\\\"\\n print\",\n \"def displayPokedex(pokedex):\\n for col1,col2 in zip(pokedex[::2],pokedex[1::2]):\\n\\t print(col1+\\\",\\\",col2+\\\",\\\")\",\n \"def human(self, query):\\n result = self.query(query)\\n width = max([len(x) for x in result.keys()])\\n fmt = (\\\" %%-%ds\\\" % width) + \\\"\\\\t%s\\\\t%s\\\"\\n for key, val in result.iteritems():\\n self._log(fmt % (key, val[0], val[1]), deadline=self._deadline)\",\n \"def print_results(list_object1, list_object2):\\n STUDENT_COLUMN = 16\\n GENERAL_COLUMN = 14\\n\\n print()\\n print(\\\"{:>{}}\\\".format(\\\"Student ID\\\",STUDENT_COLUMN),end=\\\"\\\")\\n\\n for i in range(len(list_object1)):\\n print(\\\"{:>{}}\\\".format(list_object1[i][0],GENERAL_COLUMN),end=\\\"\\\")\\n \\n print(\\\"{:>{}}\\\".format(\\\"Course grade\\\",GENERAL_COLUMN))\\n\\n for tuple_element in list_object2:\\n\\n print(\\\"{:>{}}\\\".format(tuple_element[0],STUDENT_COLUMN),end=\\\"\\\")\\n\\n for i, value in enumerate(tuple_element[1]):\\n print(\\\"{:>{}}\\\".format(value,GENERAL_COLUMN),end=\\\"\\\")\\n \\n print(\\\"{:>{}}\\\".format(round(tuple_element[-1],2),GENERAL_COLUMN))\",\n \"def print_result_r(result, write=True):\\n table = ''\\n table += '%-6s%6s%6s%6s\\\\n' % ('#', 'start', 'end', 'score')\\n for i in xrange(len(result['end'])):\\n table += '%-6s%6s%6s%6s\\\\n' % (i+1, result['start'][i]+1,\\n result['end'][i]+1,\\n result['score'][i])\\n if write:\\n print table\\n else:\\n return table\",\n \"def df_print(df):\\n with pd.option_context('display.max_rows', None, 'display.max_columns', 3):\\n print(df)\",\n \"def get_formatted_text(self, n_cols):\",\n \"def prod(): \\n query = \\\"SELECT * FROM ProducedMsg;\\\"\\n tablestr = dbwrapper._query_pretty(query)\\n result = string.replace(str(tablestr),'\\\\n','<br>')\\n return result\",\n \"def dump(self):\\n # This is pretty, but we could just return the ddl_string\\n outputs = [\\\"Table : %s\\\\n\\\" % self.name]\\n # We show the columns in sequence order, using DSU\\n # DSU = Decorate, Sort, Undecorate - a.k.a Schwartzian transform\\n deco_cols = [ (x['sequence'], x) for x in list(self.columns.values()) ]\\n deco_cols.sort()\\n cols = [ col for seq, col in deco_cols ]\\n for column in cols:\\n outputs.append(\\\" %-30s\\\" % column['name'])\\n if 'length' in column and column['length'] != None:\\n if 'precision' in column and column['precision'] != None:\\n # This column is a numeric data type\\n column_defn = column['type']+self.__class__.calc_precision(column['type'], column['length'], column['precision'], column['scale'])\\n else:\\n # This column is a text data type\\n column_defn = '%s(%d)' % (column['type'], column['length'])\\n else:\\n # This column is a simple data type such as date or boolean\\n column_defn = column['type']\\n outputs.append(\\\" %-15s \\\" % column_defn)\\n if not column['nullable']:\\n outputs.append(\\\" NOT NULL\\\")\\n if 'special' in column:\\n # Special case for e.g. 'enum' in MySQL\\n outputs.append(' %s' % column['special'])\\n outputs.append(\\\"\\\\n\\\")\\n # Constraints please\\n if len(self.constraints) != 0:\\n outputs.append(\\\" Constraints;\\\\n\\\")\\n for constraint_name, constraint in list(self.constraints.items()):\\n outputs.append(\\\" %s, \\\" % constraint_name)\\n outputs.append(\\\"%s \\\" % (constraint['type']))\\n if 'columns' in constraint:\\n outputs.append(\\\": \\\")\\n outputs.append(', '.join(constraint['columns']))\\n outputs.append(\\\"\\\\n\\\")\\n # Indexes\\n if len(self.indexes) > 0:\\n outputs.append(\\\" Indexes:\\\\n\\\")\\n for index_name, index in list(self.indexes.items()):\\n outputs.append(\\\" %s, \\\" % index_name)\\n outputs.append(\\\"%s\\\\n\\\" % index['type'])\\n # Don't check number of columns because there must be at least 1\\n outputs.append(\\\" Columns: \\\")\\n outputs.append(\\\", \\\".join(index['columns']))\\n outputs.append(\\\"\\\\n\\\")\\n # LOG.debug(\\\"Table Dump output: \\\" + \\\"\\\".join(outputs))\\n return \\\"\\\".join(outputs)\",\n \"def _print_results(results, title=''):\\n pstr = '[' + title + ']: ' if title else ''\\n for k, v in results.items():\\n pstr += '\\\\t{}: {}'.format(k, v)\\n print(pstr)\",\n \"def print_table(response, title):\\n print title + ':'\\n\\n if 'rows' not in response:\\n print 'Empty response'\\n return\\n\\n rows = response['rows']\\n row_format = '{:<20}' + '{:>20}' * 4\\n print row_format.format('Keys', 'Clicks', 'Impressions', 'CTR', 'Position')\\n for row in rows:\\n keys = ''\\n # Keys are returned only if one or more dimensions are requested.\\n if 'keys' in row:\\n keys = u','.join(row['keys']).encode('utf-8')\\n print row_format.format(\\n keys, row['clicks'], row['impressions'], row['ctr'], row['position'])\",\n \"def print_results(self, question, query, desc=\\\"views\\\"):\\n # get the resuls from the query\\n results = self.db_results(query)\\n # print out the question\\n print(question)\\n # go through the rows and format the results\\n for row in results:\\n print('\\\\t' + str(row[0]) + ' - ' + str(row[1]) + ' ' + desc)\\n print\",\n \"def __repr__(self):\\n\\n headers = [\\\"{}\\\\n({})\\\".format(column, dtype)\\n for column, dtype in zip(self.columns, self.dtypes)]\\n\\n preserve = copy.copy(tabulate.MIN_PADDING)\\n tabulate.MIN_PADDING = 0\\n\\n _repr = tabulate.tabulate(tabular_data=self.data,\\n headers=headers,\\n numalign=\\\"center\\\",\\n stralign=\\\"center\\\",\\n tablefmt=\\\"psql\\\",\\n showindex=\\\"always\\\")\\n\\n tabulate.MIN_PADDING = preserve\\n return _repr\",\n \"def print_columns(outfile):\\r\\n values = []\\r\\n for key in Output.R_COLUMNS:\\r\\n values.append(str(key))\\r\\n row = '\\\\t'.join(values)\\r\\n row = row + '\\\\n'\\r\\n outfile.write(row.encode(\\\"utf8\\\"))\",\n \"def display_data(data):\\n\\n index = 0\\n for details in data:\\n index += 1\\n print(\\\"{5:1}{0}. {1:10} in {2:15} priority {3:>3}\\\".format(index, *details))\",\n \"def formatResult(self, result):\\r\\n return '\\\\t'.join(map(str, result))\",\n \"def print_mistakes_table():\\n conn = sq.connect(host='localhost', user='root',\\n password='student', database='quiz')\\n cursor = conn.cursor()\\n\\n cursor.execute(\\\"select * from mistakes\\\")\\n data = cursor.fetchall()\\n\\n table = PrettyTable()\\n table.field_names = ['Question', 'Given Answer','User Given Answer']\\n for row in data:\\n table.add_row(row)\\n conn.close()\\n\\n return table\",\n \"def print_table(rows, header=['Operation', 'OPS']):\\n if len(rows) == 0:\\n return\\n col_max = [max([len(str(val[i])) for val in rows]) + 3 for i in range(len(rows[0]))]\\n row_format = ''.join([\\\"{:<\\\" + str(length) + \\\"}\\\" for length in col_max])\\n\\n if len(header) > 0:\\n print(row_format.format(*header))\\n print(row_format.format(*['-' * (val - 2) for val in col_max]))\\n\\n for row in rows:\\n print(row_format.format(*row))\\n print(row_format.format(*['-' * (val - 3) for val in col_max]))\",\n \"def print_row(width, items):\\n def fmt_item(x):\\n if isinstance(x, np.ndarray):\\n assert x.ndim == 0\\n x = x.item()\\n if isinstance(x, float):\\n rep = \\\"%.3f\\\" % x\\n else:\\n rep = str(x)\\n return rep.ljust(width)\\n\\n print(\\\" | \\\".join(fmt_item(item) for item in items))\",\n \"def show(self):\\n if self.columns is None:\\n return\\n\\n now = time.time()\\n if self.columns != [\\\"default\\\"]:\\n self.ctxt.sort_fields = None\\n else:\\n self.ctxt.sort_fields = []\\n\\n df = self._invoke_sqobj(self.sqobj.get,\\n hostname=self.hostname, columns=self.columns,\\n namespace=self.namespace,\\n query_str=self.query_str,\\n )\\n\\n self.ctxt.exec_time = \\\"{:5.4f}s\\\".format(time.time() - now)\\n\\n if not self.format or (self.format == 'text'):\\n self.format = 'devconfig'\\n return self._gen_output(df)\",\n \"def print_data_list(self):\\n print('\\\\n{0}'.format(self.webDataFrame))\",\n \"def sql_pp(cursor, data):\\n headers = cursor.description\\n names = []\\n lengths = []\\n dividers = []\\n\\n if not data:\\n return \\\"Query Error - PersonID does not exist in Database, please try again\\\"\\n\\n # Build out our header row, and our column length list\\n for header in headers:\\n length = len(header[0])\\n if not length:\\n length = 12\\n length = max(length, len(header[0]))\\n names.append(header[0])\\n lengths.append(length)\\n\\n # Check to see if any column data is too wide, adjust length if it is\\n for counter, length in enumerate(lengths):\\n for row in data:\\n if row[counter]:\\n row_length = len(str(row[counter]))\\n lengths[counter] = max(row_length, length)\\n # Build out the dividers\\n dividers.append(\\\"-\\\"*lengths[counter])\\n\\n # Builds a string output with correct spacing per our length list\\n output = \\\" \\\".join([\\\"%%-%ss\\\" % _ for _ in lengths])\\n\\n # Header, divider row string building\\n result = [output % tuple(names)]\\n result.append(output % tuple(dividers))\\n\\n # Build out the data rows\\n for row in data:\\n result.append(output % row)\\n\\n # Return our result string\\n return \\\"\\\\n\\\".join(result)\",\n \"def viewdata(data):\\n\\n print('_' * 50)\\n print('Number of Results: ' + str(data[0]['numResults']))\\n print('\\\\nSearchURL: ' + data[0]['searchURL'])\\n print('_' * 50)\\n\\n i = 1\\n for m in data[1]:\\n print(str(i) + '. ')\\n for n in m:\\n print(str(n) + ': ' + str(m[n]))\\n i += 1\\n print('\\\\n')\",\n \"def _print_table(stats):\\n max_key_len = max([len(key) for key in stats])\\n width_right = 15\\n width_left = max(width_right, max_key_len)\\n divider = '+-' + '-' * width_left + '-+-' + '-' * width_right + '-+'\\n\\n def get_format_char(value):\\n if isinstance(value, int):\\n return 'd'\\n elif isinstance(value, float):\\n return '.4f'\\n else:\\n return 's'\\n\\n print(divider)\\n for name, value in stats.items():\\n left_format = f':>{width_left}s'\\n right_format = f':<{width_right}{get_format_char(value)}'\\n line_format = f'| {{{left_format}}} | {{{right_format}}} |'\\n line = line_format.format(name, value)\\n print(line)\\n print(divider)\",\n \"def print_result(result, label = \\\"\\\"):\\n\\n if isinstance(label, str) and label:\\n print(f\\\"\\\\n\\\\n\\\\t{label}:\\\")\\n\\n if not result:\\n print(\\\"\\\\tNO RESULTS\\\")\\n return\\n\\n #if result is string\\n if isinstance(result, str):\\n print(\\\"\\\\n\\\\t\\\" + result)\\n return\\n #if result is integer\\n elif isinstance(result, int):\\n print(\\\"\\\\n\\\\t\\\" + result)\\n return\\n\\n text = \\\"\\\"\\n max_length = [] # max length of item for each column\\n titles = []\\n\\n # if its a list of lists\\n if isinstance(result, list): \\n # if label we received doesnt give as titles for columns\\n if not isinstance(label, list):\\n for i in range(len(result[0])):\\n titles.append(\\\"\\\")\\n elif len(label) >= len(result[0]):\\n for i in range(len(result[0])):\\n titles.append(label[i])\\n elif len(label) < len(result[0]):\\n print_error_message(\\\"\\\\n\\\\n\\\\tERROR: NUMBER OF TITLES MUST MATCH NUMBER OF COLUMNS\\\")\\n return\\n \\n if isinstance(result, dict):\\n alist = []\\n for key in result:\\n alist.append([key,result.get(key)])\\n print_table(alist, label)\\n return\\n\\n print_table(result, titles)\",\n \"def _print_summary(results):\\n if not len(results) > 0:\\n print 'No results to show in summary.'\\n return\\n\\n table = {}\\n for res in results:\\n for k, v in res.iteritems():\\n table.setdefault(k, []).append(v)\\n print tabulate(table, headers='keys', tablefmt=\\\"simple\\\")\",\n \"def dataframe_displayer(df):\\n\\n #On paramètre les options d'affichage du module pandas\\n pd.set_option('display.max_rows', None)\\n pd.set_option('display.max_columns', None)\\n pd.set_option('display.width', None)\\n pd.set_option('display.max_colwidth', -1)\\n\\n print(df)\",\n \"def print_playing_field(d):\\n print()\\n print(\\\"1 2 3 4 5 6 7\\\")\\n for row in d:\\n line = \\\"\\\"\\n for cell in row:\\n line += cell + \\\" \\\"\\n print(line)\\n print()\",\n \"def print_table(table):\\n for i in range(len(table)):\\n print \\\"Row \\\", i, \\\"\\\\t\\\",\\n for j in range(len(table[i])):\\n print table[i][j],\\n print \\\"\\\\n\\\"\",\n \"def print_rows():\\n do_four(print_row)\",\n \"def print_rows():\\n do_four(print_row)\",\n \"def pretty_print_table(result, heading=False):\\n # If the data is not in string, then it is likely a text format\\n if type(result) == 'str':\\n result = result.split('\\\\n')\\n result = [line.split() for line in result]\\n #Remove empty items\\n result = [row for row in result if row!=['']]\\n\\n columns = len(result[0]) #Get the number of columns, this is used for row formatting\\n row_format = '' #variable to construct the row formatting\\n \\n # Calculating the max length for each column\\n for i in range(0, columns):\\n # picking the length of the longest element\\n #Need to convert the elements into string\\n MAX_LEN = len(max([str(row[i]) for row in result], key=len))\\n # Constructing the string formatting\\n row_format += \\\"{:<\\\" + str(MAX_LEN) + \\\"} | \\\"\\n\\n pretty_result = ''\\n if heading:\\n pretty_result = row_format.format(*result[0]) + '\\\\n'\\n pretty_result += len(row_format.format(*result[0])) * \\\"-\\\" + '\\\\n'\\n result = result[1:]\\n for row in result:\\n pretty_result += row_format.format(*row) + '\\\\n'\\n return pretty_result\",\n \"def show_dataframe(self, df, **kwargs):\\n show_index = False\\n if 'show_index' in kwargs:\\n show_index = kwargs['show_index']\\n\\n exceed_limit = len(df) > self.max_result\\n header_buf = StringIO(\\\"\\\")\\n if show_index:\\n idx_name = str(df.index.name) if df.index.name is not None else \\\"\\\"\\n header_buf.write(self.normalizeColumn(idx_name) + \\\"\\\\t\\\")\\n header_buf.write(self.normalizeColumn(str(df.columns[0])))\\n for col in df.columns[1:]:\\n header_buf.write(\\\"\\\\t\\\")\\n header_buf.write(self.normalizeColumn(str(col)))\\n header_buf.write(\\\"\\\\n\\\")\\n\\n body_buf = StringIO(\\\"\\\")\\n rows = df.head(self.max_result).values if exceed_limit else df.values\\n rowNumber = len(rows)\\n index = df.index.values\\n for idx, row in zip(index, rows):\\n if show_index:\\n body_buf.write(\\\"%html <strong>{}</strong>\\\".format(idx))\\n body_buf.write(\\\"\\\\t\\\")\\n body_buf.write(self.normalizeColumn(str(row[0])))\\n for cell in row[1:]:\\n body_buf.write(\\\"\\\\t\\\")\\n body_buf.write(self.normalizeColumn(str(cell)))\\n # don't print '\\\\n' after the last row\\n rowNumber -=1\\n if rowNumber != 0:\\n body_buf.write(\\\"\\\\n\\\")\\n body_buf.seek(0)\\n header_buf.seek(0)\\n print(\\\"%table \\\" + header_buf.read() + body_buf.read())\\n body_buf.close()\\n header_buf.close()\\n if exceed_limit:\\n print(\\\"\\\\n%html <font color=red>Results are limited by {}.</font>\\\".format(self.max_result))\",\n \"def _print_header():\\n print()\\n print(\\n \\\" ┌─────────────────────── Measurements in BPM ─────────────────────┐\\\"\\n )\\n print(\\n \\\"ID Date Activity Distance Elevation Start Duration 5s 30s 60s 5m 10m 20m 30m 60m 90m 120m\\\"\\n )\\n _print_separator()\",\n \"def display_columns(self, display_as='table', write=False):\\n cols = self.columns\\n if display_as == 'table':\\n out = _tb(\\n [['Column', 'Description', 'Type']] +\\\\\\n [[k, v[1], v[0]] for k, v in cols.items()],\\n headers='firstrow', tablefmt='grid'\\n )\\n elif display_as == 'tab':\\n out = '\\\\n'.join(\\n ['\\\\t'.join(['Column', 'Description', 'Type'])] +\\\\\\n ['\\\\t'.join([k, v[1], v[0]]) for k, v in cols.items()],\\n )\\n elif display_as == 'list':\\n out = '\\\\n'.join([i[1] for i in cols.values()])\\n else:\\n raise Exception(\\\"'display_as' must be one of {table,tab,list}\\\")\\n if write:\\n print(out)\\n else:\\n return out\",\n \"def display_columns(self, display_as='table', write=False):\\n cols = self.columns\\n if display_as == 'table':\\n out = _tb(\\n [['Column', 'Description', 'Type']] +\\\\\\n [[k, v[1], v[0]] for k, v in cols.items()],\\n headers='firstrow', tablefmt='grid'\\n )\\n elif display_as == 'tab':\\n out = '\\\\n'.join(\\n ['\\\\t'.join(['Column', 'Description', 'Type'])] +\\\\\\n ['\\\\t'.join([k, v[1], v[0]]) for k, v in cols.items()],\\n )\\n elif display_as == 'list':\\n out = '\\\\n'.join([i[1] for i in cols.values()])\\n else:\\n raise Exception(\\\"'display_as' must be one of {table,tab,list}\\\")\\n if write:\\n print(out)\\n else:\\n return out\",\n \"def print_report():\\n width = 68\\n print(\\\"-\\\" * width)\\n header = (\\\"Donor Name\\\", \\\"Total Given\\\", \\\"Num Gifts\\\", \\\"Average Gift\\\")\\n print(\\\"{:20} | {:15} | {:10} | {:12}\\\".format(*header))\\n print(\\\"-\\\" * width)\\n for index, donor in enumerate(donors_data):\\n name = donor[\\\"name\\\"]\\n total = sum(donor[\\\"donations\\\"])\\n num_gift = len(donor[\\\"donations\\\"])\\n average = total/num_gift\\n print(\\\"{:22} ${:12,.2f} {:12d} ${:12,.2f}\\\".format(name, total, num_gift, average ))\\n print(\\\"-\\\" * width)\",\n \"def __str__(self):\\n \\n result = [\\\"rows: \\\" + str(self.rows),\\n \\\"columns: \\\"+str(self.columns),\\n \\\"data: \\\"+str(self.data)]\\n return \\\"\\\\n\\\".join(result)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7219429","0.7074841","0.6891936","0.6827231","0.6793333","0.67474353","0.67346114","0.67292243","0.6686646","0.6618329","0.65630335","0.65622455","0.65239674","0.65194356","0.6492314","0.6478941","0.64734554","0.64621496","0.6452394","0.6452233","0.645086","0.6445098","0.64372575","0.64370024","0.64279044","0.64108384","0.6410722","0.6373736","0.63562024","0.63410145","0.63202536","0.6299353","0.62910956","0.62888545","0.62881786","0.62875223","0.6261087","0.62401444","0.6227707","0.6217574","0.6212017","0.6211449","0.6209662","0.61945283","0.61895734","0.6155886","0.6155886","0.61555547","0.6150841","0.6147842","0.61446357","0.6144332","0.6142447","0.6138844","0.6133432","0.6132485","0.6126249","0.6114499","0.6109756","0.6109756","0.61096615","0.60922784","0.60871035","0.6070798","0.6068044","0.60677433","0.60646766","0.60484093","0.6046638","0.6043647","0.60432106","0.6041512","0.60299665","0.6028986","0.6027366","0.60192245","0.60159147","0.60116524","0.6005259","0.5996734","0.5994908","0.5992463","0.5992288","0.5985227","0.5976474","0.5973317","0.59721506","0.59679717","0.59483457","0.59476644","0.594391","0.59381825","0.59381825","0.59355587","0.59330904","0.5932035","0.59195006","0.59195006","0.5916846","0.5893755"],"string":"[\n \"0.7219429\",\n \"0.7074841\",\n \"0.6891936\",\n \"0.6827231\",\n \"0.6793333\",\n \"0.67474353\",\n \"0.67346114\",\n \"0.67292243\",\n \"0.6686646\",\n \"0.6618329\",\n \"0.65630335\",\n \"0.65622455\",\n \"0.65239674\",\n \"0.65194356\",\n \"0.6492314\",\n \"0.6478941\",\n \"0.64734554\",\n \"0.64621496\",\n \"0.6452394\",\n \"0.6452233\",\n \"0.645086\",\n \"0.6445098\",\n \"0.64372575\",\n \"0.64370024\",\n \"0.64279044\",\n \"0.64108384\",\n \"0.6410722\",\n \"0.6373736\",\n \"0.63562024\",\n \"0.63410145\",\n \"0.63202536\",\n \"0.6299353\",\n \"0.62910956\",\n \"0.62888545\",\n \"0.62881786\",\n \"0.62875223\",\n \"0.6261087\",\n \"0.62401444\",\n \"0.6227707\",\n \"0.6217574\",\n \"0.6212017\",\n \"0.6211449\",\n \"0.6209662\",\n \"0.61945283\",\n \"0.61895734\",\n \"0.6155886\",\n \"0.6155886\",\n \"0.61555547\",\n \"0.6150841\",\n \"0.6147842\",\n \"0.61446357\",\n \"0.6144332\",\n \"0.6142447\",\n \"0.6138844\",\n \"0.6133432\",\n \"0.6132485\",\n \"0.6126249\",\n \"0.6114499\",\n \"0.6109756\",\n \"0.6109756\",\n \"0.61096615\",\n \"0.60922784\",\n \"0.60871035\",\n \"0.6070798\",\n \"0.6068044\",\n \"0.60677433\",\n \"0.60646766\",\n \"0.60484093\",\n \"0.6046638\",\n \"0.6043647\",\n \"0.60432106\",\n \"0.6041512\",\n \"0.60299665\",\n \"0.6028986\",\n \"0.6027366\",\n \"0.60192245\",\n \"0.60159147\",\n \"0.60116524\",\n \"0.6005259\",\n \"0.5996734\",\n \"0.5994908\",\n \"0.5992463\",\n \"0.5992288\",\n \"0.5985227\",\n \"0.5976474\",\n \"0.5973317\",\n \"0.59721506\",\n \"0.59679717\",\n \"0.59483457\",\n \"0.59476644\",\n \"0.594391\",\n \"0.59381825\",\n \"0.59381825\",\n \"0.59355587\",\n \"0.59330904\",\n \"0.5932035\",\n \"0.59195006\",\n \"0.59195006\",\n \"0.5916846\",\n \"0.5893755\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6469105"},"document_rank":{"kind":"string","value":"17"}}},{"rowIdx":13086,"cells":{"query":{"kind":"string","value":"output the query results as a CSV"},"document":{"kind":"string","value":"def printCSVFromCursor(cur, args):\n import csv\n\n if not cur.description:\n return #nothing to print.\n\n writer = csv.writer(sys.stdout, delimiter=args.delimiter, quotechar='|',\n lineterminator='\\n', quoting=csv.QUOTE_MINIMAL)\n if args.header:\n hdr = [col[0] for col in cur.description]\n writer.writerow(hdr)\n for line in cur:\n writer.writerow(line)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_query_csv(self):\n\n self.query_df.to_csv(self.query_output_file)","def process_results(result, title=\"\", doWrite=True, query=\"\"):\n\n\tif not result or not result.returns_rows:\n\t\tprint \"-> 0 records returned\"\n\t\tprint result\n\t\treturn\n\n\tdoPrint = True\n\n\t# get column names\n\tcols = result.keys()\n\n\t# build template format string\n\ttemplate = \"\"\n\tfor i in range(len(cols)):\n\t\ttemplate += \"{%s:40}\" % i\n\ttemplate = template.replace(\"}{\", \"}|{\")\n\n\t# open output file\n\tif doWrite:\n\t\tresults_dir = DATA_PATH + \"query_results/\"\n\t\tif not os.path.exists(results_dir):\n\t\t\tos.makedirs(results_dir)\n\n\t\tnow = datetime.now().strftime(\"%Y_%m_%d__%I_%M_%p\")\n\t\tfilename = results_dir + \"query_results_\" + now\n\t\t\n\t\ttxt = open(filename+\".txt\", 'w')\n\t\tcsv = open(filename+\".csv\", 'w')\n\n\t\t# print query\n\t\ttxt.write(query + \"\\n\")\n\t\ttxt.write(\"=\" * len(query) + \"\\n\")\n\t\tcsv.write(query + \"\\n\")\n\n\t\t# print header\n\t\ttxt.write(template.format(*tuple(cols)) + \"\\n\") # header\n\t\ttxt.write(\"-\"*41*len(cols) + \"\\n\")\n\t\tcsv.write('|'.join(cols) + \"\\n\")\n\n\t# print records\n\tnumRecs = 0\n\tfor row in result:\n\t\t# ask user if they want ot stop printing after 100 records\n\t\tif numRecs == 10:\n\t\t\ti = raw_input(\"10 records printed. Continue printing records? (y/N) \")\n\t\t\tif i.lower() not in [\"y\", \"yes\"]:\n\t\t\t\tdoPrint = False\n\t\t\n\t\tif doPrint:\n\t\t\tscreen_write_row(row, title)\n\n\t\tif doWrite:\n\t\t\ttxt_write_row(txt, template, row)\n\t\t\tcsv_write_row(csv, row)\n\n\t\t# count records returned\n\t\tnumRecs += 1\n\n\t# show number of records returned\n\tprint \"-> %s records returned\" % numRecs\n\tif doWrite:\n\t\ttxt.write(\t\"-> %s records returned\" % numRecs)\n\n\tif doWrite:\n\t\ttxt.flush()\n\t\ttxt.close()","def write_results(results):\n fields = results[0].keys()\n with open('results.csv', 'w') as f:\n dw = csv.DictWriter(f, fieldnames=fields, delimiter='|')\n dw.writer.writerow(list(dw.fieldnames))\n dw.writerows(results)","def write_to_file(self, results):\n with open(self.outputFilename, \"w\") as csvFile:\n csvWriter = csv.writer(csvFile, delimiter=',') \n title_row = ('asset_id', 'component_id', 'latitude', 'longitude', 'installation_date', 'commissioning_date', 'street_name', 'cabinet_id', 'nominal_wattage', 'current_time', 'current_LogValue', 'current_IsLogValueOff') \n csvWriter.writerow(title_row)\n for record in results:\n csvWriter.writerow(record)","def write_results(results):\n with RESULTS_PATH.open(\"w\") as writer:\n csvwriter = csv.writer(writer)\n csvwriter.writerows(results)","def log_results(self, path):\n pd.DataFrame(self.results).to_csv(path)","def to_csv(self, path):\n results = self.all()\n if self.stop_check is not None and self.stop_check():\n return\n results.to_csv(path)","def csv_output(self):\r\n fh = open(\"output.csv\",'w')\r\n for i in range(len(self.population.columns)):\r\n if i != len(self.population.columns)-1:\r\n fh.write(str(self.population.columns[i]))\r\n fh.write(\",\")\r\n else:\r\n fh.write(str(self.population.columns[i]))\r\n fh.write(\"\\n\")\r\n\r\n for i in range(len(self.population.data)):\r\n for j in range(len(self.population.data[i])):\r\n if j != len(self.population.data[i])-1:\r\n fh.write(str(self.population.data[i][j]))\r\n fh.write(\",\")\r\n else:\r\n fh.write(str(self.population.data[i][j]))\r\n fh.write(\"\\n\")\r\n fh.close()","def printCsv(self):\n self.printCsvHeader()\n for r in self._records:\n r.printCsv()","def export_to_csv(self, request, queryset):\n fields = self.get_table_fields()\n field_names = [field.name for field in fields]\n field_verbose_names = [field.verbose_name.encode(\n 'utf-8'\n ) for field in fields]\n\n response = HttpResponse(content_type='text/csv')\n response['Content-Disposition'] = 'attachment; \\\nfilename=%s.csv' % unicode(self.model._meta).replace('.', '_')\n\n writer = csv.writer(response)\n writer.writerow(field_verbose_names)\n for obj in queryset:\n writer.writerow([unicode(getattr(obj, field)).encode(\n \"utf-8\",\n \"replace\"\n ) for field in field_names])\n return response","def to_csv(self, out_folder):\n import pandas as pd\n\n df = pd.DataFrame(zip(self.results['cids'],\n self.results['differences'],\n self.results['experimental_values']),\n columns=['cids', 'differences',\n 'experimental_values'])\n df.to_csv(out_folder, index=False)","def queryset_to_csv(self):\n csv_data = []\n custom_fields = []\n\n # Start with the column headers\n headers = self.queryset.model.csv_headers.copy()\n\n # Add custom field headers, if any\n if hasattr(self.queryset.model, 'get_custom_fields'):\n for custom_field in self.queryset.model().get_custom_fields():\n headers.append(custom_field.name)\n custom_fields.append(custom_field.name)\n\n csv_data.append(','.join(headers))\n\n # Iterate through the queryset appending each object\n for obj in self.queryset:\n data = obj.to_csv()\n\n for custom_field in custom_fields:\n data += (obj.cf.get(custom_field, ''),)\n\n csv_data.append(csv_format(data))\n\n return '\\n'.join(csv_data)","def format_raw(self,query_results,output_stream):\n #print(query_results.data)\n delimiter=query_results.delimiter\n res=[]\n for row in query_results.data:\n if 'data' in row:\n raw=delimiter.join(row['data'])\n if output_stream=='STDIO':\n print(raw)\n else:\n res.append(raw)\n\n if output_stream=='STRING':\n return res","def toCSV(self, outFileName):\n with open(outFileName, 'wb') as outFile:\n writer = csv.writer(outFile)\n writer.writerow(self.getHeaderList())\n for name, (results, params) in self.result.iteritems():\n writer.writerow([name] + list(results) + list(params))","def send_results_output(**kwargs):\n logging.info(\"Printing query results to output\")\n print(kwargs[\"results_dataset_json\"])\n return True","def csv_render(qry_domains):\n reports = dict(filter(None, map(tools.analyse, qry_domains)))\n\n def generate():\n \"\"\"Streaming download generator.\"\"\"\n for (domain, rept) in reports.items():\n for entry in rept['fuzzy_domains']:\n ip, error = tools.resolve(entry['domain-name'])\n row = map(str, (\n domain,\n entry['fuzzer'],\n entry['domain-name'],\n ip,\n error,\n ))\n yield ','.join(row) + '\\n'\n\n return flask.Response(generate(), mimetype='text/csv')","def csv_repr(self):\n if len(self._dbnames) > 1:\n output = '{0},{1},{2},{3}'.format(self.name, self.url, self.mxd, self._dbnames[0])\n for db in self._dbnames[1:]:\n dbnames_output = '\\n,,,{0}'.format(db)\n output = output + dbnames_output\n else:\n output = '{0},{1},{2},{3}'.format(self.name, self.url, self.mxd, self._dbnames[0])\n return output","def write_to_csv(results, filename):\r\n fieldnames = ('datetime_utc', 'distance_au', 'velocity_km_s',\r\n 'designation', 'name', 'diameter_km',\r\n 'potentially_hazardous')\r\n\r\n with open(filename, 'w') as outfile:\r\n writer = csv.writer(outfile)\r\n writer.writerow(fieldnames)\r\n for row in results:\r\n r = [row.time, row.distance, row.velocity, row.neo.designation,\r\n row.neo.name, row.neo.diameter, row.neo.hazardous]\r\n writer.writerow(r)","def set_query_output(self, path):\n\n file = f'sql_query_R{str(self.time_span).replace(\".\", \"_\")} ({str(self.date_time).replace(\":\",\"_\")}).csv'\n self.query_output_file = path_inc(path, file)","def print_csv():\n # read lines, and make the first a link\n show_played = request.args.get('showPlayed', 'true') == 'true'\n show_out_of_office = request.args.get('showOutOfOffice', 'true') == 'true'\n songs = database.load_songs(include_played=show_played, include_out_of_office=show_out_of_office)\n entries = [_convert_first_href(str(x)) for x in songs]\n header_line = \"YouTube Link,Played,Song Name,Added by\\n\"\n return \"%s%s\" % (header_line, \"\\n\".join(entries))","def __create_output_csv(self, df, score_list, elapsed_list):\n df['Similar']=score_list\n df['Elapsed']=elapsed_list\n df.to_csv('Output.csv',index=False)\n return df","def generate_csv(results, keys, options):\n if results and keys:\n with open(options.output_file, mode=fd_write_options) as fd_output:\n spamwriter = csv.writer(fd_output, delimiter=options.delimiter, quoting=csv.QUOTE_ALL, lineterminator='\\n')\n \n if not(options.skip_header):\n spamwriter.writerow(keys)\n \n for group in results:\n output_line = []\n \n for key in keys:\n if key in group.keys():\n if \"member\" == key:\n output_line.append(\"\\n\".join(group[key].split(\" \")))\n else:\n output_line.append(group[key])\n else:\n output_line.append('')\n \n spamwriter.writerow(output_line)\n if options.newline:\n spamwriter.writerow('')\n \n fd_output.close()\n \n return None","def to_csv(self, path):\n for table in ['datasets', 'dataruns', 'hyperpartitions', 'classifiers']:\n df = pd.read_sql('SELECT * FROM %s' % table, self.session.bind)\n df.to_csv(os.path.join(path, '%s.csv' % table), index=False)","def dwn_analysis_csv(request):\n data = []\n for i in results:\n data.append((i['sentence'], i['head'], i['tail'], i['pred_relation'], i['sent'], i['conf']))\n df = pd.DataFrame(data, columns=['Sentence', 'Head', 'Tail', 'Predicted Relation', 'Predicted Sentiment', 'Confidence'])\n df.to_csv(\"temp/analysis_results.csv\", index=False)\n \n return FileResponse(open('temp/analysis_results.csv','rb'))","def export_as_csv(modeladmin, request, queryset):\n if not request.user.is_staff:\n raise PermissionDenied\n opts = modeladmin.model._meta\n response = HttpResponse(mimetype='text/csv')\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % unicode(opts).replace('.', '_')\n writer = csv.writer(response, delimiter=';')\n field_names = [field.name for field in opts.fields]\n # Write a first row with header information\n writer.writerow(field_names)\n # Write data rows\n for obj in queryset:\n values = []\n for field in field_names:\n value = (getattr(obj, field))\n if callable(value):\n try:\n value = value() or ''\n except:\n value = 'Error retrieving value'\n if value is None:\n value = ''\n values.append(unicode(value).encode('utf-8'))\n writer.writerow(values)\n #writer.writerow([getattr(obj, field) for field in field_names])\n return response","def print_results(results):\n data = []\n for idx in results.index:\n item = results.loc[idx]\n row = (str(item.gid), \n re.sub(r'\\n', ' ', item.creators),\n re.sub(r'[\\n\\r]+', ' ', item.title), \n gut_utf8.format(item.gid))\n data.append(row)\n _ = [print('|'.join(row)) for row in data]\n print('#', len(data), \"items returned\")\n return data","def export_as_csv(modeladmin, request, queryset):\n if not request.user.is_staff:\n raise PermissionDenied\n opts = modeladmin.model._meta\n response = HttpResponse(mimetype='text/csv')\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % unicode(opts).replace('.', '_')\n writer = csv.writer(response)\n field_names = [field.name for field in opts.fields]\n # Write a first row with header information\n writer.writerow(field_names)\n # Write data rows\n for obj in queryset:\n writer.writerow([getattr(obj, field) for field in field_names])\n return response","def _csv_export(self, exppath):\n with open(exppath, 'w') as csvfile:\n csvwriter = csv.writer(csvfile, delimiter=',', skipinitialspace=True)\n csvwriter.writerow(['hexstr','dmc','name'])\n for clr in self.lookup_table:\n csvwriter.writerow([clr.hex.to_str(), clr.id, clr.name])","def to_csv(self, csvwriter):\n csvwriter.writerow(self.to_csv_row())","def dbtocsv():\n connection = sqlite3.connect(\"sensordata.db\")\n cursor = connection.cursor()\n cursor.execute(\"Select * from sensordata\")\n roadstationdata = cursor.fetchall()\n\n with open('roadstationdata.csv', 'w') as f:\n writer = csv.writer(f)\n writer.writerow(['id','name','value','unit','time'])\n writer.writerows(roadstationdata)","def response_to_df_csv():\n results = api.call_api()\n df = t.get_dataframe(results)\n t.save_csv(df)\n return df","def write_results(self, results):\n predictions = open('hmm_results.csv', 'w')\n predictions.write(\"Type,Prediction\")\n for type in results:\n if type == 'O':\n continue\n predictions.write(\"\\n\" + str(type) + \",\")\n for interval in results[type]:\n predictions.write(str(interval) + \" \")\n predictions.close()","def sites_csv():\n import io\n import csv\n\n dest = io.StringIO()\n dest.write('\\ufeff')\n writer = csv.writer(dest, quoting=csv.QUOTE_MINIMAL)\n\n with Config() as config:\n with db.Connection(config) as con:\n writer.writerow(con.fieldnames)\n writer.writerows(con.read_entries())\n\n output = flask.make_response(dest.getvalue())\n output.headers[\"Content-Disposition\"] = \"attachment; filename=spatialcitizenscience.csv\"\n output.headers[\"Content-type\"] = \"text/csv\"\n return output","def to_csv(header, rows):\r\n with open('result.csv', 'w') as result:\r\n result_writer = csv.writer(result, delimiter=';')\r\n result_writer.writerow(header)\r\n result_writer.writerows(rows)","def exportEvaluation(self,results,url):\n profbox()\n if not os.path.exists(url):\n open(url, 'w').close()\n myfile = open(url, 'a')\n\n wr = csv.writer(myfile)\n r = numpy.array(results)\n if len(r.shape) == 1:\n wr.writerow(results)\n else:\n wr.writerows(results)","def convert_to_csv(self, branch):\n names = [\"CSE_results.csv\", \"IT_results.csv\"]\n self.results = {\"ROLL_NO\": self.roll_nos, \"Name\": self.names, \"SGPA\": self.sgpa}\n print(self.results)\n df = DataFrame.from_dict(self.results)\n df.to_csv(names[branch], index=False)","def export_to_csv(self, outputfilepath, separator):\n\n con = fdb.connect(\n database=self.db_filepath,\n # dsn='localhost:~/test/CGI.vvv', #localhost:3050\n user='sysdba', password='masterkey'\n #charset='UTF8' # specify a character set for the connection\n )\n cur = con.cursor()\n statement = \"select * from FILES\"\n cur.execute(statement)\n # Retrieve all rows as a sequence and print that sequence:\n print(cur.fetchall())\n\n # VVV export format: Volume,Path,Name,Size,Ext,Last modified,Description\n\n with open(outputfilepath, 'w') as csvfile:\n writer = csv.writer(csvfile)\n writer.writerow([ i[0] for i in cur.description ]) \n writer.writerows(cur.fetchall())","def send_csv_reply(self, request, result, tags):\n request.setHeader('Content-disposition', 'attachment; filename=%s.csv' % \n result[0]['uuid'])\n if tags[0][0]:\n tags = tags[0][1][0][0]\n else:\n tags = None\n self.write_one_stream(request, \n result[0], \n tags)\n \n request.finish()","def print_output(blast_results):\n output = ''\n header = ['query ID', 'query length', 'subject ID', 'percent identity',\n 'query coverage']\n line = '\\t'.join(header) + '\\n'\n output += line\n for query in blast_results:\n length = str(query_length(query))\n coverage = query_coverage(query)\n coverage = '{:.2}'.format(coverage)\n identity = '{:.2f}'.format(float(query['% identity']))\n line = '\\t'.join([query['query acc.ver'], length, \n query['subject acc.ver'], identity,\n coverage])\n line += '\\n'\n output += line\n print(output)","def export_as_csv(modeladmin, request, queryset):\n opts = modeladmin.model._meta\n field_names = [field.name for field in opts.fields]\n labels = []\n\n if exclude:\n field_names = [f for f in field_names if f not in exclude]\n\n elif fields:\n field_names = [field for field, _ in fields]\n labels = [label for _, label in fields]\n\n response = HttpResponse(content_type='text/csv')\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % (\n str(opts).replace('.', '_')\n )\n\n writer = csv.writer(response)\n\n if header:\n writer.writerow(labels if labels else field_names)\n\n for obj in queryset:\n writer.writerow([prep_field(request, obj, field, manyToManySep) for field in field_names])\n return response","def outputFunc(filename, resultList):\n #assert len(parks) == 3\n \n f = open(filename, 'wt')\n \n try:\n writer = csv.writer(f)\n for i in range(len(resultList)):\n print resultList[0]\n writer.writerow(resultList[i])\n \n finally:\n f.close()","def export(self, out_filename='RESULT.csv'):\n\n query = input(\n \"Enter output filename (Default = {}):\\n>\".format(out_filename))\n # Set filename to the default value if user doesn't enter one\n if query == '':\n query = out_filename\n\n with open(query, encoding='utf-8', mode='w', newline='\\n') as out_file:\n writer = csv.DictWriter(out_file, fieldnames=self.headers)\n\n writer.writeheader() # Write the headers to the first row\n for record in self.records:\n writer.writerow(record.attributes)\n\n print(\"Successfully output to {}\".format(query))","def generate_csv(self, output_file):\n try: # We are going to \"try\" something\n csv_file = open(output_file, 'w+') # open \"output_file\" as a writable file and return a handle called \"csv_file\"\n except OSError as err: # If something goes wrong with the open, we catch the exception\n fatal(\"{0}\".format(err), -1) # exit with something other than 0 so the shell knows something went wrong\n \n writer = csv.writer(csv_file) # create a CSV writing object that's pointing at our open file handle\n\n writer.writerow([\"Question\",\"Answers\"]) # Let's write the top row\n for k in self.questions.keys(): # Let's walk down the directory by key\n # write the \"key\" (which is the question) and then let's take the list of answers and create a comma delmited list.\n # this is likely totally wrong since you could have an answer in it that also has a comma...\n writer.writerow([k, \",\".join(self.questions[k].answers)]) # insert a key (which is the question) and then let's take the array of \n\n csv_file.close() # close the csv_file file handle","def export_as_csv(modeladmin, request, queryset):\n opts = modeladmin.model._meta\n field_names = set([field.name for field in opts.fields])\n if fields:\n fieldset = set(fields)\n field_names = field_names & fieldset\n elif exclude:\n excludeset = set(exclude)\n field_names = field_names - excludeset\n\n response = HttpResponse(mimetype='text/csv')\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % str(opts).replace('.', '_')\n\n writer = csv.DictWriter(response, fields)\n writer.writeheader()\n\n for obj in queryset:\n writer.writerow(dict(zip(fields, [getattr(obj, field) for field in fields])))\n\n return response","def outputData(tname):\n\n table = pd.read_sql(\"SELECT * FROM {0}\".format(tname), ENGINE)\n table.to_csv(\"data/{0}.csv\".format(tname), sep=\",\", header=True, index=False, quoting=csv.QUOTE_NONNUMERIC)","def write_csv(self):\n with open(paths.CSV_FILE, 'w', newline='') as csv_file:\n writer = csv.writer(csv_file)\n assg = AssignmentConfig().get_assignment()\n writer.writerow([\"Student\"] + assg.get_test_list() + assg.get_programs_list() +\n [\"normalised_test_score\"] + [\"normalised_prog_score\"] + [\"total\"] + [\"total_rounded\"])\n\n for (submitter, submitter_data) in sorted(self.snapshot['results'].items()):\n total_score = submitter_data[\"normalised_test_score\"] + submitter_data[\"normalised_prog_score\"]\n total_rounded = round(total_score * 2) / 2 # total score rounded to nearest 0.5\n writer.writerow([submitter] +\n [submitter_data[\"tests\"][test] for test in sorted(submitter_data[\"tests\"])] +\n [submitter_data[\"progs\"][prog] for prog in sorted(submitter_data[\"progs\"])] +\n [submitter_data[\"normalised_test_score\"]] +\n [submitter_data[\"normalised_prog_score\"]] +\n [round(total_score, 2)] +\n [total_rounded])","def output_columns(self) -> List[str]:","def generate_csv(results, path):\n csvpath = path + '/results.csv'\n\n if os.path.exists(csvpath):\n os.remove(csvpath)\n\n csvf = open(csvpath, 'w')\n\n # Header\n csvf.write(\"Powerpoint, Mean, Mode\\n\")\n\n # Results\n for power in results:\n mean = 0\n count = 0\n mode = 0\n maxc = 0\n for freq in results[power]:\n freqc = results[power][freq]\n\n mean += freq * freqc\n count += freqc\n\n if freqc > maxc:\n mode = freq\n\n mean /= count\n\n csvf.write(f\"{power}, {mean}, {mode}\\n\")\n\n csvf.close()","def gen_csv(self, show_headers=True, show_tags=True):\n class TextOut:\n \"\"\"Simple string output source to capture CSV\"\"\"\n def __init__(self):\n self.data = ''\n def write(self, s):\n self.data += s\n def get(self):\n data = self.data\n self.data = ''\n return data\n output = TextOut()\n writer = csv.writer(output)\n for raw in self.gen_raw(show_headers, show_tags):\n writer.writerow(raw)\n yield output.get()","def export_to_ranking_csv(request, token, project):\n from appraise.local_settings import EXPORT_TOKEN\n if not token == EXPORT_TOKEN:\n return HttpResponseForbidden()\n \n annotation_project = get_object_or_404(Project, name=project)\n \n queryset = RankingResult.objects.filter(item__hit__completed=True)\n\n results = [u'srclang,trglang,srcIndex,doucmentId,segmentId,judgeId,' \\\n 'system1Number,system1Id,system2Number,system2Id,system3Number,' \\\n 'system3Id,system4Number,system4Id,system5Number,system5Id,' \\\n 'system1rank,system2rank,system3rank,system4rank,system5rank']\n \n for result in queryset:\n if isinstance(result, RankingResult):\n if result.item.hit.project_set.filter(id=annotation_project.id):\n # Current implementation of export_to_pairwise_csv() is weird.\n # By contrast, export_to_csv() generates the right thing...\n current_csv = result.export_to_csv()\n if current_csv is None:\n continue\n results.append(current_csv)\n \n export_csv = u\"\\n\".join(results)\n export_csv = export_csv + u\"\\n\"\n return HttpResponse(export_csv, mimetype='text/plain')","def export_csv(state, out_file=None):\n\n if out_file is None:\n csvfile = sys.stdout\n else:\n csvfile = open(out_file, 'w')\n\n try:\n writer = csv.writer(csvfile)\n for grade in state.grades:\n writer.writerow([grade.student_name(), grade.score(),\n grade.breakdown(state.user_name)])\n finally:\n if out_file is not None:\n csvfile.close()","def convert_to_csv(table):\n print(f'writing {table} to csv')\n\n destination = Path(__file__).parent.parent.parent / 'data' / 'results' / f'{table}.csv'\n\n with arcpy.da.SearchCursor(\n in_table=table,\n field_names=['type', 'primary_key', 'county_name', 'senate_district', 'house_district', 'census_id'],\n where_clause='message is null'\n ) as cursor, open(destination, 'w', encoding='utf-8', newline='') as result_file:\n writer = csv.writer(result_file, delimiter='|', quoting=csv.QUOTE_MINIMAL)\n\n for row in cursor:\n writer.writerow(row)","def print(self):\n df = self.gen_test()\n # print(df)\n df.to_csv('some_dated_file.csv', index=False)\n return df","def get_csv_string(self):\n df = None\n for d in self.data:\n if df is None:\n df = d.as_dataframe()\n else:\n df = df.append(d.as_dataframe())\n\n if df is None:\n return \"\"\n else:\n return df.to_csv(index=False)","def outputLevelCsv(self):\n # extract level information from result info\n extract_level = []\n extract_level = [item for item in self._result_info if self._result_info[2][0:5]=='LEVEL']\n if extract_level == []:\n print('No Result of LEVEL')\n return None\n # copy need information\n for i, item in enumerate(extract_level):\n self._level_csv_list[i][0] = item[1]\n self._level_csv_list[i][1] = item[2].split('-')[1]\n self._level_csv_list[i][2] = item[2].split('-')[2]\n self._level_csv_list[i][3] = item[4]\n # set csv file name\n csv_file_name = self._filename.rsplit('.', 1)[1] + '.csv'\n # write csv\n with open(csv_file_name, 'w') as csv_file:\n writer = csv.writer(csv_file)\n writer.writerows(self._level_csv_list)","def export_to_pairwise_csv(request, token, project):\n from appraise.local_settings import EXPORT_TOKEN\n if not token == EXPORT_TOKEN:\n return HttpResponseForbidden()\n \n annotation_project = get_object_or_404(Project, name=project)\n \n queryset = RankingResult.objects.filter(item__hit__completed=True)\n\n results = [u'srclang,trglang,srcIndex,segmentId,judgeId,' \\\n 'system1Id,system1rank,system2Id,system2rank,rankingID']\n \n for result in queryset:\n if isinstance(result, RankingResult):\n if result.item.hit.project_set.filter(id=annotation_project.id):\n current_csv = result.export_to_pairwise_csv()\n if current_csv is None:\n continue\n results.append(current_csv)\n \n export_csv = u\"\\n\".join(results)\n export_csv = export_csv + u\"\\n\"\n return HttpResponse(export_csv, mimetype='text/plain')","def generate_report(self, output_path):\n with open(output_path, 'w', newline='', encoding=\"utf-8\") as csv_fd:\n writer = csv.writer(csv_fd, quoting=csv.QUOTE_NONNUMERIC, doublequote=False, escapechar=\"\\\\\")\n writer.writerow([\"category\", \"level\", \"description\", \"method\", \"parameter\", \"url\", \"body\"])\n writer.writerows(self._vulns)\n writer.writerows(self._anomalies)\n writer.writerows(self._additionals)","def csv_response(filename, header, rows):\r\n response = HttpResponse(mimetype='text/csv')\r\n response['Content-Disposition'] = 'attachment; filename={0}'.format(filename)\r\n writer = csv.writer(response, dialect='excel', quotechar='\"', quoting=csv.QUOTE_ALL)\r\n # In practice, there should not be non-ascii data in this query,\r\n # but trying to do the right thing anyway.\r\n encoded = [unicode(s).encode('utf-8') for s in header]\r\n writer.writerow(encoded)\r\n for row in rows:\r\n encoded = [unicode(s).encode('utf-8') for s in row]\r\n writer.writerow(encoded)\r\n return response","def dwn_saved_result_csv(request):\n source_id = request.GET.get('source_id')\n data = []\n objs = ExtractedRelation.objects.filter(source=source_id)\n s = Source.objects.filter(source_id=source_id)[0]\n for i in objs:\n data.append((i.sentence, i.head, i.tail, i.pred_relation, i.sentiment, i.conf, s.source, i.rel_id, os.path.basename(i.ckpt)))\n \n df = pd.DataFrame(data, columns=['Sentence', 'Head', 'Tail', 'Predicted Relation', 'Predicted Sentiment', 'Confidence', 'Source', 'rel_id', 'Checkpoint'])\n df.to_csv(\"temp/analysis_results.csv\", index=False)\n \n return FileResponse(open('temp/analysis_results.csv','rb'))","def write_csv(self, file: str, table: str, libref: str =\"\", nosub: bool =False, dsopts: dict = None, opts: dict = None) -> 'The LOG showing the results of the step':\n dsopts = dsopts if dsopts is not None else {}\n opts = opts if opts is not None else {}\n\n code = \"filename x \\\"\"+file+\"\\\";\\n\"\n code += \"options nosource;\\n\"\n code += \"proc export data=\"\n\n if len(libref):\n code += libref+\".\"\n\n code += \"'\"+table.strip()+\"'n \"+self._sb._dsopts(dsopts)+\" outfile=x dbms=csv replace; \"\n code += self._sb._expopts(opts)+\" run\\n;\"\n code += \"options source;\\n\"\n\n if nosub:\n print(code)\n else:\n ll = self.submit(code, \"text\")\n return ll['LOG']","def csvprint(self, data):\n import csv\n import sys\n # self._assert(data) CSV data row lenght can vary\n data = self._render(data) # make elements ascii\n writer = csv.writer(sys.stdout, delimiter=',',\n quotechar='\"', \n quoting=csv.QUOTE_MINIMAL,\n lineterminator=\"\\n\")\n for row in data: writer.writerow(row)","def write_csv(self, outfile, collapse_orders=False, show_age=False):\r\n # Write header row\r\n outfile.write(self.get_csv_header(collapse_orders, show_age).encode())\r\n\r\n # Write content\r\n for x in self.records:\r\n x.write_csv(outfile, collapse_orders, show_age)","def handle_output(all_rows, opts):\n for dev, rows in all_rows.iteritems():\n\n if opts.csv:\n writer = csv.writer(sys.stdout)\n for row in rows:\n writer.writerow([dev] + row)\n elif opts.dotty:\n continue\n elif opts.sqldb:\n write_sqldb(opts.sqldb, dev, rows)\n else:\n print 'DEVICE: {}'.format(dev)\n print_table(rows)","def save_csv(connection, query, columns, name):\n\n try:\n df = pd.read_sql(query, connection, columns=columns)\n df.to_csv(name, index=False)\n except Exception as ex:\n print(type(ex))\n print(ex)","def write_results_to_disk(self, result_path,results):\n with open(result_path+\"/results.txt\",\"w+\") as out:\n\n for query_num in results:\n for doc_num in results[query_num]:\n out.write(str(query_num)+\" 0 \"+doc_num+\" 1 42.38 mt\\n\")\n out.close()","def construct_csv(cursor):\n header, data = construct_list(cursor)\n # python 2 and 3 handle writing files differently\n if sys.version_info[0] <= 2:\n output = io.BytesIO()\n else:\n output = io.StringIO()\n writer = csv.writer(output)\n\n writer.writerow(header)\n for row in data:\n writer.writerow(row)\n\n return output.getvalue()","def export(self,**kwargs):\n \n # import pdb;pdb.set_trace()\n \n # provide for case where recs are set extenally\n if not self.recs:\n self.select_recs(**kwargs)\n if self.recs:\n if self.export_file_name:\n filename = self.export_file_name\n else:\n filename = \"{table_name}_report_{datetime}.csv\".format(\n table_name = self.table.display_name,\n datetime = date_to_string(local_datetime_now(),'iso_datetime'),\n ).replace(' ','_').lower()\n \n if not self.export_fields:\n # include all fields by default\n self.export_fields = self._set_default_list_fields(include_all=True).copy()\n\n self.set_list_fields(self.export_fields)\n \n \n if self.export_template:\n result = render_template(self.export_template, data=self)\n else:\n # add a descriptive title row\n if self.export_title:\n result = self.export_title.strip() + '\\n'\n else:\n result = \"Export of table {} as of {}\\n\".format(self.table.table_name,excel_date_and_time_string(local_datetime_now()))\n \n result += ','.join([x['label'] for x in self.export_fields]) + '\\n'\n for rec in self.recs:\n rec_row = []\n for field in self.export_fields:\n data = rec.__getattribute__(field['name'])\n if field['type'].upper() == \"DATE\":\n data = local_date_string(data)\n elif field['type'].upper() == \"DATETIME\":\n data = excel_date_and_time_string(data)\n else:\n # just text\n data = str(data).strip()\n \n # replace double quotes with double-double quotes\n data = data.replace('\"','\"\"') #double up on double quotes\n \n if \",\" in data:\n # if any commas, wrap in quotes\n data = '\"' + data + '\"'\n \n #replace returns\n data = data.replace('\\r\\n',' -crnl- ')\n data = data.replace('\\n',' -nl- ')\n data = data.replace('\\r',' -rtn- ')\n\n rec_row.append(data)\n \n result += ','.join([str(x) for x in rec_row]) + '\\n'\n \n return DataStreamer(result,filename,'text/csv').send()\n \n self.result_text = \"No records selected\"\n self.success = False\n \n flash(self.result_text)\n return self.list(**kwargs)","def writeCSV():\n final_list = get_final_list()\n path_to_csv_File = 'system_metrics.csv'\n\n csv_file = open(path_to_csv_File, 'w+', newline='', encoding=\"utf8\")\n csv_file_writer = csv.writer(csv_file, delimiter=',')\n\n csv_file_writer.writerow(['Subscription', 'Resource', 'MetricType',\n 'Timestamp', 'Unit', 'Minimum', 'Maximum', 'Average'])\n\n for item in final_list:\n csv_file_writer.writerow([item['subscription'], item['resource'], item['metricType'], item['timestamp'],\n item['unit'], item['minimum'], item['maximum'], item['average']])\n\n print('Output written successfully!!')","def export(request):\n\n if not request.user.is_authenticated():\n return HttpResponseRedirect('/login/?next=%s' % request.path)\n\n filename = 'export-inscrits%s.csv' % date.today().strftime(\"%y-%m-%d\")\n\n person_list = Person.objects.all()\n\n table = ExportPersonTable(person_list)\n table.order_by = request.GET.get(\"sort\",'last_name')\n\n response = HttpResponse(mimetype='text/csv')\n response['Content-Disposition'] = 'attachment; filename=%s' % filename\n writer = csv.writer(response)\n # Write headers to CSV file\n headers = []\n for column in table.columns:\n headers.append(column.header.encode('utf8'))\n writer.writerow(headers)\n\n # Write data to CSV file\n for obj in table.rows:\n row = []\n for value in obj:\n row.append(value.encode('utf8'))\n writer.writerow(row)\n\n # Return CSV file to browser as download\n return response","def _csv(content):\n response = _data_frame(content).to_csv(index=False)\n return response","def _pipe(content):\n response = _data_frame(content).to_csv(index=False,sep='|')\n return response","def write_csv(self, filelike):\r\n items = self.rows()\r\n writer = unicodecsv.writer(filelike, encoding=\"utf-8\")\r\n writer.writerow(self.header())\r\n for item in items:\r\n writer.writerow(item)","def export_users(_request):\n query = models.UserProfile.all().order('email')\n rows = []\n for user in query:\n is_superuser = 0\n if user.is_superuser:\n is_superuser = 1\n rows.append('%s,%s\\n' % (user.email, is_superuser))\n\n response = http.HttpResponse(''.join(rows), mimetype='text/csv')\n response['Content-Disposition'] = 'attachment; filename=users.csv'\n return response","def write_to_csv(results, filename):\n fieldnames = ('datetime_utc', 'distance_au',\n 'velocity_km_s', 'designation', 'name',\n 'diameter_km', 'potentially_hazardous')\n\n with open(filename, 'w') as results_file:\n writer = csv.DictWriter(results_file, fieldnames)\n writer.writeheader()\n for result in results:\n resultsDict = {fieldnames[0]: result.time,\n fieldnames[1]: result.distance,\n fieldnames[2]: result.velocity,\n fieldnames[3]: result._designation,\n fieldnames[4]: result.neo.name,\n fieldnames[5]: result.neo.diameter,\n fieldnames[6]: result.neo.hazardous}\n writer.writerow(resultsDict)","def output_results(self, model, limit):\n out = []\n for key in self.results[model].keys():\n qId = key\n count = 1\n sorted_docs = sorted(self.results[model][key].items(), key=operator.itemgetter(1), reverse=True)[:limit] \n for val in sorted_docs:\n dId = val[0]\n dScore = val[1]\n dRank = count\n out.append(str(qId) + \" \" + \"Q0\" + \" \" + str(dId) + \" \" + str(dRank) + \" \" + str(dScore) + \" \" + \"Exp\")\n count += 1\n return out","def export_sensor_data_to_csv(self):\n df = pd.read_sql('SELECT * FROM sensor_data', self.conn)\n df.to_csv('output/sensor_data.csv', index=False)","def write_results(self, results, fname, folder=None):\n folder = folder or self.output_dir\n\n if not os.path.exists(folder):\n logger.info(\"creating {} (did not exist)\".format(folder))\n os.makedirs(folder)\n\n out_file = os.path.join(folder, fname)\n logger.info(\"writing to {}\".format(out_file))\n df = pd.DataFrame(results)\n df.to_csv(out_file, index=False)\n \n return None","def to_csv(self):\n if not self._fitted:\n self.fit()\n #self._message(\"Saving results into a csv (comma separated values) file.\")\n v=np.array([list(self.initialConcentration.values()),\n list(self.fitting_error.values()),\n list(self.k.values()),\n list(self.Fb.values()),\n list(self.slope.values())]).T\n k=list(self.initialConcentration.keys())\n d=pd.DataFrame(v,columns=['Initial Concentration','Fitting Error','k','Fb','Slope'],index=k)\n fn=get_valid_fname(self.ID)\n self.csvname=\"%s_initial_concentrations.csv\"%(fn)\n self.fullcsvname=\"%s/%s_initial_concentrations.csv\"%(self.info['resultsdir'],fn)\n self.info['csvname_initialConcentration']=self.csvname\n print(self.csvname)\n d.to_csv('%s/%s'%(self.info['resultsdir'],self.csvname))","def export_csv(table_name, out_file):\n con = sqlite3.connect(dbname)\n import pandas as pd\n\n df = pd.read_sql_query(f\"SELECT * FROM {table_name}\", con)\n df.to_csv(out_file, index=False)","def print_csv_format(results):\n assert isinstance(results, OrderedDict), results # unordered results cannot be properly printed\n for task, res in results.items():\n # Don't print \"AP-category\" metrics since they are usually not tracked.\n important_res = [(k, v) for k, v in res.items() if \"-\" not in k]\n print(\"copypaste: Task: {}\".format(task))\n print(\"copypaste: \" + \",\".join([k[0] for k in important_res]))\n print(\"copypaste: \" + \",\".join([\"{0:.4f}\".format(k[1]) for k in important_res]))","def exportEvaluation(self, results, url):\r\n # research\r\n profprint()\r\n if not os.path.exists(url):\r\n print \"creating new results file: \",url\r\n open(url, 'w').close()\r\n myfile = open(url, 'a')\r\n\r\n wr = csv.writer(myfile)\r\n r = numpy.array(results)\r\n if len(r.shape) == 1:\r\n wr.writerow(results)\r\n else:\r\n wr.writerows(results)","def generate_csv(table, header):\n with open(\"%s.csv\" % header, \"w\") as csvfile:\n for i in range(len(table)):\n for j in range(len(table[i])):\n if j != len(table[i])-1:\n tmp = table[i][j] + \",\"\n else:\n tmp = table[i][j] + \"\\n\"\n csvfile.write(tmp)","def save_results(self):\n results = pd.concat([\n pd.DataFrame(self.IDs.cpu().numpy(), columns= ['ID']), \n pd.DataFrame(self.predicted_labels.cpu().numpy(), columns= ['predicted_label']),\n pd.DataFrame(self.correct_predictions.cpu().numpy(), columns= ['correct_prediction']),\n pd.DataFrame(self.epistemic_uncertainty.cpu().numpy(), columns= ['epistemic_uncertainty']), \n pd.DataFrame(self.aleatoric_uncertainty.cpu().numpy(), columns= ['aleatoric_uncertainty']), \n pd.DataFrame(self.total_uncertainty.cpu().numpy(), columns= ['total_uncertainty']), \n ], axis=1)\n\n create_results_directory()\n results.to_csv('results/{}_{}_results.csv'.format(self.__class__.__name__, datetime.datetime.now().replace(microsecond=0).isoformat()), index=False)","def downloadResponse(request, formcode=None):\n if formcode !=None:\n response = HttpResponse(content_type='text/csv')\n responses = Response.objects.filter(form_id=formcode)\n writer = csv.writer(response)\n writer.writerow(['User', 'Submit Date', 'Answer1', 'Answer2', 'Answer3'])\n for r in responses:\n user = User.objects.get(id=r.user_id)\n writer.writerow([user, r.submitDate, r.answer1 ,r.answer2 , r.answer3])\n\n response['Content-Disposition'] = 'attachment; filename=\"response.csv\"'\n return response \n return render(request, 'download.html')","def create_file_output(self, results):\n for key, value in results.table_output.items():\n name_timestamp = key.split('&')\n _name = name_timestamp[0]\n timestamp = name_timestamp[1]\n file_name = output_file_prefix + \"-\" + _name + \".csv\"\n if file_name not in self.file_creation_set:\n self._header_written = False\n self.file_creation_set.update([file_name])\n for row in value:\n with open(file_name, 'a+') as file_to_write:\n row.update({'Timestamp': timestamp})\n _keys = row.keys()\n file_output = csv.DictWriter(file_to_write, _keys)\n if not self._header_written:\n file_output.writeheader()\n self._header_written = True\n file_output.writerow(row)\n file_to_write.close()\n return results","def output(items, headers, outputFile):\n\tdictToValues = lambda d: \\\n\t\tmap(lambda h: d.get(h, ''), headers)\n\n\treturn writeCsv(outputFile, map(dictToValues, items))","def csv(self, section=\"main\", column_headers=True):\n table_end = \"\\r\\n\\r\\n\\r\\n\"\n table_head_pos = self.header_dictionary[section]\n table_end_pos = self.raw_data[table_head_pos:].find(table_end)\n if table_end_pos == -1:\n table_end_pos = len(self.raw_data)\n else:\n table_end_pos += table_head_pos\n if column_headers:\n a = \",\".join(self.columns()) + \"\\n\"\n else:\n a = \"\"\n return a + self.raw_data[table_head_pos:table_end_pos].replace(\"\\t\",\",\").replace(\"\\r\",\"\")","def generate_csv(inf, outf):\n o = csv.writer(outf)\n o.writerow(COLUMNS)\n for row in reformat_data(inf):\n o.writerow([inf.name] + row)","def querySciDB(cmd):\n #startT = benchmark.startTimer(cmd)\n\n proc = subprocess.Popen([\"/opt/scidb/12.10/bin/iquery\", \"-o\", \"csv+\", \"-a\", \"-q\", cmd], stdout = subprocess.PIPE)\n out,err = proc.communicate()\n\n lines = out.split(\"\\n\")\n # first line is header, last line is empty\n header = lines[0].split(\",\")\n rows = [line.split(\",\") for line in lines[1:-1]]\n #benchmark.endTimer(cmd, startT)\n\n return header, rows","def write_to_csv(self, output_dir, delimiter, include_language, filename=None):\n\n if filename is not None:\n self.filename = filename\n\n if len(self.values) == 0:\n logger.info(\"Nothing to export.\")\n return\n\n if not os.path.exists(output_dir):\n os.makedirs(output_dir)\n\n file_path = os.path.join(output_dir, self.filename)\n\n # write search results to UTF8-encoded CSV file (see also http://stackoverflow.com/a/844443)\n with codecs.open(file_path, 'w', encoding='utf8') as fp:\n logger.info('Exporting search results to ' + file_path + '...')\n writer = csv.writer(fp, delimiter=delimiter)\n\n column_names = SearchResult.get_column_names(include_language)\n\n # write header of CSV file\n writer.writerow(column_names)\n\n count = 0\n try:\n for row in self.get_rows(include_language):\n if len(row) == len(column_names):\n writer.writerow(row)\n count = count + 1\n else:\n raise IllegalArgumentError(\n str(abs(len(column_names) - len(row))) + ' parameter(s) is/are missing for \"'\n + str(row) + '\"')\n\n except UnicodeEncodeError:\n logger.error('Encoding error while writing data for: ' + str(row))\n\n logger.info(str(count) + ' search results have been exported.')","def save_results(self, results, file_name, file_type):\n if file_type == 'csv':\n csv_filename = '{}.csv'.format(file_name)\n\n with open(csv_filename, 'w', newline='') as file:\n writer = csv.writer(file)\n writer.writerows(results)","def write_csv(self, outputfile):\n d = csv.writer(outputfile, quoting=csv.QUOTE_ALL)\n for row in self.translations.iteritems():\n d.writerow(row)","def write_output(self) -> None:\n self.home.round(2).to_csv(var.indicators_base_cumsum + \"home_\" + str(self.year) + \".csv\")\n self.away.round(2).to_csv(var.indicators_base_cumsum + \"away_\" + str(self.year) + \".csv\")","def csv_response(rows, filename=\"export.csv\"):\n\t# Unfortunately Flask doesn't let you output response as an IO Stream, so you have\n\t# buffer the entire response to a string first.\n\tsi = StringIO.StringIO()\n\tcw = csv.writer(si)\n\tcw.writerow(header)\n\tfor row in rows:\n\t\tcw.writerow()\n\toutput = make_response(si.getvalue())\n\toutput.headers[\"Content-Disposition\"] = \"attachment; filename=%s\" % filename\n\toutput.headers[\"Content-type\"] = \"text/csv\"\n\treturn output","def export_data(fp, app_name):\n from otree.views.admin import get_display_table_rows\n colnames, rows = get_display_table_rows(\n app_name, for_export=True, subsession_pk=None)\n colnames = ['{}.{}'.format(k, v) for k, v in colnames]\n writer = csv.writer(fp)\n writer.writerows([colnames])\n writer.writerows(rows)","def list_apiscout_csv(self, destination):\n res = self.__make_api_call('list/apiscout/csv', raw=True)\n with open(destination, \"wb\") as csvfile:\n csvfile.write(res)","def write_results(filename):\n \n with open(filename, 'w', newline='') as fn:\n writer = csv.writer(fn)\n writer.writerows([('id', 'number_of_places_available'), ''])\n pair: Point = yield # where x is the user id and y is the number of places available\n while pair is not None:\n writer.writerow(pair)\n pair = yield","def df_to_csvtxt(df, out_fields = ['top', 'Comp formation']): \n header = 'top, Comp formation\\n'\n csv_txt = ''\n csv_txt += csv_txt + header\n for i, row in df.iterrows():\n csv_txt = csv_txt + str(row['MD']) + ', ' + row['PICK'] + '\\n'\n return csv_txt","def get_csv_logs(how_many_rows: int) -> str:\n db = get_db()\n counts = db.get_newest_counts(how_many_rows, hc_db.NewestSort.SUBMIT_TIME)\n counts_as_string = \"\"\n for count in counts:\n username = db.get_user_by_id(count[\"user_id\"])\n # Don't error out when there are headcounts by users who no longer exist\n if username is None:\n username = \"(Deleted user; ID %s)\" % (count[\"user_id\"],)\n else:\n username = username[\"username\"]\n room_rows = db.get_roomdata_for_count_id(count[\"id\"])\n counts_as_string += username + \",\"\n counts_as_string += count[\"submit_time\"] + \",\" + count[\"entered_time\"] + \",\"\n room_counts = {}\n for row in room_rows:\n room_counts[row[\"room\"]] = row[\"people_count\"]\n room_counts = OrderedDict(sorted(room_counts.items()))\n counts_as_string += \",\".join([str(x) for x in room_counts.values()])\n counts_as_string += \"\\n\"\n return counts_as_string","def write_csv_fulltext(records, output_file):\n with open(output_file, 'a') as csv_out:\n\n csv_writer = csv.writer(csv_out)\n csv_writer.writerow(['PMCID', 'Title', 'Abstract'])\n\n for record in records['PubmedArticle']:\n pmid_text = record['MedlineCitation']['PMCID']\n title_text = record['MedlineCitation']['Article']['ArticleTitle']\n abs_text = get_abs_text(record)\n csv_writer.writerow([pmid_text, title_text, abs_text])","def write_rating_data():\n with open('outward.csv', 'w') as f:\n out = csv.writer(f)\n\n for item in Rating.query.filter(Rating.score != None).all():\n out.writerow([item.user_id, item.book_id, item.score])"],"string":"[\n \"def create_query_csv(self):\\n\\n self.query_df.to_csv(self.query_output_file)\",\n \"def process_results(result, title=\\\"\\\", doWrite=True, query=\\\"\\\"):\\n\\n\\tif not result or not result.returns_rows:\\n\\t\\tprint \\\"-> 0 records returned\\\"\\n\\t\\tprint result\\n\\t\\treturn\\n\\n\\tdoPrint = True\\n\\n\\t# get column names\\n\\tcols = result.keys()\\n\\n\\t# build template format string\\n\\ttemplate = \\\"\\\"\\n\\tfor i in range(len(cols)):\\n\\t\\ttemplate += \\\"{%s:40}\\\" % i\\n\\ttemplate = template.replace(\\\"}{\\\", \\\"}|{\\\")\\n\\n\\t# open output file\\n\\tif doWrite:\\n\\t\\tresults_dir = DATA_PATH + \\\"query_results/\\\"\\n\\t\\tif not os.path.exists(results_dir):\\n\\t\\t\\tos.makedirs(results_dir)\\n\\n\\t\\tnow = datetime.now().strftime(\\\"%Y_%m_%d__%I_%M_%p\\\")\\n\\t\\tfilename = results_dir + \\\"query_results_\\\" + now\\n\\t\\t\\n\\t\\ttxt = open(filename+\\\".txt\\\", 'w')\\n\\t\\tcsv = open(filename+\\\".csv\\\", 'w')\\n\\n\\t\\t# print query\\n\\t\\ttxt.write(query + \\\"\\\\n\\\")\\n\\t\\ttxt.write(\\\"=\\\" * len(query) + \\\"\\\\n\\\")\\n\\t\\tcsv.write(query + \\\"\\\\n\\\")\\n\\n\\t\\t# print header\\n\\t\\ttxt.write(template.format(*tuple(cols)) + \\\"\\\\n\\\") # header\\n\\t\\ttxt.write(\\\"-\\\"*41*len(cols) + \\\"\\\\n\\\")\\n\\t\\tcsv.write('|'.join(cols) + \\\"\\\\n\\\")\\n\\n\\t# print records\\n\\tnumRecs = 0\\n\\tfor row in result:\\n\\t\\t# ask user if they want ot stop printing after 100 records\\n\\t\\tif numRecs == 10:\\n\\t\\t\\ti = raw_input(\\\"10 records printed. Continue printing records? (y/N) \\\")\\n\\t\\t\\tif i.lower() not in [\\\"y\\\", \\\"yes\\\"]:\\n\\t\\t\\t\\tdoPrint = False\\n\\t\\t\\n\\t\\tif doPrint:\\n\\t\\t\\tscreen_write_row(row, title)\\n\\n\\t\\tif doWrite:\\n\\t\\t\\ttxt_write_row(txt, template, row)\\n\\t\\t\\tcsv_write_row(csv, row)\\n\\n\\t\\t# count records returned\\n\\t\\tnumRecs += 1\\n\\n\\t# show number of records returned\\n\\tprint \\\"-> %s records returned\\\" % numRecs\\n\\tif doWrite:\\n\\t\\ttxt.write(\\t\\\"-> %s records returned\\\" % numRecs)\\n\\n\\tif doWrite:\\n\\t\\ttxt.flush()\\n\\t\\ttxt.close()\",\n \"def write_results(results):\\n fields = results[0].keys()\\n with open('results.csv', 'w') as f:\\n dw = csv.DictWriter(f, fieldnames=fields, delimiter='|')\\n dw.writer.writerow(list(dw.fieldnames))\\n dw.writerows(results)\",\n \"def write_to_file(self, results):\\n with open(self.outputFilename, \\\"w\\\") as csvFile:\\n csvWriter = csv.writer(csvFile, delimiter=',') \\n title_row = ('asset_id', 'component_id', 'latitude', 'longitude', 'installation_date', 'commissioning_date', 'street_name', 'cabinet_id', 'nominal_wattage', 'current_time', 'current_LogValue', 'current_IsLogValueOff') \\n csvWriter.writerow(title_row)\\n for record in results:\\n csvWriter.writerow(record)\",\n \"def write_results(results):\\n with RESULTS_PATH.open(\\\"w\\\") as writer:\\n csvwriter = csv.writer(writer)\\n csvwriter.writerows(results)\",\n \"def log_results(self, path):\\n pd.DataFrame(self.results).to_csv(path)\",\n \"def to_csv(self, path):\\n results = self.all()\\n if self.stop_check is not None and self.stop_check():\\n return\\n results.to_csv(path)\",\n \"def csv_output(self):\\r\\n fh = open(\\\"output.csv\\\",'w')\\r\\n for i in range(len(self.population.columns)):\\r\\n if i != len(self.population.columns)-1:\\r\\n fh.write(str(self.population.columns[i]))\\r\\n fh.write(\\\",\\\")\\r\\n else:\\r\\n fh.write(str(self.population.columns[i]))\\r\\n fh.write(\\\"\\\\n\\\")\\r\\n\\r\\n for i in range(len(self.population.data)):\\r\\n for j in range(len(self.population.data[i])):\\r\\n if j != len(self.population.data[i])-1:\\r\\n fh.write(str(self.population.data[i][j]))\\r\\n fh.write(\\\",\\\")\\r\\n else:\\r\\n fh.write(str(self.population.data[i][j]))\\r\\n fh.write(\\\"\\\\n\\\")\\r\\n fh.close()\",\n \"def printCsv(self):\\n self.printCsvHeader()\\n for r in self._records:\\n r.printCsv()\",\n \"def export_to_csv(self, request, queryset):\\n fields = self.get_table_fields()\\n field_names = [field.name for field in fields]\\n field_verbose_names = [field.verbose_name.encode(\\n 'utf-8'\\n ) for field in fields]\\n\\n response = HttpResponse(content_type='text/csv')\\n response['Content-Disposition'] = 'attachment; \\\\\\nfilename=%s.csv' % unicode(self.model._meta).replace('.', '_')\\n\\n writer = csv.writer(response)\\n writer.writerow(field_verbose_names)\\n for obj in queryset:\\n writer.writerow([unicode(getattr(obj, field)).encode(\\n \\\"utf-8\\\",\\n \\\"replace\\\"\\n ) for field in field_names])\\n return response\",\n \"def to_csv(self, out_folder):\\n import pandas as pd\\n\\n df = pd.DataFrame(zip(self.results['cids'],\\n self.results['differences'],\\n self.results['experimental_values']),\\n columns=['cids', 'differences',\\n 'experimental_values'])\\n df.to_csv(out_folder, index=False)\",\n \"def queryset_to_csv(self):\\n csv_data = []\\n custom_fields = []\\n\\n # Start with the column headers\\n headers = self.queryset.model.csv_headers.copy()\\n\\n # Add custom field headers, if any\\n if hasattr(self.queryset.model, 'get_custom_fields'):\\n for custom_field in self.queryset.model().get_custom_fields():\\n headers.append(custom_field.name)\\n custom_fields.append(custom_field.name)\\n\\n csv_data.append(','.join(headers))\\n\\n # Iterate through the queryset appending each object\\n for obj in self.queryset:\\n data = obj.to_csv()\\n\\n for custom_field in custom_fields:\\n data += (obj.cf.get(custom_field, ''),)\\n\\n csv_data.append(csv_format(data))\\n\\n return '\\\\n'.join(csv_data)\",\n \"def format_raw(self,query_results,output_stream):\\n #print(query_results.data)\\n delimiter=query_results.delimiter\\n res=[]\\n for row in query_results.data:\\n if 'data' in row:\\n raw=delimiter.join(row['data'])\\n if output_stream=='STDIO':\\n print(raw)\\n else:\\n res.append(raw)\\n\\n if output_stream=='STRING':\\n return res\",\n \"def toCSV(self, outFileName):\\n with open(outFileName, 'wb') as outFile:\\n writer = csv.writer(outFile)\\n writer.writerow(self.getHeaderList())\\n for name, (results, params) in self.result.iteritems():\\n writer.writerow([name] + list(results) + list(params))\",\n \"def send_results_output(**kwargs):\\n logging.info(\\\"Printing query results to output\\\")\\n print(kwargs[\\\"results_dataset_json\\\"])\\n return True\",\n \"def csv_render(qry_domains):\\n reports = dict(filter(None, map(tools.analyse, qry_domains)))\\n\\n def generate():\\n \\\"\\\"\\\"Streaming download generator.\\\"\\\"\\\"\\n for (domain, rept) in reports.items():\\n for entry in rept['fuzzy_domains']:\\n ip, error = tools.resolve(entry['domain-name'])\\n row = map(str, (\\n domain,\\n entry['fuzzer'],\\n entry['domain-name'],\\n ip,\\n error,\\n ))\\n yield ','.join(row) + '\\\\n'\\n\\n return flask.Response(generate(), mimetype='text/csv')\",\n \"def csv_repr(self):\\n if len(self._dbnames) > 1:\\n output = '{0},{1},{2},{3}'.format(self.name, self.url, self.mxd, self._dbnames[0])\\n for db in self._dbnames[1:]:\\n dbnames_output = '\\\\n,,,{0}'.format(db)\\n output = output + dbnames_output\\n else:\\n output = '{0},{1},{2},{3}'.format(self.name, self.url, self.mxd, self._dbnames[0])\\n return output\",\n \"def write_to_csv(results, filename):\\r\\n fieldnames = ('datetime_utc', 'distance_au', 'velocity_km_s',\\r\\n 'designation', 'name', 'diameter_km',\\r\\n 'potentially_hazardous')\\r\\n\\r\\n with open(filename, 'w') as outfile:\\r\\n writer = csv.writer(outfile)\\r\\n writer.writerow(fieldnames)\\r\\n for row in results:\\r\\n r = [row.time, row.distance, row.velocity, row.neo.designation,\\r\\n row.neo.name, row.neo.diameter, row.neo.hazardous]\\r\\n writer.writerow(r)\",\n \"def set_query_output(self, path):\\n\\n file = f'sql_query_R{str(self.time_span).replace(\\\".\\\", \\\"_\\\")} ({str(self.date_time).replace(\\\":\\\",\\\"_\\\")}).csv'\\n self.query_output_file = path_inc(path, file)\",\n \"def print_csv():\\n # read lines, and make the first a link\\n show_played = request.args.get('showPlayed', 'true') == 'true'\\n show_out_of_office = request.args.get('showOutOfOffice', 'true') == 'true'\\n songs = database.load_songs(include_played=show_played, include_out_of_office=show_out_of_office)\\n entries = [_convert_first_href(str(x)) for x in songs]\\n header_line = \\\"YouTube Link,Played,Song Name,Added by\\\\n\\\"\\n return \\\"%s%s\\\" % (header_line, \\\"\\\\n\\\".join(entries))\",\n \"def __create_output_csv(self, df, score_list, elapsed_list):\\n df['Similar']=score_list\\n df['Elapsed']=elapsed_list\\n df.to_csv('Output.csv',index=False)\\n return df\",\n \"def generate_csv(results, keys, options):\\n if results and keys:\\n with open(options.output_file, mode=fd_write_options) as fd_output:\\n spamwriter = csv.writer(fd_output, delimiter=options.delimiter, quoting=csv.QUOTE_ALL, lineterminator='\\\\n')\\n \\n if not(options.skip_header):\\n spamwriter.writerow(keys)\\n \\n for group in results:\\n output_line = []\\n \\n for key in keys:\\n if key in group.keys():\\n if \\\"member\\\" == key:\\n output_line.append(\\\"\\\\n\\\".join(group[key].split(\\\" \\\")))\\n else:\\n output_line.append(group[key])\\n else:\\n output_line.append('')\\n \\n spamwriter.writerow(output_line)\\n if options.newline:\\n spamwriter.writerow('')\\n \\n fd_output.close()\\n \\n return None\",\n \"def to_csv(self, path):\\n for table in ['datasets', 'dataruns', 'hyperpartitions', 'classifiers']:\\n df = pd.read_sql('SELECT * FROM %s' % table, self.session.bind)\\n df.to_csv(os.path.join(path, '%s.csv' % table), index=False)\",\n \"def dwn_analysis_csv(request):\\n data = []\\n for i in results:\\n data.append((i['sentence'], i['head'], i['tail'], i['pred_relation'], i['sent'], i['conf']))\\n df = pd.DataFrame(data, columns=['Sentence', 'Head', 'Tail', 'Predicted Relation', 'Predicted Sentiment', 'Confidence'])\\n df.to_csv(\\\"temp/analysis_results.csv\\\", index=False)\\n \\n return FileResponse(open('temp/analysis_results.csv','rb'))\",\n \"def export_as_csv(modeladmin, request, queryset):\\n if not request.user.is_staff:\\n raise PermissionDenied\\n opts = modeladmin.model._meta\\n response = HttpResponse(mimetype='text/csv')\\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % unicode(opts).replace('.', '_')\\n writer = csv.writer(response, delimiter=';')\\n field_names = [field.name for field in opts.fields]\\n # Write a first row with header information\\n writer.writerow(field_names)\\n # Write data rows\\n for obj in queryset:\\n values = []\\n for field in field_names:\\n value = (getattr(obj, field))\\n if callable(value):\\n try:\\n value = value() or ''\\n except:\\n value = 'Error retrieving value'\\n if value is None:\\n value = ''\\n values.append(unicode(value).encode('utf-8'))\\n writer.writerow(values)\\n #writer.writerow([getattr(obj, field) for field in field_names])\\n return response\",\n \"def print_results(results):\\n data = []\\n for idx in results.index:\\n item = results.loc[idx]\\n row = (str(item.gid), \\n re.sub(r'\\\\n', ' ', item.creators),\\n re.sub(r'[\\\\n\\\\r]+', ' ', item.title), \\n gut_utf8.format(item.gid))\\n data.append(row)\\n _ = [print('|'.join(row)) for row in data]\\n print('#', len(data), \\\"items returned\\\")\\n return data\",\n \"def export_as_csv(modeladmin, request, queryset):\\n if not request.user.is_staff:\\n raise PermissionDenied\\n opts = modeladmin.model._meta\\n response = HttpResponse(mimetype='text/csv')\\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % unicode(opts).replace('.', '_')\\n writer = csv.writer(response)\\n field_names = [field.name for field in opts.fields]\\n # Write a first row with header information\\n writer.writerow(field_names)\\n # Write data rows\\n for obj in queryset:\\n writer.writerow([getattr(obj, field) for field in field_names])\\n return response\",\n \"def _csv_export(self, exppath):\\n with open(exppath, 'w') as csvfile:\\n csvwriter = csv.writer(csvfile, delimiter=',', skipinitialspace=True)\\n csvwriter.writerow(['hexstr','dmc','name'])\\n for clr in self.lookup_table:\\n csvwriter.writerow([clr.hex.to_str(), clr.id, clr.name])\",\n \"def to_csv(self, csvwriter):\\n csvwriter.writerow(self.to_csv_row())\",\n \"def dbtocsv():\\n connection = sqlite3.connect(\\\"sensordata.db\\\")\\n cursor = connection.cursor()\\n cursor.execute(\\\"Select * from sensordata\\\")\\n roadstationdata = cursor.fetchall()\\n\\n with open('roadstationdata.csv', 'w') as f:\\n writer = csv.writer(f)\\n writer.writerow(['id','name','value','unit','time'])\\n writer.writerows(roadstationdata)\",\n \"def response_to_df_csv():\\n results = api.call_api()\\n df = t.get_dataframe(results)\\n t.save_csv(df)\\n return df\",\n \"def write_results(self, results):\\n predictions = open('hmm_results.csv', 'w')\\n predictions.write(\\\"Type,Prediction\\\")\\n for type in results:\\n if type == 'O':\\n continue\\n predictions.write(\\\"\\\\n\\\" + str(type) + \\\",\\\")\\n for interval in results[type]:\\n predictions.write(str(interval) + \\\" \\\")\\n predictions.close()\",\n \"def sites_csv():\\n import io\\n import csv\\n\\n dest = io.StringIO()\\n dest.write('\\\\ufeff')\\n writer = csv.writer(dest, quoting=csv.QUOTE_MINIMAL)\\n\\n with Config() as config:\\n with db.Connection(config) as con:\\n writer.writerow(con.fieldnames)\\n writer.writerows(con.read_entries())\\n\\n output = flask.make_response(dest.getvalue())\\n output.headers[\\\"Content-Disposition\\\"] = \\\"attachment; filename=spatialcitizenscience.csv\\\"\\n output.headers[\\\"Content-type\\\"] = \\\"text/csv\\\"\\n return output\",\n \"def to_csv(header, rows):\\r\\n with open('result.csv', 'w') as result:\\r\\n result_writer = csv.writer(result, delimiter=';')\\r\\n result_writer.writerow(header)\\r\\n result_writer.writerows(rows)\",\n \"def exportEvaluation(self,results,url):\\n profbox()\\n if not os.path.exists(url):\\n open(url, 'w').close()\\n myfile = open(url, 'a')\\n\\n wr = csv.writer(myfile)\\n r = numpy.array(results)\\n if len(r.shape) == 1:\\n wr.writerow(results)\\n else:\\n wr.writerows(results)\",\n \"def convert_to_csv(self, branch):\\n names = [\\\"CSE_results.csv\\\", \\\"IT_results.csv\\\"]\\n self.results = {\\\"ROLL_NO\\\": self.roll_nos, \\\"Name\\\": self.names, \\\"SGPA\\\": self.sgpa}\\n print(self.results)\\n df = DataFrame.from_dict(self.results)\\n df.to_csv(names[branch], index=False)\",\n \"def export_to_csv(self, outputfilepath, separator):\\n\\n con = fdb.connect(\\n database=self.db_filepath,\\n # dsn='localhost:~/test/CGI.vvv', #localhost:3050\\n user='sysdba', password='masterkey'\\n #charset='UTF8' # specify a character set for the connection\\n )\\n cur = con.cursor()\\n statement = \\\"select * from FILES\\\"\\n cur.execute(statement)\\n # Retrieve all rows as a sequence and print that sequence:\\n print(cur.fetchall())\\n\\n # VVV export format: Volume,Path,Name,Size,Ext,Last modified,Description\\n\\n with open(outputfilepath, 'w') as csvfile:\\n writer = csv.writer(csvfile)\\n writer.writerow([ i[0] for i in cur.description ]) \\n writer.writerows(cur.fetchall())\",\n \"def send_csv_reply(self, request, result, tags):\\n request.setHeader('Content-disposition', 'attachment; filename=%s.csv' % \\n result[0]['uuid'])\\n if tags[0][0]:\\n tags = tags[0][1][0][0]\\n else:\\n tags = None\\n self.write_one_stream(request, \\n result[0], \\n tags)\\n \\n request.finish()\",\n \"def print_output(blast_results):\\n output = ''\\n header = ['query ID', 'query length', 'subject ID', 'percent identity',\\n 'query coverage']\\n line = '\\\\t'.join(header) + '\\\\n'\\n output += line\\n for query in blast_results:\\n length = str(query_length(query))\\n coverage = query_coverage(query)\\n coverage = '{:.2}'.format(coverage)\\n identity = '{:.2f}'.format(float(query['% identity']))\\n line = '\\\\t'.join([query['query acc.ver'], length, \\n query['subject acc.ver'], identity,\\n coverage])\\n line += '\\\\n'\\n output += line\\n print(output)\",\n \"def export_as_csv(modeladmin, request, queryset):\\n opts = modeladmin.model._meta\\n field_names = [field.name for field in opts.fields]\\n labels = []\\n\\n if exclude:\\n field_names = [f for f in field_names if f not in exclude]\\n\\n elif fields:\\n field_names = [field for field, _ in fields]\\n labels = [label for _, label in fields]\\n\\n response = HttpResponse(content_type='text/csv')\\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % (\\n str(opts).replace('.', '_')\\n )\\n\\n writer = csv.writer(response)\\n\\n if header:\\n writer.writerow(labels if labels else field_names)\\n\\n for obj in queryset:\\n writer.writerow([prep_field(request, obj, field, manyToManySep) for field in field_names])\\n return response\",\n \"def outputFunc(filename, resultList):\\n #assert len(parks) == 3\\n \\n f = open(filename, 'wt')\\n \\n try:\\n writer = csv.writer(f)\\n for i in range(len(resultList)):\\n print resultList[0]\\n writer.writerow(resultList[i])\\n \\n finally:\\n f.close()\",\n \"def export(self, out_filename='RESULT.csv'):\\n\\n query = input(\\n \\\"Enter output filename (Default = {}):\\\\n>\\\".format(out_filename))\\n # Set filename to the default value if user doesn't enter one\\n if query == '':\\n query = out_filename\\n\\n with open(query, encoding='utf-8', mode='w', newline='\\\\n') as out_file:\\n writer = csv.DictWriter(out_file, fieldnames=self.headers)\\n\\n writer.writeheader() # Write the headers to the first row\\n for record in self.records:\\n writer.writerow(record.attributes)\\n\\n print(\\\"Successfully output to {}\\\".format(query))\",\n \"def generate_csv(self, output_file):\\n try: # We are going to \\\"try\\\" something\\n csv_file = open(output_file, 'w+') # open \\\"output_file\\\" as a writable file and return a handle called \\\"csv_file\\\"\\n except OSError as err: # If something goes wrong with the open, we catch the exception\\n fatal(\\\"{0}\\\".format(err), -1) # exit with something other than 0 so the shell knows something went wrong\\n \\n writer = csv.writer(csv_file) # create a CSV writing object that's pointing at our open file handle\\n\\n writer.writerow([\\\"Question\\\",\\\"Answers\\\"]) # Let's write the top row\\n for k in self.questions.keys(): # Let's walk down the directory by key\\n # write the \\\"key\\\" (which is the question) and then let's take the list of answers and create a comma delmited list.\\n # this is likely totally wrong since you could have an answer in it that also has a comma...\\n writer.writerow([k, \\\",\\\".join(self.questions[k].answers)]) # insert a key (which is the question) and then let's take the array of \\n\\n csv_file.close() # close the csv_file file handle\",\n \"def export_as_csv(modeladmin, request, queryset):\\n opts = modeladmin.model._meta\\n field_names = set([field.name for field in opts.fields])\\n if fields:\\n fieldset = set(fields)\\n field_names = field_names & fieldset\\n elif exclude:\\n excludeset = set(exclude)\\n field_names = field_names - excludeset\\n\\n response = HttpResponse(mimetype='text/csv')\\n response['Content-Disposition'] = 'attachment; filename=%s.csv' % str(opts).replace('.', '_')\\n\\n writer = csv.DictWriter(response, fields)\\n writer.writeheader()\\n\\n for obj in queryset:\\n writer.writerow(dict(zip(fields, [getattr(obj, field) for field in fields])))\\n\\n return response\",\n \"def outputData(tname):\\n\\n table = pd.read_sql(\\\"SELECT * FROM {0}\\\".format(tname), ENGINE)\\n table.to_csv(\\\"data/{0}.csv\\\".format(tname), sep=\\\",\\\", header=True, index=False, quoting=csv.QUOTE_NONNUMERIC)\",\n \"def write_csv(self):\\n with open(paths.CSV_FILE, 'w', newline='') as csv_file:\\n writer = csv.writer(csv_file)\\n assg = AssignmentConfig().get_assignment()\\n writer.writerow([\\\"Student\\\"] + assg.get_test_list() + assg.get_programs_list() +\\n [\\\"normalised_test_score\\\"] + [\\\"normalised_prog_score\\\"] + [\\\"total\\\"] + [\\\"total_rounded\\\"])\\n\\n for (submitter, submitter_data) in sorted(self.snapshot['results'].items()):\\n total_score = submitter_data[\\\"normalised_test_score\\\"] + submitter_data[\\\"normalised_prog_score\\\"]\\n total_rounded = round(total_score * 2) / 2 # total score rounded to nearest 0.5\\n writer.writerow([submitter] +\\n [submitter_data[\\\"tests\\\"][test] for test in sorted(submitter_data[\\\"tests\\\"])] +\\n [submitter_data[\\\"progs\\\"][prog] for prog in sorted(submitter_data[\\\"progs\\\"])] +\\n [submitter_data[\\\"normalised_test_score\\\"]] +\\n [submitter_data[\\\"normalised_prog_score\\\"]] +\\n [round(total_score, 2)] +\\n [total_rounded])\",\n \"def output_columns(self) -> List[str]:\",\n \"def generate_csv(results, path):\\n csvpath = path + '/results.csv'\\n\\n if os.path.exists(csvpath):\\n os.remove(csvpath)\\n\\n csvf = open(csvpath, 'w')\\n\\n # Header\\n csvf.write(\\\"Powerpoint, Mean, Mode\\\\n\\\")\\n\\n # Results\\n for power in results:\\n mean = 0\\n count = 0\\n mode = 0\\n maxc = 0\\n for freq in results[power]:\\n freqc = results[power][freq]\\n\\n mean += freq * freqc\\n count += freqc\\n\\n if freqc > maxc:\\n mode = freq\\n\\n mean /= count\\n\\n csvf.write(f\\\"{power}, {mean}, {mode}\\\\n\\\")\\n\\n csvf.close()\",\n \"def gen_csv(self, show_headers=True, show_tags=True):\\n class TextOut:\\n \\\"\\\"\\\"Simple string output source to capture CSV\\\"\\\"\\\"\\n def __init__(self):\\n self.data = ''\\n def write(self, s):\\n self.data += s\\n def get(self):\\n data = self.data\\n self.data = ''\\n return data\\n output = TextOut()\\n writer = csv.writer(output)\\n for raw in self.gen_raw(show_headers, show_tags):\\n writer.writerow(raw)\\n yield output.get()\",\n \"def export_to_ranking_csv(request, token, project):\\n from appraise.local_settings import EXPORT_TOKEN\\n if not token == EXPORT_TOKEN:\\n return HttpResponseForbidden()\\n \\n annotation_project = get_object_or_404(Project, name=project)\\n \\n queryset = RankingResult.objects.filter(item__hit__completed=True)\\n\\n results = [u'srclang,trglang,srcIndex,doucmentId,segmentId,judgeId,' \\\\\\n 'system1Number,system1Id,system2Number,system2Id,system3Number,' \\\\\\n 'system3Id,system4Number,system4Id,system5Number,system5Id,' \\\\\\n 'system1rank,system2rank,system3rank,system4rank,system5rank']\\n \\n for result in queryset:\\n if isinstance(result, RankingResult):\\n if result.item.hit.project_set.filter(id=annotation_project.id):\\n # Current implementation of export_to_pairwise_csv() is weird.\\n # By contrast, export_to_csv() generates the right thing...\\n current_csv = result.export_to_csv()\\n if current_csv is None:\\n continue\\n results.append(current_csv)\\n \\n export_csv = u\\\"\\\\n\\\".join(results)\\n export_csv = export_csv + u\\\"\\\\n\\\"\\n return HttpResponse(export_csv, mimetype='text/plain')\",\n \"def export_csv(state, out_file=None):\\n\\n if out_file is None:\\n csvfile = sys.stdout\\n else:\\n csvfile = open(out_file, 'w')\\n\\n try:\\n writer = csv.writer(csvfile)\\n for grade in state.grades:\\n writer.writerow([grade.student_name(), grade.score(),\\n grade.breakdown(state.user_name)])\\n finally:\\n if out_file is not None:\\n csvfile.close()\",\n \"def convert_to_csv(table):\\n print(f'writing {table} to csv')\\n\\n destination = Path(__file__).parent.parent.parent / 'data' / 'results' / f'{table}.csv'\\n\\n with arcpy.da.SearchCursor(\\n in_table=table,\\n field_names=['type', 'primary_key', 'county_name', 'senate_district', 'house_district', 'census_id'],\\n where_clause='message is null'\\n ) as cursor, open(destination, 'w', encoding='utf-8', newline='') as result_file:\\n writer = csv.writer(result_file, delimiter='|', quoting=csv.QUOTE_MINIMAL)\\n\\n for row in cursor:\\n writer.writerow(row)\",\n \"def print(self):\\n df = self.gen_test()\\n # print(df)\\n df.to_csv('some_dated_file.csv', index=False)\\n return df\",\n \"def get_csv_string(self):\\n df = None\\n for d in self.data:\\n if df is None:\\n df = d.as_dataframe()\\n else:\\n df = df.append(d.as_dataframe())\\n\\n if df is None:\\n return \\\"\\\"\\n else:\\n return df.to_csv(index=False)\",\n \"def outputLevelCsv(self):\\n # extract level information from result info\\n extract_level = []\\n extract_level = [item for item in self._result_info if self._result_info[2][0:5]=='LEVEL']\\n if extract_level == []:\\n print('No Result of LEVEL')\\n return None\\n # copy need information\\n for i, item in enumerate(extract_level):\\n self._level_csv_list[i][0] = item[1]\\n self._level_csv_list[i][1] = item[2].split('-')[1]\\n self._level_csv_list[i][2] = item[2].split('-')[2]\\n self._level_csv_list[i][3] = item[4]\\n # set csv file name\\n csv_file_name = self._filename.rsplit('.', 1)[1] + '.csv'\\n # write csv\\n with open(csv_file_name, 'w') as csv_file:\\n writer = csv.writer(csv_file)\\n writer.writerows(self._level_csv_list)\",\n \"def export_to_pairwise_csv(request, token, project):\\n from appraise.local_settings import EXPORT_TOKEN\\n if not token == EXPORT_TOKEN:\\n return HttpResponseForbidden()\\n \\n annotation_project = get_object_or_404(Project, name=project)\\n \\n queryset = RankingResult.objects.filter(item__hit__completed=True)\\n\\n results = [u'srclang,trglang,srcIndex,segmentId,judgeId,' \\\\\\n 'system1Id,system1rank,system2Id,system2rank,rankingID']\\n \\n for result in queryset:\\n if isinstance(result, RankingResult):\\n if result.item.hit.project_set.filter(id=annotation_project.id):\\n current_csv = result.export_to_pairwise_csv()\\n if current_csv is None:\\n continue\\n results.append(current_csv)\\n \\n export_csv = u\\\"\\\\n\\\".join(results)\\n export_csv = export_csv + u\\\"\\\\n\\\"\\n return HttpResponse(export_csv, mimetype='text/plain')\",\n \"def generate_report(self, output_path):\\n with open(output_path, 'w', newline='', encoding=\\\"utf-8\\\") as csv_fd:\\n writer = csv.writer(csv_fd, quoting=csv.QUOTE_NONNUMERIC, doublequote=False, escapechar=\\\"\\\\\\\\\\\")\\n writer.writerow([\\\"category\\\", \\\"level\\\", \\\"description\\\", \\\"method\\\", \\\"parameter\\\", \\\"url\\\", \\\"body\\\"])\\n writer.writerows(self._vulns)\\n writer.writerows(self._anomalies)\\n writer.writerows(self._additionals)\",\n \"def csv_response(filename, header, rows):\\r\\n response = HttpResponse(mimetype='text/csv')\\r\\n response['Content-Disposition'] = 'attachment; filename={0}'.format(filename)\\r\\n writer = csv.writer(response, dialect='excel', quotechar='\\\"', quoting=csv.QUOTE_ALL)\\r\\n # In practice, there should not be non-ascii data in this query,\\r\\n # but trying to do the right thing anyway.\\r\\n encoded = [unicode(s).encode('utf-8') for s in header]\\r\\n writer.writerow(encoded)\\r\\n for row in rows:\\r\\n encoded = [unicode(s).encode('utf-8') for s in row]\\r\\n writer.writerow(encoded)\\r\\n return response\",\n \"def dwn_saved_result_csv(request):\\n source_id = request.GET.get('source_id')\\n data = []\\n objs = ExtractedRelation.objects.filter(source=source_id)\\n s = Source.objects.filter(source_id=source_id)[0]\\n for i in objs:\\n data.append((i.sentence, i.head, i.tail, i.pred_relation, i.sentiment, i.conf, s.source, i.rel_id, os.path.basename(i.ckpt)))\\n \\n df = pd.DataFrame(data, columns=['Sentence', 'Head', 'Tail', 'Predicted Relation', 'Predicted Sentiment', 'Confidence', 'Source', 'rel_id', 'Checkpoint'])\\n df.to_csv(\\\"temp/analysis_results.csv\\\", index=False)\\n \\n return FileResponse(open('temp/analysis_results.csv','rb'))\",\n \"def write_csv(self, file: str, table: str, libref: str =\\\"\\\", nosub: bool =False, dsopts: dict = None, opts: dict = None) -> 'The LOG showing the results of the step':\\n dsopts = dsopts if dsopts is not None else {}\\n opts = opts if opts is not None else {}\\n\\n code = \\\"filename x \\\\\\\"\\\"+file+\\\"\\\\\\\";\\\\n\\\"\\n code += \\\"options nosource;\\\\n\\\"\\n code += \\\"proc export data=\\\"\\n\\n if len(libref):\\n code += libref+\\\".\\\"\\n\\n code += \\\"'\\\"+table.strip()+\\\"'n \\\"+self._sb._dsopts(dsopts)+\\\" outfile=x dbms=csv replace; \\\"\\n code += self._sb._expopts(opts)+\\\" run\\\\n;\\\"\\n code += \\\"options source;\\\\n\\\"\\n\\n if nosub:\\n print(code)\\n else:\\n ll = self.submit(code, \\\"text\\\")\\n return ll['LOG']\",\n \"def csvprint(self, data):\\n import csv\\n import sys\\n # self._assert(data) CSV data row lenght can vary\\n data = self._render(data) # make elements ascii\\n writer = csv.writer(sys.stdout, delimiter=',',\\n quotechar='\\\"', \\n quoting=csv.QUOTE_MINIMAL,\\n lineterminator=\\\"\\\\n\\\")\\n for row in data: writer.writerow(row)\",\n \"def write_csv(self, outfile, collapse_orders=False, show_age=False):\\r\\n # Write header row\\r\\n outfile.write(self.get_csv_header(collapse_orders, show_age).encode())\\r\\n\\r\\n # Write content\\r\\n for x in self.records:\\r\\n x.write_csv(outfile, collapse_orders, show_age)\",\n \"def handle_output(all_rows, opts):\\n for dev, rows in all_rows.iteritems():\\n\\n if opts.csv:\\n writer = csv.writer(sys.stdout)\\n for row in rows:\\n writer.writerow([dev] + row)\\n elif opts.dotty:\\n continue\\n elif opts.sqldb:\\n write_sqldb(opts.sqldb, dev, rows)\\n else:\\n print 'DEVICE: {}'.format(dev)\\n print_table(rows)\",\n \"def save_csv(connection, query, columns, name):\\n\\n try:\\n df = pd.read_sql(query, connection, columns=columns)\\n df.to_csv(name, index=False)\\n except Exception as ex:\\n print(type(ex))\\n print(ex)\",\n \"def write_results_to_disk(self, result_path,results):\\n with open(result_path+\\\"/results.txt\\\",\\\"w+\\\") as out:\\n\\n for query_num in results:\\n for doc_num in results[query_num]:\\n out.write(str(query_num)+\\\" 0 \\\"+doc_num+\\\" 1 42.38 mt\\\\n\\\")\\n out.close()\",\n \"def construct_csv(cursor):\\n header, data = construct_list(cursor)\\n # python 2 and 3 handle writing files differently\\n if sys.version_info[0] <= 2:\\n output = io.BytesIO()\\n else:\\n output = io.StringIO()\\n writer = csv.writer(output)\\n\\n writer.writerow(header)\\n for row in data:\\n writer.writerow(row)\\n\\n return output.getvalue()\",\n \"def export(self,**kwargs):\\n \\n # import pdb;pdb.set_trace()\\n \\n # provide for case where recs are set extenally\\n if not self.recs:\\n self.select_recs(**kwargs)\\n if self.recs:\\n if self.export_file_name:\\n filename = self.export_file_name\\n else:\\n filename = \\\"{table_name}_report_{datetime}.csv\\\".format(\\n table_name = self.table.display_name,\\n datetime = date_to_string(local_datetime_now(),'iso_datetime'),\\n ).replace(' ','_').lower()\\n \\n if not self.export_fields:\\n # include all fields by default\\n self.export_fields = self._set_default_list_fields(include_all=True).copy()\\n\\n self.set_list_fields(self.export_fields)\\n \\n \\n if self.export_template:\\n result = render_template(self.export_template, data=self)\\n else:\\n # add a descriptive title row\\n if self.export_title:\\n result = self.export_title.strip() + '\\\\n'\\n else:\\n result = \\\"Export of table {} as of {}\\\\n\\\".format(self.table.table_name,excel_date_and_time_string(local_datetime_now()))\\n \\n result += ','.join([x['label'] for x in self.export_fields]) + '\\\\n'\\n for rec in self.recs:\\n rec_row = []\\n for field in self.export_fields:\\n data = rec.__getattribute__(field['name'])\\n if field['type'].upper() == \\\"DATE\\\":\\n data = local_date_string(data)\\n elif field['type'].upper() == \\\"DATETIME\\\":\\n data = excel_date_and_time_string(data)\\n else:\\n # just text\\n data = str(data).strip()\\n \\n # replace double quotes with double-double quotes\\n data = data.replace('\\\"','\\\"\\\"') #double up on double quotes\\n \\n if \\\",\\\" in data:\\n # if any commas, wrap in quotes\\n data = '\\\"' + data + '\\\"'\\n \\n #replace returns\\n data = data.replace('\\\\r\\\\n',' -crnl- ')\\n data = data.replace('\\\\n',' -nl- ')\\n data = data.replace('\\\\r',' -rtn- ')\\n\\n rec_row.append(data)\\n \\n result += ','.join([str(x) for x in rec_row]) + '\\\\n'\\n \\n return DataStreamer(result,filename,'text/csv').send()\\n \\n self.result_text = \\\"No records selected\\\"\\n self.success = False\\n \\n flash(self.result_text)\\n return self.list(**kwargs)\",\n \"def writeCSV():\\n final_list = get_final_list()\\n path_to_csv_File = 'system_metrics.csv'\\n\\n csv_file = open(path_to_csv_File, 'w+', newline='', encoding=\\\"utf8\\\")\\n csv_file_writer = csv.writer(csv_file, delimiter=',')\\n\\n csv_file_writer.writerow(['Subscription', 'Resource', 'MetricType',\\n 'Timestamp', 'Unit', 'Minimum', 'Maximum', 'Average'])\\n\\n for item in final_list:\\n csv_file_writer.writerow([item['subscription'], item['resource'], item['metricType'], item['timestamp'],\\n item['unit'], item['minimum'], item['maximum'], item['average']])\\n\\n print('Output written successfully!!')\",\n \"def export(request):\\n\\n if not request.user.is_authenticated():\\n return HttpResponseRedirect('/login/?next=%s' % request.path)\\n\\n filename = 'export-inscrits%s.csv' % date.today().strftime(\\\"%y-%m-%d\\\")\\n\\n person_list = Person.objects.all()\\n\\n table = ExportPersonTable(person_list)\\n table.order_by = request.GET.get(\\\"sort\\\",'last_name')\\n\\n response = HttpResponse(mimetype='text/csv')\\n response['Content-Disposition'] = 'attachment; filename=%s' % filename\\n writer = csv.writer(response)\\n # Write headers to CSV file\\n headers = []\\n for column in table.columns:\\n headers.append(column.header.encode('utf8'))\\n writer.writerow(headers)\\n\\n # Write data to CSV file\\n for obj in table.rows:\\n row = []\\n for value in obj:\\n row.append(value.encode('utf8'))\\n writer.writerow(row)\\n\\n # Return CSV file to browser as download\\n return response\",\n \"def _csv(content):\\n response = _data_frame(content).to_csv(index=False)\\n return response\",\n \"def _pipe(content):\\n response = _data_frame(content).to_csv(index=False,sep='|')\\n return response\",\n \"def write_csv(self, filelike):\\r\\n items = self.rows()\\r\\n writer = unicodecsv.writer(filelike, encoding=\\\"utf-8\\\")\\r\\n writer.writerow(self.header())\\r\\n for item in items:\\r\\n writer.writerow(item)\",\n \"def export_users(_request):\\n query = models.UserProfile.all().order('email')\\n rows = []\\n for user in query:\\n is_superuser = 0\\n if user.is_superuser:\\n is_superuser = 1\\n rows.append('%s,%s\\\\n' % (user.email, is_superuser))\\n\\n response = http.HttpResponse(''.join(rows), mimetype='text/csv')\\n response['Content-Disposition'] = 'attachment; filename=users.csv'\\n return response\",\n \"def write_to_csv(results, filename):\\n fieldnames = ('datetime_utc', 'distance_au',\\n 'velocity_km_s', 'designation', 'name',\\n 'diameter_km', 'potentially_hazardous')\\n\\n with open(filename, 'w') as results_file:\\n writer = csv.DictWriter(results_file, fieldnames)\\n writer.writeheader()\\n for result in results:\\n resultsDict = {fieldnames[0]: result.time,\\n fieldnames[1]: result.distance,\\n fieldnames[2]: result.velocity,\\n fieldnames[3]: result._designation,\\n fieldnames[4]: result.neo.name,\\n fieldnames[5]: result.neo.diameter,\\n fieldnames[6]: result.neo.hazardous}\\n writer.writerow(resultsDict)\",\n \"def output_results(self, model, limit):\\n out = []\\n for key in self.results[model].keys():\\n qId = key\\n count = 1\\n sorted_docs = sorted(self.results[model][key].items(), key=operator.itemgetter(1), reverse=True)[:limit] \\n for val in sorted_docs:\\n dId = val[0]\\n dScore = val[1]\\n dRank = count\\n out.append(str(qId) + \\\" \\\" + \\\"Q0\\\" + \\\" \\\" + str(dId) + \\\" \\\" + str(dRank) + \\\" \\\" + str(dScore) + \\\" \\\" + \\\"Exp\\\")\\n count += 1\\n return out\",\n \"def export_sensor_data_to_csv(self):\\n df = pd.read_sql('SELECT * FROM sensor_data', self.conn)\\n df.to_csv('output/sensor_data.csv', index=False)\",\n \"def write_results(self, results, fname, folder=None):\\n folder = folder or self.output_dir\\n\\n if not os.path.exists(folder):\\n logger.info(\\\"creating {} (did not exist)\\\".format(folder))\\n os.makedirs(folder)\\n\\n out_file = os.path.join(folder, fname)\\n logger.info(\\\"writing to {}\\\".format(out_file))\\n df = pd.DataFrame(results)\\n df.to_csv(out_file, index=False)\\n \\n return None\",\n \"def to_csv(self):\\n if not self._fitted:\\n self.fit()\\n #self._message(\\\"Saving results into a csv (comma separated values) file.\\\")\\n v=np.array([list(self.initialConcentration.values()),\\n list(self.fitting_error.values()),\\n list(self.k.values()),\\n list(self.Fb.values()),\\n list(self.slope.values())]).T\\n k=list(self.initialConcentration.keys())\\n d=pd.DataFrame(v,columns=['Initial Concentration','Fitting Error','k','Fb','Slope'],index=k)\\n fn=get_valid_fname(self.ID)\\n self.csvname=\\\"%s_initial_concentrations.csv\\\"%(fn)\\n self.fullcsvname=\\\"%s/%s_initial_concentrations.csv\\\"%(self.info['resultsdir'],fn)\\n self.info['csvname_initialConcentration']=self.csvname\\n print(self.csvname)\\n d.to_csv('%s/%s'%(self.info['resultsdir'],self.csvname))\",\n \"def export_csv(table_name, out_file):\\n con = sqlite3.connect(dbname)\\n import pandas as pd\\n\\n df = pd.read_sql_query(f\\\"SELECT * FROM {table_name}\\\", con)\\n df.to_csv(out_file, index=False)\",\n \"def print_csv_format(results):\\n assert isinstance(results, OrderedDict), results # unordered results cannot be properly printed\\n for task, res in results.items():\\n # Don't print \\\"AP-category\\\" metrics since they are usually not tracked.\\n important_res = [(k, v) for k, v in res.items() if \\\"-\\\" not in k]\\n print(\\\"copypaste: Task: {}\\\".format(task))\\n print(\\\"copypaste: \\\" + \\\",\\\".join([k[0] for k in important_res]))\\n print(\\\"copypaste: \\\" + \\\",\\\".join([\\\"{0:.4f}\\\".format(k[1]) for k in important_res]))\",\n \"def exportEvaluation(self, results, url):\\r\\n # research\\r\\n profprint()\\r\\n if not os.path.exists(url):\\r\\n print \\\"creating new results file: \\\",url\\r\\n open(url, 'w').close()\\r\\n myfile = open(url, 'a')\\r\\n\\r\\n wr = csv.writer(myfile)\\r\\n r = numpy.array(results)\\r\\n if len(r.shape) == 1:\\r\\n wr.writerow(results)\\r\\n else:\\r\\n wr.writerows(results)\",\n \"def generate_csv(table, header):\\n with open(\\\"%s.csv\\\" % header, \\\"w\\\") as csvfile:\\n for i in range(len(table)):\\n for j in range(len(table[i])):\\n if j != len(table[i])-1:\\n tmp = table[i][j] + \\\",\\\"\\n else:\\n tmp = table[i][j] + \\\"\\\\n\\\"\\n csvfile.write(tmp)\",\n \"def save_results(self):\\n results = pd.concat([\\n pd.DataFrame(self.IDs.cpu().numpy(), columns= ['ID']), \\n pd.DataFrame(self.predicted_labels.cpu().numpy(), columns= ['predicted_label']),\\n pd.DataFrame(self.correct_predictions.cpu().numpy(), columns= ['correct_prediction']),\\n pd.DataFrame(self.epistemic_uncertainty.cpu().numpy(), columns= ['epistemic_uncertainty']), \\n pd.DataFrame(self.aleatoric_uncertainty.cpu().numpy(), columns= ['aleatoric_uncertainty']), \\n pd.DataFrame(self.total_uncertainty.cpu().numpy(), columns= ['total_uncertainty']), \\n ], axis=1)\\n\\n create_results_directory()\\n results.to_csv('results/{}_{}_results.csv'.format(self.__class__.__name__, datetime.datetime.now().replace(microsecond=0).isoformat()), index=False)\",\n \"def downloadResponse(request, formcode=None):\\n if formcode !=None:\\n response = HttpResponse(content_type='text/csv')\\n responses = Response.objects.filter(form_id=formcode)\\n writer = csv.writer(response)\\n writer.writerow(['User', 'Submit Date', 'Answer1', 'Answer2', 'Answer3'])\\n for r in responses:\\n user = User.objects.get(id=r.user_id)\\n writer.writerow([user, r.submitDate, r.answer1 ,r.answer2 , r.answer3])\\n\\n response['Content-Disposition'] = 'attachment; filename=\\\"response.csv\\\"'\\n return response \\n return render(request, 'download.html')\",\n \"def create_file_output(self, results):\\n for key, value in results.table_output.items():\\n name_timestamp = key.split('&')\\n _name = name_timestamp[0]\\n timestamp = name_timestamp[1]\\n file_name = output_file_prefix + \\\"-\\\" + _name + \\\".csv\\\"\\n if file_name not in self.file_creation_set:\\n self._header_written = False\\n self.file_creation_set.update([file_name])\\n for row in value:\\n with open(file_name, 'a+') as file_to_write:\\n row.update({'Timestamp': timestamp})\\n _keys = row.keys()\\n file_output = csv.DictWriter(file_to_write, _keys)\\n if not self._header_written:\\n file_output.writeheader()\\n self._header_written = True\\n file_output.writerow(row)\\n file_to_write.close()\\n return results\",\n \"def output(items, headers, outputFile):\\n\\tdictToValues = lambda d: \\\\\\n\\t\\tmap(lambda h: d.get(h, ''), headers)\\n\\n\\treturn writeCsv(outputFile, map(dictToValues, items))\",\n \"def csv(self, section=\\\"main\\\", column_headers=True):\\n table_end = \\\"\\\\r\\\\n\\\\r\\\\n\\\\r\\\\n\\\"\\n table_head_pos = self.header_dictionary[section]\\n table_end_pos = self.raw_data[table_head_pos:].find(table_end)\\n if table_end_pos == -1:\\n table_end_pos = len(self.raw_data)\\n else:\\n table_end_pos += table_head_pos\\n if column_headers:\\n a = \\\",\\\".join(self.columns()) + \\\"\\\\n\\\"\\n else:\\n a = \\\"\\\"\\n return a + self.raw_data[table_head_pos:table_end_pos].replace(\\\"\\\\t\\\",\\\",\\\").replace(\\\"\\\\r\\\",\\\"\\\")\",\n \"def generate_csv(inf, outf):\\n o = csv.writer(outf)\\n o.writerow(COLUMNS)\\n for row in reformat_data(inf):\\n o.writerow([inf.name] + row)\",\n \"def querySciDB(cmd):\\n #startT = benchmark.startTimer(cmd)\\n\\n proc = subprocess.Popen([\\\"/opt/scidb/12.10/bin/iquery\\\", \\\"-o\\\", \\\"csv+\\\", \\\"-a\\\", \\\"-q\\\", cmd], stdout = subprocess.PIPE)\\n out,err = proc.communicate()\\n\\n lines = out.split(\\\"\\\\n\\\")\\n # first line is header, last line is empty\\n header = lines[0].split(\\\",\\\")\\n rows = [line.split(\\\",\\\") for line in lines[1:-1]]\\n #benchmark.endTimer(cmd, startT)\\n\\n return header, rows\",\n \"def write_to_csv(self, output_dir, delimiter, include_language, filename=None):\\n\\n if filename is not None:\\n self.filename = filename\\n\\n if len(self.values) == 0:\\n logger.info(\\\"Nothing to export.\\\")\\n return\\n\\n if not os.path.exists(output_dir):\\n os.makedirs(output_dir)\\n\\n file_path = os.path.join(output_dir, self.filename)\\n\\n # write search results to UTF8-encoded CSV file (see also http://stackoverflow.com/a/844443)\\n with codecs.open(file_path, 'w', encoding='utf8') as fp:\\n logger.info('Exporting search results to ' + file_path + '...')\\n writer = csv.writer(fp, delimiter=delimiter)\\n\\n column_names = SearchResult.get_column_names(include_language)\\n\\n # write header of CSV file\\n writer.writerow(column_names)\\n\\n count = 0\\n try:\\n for row in self.get_rows(include_language):\\n if len(row) == len(column_names):\\n writer.writerow(row)\\n count = count + 1\\n else:\\n raise IllegalArgumentError(\\n str(abs(len(column_names) - len(row))) + ' parameter(s) is/are missing for \\\"'\\n + str(row) + '\\\"')\\n\\n except UnicodeEncodeError:\\n logger.error('Encoding error while writing data for: ' + str(row))\\n\\n logger.info(str(count) + ' search results have been exported.')\",\n \"def save_results(self, results, file_name, file_type):\\n if file_type == 'csv':\\n csv_filename = '{}.csv'.format(file_name)\\n\\n with open(csv_filename, 'w', newline='') as file:\\n writer = csv.writer(file)\\n writer.writerows(results)\",\n \"def write_csv(self, outputfile):\\n d = csv.writer(outputfile, quoting=csv.QUOTE_ALL)\\n for row in self.translations.iteritems():\\n d.writerow(row)\",\n \"def write_output(self) -> None:\\n self.home.round(2).to_csv(var.indicators_base_cumsum + \\\"home_\\\" + str(self.year) + \\\".csv\\\")\\n self.away.round(2).to_csv(var.indicators_base_cumsum + \\\"away_\\\" + str(self.year) + \\\".csv\\\")\",\n \"def csv_response(rows, filename=\\\"export.csv\\\"):\\n\\t# Unfortunately Flask doesn't let you output response as an IO Stream, so you have\\n\\t# buffer the entire response to a string first.\\n\\tsi = StringIO.StringIO()\\n\\tcw = csv.writer(si)\\n\\tcw.writerow(header)\\n\\tfor row in rows:\\n\\t\\tcw.writerow()\\n\\toutput = make_response(si.getvalue())\\n\\toutput.headers[\\\"Content-Disposition\\\"] = \\\"attachment; filename=%s\\\" % filename\\n\\toutput.headers[\\\"Content-type\\\"] = \\\"text/csv\\\"\\n\\treturn output\",\n \"def export_data(fp, app_name):\\n from otree.views.admin import get_display_table_rows\\n colnames, rows = get_display_table_rows(\\n app_name, for_export=True, subsession_pk=None)\\n colnames = ['{}.{}'.format(k, v) for k, v in colnames]\\n writer = csv.writer(fp)\\n writer.writerows([colnames])\\n writer.writerows(rows)\",\n \"def list_apiscout_csv(self, destination):\\n res = self.__make_api_call('list/apiscout/csv', raw=True)\\n with open(destination, \\\"wb\\\") as csvfile:\\n csvfile.write(res)\",\n \"def write_results(filename):\\n \\n with open(filename, 'w', newline='') as fn:\\n writer = csv.writer(fn)\\n writer.writerows([('id', 'number_of_places_available'), ''])\\n pair: Point = yield # where x is the user id and y is the number of places available\\n while pair is not None:\\n writer.writerow(pair)\\n pair = yield\",\n \"def df_to_csvtxt(df, out_fields = ['top', 'Comp formation']): \\n header = 'top, Comp formation\\\\n'\\n csv_txt = ''\\n csv_txt += csv_txt + header\\n for i, row in df.iterrows():\\n csv_txt = csv_txt + str(row['MD']) + ', ' + row['PICK'] + '\\\\n'\\n return csv_txt\",\n \"def get_csv_logs(how_many_rows: int) -> str:\\n db = get_db()\\n counts = db.get_newest_counts(how_many_rows, hc_db.NewestSort.SUBMIT_TIME)\\n counts_as_string = \\\"\\\"\\n for count in counts:\\n username = db.get_user_by_id(count[\\\"user_id\\\"])\\n # Don't error out when there are headcounts by users who no longer exist\\n if username is None:\\n username = \\\"(Deleted user; ID %s)\\\" % (count[\\\"user_id\\\"],)\\n else:\\n username = username[\\\"username\\\"]\\n room_rows = db.get_roomdata_for_count_id(count[\\\"id\\\"])\\n counts_as_string += username + \\\",\\\"\\n counts_as_string += count[\\\"submit_time\\\"] + \\\",\\\" + count[\\\"entered_time\\\"] + \\\",\\\"\\n room_counts = {}\\n for row in room_rows:\\n room_counts[row[\\\"room\\\"]] = row[\\\"people_count\\\"]\\n room_counts = OrderedDict(sorted(room_counts.items()))\\n counts_as_string += \\\",\\\".join([str(x) for x in room_counts.values()])\\n counts_as_string += \\\"\\\\n\\\"\\n return counts_as_string\",\n \"def write_csv_fulltext(records, output_file):\\n with open(output_file, 'a') as csv_out:\\n\\n csv_writer = csv.writer(csv_out)\\n csv_writer.writerow(['PMCID', 'Title', 'Abstract'])\\n\\n for record in records['PubmedArticle']:\\n pmid_text = record['MedlineCitation']['PMCID']\\n title_text = record['MedlineCitation']['Article']['ArticleTitle']\\n abs_text = get_abs_text(record)\\n csv_writer.writerow([pmid_text, title_text, abs_text])\",\n \"def write_rating_data():\\n with open('outward.csv', 'w') as f:\\n out = csv.writer(f)\\n\\n for item in Rating.query.filter(Rating.score != None).all():\\n out.writerow([item.user_id, item.book_id, item.score])\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7392405","0.70663726","0.7028599","0.69381297","0.690984","0.6848239","0.679453","0.67345744","0.6721","0.667645","0.6661048","0.6578225","0.6552651","0.65504265","0.6536412","0.6536164","0.6484346","0.6483709","0.64407593","0.6437607","0.64326495","0.6389281","0.6377862","0.6367268","0.6353683","0.63533413","0.63429064","0.634215","0.63244593","0.63231","0.6321816","0.63172185","0.6308071","0.6307505","0.6270999","0.6270568","0.62687236","0.6261964","0.6260759","0.62346584","0.62212896","0.6221203","0.62205344","0.6219477","0.6199692","0.61952007","0.6195036","0.6183014","0.61582386","0.61432636","0.614322","0.6138402","0.6137936","0.613672","0.61329085","0.61159617","0.61142343","0.6110549","0.61047626","0.6094154","0.60874444","0.60734695","0.6065094","0.605294","0.6039751","0.603734","0.6035815","0.6031159","0.60285896","0.60237134","0.6012543","0.60017985","0.5993288","0.59919894","0.59896165","0.59853166","0.5979829","0.59795356","0.59690213","0.596884","0.59553725","0.5950506","0.5950338","0.59498453","0.594728","0.59463215","0.59403056","0.5939046","0.5938395","0.5931308","0.59221196","0.59211457","0.59210914","0.59172606","0.591581","0.5910591","0.59049714","0.5904526","0.5902979","0.59006166","0.5896554"],"string":"[\n \"0.7392405\",\n \"0.70663726\",\n \"0.7028599\",\n \"0.69381297\",\n \"0.690984\",\n \"0.6848239\",\n \"0.679453\",\n \"0.67345744\",\n \"0.6721\",\n \"0.667645\",\n \"0.6661048\",\n \"0.6578225\",\n \"0.6552651\",\n \"0.65504265\",\n \"0.6536412\",\n \"0.6536164\",\n \"0.6484346\",\n \"0.6483709\",\n \"0.64407593\",\n \"0.6437607\",\n \"0.64326495\",\n \"0.6389281\",\n \"0.6377862\",\n \"0.6367268\",\n \"0.6353683\",\n \"0.63533413\",\n \"0.63429064\",\n \"0.634215\",\n \"0.63244593\",\n \"0.63231\",\n \"0.6321816\",\n \"0.63172185\",\n \"0.6308071\",\n \"0.6307505\",\n \"0.6270999\",\n \"0.6270568\",\n \"0.62687236\",\n \"0.6261964\",\n \"0.6260759\",\n \"0.62346584\",\n \"0.62212896\",\n \"0.6221203\",\n \"0.62205344\",\n \"0.6219477\",\n \"0.6199692\",\n \"0.61952007\",\n \"0.6195036\",\n \"0.6183014\",\n \"0.61582386\",\n \"0.61432636\",\n \"0.614322\",\n \"0.6138402\",\n \"0.6137936\",\n \"0.613672\",\n \"0.61329085\",\n \"0.61159617\",\n \"0.61142343\",\n \"0.6110549\",\n \"0.61047626\",\n \"0.6094154\",\n \"0.60874444\",\n \"0.60734695\",\n \"0.6065094\",\n \"0.605294\",\n \"0.6039751\",\n \"0.603734\",\n \"0.6035815\",\n \"0.6031159\",\n \"0.60285896\",\n \"0.60237134\",\n \"0.6012543\",\n \"0.60017985\",\n \"0.5993288\",\n \"0.59919894\",\n \"0.59896165\",\n \"0.59853166\",\n \"0.5979829\",\n \"0.59795356\",\n \"0.59690213\",\n \"0.596884\",\n \"0.59553725\",\n \"0.5950506\",\n \"0.5950338\",\n \"0.59498453\",\n \"0.594728\",\n \"0.59463215\",\n \"0.59403056\",\n \"0.5939046\",\n \"0.5938395\",\n \"0.5931308\",\n \"0.59221196\",\n \"0.59211457\",\n \"0.59210914\",\n \"0.59172606\",\n \"0.591581\",\n \"0.5910591\",\n \"0.59049714\",\n \"0.5904526\",\n \"0.5902979\",\n \"0.59006166\",\n \"0.5896554\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13087,"cells":{"query":{"kind":"string","value":"Send the query to the database and render the results as requested"},"document":{"kind":"string","value":"def query(args):\n dbh = despydb.DesDbi(args.service, args.section)\n if args.query not in \"-+\":\n do1Query(dbh, args.query, args)\n elif args.query == \"-\":\n line = sys.stdin.readline()\n while line:\n line = line.strip()\n if not line or line.startswith(\"#\"):\n pass\n else:\n do1Query(dbh, line, args)\n line = sys.stdin.readline()\n else: #if args.query == \"+\":\n lines = sys.stdin.read()\n do1Query(dbh, lines, args)\n dbh.close()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def execute_query(self):\n try:\n # get query and templates\n query = self.request.data.get(\"query\", None)\n templates = self.request.data.get(\"templates\", \"[]\")\n registries = self.get_registries()\n order_by_field = self.request.data.get(\"order_by_field\", \"\")\n\n if order_by_field:\n order_by_field = order_by_field.split(\",\")\n\n if query is None:\n content = {\"message\": \"Query should be passed in parameter.\"}\n return Response(content, status=status.HTTP_400_BAD_REQUEST)\n\n # prepare query\n raw_query = self.build_query(query, templates, registries)\n # execute query\n data_list = self.execute_json_query(raw_query, order_by_field)\n # build and return response\n return self.build_response(data_list)\n\n except Exception as api_exception:\n content = {\"message\": str(api_exception)}\n return Response(\n content, status=status.HTTP_500_INTERNAL_SERVER_ERROR\n )","def query(self, query):","def fluff_results():\n # we get carriage returns from the form somehow. so split on them and join via\n # regular newline. add a newline to avoid the annoying newline-at-end-of-file error.\n sql = sql_decode(request.args[\"sql\"]).strip()\n sql = \"\\n\".join(sql.splitlines()) + \"\\n\"\n\n dialect = request.args[\"dialect\"]\n linted = lint(sql, dialect=dialect)\n fixed_sql = \"\"\n\n # Fix can fail badly if linting fails so wrap in a try/except.\n # See: https://github.com/sqlfluff/sqlfluff-online/issues/25\n try:\n fixed_sql = fix(sql, dialect=dialect)\n except Exception:\n pass\n\n return render_template(\n \"index.html\",\n results=True,\n sql=sql,\n dialect=dialect,\n lint_errors=linted,\n fixed_sql=fixed_sql,\n )","def query(self):\n pass","def query(self):","def vis_results():\n try:\n uuid = session['uuid']\n dm = DatabaseManager()\n genes, diseases, uuiddb, query, genpanel, date \\\n = dm.retreieve_zoekopdracht(uuid)\n\n return render_template(\"results.html\", genes=genes, diseases=diseases,\n uuid=uuid, query=query, genpanel=genpanel,\n date=date)\n except KeyError:\n flash(\"Please run a search or retrieve one from the archived \"\n \"searches before visiting this page!\")\n return redirect(url_for('search'))","def results():\n\n queryName = request.form['query']\n queryStars = request.form['stars']\n \n datasource = DataSource()\n listOfRestaurantNames = datasource.searchRestaurantsByNameAndMinimumStars(queryName, queryStars)\n restaurants = datasource.generateRestaurantObjects(listOfRestaurantNames[:15])\n\n return render_template('results.html', restaurants=restaurants)","def show_results(ninja_id):\n query = \"SELECT \" # get the ninja based on ninja id\n data = {} # ninja id\n mysql = # connect to mysql \n ninja = mysql.query_db(query, data)\n return render_template ('submitted_info.html', ninja = ninja) # [{ninja_data: \"stuff\"}]","def _run_query(self):","def search_results(request):\n #key\n\n user_input = request.GET['q']\n\n people_objs = Person.objects.filter(Q(last__contains=user_input) | Q(\n first__contains=user_input))\n document_objs = Document.objects.filter(title__contains=user_input)\n folder_objs = Folder.objects.filter(full__contains=user_input)\n organization_objs = Organization.objects.filter(Q(name__contains=user_input)|Q(\n location__contains=user_input))\n obj_dict = {\n 'people_objs': people_objs,\n 'document_objs': document_objs,\n 'folder_objs': folder_objs,\n 'organization_objs': organization_objs,\n 'query': user_input,\n }\n response = render(request, 'search_results.jinja2', obj_dict)\n return response","def query(self, **kwargs):","def make_query(self):","def handleQuery(self,query):\n results = None\n return results","def submitQuery(self):\r\n #open connection, retrieve cursor and execute query\r\n\r\n try:\r\n connection = pymysql.connect(host='localhost', user='root',\r\n password='user', db='bank',\r\n charset='utf8mb4',\r\n cursorclass=pymysql.cursors.DictCursor)\r\n\r\n cursor = connection.cursor()\r\n cursor.execute(self.query.get())\r\n except (pymysql.OperationalError):\r\n errorMessage = \"Error\"\r\n showerror(\"Error\", errorMessage)\r\n return\r\n\r\n else: #obtain user requested info\r\n data = cursor.fetchall()\r\n fields = cursor.description\r\n cursor.close()\r\n connection.close()\r\n\r\n # clear results of last query\r\n self.panes.destroy()\r\n self.panes = Pmw.PanedWidget(self.frame.interior(),\r\n orient = \"vertical\")\r\n self.panes.pack(expand = YES, fill = BOTH)\r\n\r\n # create panel and label for each field\r\n for item in fields:\r\n## print(item)\r\n self.panes.add(item[0])\r\n label = Label(self.panes.pane(item[0]),\r\n text = item[0], relief = RAISED)\r\n label.pack(fill = X)\r\n\r\n # enter results into panes using labels\r\n for entry in data:\r\n\r\n for i in range(len(entry)):\r\n## print(entry)\r\n label = Label(self.panes.pane(fields[i][0]),\r\n text = entry[fields[i][0]], anchor = W, \r\n relief = GROOVE, bg = \"white\")\r\n label.pack(fill = X)\r\n\r\n self.panes.setnaturalsize()","def postQuery(self):\n pass","def respond():\n projects = db.execute(\"SELECT * FROM projects\")\n return render_template(\"respond.html\", projects=projects)","def update_results(self):\n try:\n results = self.shared_state[\"active_collection\"].query_source(\n self.query_str\n )\n self.results = results\n\n except Exception:\n self.results = {}\n self.status_textcontrol.text = \"(invalid query)\"\n else:\n self.formatted_results = self._apply_default_format(self.results)\n self.results_textcontrol.text = self.formatted_results\n self.index = 0\n self.status_textcontrol.text = (\n f\"showing {len(self.results)} of \"\n f\"{self.shared_state['active_collection'].df.shape[0]} records \"\n f\"syntax: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-string-query.html#query-string-syntax)\"\n )","def render_POST(self, request, query=None):\n # make a parser and parse the request\n parser = qp.QueryParser(request)\n if not query: query = request.content.read() \n try: \n # run the query locally\n d = parser.runquery(self.db, query)\n except Exception, e:\n log.err(\"Failing query: \" + str(query))\n log.err()\n setResponseCode(request, e, 400)\n return str(e)\n else:\n # and send the reply\n request.setHeader('Content-type', 'application/json')\n\n if not query.strip().startswith('apply'):\n # apply streams the output out itself\n d.addCallback(lambda reply: (request, reply))\n d.addCallback(self.send_reply)\n d.addErrback(lambda x: self.send_error(request, x))\n return server.NOT_DONE_YET","def db_results(self, query):\n try:\n # Connect to database\n db = psycopg2.connect(\"dbname=news\")\n c = db.cursor()\n # executing query and getting all results\n c.execute(query)\n db_res = c.fetchall()\n # closing connection\n db.close()\n return db_res\n except Error:\n print (\"Error when attempting to connect to db\")","def render_result():\n\n action = request.form['action']\n session['visibility'] = request.form['vis'] == 'pub'\n if(action == 'list'):\n resp = utils.get_posts(g.graph,session['visibility'],session['page']['id'])\n return render_template('display_posts.html', data = resp, next = resp['next'])\n elif (action == 'add'): \n return render_template('input_post.html')\n else:\n return redirect(url_for('error')) #TODO: add this page","def _run_queries(self, persist):\n self._mark_start()\n self._run_query()\n\n # Check if we want to keep going.\n if not persist:\n self._compile_results()\n return\n\n # Get the rest of the content.\n while not self._done():\n self._run_query()\n\n # Create the actual statements.\n self._compile_results()\n\n # This is end of the loop, one way or another. Restore logging if it\n # was redirected.\n request_logger.unquiet()\n util_logger.unquiet()\n return","def query(self) -> None:\n raise NotImplementedError()","def execute():\n # print('Wow')\n result = gui.controller.main('execute')\n print(result)\n\n return render_template('results.html', data=json.dumps(result))","def __call__(self, query=None, limit=1, uid=None):\n\n # Query prefix\n prefix = \"select id, score, questionuser, question, tags, date, answeruser, object answer, reference from txtai where\"\n\n if uid is not None:\n # ID query\n query = f\"{prefix} id = '{uid}'\"\n elif self.embeddings.scoring:\n # Use custom tokenizer for word vector models\n query = Tokenizer.tokenize(query)\n\n # Run search and build id query\n result = self.embeddings.search(query, 1)[0] if query else {}\n query = f\"\"\"\n select id, {result.get('score')} score, questionuser, question, tags, date, answeruser, object answer, reference\n from txtai\n where id = '{result.get('id')}'\n \"\"\"\n else:\n # Default similar clause query\n query = f\"{prefix} similar('{query}')\"\n\n # Render results\n for result in self.embeddings.search(query, limit):\n # Show result\n self.result(result, limit)\n\n self.console.print()","def query(self):\r\n records = self.input()\r\n if self.to_investigate:\r\n records = self.investigate(records)\r\n post.log.info(\"Caching {} records for {}\".format(len(records), self.name))\r\n self.cache_records(records)","def run_query(self):\n return _run_query(self.query)","def execute_query():\n start_time = time.time()\n\n queries = request.json[\"queries\"]\n random_command = request.json[\"random_command\"]\n\n \"\"\" Running the queries against the pre-loaded index. \"\"\"\n output_dict = runner.run_queries(queries, random_command)\n\n \"\"\" Dumping the results to a JSON file. \"\"\"\n with open(output_location, 'w') as fp:\n json.dump(output_dict, fp)\n\n response = {\n \"Response\": output_dict,\n \"time_taken\": str(time.time() - start_time),\n \"username_hash\": username_hash\n }\n return flask.jsonify(response)","def search(self, query):","def getresult(request):\r\n\r\n form = forms.SearchForm(request.POST)\r\n form.find_minmax_criteria(request.POST)\r\n\r\n if form.is_valid():\r\n\r\n headers, results = search.query(form.to_criteria(), form.cleaned_data['sector'], form.cleaned_data['exchange'], form.cleaned_data['show_result'])\r\n\r\n # show result in response\r\n return render_to_response('search/result.html', {\r\n 'headers': headers,\r\n 'results': results\r\n })\r\n\r\n else:\r\n # show error message in response\r\n return render_to_response('search/result-error.html', {\r\n 'message': 'Please enter details correctly.',\r\n 'form': form\r\n })","def search():\n query = input('Please enter your search query\\n')\n # For now, we will just print the whole database\n #db_actions.display()\n db_actions.search(query)","def index():\n rows=db.execute(\"SELECT symbol, SUM(transactions) as amount FROM record WHERE userID=? GROUP BY symbol HAVING transactions\",session[\"user_id\"])\n cash=db.execute(\"SELECT cash FROM users WHERE id=?\",session[\"user_id\"])\n cash_=cash[0][\"cash\"]\n\n #store all the data into a dict so its easier to pass in to html\n display=[]\n total_share=0\n for row in rows:\n symbol=str(row[\"symbol\"])\n print(symbol)\n name=lookup(symbol)[\"name\"]\n shares=int(row[\"amount\"])\n price=float(lookup(symbol)[\"price\"])\n total=float(shares) *price\n total_share+=total\n display.append({'symbol':symbol, 'name':name, 'shares':shares, 'price':price, 'total':total})\n\n total_money=total_share+cash[0][\"cash\"]\n return render_template(\"index.html\",display=display,total_money=total_money,cash=cash_)","def show_results():\n\n\tuser_query = request.args.get(\"search\")\n\tsearch_activity = SearchActivity(user_id=session.get('user_id'), search_query=user_query, datetime = datetime.now())\n\n\tdb.session.add(search_activity)\n\tdb.session.commit()\n\tsearch_items_not_filtered_list = user_search(user_query)\n\tfound_items = []\n\t\n\tfor item in search_items_not_filtered_list:\n\t\tTaxonomy_obj = db.session.query(Taxonomy).filter(Taxonomy.path.like(\"%Food%\")).filter_by(category_node=item[u'categoryNode']).all()\n\t\tfor obj in Taxonomy_obj:\n\t\t\tif item[u'categoryNode'] == obj.category_node:\t\n\t\t\t\tfound_items.append({\n\t\t\t\t\t\"name\": item.get(u'name', \"\"), \n\t\t\t\t\t\"item_id\": item.get(u'itemId', \"\"),\n\t\t\t\t\t\"category\": item.get(u'categoryPath', \"\"), \n\t\t\t\t\t\"sale_price\": format(item.get(u'salePrice', \"\"), \".2f\"), \n\t\t\t\t\t\"description\": unescape(item.get(u'shortDescription', \"\")), \n\t\t\t\t\t\"customer_rating_img\": item.get(u'customerRatingImage', \"\"),\n\t\t\t\t\t\"thumbnail_image\": item.get(u'thumbnailImage', \"\")\n\t\t\t\t\t})\n\t\t\t\t\n\treturn render_template(\"searchresults.html\", found_items=found_items)","def _run_query(self, query):\n cursor = self.conn.cursor()\n cursor.execute(query)\n return cursor.fetchall()","def search_results(request):\n competencies = Competence.objects.all()\n comp_user = request.user\n comp_list_filer = []\n comp_num = 0\n for competence in competencies:\n if competence.person == comp_user:\n comp_list_filer.append((competence.title_of_competence, competence.level_of_competence))\n comp_num = comp_num + 1\n\n q = request.GET.get('q')\n add_list = get_vac(q)\n competence_list = []\n for vacancy_dict in add_list:\n if Vacancy.objects.filter(title_of_vacancy=vacancy_dict['name']):\n percent = get_percent(comp_list_filer, comp_num, vacancy_dict['name'])\n obj = Vacancy.objects.get(title_of_vacancy=vacancy_dict['name'])\n obj.percent = percent\n obj.save()\n continue\n else:\n percent = 0\n if vacancy_dict['salary'] == 0:\n vacancy = Vacancy.objects.create_vacancy(vacancy_dict['name'], vacancy_dict['description'],\n vacancy_dict['city'],\n 0, vacancy_dict['webSite'], percent)\n else:\n vacancy = Vacancy.objects.create_vacancy(vacancy_dict['name'], vacancy_dict['description'],\n vacancy_dict['city'],\n vacancy_dict['salary'], vacancy_dict['webSite'], percent)\n for i in vacancy_dict['description'].split(\" \"):\n competence_list.append(i)\n graph_dict = {\"vac_name\": vacancy_dict['name'], \"com_name\": competence_list}\n graph_add(graph_dict)\n percent = get_percent(comp_list_filer, comp_num, vacancy_dict['name'])\n obj = Vacancy.objects.get(title_of_vacancy=vacancy_dict['name'])\n obj.percent = percent\n obj.save()\n competence_list = []\n if q:\n vacs = VacDocument.search().query(\"match\", title_of_vacancy=q)\n vacs = vacs.sort({\"percent\": {\"order\": \"desc\"}})\n else:\n vacs = ''\n return render(request, 'core/search-results.html', {'vacs': vacs, 'competencies': competencies})","def record():\n\n try:\n newcurs = g.conn.execute(\"\"\"SELECT * FROM record\"\"\")\n except Exception:\n print \"can not read record from database\"\n return redirect('/error')\n\n info = []\n for result in newcurs:\n temp = [result['user_name'].encode(\"utf-8\"), result['message'].encode(\"utf-8\")]\n info.append(temp)\n newcurs.close()\n\n if not record:\n return redirect('/')\n\n return render_template(\"record.html\", **locals())","def all(request):\n\n posts = Post.objects.filter()\n\n print(\"made a query\")\n return render(request, 'posts/all.html', {'posts':posts})","def query(self):\r\n raise NotImplementedError","def query3() :","def search(request, query):\n try:\n if(query == ''):\n query = request.GET['query']\n posts = Post.search.query(query)\n context = { 'posts': list(posts),'query': query, 'search_meta':posts._sphinx }\n except:\n context = { 'posts': list() }\n\n return render_to_response('search/search_results.html', context, context_instance=RequestContext(request))","def results():\n df = mdr.elo_ratings.sort_values([\"elo\", \"matches\"], ascending=False)\n df[\"score\"] = (1 / (1 + 10**((1500 - df[\"elo\"]) / 400))) * 100\n df = df[[\"items\", \"score\", \"matches\"]]\n\n html_formatted = df.to_html(classes=[\"table\", \"table-dark\", \"table-hover\"], index=False, float_format=\"%.1f\")\n\n return render_template('results.html', table=html_formatted)","def create_response(self):\n (paginator, page) = self.build_page()\n\n context = {\n 'query': self.query,\n 'form': self.form,\n 'page': page,\n 'paginator': paginator,\n 'suggestion': None,\n }\n\n if hasattr(self.results, 'query') and self.results.query.backend.include_spelling:\n context['suggestion'] = self.form.get_suggestion()\n\n context.update(self.extra_context())\n return render_to_response(self.template, context, context_instance=self.context_class(self.request))","def post(self, request):\n return self.execute_query()","def run(self):\n query = self.query\n\n # count before filtering\n # self.cardinality = query.add_columns(self.columns[0].sqla_expr).count()\n\n self._set_column_filter_expressions()\n self._set_global_filter_expression()\n self._set_sort_expressions()\n self._set_yadcf_data(query)\n\n # apply filters\n query = query.filter(\n *[e for e in self.filter_expressions if e is not None])\n self.filtered_query = deepcopy(query)\n\n # self.cardinality_filtered = query.add_columns(\n # self.columns[0].sqla_expr).count()\n\n # apply sorts\n query = query.order_by(\n *[e for e in self.sort_expressions if e is not None])\n\n # add paging options\n length = int(self.params.get('length'))\n if length >= 0:\n query = query.limit(length)\n elif length == -1:\n pass\n else:\n raise(ValueError(\n 'Length should be a positive integer or -1 to disable'))\n query = query.offset(int(self.params.get('start')))\n\n # add columns to query\n query = query.add_columns(\n *[c.sqla_expr for c in self.columns])\n\n self.filtered_query = self.filtered_query.add_columns(\n *[c.sqla_expr for c in self.columns])\n\n self.query = query\n # fetch the result of the queries\n column_names = [col.mData if col.mData else str(i)\n for i, col in enumerate(self.columns)]\n # self.results = [{k: v for k, v in zip(\n # column_names, row)} for row in query.all()]","def do_query(self, query):\n query = query.replace('\\n', ' ')\n self.cursor.execute(query)\n return self.cursor.fetchall()","def index():\n parsed = database.mongodb[db_name].find({'parsed': True}).limit(100)\n\n return render_template('index.html', data=list(parsed))","def process_results(result, title=\"\", doWrite=True, query=\"\"):\n\n\tif not result or not result.returns_rows:\n\t\tprint \"-> 0 records returned\"\n\t\tprint result\n\t\treturn\n\n\tdoPrint = True\n\n\t# get column names\n\tcols = result.keys()\n\n\t# build template format string\n\ttemplate = \"\"\n\tfor i in range(len(cols)):\n\t\ttemplate += \"{%s:40}\" % i\n\ttemplate = template.replace(\"}{\", \"}|{\")\n\n\t# open output file\n\tif doWrite:\n\t\tresults_dir = DATA_PATH + \"query_results/\"\n\t\tif not os.path.exists(results_dir):\n\t\t\tos.makedirs(results_dir)\n\n\t\tnow = datetime.now().strftime(\"%Y_%m_%d__%I_%M_%p\")\n\t\tfilename = results_dir + \"query_results_\" + now\n\t\t\n\t\ttxt = open(filename+\".txt\", 'w')\n\t\tcsv = open(filename+\".csv\", 'w')\n\n\t\t# print query\n\t\ttxt.write(query + \"\\n\")\n\t\ttxt.write(\"=\" * len(query) + \"\\n\")\n\t\tcsv.write(query + \"\\n\")\n\n\t\t# print header\n\t\ttxt.write(template.format(*tuple(cols)) + \"\\n\") # header\n\t\ttxt.write(\"-\"*41*len(cols) + \"\\n\")\n\t\tcsv.write('|'.join(cols) + \"\\n\")\n\n\t# print records\n\tnumRecs = 0\n\tfor row in result:\n\t\t# ask user if they want ot stop printing after 100 records\n\t\tif numRecs == 10:\n\t\t\ti = raw_input(\"10 records printed. Continue printing records? (y/N) \")\n\t\t\tif i.lower() not in [\"y\", \"yes\"]:\n\t\t\t\tdoPrint = False\n\t\t\n\t\tif doPrint:\n\t\t\tscreen_write_row(row, title)\n\n\t\tif doWrite:\n\t\t\ttxt_write_row(txt, template, row)\n\t\t\tcsv_write_row(csv, row)\n\n\t\t# count records returned\n\t\tnumRecs += 1\n\n\t# show number of records returned\n\tprint \"-> %s records returned\" % numRecs\n\tif doWrite:\n\t\ttxt.write(\t\"-> %s records returned\" % numRecs)\n\n\tif doWrite:\n\t\ttxt.flush()\n\t\ttxt.close()","def send_results(self):\n # Send total records count for the progress bar\n url_count = self.session.query(Uurl).count()\n total_records = url_count + self.session.query(Session).count()\n self.total_count_signal.emit(total_records)\n\n url_query = self.session.query(Uurl).all()\n result_string = settings.URL_OUTPUT_HEADING\n for q in url_query:\n result_string = result_string + \"\\n\" + str(q)\n if not (q.id % settings.RESULT_SIGNAL_SIZE):\n self.update_progress_signal.emit(q.id, result_string)\n result_string = \"\"\n # Send remaining results\n self.update_progress_signal.emit(url_count, result_string)\n logging.info(\"All urls sent to the GUI\")\n # Printing urls completed\n self.step_completed_signal.emit(2)\n\n # Id of the last element inserted. It is used to calculate progressbar\n # value\n last_id = self.session.query(Uurl.id).order_by(\n Uurl.id.desc()).first()[0]\n\n self.update_progress_signal.emit(last_id, \"\\n\\n\")\n\n result_string = settings.SESSION_OUTPUT_HEADING\n\n # Send all sessions back to GUI\n session_query = self.session.query(Session).all()\n for s in session_query:\n result_string = result_string + \"\\n\" + str(s)\n if not ((last_id + s.id - 1) % settings.RESULT_SIGNAL_SIZE):\n self.update_progress_signal.emit(\n last_id + s.id - 1, result_string)\n result_string = \"\"\n self.update_progress_signal.emit(total_records - 1, result_string)\n logging.info(\"All sessions sent to the GUI\")\n # Printing sessions completed\n self.step_completed_signal.emit(3)\n\n self.number_of_sessions_signal.emit(\n self.session.query(Session).count())","def _(event):\n try:\n self.view_model.update_results()\n except Exception:\n self.view_model.status_textcontrol.text = \"(no results available)\"","def ng_query(self, request, *args, **kwargs):\r\n return self.build_json_response(self.get_queryset())","def query(request):\r\n\t# initialize form\r\n\tform = featureSelectionForm()\r\n\t# query output for displaying\r\n\toutput = []\r\n\t# preset variables\r\n\tstring_id_series = []\r\n\t# Mongo query to be defined\r\n\tquery = ''\r\n\tif request.method == 'POST' :\r\n\t\tform = featureSelectionForm(request.POST)\r\n\t\tif form.is_valid():\r\n\t\t\t# Presumed variables\r\n\t\t\t# collection_name = \"RNA_brain_gender-F_AD-vs-Control\"\r\n\t\t\t# feature_symbols_in_interest = ['APOE', 'BIN1', 'CLU']\r\n\t\t\t# way_to_choose_probe = \"fold change\"\r\n\t\t\t### Get variables from POST\r\n\t\t\tcollection_name = \"%s_%s_%s-%s_%s\" % (request.POST[\"dataType\"],\r\n\t\t\t\t\t\t\t\t\t\t\t\t\trequest.POST[\"tissue\"],\r\n\t\t\t\t\t\t\t\t\t\t\t\t\trequest.POST[\"category\"],\r\n\t\t\t\t\t\t\t\t\t\t\t\t\trequest.POST[\"group\"],\r\n\t\t\t\t\t\t\t\t\t\t\t\t\trequest.POST[\"comparison\"])\r\n\t\t\t\"\"\"\r\n\t\t\t\tWe should split POST[\"featureInput\"] here\r\n\t\t\t\"\"\"\r\n\t\t\t# import pdb; pdb.set_trace();\r\n\t\t\tfeature_symbols_in_interest = split_feature_input_to_list(request.POST[\"featureInput\"])\r\n\r\n\t\t\tway_to_choose_probe = request.POST[\"probeSelectionMethod\"]\r\n\r\n\t\t\ttest_stat_output_dict = {}\r\n\r\n\t\t\tall_datasets = test_stat_client.get_all_datasets(collection_name)\r\n\r\n\t\t\ttest_statistics = list(test_stat_client.get_all_for_this_category(collection_name))\r\n\r\n\t\t\ttest_statistics = pd.DataFrame(test_statistics)\r\n\r\n\t\t\tfor dataset in all_datasets:\r\n\t\t\t\t# Filter 1 - dataset accession & features in interest\r\n\t\t\t\tif request.POST[\"dataType\"] == \"RNA\":\r\n\t\t\t\t\tfilt_ind = (test_statistics['dataset_accession'] == dataset) & (test_statistics['symb'].isin(feature_symbols_in_interest))\r\n\t\t\t\telif request.POST[\"dataType\"] == \"protein\":\r\n\t\t\t\t\tsymbol_series = test_statistics['symb'].apply(extract_gene_symbol_from_protein_name)\r\n\t\t\t\t\tfilt_ind = (test_statistics['dataset_accession'] == dataset) & (symbol_series.isin(feature_symbols_in_interest))\r\n\r\n\t\t\t\ttest_stat_df = test_statistics[filt_ind]\r\n\r\n\t\t\t\t# Filter 2 - remove duplicates\r\n\t\t\t\t\"\"\"\r\n\t\t\t\t\tHere we provide options for user to choose how to select a probe when \r\n\t\t\t\t\tmultiple probes are corresponding to one feature\r\n\t\t\t\t\"\"\"\r\n\r\n\t\t\t\tif way_to_choose_probe == \"fold change\":\r\n\t\t\t\t\ttest_stat_df = filtered_duplicate_by(test_stat_df, by='fc', group_index=['symb'])\r\n\r\n\t\t\t\telif way_to_choose_probe == \"limma p value\" : \r\n\t\t\t\t\ttest_stat_df = filtered_duplicate_by(test_stat_df, by='lp', group_index=['symb'])\r\n\r\n\t\t\t\telif way_to_choose_probe == \"t test p value\" :\r\n\t\t\t\t\ttest_stat_df = filtered_duplicate_by(test_stat_df, by='tp', group_index=['symb'])\r\n\r\n\t\t\t\tif test_stat_df.empty:\r\n\t\t\t\t\tall_datasets.remove(dataset)\r\n\t\t\t\t\tcontinue\r\n\t\t\t\t# Split dataframe for stat table display and graph display\r\n\t\t\t\t# stat_table = test_stat_df.drop(['eval', 'dsl'], axis=1)\r\n\t\t\t\tstat_table = test_stat_df.drop(['eval'], axis=1)\r\n\t\t\t\t# import pdb; pdb.set_trace()\r\n\t\t\t\tstat_table['entrez_gene_id'] = stat_table.apply(from_symbol_to_entrez_gene_id, axis=1)\r\n\t\t\t\tstat_table['string_id'] = from_single_symbol_to_string_id(stat_table['symb'])\r\n\t\t\t\tstring_id_series = stat_table['string_id']\r\n\t\t\t\t\r\n\t\t\t\t# import pdb; pdb.set_trace()\r\n\r\n\t\t\t\tstat_table_output = stat_table.to_dict(outtype='records')\r\n\r\n\t\t\t\t# import pdb; pdb.set_trace()\r\n\t\t\t\ttest_stat_output_dict.update({dataset : stat_table_output})\r\n\r\n\r\n\r\n\t\t\treturn render(request, 'feature_stat.html',\r\n\t\t\t\t\t\t{\r\n\t\t\t\t\t\t\t'dataset_names' : all_datasets,\r\n\t\t\t\t\t\t\t'test_stat' : test_stat_output_dict,\r\n\t\t\t\t\t\t\t'way_to_choose_probe' : way_to_choose_probe,\r\n\t\t\t\t\t\t\t'datatype' : request.POST[\"dataType\"],\r\n\t\t\t\t\t\t\t'tissue' : request.POST[\"tissue\"],\r\n\t\t\t\t\t\t\t'category' : request.POST[\"category\"],\r\n\t\t\t\t\t\t\t'group' : request.POST[\"group\"],\r\n\t\t\t\t\t\t\t'comparison' : request.POST[\"comparison\"],\r\n\t\t\t\t\t\t\t'features' : generate_mulivariable_series_from_list(feature_symbols_in_interest),\r\n\t\t\t\t\t\t\t'string_url_id_component' : generate_string_id_get_query_from_list(string_id_series)\r\n\t\t\t\t\t\t})\r\n\telse:\t\t\r\n\t\treturn render(request, 'query.html', {\r\n\t\t\t'form' : form\r\n\t\t})","def submit_query(self, username, password):\n\n #username = os.environ['NEWSREADER_USERNAME']\n #password = os.environ['NEWSREADER_PASSWORD']\n payload = {'id': self.query}\n \n endpoint_url = self.endpoint_stub_url.format(action=self.action)\n print \"\\n\\n**New CRUD query**\"\n print endpoint_url, payload\n t0 = time.time()\n try:\n response = requests.get(endpoint_url, auth=(username, password),\n params=payload)\n except Exception as e:\n print \"Query raised an exception\"\n print type(e)\n t1 = time.time()\n total = t1-t0\n raise QueryException(\"Query raised an exception: {0}\".format(type(e).__name__))\n else:\n t1 = time.time()\n total = t1-t0\n print \"Time to return from query: {0:.2f} seconds\".format(total)\n print \"Response code: {0}\".format(response.status_code)\n print \"From cache: {0}\".format(response.from_cache)\n\n #print response.content\n \n if response and (response.status_code == requests.codes.ok):\n self.json_result = {\"content\":response.content}\n self.clean_json = self.json_result\n else:\n raise QueryException(\"Response code not OK: {0}\".format(response.status_code))","def query1(request):\n with connection.cursor() as cursor:\n cursor.execute('SELECT * FROM (\\\n example_usuario as u \\\n JOIN\\\n example_pessoa as p \\\n ON u.cpf_pessoa_id = p.cpf)')\n result = named_tuple_fetchall(cursor)\n\n template = loader.get_template('example/query1.html')\n context = {'query1_result_list': result, }\n\n return HttpResponse(template.render(context, request))","def index():\n\twith get_db().cursor() as cursor :\n\t\tcursor.execute(\"SELECT *, (SELECT COUNT(*) FROM `cheer` WHERE ask_id = ask.id) AS cheer_cnt FROM `ask`\")\n\t\tresult = cursor.fetchall()\n\n\treturn render_template('main.html',\n\t\tdataset=result,\n\t)","def search(request):\r\n assert isinstance(request, HttpRequest)\r\n return render(\r\n request,\r\n 'app/geral/resultados.html',\r\n context_instance=RequestContext(request,\r\n {\r\n 'title': 'Colmeia | Resultados',\r\n 'year': datetime.now().year,\r\n })\r\n )","def run_query(cur, query, show_results=False):\n num_rows = cur.execute(query)\n print('the query returned {} rows'.format(num_rows))\n if show_results:\n for row in cur.fetchall():\n print(row)","def generate_query(self):\n return","def display_results():\n pass","def query3(request):\n query = \"SELECT pessoa_tutorada.nome as tutorado, pessoa_tutora.nome as tutor \\\n FROM example_usuario as usuario_tutelado \\\n JOIN \\\n example_tutelamento as tutelamento \\\n ON usuario_tutelado.id_usuario = tutelamento.id_usuario_tutelado_id \\\n JOIN \\\n example_usuario as usuario_tutor \\\n ON usuario_tutor.id_usuario = tutelamento.id_tutor_id \\\n JOIN example_pessoa as pessoa_tutorada\\\n ON pessoa_tutorada.cpf = usuario_tutelado.cpf_pessoa_id \\\n JOIN \\\n example_pessoa as pessoa_tutora \\\n ON pessoa_tutora.cpf = usuario_tutor.cpf_pessoa_id\"\n\n with connection.cursor() as cursor:\n cursor.execute(query)\n result = named_tuple_fetchall(cursor)\n\n # remove duplicates\n result = list(set(result))\n\n template = loader.get_template('example/query3.html')\n context = {'query3_result_list': result, }\n\n return HttpResponse(template.render(context, request))","def result_page():\n results = session.get('results')\n points = 0\n if results:\n for k,p in results.items():\n points += p['points']\n return render_template('results.html', results=results, points=points),","def get_query_results(self, conn, sql):\n\n cur = conn.cursor()\n cur.execute(sql)\n yield from cur.fetchall()","def submitForm():\n try:\n rec = db.session.query(Rec)\n StockCode = request.form.get('prod')\n this_rec = Rec.query.filter_by(StockCode=StockCode).first()\n logger.debug(\"Successfully loaded data.\")\n return render_template('index.html', recs=rec, this_rec=this_rec)\n except:\n traceback.print_exc()\n logger.warning(\"Not able to get recommendations, error page returned\")\n return render_template('error.html')","def execute_queries():\n fetch_job_listings(engine)\n update_job_listing(engine)","def show_results():\n\n if request.args.get('cheery'):\n msg_type = \"cheery\"\n message = \"\"\"\n Life’s like a movie. Write your own ending.\n \"\"\"\n auth = \"— Kermit the Frog\"\n elif request.args.get('dreary'):\n msg_type = \"dreary\"\n message = \"\"\"\n Bad days happen to everyone, but when one happens to you, just\n keep doing your best and never let a bad day make you feel bad\n about yourself.\n \"\"\"\n author = \"— Big Bird\"\n elif request.args.get('honest'):\n msg_type = \"honest\"\n message = \"\"\"\n Who care if me eat carrot or collard greens? Me also like broccoli\n and lettuce and lima beans. Me still Cookie Monster. That not a sham.\n \"\"\"\n author = \"— Cookie Monster\"\n\n return render_template(\"results.html\",\n message=message,\n author=author,\n msg_type=msg_type)","def search_results():\n skip = int(flask.request.args.get(\"skip\", \"0\"))\n limit = int(flask.request.args.get(\"limit\", \"20\"))\n\n obj = {}\n\n # query : will be event kit in case of triage information\n uidstr = flask.request.args.get(\"query\", None)\n\n if uidstr == None:\n obj[\"error\"] = \"Missing search ID\"\n\n uidstr = json.loads(uidstr)\n\n obj[\"query\"] = {}\n obj[\"query\"][\"uid\"] = uidstr\n obj[\"clips\"] = []\n states = backend.get_search_sessions()\n obj[\"sessions\"] = []\n for astate in states:\n obj[\"sessions\"].append(str(astate))\n try:\n uid = uuid.UUID(uidstr)\n state = backend.get_iqr_search_state(uid)\n # use the uid of the state and get the information from the database\n col = str(state.uuid)\n obj[\"collection\"] = col\n searchdb[col].ensure_index([(\"model_id\", pymongo.ASCENDING),(\"probability\", pymongo.DESCENDING) ])\n # Force probabilities\n obj[\"positives\"] = list(state.positives)\n obj[\"negatives\"] = list(state.negatives)\n log = \"\"\n for id in state.positives:\n # log = log + \"Found %d\"%(searchdb[col].find({\"model_id\" : \"FUSION\", \"clip_id\" : id}).count()) + \", \"\n # res = searchdb[col].update({\"model_id\" : \"FUSION\", \"clip_id\" : id}, {\"$set\" : { \"probability\" : 1.0}})\n # log = log + \"Done %d\"%id + \", \"\n news = searchdb[col].find_one({\"model_id\" : \"FUSION\", \"clip_id\" : id})\n news[\"probability\"] = 1.0001\n searchdb[col].save(news)\n log = log + \"Now : \" + str(news)\n\n\n for id in state.negatives:\n # log = log + \"Found %d\"%(searchdb[col].find({\"model_id\" : \"FUSION\", \"clip_id\" : id}).count()) + \", \"\n # res = searchdb[col].update({\"model_id\" : \"FUSION\", \"clip_id\" : id}, {\"$set\" : { \"probability\" : 0.0}})\n # log = log + \"Done %d\"%id + \", \"\n news = searchdb[col].find_one({\"model_id\" : \"FUSION\", \"clip_id\" : id})\n news[\"probability\"] = 0.0\n searchdb[col].save(news)\n log = log + \"Now : \" + str(news)\n\n obj[\"log\"] = log\n\n allres = searchdb[col].find({\"model_id\" : \"FUSION\"}).sort([(\"probability\", pymongo.DESCENDING)]).skip(skip).limit(limit)\n rank = skip + 1\n for one in allres:\n aclip = {}\n aclip[\"score\"] = one[\"probability\"]\n aclip[\"id\"] = \"HVC\" + str(one[\"clip_id\"]).zfill(6)\n clipobj = db[\"clips\"].find_one({\"id\" : \"HVC\" + str(one[\"clip_id\"]).zfill(6)},{\"duration\" : 1})\n aclip[\"duration\"] = clipobj[\"duration\"]\n aclip[\"rank\"] = rank\n rank = rank + 1\n obj[\"clips\"].append(aclip)\n obj[\"count\"] = len(obj[\"clips\"])\n\n except Exception as e:\n obj[\"error\"] = str(type(e)) + \": \" + str(e)\n return jsonify(obj)\n\n obj[\"next\"] = \"http://localhost:5003/iqr/search_results?\" + urllib.urlencode({\"uid\" : uid, \"skip\" : skip+limit } )\n return jsonify(obj)","def create_response(self):\n (paginator, page) = self.build_page()\n\n context = {\n 'query': self.query,\n 'form': self.form,\n 'page': page,\n 'paginator': paginator,\n 'suggestion': None,\n }\n\n if self.results and hasattr(self.results, 'query') and self.results.query.backend.include_spelling:\n context['suggestion'] = self.form.get_suggestion()\n\n context.update(self.extra_context())\n return render_to_response(self.template, \\\n context, \\\n context_instance=self.context_class(self.request), \\\n mimetype=\"application/json\")","def query(env):\n if app.config['ENABLE_QUERY']:\n envs = environments()\n check_env(env, envs)\n\n form = QueryForm(meta={\n 'csrf_secret': app.config['SECRET_KEY'],\n 'csrf_context': session})\n if form.validate_on_submit():\n if form.endpoints.data == 'pql':\n query = form.query.data\n elif form.query.data[0] == '[':\n query = form.query.data\n else:\n query = '[{0}]'.format(form.query.data)\n result = get_or_abort(\n puppetdb._query,\n form.endpoints.data,\n query=query)\n return render_template('query.html',\n form=form,\n result=result,\n envs=envs,\n current_env=env)\n return render_template('query.html',\n form=form,\n envs=envs,\n current_env=env)\n else:\n log.warn('Access to query interface disabled by administrator..')\n abort(403)","def index(request, template_name='index.html'):\n\n context_dict = {}\n model = Uni\n column_headers = ['rank', 'name', 'location', 'city', 'scores_overall']\n check_fields = ['scores_citations', 'scores_industry_income', 'scores_international_outlook', 'scores_research', 'scores_teaching', 'stats_student_staff_ratio', 'stats_pc_intl_students', 'stats_number_students', 'quality_of_life_index', 'safety_index', 'cost_of_living_index', 'climate_index' ]\n \n uni_main = Uni.objects.values(*column_headers)\n \n # subject filter\n if request.GET.get('sub_drop'):\n subject_filter = request.GET.get('sub_drop')\n if subject_filter == 'All':\n uni_main = Uni.objects.values(*column_headers)\n\n elif subject_filter == 'Computer Science':\n model = Uni_cs\n uni_main = Uni_cs.objects.values(*column_headers)\n elif subject_filter == 'Engineering':\n model = Uni_eng\n uni_main = Uni_eng.objects.values(*column_headers)\n else:\n uni_main = Uni.objects.values(*column_headers)\n\n\n # Locations filter\n if request.GET.get('loc_drop'):\n location_filter = request.GET.get('loc_drop')\n if location_filter == 'All':\n listings = uni_main\n\n else:\n listings = uni_main.filter(location=location_filter)\n else:\n listings = uni_main\n\n # advanced search\n qs = listings\n if request.GET.getlist('v_scores[]'):\n scorevar = request.GET.getlist('v_scores[]')\n if scorevar != ['0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0']:\n for i in range (0, len(scorevar)):\n if scorevar[i]=='0':\n check_fields[i]='0' \n check_fields = [x for x in check_fields if x != '0']\n checkvar = check_fields\n gen_rank(checkvar,scorevar,model)\n column_headers[0] = 'new_rank'\n values = column_headers + checkvar\n qs = listings.values(*values).order_by('new_rank')\n listings = qs\n uni_name = listings\n\n paginator = Paginator(listings, 10)\n page = request.GET.get('page')\n try:\n uni_list = paginator.page(page) \n except PageNotAnInteger: \n uni_list = paginator.page(1) \n except EmptyPage: \n uni_list = paginator.page(paginator.num_pages)\n\n context_dict = {'uni_list': uni_list, 'uni_name': uni_name, 'loc_list' : Uni.objects.order_by('location').values_list('location', flat=True).distinct()}\n\n # Render the HTML template index.html with the data in the context variable\n# return render(request, 'index.html', context=context)\n return render(request, template_name, context_dict)","def results_overview():\n\n if request.method == \"POST\":\n # clean out all unwanted storage\n if _pool:\n _pool.terminate()\n del _drivers[:]\n \n return redirect(url_for('upload.upload'))\n\n # GET\n \n # Captures the global drivers variable\n global _drivers\n\n processType = g.processType\n coreFactor = g.coreFactor\n\n if processType == 'parallel':\n current_app.logger.info(time.ctime() + \"\\tProcess pool with %s processes initialized for execution\" % coreFactor)\n results = _pool.map(_get_result, _drivers)\n else:\n results = [_get_result(driver) for driver in _drivers]\n\n return render_template('checks/results_overview.html', results=results)","def search():\r\n\r\n # Ensure parameter is present\r\n if not request.args.get(\"q\"):\r\n raise RuntimeError(\"missing search string\")\r\n\r\n # Query db with the string LIMIT result to 10\r\n # TODO\r\n\r\n # send back as json\r\n # TODO\r\n\r\n return jsonify({})","def post(self, request, *args, **kwargs):\n self.form = self.get_form()\n self.form.full_clean()\n results = self.get_queryset()\n nb_results = results.count()\n first_results = results[:10]\n site = get_current_site(self.request)\n querystring = self.get_form_data().urlencode()\n scheme = 'https'\n search_url = reverse('search_view')\n full_url = '{scheme}://{domain}{search_url}?{querystring}'.format(\n scheme=scheme,\n domain=site.domain,\n search_url=search_url,\n querystring=querystring)\n results_body = render_to_string('emails/search_results.txt', {\n 'user_name': self.request.user.full_name,\n 'aids': first_results,\n 'nb_results': nb_results,\n 'full_url': full_url,\n 'scheme': scheme,\n 'domain': site.domain,\n })\n send_mail(\n self.EMAIL_SUBJECT,\n results_body,\n settings.DEFAULT_FROM_EMAIL,\n [self.request.user.email],\n fail_silently=False)\n return HttpResponse('')","def index(request):\n\n pres = ParseResult.objects.filter()[:10]\n count = ParseResult.objects.filter().count()\n\n template = loader.get_template('index.html')\n context = RequestContext(request, {\n 'parseresults': pres,\n 'parsecount': count\n })\n return HttpResponse(template.render(context))","def get(self):\n if 'wipe' in self.request.path_url:\n InboundRequest.wipe()\n self.response.write('Db wiped')\n return\n\n # log out last 10 requests\n data = InboundRequest.get_latest()\n\n resultList = []\n for item in data:\n headers = ''\n header_list = item.request_headers.split('\\r\\n')\n\n # try format if json\n body = item.request_body\n try:\n json_body = json.loads(item.request_body)\n body = json.dumps(json_body, indent=2, separators=(',', ': '))\n except:\n #logging.info('not in json')\n pass\n\n resultfields = {'ts': item.time_stamp, 'host_url': item.request_host_url, 'path': item.request_path,\n 'query_params': item.request_query_params, 'headers': header_list, 'body': body}\n resultList.append(resultfields)\n\n template_values = {\n 'number_returned': len(data),\n 'results': resultList\n }\n self.render_template('index.html', template_values)","def _run_async_query(self, context):\n url = self._build_url(\"/_search\")\n request = self._build_request(0, -1)\n resp = self._cb.post_object(url, body=request)\n result = resp.json()\n self._total_results = result[\"num_found\"]\n self._count_valid = True\n results = result.get(\"results\", [])\n return [self._doc_class(self._cb, item[\"id\"], item) for item in results]","def _run_async_query(self, context):\n url = self._build_url(\"/_search\")\n request = self._build_request(0, -1)\n resp = self._cb.post_object(url, body=request)\n result = resp.json()\n self._total_results = result[\"num_found\"]\n self._count_valid = True\n results = result.get(\"results\", [])\n return [self._doc_class(self._cb, item[\"id\"], item) for item in results]","def execute_query(self, *args, **kwargs):","def execQuery():\n\n if request.method == \"POST\":\n result = exec_query(request)\n if result:\n status = 200\n else:\n status = 400\n return result, status # HTTP Status Created [201]","def search_results(request):\n\n query = None\n results_list = ()\n filtered_products = Product.objects.filter(discontinued=False)\n filtered_programmes = Programme.objects.filter(discontinued=False)\n filtered_posts = Post.objects.filter(status=1)\n\n if 'q' in request.GET:\n query = request.GET['q']\n if not query:\n messages.warning(request,\n \"You didn't enter any search criteria!\")\n return redirect(reverse('search_results'))\n\n products = filtered_products.filter(Q(name__icontains=query) | Q(\n description__icontains=query))\n programmes = filtered_programmes.filter(Q(\n name__icontains=query) | Q(description__icontains=query))\n posts = filtered_posts.filter(Q(title__icontains=query))\n\n results_list = list(chain(products, programmes, posts))\n\n context = {\n 'search_term': query,\n 'results_list': results_list,\n }\n\n return render(request, 'home/search.html', context)","def index():\n response.flash=\"Welcome to TheChef\"\n \"\"\"recepies = db(db.recepies).select(orderby=~db.recepies.pub_date)\n return dict(recepies=recepies) \"\"\"\n if len(request.args): page=int(request.args[0])\n else: page=0\n items_per_page=9\n limitby=(page*items_per_page,(page+1)*items_per_page+1)\n rows=db(db.recepies).select(orderby=~db.recepies.pub_date,limitby=limitby)\n return dict(rows=rows,page=page,items_per_page=items_per_page)","def refresh():\n DB.drop_all()\n DB.create_all()\n results = get_results()\n for i, result in enumerate(results):\n record = Record(id=i, datetime=result[0], value=result[1])\n DB.session.add(record)\n DB.session.commit()\n return redirect(\"/\")","def search_results(self):\r\n route_name = self.request.matched_route.name\r\n mdict = self.matchdict\r\n rdict = self.GET\r\n\r\n if 'terms' in mdict:\r\n phrase = \" \".join(mdict['terms'])\r\n else:\r\n phrase = rdict.get('search', '')\r\n\r\n # Always search the fulltext content\r\n with_content = True\r\n\r\n conn_str = self.settings.get('sqlalchemy.url', False)\r\n searcher = get_fulltext_handler(conn_str)\r\n\r\n # check if we have a page count submitted\r\n params = self.params\r\n page = params.get('page', 0)\r\n count = params.get('count', 50)\r\n\r\n if rdict.get('search_mine') or 'username' in mdict:\r\n with_user = True\r\n else:\r\n with_user = False\r\n\r\n username = None\r\n if with_user:\r\n if 'username' in mdict:\r\n username = mdict.get('username')\r\n elif self.request.user and self.request.user.username:\r\n username = self.request.user.username\r\n\r\n res_list = searcher.search(\r\n phrase,\r\n content=with_content,\r\n username=username if with_user else None,\r\n ct=count,\r\n page=page,\r\n )\r\n\r\n # if the route name is search_ajax we want a json response\r\n # else we just want to return the payload data to the mako template\r\n if 'ajax' in route_name or 'api' in route_name:\r\n return {\r\n 'success': True,\r\n 'message': \"\",\r\n 'payload': {\r\n 'search_results': [dict(res) for res in res_list],\r\n 'result_count': len(res_list),\r\n 'phrase': phrase,\r\n 'page': page,\r\n 'username': username,\r\n }\r\n }\r\n else:\r\n return {\r\n 'search_results': res_list,\r\n 'count': len(res_list),\r\n 'max_count': 50,\r\n 'phrase': phrase,\r\n 'page': page,\r\n 'username': username,\r\n }","def get_results():\n try:\n firstbeer = int(request.form['beerchoice1'])\n secondbeer = int(request.form['beerchoice2'])\n except:\n traceback.print_exc()\n logger.warning(\"Not able to display recommendations, error page returned\")\n return render_template('error-noselection.html')\n try:\n listbeers = db.session.query(Top_Ten_Beers).filter_by(Type=beertype)\n logger.debug(\"Top Ten Beers Query Accessed\")\n except:\n traceback.print_exc()\n logger.warning(\"Not able to display recommendations, error page returned\")\n if firstbeer==secondbeer:\n return render_template('error-samebeers.html')\n names, data = query_to_list(listbeers)\n top10df = pd.DataFrame.from_records(data, columns=names)\n usercomb = top10df.iloc[[firstbeer, secondbeer],:]\n try:\n allcomb = db.session.query(User_Combinations).filter_by(Type=beertype)\n logger.debug(\"Recommendation Query Accessed\")\n except:\n traceback.print_exc()\n logger.warning(\"Not able to display recommendations, error page returned\")\n names, data = query_to_list(allcomb)\n allcombdf = pd.DataFrame.from_records(data, columns=names)\n probablerows = allcombdf[allcombdf['Beer_ID'].isin(usercomb['Beer_ID'].values)]\n realrows = probablerows.groupby(['ID']).count()\n ID = realrows[realrows['Beer_ID']==2].index[0]\n try:\n preds = db.session.query(User_Predictions).filter_by(Type=beertype, ID=ID)\n logger.debug(\"Recommendation Results Query Accessed\")\n return render_template('results.html', beertype=beertype, preds=preds)\n except:\n traceback.print_exc()\n logger.warning(\"Not able to display beers, error page returned\")\n return render_template('error-noselection.html')","def index(request):\n\n # Generate counts of some of the main objects\n num_para = Paragraph.objects.all().count()\n num_source = Source.objects.all().count()\n\n context = {\n 'num_para': num_para,\n 'num_source': num_source,\n 'paragraph_list': queryset[:10],\n }\n\n return render(request, 'index.html', context=context)","def send_table_as_html(self, event):\n # todo: for now we send all pending tasks serialized as json\n # further changes:\n # * filter by the user object based permissions to show only pending tasks for that the user\n # has permissions\n # * check if the self.user has permissions for the instance that is created/modified. If not skip sending\n\n # create dummy request to render table as html\n url = self.scope['path']\n if self.scope['query_string']:\n url += f\"?{self.scope['query_string'].decode('utf-8')}\"\n\n request = RequestFactory().get(url)\n request.user = self.user\n\n all_task_results = TaskResult.objects.all()\n\n pending_tasks_filterset = TaskResultFilter(data=request.GET, queryset=all_task_results)\n if pending_tasks_filterset.qs:\n # render the table only if the filtered qs in not empty\n pending_task_table = PendingTaskTable(data=pending_tasks_filterset.qs)\n pending_task_table.context = Context()\n pending_task_table.context.update({'filter': pending_tasks_filterset})\n\n RequestConfig(request=request).configure(table=pending_task_table)\n\n rendered_table = pending_task_table.as_html(request=request)\n self.send_json(content=json.dumps({'rendered_table': rendered_table}))","def execute(self, request):\n CheckValue.check_not_none(request, 'request')\n request.set_defaults(self._config)\n request.validate()\n if request.is_query_request():\n self._stats_control.observe_query(request)\n\n \"\"\"\n The following 'if' may be True for advanced queries only. For such\n queries, the 'if' will be True (i.e., the QueryRequest will be bound\n with a QueryDriver) if and only if this is not the 1st execute()\n call for this query. In this case we just return a new, empty\n QueryResult. Actual computation of a result batch will take place\n when the app calls get_results() on the QueryResult.\n \"\"\"\n if request.has_driver():\n self._trace('QueryRequest has QueryDriver', 2)\n return QueryResult(request, False)\n \"\"\"\n If it is an advanced query and we are here, then this must be the\n 1st execute() call for the query. If the query has been prepared\n before, we create a QueryDriver and bind it with the QueryRequest.\n Then, we create and return an empty QueryResult. Actual computation\n of a result batch will take place when the app calls get_results()\n on the QueryResult.\n \"\"\"\n if request.is_prepared() and not request.is_simple_query():\n self._trace(\n 'QueryRequest has no QueryDriver, but is prepared', 2)\n driver = QueryDriver(request)\n driver.set_client(self)\n driver.set_topology_info(request.topology_info())\n return QueryResult(request, False)\n \"\"\"\n If we are here, then this is either (a) a simple query or (b) an\n advanced query that has not been prepared already, which also\n implies that this is the 1st execute() call on this query. For a\n non-prepared advanced query, the effect of this 1st execute() call\n is to send the query to the proxy for compilation, get back the\n prepared query, but no query results, create a QueryDriver, and bind\n it with the QueryRequest (see QueryRequestSerializer.deserialize()),\n and return an empty QueryResult.\n \"\"\"\n self._trace(\n 'QueryRequest has no QueryDriver and is not prepared', 2)\n timeout_ms = request.get_timeout()\n headers = {'Host': self._url.hostname,\n 'Content-Type': 'application/octet-stream',\n 'Connection': 'keep-alive',\n 'Accept': 'application/octet-stream',\n 'User-Agent': self._user_agent}\n\n # set the session cookie if available\n if self._session_cookie is not None:\n headers['Cookie'] = self._session_cookie\n\n # set namespace if configured\n namespace = request.get_namespace()\n if namespace is None:\n namespace = self._config.get_default_namespace()\n if namespace is not None:\n headers[HttpConstants.REQUEST_NAMESPACE_HEADER] = namespace\n\n content = self.serialize_request(request, headers)\n content_len = len(content)\n # If on-premise the auth_provider will always be a\n # StoreAccessTokenProvider. If so, check against configurable limit.\n # Otherwise check against internal hardcoded cloud limit.\n if isinstance(self._auth_provider, StoreAccessTokenProvider):\n if content_len > self._max_content_length:\n raise RequestSizeLimitException(\n 'The request size of ' + str(content_len) + ' exceeded ' +\n 'the limit of ' + str(self._max_content_length))\n if request.get_compartment() is None:\n request.set_compartment_internal(\n self._config.get_default_compartment())\n if self._logutils.is_enabled_for(DEBUG):\n self._logutils.log_debug('Request: ' + request.__class__.__name__)\n request_id = self._next_request_id()\n headers[HttpConstants.REQUEST_ID_HEADER] = request_id\n self.check_request(request)\n # TODO: look at avoiding creating this object on each request\n request_utils = RequestUtils(\n self._sess, self._logutils, request, self._retry_handler, self,\n self._rate_limiter_map)\n return request_utils.do_post_request(self._request_uri, headers,\n content, timeout_ms,\n self._stats_control)","def generate(self):\n redash_session = type(self)._create_redash_session()\n refresh_data = type(self)._refresh_query(redash_session, self.query_id)\n if refresh_data.status_code != 200:\n raise ValueError(\"Could not refresh query {}\".format(self.query_id))\n\n refresh_job = refresh_data.json()['job']\n result_id = type(self)._poll_for_new_result(redash_session, refresh_job)\n if not result_id:\n raise ValueError(\"Query execution failed\")\n\n results_data = type(self)._get_fresh_results(redash_session, self.query_id, result_id)\n if results_data.status_code != 200:\n raise ValueError(\"Failed fetching result id {}\".format(result_id))\n\n rows = results_data.json()['query_result']['data']['rows']\n for row in rows:\n yield {'_raw': json.dumps(row)}","def query(self, sql):\n self.cursor.execute(sql)\n result = self.cursor.fetchall()\n return result","def send_sql_query(self, query):\n # TODO: MAKE SQL SELECT and SQL INSERT modules\n self.cursor.execute(query)\n self.cnx.commit()","def results(self):\r\n pass","def index():\n rows = db.execute(\"SELECT symbol, SUM(shares) as shares FROM 'transaction' WHERE u_id = :user_id GROUP BY symbol\", user_id = session[\"user_id\"])\n user = db.execute(\"SELECT * FROM 'users' WHERE id = :user_id\", user_id = session[\"user_id\"])\n\n if len(rows) == 0:\n return render_template(\"index.html\", rows = 0, username = user[0][\"username\"], cash = user[0][\"cash\"], total = user[0][\"cash\"])\n\n else:\n cur_price = []\n value = []\n names = []\n total = 0\n for row in rows:\n returned_quote = lookup(row[\"symbol\"])\n cur_price.append(returned_quote[\"price\"])\n value.append(round(returned_quote[\"price\"] * row[\"shares\"], 2))\n names.append(returned_quote[\"name\"])\n total = total + round(returned_quote[\"price\"] * row[\"shares\"], 2)\n\t\t\n\t\ttotal = round(total, 2)\n\t\t\n return render_template(\"index.html\", username = user[0][\"username\"], cash = user[0][\"cash\"], total = total, rows = rows, cur_price = cur_price, value = value, names = names)","def _prepare_result(self, request):\n # TODO: get all params from request (via self)\n self._request = request\n return super(FullTextSearchModel, self)._prepare_result(self.__query_params)","def index():\n rows = db.execute(\"SELECT Symbol, SUM(Shares) as totalShares FROM cash WHERE id=:id GROUP BY Symbol HAVING totalShares > 0\", id=session[\"user_id\"])\n transactions=[]\n grand_total = 0\n for row in rows:\n stock = lookup(row[\"Symbol\"])\n transactions.append({\n \"Symbol\": stock[\"symbol\"],\n \"Name\": stock[\"name\"],\n \"Shares\": row[\"totalShares\"],\n \"Price\": usd(stock[\"price\"]),\n \"Total\": usd(stock[\"price\"] * row[\"totalShares\"])\n })\n grand_total += stock[\"price\"] * row[\"totalShares\"]\n rows = db.execute(\"SELECT cash FROM users WHERE id=:id\", id=session[\"user_id\"])\n cash = rows[0][\"cash\"]\n return render_template(\"table.html\", transactions=transactions, cash=usd(cash), grand_total=usd(grand_total))","def _raw(self, query: Any, data: Any = None):\n assert isinstance(query, str)\n\n conn = self._get_session()\n try:\n results = conn.execute(query)\n\n entity_items = []\n for item in results:\n entity = self.model_cls.to_entity(item)\n entity.state_.mark_retrieved()\n entity_items.append(entity)\n\n result = ResultSet(\n offset=0,\n limit=len(entity_items),\n total=len(entity_items),\n items=entity_items,\n )\n except DatabaseError as exc:\n logger.error(f\"Error while running raw query: {exc}\")\n raise\n finally:\n if not current_uow:\n conn.commit()\n conn.close()\n\n return result","def query(self, *sql):\n self.cursor.execute(*sql)\n self.conn.commit()","def home(request):\n context = {\n \"results\": Result.objects.all()\n .filter(patient_capacity__gt=0)\n .order_by(\"drive_time\")[:4],\n }\n return render(request, \"landing/index.html\", context)","def results(self):\n pass","def update_query(self):\n text = self.lineedit.text()\n self.results = self.lookup(text)\n self.update_ui()\n self.copy_entry(self.table.currentRow(), self.table.currentColumn())","def process(self, query):\n response_text = self.fetch(query)\n content = self.get_content(response_text)\n return content","def run(self):\n rows = None\n if self.sql.startswith('select'):\n conn = self.table.connect()\n with conn.cursor() as curs:\n try:\n curs.execute(self.sql)\n except conn.DatabaseError as exc:\n error, = exc.args\n logging.error(f\"\"\"error executing {self.sql}:\n {error.code}\"\"\")\n self.excep = exc\n raise exc\n else:\n rows = curs.fetchall()\n # logging.critical(f\"\"\"executed {self.sql}\"\"\")\n self.result_exec = rows","def process_query_results(self, query_results: dict or list, analysis, observable: Observable) -> None:\n pass","def queryDB(db):\n def printunichars(row):\n \"\"\"Helper function for print utf 8 chars\"\"\"\n print(\"Title:\")\n print(row[0].encode('utf-8'))\n print(\"Body:\")\n print(row[1].encode('utf-8'))\n print(\"Ref:\")\n print(row[2].encode('utf-8'))\n print(\"Url:\")\n print(row[3].encode('utf-8'))\n \n cursor = db.cursor()\n cursor.execute(\"SET NAMES 'utf8';\")\n print(\"SET NAMES utf8;\")\n sql = \"SELECT Title FROM pages LIMIT 100\"\n cursor.execute(sql)\n rows = cursor.fetchall()\n for row in rows:\n printchars(row)","def get(self, request):\n return self.execute_query()"],"string":"[\n \"def execute_query(self):\\n try:\\n # get query and templates\\n query = self.request.data.get(\\\"query\\\", None)\\n templates = self.request.data.get(\\\"templates\\\", \\\"[]\\\")\\n registries = self.get_registries()\\n order_by_field = self.request.data.get(\\\"order_by_field\\\", \\\"\\\")\\n\\n if order_by_field:\\n order_by_field = order_by_field.split(\\\",\\\")\\n\\n if query is None:\\n content = {\\\"message\\\": \\\"Query should be passed in parameter.\\\"}\\n return Response(content, status=status.HTTP_400_BAD_REQUEST)\\n\\n # prepare query\\n raw_query = self.build_query(query, templates, registries)\\n # execute query\\n data_list = self.execute_json_query(raw_query, order_by_field)\\n # build and return response\\n return self.build_response(data_list)\\n\\n except Exception as api_exception:\\n content = {\\\"message\\\": str(api_exception)}\\n return Response(\\n content, status=status.HTTP_500_INTERNAL_SERVER_ERROR\\n )\",\n \"def query(self, query):\",\n \"def fluff_results():\\n # we get carriage returns from the form somehow. so split on them and join via\\n # regular newline. add a newline to avoid the annoying newline-at-end-of-file error.\\n sql = sql_decode(request.args[\\\"sql\\\"]).strip()\\n sql = \\\"\\\\n\\\".join(sql.splitlines()) + \\\"\\\\n\\\"\\n\\n dialect = request.args[\\\"dialect\\\"]\\n linted = lint(sql, dialect=dialect)\\n fixed_sql = \\\"\\\"\\n\\n # Fix can fail badly if linting fails so wrap in a try/except.\\n # See: https://github.com/sqlfluff/sqlfluff-online/issues/25\\n try:\\n fixed_sql = fix(sql, dialect=dialect)\\n except Exception:\\n pass\\n\\n return render_template(\\n \\\"index.html\\\",\\n results=True,\\n sql=sql,\\n dialect=dialect,\\n lint_errors=linted,\\n fixed_sql=fixed_sql,\\n )\",\n \"def query(self):\\n pass\",\n \"def query(self):\",\n \"def vis_results():\\n try:\\n uuid = session['uuid']\\n dm = DatabaseManager()\\n genes, diseases, uuiddb, query, genpanel, date \\\\\\n = dm.retreieve_zoekopdracht(uuid)\\n\\n return render_template(\\\"results.html\\\", genes=genes, diseases=diseases,\\n uuid=uuid, query=query, genpanel=genpanel,\\n date=date)\\n except KeyError:\\n flash(\\\"Please run a search or retrieve one from the archived \\\"\\n \\\"searches before visiting this page!\\\")\\n return redirect(url_for('search'))\",\n \"def results():\\n\\n queryName = request.form['query']\\n queryStars = request.form['stars']\\n \\n datasource = DataSource()\\n listOfRestaurantNames = datasource.searchRestaurantsByNameAndMinimumStars(queryName, queryStars)\\n restaurants = datasource.generateRestaurantObjects(listOfRestaurantNames[:15])\\n\\n return render_template('results.html', restaurants=restaurants)\",\n \"def show_results(ninja_id):\\n query = \\\"SELECT \\\" # get the ninja based on ninja id\\n data = {} # ninja id\\n mysql = # connect to mysql \\n ninja = mysql.query_db(query, data)\\n return render_template ('submitted_info.html', ninja = ninja) # [{ninja_data: \\\"stuff\\\"}]\",\n \"def _run_query(self):\",\n \"def search_results(request):\\n #key\\n\\n user_input = request.GET['q']\\n\\n people_objs = Person.objects.filter(Q(last__contains=user_input) | Q(\\n first__contains=user_input))\\n document_objs = Document.objects.filter(title__contains=user_input)\\n folder_objs = Folder.objects.filter(full__contains=user_input)\\n organization_objs = Organization.objects.filter(Q(name__contains=user_input)|Q(\\n location__contains=user_input))\\n obj_dict = {\\n 'people_objs': people_objs,\\n 'document_objs': document_objs,\\n 'folder_objs': folder_objs,\\n 'organization_objs': organization_objs,\\n 'query': user_input,\\n }\\n response = render(request, 'search_results.jinja2', obj_dict)\\n return response\",\n \"def query(self, **kwargs):\",\n \"def make_query(self):\",\n \"def handleQuery(self,query):\\n results = None\\n return results\",\n \"def submitQuery(self):\\r\\n #open connection, retrieve cursor and execute query\\r\\n\\r\\n try:\\r\\n connection = pymysql.connect(host='localhost', user='root',\\r\\n password='user', db='bank',\\r\\n charset='utf8mb4',\\r\\n cursorclass=pymysql.cursors.DictCursor)\\r\\n\\r\\n cursor = connection.cursor()\\r\\n cursor.execute(self.query.get())\\r\\n except (pymysql.OperationalError):\\r\\n errorMessage = \\\"Error\\\"\\r\\n showerror(\\\"Error\\\", errorMessage)\\r\\n return\\r\\n\\r\\n else: #obtain user requested info\\r\\n data = cursor.fetchall()\\r\\n fields = cursor.description\\r\\n cursor.close()\\r\\n connection.close()\\r\\n\\r\\n # clear results of last query\\r\\n self.panes.destroy()\\r\\n self.panes = Pmw.PanedWidget(self.frame.interior(),\\r\\n orient = \\\"vertical\\\")\\r\\n self.panes.pack(expand = YES, fill = BOTH)\\r\\n\\r\\n # create panel and label for each field\\r\\n for item in fields:\\r\\n## print(item)\\r\\n self.panes.add(item[0])\\r\\n label = Label(self.panes.pane(item[0]),\\r\\n text = item[0], relief = RAISED)\\r\\n label.pack(fill = X)\\r\\n\\r\\n # enter results into panes using labels\\r\\n for entry in data:\\r\\n\\r\\n for i in range(len(entry)):\\r\\n## print(entry)\\r\\n label = Label(self.panes.pane(fields[i][0]),\\r\\n text = entry[fields[i][0]], anchor = W, \\r\\n relief = GROOVE, bg = \\\"white\\\")\\r\\n label.pack(fill = X)\\r\\n\\r\\n self.panes.setnaturalsize()\",\n \"def postQuery(self):\\n pass\",\n \"def respond():\\n projects = db.execute(\\\"SELECT * FROM projects\\\")\\n return render_template(\\\"respond.html\\\", projects=projects)\",\n \"def update_results(self):\\n try:\\n results = self.shared_state[\\\"active_collection\\\"].query_source(\\n self.query_str\\n )\\n self.results = results\\n\\n except Exception:\\n self.results = {}\\n self.status_textcontrol.text = \\\"(invalid query)\\\"\\n else:\\n self.formatted_results = self._apply_default_format(self.results)\\n self.results_textcontrol.text = self.formatted_results\\n self.index = 0\\n self.status_textcontrol.text = (\\n f\\\"showing {len(self.results)} of \\\"\\n f\\\"{self.shared_state['active_collection'].df.shape[0]} records \\\"\\n f\\\"syntax: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-string-query.html#query-string-syntax)\\\"\\n )\",\n \"def render_POST(self, request, query=None):\\n # make a parser and parse the request\\n parser = qp.QueryParser(request)\\n if not query: query = request.content.read() \\n try: \\n # run the query locally\\n d = parser.runquery(self.db, query)\\n except Exception, e:\\n log.err(\\\"Failing query: \\\" + str(query))\\n log.err()\\n setResponseCode(request, e, 400)\\n return str(e)\\n else:\\n # and send the reply\\n request.setHeader('Content-type', 'application/json')\\n\\n if not query.strip().startswith('apply'):\\n # apply streams the output out itself\\n d.addCallback(lambda reply: (request, reply))\\n d.addCallback(self.send_reply)\\n d.addErrback(lambda x: self.send_error(request, x))\\n return server.NOT_DONE_YET\",\n \"def db_results(self, query):\\n try:\\n # Connect to database\\n db = psycopg2.connect(\\\"dbname=news\\\")\\n c = db.cursor()\\n # executing query and getting all results\\n c.execute(query)\\n db_res = c.fetchall()\\n # closing connection\\n db.close()\\n return db_res\\n except Error:\\n print (\\\"Error when attempting to connect to db\\\")\",\n \"def render_result():\\n\\n action = request.form['action']\\n session['visibility'] = request.form['vis'] == 'pub'\\n if(action == 'list'):\\n resp = utils.get_posts(g.graph,session['visibility'],session['page']['id'])\\n return render_template('display_posts.html', data = resp, next = resp['next'])\\n elif (action == 'add'): \\n return render_template('input_post.html')\\n else:\\n return redirect(url_for('error')) #TODO: add this page\",\n \"def _run_queries(self, persist):\\n self._mark_start()\\n self._run_query()\\n\\n # Check if we want to keep going.\\n if not persist:\\n self._compile_results()\\n return\\n\\n # Get the rest of the content.\\n while not self._done():\\n self._run_query()\\n\\n # Create the actual statements.\\n self._compile_results()\\n\\n # This is end of the loop, one way or another. Restore logging if it\\n # was redirected.\\n request_logger.unquiet()\\n util_logger.unquiet()\\n return\",\n \"def query(self) -> None:\\n raise NotImplementedError()\",\n \"def execute():\\n # print('Wow')\\n result = gui.controller.main('execute')\\n print(result)\\n\\n return render_template('results.html', data=json.dumps(result))\",\n \"def __call__(self, query=None, limit=1, uid=None):\\n\\n # Query prefix\\n prefix = \\\"select id, score, questionuser, question, tags, date, answeruser, object answer, reference from txtai where\\\"\\n\\n if uid is not None:\\n # ID query\\n query = f\\\"{prefix} id = '{uid}'\\\"\\n elif self.embeddings.scoring:\\n # Use custom tokenizer for word vector models\\n query = Tokenizer.tokenize(query)\\n\\n # Run search and build id query\\n result = self.embeddings.search(query, 1)[0] if query else {}\\n query = f\\\"\\\"\\\"\\n select id, {result.get('score')} score, questionuser, question, tags, date, answeruser, object answer, reference\\n from txtai\\n where id = '{result.get('id')}'\\n \\\"\\\"\\\"\\n else:\\n # Default similar clause query\\n query = f\\\"{prefix} similar('{query}')\\\"\\n\\n # Render results\\n for result in self.embeddings.search(query, limit):\\n # Show result\\n self.result(result, limit)\\n\\n self.console.print()\",\n \"def query(self):\\r\\n records = self.input()\\r\\n if self.to_investigate:\\r\\n records = self.investigate(records)\\r\\n post.log.info(\\\"Caching {} records for {}\\\".format(len(records), self.name))\\r\\n self.cache_records(records)\",\n \"def run_query(self):\\n return _run_query(self.query)\",\n \"def execute_query():\\n start_time = time.time()\\n\\n queries = request.json[\\\"queries\\\"]\\n random_command = request.json[\\\"random_command\\\"]\\n\\n \\\"\\\"\\\" Running the queries against the pre-loaded index. \\\"\\\"\\\"\\n output_dict = runner.run_queries(queries, random_command)\\n\\n \\\"\\\"\\\" Dumping the results to a JSON file. \\\"\\\"\\\"\\n with open(output_location, 'w') as fp:\\n json.dump(output_dict, fp)\\n\\n response = {\\n \\\"Response\\\": output_dict,\\n \\\"time_taken\\\": str(time.time() - start_time),\\n \\\"username_hash\\\": username_hash\\n }\\n return flask.jsonify(response)\",\n \"def search(self, query):\",\n \"def getresult(request):\\r\\n\\r\\n form = forms.SearchForm(request.POST)\\r\\n form.find_minmax_criteria(request.POST)\\r\\n\\r\\n if form.is_valid():\\r\\n\\r\\n headers, results = search.query(form.to_criteria(), form.cleaned_data['sector'], form.cleaned_data['exchange'], form.cleaned_data['show_result'])\\r\\n\\r\\n # show result in response\\r\\n return render_to_response('search/result.html', {\\r\\n 'headers': headers,\\r\\n 'results': results\\r\\n })\\r\\n\\r\\n else:\\r\\n # show error message in response\\r\\n return render_to_response('search/result-error.html', {\\r\\n 'message': 'Please enter details correctly.',\\r\\n 'form': form\\r\\n })\",\n \"def search():\\n query = input('Please enter your search query\\\\n')\\n # For now, we will just print the whole database\\n #db_actions.display()\\n db_actions.search(query)\",\n \"def index():\\n rows=db.execute(\\\"SELECT symbol, SUM(transactions) as amount FROM record WHERE userID=? GROUP BY symbol HAVING transactions\\\",session[\\\"user_id\\\"])\\n cash=db.execute(\\\"SELECT cash FROM users WHERE id=?\\\",session[\\\"user_id\\\"])\\n cash_=cash[0][\\\"cash\\\"]\\n\\n #store all the data into a dict so its easier to pass in to html\\n display=[]\\n total_share=0\\n for row in rows:\\n symbol=str(row[\\\"symbol\\\"])\\n print(symbol)\\n name=lookup(symbol)[\\\"name\\\"]\\n shares=int(row[\\\"amount\\\"])\\n price=float(lookup(symbol)[\\\"price\\\"])\\n total=float(shares) *price\\n total_share+=total\\n display.append({'symbol':symbol, 'name':name, 'shares':shares, 'price':price, 'total':total})\\n\\n total_money=total_share+cash[0][\\\"cash\\\"]\\n return render_template(\\\"index.html\\\",display=display,total_money=total_money,cash=cash_)\",\n \"def show_results():\\n\\n\\tuser_query = request.args.get(\\\"search\\\")\\n\\tsearch_activity = SearchActivity(user_id=session.get('user_id'), search_query=user_query, datetime = datetime.now())\\n\\n\\tdb.session.add(search_activity)\\n\\tdb.session.commit()\\n\\tsearch_items_not_filtered_list = user_search(user_query)\\n\\tfound_items = []\\n\\t\\n\\tfor item in search_items_not_filtered_list:\\n\\t\\tTaxonomy_obj = db.session.query(Taxonomy).filter(Taxonomy.path.like(\\\"%Food%\\\")).filter_by(category_node=item[u'categoryNode']).all()\\n\\t\\tfor obj in Taxonomy_obj:\\n\\t\\t\\tif item[u'categoryNode'] == obj.category_node:\\t\\n\\t\\t\\t\\tfound_items.append({\\n\\t\\t\\t\\t\\t\\\"name\\\": item.get(u'name', \\\"\\\"), \\n\\t\\t\\t\\t\\t\\\"item_id\\\": item.get(u'itemId', \\\"\\\"),\\n\\t\\t\\t\\t\\t\\\"category\\\": item.get(u'categoryPath', \\\"\\\"), \\n\\t\\t\\t\\t\\t\\\"sale_price\\\": format(item.get(u'salePrice', \\\"\\\"), \\\".2f\\\"), \\n\\t\\t\\t\\t\\t\\\"description\\\": unescape(item.get(u'shortDescription', \\\"\\\")), \\n\\t\\t\\t\\t\\t\\\"customer_rating_img\\\": item.get(u'customerRatingImage', \\\"\\\"),\\n\\t\\t\\t\\t\\t\\\"thumbnail_image\\\": item.get(u'thumbnailImage', \\\"\\\")\\n\\t\\t\\t\\t\\t})\\n\\t\\t\\t\\t\\n\\treturn render_template(\\\"searchresults.html\\\", found_items=found_items)\",\n \"def _run_query(self, query):\\n cursor = self.conn.cursor()\\n cursor.execute(query)\\n return cursor.fetchall()\",\n \"def search_results(request):\\n competencies = Competence.objects.all()\\n comp_user = request.user\\n comp_list_filer = []\\n comp_num = 0\\n for competence in competencies:\\n if competence.person == comp_user:\\n comp_list_filer.append((competence.title_of_competence, competence.level_of_competence))\\n comp_num = comp_num + 1\\n\\n q = request.GET.get('q')\\n add_list = get_vac(q)\\n competence_list = []\\n for vacancy_dict in add_list:\\n if Vacancy.objects.filter(title_of_vacancy=vacancy_dict['name']):\\n percent = get_percent(comp_list_filer, comp_num, vacancy_dict['name'])\\n obj = Vacancy.objects.get(title_of_vacancy=vacancy_dict['name'])\\n obj.percent = percent\\n obj.save()\\n continue\\n else:\\n percent = 0\\n if vacancy_dict['salary'] == 0:\\n vacancy = Vacancy.objects.create_vacancy(vacancy_dict['name'], vacancy_dict['description'],\\n vacancy_dict['city'],\\n 0, vacancy_dict['webSite'], percent)\\n else:\\n vacancy = Vacancy.objects.create_vacancy(vacancy_dict['name'], vacancy_dict['description'],\\n vacancy_dict['city'],\\n vacancy_dict['salary'], vacancy_dict['webSite'], percent)\\n for i in vacancy_dict['description'].split(\\\" \\\"):\\n competence_list.append(i)\\n graph_dict = {\\\"vac_name\\\": vacancy_dict['name'], \\\"com_name\\\": competence_list}\\n graph_add(graph_dict)\\n percent = get_percent(comp_list_filer, comp_num, vacancy_dict['name'])\\n obj = Vacancy.objects.get(title_of_vacancy=vacancy_dict['name'])\\n obj.percent = percent\\n obj.save()\\n competence_list = []\\n if q:\\n vacs = VacDocument.search().query(\\\"match\\\", title_of_vacancy=q)\\n vacs = vacs.sort({\\\"percent\\\": {\\\"order\\\": \\\"desc\\\"}})\\n else:\\n vacs = ''\\n return render(request, 'core/search-results.html', {'vacs': vacs, 'competencies': competencies})\",\n \"def record():\\n\\n try:\\n newcurs = g.conn.execute(\\\"\\\"\\\"SELECT * FROM record\\\"\\\"\\\")\\n except Exception:\\n print \\\"can not read record from database\\\"\\n return redirect('/error')\\n\\n info = []\\n for result in newcurs:\\n temp = [result['user_name'].encode(\\\"utf-8\\\"), result['message'].encode(\\\"utf-8\\\")]\\n info.append(temp)\\n newcurs.close()\\n\\n if not record:\\n return redirect('/')\\n\\n return render_template(\\\"record.html\\\", **locals())\",\n \"def all(request):\\n\\n posts = Post.objects.filter()\\n\\n print(\\\"made a query\\\")\\n return render(request, 'posts/all.html', {'posts':posts})\",\n \"def query(self):\\r\\n raise NotImplementedError\",\n \"def query3() :\",\n \"def search(request, query):\\n try:\\n if(query == ''):\\n query = request.GET['query']\\n posts = Post.search.query(query)\\n context = { 'posts': list(posts),'query': query, 'search_meta':posts._sphinx }\\n except:\\n context = { 'posts': list() }\\n\\n return render_to_response('search/search_results.html', context, context_instance=RequestContext(request))\",\n \"def results():\\n df = mdr.elo_ratings.sort_values([\\\"elo\\\", \\\"matches\\\"], ascending=False)\\n df[\\\"score\\\"] = (1 / (1 + 10**((1500 - df[\\\"elo\\\"]) / 400))) * 100\\n df = df[[\\\"items\\\", \\\"score\\\", \\\"matches\\\"]]\\n\\n html_formatted = df.to_html(classes=[\\\"table\\\", \\\"table-dark\\\", \\\"table-hover\\\"], index=False, float_format=\\\"%.1f\\\")\\n\\n return render_template('results.html', table=html_formatted)\",\n \"def create_response(self):\\n (paginator, page) = self.build_page()\\n\\n context = {\\n 'query': self.query,\\n 'form': self.form,\\n 'page': page,\\n 'paginator': paginator,\\n 'suggestion': None,\\n }\\n\\n if hasattr(self.results, 'query') and self.results.query.backend.include_spelling:\\n context['suggestion'] = self.form.get_suggestion()\\n\\n context.update(self.extra_context())\\n return render_to_response(self.template, context, context_instance=self.context_class(self.request))\",\n \"def post(self, request):\\n return self.execute_query()\",\n \"def run(self):\\n query = self.query\\n\\n # count before filtering\\n # self.cardinality = query.add_columns(self.columns[0].sqla_expr).count()\\n\\n self._set_column_filter_expressions()\\n self._set_global_filter_expression()\\n self._set_sort_expressions()\\n self._set_yadcf_data(query)\\n\\n # apply filters\\n query = query.filter(\\n *[e for e in self.filter_expressions if e is not None])\\n self.filtered_query = deepcopy(query)\\n\\n # self.cardinality_filtered = query.add_columns(\\n # self.columns[0].sqla_expr).count()\\n\\n # apply sorts\\n query = query.order_by(\\n *[e for e in self.sort_expressions if e is not None])\\n\\n # add paging options\\n length = int(self.params.get('length'))\\n if length >= 0:\\n query = query.limit(length)\\n elif length == -1:\\n pass\\n else:\\n raise(ValueError(\\n 'Length should be a positive integer or -1 to disable'))\\n query = query.offset(int(self.params.get('start')))\\n\\n # add columns to query\\n query = query.add_columns(\\n *[c.sqla_expr for c in self.columns])\\n\\n self.filtered_query = self.filtered_query.add_columns(\\n *[c.sqla_expr for c in self.columns])\\n\\n self.query = query\\n # fetch the result of the queries\\n column_names = [col.mData if col.mData else str(i)\\n for i, col in enumerate(self.columns)]\\n # self.results = [{k: v for k, v in zip(\\n # column_names, row)} for row in query.all()]\",\n \"def do_query(self, query):\\n query = query.replace('\\\\n', ' ')\\n self.cursor.execute(query)\\n return self.cursor.fetchall()\",\n \"def index():\\n parsed = database.mongodb[db_name].find({'parsed': True}).limit(100)\\n\\n return render_template('index.html', data=list(parsed))\",\n \"def process_results(result, title=\\\"\\\", doWrite=True, query=\\\"\\\"):\\n\\n\\tif not result or not result.returns_rows:\\n\\t\\tprint \\\"-> 0 records returned\\\"\\n\\t\\tprint result\\n\\t\\treturn\\n\\n\\tdoPrint = True\\n\\n\\t# get column names\\n\\tcols = result.keys()\\n\\n\\t# build template format string\\n\\ttemplate = \\\"\\\"\\n\\tfor i in range(len(cols)):\\n\\t\\ttemplate += \\\"{%s:40}\\\" % i\\n\\ttemplate = template.replace(\\\"}{\\\", \\\"}|{\\\")\\n\\n\\t# open output file\\n\\tif doWrite:\\n\\t\\tresults_dir = DATA_PATH + \\\"query_results/\\\"\\n\\t\\tif not os.path.exists(results_dir):\\n\\t\\t\\tos.makedirs(results_dir)\\n\\n\\t\\tnow = datetime.now().strftime(\\\"%Y_%m_%d__%I_%M_%p\\\")\\n\\t\\tfilename = results_dir + \\\"query_results_\\\" + now\\n\\t\\t\\n\\t\\ttxt = open(filename+\\\".txt\\\", 'w')\\n\\t\\tcsv = open(filename+\\\".csv\\\", 'w')\\n\\n\\t\\t# print query\\n\\t\\ttxt.write(query + \\\"\\\\n\\\")\\n\\t\\ttxt.write(\\\"=\\\" * len(query) + \\\"\\\\n\\\")\\n\\t\\tcsv.write(query + \\\"\\\\n\\\")\\n\\n\\t\\t# print header\\n\\t\\ttxt.write(template.format(*tuple(cols)) + \\\"\\\\n\\\") # header\\n\\t\\ttxt.write(\\\"-\\\"*41*len(cols) + \\\"\\\\n\\\")\\n\\t\\tcsv.write('|'.join(cols) + \\\"\\\\n\\\")\\n\\n\\t# print records\\n\\tnumRecs = 0\\n\\tfor row in result:\\n\\t\\t# ask user if they want ot stop printing after 100 records\\n\\t\\tif numRecs == 10:\\n\\t\\t\\ti = raw_input(\\\"10 records printed. Continue printing records? (y/N) \\\")\\n\\t\\t\\tif i.lower() not in [\\\"y\\\", \\\"yes\\\"]:\\n\\t\\t\\t\\tdoPrint = False\\n\\t\\t\\n\\t\\tif doPrint:\\n\\t\\t\\tscreen_write_row(row, title)\\n\\n\\t\\tif doWrite:\\n\\t\\t\\ttxt_write_row(txt, template, row)\\n\\t\\t\\tcsv_write_row(csv, row)\\n\\n\\t\\t# count records returned\\n\\t\\tnumRecs += 1\\n\\n\\t# show number of records returned\\n\\tprint \\\"-> %s records returned\\\" % numRecs\\n\\tif doWrite:\\n\\t\\ttxt.write(\\t\\\"-> %s records returned\\\" % numRecs)\\n\\n\\tif doWrite:\\n\\t\\ttxt.flush()\\n\\t\\ttxt.close()\",\n \"def send_results(self):\\n # Send total records count for the progress bar\\n url_count = self.session.query(Uurl).count()\\n total_records = url_count + self.session.query(Session).count()\\n self.total_count_signal.emit(total_records)\\n\\n url_query = self.session.query(Uurl).all()\\n result_string = settings.URL_OUTPUT_HEADING\\n for q in url_query:\\n result_string = result_string + \\\"\\\\n\\\" + str(q)\\n if not (q.id % settings.RESULT_SIGNAL_SIZE):\\n self.update_progress_signal.emit(q.id, result_string)\\n result_string = \\\"\\\"\\n # Send remaining results\\n self.update_progress_signal.emit(url_count, result_string)\\n logging.info(\\\"All urls sent to the GUI\\\")\\n # Printing urls completed\\n self.step_completed_signal.emit(2)\\n\\n # Id of the last element inserted. It is used to calculate progressbar\\n # value\\n last_id = self.session.query(Uurl.id).order_by(\\n Uurl.id.desc()).first()[0]\\n\\n self.update_progress_signal.emit(last_id, \\\"\\\\n\\\\n\\\")\\n\\n result_string = settings.SESSION_OUTPUT_HEADING\\n\\n # Send all sessions back to GUI\\n session_query = self.session.query(Session).all()\\n for s in session_query:\\n result_string = result_string + \\\"\\\\n\\\" + str(s)\\n if not ((last_id + s.id - 1) % settings.RESULT_SIGNAL_SIZE):\\n self.update_progress_signal.emit(\\n last_id + s.id - 1, result_string)\\n result_string = \\\"\\\"\\n self.update_progress_signal.emit(total_records - 1, result_string)\\n logging.info(\\\"All sessions sent to the GUI\\\")\\n # Printing sessions completed\\n self.step_completed_signal.emit(3)\\n\\n self.number_of_sessions_signal.emit(\\n self.session.query(Session).count())\",\n \"def _(event):\\n try:\\n self.view_model.update_results()\\n except Exception:\\n self.view_model.status_textcontrol.text = \\\"(no results available)\\\"\",\n \"def ng_query(self, request, *args, **kwargs):\\r\\n return self.build_json_response(self.get_queryset())\",\n \"def query(request):\\r\\n\\t# initialize form\\r\\n\\tform = featureSelectionForm()\\r\\n\\t# query output for displaying\\r\\n\\toutput = []\\r\\n\\t# preset variables\\r\\n\\tstring_id_series = []\\r\\n\\t# Mongo query to be defined\\r\\n\\tquery = ''\\r\\n\\tif request.method == 'POST' :\\r\\n\\t\\tform = featureSelectionForm(request.POST)\\r\\n\\t\\tif form.is_valid():\\r\\n\\t\\t\\t# Presumed variables\\r\\n\\t\\t\\t# collection_name = \\\"RNA_brain_gender-F_AD-vs-Control\\\"\\r\\n\\t\\t\\t# feature_symbols_in_interest = ['APOE', 'BIN1', 'CLU']\\r\\n\\t\\t\\t# way_to_choose_probe = \\\"fold change\\\"\\r\\n\\t\\t\\t### Get variables from POST\\r\\n\\t\\t\\tcollection_name = \\\"%s_%s_%s-%s_%s\\\" % (request.POST[\\\"dataType\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\trequest.POST[\\\"tissue\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\trequest.POST[\\\"category\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\trequest.POST[\\\"group\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\trequest.POST[\\\"comparison\\\"])\\r\\n\\t\\t\\t\\\"\\\"\\\"\\r\\n\\t\\t\\t\\tWe should split POST[\\\"featureInput\\\"] here\\r\\n\\t\\t\\t\\\"\\\"\\\"\\r\\n\\t\\t\\t# import pdb; pdb.set_trace();\\r\\n\\t\\t\\tfeature_symbols_in_interest = split_feature_input_to_list(request.POST[\\\"featureInput\\\"])\\r\\n\\r\\n\\t\\t\\tway_to_choose_probe = request.POST[\\\"probeSelectionMethod\\\"]\\r\\n\\r\\n\\t\\t\\ttest_stat_output_dict = {}\\r\\n\\r\\n\\t\\t\\tall_datasets = test_stat_client.get_all_datasets(collection_name)\\r\\n\\r\\n\\t\\t\\ttest_statistics = list(test_stat_client.get_all_for_this_category(collection_name))\\r\\n\\r\\n\\t\\t\\ttest_statistics = pd.DataFrame(test_statistics)\\r\\n\\r\\n\\t\\t\\tfor dataset in all_datasets:\\r\\n\\t\\t\\t\\t# Filter 1 - dataset accession & features in interest\\r\\n\\t\\t\\t\\tif request.POST[\\\"dataType\\\"] == \\\"RNA\\\":\\r\\n\\t\\t\\t\\t\\tfilt_ind = (test_statistics['dataset_accession'] == dataset) & (test_statistics['symb'].isin(feature_symbols_in_interest))\\r\\n\\t\\t\\t\\telif request.POST[\\\"dataType\\\"] == \\\"protein\\\":\\r\\n\\t\\t\\t\\t\\tsymbol_series = test_statistics['symb'].apply(extract_gene_symbol_from_protein_name)\\r\\n\\t\\t\\t\\t\\tfilt_ind = (test_statistics['dataset_accession'] == dataset) & (symbol_series.isin(feature_symbols_in_interest))\\r\\n\\r\\n\\t\\t\\t\\ttest_stat_df = test_statistics[filt_ind]\\r\\n\\r\\n\\t\\t\\t\\t# Filter 2 - remove duplicates\\r\\n\\t\\t\\t\\t\\\"\\\"\\\"\\r\\n\\t\\t\\t\\t\\tHere we provide options for user to choose how to select a probe when \\r\\n\\t\\t\\t\\t\\tmultiple probes are corresponding to one feature\\r\\n\\t\\t\\t\\t\\\"\\\"\\\"\\r\\n\\r\\n\\t\\t\\t\\tif way_to_choose_probe == \\\"fold change\\\":\\r\\n\\t\\t\\t\\t\\ttest_stat_df = filtered_duplicate_by(test_stat_df, by='fc', group_index=['symb'])\\r\\n\\r\\n\\t\\t\\t\\telif way_to_choose_probe == \\\"limma p value\\\" : \\r\\n\\t\\t\\t\\t\\ttest_stat_df = filtered_duplicate_by(test_stat_df, by='lp', group_index=['symb'])\\r\\n\\r\\n\\t\\t\\t\\telif way_to_choose_probe == \\\"t test p value\\\" :\\r\\n\\t\\t\\t\\t\\ttest_stat_df = filtered_duplicate_by(test_stat_df, by='tp', group_index=['symb'])\\r\\n\\r\\n\\t\\t\\t\\tif test_stat_df.empty:\\r\\n\\t\\t\\t\\t\\tall_datasets.remove(dataset)\\r\\n\\t\\t\\t\\t\\tcontinue\\r\\n\\t\\t\\t\\t# Split dataframe for stat table display and graph display\\r\\n\\t\\t\\t\\t# stat_table = test_stat_df.drop(['eval', 'dsl'], axis=1)\\r\\n\\t\\t\\t\\tstat_table = test_stat_df.drop(['eval'], axis=1)\\r\\n\\t\\t\\t\\t# import pdb; pdb.set_trace()\\r\\n\\t\\t\\t\\tstat_table['entrez_gene_id'] = stat_table.apply(from_symbol_to_entrez_gene_id, axis=1)\\r\\n\\t\\t\\t\\tstat_table['string_id'] = from_single_symbol_to_string_id(stat_table['symb'])\\r\\n\\t\\t\\t\\tstring_id_series = stat_table['string_id']\\r\\n\\t\\t\\t\\t\\r\\n\\t\\t\\t\\t# import pdb; pdb.set_trace()\\r\\n\\r\\n\\t\\t\\t\\tstat_table_output = stat_table.to_dict(outtype='records')\\r\\n\\r\\n\\t\\t\\t\\t# import pdb; pdb.set_trace()\\r\\n\\t\\t\\t\\ttest_stat_output_dict.update({dataset : stat_table_output})\\r\\n\\r\\n\\r\\n\\r\\n\\t\\t\\treturn render(request, 'feature_stat.html',\\r\\n\\t\\t\\t\\t\\t\\t{\\r\\n\\t\\t\\t\\t\\t\\t\\t'dataset_names' : all_datasets,\\r\\n\\t\\t\\t\\t\\t\\t\\t'test_stat' : test_stat_output_dict,\\r\\n\\t\\t\\t\\t\\t\\t\\t'way_to_choose_probe' : way_to_choose_probe,\\r\\n\\t\\t\\t\\t\\t\\t\\t'datatype' : request.POST[\\\"dataType\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t'tissue' : request.POST[\\\"tissue\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t'category' : request.POST[\\\"category\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t'group' : request.POST[\\\"group\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t'comparison' : request.POST[\\\"comparison\\\"],\\r\\n\\t\\t\\t\\t\\t\\t\\t'features' : generate_mulivariable_series_from_list(feature_symbols_in_interest),\\r\\n\\t\\t\\t\\t\\t\\t\\t'string_url_id_component' : generate_string_id_get_query_from_list(string_id_series)\\r\\n\\t\\t\\t\\t\\t\\t})\\r\\n\\telse:\\t\\t\\r\\n\\t\\treturn render(request, 'query.html', {\\r\\n\\t\\t\\t'form' : form\\r\\n\\t\\t})\",\n \"def submit_query(self, username, password):\\n\\n #username = os.environ['NEWSREADER_USERNAME']\\n #password = os.environ['NEWSREADER_PASSWORD']\\n payload = {'id': self.query}\\n \\n endpoint_url = self.endpoint_stub_url.format(action=self.action)\\n print \\\"\\\\n\\\\n**New CRUD query**\\\"\\n print endpoint_url, payload\\n t0 = time.time()\\n try:\\n response = requests.get(endpoint_url, auth=(username, password),\\n params=payload)\\n except Exception as e:\\n print \\\"Query raised an exception\\\"\\n print type(e)\\n t1 = time.time()\\n total = t1-t0\\n raise QueryException(\\\"Query raised an exception: {0}\\\".format(type(e).__name__))\\n else:\\n t1 = time.time()\\n total = t1-t0\\n print \\\"Time to return from query: {0:.2f} seconds\\\".format(total)\\n print \\\"Response code: {0}\\\".format(response.status_code)\\n print \\\"From cache: {0}\\\".format(response.from_cache)\\n\\n #print response.content\\n \\n if response and (response.status_code == requests.codes.ok):\\n self.json_result = {\\\"content\\\":response.content}\\n self.clean_json = self.json_result\\n else:\\n raise QueryException(\\\"Response code not OK: {0}\\\".format(response.status_code))\",\n \"def query1(request):\\n with connection.cursor() as cursor:\\n cursor.execute('SELECT * FROM (\\\\\\n example_usuario as u \\\\\\n JOIN\\\\\\n example_pessoa as p \\\\\\n ON u.cpf_pessoa_id = p.cpf)')\\n result = named_tuple_fetchall(cursor)\\n\\n template = loader.get_template('example/query1.html')\\n context = {'query1_result_list': result, }\\n\\n return HttpResponse(template.render(context, request))\",\n \"def index():\\n\\twith get_db().cursor() as cursor :\\n\\t\\tcursor.execute(\\\"SELECT *, (SELECT COUNT(*) FROM `cheer` WHERE ask_id = ask.id) AS cheer_cnt FROM `ask`\\\")\\n\\t\\tresult = cursor.fetchall()\\n\\n\\treturn render_template('main.html',\\n\\t\\tdataset=result,\\n\\t)\",\n \"def search(request):\\r\\n assert isinstance(request, HttpRequest)\\r\\n return render(\\r\\n request,\\r\\n 'app/geral/resultados.html',\\r\\n context_instance=RequestContext(request,\\r\\n {\\r\\n 'title': 'Colmeia | Resultados',\\r\\n 'year': datetime.now().year,\\r\\n })\\r\\n )\",\n \"def run_query(cur, query, show_results=False):\\n num_rows = cur.execute(query)\\n print('the query returned {} rows'.format(num_rows))\\n if show_results:\\n for row in cur.fetchall():\\n print(row)\",\n \"def generate_query(self):\\n return\",\n \"def display_results():\\n pass\",\n \"def query3(request):\\n query = \\\"SELECT pessoa_tutorada.nome as tutorado, pessoa_tutora.nome as tutor \\\\\\n FROM example_usuario as usuario_tutelado \\\\\\n JOIN \\\\\\n example_tutelamento as tutelamento \\\\\\n ON usuario_tutelado.id_usuario = tutelamento.id_usuario_tutelado_id \\\\\\n JOIN \\\\\\n example_usuario as usuario_tutor \\\\\\n ON usuario_tutor.id_usuario = tutelamento.id_tutor_id \\\\\\n JOIN example_pessoa as pessoa_tutorada\\\\\\n ON pessoa_tutorada.cpf = usuario_tutelado.cpf_pessoa_id \\\\\\n JOIN \\\\\\n example_pessoa as pessoa_tutora \\\\\\n ON pessoa_tutora.cpf = usuario_tutor.cpf_pessoa_id\\\"\\n\\n with connection.cursor() as cursor:\\n cursor.execute(query)\\n result = named_tuple_fetchall(cursor)\\n\\n # remove duplicates\\n result = list(set(result))\\n\\n template = loader.get_template('example/query3.html')\\n context = {'query3_result_list': result, }\\n\\n return HttpResponse(template.render(context, request))\",\n \"def result_page():\\n results = session.get('results')\\n points = 0\\n if results:\\n for k,p in results.items():\\n points += p['points']\\n return render_template('results.html', results=results, points=points),\",\n \"def get_query_results(self, conn, sql):\\n\\n cur = conn.cursor()\\n cur.execute(sql)\\n yield from cur.fetchall()\",\n \"def submitForm():\\n try:\\n rec = db.session.query(Rec)\\n StockCode = request.form.get('prod')\\n this_rec = Rec.query.filter_by(StockCode=StockCode).first()\\n logger.debug(\\\"Successfully loaded data.\\\")\\n return render_template('index.html', recs=rec, this_rec=this_rec)\\n except:\\n traceback.print_exc()\\n logger.warning(\\\"Not able to get recommendations, error page returned\\\")\\n return render_template('error.html')\",\n \"def execute_queries():\\n fetch_job_listings(engine)\\n update_job_listing(engine)\",\n \"def show_results():\\n\\n if request.args.get('cheery'):\\n msg_type = \\\"cheery\\\"\\n message = \\\"\\\"\\\"\\n Life’s like a movie. Write your own ending.\\n \\\"\\\"\\\"\\n auth = \\\"— Kermit the Frog\\\"\\n elif request.args.get('dreary'):\\n msg_type = \\\"dreary\\\"\\n message = \\\"\\\"\\\"\\n Bad days happen to everyone, but when one happens to you, just\\n keep doing your best and never let a bad day make you feel bad\\n about yourself.\\n \\\"\\\"\\\"\\n author = \\\"— Big Bird\\\"\\n elif request.args.get('honest'):\\n msg_type = \\\"honest\\\"\\n message = \\\"\\\"\\\"\\n Who care if me eat carrot or collard greens? Me also like broccoli\\n and lettuce and lima beans. Me still Cookie Monster. That not a sham.\\n \\\"\\\"\\\"\\n author = \\\"— Cookie Monster\\\"\\n\\n return render_template(\\\"results.html\\\",\\n message=message,\\n author=author,\\n msg_type=msg_type)\",\n \"def search_results():\\n skip = int(flask.request.args.get(\\\"skip\\\", \\\"0\\\"))\\n limit = int(flask.request.args.get(\\\"limit\\\", \\\"20\\\"))\\n\\n obj = {}\\n\\n # query : will be event kit in case of triage information\\n uidstr = flask.request.args.get(\\\"query\\\", None)\\n\\n if uidstr == None:\\n obj[\\\"error\\\"] = \\\"Missing search ID\\\"\\n\\n uidstr = json.loads(uidstr)\\n\\n obj[\\\"query\\\"] = {}\\n obj[\\\"query\\\"][\\\"uid\\\"] = uidstr\\n obj[\\\"clips\\\"] = []\\n states = backend.get_search_sessions()\\n obj[\\\"sessions\\\"] = []\\n for astate in states:\\n obj[\\\"sessions\\\"].append(str(astate))\\n try:\\n uid = uuid.UUID(uidstr)\\n state = backend.get_iqr_search_state(uid)\\n # use the uid of the state and get the information from the database\\n col = str(state.uuid)\\n obj[\\\"collection\\\"] = col\\n searchdb[col].ensure_index([(\\\"model_id\\\", pymongo.ASCENDING),(\\\"probability\\\", pymongo.DESCENDING) ])\\n # Force probabilities\\n obj[\\\"positives\\\"] = list(state.positives)\\n obj[\\\"negatives\\\"] = list(state.negatives)\\n log = \\\"\\\"\\n for id in state.positives:\\n # log = log + \\\"Found %d\\\"%(searchdb[col].find({\\\"model_id\\\" : \\\"FUSION\\\", \\\"clip_id\\\" : id}).count()) + \\\", \\\"\\n # res = searchdb[col].update({\\\"model_id\\\" : \\\"FUSION\\\", \\\"clip_id\\\" : id}, {\\\"$set\\\" : { \\\"probability\\\" : 1.0}})\\n # log = log + \\\"Done %d\\\"%id + \\\", \\\"\\n news = searchdb[col].find_one({\\\"model_id\\\" : \\\"FUSION\\\", \\\"clip_id\\\" : id})\\n news[\\\"probability\\\"] = 1.0001\\n searchdb[col].save(news)\\n log = log + \\\"Now : \\\" + str(news)\\n\\n\\n for id in state.negatives:\\n # log = log + \\\"Found %d\\\"%(searchdb[col].find({\\\"model_id\\\" : \\\"FUSION\\\", \\\"clip_id\\\" : id}).count()) + \\\", \\\"\\n # res = searchdb[col].update({\\\"model_id\\\" : \\\"FUSION\\\", \\\"clip_id\\\" : id}, {\\\"$set\\\" : { \\\"probability\\\" : 0.0}})\\n # log = log + \\\"Done %d\\\"%id + \\\", \\\"\\n news = searchdb[col].find_one({\\\"model_id\\\" : \\\"FUSION\\\", \\\"clip_id\\\" : id})\\n news[\\\"probability\\\"] = 0.0\\n searchdb[col].save(news)\\n log = log + \\\"Now : \\\" + str(news)\\n\\n obj[\\\"log\\\"] = log\\n\\n allres = searchdb[col].find({\\\"model_id\\\" : \\\"FUSION\\\"}).sort([(\\\"probability\\\", pymongo.DESCENDING)]).skip(skip).limit(limit)\\n rank = skip + 1\\n for one in allres:\\n aclip = {}\\n aclip[\\\"score\\\"] = one[\\\"probability\\\"]\\n aclip[\\\"id\\\"] = \\\"HVC\\\" + str(one[\\\"clip_id\\\"]).zfill(6)\\n clipobj = db[\\\"clips\\\"].find_one({\\\"id\\\" : \\\"HVC\\\" + str(one[\\\"clip_id\\\"]).zfill(6)},{\\\"duration\\\" : 1})\\n aclip[\\\"duration\\\"] = clipobj[\\\"duration\\\"]\\n aclip[\\\"rank\\\"] = rank\\n rank = rank + 1\\n obj[\\\"clips\\\"].append(aclip)\\n obj[\\\"count\\\"] = len(obj[\\\"clips\\\"])\\n\\n except Exception as e:\\n obj[\\\"error\\\"] = str(type(e)) + \\\": \\\" + str(e)\\n return jsonify(obj)\\n\\n obj[\\\"next\\\"] = \\\"http://localhost:5003/iqr/search_results?\\\" + urllib.urlencode({\\\"uid\\\" : uid, \\\"skip\\\" : skip+limit } )\\n return jsonify(obj)\",\n \"def create_response(self):\\n (paginator, page) = self.build_page()\\n\\n context = {\\n 'query': self.query,\\n 'form': self.form,\\n 'page': page,\\n 'paginator': paginator,\\n 'suggestion': None,\\n }\\n\\n if self.results and hasattr(self.results, 'query') and self.results.query.backend.include_spelling:\\n context['suggestion'] = self.form.get_suggestion()\\n\\n context.update(self.extra_context())\\n return render_to_response(self.template, \\\\\\n context, \\\\\\n context_instance=self.context_class(self.request), \\\\\\n mimetype=\\\"application/json\\\")\",\n \"def query(env):\\n if app.config['ENABLE_QUERY']:\\n envs = environments()\\n check_env(env, envs)\\n\\n form = QueryForm(meta={\\n 'csrf_secret': app.config['SECRET_KEY'],\\n 'csrf_context': session})\\n if form.validate_on_submit():\\n if form.endpoints.data == 'pql':\\n query = form.query.data\\n elif form.query.data[0] == '[':\\n query = form.query.data\\n else:\\n query = '[{0}]'.format(form.query.data)\\n result = get_or_abort(\\n puppetdb._query,\\n form.endpoints.data,\\n query=query)\\n return render_template('query.html',\\n form=form,\\n result=result,\\n envs=envs,\\n current_env=env)\\n return render_template('query.html',\\n form=form,\\n envs=envs,\\n current_env=env)\\n else:\\n log.warn('Access to query interface disabled by administrator..')\\n abort(403)\",\n \"def index(request, template_name='index.html'):\\n\\n context_dict = {}\\n model = Uni\\n column_headers = ['rank', 'name', 'location', 'city', 'scores_overall']\\n check_fields = ['scores_citations', 'scores_industry_income', 'scores_international_outlook', 'scores_research', 'scores_teaching', 'stats_student_staff_ratio', 'stats_pc_intl_students', 'stats_number_students', 'quality_of_life_index', 'safety_index', 'cost_of_living_index', 'climate_index' ]\\n \\n uni_main = Uni.objects.values(*column_headers)\\n \\n # subject filter\\n if request.GET.get('sub_drop'):\\n subject_filter = request.GET.get('sub_drop')\\n if subject_filter == 'All':\\n uni_main = Uni.objects.values(*column_headers)\\n\\n elif subject_filter == 'Computer Science':\\n model = Uni_cs\\n uni_main = Uni_cs.objects.values(*column_headers)\\n elif subject_filter == 'Engineering':\\n model = Uni_eng\\n uni_main = Uni_eng.objects.values(*column_headers)\\n else:\\n uni_main = Uni.objects.values(*column_headers)\\n\\n\\n # Locations filter\\n if request.GET.get('loc_drop'):\\n location_filter = request.GET.get('loc_drop')\\n if location_filter == 'All':\\n listings = uni_main\\n\\n else:\\n listings = uni_main.filter(location=location_filter)\\n else:\\n listings = uni_main\\n\\n # advanced search\\n qs = listings\\n if request.GET.getlist('v_scores[]'):\\n scorevar = request.GET.getlist('v_scores[]')\\n if scorevar != ['0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0']:\\n for i in range (0, len(scorevar)):\\n if scorevar[i]=='0':\\n check_fields[i]='0' \\n check_fields = [x for x in check_fields if x != '0']\\n checkvar = check_fields\\n gen_rank(checkvar,scorevar,model)\\n column_headers[0] = 'new_rank'\\n values = column_headers + checkvar\\n qs = listings.values(*values).order_by('new_rank')\\n listings = qs\\n uni_name = listings\\n\\n paginator = Paginator(listings, 10)\\n page = request.GET.get('page')\\n try:\\n uni_list = paginator.page(page) \\n except PageNotAnInteger: \\n uni_list = paginator.page(1) \\n except EmptyPage: \\n uni_list = paginator.page(paginator.num_pages)\\n\\n context_dict = {'uni_list': uni_list, 'uni_name': uni_name, 'loc_list' : Uni.objects.order_by('location').values_list('location', flat=True).distinct()}\\n\\n # Render the HTML template index.html with the data in the context variable\\n# return render(request, 'index.html', context=context)\\n return render(request, template_name, context_dict)\",\n \"def results_overview():\\n\\n if request.method == \\\"POST\\\":\\n # clean out all unwanted storage\\n if _pool:\\n _pool.terminate()\\n del _drivers[:]\\n \\n return redirect(url_for('upload.upload'))\\n\\n # GET\\n \\n # Captures the global drivers variable\\n global _drivers\\n\\n processType = g.processType\\n coreFactor = g.coreFactor\\n\\n if processType == 'parallel':\\n current_app.logger.info(time.ctime() + \\\"\\\\tProcess pool with %s processes initialized for execution\\\" % coreFactor)\\n results = _pool.map(_get_result, _drivers)\\n else:\\n results = [_get_result(driver) for driver in _drivers]\\n\\n return render_template('checks/results_overview.html', results=results)\",\n \"def search():\\r\\n\\r\\n # Ensure parameter is present\\r\\n if not request.args.get(\\\"q\\\"):\\r\\n raise RuntimeError(\\\"missing search string\\\")\\r\\n\\r\\n # Query db with the string LIMIT result to 10\\r\\n # TODO\\r\\n\\r\\n # send back as json\\r\\n # TODO\\r\\n\\r\\n return jsonify({})\",\n \"def post(self, request, *args, **kwargs):\\n self.form = self.get_form()\\n self.form.full_clean()\\n results = self.get_queryset()\\n nb_results = results.count()\\n first_results = results[:10]\\n site = get_current_site(self.request)\\n querystring = self.get_form_data().urlencode()\\n scheme = 'https'\\n search_url = reverse('search_view')\\n full_url = '{scheme}://{domain}{search_url}?{querystring}'.format(\\n scheme=scheme,\\n domain=site.domain,\\n search_url=search_url,\\n querystring=querystring)\\n results_body = render_to_string('emails/search_results.txt', {\\n 'user_name': self.request.user.full_name,\\n 'aids': first_results,\\n 'nb_results': nb_results,\\n 'full_url': full_url,\\n 'scheme': scheme,\\n 'domain': site.domain,\\n })\\n send_mail(\\n self.EMAIL_SUBJECT,\\n results_body,\\n settings.DEFAULT_FROM_EMAIL,\\n [self.request.user.email],\\n fail_silently=False)\\n return HttpResponse('')\",\n \"def index(request):\\n\\n pres = ParseResult.objects.filter()[:10]\\n count = ParseResult.objects.filter().count()\\n\\n template = loader.get_template('index.html')\\n context = RequestContext(request, {\\n 'parseresults': pres,\\n 'parsecount': count\\n })\\n return HttpResponse(template.render(context))\",\n \"def get(self):\\n if 'wipe' in self.request.path_url:\\n InboundRequest.wipe()\\n self.response.write('Db wiped')\\n return\\n\\n # log out last 10 requests\\n data = InboundRequest.get_latest()\\n\\n resultList = []\\n for item in data:\\n headers = ''\\n header_list = item.request_headers.split('\\\\r\\\\n')\\n\\n # try format if json\\n body = item.request_body\\n try:\\n json_body = json.loads(item.request_body)\\n body = json.dumps(json_body, indent=2, separators=(',', ': '))\\n except:\\n #logging.info('not in json')\\n pass\\n\\n resultfields = {'ts': item.time_stamp, 'host_url': item.request_host_url, 'path': item.request_path,\\n 'query_params': item.request_query_params, 'headers': header_list, 'body': body}\\n resultList.append(resultfields)\\n\\n template_values = {\\n 'number_returned': len(data),\\n 'results': resultList\\n }\\n self.render_template('index.html', template_values)\",\n \"def _run_async_query(self, context):\\n url = self._build_url(\\\"/_search\\\")\\n request = self._build_request(0, -1)\\n resp = self._cb.post_object(url, body=request)\\n result = resp.json()\\n self._total_results = result[\\\"num_found\\\"]\\n self._count_valid = True\\n results = result.get(\\\"results\\\", [])\\n return [self._doc_class(self._cb, item[\\\"id\\\"], item) for item in results]\",\n \"def _run_async_query(self, context):\\n url = self._build_url(\\\"/_search\\\")\\n request = self._build_request(0, -1)\\n resp = self._cb.post_object(url, body=request)\\n result = resp.json()\\n self._total_results = result[\\\"num_found\\\"]\\n self._count_valid = True\\n results = result.get(\\\"results\\\", [])\\n return [self._doc_class(self._cb, item[\\\"id\\\"], item) for item in results]\",\n \"def execute_query(self, *args, **kwargs):\",\n \"def execQuery():\\n\\n if request.method == \\\"POST\\\":\\n result = exec_query(request)\\n if result:\\n status = 200\\n else:\\n status = 400\\n return result, status # HTTP Status Created [201]\",\n \"def search_results(request):\\n\\n query = None\\n results_list = ()\\n filtered_products = Product.objects.filter(discontinued=False)\\n filtered_programmes = Programme.objects.filter(discontinued=False)\\n filtered_posts = Post.objects.filter(status=1)\\n\\n if 'q' in request.GET:\\n query = request.GET['q']\\n if not query:\\n messages.warning(request,\\n \\\"You didn't enter any search criteria!\\\")\\n return redirect(reverse('search_results'))\\n\\n products = filtered_products.filter(Q(name__icontains=query) | Q(\\n description__icontains=query))\\n programmes = filtered_programmes.filter(Q(\\n name__icontains=query) | Q(description__icontains=query))\\n posts = filtered_posts.filter(Q(title__icontains=query))\\n\\n results_list = list(chain(products, programmes, posts))\\n\\n context = {\\n 'search_term': query,\\n 'results_list': results_list,\\n }\\n\\n return render(request, 'home/search.html', context)\",\n \"def index():\\n response.flash=\\\"Welcome to TheChef\\\"\\n \\\"\\\"\\\"recepies = db(db.recepies).select(orderby=~db.recepies.pub_date)\\n return dict(recepies=recepies) \\\"\\\"\\\"\\n if len(request.args): page=int(request.args[0])\\n else: page=0\\n items_per_page=9\\n limitby=(page*items_per_page,(page+1)*items_per_page+1)\\n rows=db(db.recepies).select(orderby=~db.recepies.pub_date,limitby=limitby)\\n return dict(rows=rows,page=page,items_per_page=items_per_page)\",\n \"def refresh():\\n DB.drop_all()\\n DB.create_all()\\n results = get_results()\\n for i, result in enumerate(results):\\n record = Record(id=i, datetime=result[0], value=result[1])\\n DB.session.add(record)\\n DB.session.commit()\\n return redirect(\\\"/\\\")\",\n \"def search_results(self):\\r\\n route_name = self.request.matched_route.name\\r\\n mdict = self.matchdict\\r\\n rdict = self.GET\\r\\n\\r\\n if 'terms' in mdict:\\r\\n phrase = \\\" \\\".join(mdict['terms'])\\r\\n else:\\r\\n phrase = rdict.get('search', '')\\r\\n\\r\\n # Always search the fulltext content\\r\\n with_content = True\\r\\n\\r\\n conn_str = self.settings.get('sqlalchemy.url', False)\\r\\n searcher = get_fulltext_handler(conn_str)\\r\\n\\r\\n # check if we have a page count submitted\\r\\n params = self.params\\r\\n page = params.get('page', 0)\\r\\n count = params.get('count', 50)\\r\\n\\r\\n if rdict.get('search_mine') or 'username' in mdict:\\r\\n with_user = True\\r\\n else:\\r\\n with_user = False\\r\\n\\r\\n username = None\\r\\n if with_user:\\r\\n if 'username' in mdict:\\r\\n username = mdict.get('username')\\r\\n elif self.request.user and self.request.user.username:\\r\\n username = self.request.user.username\\r\\n\\r\\n res_list = searcher.search(\\r\\n phrase,\\r\\n content=with_content,\\r\\n username=username if with_user else None,\\r\\n ct=count,\\r\\n page=page,\\r\\n )\\r\\n\\r\\n # if the route name is search_ajax we want a json response\\r\\n # else we just want to return the payload data to the mako template\\r\\n if 'ajax' in route_name or 'api' in route_name:\\r\\n return {\\r\\n 'success': True,\\r\\n 'message': \\\"\\\",\\r\\n 'payload': {\\r\\n 'search_results': [dict(res) for res in res_list],\\r\\n 'result_count': len(res_list),\\r\\n 'phrase': phrase,\\r\\n 'page': page,\\r\\n 'username': username,\\r\\n }\\r\\n }\\r\\n else:\\r\\n return {\\r\\n 'search_results': res_list,\\r\\n 'count': len(res_list),\\r\\n 'max_count': 50,\\r\\n 'phrase': phrase,\\r\\n 'page': page,\\r\\n 'username': username,\\r\\n }\",\n \"def get_results():\\n try:\\n firstbeer = int(request.form['beerchoice1'])\\n secondbeer = int(request.form['beerchoice2'])\\n except:\\n traceback.print_exc()\\n logger.warning(\\\"Not able to display recommendations, error page returned\\\")\\n return render_template('error-noselection.html')\\n try:\\n listbeers = db.session.query(Top_Ten_Beers).filter_by(Type=beertype)\\n logger.debug(\\\"Top Ten Beers Query Accessed\\\")\\n except:\\n traceback.print_exc()\\n logger.warning(\\\"Not able to display recommendations, error page returned\\\")\\n if firstbeer==secondbeer:\\n return render_template('error-samebeers.html')\\n names, data = query_to_list(listbeers)\\n top10df = pd.DataFrame.from_records(data, columns=names)\\n usercomb = top10df.iloc[[firstbeer, secondbeer],:]\\n try:\\n allcomb = db.session.query(User_Combinations).filter_by(Type=beertype)\\n logger.debug(\\\"Recommendation Query Accessed\\\")\\n except:\\n traceback.print_exc()\\n logger.warning(\\\"Not able to display recommendations, error page returned\\\")\\n names, data = query_to_list(allcomb)\\n allcombdf = pd.DataFrame.from_records(data, columns=names)\\n probablerows = allcombdf[allcombdf['Beer_ID'].isin(usercomb['Beer_ID'].values)]\\n realrows = probablerows.groupby(['ID']).count()\\n ID = realrows[realrows['Beer_ID']==2].index[0]\\n try:\\n preds = db.session.query(User_Predictions).filter_by(Type=beertype, ID=ID)\\n logger.debug(\\\"Recommendation Results Query Accessed\\\")\\n return render_template('results.html', beertype=beertype, preds=preds)\\n except:\\n traceback.print_exc()\\n logger.warning(\\\"Not able to display beers, error page returned\\\")\\n return render_template('error-noselection.html')\",\n \"def index(request):\\n\\n # Generate counts of some of the main objects\\n num_para = Paragraph.objects.all().count()\\n num_source = Source.objects.all().count()\\n\\n context = {\\n 'num_para': num_para,\\n 'num_source': num_source,\\n 'paragraph_list': queryset[:10],\\n }\\n\\n return render(request, 'index.html', context=context)\",\n \"def send_table_as_html(self, event):\\n # todo: for now we send all pending tasks serialized as json\\n # further changes:\\n # * filter by the user object based permissions to show only pending tasks for that the user\\n # has permissions\\n # * check if the self.user has permissions for the instance that is created/modified. If not skip sending\\n\\n # create dummy request to render table as html\\n url = self.scope['path']\\n if self.scope['query_string']:\\n url += f\\\"?{self.scope['query_string'].decode('utf-8')}\\\"\\n\\n request = RequestFactory().get(url)\\n request.user = self.user\\n\\n all_task_results = TaskResult.objects.all()\\n\\n pending_tasks_filterset = TaskResultFilter(data=request.GET, queryset=all_task_results)\\n if pending_tasks_filterset.qs:\\n # render the table only if the filtered qs in not empty\\n pending_task_table = PendingTaskTable(data=pending_tasks_filterset.qs)\\n pending_task_table.context = Context()\\n pending_task_table.context.update({'filter': pending_tasks_filterset})\\n\\n RequestConfig(request=request).configure(table=pending_task_table)\\n\\n rendered_table = pending_task_table.as_html(request=request)\\n self.send_json(content=json.dumps({'rendered_table': rendered_table}))\",\n \"def execute(self, request):\\n CheckValue.check_not_none(request, 'request')\\n request.set_defaults(self._config)\\n request.validate()\\n if request.is_query_request():\\n self._stats_control.observe_query(request)\\n\\n \\\"\\\"\\\"\\n The following 'if' may be True for advanced queries only. For such\\n queries, the 'if' will be True (i.e., the QueryRequest will be bound\\n with a QueryDriver) if and only if this is not the 1st execute()\\n call for this query. In this case we just return a new, empty\\n QueryResult. Actual computation of a result batch will take place\\n when the app calls get_results() on the QueryResult.\\n \\\"\\\"\\\"\\n if request.has_driver():\\n self._trace('QueryRequest has QueryDriver', 2)\\n return QueryResult(request, False)\\n \\\"\\\"\\\"\\n If it is an advanced query and we are here, then this must be the\\n 1st execute() call for the query. If the query has been prepared\\n before, we create a QueryDriver and bind it with the QueryRequest.\\n Then, we create and return an empty QueryResult. Actual computation\\n of a result batch will take place when the app calls get_results()\\n on the QueryResult.\\n \\\"\\\"\\\"\\n if request.is_prepared() and not request.is_simple_query():\\n self._trace(\\n 'QueryRequest has no QueryDriver, but is prepared', 2)\\n driver = QueryDriver(request)\\n driver.set_client(self)\\n driver.set_topology_info(request.topology_info())\\n return QueryResult(request, False)\\n \\\"\\\"\\\"\\n If we are here, then this is either (a) a simple query or (b) an\\n advanced query that has not been prepared already, which also\\n implies that this is the 1st execute() call on this query. For a\\n non-prepared advanced query, the effect of this 1st execute() call\\n is to send the query to the proxy for compilation, get back the\\n prepared query, but no query results, create a QueryDriver, and bind\\n it with the QueryRequest (see QueryRequestSerializer.deserialize()),\\n and return an empty QueryResult.\\n \\\"\\\"\\\"\\n self._trace(\\n 'QueryRequest has no QueryDriver and is not prepared', 2)\\n timeout_ms = request.get_timeout()\\n headers = {'Host': self._url.hostname,\\n 'Content-Type': 'application/octet-stream',\\n 'Connection': 'keep-alive',\\n 'Accept': 'application/octet-stream',\\n 'User-Agent': self._user_agent}\\n\\n # set the session cookie if available\\n if self._session_cookie is not None:\\n headers['Cookie'] = self._session_cookie\\n\\n # set namespace if configured\\n namespace = request.get_namespace()\\n if namespace is None:\\n namespace = self._config.get_default_namespace()\\n if namespace is not None:\\n headers[HttpConstants.REQUEST_NAMESPACE_HEADER] = namespace\\n\\n content = self.serialize_request(request, headers)\\n content_len = len(content)\\n # If on-premise the auth_provider will always be a\\n # StoreAccessTokenProvider. If so, check against configurable limit.\\n # Otherwise check against internal hardcoded cloud limit.\\n if isinstance(self._auth_provider, StoreAccessTokenProvider):\\n if content_len > self._max_content_length:\\n raise RequestSizeLimitException(\\n 'The request size of ' + str(content_len) + ' exceeded ' +\\n 'the limit of ' + str(self._max_content_length))\\n if request.get_compartment() is None:\\n request.set_compartment_internal(\\n self._config.get_default_compartment())\\n if self._logutils.is_enabled_for(DEBUG):\\n self._logutils.log_debug('Request: ' + request.__class__.__name__)\\n request_id = self._next_request_id()\\n headers[HttpConstants.REQUEST_ID_HEADER] = request_id\\n self.check_request(request)\\n # TODO: look at avoiding creating this object on each request\\n request_utils = RequestUtils(\\n self._sess, self._logutils, request, self._retry_handler, self,\\n self._rate_limiter_map)\\n return request_utils.do_post_request(self._request_uri, headers,\\n content, timeout_ms,\\n self._stats_control)\",\n \"def generate(self):\\n redash_session = type(self)._create_redash_session()\\n refresh_data = type(self)._refresh_query(redash_session, self.query_id)\\n if refresh_data.status_code != 200:\\n raise ValueError(\\\"Could not refresh query {}\\\".format(self.query_id))\\n\\n refresh_job = refresh_data.json()['job']\\n result_id = type(self)._poll_for_new_result(redash_session, refresh_job)\\n if not result_id:\\n raise ValueError(\\\"Query execution failed\\\")\\n\\n results_data = type(self)._get_fresh_results(redash_session, self.query_id, result_id)\\n if results_data.status_code != 200:\\n raise ValueError(\\\"Failed fetching result id {}\\\".format(result_id))\\n\\n rows = results_data.json()['query_result']['data']['rows']\\n for row in rows:\\n yield {'_raw': json.dumps(row)}\",\n \"def query(self, sql):\\n self.cursor.execute(sql)\\n result = self.cursor.fetchall()\\n return result\",\n \"def send_sql_query(self, query):\\n # TODO: MAKE SQL SELECT and SQL INSERT modules\\n self.cursor.execute(query)\\n self.cnx.commit()\",\n \"def results(self):\\r\\n pass\",\n \"def index():\\n rows = db.execute(\\\"SELECT symbol, SUM(shares) as shares FROM 'transaction' WHERE u_id = :user_id GROUP BY symbol\\\", user_id = session[\\\"user_id\\\"])\\n user = db.execute(\\\"SELECT * FROM 'users' WHERE id = :user_id\\\", user_id = session[\\\"user_id\\\"])\\n\\n if len(rows) == 0:\\n return render_template(\\\"index.html\\\", rows = 0, username = user[0][\\\"username\\\"], cash = user[0][\\\"cash\\\"], total = user[0][\\\"cash\\\"])\\n\\n else:\\n cur_price = []\\n value = []\\n names = []\\n total = 0\\n for row in rows:\\n returned_quote = lookup(row[\\\"symbol\\\"])\\n cur_price.append(returned_quote[\\\"price\\\"])\\n value.append(round(returned_quote[\\\"price\\\"] * row[\\\"shares\\\"], 2))\\n names.append(returned_quote[\\\"name\\\"])\\n total = total + round(returned_quote[\\\"price\\\"] * row[\\\"shares\\\"], 2)\\n\\t\\t\\n\\t\\ttotal = round(total, 2)\\n\\t\\t\\n return render_template(\\\"index.html\\\", username = user[0][\\\"username\\\"], cash = user[0][\\\"cash\\\"], total = total, rows = rows, cur_price = cur_price, value = value, names = names)\",\n \"def _prepare_result(self, request):\\n # TODO: get all params from request (via self)\\n self._request = request\\n return super(FullTextSearchModel, self)._prepare_result(self.__query_params)\",\n \"def index():\\n rows = db.execute(\\\"SELECT Symbol, SUM(Shares) as totalShares FROM cash WHERE id=:id GROUP BY Symbol HAVING totalShares > 0\\\", id=session[\\\"user_id\\\"])\\n transactions=[]\\n grand_total = 0\\n for row in rows:\\n stock = lookup(row[\\\"Symbol\\\"])\\n transactions.append({\\n \\\"Symbol\\\": stock[\\\"symbol\\\"],\\n \\\"Name\\\": stock[\\\"name\\\"],\\n \\\"Shares\\\": row[\\\"totalShares\\\"],\\n \\\"Price\\\": usd(stock[\\\"price\\\"]),\\n \\\"Total\\\": usd(stock[\\\"price\\\"] * row[\\\"totalShares\\\"])\\n })\\n grand_total += stock[\\\"price\\\"] * row[\\\"totalShares\\\"]\\n rows = db.execute(\\\"SELECT cash FROM users WHERE id=:id\\\", id=session[\\\"user_id\\\"])\\n cash = rows[0][\\\"cash\\\"]\\n return render_template(\\\"table.html\\\", transactions=transactions, cash=usd(cash), grand_total=usd(grand_total))\",\n \"def _raw(self, query: Any, data: Any = None):\\n assert isinstance(query, str)\\n\\n conn = self._get_session()\\n try:\\n results = conn.execute(query)\\n\\n entity_items = []\\n for item in results:\\n entity = self.model_cls.to_entity(item)\\n entity.state_.mark_retrieved()\\n entity_items.append(entity)\\n\\n result = ResultSet(\\n offset=0,\\n limit=len(entity_items),\\n total=len(entity_items),\\n items=entity_items,\\n )\\n except DatabaseError as exc:\\n logger.error(f\\\"Error while running raw query: {exc}\\\")\\n raise\\n finally:\\n if not current_uow:\\n conn.commit()\\n conn.close()\\n\\n return result\",\n \"def query(self, *sql):\\n self.cursor.execute(*sql)\\n self.conn.commit()\",\n \"def home(request):\\n context = {\\n \\\"results\\\": Result.objects.all()\\n .filter(patient_capacity__gt=0)\\n .order_by(\\\"drive_time\\\")[:4],\\n }\\n return render(request, \\\"landing/index.html\\\", context)\",\n \"def results(self):\\n pass\",\n \"def update_query(self):\\n text = self.lineedit.text()\\n self.results = self.lookup(text)\\n self.update_ui()\\n self.copy_entry(self.table.currentRow(), self.table.currentColumn())\",\n \"def process(self, query):\\n response_text = self.fetch(query)\\n content = self.get_content(response_text)\\n return content\",\n \"def run(self):\\n rows = None\\n if self.sql.startswith('select'):\\n conn = self.table.connect()\\n with conn.cursor() as curs:\\n try:\\n curs.execute(self.sql)\\n except conn.DatabaseError as exc:\\n error, = exc.args\\n logging.error(f\\\"\\\"\\\"error executing {self.sql}:\\n {error.code}\\\"\\\"\\\")\\n self.excep = exc\\n raise exc\\n else:\\n rows = curs.fetchall()\\n # logging.critical(f\\\"\\\"\\\"executed {self.sql}\\\"\\\"\\\")\\n self.result_exec = rows\",\n \"def process_query_results(self, query_results: dict or list, analysis, observable: Observable) -> None:\\n pass\",\n \"def queryDB(db):\\n def printunichars(row):\\n \\\"\\\"\\\"Helper function for print utf 8 chars\\\"\\\"\\\"\\n print(\\\"Title:\\\")\\n print(row[0].encode('utf-8'))\\n print(\\\"Body:\\\")\\n print(row[1].encode('utf-8'))\\n print(\\\"Ref:\\\")\\n print(row[2].encode('utf-8'))\\n print(\\\"Url:\\\")\\n print(row[3].encode('utf-8'))\\n \\n cursor = db.cursor()\\n cursor.execute(\\\"SET NAMES 'utf8';\\\")\\n print(\\\"SET NAMES utf8;\\\")\\n sql = \\\"SELECT Title FROM pages LIMIT 100\\\"\\n cursor.execute(sql)\\n rows = cursor.fetchall()\\n for row in rows:\\n printchars(row)\",\n \"def get(self, request):\\n return self.execute_query()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6671056","0.6531192","0.64979106","0.63335913","0.6329612","0.6328952","0.6239457","0.6226256","0.6211864","0.6154065","0.61292285","0.611252","0.60824287","0.6070119","0.60307413","0.6025734","0.5974545","0.5968892","0.59402233","0.5872386","0.5866393","0.5826621","0.5824343","0.58162934","0.58155876","0.5807666","0.5796463","0.5791076","0.5784336","0.5774189","0.5761398","0.5736807","0.57128984","0.56910515","0.5685938","0.5671946","0.5664085","0.5660816","0.56561035","0.56552166","0.56518584","0.5651804","0.5650152","0.56423557","0.563925","0.5629951","0.5622183","0.5614843","0.56114274","0.5607041","0.56041163","0.55936944","0.5592378","0.5592042","0.5584571","0.556004","0.55582947","0.5555759","0.55550647","0.5554576","0.5552363","0.55476993","0.55462295","0.55420285","0.5540989","0.55336386","0.5530033","0.5520288","0.55162895","0.5508587","0.550771","0.550681","0.55064756","0.55064756","0.5504951","0.5504527","0.55039483","0.5494147","0.5488244","0.54843915","0.548357","0.54810363","0.54642475","0.54623634","0.54613084","0.5455563","0.54543954","0.5454029","0.54519856","0.5450964","0.5447038","0.54396635","0.5433047","0.54275286","0.54224765","0.5418389","0.54160774","0.5412023","0.5409786","0.54082173","0.54073274"],"string":"[\n \"0.6671056\",\n \"0.6531192\",\n \"0.64979106\",\n \"0.63335913\",\n \"0.6329612\",\n \"0.6328952\",\n \"0.6239457\",\n \"0.6226256\",\n \"0.6211864\",\n \"0.6154065\",\n \"0.61292285\",\n \"0.611252\",\n \"0.60824287\",\n \"0.6070119\",\n \"0.60307413\",\n \"0.6025734\",\n \"0.5974545\",\n \"0.5968892\",\n \"0.59402233\",\n \"0.5872386\",\n \"0.5866393\",\n \"0.5826621\",\n \"0.5824343\",\n \"0.58162934\",\n \"0.58155876\",\n \"0.5807666\",\n \"0.5796463\",\n \"0.5791076\",\n \"0.5784336\",\n \"0.5774189\",\n \"0.5761398\",\n \"0.5736807\",\n \"0.57128984\",\n \"0.56910515\",\n \"0.5685938\",\n \"0.5671946\",\n \"0.5664085\",\n \"0.5660816\",\n \"0.56561035\",\n \"0.56552166\",\n \"0.56518584\",\n \"0.5651804\",\n \"0.5650152\",\n \"0.56423557\",\n \"0.563925\",\n \"0.5629951\",\n \"0.5622183\",\n \"0.5614843\",\n \"0.56114274\",\n \"0.5607041\",\n \"0.56041163\",\n \"0.55936944\",\n \"0.5592378\",\n \"0.5592042\",\n \"0.5584571\",\n \"0.556004\",\n \"0.55582947\",\n \"0.5555759\",\n \"0.55550647\",\n \"0.5554576\",\n \"0.5552363\",\n \"0.55476993\",\n \"0.55462295\",\n \"0.55420285\",\n \"0.5540989\",\n \"0.55336386\",\n \"0.5530033\",\n \"0.5520288\",\n \"0.55162895\",\n \"0.5508587\",\n \"0.550771\",\n \"0.550681\",\n \"0.55064756\",\n \"0.55064756\",\n \"0.5504951\",\n \"0.5504527\",\n \"0.55039483\",\n \"0.5494147\",\n \"0.5488244\",\n \"0.54843915\",\n \"0.548357\",\n \"0.54810363\",\n \"0.54642475\",\n \"0.54623634\",\n \"0.54613084\",\n \"0.5455563\",\n \"0.54543954\",\n \"0.5454029\",\n \"0.54519856\",\n \"0.5450964\",\n \"0.5447038\",\n \"0.54396635\",\n \"0.5433047\",\n \"0.54275286\",\n \"0.54224765\",\n \"0.5418389\",\n \"0.54160774\",\n \"0.5412023\",\n \"0.5409786\",\n \"0.54082173\",\n \"0.54073274\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13088,"cells":{"query":{"kind":"string","value":"Parse command line arguments and pass them to the query engine"},"document":{"kind":"string","value":"def main():\n parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)\n parser.add_argument('--service', default=os.path.join(os.getenv(\"HOME\"), \".desservices.ini\"))\n parser.add_argument('--section', '-s', default='db-desoper',\n help='section in the .desservices file w/ DB connection information')\n parser.add_argument('--debug', '-d', help='print debug info', default=False, action='store_true')\n parser.add_argument('--header', help='print header derived from query', default=False, action='store_true')\n parser.add_argument('--format', '-f', help='format = csv or pretty', default=\"pretty\", choices=[\"pretty\", \"csv\"])\n parser.add_argument('--delimiter', help='delimiter for csv', default=\",\")\n parser.add_argument('--log', help='log queries to file (via append)', default=None)\n parser.add_argument('query', help='query to execute (or -, read from standard in)', default=None)\n\n args = parser.parse_args()\n if not args.log:\n args.log = os.getenv(\"DESPYDB_QUERY_LOG\") # Undefined -> returns None\n query(args)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def parse_arguments(args):","def arg_parse():\n p = ap.ArgumentParser()\n p.add_argument('column_name',\n type=str,\n help='column_name to search')\n p.add_argument('operation',\n choices=['gt', 'lt', 'eq'])\n p.add_argument('limit',\n type=float,\n help='limit to search by')\n return p.parse_args()","def query_cmdline():","def query(args):\n dbh = despydb.DesDbi(args.service, args.section)\n if args.query not in \"-+\":\n do1Query(dbh, args.query, args)\n elif args.query == \"-\":\n line = sys.stdin.readline()\n while line:\n line = line.strip()\n if not line or line.startswith(\"#\"):\n pass\n else:\n do1Query(dbh, line, args)\n line = sys.stdin.readline()\n else: #if args.query == \"+\":\n lines = sys.stdin.read()\n do1Query(dbh, lines, args)\n dbh.close()","def parse_cmdline_args():\n parser = argparse.ArgumentParser(description=\"Guesses the functional element for host.\")\n ##\n ## Internal options\n ##\n parser.add_argument(\"--json\", dest=\"json\", action='store_true', help=\"output in JSON\")\n\n ##\n ## PuppetDB options\n ##\n pdbconf = PdbConfig()\n pdbconf.add_standard_args(parser)\n\n parser.add_argument(\"host\", metavar=\"HOST\",\n help=\"hostnames to query for FE\")\n\n return parser.parse_args()","def _parse_args():\n parser = argparse.ArgumentParser(description='main.py')\n \n # General system running and configuration options\n parser.add_argument('--do_nearest_neighbor', dest='do_nearest_neighbor', default=False, action='store_true', help='run the nearest neighbor model')\n\n parser.add_argument('--train_path', type=str, default='data/geo_train.tsv', help='path to train data')\n parser.add_argument('--dev_path', type=str, default='data/geo_dev.tsv', help='path to dev data')\n parser.add_argument('--test_path', type=str, default='data/geo_test.tsv', help='path to blind test data')\n parser.add_argument('--test_output_path', type=str, default='geo_test_output.tsv', help='path to write blind test results')\n parser.add_argument('--domain', type=str, default='geo', help='domain (geo for geoquery)')\n \n # Some common arguments for your convenience\n parser.add_argument('--seed', type=int, default=0, help='RNG seed (default = 0)')\n parser.add_argument('--epochs', type=int, default=100, help='num epochs to train for')\n parser.add_argument('--lr', type=float, default=.001)\n parser.add_argument('--batch_size', type=int, default=2, help='batch size')\n # 65 is all you need for GeoQuery\n parser.add_argument('--decoder_len_limit', type=int, default=65, help='output length limit of the decoder')\n\n # Feel free to add other hyperparameters for your input dimension, etc. to control your network\n # 50-200 might be a good range to start with for embedding and LSTM sizes\n args = parser.parse_args()\n return args","def ParseCommandArguments(args):\n\n\n\n import argparse\n from google.appengine.tools import boolean_action\n\n parser = argparse.ArgumentParser()\n parser.add_argument('-A', '--application', required=True)\n parser.add_argument('--api_host', default='')\n\n parser.add_argument('--api_port', default=8000, type=int)\n parser.add_argument('--trusted',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n parser.add_argument('--application_root', default=None)\n parser.add_argument('--application_host', default='localhost')\n parser.add_argument('--application_port', default=None)\n\n\n parser.add_argument('--blobstore_path', default=None)\n\n\n parser.add_argument('--datastore_path', default=None)\n\n parser.add_argument('--auto_id_policy', default='scattered',\n type=lambda s: s.lower(),\n choices=(datastore_stub_util.SEQUENTIAL,\n datastore_stub_util.SCATTERED))\n\n parser.add_argument('--use_sqlite',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n parser.add_argument('--high_replication',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n parser.add_argument('--require_indexes',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n parser.add_argument('--clear_datastore',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n\n\n parser.add_argument('--logs_path', default=None)\n\n\n parser.add_argument('--enable_sendmail',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n parser.add_argument('--smtp_host', default='')\n\n parser.add_argument('--smtp_port', default=25, type=int)\n parser.add_argument('--smtp_user', default='')\n parser.add_argument('--smtp_password', default='')\n parser.add_argument('--show_mail_body',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n\n\n parser.add_argument('--prospective_search_path', default=None)\n parser.add_argument('--clear_prospective_search',\n action=boolean_action.BooleanAction,\n const=True,\n default=False)\n\n\n parser.add_argument('--enable_task_running',\n action=boolean_action.BooleanAction,\n const=True,\n default=True)\n\n parser.add_argument('--task_retry_seconds', default=30, type=int)\n\n\n parser.add_argument('--user_login_url', default=None)\n parser.add_argument('--user_logout_url', default=None)\n\n return parser.parse_args(args)","def main(args):\n index = Index()\n tag_query = keyword_query = None\n\n if args.get(\"--tag\"):\n tags = [s.strip() for s in args[\"--tag\"].split(\",\")]\n terms = [Term(\"tag\", s) for s in tags if s]\n if terms:\n tag_query = And(terms)\n\n if args.get(\"KEYWORD\"):\n keyword_query = index.parse(\" \".join(kw for kw in args[\"KEYWORD\"]))\n\n if keyword_query:\n search = index.search(keyword_query, filter=tag_query)\n else:\n assert tag_query # at least one should have been required by docopt\n search = index.search(tag_query)\n\n with search as results:\n for result in results:\n print(format(result, TEMPLATE))\n return 0","def handle_cmdline_args():\n\n parser = argparse.ArgumentParser(\n description='Generate synthetic data from a specification in a json '\n 'file using the \"synth-method\" described in the json file. ')\n\n parser.add_argument(\n '-i', dest='infile', required=True,\n help='The input json file. Must contain a \"synth-method\" property')\n\n parser.add_argument(\n '-o', dest='outfile_prefix', required=True, help='The prefix of the output paths (data json and csv), relative to the QUIPP-pipeline root directory')\n\n args = parser.parse_args()\n return args","def parseArguments():\n parser = argparse.ArgumentParser(description='Tool run benchmarks and query database')\n parser.add_argument('--version', action=\"store_true\", dest=\"version\", default=False, help=\"Print version\")\n parser.add_argument(\"--query\", \"-q\", action=\"store_true\", dest=\"queryDataBase\", default=False, help=\"Query Data Base\")\n parser.add_argument(\"--performance\", \"-p\", action=\"store_true\", dest=\"queryPerformance\", default=False, help=\"Query Data Base - Performance Metrics\")\n parser.add_argument(\"--run\", \"-r\", action=\"store_true\", dest=\"runBenchmarks\", default=False, help=\"Run Benchmarks and store results in the DB\")\n args = parser.parse_args()\n return args","def parse_command_line_arguments(argv):\n print(\"reading command line arguments in...\")\n\n parser = argparse.ArgumentParser(description='Description of your program')\n parser.add_argument('-i', '--input', help='Location of input csv file', required=True)\n parser.add_argument('-p', '--predicting', help='The column name containing the category to predict', required=True)\n parser.add_argument('-s', '--scoring', help='The scoring type to be used with model evaluation', required=False)\n parser.add_argument('-c', '--scale', help='List of column names to scale values for', nargs='+', required=False)\n args = parser.parse_args()\n\n return args.input, args.predicting, args.scoring, args.scale","def parse_args():\n parser = argparse.ArgumentParser(description='database update')\n parser.add_argument('--host', dest='host', help='database host',\n default=\"localhost\")\n parser.add_argument('--database', dest='database', help='database name',\n default='x5gon_dirty')\n parser.add_argument('--user', dest='user', help='database user',\n default=\"postgres\")\n parser.add_argument('--password', dest='password', help='database password',\n default='hayleys')\n parser.add_argument('--procs', dest='procs', help='number of parallel processes',\n default=10)\n parser.add_argument('--out', dest='out', help='output file name',\n default=\"output\")\n parser.add_argument('--tf_conf', dest='tf_conf', help='threshold for TF similarity',\n default=0.85)\n parser.add_argument('--wiki_conf', dest='wiki_conf', help='threshold for WIKI similarity',\n default=0.95)\n arguments = parser.parse_args()\n return arguments","def _parse_args():\n parser = argparse.ArgumentParser(description='main.py')\n \n # General system running and configuration options\n parser.add_argument('--do_nearest_neighbor', dest='do_nearest_neighbor', default=False, action='store_true', help='run the nearest neighbor model')\n parser.add_argument('--debug', dest='debug', default=False, action='store_true', help='set to debug mode ')\n parser.add_argument('--num_train_sentence', dest='num_train_sentence', type=int, default=-1,\n help='set number of sentence to train on')\n parser.add_argument('--train_path', type=str, default='data/geo_train.tsv', help='path to train data')\n parser.add_argument('--dev_path', type=str, default='data/geo_dev.tsv', help='path to dev data')\n parser.add_argument('--test_path', type=str, default='data/geo_test.tsv', help='path to blind test data')\n parser.add_argument('--test_output_path', type=str, default='geo_test_output.tsv', help='path to write blind test results')\n parser.add_argument('--domain', type=str, default='geo', help='domain (geo for geoquery)')\n parser.add_argument('--attn_model', type=str, default='general', help='Attention model to use: general (default), dot, concat')\n\n # Some common arguments for your convenience\n parser.add_argument('--seed', type=int, default=0, help='RNG seed (default = 0)')\n parser.add_argument('--epochs', type=int, default=100, help='num epochs to train for')\n parser.add_argument('--lr', type=float, default=.001)\n parser.add_argument('--batch_size', type=int, default=2, help='batch size')\n # 65 is all you need for GeoQuery\n parser.add_argument('--decoder_len_limit', type=int, default=65, help='output length limit of the decoder')\n\n # Feel free to add other hyperparameters for your input dimension, etc. to control your network\n # 50-200 might be a good range to start with for embedding and LSTM sizes\n args = parser.parse_args()\n return args","def handle_arguments(cls, *args, **kwargs):\n connection_info = misc_utils.ConnectionInfo(\n kwargs[\"dictionary\"], kwargs[\"ip_address\"], kwargs[\"port\"]\n )\n search_info = misc_utils.SearchInfo(\n kwargs[\"is_printing_list\"],\n kwargs[\"ids\"],\n kwargs[\"components\"],\n kwargs[\"search\"],\n kwargs[\"json\"],\n )\n\n cls._execute_command(\n connection_info, search_info, kwargs[\"command_name\"], kwargs[\"arguments\"]\n )","def parse_parameters():\n parser = argparse.ArgumentParser(description='Program that checks for bad evaluations.')\n parser.usage = 'bettercorrectors [-h] client_id client_secret start_date [end_date] [--sql file]'\n parser.add_argument('client_id', help='the client_id of your intranet application', type=str)\n parser.add_argument('client_secret', help='the client_secret of your intra application', type=str)\n parser.add_argument('start_date', help='the latest date in iso format', type=datetime.fromisoformat)\n parser.add_argument('end_date', help='the closest date in iso format (optional)', type=datetime.fromisoformat,\n default=datetime.now(), nargs='?')\n parser.add_argument('--sql', dest='file', help='''name of the database file in case you want to save results in a \n sqlite database''', type=str)\n args = parser.parse_args()\n return args","def main():\n args = parse_args()\n\n make_session = bootstrap(\n 'sqlite:///{}'.format(DB_NAME),\n )\n session = make_session()\n\n for vase in session.query(Vase).order_by(Vase.produced_start):\n for query_str in make_searches(vase):\n pass","def parse_command_line():\n parser = ArgumentParser(description=__doc__,\n formatter_class=RawTextHelpFormatter,\n epilog=\"For a list of table formats check this page: \"\n \"https://github.com/astanin/python-tabulate#table-format\"\n )\n requir = parser.add_argument_group(\"required arguments\")\n requir.add_argument(\"-f\", \"--find\",\n required=True,\n help=\"Search string to identify\"\n )\n requir.add_argument(\"-k\", \"--client_id\",\n required=True,\n help=\"CrowdStrike API client ID\"\n )\n requir.add_argument(\"-s\", \"--client_secret\",\n required=True,\n help=\"CrowdStrike API client secret\"\n )\n parser.add_argument(\"-r\", \"--reverse\",\n help=\"Reverse the sort.\",\n default=False,\n action=\"store_true\"\n )\n parser.add_argument(\"-t\", \"--types\",\n help=\"Types to search (indicator, report or actor). Comma delimited.\"\n )\n parser.add_argument(\"-tf\", \"--table_format\",\n help=\"Set the table format.\",\n default=\"fancy_grid\"\n )\n parser.add_argument(\"-o\", \"--output_prefix\",\n help=\"Output filename prefix for storing results (CSV format).\",\n default=None\n )\n\n parsed = parser.parse_args()\n allow = [\"indicator\", \"report\", \"actor\"]\n parsed.types = [t for t in parsed.types.split(\",\") if t in allow] if parsed.types else allow\n\n return parsed","def parse_arguments(self):\n \n for arg in sys.argv[1:]:\n (key, sep, value) = arg.partition(\"=\")\n if sep != \"=\":\n raise ProcessorError(\"Illegal argument '%s'\" % arg)\n self.update_data(key, value)","def parse_args():\n parser = MyParser(description='Data processing and analytics library \\\n for OpenStack Browbeat perf data')\n\n parser.add_argument('-s', '--summary', dest=\"days\", type=int, default=-1,\n help='-s N summary of last N days of results')\n\n parser.add_argument('--summary-uuid', dest=\"summary_uuid\", type=str,\n default=None,\n help='--summary-uuid UUID summary of a specific uuid')\n\n parser.add_argument('--short-summary', dest=\"short_days\", type=int,\n default=-1,\n help='--short-summary N gives \\\n summary of last N days of results but uses cockroach \\\n db so only provides with basic summary')\n\n parser.add_argument('--upload-timesummary', dest=\"timeseries_uuid\",\n type=str, default=None,\n help='--upload-timesummary UUID \\\n uploads the features computed from data obtained from\\\n graphite. ')\n\n parser.add_argument('--upload-logsummary', dest=\"loggin_uuid\",\n type=str, default=None,\n help='--upload-logsummary UUID \\\n uploads the log summary to crdb \\\n currently just summarizes over entire timeperiod. ')\n\n parser.add_argument('-u', '--update-db', dest='update', type=bool,\n default=False,\n help='-u True pushes data to cockroach db')\n\n parser.add_argument('--update-clf', dest=\"clf_days\", type=int,\n default=-1,\n help='--update-clf 60 will update all classifiers \\\n listed in config file under classifier_lists \\\n using data from last 60 days')\n\n parser.add_argument('--test-clf', dest=\"test_days\", type=int,\n default=-1,\n help='--test-clf 60 will train all classifiers \\\n listed in config file under classifier_lists \\\n using data from last 60 days and then test it \\\n and display metrics')\n\n parser.add_argument('-v', '--osp-version', dest='version', type=str,\n default=None,\n help='-v 11-tripleo only returns hits for that \\\n OpenStack version, \\\n only supported by summary right now')\n\n parser.add_argument('-c', '--config', dest='config', type=str,\n default=pkg_resources.resource_filename('bml',\n \"config.yml\"),\n help='-c <config file path> use custom config file')\n\n args = parser.parse_args()\n return args","def command_line_args(parser):\n AbyssAssembler.command_line_args(parser)\n SpadesAssembler.command_line_args(parser)\n TrinityAssembler.command_line_args(parser)\n VelvetAssembler.command_line_args(parser)","def main():\n args = parse_args()\n process_args(args)","def parse_arguments():\n\n parser = argparse.ArgumentParser()\n parser.add_argument(\n '--output',\n type=str,\n required=False,\n help='GCS URL where results will be saved as a CSV.')\n parser.add_argument(\n '--query',\n type=str,\n required=True,\n help='The SQL query to be run in BigQuery')\n parser.add_argument(\n '--dataset_id',\n type=str,\n required=True,\n help='Dataset of the destination table.')\n parser.add_argument(\n '--table_id',\n type=str,\n required=True,\n help='Name of the destination table.')\n parser.add_argument(\n '--project',\n type=str,\n required=True,\n help='The GCP project to run the query.')\n\n args = parser.parse_args()\n return args","def main(args):\n cli = CLI()\n # Check arguments\n cli.parse_arguments(args)","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument('-u', '--urls_dirpath', type=unicode)\n parser.add_argument('-r', '--resources_dir', type=unicode)\n parser.add_argument('-t', '--total_docs', type=int)\n parser.add_argument('-m', '--mapping', type=unicode,\n help='File with the yago to lkif mapping')\n\n return parser.parse_args()","def parse_arguments(args):\n \n parser = argparse.ArgumentParser(\n description= \"Join gene, pathway, or taxonomy tables\\n\",\n formatter_class=argparse.RawTextHelpFormatter)\n parser.add_argument(\n \"-v\",\"--verbose\", \n help=\"additional output is printed\\n\", \n action=\"store_true\",\n default=False)\n parser.add_argument(\n \"-i\",\"--input\",\n help=\"the directory of tables\\n\",\n required=True)\n parser.add_argument(\n \"-o\",\"--output\",\n help=\"the table to write\\n\",\n required=True)\n parser.add_argument(\n \"--file_name\",\n help=\"only join tables with this string included in the file name\")\n parser.add_argument(\n \"-s\",\"--search-subdirectories\", \n help=\"search sub-directories of input folder for files\\n\", \n action=\"store_true\",\n default=False)\n\n return parser.parse_args()","def parse_cmdline():\n\tparser = ArgumentParser(prog=\"FastP_QC.py\", description=\"\"\"Script collects stats from fastp jsons.\"\"\")\n\tparser.add_argument(\"-r1\", \"--r1_stats\", dest=\"r1_stats\", action=\"store\", required=True, help=\"Text file with r1 stats, from q30.py script.\")\n\tparser.add_argument(\"-r2\", \"--r2_stats\", dest=\"r2_stats\", action=\"store\", required=True, help=\"Text file with r2 stats, from q30.py script.\")\n\tparser.add_argument(\"-n\", \"--name\", dest=\"name\", action=\"store\", required=True, help=\"Sample name\")\n\targs = parser.parse_args()\n\treturn args","def get_query_params_from_command_line():\n\n parser = argparse.ArgumentParser()\n parser.add_argument('-w', '--way',\n help='input way type(\"ONE_WAY\" or \"ROUND_TRIP\")')\n parser.add_argument('-d', '--dep_city',\n help='input departure city(\"LIS\", \"CUN\", \"PUJ\")')\n parser.add_argument('-a', '--arr_city',\n help='input arrival city(\"LIS\", \"CUN\", \"PUJ\")')\n parser.add_argument('-d_d', '--dep_date', help='input a departure date')\n parser.add_argument('-r', '--ret_date', help='input a return date')\n parser.add_argument('-n_a', '--num_adults',\n help='input a number of adults')\n parser.add_argument('-n_c', '--num_child',\n help='input a number of children')\n parser.add_argument('-n_i', '--num_infants',\n help='input a number of infants')\n args = parser.parse_args()\n\n if not check_flight_type(args.way):\n return None\n else:\n args.way = args.way.upper()\n\n if not check_cities(args.dep_city, args.arr_city):\n return None\n else:\n args.dep_city = args.dep_city.upper()\n args.arr_city = args.arr_city.upper()\n\n if args.way == 'ONE_WAY':\n args.ret_date = args.dep_date\n if not check_dates(args.dep_date, args.ret_date):\n return None\n\n if not check_passengers(args.num_adults, args.num_child, args.num_infants):\n return None\n\n cl_args = {'flight_type': args.way, 'dep_city': args.dep_city, 'arr_city': args.arr_city,\n 'dep_date': args.dep_date, 'ret_date': args.ret_date, 'adults': args.num_adults,\n 'children': args.num_child, 'infants': args.num_infants}\n\n return cl_args","def parseArgs():\n parser = argparse.ArgumentParser(description='Runs RHEAS simulation.')\n parser.add_argument('config', help='configuration file')\n parser.add_argument('-d', metavar='DB', help='name of database to connect')\n parser.add_argument('-u', help='update database', action='store_true')\n args = parser.parse_args()\n return args.config, args.d, args.u","def main_parse_args():\n parser = ArgumentParser()\n parser.add_argument('infile', help='path to the file to be mapped.It should\\\n contain one identifer on each line.')\n parser.add_argument('-rh', '--redis_host', default=DEFAULT_REDIS_URL,\n help='url of Redis db')\n parser.add_argument('-rp', '--redis_port', default=DEFAULT_REDIS_PORT,\n help='port for Redis db')\n parser.add_argument('-rps', '--redis_pass', default=DEFAULT_REDIS_PASS,\n help='password for Redis db')\n parser.add_argument('-of', '--outfile', default=None,\n help='path to the output file')\n parser.add_argument('-sh', '--source_hint', help='suggestion for ID source \\\n database used to resolve ambiguities in mapping',\n default=DEFAULT_HINT)\n parser.add_argument('-t', '--taxon', help='taxon id of species of all gene \\\n names', default=DEFAULT_TAXON)\n myargs = parser.parse_args()\n return myargs","def add_args(self): \n self.parser.add_argument('-u', '--username',\n default=None,\n help='the username for mongoDB (Default: None)')\n\n self.parser.add_argument('-p', '--password',\n default=None,\n help='the password for mongoDB (Default: None)')\n\n self.parser.add_argument('-d', '--database',\n default='grits',\n help='the database for mongoDB (Default: grits)')\n\n self.parser.add_argument('-m', '--mongohost',\n default='localhost',\n help='the hostname for mongoDB (Default: localhost)')\n\n self.parser.add_argument('-f', '--force', \n action='store_true',\n help='do not require confirmation to create indexes (Default: False)')","def parse(args, query):\n\n global query_type\n\n # Deal first with requests for definition or pronunciation\n # 1. Make the code easier to read\n first_word = args[0]\n second_word = args[1] if len(args) > 1 else \"\"\n third_word = args[2] if len(args) > 2 else \"\"\n fourth_word = args[3] if len(args) > 3 else \"\"\n # we use the teranary operator (this if ____ else that) to avoid an IndexError\n # IndexError would be raised if we tried to access the second element (args[1])\n # in a list which contained only one item (eg args == [\"lonely\"])\n # the teranary operator (in most languages it looks like \"____ ? this : that\")\n # returns \"this\" when the if is true and \"that\" when the if is false\n # meaning, if len(args) is NOT greater than 1, second_word == \"\"\n\n # 2. Check for keywords in the list of arguments\n # Example: nostrum defined\n # Example: pronunciation of otolaryngology\n if first_word == \"define\":\n # e.g. if the first word is \"define\" we'll add the second word to the query\n query = {\"sp\": second_word, \"md\": \"d\", \"max\": \"1\", \"qe\": \"sp\", \"ipa\": \"1\"}\n # the query is a dictionary of GET parameters for the http request, eg\n # https://api.datamuse.com/words?max=1&sp=SECOND_WORD_HERE&qe=sp&md=d&ipa=1\n elif second_word == \"defined\" or second_word == \"definition\":\n query = {\"sp\": first_word, \"md\": \"d\", \"max\": \"1\", \"qe\": \"sp\", \"ipa\": \"1\"}\n # this one uses string interpolation (the f\"\" stuff)\n elif f\"{second_word} {third_word}\" == \"means what\":\n query = {\"sp\": first_word, \"md\": \"d\", \"max\": \"1\", \"qe\": \"sp\", \"ipa\": \"1\"}\n elif f\"{second_word} {third_word} {fourth_word}\" == \"is said how\":\n query = {\"sp\": first_word, \"md\": \"r\", \"max\": \"1\", \"qe\": \"sp\", \"ipa\": \"1\"}\n # this one uses regular expressions -- i.e. if the second_word is \"of\" or \"for\"\n elif first_word == \"definition\" and re.match(r'(of)|(for)',second_word):\n query = {\"sp\": third_word, \"md\": \"d\", \"max\": \"1\", \"qe\": \"sp\", \"ipa\": \"1\"}\n # the is_pronounced function returns true if first_word is a (mis)spelling of pronounced\n elif re.match(r'(of)|(for)',second_word) and is_pronounced(first_word):\n query = {\"sp\": third_word, \"md\": \"r\", \"max\": \"1\", \"qe\": \"sp\", \"ipa\": \"1\"}\n # the ordering in the above list is not entirely random\n # since an if-elif-else statement won't keep evaluating after it finds a match\n # it makes sense to put the most computationally complex clauses at the end\n # >>> import timeit\n # >>> timeit.timeit('from word_helpers import is_pronounced; is_pronounced(\"pronounced\")', number=10000)\n # 0.022870146989589557\n # >>> timeit.timeit('args = [\"defined\"]; args[0] == \"defined\"', number=10000)\n # 0.002359684993280098\n # it takes 2 milliseconds to compare a string in a list 10,000 times\n # -- versus 2 centiseconds to run is_pronounced 10,000 times\n # (on my Intel Core i5 2.67GHz CPU -- obviously speed depends on the processor)\n # it's also worth noting that readability counts more than speed optimization (most of the time!)\n\n # Quick way to check if any of the above if statements matched\n if \"sp\" in query:\n # if so, we are done in this function\n if query[\"md\"] == \"r\": query_type = \"PRO\"\n if query[\"md\"] == \"d\": query_type = \"DEF\"\n return query\n\n # these will be useful later\n STOP_WORDS = (\"and\", \"meaning\", \"means\", \"max\", \"about\", \"which\", \"that\")\n\n # Parse more complicated requests for synonyms, etc\n # 0 is false in python, so this loop will run until we've removed all the args\n while len(args):\n # we must reset these vars each time the loop starts\n # in case we've deleted items from the args list\n first_word = args[0]\n second_word = args[1] if len(args) > 1 else \"\"\n third_word = args[2] if len(args) > 2 else \"\"\n # we use the teranary operator (this if ____ else that) to avoid an IndexError\n # IndexError would be raised if we tried to access the second element (args[1])\n # in a list which contained only one item (eg args == [\"lonely\"])\n # the teranary operator (in most languages it looks like \"____ ? this : that\")\n # returns \"this\" when the if is true and \"that\" when the if is false\n # meaning, if len(args) is NOT greater than 1, second_word == \"\"\n\n # Disambiguate homonym requests from spelling correction requests\n # Example: sounding like tung\n # Example: sounds like doe but spelled differently\n if re.match(r'sound((s)|(ing)) like',f\"{first_word} {second_word}\"):\n\n # again, use len(args) to avoid an IndexError\n if len(args) >= 6 and \\\n re.match(r'((but)|(except)) spelled different(ly)?',f\"{args[3]} {args[4]} {args[5]}\"):\n # but instead of teranary operator,\n # use \"short circuit logic\" -- when python sees \"if __A__ and __B__ \",\n # it knows that if A is false, the whole thing will be false\n # (you can't have \"ice cream and potatoes\" for dinner if you don't have ice cream)\n # and it won't waste time evaluating B, so re.match won't run and args[4]\n # won't be accessed and no IndexError will be raised, yay!\n # regex explained: ? means the prior thing matched zero or one times\n # different(ly)? matches \"different\" and \"differently\"\n query[\"rel_hom\"] = third_word\n # now, delete 6 items from args, starting at item 0\n del args[0:6]\n else:\n query[\"sl\"] = third_word\n del args[0:3]\n\n # Example: spelled like 'cens?r'\n elif re.match(r'spell((ed)|(ing)) like',f\"{first_word} {second_word}\"):\n # two stars (**) means \"unpack\" a dictionary\n # just like unpacking a suitcase, we've dumped the old contents of query\n # into a new dictionary (which we are saving with the same variable name!)\n query = {**query,\"sp\": third_word}\n # query[\"sp\"] = third_word also works fine\n # just showing off how to combine two dictionaries :)\n del args[0:3]\n\n # Example: rhymes with culminate\n elif len(args) > 2 and second_word == \"with\" and is_rhymes(first_word):\n query[\"rel_rhy\"] = third_word\n del args[0:3]\n\n # Example: almost rhymes with culminate\n elif len(args) > 3 and \\\n f\"{first_word} {third_word}\" == \"almost with\" and \\\n is_rhymes(second_word):\n query[\"rel_nry\"] = args[3] # fourth_word\n del args[0:4]\n\n # Example: comes after sea\n elif f\"{first_word} {second_word}\" == \"comes after\":\n query[\"lc\"] = third_word\n del args[0:3]\n elif first_word == \"follows\":\n query[\"lc\"] = second_word\n del args[0:2]\n elif f\"{first_word} {second_word}\" == \"comes before\":\n query[\"rc\"] = third_word\n del args[0:3]\n elif first_word == \"preceeds\":\n query[\"rc\"] = second_word\n del args[0:2]\n\n # Example: describes paint\n elif first_word == \"describes\":\n query[\"rel_jjb\"] = second_word\n del args[0:2]\n\n # Example: associated with feet\n elif f\"{first_word} {second_word}\" == \"associated with\" or \\\n f\"{first_word} {second_word}\" == \"triggered by\":\n query[\"rel_trg\"] = third_word\n del args[0:3]\n\n # Example: meaning feeling tired\n elif first_word in [\"means\",\"meaning\",\"like\"]:\n # get rid of first_word\n del args[0]\n # now short circuit logic again, plus using the tuple from ealier\n # b/c if we have \"meaning deer and sounds like roe\" we don't want\n # query[\"ml\"] == \"deer and sounds like roe\" -- it should be just \"deer\"\n while len(args) and args[0] not in STOP_WORDS:\n # teranary operator prevents KeyError if \"ml\" not already in query dictionary\n query[\"ml\"] = f\"{query['ml']} {args[0]}\" if \"ml\" in query else args[0]\n del args[0]\n # an example with the previous code to make things clearer\n # say args == [\"means\", \"egg\", \"beater\", \"and\", \"max\", \"35\"]\n # first_word IS in [\"means\",\"meaning\",\"like\"]\n # del first_word, args is now [\"egg\", \"beater\", \"and\", \"max\", \"35\"]\n # len(args) == 5, args[0] is NOT in STOP_WORDS\n # \"ml\" is NOT in query, so teranary returns args[0] (\"egg\")\n # args[0] is copied to query[\"ml\"] (query is now {ml: \"egg\"})\n # del args[0], args is now [\"beater\", \"and\", \"max\", \"35\"]\n # return to top of while loop, len(args) == 4, args[0] is NOT in STOP_WORDS\n # \"ml\" IS in query, so teranary returns f\"{query['ml']} {args[0]}\" (\"egg beater\") \n # f\"{query['ml']} {args[0]}\" is copied to query[\"ml\"]\n # (query is now {ml: \"egg beater\"})\n # del args[0], args is now [\"and\", \"max\", \"35\"]\n # return to top of while loop, len(args) == 3,\n # args[0] IS in STOP_WORDS (args[0] == \"and\")\n # DO NOT enter the while loop, continue past this code block\n\n # Discover the topic of our query\n elif first_word == \"about\":\n del args[0]\n count = 0\n # Datamuse allows a max of five topic words\n while len(args) and args[0] not in STOP_WORDS and count <= 5:\n query[\"topics\"] = f\"{query['topics']} {args[0]}\" if \"topics\" in query else args[0]\n del args[0]\n # count += 1 is the same as count = count + 1\n count += 1\n\n # How many results to return (max 1000)\n elif first_word in [\"max\", \"maximum\", \"only\"]:\n user_max = convert_num(second_word)\n if user_max and int(user_max) <= 1000:\n query[\"max\"] = user_max\n del args[0:2]\n\n # Remove filler words if they weren't parsed out above\n elif first_word in [\"that\",\"which\",\"and\",\"like\",\"is\"]:\n del args[0]\n\n # Add anything not otherwise parsable to the ml parameter\n else:\n query[\"ml\"] = f\"{query['ml']} {first_word}\" if \"ml\" in query else first_word\n del args[0]\n\n # this is the bottom of that massive while loop\n # if args is not empty by now, we'll start over from the top ^\n\n return query\n # and this is the end of the \"def parse(args, query)\" function\n # whew!","def parse_arguments():\n parser = argparse.ArgumentParser(prog='AdapterRunner', description='Adapter Runner Application')\n parser.add_argument('-a', '--application', action='store', dest='app_name', help='Application Name',\n metavar='<application_name>')\n parser.add_argument('-fi', '--fetch_interval', action='store', dest='fetch_stats_interval', help='Fetch Stats Interval',\n metavar='<fetch_interval in seconds>')\n return parser.parse_args()","def parse_arguments():\n \n parser = argparse.ArgumentParser()\n parser.add_argument(\"postcode\", type=str, help=\"Postcode of current location\")\n parser.add_argument(\"-d\", \"--debug\", \n help=\"Turns on debug mode\", \n action='store_true')\n parser.add_argument(\"-fp\",\"--postcode-file\", \n default=\"postcodes_swift_sample.csv\",\n help=\"Location of Postcode CSV file (default postcodes_swift_sample.csv)\",\n type=str)\n parser.add_argument(\"-fb\",\"--pub-file\", \n default=\"pubnames_swift_sample.csv\",\n help=\"Location of Pub Postcode CSV file (default pubnames_swift_sample.csv)\",\n type=str)\n parser.add_argument(\"-l\",\"--limit\", \n default=10, \n help=\"Limit Number of Results (default 10)\",\n type=int)\n parser.add_argument(\"-m\",\"--max-distance\", \n default=50, \n help=\"Only return results less than this distance (default 50)\",\n type=int)\n return parser","def main():\n parser = argparse.ArgumentParser(description=\"\"\"Tester for YT Data API and different inputs\"\"\")\n parser.add_argument('-a', '--analytics', help='Performs a basic analytics lookup for the user\\'s channel entered')\n parser.add_argument('-c', '--comments', help='Performs a lookup of comments for the video id entered')\n args = parser.parse_args()\n\n if args.analytics:\n analytics = args.analytics\n analyt(analytics)\n\n if args.comments:\n comments = args.comments\n get_comments(comments)","def parse_args():\n default_file_name = 'test.db'\n default_table_name = 'test'\n default_location = 'hasan_bedroom'\n default_node_id = 'SecuritySystem_1'\n\n parser = argparse.ArgumentParser(\n description='Run the SecuritySystemDB test program')\n\n parser.add_argument('-v',\n '--verbose',\n default=False,\n action='store_true',\n help='Print all debug logs')\n\n parser.add_argument('-ss',\n '--security_system',\n default=False,\n action='store_true',\n help='Run SecuritySystemDB test')\n\n parser.add_argument('-f',\n '--file_name',\n type=str,\n default=default_file_name,\n metavar='<file_name.db>',\n help='Specify file name of SQL db (Relative to pwd)')\n\n parser.add_argument('-t',\n '--table_name',\n type=str,\n default=default_table_name,\n metavar='<test_table_name>',\n help='Specify table name of SQL db')\n\n parser.add_argument('-l',\n '--location',\n type=str,\n default=default_location,\n metavar='<owner_room>',\n help='Specify owner and room')\n\n parser.add_argument('-id',\n '--node_id',\n type=str,\n default=default_node_id,\n metavar='<node_id>',\n help='Specify node ID')\n\n args = parser.parse_args()\n return args","def parse_command_line():\n parser = argparse.ArgumentParser(description='Parses ID\\'s from the DDI compendium search results, and then downloads the html and puts them into a sqlite database.')\n parser.add_argument('-f', '--file', dest='file',\n action='store',\n help='Filenname to be read')\n arg_manager = parser.parse_args()\n return arg_manager","def command_line_arguments():\n\n try:\n parser = argparse.ArgumentParser(description='Log Handler/Cleaner/Copier for Idemia DocAuth')\n\n # Add required arguments.\n parser.add_argument('action', choices=['clean', 'download'], type=str, help='clean or download')\n\n # Parse the arguments\n args = parser.parse_args()\n\n return args\n\n except Exception as err:\n print(err)\n return","def __init__(self):\n\n # Set-up the parser object.\n self.parser = argparse.ArgumentParser(description='Boolean query documents using inverted index', formatter_class=RawTextHelpFormatter)\n\n # Option to load the desired documents from a CSV file.\n self.parser.add_argument('documents', type=str, help='''Constructs an inverted index from a CSV file. Required format: One document per line. First line is discarded.\n<id>\\\\t<url>\\\\t<pub_date>\\\\t<title>\\\\t<document_content>\\\\n\n ''')\n\n self.parser.add_argument('-q',metavar='query', type=str, help='Boolean query', action='append')","def main(args):\n options = parse_cmd_parameters_(args)\n execute_(options)","def parse_arguments():\n parser = argparse.ArgumentParser(\n formatter_class=argparse.RawDescriptionHelpFormatter,\n description='''ABX task specification\n\n 'database' is a text file with the '.item' extension containing an\n index of the database and a set of labels or attributes. See input\n format specifications at\n http://abxpy.readthedocs.io/en/latest/FilesFormat.html#dataset\n\n The --on, --across, --by, --filters and --regressors arguments must\n be defined as columns in the database (e.g. speaker or phonemes, if\n your database contains columns defining these attributes)\n\nExample call:\n\n task.py ./my_data.item -o column1 -a column2 column3 -b column4 column5 \\\\\n -f \"[attr == 0 for attr in column3_X]\"\n\n Because optional arguments can have various numbers of inputs, the\n positional arguments ('database' and 'output') must come before the\n mandatory ones, one being preceded by '--'. Thus, those two calls\n are equivalent:\n\n task.py ./my_data.item -o column1 -a column2 column3\n task.py -o column1 -a column2 column3 -- ./my_data.item''')\n\n parser.add_argument(\n '-v', '--verbose', action='store_true',\n help='output messages to the standard output')\n\n parser.add_argument(\n '--stats-only', action='store_true',\n help='add this flag if you only want some statistics '\n 'about the specified task')\n\n parser.add_argument(\n '--tempdir', default=None,\n help='directory where temporary files will be stored')\n\n parser.add_argument(\n '--seed', default=None, type=int,\n help='seed used to initialize the pseudo-random number generator')\n\n # I/O files\n g1 = parser.add_argument_group('I/O files')\n g1.add_argument(\n 'database', help='database item file used to form ABX triplets')\n\n g1.add_argument(\n 'output', nargs='?', default=None,\n help='file to write the generated ABX task, '\n 'default to the database basename with the \\'.abx\\' extension')\n\n # Task specification\n g2 = parser.add_argument_group('Task specification')\n\n g2.add_argument(\n '-o', '--on', required=True, help='ON attribute')\n\n g2.add_argument(\n '-a', '--across', nargs='+', default=[],\n help='ACROSS attributes')\n\n g2.add_argument(\n '-b', '--by', nargs='+', default=[],\n help='BY attributes')\n\n g2.add_argument(\n '-f', '--filters', nargs='+', default=[],\n help='filters specification')\n\n g2.add_argument(\n '-r', '--regressors', nargs='+', default=[],\n help='regressors specification')\n\n g2.add_argument(\n '-t', '--threshold', default=None, type=int,\n help='threshold on the maximal size of a block of'\n ' triplets sharing the same regressors')\n\n return parser.parse_args()","def main(args):","def main(args):","def parse_command_line():\r\n\r\n parser = argparse.ArgumentParser(description='User args')\r\n parser.add_argument(\"--action\", choices=['train', 'predict', 'demo', 'test'], required=True, help=\"Choose action.\")\r\n parser.add_argument(\"--model\", choices=['vgg', 'unet', 'fpn'], required=True, help=\"Choose model.\")\r\n parser.add_argument(\"--dataset\", choices=['full', 'small'], required=True, help=\"Choose dataset.\")\r\n\r\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser(\n description='Manage a database of Airbnb listings.',\n usage='%(prog)s [options]')\n parser.add_argument(\"-v\", \"--verbose\",\n action=\"store_true\", default=False,\n help=\"\"\"write verbose (debug) output to the log file\"\"\")\n parser.add_argument(\"-c\", \"--config_file\",\n metavar=\"config_file\", action=\"store\", default=None,\n help=\"\"\"explicitly set configuration file, instead of\n using the default <username>.config\"\"\")\n # Only one argument!\n group = parser.add_mutually_exclusive_group()\n group.add_argument('-asa', '--addsearcharea',\n metavar='search_area', action='store', default=False,\n help=\"\"\"get and save the name and neighborhoods\n for search area (city)\"\"\")\n group.add_argument('-asv', '--addsurvey',\n metavar='search_area', type=str,\n help=\"\"\"add a survey entry to the database,\n for search_area\"\"\")\n group.add_argument('-dbp', '--dbping',\n action='store_true', default=False,\n help='Test the database connection')\n group.add_argument('-dh', '--displayhost',\n metavar='host_id', type=int,\n help='display web page for host_id in browser')\n group.add_argument('-dr', '--displayroom',\n metavar='room_id', type=int,\n help='display web page for room_id in browser')\n group.add_argument('-f', '--fill', nargs='?',\n metavar='survey_id', type=int, const=0,\n help='fill details for rooms collected with -s')\n group.add_argument('-lsa', '--listsearcharea',\n metavar='search_area', type=str,\n help=\"\"\"list information about this search area\n from the database\"\"\")\n group.add_argument('-lr', '--listroom',\n metavar='room_id', type=int,\n help='list information about room_id from the database')\n group.add_argument('-ls', '--listsurveys',\n action='store_true', default=False,\n help='list the surveys in the database')\n group.add_argument('-psa', '--printsearcharea',\n metavar='search_area', action='store', default=False,\n help=\"\"\"print the name and neighborhoods for\n search area (city) from the Airbnb web site\"\"\")\n group.add_argument('-pr', '--printroom',\n metavar='room_id', type=int,\n help=\"\"\"print room_id information\n from the Airbnb web site\"\"\")\n group.add_argument('-ps', '--printsearch',\n metavar='survey_id', type=int,\n help=\"\"\"print first page of search information\n for survey from the Airbnb web site\"\"\")\n group.add_argument('-psn', '--printsearch_by_neighborhood',\n metavar='survey_id', type=int,\n help=\"\"\"print first page of search information\n for survey from the Airbnb web site,\n by neighborhood\"\"\")\n group.add_argument('-psz', '--printsearch_by_zipcode',\n metavar='survey_id', type=int,\n help=\"\"\"print first page of search information\n for survey from the Airbnb web site,\n by zipcode\"\"\")\n group.add_argument('-psb', '--printsearch_by_bounding_box',\n metavar='survey_id', type=int,\n help=\"\"\"print first page of search information\n for survey from the Airbnb web site,\n by bounding_box\"\"\")\n group.add_argument('-s', '--search',\n metavar='survey_id', type=int,\n help='search for rooms using survey survey_id')\n group.add_argument('-sn', '--search_by_neighborhood',\n metavar='survey_id', type=int,\n help='search for rooms using survey survey_id')\n group.add_argument('-sb', '--search_by_bounding_box',\n metavar='survey_id', type=int,\n help=\"\"\"search for rooms using survey survey_id,\n by bounding box\n \"\"\")\n group.add_argument('-sz', '--search_by_zipcode',\n metavar='survey_id', type=int,\n help=\"\"\"search for rooms using survey_id,\n by zipcode\"\"\")\n group.add_argument('-V', '--version',\n action='version',\n version='%(prog)s, version ' +\n str(SCRIPT_VERSION_NUMBER))\n group.add_argument('-?', action='help')\n\n args = parser.parse_args()\n return (parser, args)","def set_args():\n # Initialise argparse object\n parser = argparse.ArgumentParser(description='Set some arguments for our script')\n # Add some arguments, elements are: short form name, long form name, type of input expected\n # default value if you don't set an argument, help string (shown if you run with --help)\n # nargs is so that we can define multiple values for a single argument\n\n parser.add_argument('-q', '--query-terms', type=str, default='Venezuela Covid',\n help='list of strings to search for', nargs='*')\n\n parser.add_argument('-p', '--page-limit', type=int,\n help='number to limit search pages to')\n\n # set the argument parser and return\n args = parser.parse_args()\n return args","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-e\", \"--events\", type=str,\n help=\"path to events CSV-file\")\n parser.add_argument(\"-d\", \"--data\", type=str,\n help=\"path to data CSV-file\")\n parser.add_argument(\"-l\", \"--limit\", nargs='?', type=int, default=None,\n help=\"max records to be processed\")\n parser.add_argument(\"-t\", \"--timezone\", nargs='?', type=int, default=5,\n help=\"date and time shift\")\n parser.add_argument(\"-o\", \"--optimized\", action='store_true',\n help=\"if specified, then data CSV will be processed\"\n \" by small chunks to escape memory issues\")\n parser.add_argument(\"-v\", \"--verbose\", action='store_true')\n parser.add_argument(\"--output-folder\", nargs='?', type=str,\n default=\"linked\")\n return vars(parser.parse_args())","def parse_args():\n parser = argparse.ArgumentParser(\n description=\"Reads datapacket pcds, interpolates quaternions and generates scans from dataset in config file\")\n parser.add_argument(\"--visualization\", \"-v\", action=\"store_true\", help=\"if generated clouds should be visualized\")\n parser.add_argument(\"--directory\", \"-d\",\n help=\"if only specified directory should be interpolated, e.g. 'fragments/fragment0'\")\n args = parser.parse_args()\n return args.visualization, args.directory","def main(argv, out=print):\n opts = parser.parse_args(argv[1:])\n out(generate_sql(vars(opts)))","def parse_command_line(self, argv):\n from optparse import OptionParser\n usage = \"usage: %prog [options]\"\n parser = OptionParser(usage)\n\n (options, args) = parser.parse_args(argv)","def __parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument('-f', '--force', action=\"store_true\", default=False,\n help='overwrite existing database files during import')\n parser.add_argument('-e', '--extension', action=\"store\", default='txt',\n help='specify file extension. default is \"txt\"')\n parser.add_argument('-d', '--delimiter', action=\"store\", default='\\t',\n help='specify column delimiter. default is tab (\\\\t)')\n parser.add_argument('-m', '--mark', action=\"store\", default='.',\n help='specify decimal mark for numeric data. default is'\n ' dot (.)')\n parser.add_argument('-o', '--outformat', action=\"store\", default='npz',\n help='specify output database format. default is \"npz\"'\n ' for numpy database. use \"mat\" for matlab '\n ' database format.')\n parser.add_argument('-r', '--recursive', action=\"store_true\", default=False,\n help='recursively walk through all sub-directories of'\n ' current working directory')\n parser.add_argument('-p', '--pcs', action=\"store_true\", default=True,\n help='indicate if files are pcs files.')\n parser.add_argument('-c', '--colheadlines', action=\"store\", default='1',\n help='number of lines spanned by the column headers')\n args = parser.parse_args()\n return args","def add_arguments(self):\n super().add_arguments()\n self.parser.add_argument(\n \"sql_command\",\n help=\"The SQL commmand to execute. Use <odb> to reference the filename.\",\n type=str\n )","def parse_command_line():\n parser = argparse.ArgumentParser(\"Falcon Quick Scan\")\n parser.add_argument(\"-f\", \"--config\",\n dest=\"config_file\",\n help=\"Path to the configuration file\",\n required=False\n )\n parser.add_argument(\"-l\", \"--log-level\",\n dest=\"log_level\",\n help=\"Default log level (DEBUG, WARN, INFO, ERROR)\",\n required=False\n )\n parser.add_argument(\"-d\", \"--check-delay\",\n dest=\"check_delay\",\n help=\"Delay between checks for scan results\",\n required=False\n )\n parser.add_argument(\"-p\", \"--pattern\",\n dest=\"pattern\",\n help=\"Target file patterns to scan (defaults to *.*)\",\n required=False\n )\n parser.add_argument(\"-r\", \"--region\",\n dest=\"region\",\n help=\"Region the target bucket resides in\",\n required=False\n )\n parser.add_argument(\"-t\", \"--target\",\n dest=\"target\",\n help=\"Target folder or bucket to scan. Bucket must have 's3://' prefix.\",\n required=True\n )\n\n return parser.parse_args()","def handle_cmdline():\n\n cmdline = ArgumentParser(init_args=['address', 'arch', 'file'],\n address_required=True, address_default=None,\n file_required=True,\n file_help='Flash or memory image to inspect',\n formatter_class=RawDescriptionHelpFormatter,\n usage=_USAGE, description=_DESCRIPTION, epilog=_EPILOG)\n\n cmdline.add_argument('--longhelp',\n choices=['Y', 'N'],\n default=None,\n help=_LONGHELP_TEXT)\n\n cmdline.add_argument('--autocomplete',\n choices=['Y', 'N'],\n default=None,\n help=_AUTOCOMPLETE_TEXT)\n\n cmdline.add_argument('--threshold',\n type=int,\n default=5,\n help='Minimum table size to report. Default: 5')\n\n cmdline.add_argument('--subcmds',\n action='store_true',\n default=False,\n help='Include sub-command tables in displayed results')\n\n cmdline.add_argument('--details',\n action='store_true',\n default=False,\n help='Display more detailed output')\n\n args = cmdline.parse_args()\n\n if args.longhelp is not None:\n args.longhelp = args.longhelp == 'Y'\n\n if args.autocomplete is not None:\n args.autocomplete = args.autocomplete == 'Y'\n\n return args","def parse_arguments():\n parser = ArgumentParser()\n parser.add_argument(\"-p\", \"--path\", required=True, nargs=1,\n dest=\"file_path\", type=str, action=\"store\",\n help=\"path to the root directory\")\n parser.add_argument(\"-q\", \"--quick\", action=\"store_true\",\n default=False, dest=\"quick\",\n help=\"Speed up the search or not\")\n return parser.parse_args()","def parse_arguments(argv):\n parser = argparse.ArgumentParser(\n description='Runs Preprocessing on structured data.')\n parser.add_argument('--output-dir',\n type=str,\n required=True,\n help='Google Cloud Storage which to place outputs.')\n\n parser.add_argument('--schema-file',\n type=str,\n required=False,\n help=('BigQuery json schema file'))\n parser.add_argument('--input-file-pattern',\n type=str,\n required=False,\n help='Input CSV file names. May contain a file pattern')\n\n # If using bigquery table\n # TODO(brandondutra): maybe also support an sql input, so the table can be\n # ad-hoc.\n parser.add_argument('--bigquery-table',\n type=str,\n required=False,\n help=('project:dataset.table_name'))\n\n args = parser.parse_args(args=argv[1:])\n\n if not args.output_dir.startswith('gs://'):\n raise ValueError('--output-dir must point to a location on GCS')\n\n if args.bigquery_table:\n if args.schema_file or args.input_file_pattern:\n raise ValueError('If using --bigquery-table, then --schema-file and '\n '--input-file-pattern, '\n 'are not needed.')\n else:\n if not args.schema_file or not args.input_file_pattern:\n raise ValueError('If not using --bigquery-table, then --schema-file and '\n '--input-file-pattern '\n 'are required.')\n\n if not args.input_file_pattern.startswith('gs://'):\n raise ValueError('--input-file-pattern must point to files on GCS')\n\n return args","def parse_args(self, argv):\n\t\tself.argv={'user': argv[1]}","def _parse_command_line_arguments():\n parser = ArgumentParser(\n description=(\n 'Command-line tool to generate a list of unique from a TS file from FermiFAST'\n ),\n )\n parser.add_argument(\n 'ts-file',\n type=str,\n help=(\n 'A file containing the TS sky map'\n ),\n )\n parser.add_argument('--skiprows',\n type=int,\n help='number of rows to skip at the top (default 0)',\n required=False)\n parser.set_defaults(skiprows=0)\n arguments = vars(parser.parse_args())\n return arguments","def ReadArguments():\n\n args = ParseArguments()\n\n logging.info('Command line arguments...')\n for arg in vars(args):\n logging.info(str(arg) + ': ' + str(getattr(args, arg)))\n logging.info('')\n\n IsTest(args)\n ProcessCacheSize(args)\n ProcessLineSize(args)\n ProcessMulti(args)\n ProcessMemPattern(args)\n ProcessMemFile(args)","def parse_args():\n parser = argparse.ArgumentParser(description='Create a database server to save and return key pair values')\n parser.add_argument('--ip', type=str, required=False, default='localhost', help='IP for server to listen on')\n parser.add_argument('--port', type=int, required=False, default=4000, help='Port for server to listen on')\n\n return parser.parse_args()","def parse_command_line_arguments():\n\n description, epilog = __doc__.split(\"\\n\\n\", 1)\n\n parser = argparse.ArgumentParser(\n formatter_class=argparse.RawDescriptionHelpFormatter,\n description=description,\n epilog=epilog)\n\n parser.add_argument('-s', '--s', dest='s', action='store', type=float, required=True,\n help='Minimum frequency')\n parser.add_argument('-c', '--credentials', dest='credentials', action='store',\n default=\"./.tpass\",\n help='File with Twitter credentials (username and password, separated by a space)')\n\n args = parser.parse_args()\n \n return args","def parseArgs(args):\n parser = argparse.ArgumentParser(description = \"Scrapes baseball-reference.com for player statistics\")\n\n parser.add_argument(\"-d\", \"--domain\", help=\"domain to scrape for statistics. Default is baseball-reference.com\", nargs=1, default=[\"http://www.baseball-reference.com\"])\n parser.add_argument(\"-f\", \"--filename\", help=\"database file to store data in\", required=True, nargs=1, type=argparse.FileType(\"r+\"))\n parser.add_argument(\"-r\", \"--reset\", help=\"removes database before scraping all data from baseball-reference. Conflicts with -u. One of -r and -u must be specified\", action=\"store_true\")\n parser.add_argument(\"-u\", \"--update\", help=\"scrapes baseball-reference and adds all new information to the database. Conflicts with -r. One of -r and -u must be specified\", action=\"store_true\")\n parser.add_argument(\"--verbose\", help=\"enables verbose output\", action=\"store_true\")\n parser.add_argument(\"--version\", help=\"prints out version and exits\", action=\"version\", version=\"%(prog)s ({version})\".format(version=__version__))\n\n parsedArgs = parser.parse_args()\n\n if parsedArgs.reset == parsedArgs.update:\n parser.error(\"-r and -u are conflicting flags. Exactly one must be specified\")\n parser.print_help()\n\n return parsedArgs","def parseArgs( argv ):\r\n\r\n parser = OptionParser()\r\n parser.add_option(\"-o\", \"--order\", type=\"choice\", action=\"store\", choices=[\"p\",\"h\",\"g\",\"c\"], default=\"p\", dest=\"orderType\",\r\n help=\"specify a display sorted by (p)lugin, (c)ve id, (h)ost, or just (g)enerate a hostfile\")\r\n parser.add_option(\"-f\", \"--odf\", type=\"string\", action=\"store\", dest=\"odfOutputFilename\",\r\n help=\"output to this file in ODF format\", default=\"\")\r\n parser.add_option(\"-p\", \"--portlist\", type=\"string\", action=\"store\", dest=\"portList\",\r\n help=\"specify specific ports to show\")\r\n parser.add_option(\"-r\", \"--riskfactors\", type=\"string\", action=\"store\", dest=\"riskFactorsList\", default=\"critical,high,moderate,medium,low,none\",\r\n help=\"specify list of allowable risk factors (default is any of critical,high,moderate,medium,low,none\")\r\n parser.add_option(\"-t\", \"--hostlist\", type=\"string\", action=\"store\", dest=\"hostList\",\r\n help=\"specify specific hosts to show\")\r\n parser.add_option(\"-s\", \"--severities\", type=\"string\", action=\"store\", dest=\"severityList\", default=\"critical_hole,hole,warn,note,info,openport\",\r\n help=\"specify specific list of severity codes to show (default is any of critical_hole,hole,warn,note,info,openport\")\r\n parser.add_option(\"-q\", \"--query\", type=\"string\", action=\"store\", dest=\"contentQuery\",\r\n help=\"show all results whose synopses match this regular expression\")\r\n parser.add_option(\"-i\", \"--idlist\", type=\"string\", action=\"store\", dest=\"pluginIDList\",\r\n help=\"display only results that match these Nessus plugin IDs\")\r\n parser.add_option(\"-c\", \"--csv\", type=\"string\", action=\"store\", dest=\"csvOutputFilename\", default=\"\",\r\n help='output CSV-friendly text delimitted by default or overriden delimiter to a given filename (use \"0\" for standard output)')\r\n# parser.add_option(\"-c\", \"--csv\", action=\"store_true\", dest=\"CSV\", default=False,\r\n# help=\"output CSV-friendly text delimitted by |++| (overridable with the 'd' option)\")\r\n parser.add_option(\"-d\", \"--delimiter\", type=\"string\", action=\"store\", dest=\"delimiter\", default=\"|++|\", \r\n help=\"override CSV delimiter default of |++|\")\r\n\r\n (options, args) = parser.parse_args() \r\n \r\n if options.orderType: options.orderType = options.orderType.lower()\r\n\r\n return (options,args)","def _add_arguments(self):\r\n self._parser.add_argument(\r\n '-s', '--server',\r\n required=True,\r\n help=\"enter server name\")\r\n self._parser.add_argument(\r\n '-db', '--database',\r\n required=True,\r\n help='enter database name')\r\n self._parser.add_argument(\r\n '-u', '--username',\r\n help='enter username')\r\n self._parser.add_argument(\r\n '-p', '--password',\r\n help='enter password')\r\n #self._parser.add_argument(\r\n # '-h', '--help',\r\n # help='show this help message and exit')\r","def parse_arguments(raw_args=sys.argv[1:]):\n parser = optparse.OptionParser(\n usage=\"usage: %prog [OPTIONS] DOMAIN_NAME DOMAIN_CONFIG_FILE\",\n description=\"A tool for provisioning a Khan Academy CloudSearch \"\n \"domain.\")\n\n parser.add_option(\"-v\", \"--verbose\", action=\"store_true\", default=False,\n help=\"If specified, DEBUG messages will be printed and more \"\n \"information will be printed with each log message.\")\n\n parser.add_option(\"--leave-temp-dir\", action=\"store_true\", default=False,\n help=\"If specified, the created temporary directory will not be \"\n \"deleted when the script exits.\")\n\n parser.add_option(\"-n\", \"--dry-run\", action=\"store_true\", default=False,\n help=\"If specified, no commands will actually be executed.\")\n\n parser.add_option(\"--no-reindex\", action=\"store_true\", default=False,\n help=\"If specified, will only update the config, without reindexing.\")\n\n options, args = parser.parse_args(raw_args)\n\n if len(args) != 2:\n parser.error(\"You must specify the name of the domain and a file \"\n \"containing the domain configuration.\")\n\n return (options, args[0], args[1])","def arguments():\n\tparser = argparse.ArgumentParser(description=\"Integrate all columns of a data file. Time is in column 0.\")\n\tparser.add_argument(\"-v\", \"--verbose\", action=\"store_true\", dest=\"verbose\", default=False, help=\"Print debug info.\")\n\tparser.add_argument(\"-k\", \"--kwh\", action=\"store_true\", dest=\"kwh\", default=False, help=\"output in kWh (instead of Ws)\")\n\tparser.add_argument(\"-f\", \"--file\", action=\"store\", dest=\"filename\", help=\"Path to file to read. Defaults to STDIN.\")\n\tparser.add_argument(\"-s\", \"--separator\", dest=\"separator\", default=\",\", help=\"Specify the separation character. Defaults to comma (,).\")\n\n\treturn parser.parse_args()","def get_args_from_command_line():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--input_csv_path\", type=str)\n parser.add_argument(\"--text_column_order\", type=int)\n args = parser.parse_args()\n return args","def _makeParser_search() :\n parser = argparse.ArgumentParser(\n description = SCRIPT_DESCRIPTION_SEARCH)\n parser.add_argument(\"-c\", \"--count\", action = \"store_true\",\n help = \"Just return the number of records, no fetch\")\n # Required named arguments (http://stackoverflow.com/questions/24180527/argparse-required-arguments-listed-under-optional-arguments)\n required = parser.add_argument_group(\"required named arguments\")\n # --email\n required.add_argument(\"-e\", \"--email\", type = str,\n help = \"User's email (required by Entrez)\")\n # --listId\n required.add_argument(\"-l\", \"--listId\", type = str,\n help = \"File containing one GenBank identifier per \"\n \"line. Use - for reading from stdin. \"\n \"Exactly one of --listId or \"\n \"--query must be specified, but not both.\")\n # --query\n required.add_argument(\"-q\", \"--query\", type = str,\n help = \"Query string for GenBank search. \"\n \"Exactly one of --listId or \"\n \"--query must be specified, but not both.\",\n metavar = \"SEARCH_TERM\")\n # Download options\n download = parser.add_argument_group(\"download-related options\")\n # --retmax\n download.add_argument(\"-r\", \"--retmax\", type = int, default = 0,\n help = \"Maximum number of entries to retrieve from \"\n \"GenBank, comprised between 1 and 10000. Use 0 for \"\n \"unlimited number of returned entries. (default: 0)\")\n # --download\n download.add_argument(\"-d\", \"--download\", action = \"store_true\",\n help = \"Download the full GenBank records\")\n # --forceDownload\n download.add_argument(\"-f\", \"--forceDownload\", action = \"store_true\",\n help = \"Download record even if file already exists \"\n \"(implies --download)\")\n # --fullWGS\n download.add_argument(\"--fullWGS\", action = \"store_true\",\n help = \"Also download full WGS sequence data when \"\n \"WGS trace reference is present in a GenBank record \"\n \"(only works if the original GenBank record is to be \"\n \"downloaded too or if --forceDownload is used)\")\n # --outputDir\n download.add_argument(\"-o\", \"--outputDir\", type = str, default = \".\",\n help = \"Destination folder for downloaded records \"\n \"(default: current directory)\")\n # --batchSize\n download.add_argument(\"-b\", \"--batchSize\", type = int, default = 5,\n help = \"Batch size for full record retrieval \"\n \"(default: 5)\")\n # --delay\n download.add_argument(\"--delay\", type = int, default = 15,\n help = \"Delay in seconds between successive batch \"\n \"retrieval of the full records (default: 15)\")\n return parser","def get_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-i\", \"--input\",\n help=\"text file, one compound per line\", required=True)\n parser.add_argument(\"-j\", \"--jsononto\",\n help=\"json ontology of families\", required=True)\n parser.add_argument(\"-o\", \"--output\",\n help=\"output file\", required=True)\n parser.add_argument(\"-e\", \"--encoded\",\n help=\"identifiers are encoded\", action=\"store_true\", default=False)\n\n args = parser.parse_args()\n\n run_analysis(args.input, args.jsononto, args.output, args.encoded)","def _parse_command_line(self):\n DESCRIPTION = (\n \"Application for searching PyLith .cfg parameter files.\"\n )\n\n parser = argparse.ArgumentParser(description=DESCRIPTION,\n formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\"--path\", action=\"store\",\n dest=\"searchpath\", default=\".\", help=\"Search path for .cfg files.\")\n parser.add_argument(\"--display\", action=\"store\",\n dest=\"display\", default=\"all\", help=\"List of metadata to display in search results.\")\n parser.add_argument(\"--verbose\", action=\"store_true\", dest=\"verbose\",\n help=\"Report missing metadata.\")\n\n parser.add_argument(\"--keywords\", action=\"store\", dest=\"keywords\",\n help=\"Comma delimited list of keywords for filtering search results.\")\n parser.add_argument(\"--features\", action=\"store\", dest=\"features\",\n help=\"Comma delimited list of features for filtering search results.\")\n parser.add_argument(\"--authors\", action=\"store\", dest=\"authors\",\n help=\"Comma delimited list of authors for filtering search results.\")\n parser.add_argument(\"--version\", action=\"store\", dest=\"version\",\n help=\"PyLith version for filtering search results.\")\n parser.add_argument(\"--incompatible\", action=\"store_true\", dest=\"incompatible\",\n help=\"Filter search results to show incompatible parameter files.\")\n parser.add_argument(\"--output-format\", action=\"store\", dest=\"output_format\", \n help=\"Output format\", default=\"txt\", choices=[\"text\", \"markdown\"])\n\n args = parser.parse_args()\n\n return args","def process_command_line_arguments() -> Namespace:\n\n parser = build_parser()\n arguments = parser.parse_args()\n\n return arguments","def get_input():\n parser = argparse.ArgumentParser(description='Parameters')\n parser.add_argument('--host', help='adress of the host')\n parser.add_argument('--port', help='port of IPMI host')\n parser.add_argument('--user', help='user allowed to acces IPMI')\n parser.add_argument('--passwd', help='password for the specific user')\n parser.add_argument('--interval', help='seconds between each data reading')\n parser.add_argument('--nread', help='number of time to collect data')\n parser.add_argument('--store', action='store_true',\n help='save the data collected in a nosql db')\n args = parser.parse_args()\n return args, parser","def parse_args():\n\n parser = argparse.ArgumentParser(description='CLI to store Actisense-NGT Gateway values to InfluxDB and publish via MQTT')\n parser.add_argument('--config', '-c', type=str, required=True, help='JSON configuraton file with path')\n return parser.parse_args()","def ParseArguments():\n\n\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--db_file_path\", required = False, help = \"SQLite database filename\", type = str, default = '')\n parser.add_argument(\"--server_url\", required = False, help = \"Server's domain name\", type = str, default = '')\n parser.add_argument(\"--substation_name\", required = False, help = \"Substation name\", type = str, default = '')\n parser.add_argument(\"--net_interfaces\", required = False, help = \"List of network interfaces\", type = str)\n parser.add_argument(\"--no_hostname_check\", required = False, help = \"Disable TLS certificate hostname validation (insecure)\", action = 'store_true')\n parser.add_argument(\"--external_interval\", required = False, help = \"Interval (s) between invocations of external commands\", default = '3')\n parser.add_argument(\"--external_timeout\", required = False, help = \"Maximum time (s) an external command is allowed to run\", default = None)\n parser.add_argument(\"--external_command\", required = False, help = \"Periodically invoke given command to gather external data. Use repeatedly.\", action = 'append', default = [])\n parser.add_argument(\"--uuid\", required = False, help = \"To get UUID or hostname (set by default) as an unique ID.\", action = 'store_true')\n\n argv = parser.parse_args(sys.argv[1:])\n\n config_data = {}\n try:\n if os.path.isfile('config.json'):\n json_data_file = open('config.json', 'r')\n config_data = json.load(json_data_file)\n required_keys = ['db_file_path', 'server_url']\n for key in required_keys:\n if key not in config_data:\n print('config.json file does not contain required key %s' % key)\n sys.exit()\n else:\n print('config.json does not exist in the current directory.')\n sys.exit()\n except IOError:\n sys.exit()\n\n config_data['no_hostname_check'] = argv.no_hostname_check or config_data.get('no_hostname_check', False)\n\n interval = float(argv.external_interval)\n\n if argv.external_timeout is None:\n timeout = interval\n else:\n timeout = float(argv.external_timeout)\n\n if timeout > interval:\n print('Error: External command timeout is longer than interval')\n sys.exit()\n\n config_data['external_interval'] = interval\n config_data['external_timeout'] = timeout\n config_data['external_command'] = argv.external_command\n config_data['substation_name'] = argv.substation_name\n config_data['uuid'] = argv.uuid\n\n if argv.db_file_path == '':\n if not config_data['db_file_path']:\n config_data['db_file_path'] = '/var/local/agent_sqlite3.db'\n print('SQLite3 database file is set by default: /var/local/agent_sqlite3.db')\n else:\n config_data['db_file_path'] = argv.db_file_path\n\n ifs = argv.net_interfaces or config_data.get('net_interfaces', [])\n if isinstance(ifs, str):\n ifs = ifs.split(',')\n config_data['net_interfaces'] = utils.interfaces_to_ip(ifs)\n\n # TODO verify provided URL\n if argv.server_url == '':\n if not config_data['server_url']:\n print('Please, provide server URL as an argument or in config.json file.')\n print('It must be in this format: wss://<domain_name>:443/agent')\n sys.exit()\n else:\n config_data['server_url'] = argv.server_url\n\n\n return config_data","def parse_arguments():\n parser = argparse.ArgumentParser(description='Helps analyze articles.')\n parser.add_argument('--config', default='config.yaml',\n help='Configuration file for the options of this script')\n parser.add_argument('--search', default=None, type=str,\n help='Search for text in the articles')\n parser.add_argument('--case-sensitive', action='store_true',\n help='Makes search case-senstive (only applicatble to --search)')\n parser.add_argument('--list', default=None, type=str,\n help='List [title|authors|date|word-count|author|excerpt|content] of the articles')\n parser.add_argument('--sort', action='store_true',\n help='Sorts output (only applicable to --list).')\n parser.add_argument('--sort-by', default=None, type=str,\n help='Sorts output by another attribute [title|author|date] (only applicable to --list)')\n parser.add_argument('--statistics', action='store_true',\n help='Gives basic statistics about the articles.')\n parser.add_argument('--count-articles', action='store_true',\n help='Counts the total number of articles')\n parser.add_argument('--count-words', action='store_true',\n help='Counts the total number of words')\n parser.add_argument('--count-paragraphs', action='store_true',\n help='Counts the total number of paragraphs')\n parser.add_argument('--count-by-author', action='store_true',\n help='Counts the number of articles by each author')\n parser.add_argument('--count-by-year', action='store_true',\n help='Counts the number of articles bucketed by year')\n parser.add_argument('--count-by-months', default=None, type=int,\n help='Counts the number of articles bucketed by number of months')\n \n return parser, parser.parse_args()","def process_arguments():\r\n # Create ArgumentParser object. Description message will be displayed as part of help message if script is run with -h flag\r\n parser = argparse.ArgumentParser(description='Downloads summary of findings for given interpretation request')\r\n # Define the arguments that will be taken.\r\n parser.add_argument('--ir_id', required=True, help='Interpretation request ID')\r\n parser.add_argument('--ir_version', required=True, help='Interpretation request version')\r\n parser.add_argument('-o', '--output_file', required=True, help='Output PDF')\r\n parser.add_argument('--header', required=False, help='Text for header of report')\r\n # Return the arguments\r\n return parser.parse_args()","def parse_user_arguments(*args, **kwds):\n\n parser = argparse.ArgumentParser(\n description = \"Generates the profiles of the input drug by using a network of expansion created expanding the protein-protein interactions from the targets of the drug\",\n epilog = \"@oliva's lab 2017\")\n parser.add_argument('-d','--drug_name',dest='drug_name',action = 'store',\n help = \"\"\" Name of the drug. If you do not provide targets for this drug or the number of targets is not large enough,\n the program will use this name to search for targets in BIANA database. If targets are provided, this field will be only used\n for naming purposes and will be completely optional.\n If the name of the drug has more than one word or special characters (parentheses, single quotes), introduce the name between \n double quotes. \"\"\")\n parser.add_argument('-t','--targets',dest='targets',action = 'store',\n help = 'Input file with the targets of the drug. Each target must be separated by a newline character.')\n parser.add_argument('-pt','--proteins_type_id',dest='proteins_type_id',action = 'store', default='geneid',\n help = 'Input the type of ID of the targets introduced / proteins of the network. It must be the same! (default is geneid).')\n parser.add_argument('-rad','--radius',dest='radius',action = 'store',default='3',\n help = \"\"\" Define the radius of expansion for the creation of the network from targets (default is 3). \"\"\")\n parser.add_argument('-tax','--taxid',dest='taxid',action = 'store',default='9606',\n help = \"\"\"Define the restriction of species for the creation of the network from targets using a Taxonomy ID (default is '9606' (human))\"\"\")\n parser.add_argument('-res','--restriction',dest='restriction',action = 'store',\n help = \"\"\"Define an experiment restriction for the creation of the network from targets.\\n\n Options:\\n\n - AFF: Use interactions at least described by affinity methods (i.e. Tandem Affinity Purification)\\n\n - Y2H: Use interactions at least described by yeast two hybrid methods (Y2H)\\n\n - eAFF: Use all interactions except those described by affinity methods (i.e. Tandem Affinity Purification)\\n\n - eY2H: Use all interactions except those described by yeast two hybrid methods (Y2H)\\n\n - None: Not use experiment restrictions\n \"\"\")\n parser.add_argument('-th','--threshold_list',dest='threshold_list',action = 'store',\n help = \"\"\"List of percentages that will be used as cut-offs to define the profiles of the drugs. It has to be a file containing:\n - Different numbers that will be the threshold values separated by newline characters. \n For example, a file called \"top_threshold.list\" containing:\n 0.1\n 0.5\n 1\n 5\n 10\n \"\"\")\n parser.add_argument('-ws','--workspace',dest='workspace',action = 'store',default=os.path.join(os.path.join(os.path.dirname(__file__), '..'), 'workspace'),\n help = \"\"\"Define the workspace directory where the data directory and the results directory will be created\"\"\")\n\n options=parser.parse_args()\n\n return options","def parse_args():\n parser = argparse.ArgumentParser(description=\"evaluate the recovered derg by comparing with ground truth mapping file\")\n parser.add_argument(\"-mapping\", action=\"store\", dest=\"mapping_file\",\n required=True, help=\"path to proguard-generated mapping.txt\")\n parser.add_argument(\"-recovered_derg\", action=\"store\", dest=\"recovered_derg\",\n required=True, help=\"path to recovered derg\")\n parser.add_argument(\"-nice2predict_mapping\", action=\"store\", dest=\"nice2predict_mapping_file\",\n help=\"path to nice2predict-generated mapping.txt\")\n parser.add_argument(\"-o\", action=\"store\", dest=\"report_dir\",\n default=\".\", help=\"directory of report files\")\n parser.add_argument(\"-report_name\", action=\"store\", dest=\"report_name\",\n default=DEFAULT_REPORT_NAME, help=\"name of report file\")\n parser.add_argument(\"-match_mode\", action=\"store\", dest=\"match_mode\",\n default=MATCH_MODE_EXACT, help=\"match mode\")\n\n options = parser.parse_args()\n print options\n return options","def run(argv=None):\n parser = argparse.ArgumentParser(description='Query elasticsearch indices/index/documents and print them '\n 'formatted as JSON-Objects',\n formatter_class=argparse.RawTextHelpFormatter)\n parser.add_argument('-server', type=str, help=\"use http://host:port/index/type/id.\\n\"\n \"host:port - hostname or IP with port of the elasticsearch node to query\\n\"\n \" default: localhost:9200\\n\"\n \"index - index to query\\n\"\n \" default: None → queries across all available indices\\n\"\n \"type - elasticsearch doctype to use (optional)\\n\"\n \"id - identifier of one specific document to query (optional)\",\n default=\"http://127.0.0.1:9200\")\n parser.add_argument('-ign-source', action=\"store_true\",\n help='return the Document or just the Elasticsearch-Metadata')\n parser.add_argument('-size', type=str, default=None, metavar=\"N[:M]\",\n help='just return the first n-Records of the search,\\n'\n 'or return a python slice, e.g. 2:10 returns a list\\n'\n 'from the 2nd including the 9th element of the search\\n'\n 'only works with the ESGenerator\\n'\n 'Note: Not all slice variants may be supported')\n parser.add_argument('-timeout', type=int, default=10,\n help='Set the time in seconds after when a ReadTimeoutError can occur.\\n'\n 'Default is 10 seconds. Raise for big/difficult querys ')\n parser.add_argument(\"-includes\", type=str,\n help=\"just include following _source field(s) in the _source object\")\n parser.add_argument(\"-excludes\", type=str,\n help=\"exclude following _source field(s) from the _source object\")\n parser.add_argument(\"-headless\", action='store_true',\n help=\"don't print Elasticsearch metadata\")\n parser.add_argument('-body', type=helperscripts.jsonstring_or_file,\n help='Elasticsearch Query object that can be in the form of\\n'\n '1) a JSON string (e.g. \\'{\"query\": {\"match\": {\"name\": \"foo\"}}}\\')\\n'\n '2) a file containing the upper query string')\n parser.add_argument('-idfile', type=str,\n help=\"path to a file with \\\\n-delimited IDs to process\")\n parser.add_argument('-idfile_consume', type=str,\n help=\"path to a file with \\\\n-delimited IDs to process\")\n parser.add_argument('-missing_behaviour', type=str, choices=['print', 'yield'], default='print',\n help=\"If IDs from an idfile are missing: 'print' or 'yield'\\n\"\n \"and json dict containing the ID, default is 'print'\")\n parser.add_argument('-pretty', action='store_true',\n help=\"prettyprint the json output\")\n parser.add_argument('-verbose', action='store_true',\n help=\"print progress for large dumps\")\n parser.add_argument('-chunksize', type=int, default=1000,\n help=\"chunksize of the search window to use\")\n parser.add_argument(\"-auth\", type=str, nargs=\"?\", const=\"ENV\", metavar=\"USER\",\n help='Provide authentication, this can be done using:\\n'\n '1) set environment variables E2J_USER and E2J_PASSWD. In\\n'\n ' this case there is no further argument needed here\\n'\n '2) as a string \"username\". The password is then asked interactively\\n'\n '3) as \"username:password\" (not recommended)')\n args = parser.parse_args(argv)\n es_kwargs = {} # dict to collect kwargs for ESgenerator\n #parsing server # http://server.de:1234/index/_doc/101\n slashsplit = args.server.split(\"/\") # → [http:, , server.de:1234, index, _doc, 101]\n es_kwargs[\"host\"] = slashsplit[2].rsplit(\":\")[0]\n es_kwargs[\"port\"] = int(args.server.split(\":\")[2].rsplit(\"/\")[0]) # raise Error if port not castable to int\n if len(slashsplit) > 3:\n es_kwargs[\"index\"] = slashsplit[3]\n if len(slashsplit) > 4:\n es_kwargs[\"type_\"] = slashsplit[4]\n if len(slashsplit) > 5:\n es_kwargs[\"id_\"] = slashsplit[5]\n\n if args.auth:\n raise NotImplementedError(\"authentication not yet implemented\")\n # args.pop(\"auth\")\n if args.auth == \"ENV\":\n # check and use environmental username (E2J_USER) and password (E2J_PASSWD)\n pass\n else:\n # parse authentication string: either \"username\" or \"username:password\"\n pass\n\n if args.size:\n \"\"\"\n we build the slice() object here, if this fails because of user input,\n the stacktrace of slice() is very informative, so we don't do our own Error handling here\n for size-searches, we don't use a scroll since the user wants only a small searchwindow\n \"\"\"\n if isinstance(args.size, int): # oh, we got an single number, not a string with an number or even an string describing a slice\n args.size = str(args.size)\n if ':' in args.size:\n es_kwargs[\"slice_\"] = slice(int(args.size.split(':')[0]), int(args.size.split(':')[1]), 1)\n else:\n es_kwargs[\"slice_\"] = slice(0, int(args.size), 1)\n\n if args.headless and args.ign_source:\n helperscripts.eprint(\"ERROR! do not use -headless and -ign-source at the same Time!\")\n exit(-1)\n else:\n es_kwargs[\"headless\"] = args.headless\n es_kwargs[\"source\"] = not args.ign_source\n\n if args.pretty:\n tabbing = 4\n else:\n tabbing = None\n\n if args.includes and isinstance(args.includes, str):\n es_kwargs[\"includes\"] = args.includes.split(\",\")\n if args.excludes and isinstance(args.excludes, str):\n es_kwargs[\"excludes\"] = args.excludes.split(\",\")\n\n if args.chunksize:\n es_kwargs[\"chunksize\"] = args.chunksize\n if args.body:\n es_kwargs[\"body\"] = args.body\n if args.timeout:\n es_kwargs[\"timeout\"] = args.timeout\n if args.verbose:\n es_kwargs[\"verbose\"] = args.verbose\n if args.missing_behaviour and (args.idfile or args.idfile_consume):\n es_kwargs[\"missing_behaviour\"] = args.missing_behaviour\n if args.idfile:\n es_kwargs[\"idfile\"] = args.idfile\n ESGeneratorFunction = IDFile(**es_kwargs).generator()\n elif args.idfile_consume:\n es_kwargs[\"idfile\"] = args.idfile_consume\n ESGeneratorFunction = IDFileConsume(**es_kwargs).generator()\n else:\n ESGeneratorFunction = ESGenerator(**es_kwargs).generator()\n for json_record in ESGeneratorFunction:\n print(json.dumps(json_record, indent=tabbing))","def readArgs():\n parser = argparse.ArgumentParser(description=\n \"\"\"Debug script. This program is used in order to generate a summary\n statistics for the csv files generated by the annotation_parser. Things\n like the average amount of overlap of each window and the average deviation.\n \"\"\")\n\n parser.add_argument('-f', '--csv-dir', metavar='',\n dest='csv_dir',\n action='store', default=os.path.dirname(os.path.abspath(__file__)),\n help='Specify the csv directory.')\n parser.add_argument('-d', '--deviation', metavar='',\n dest='deviation', action='store',\n default=50,\n help='percentage set point from which evaluate the deviation from.')\n\n return parser.parse_args()","def parseArguments(self):\n iterator = iter(sys.argv[1:]) # Skip file name\n for argument in iterator:\n if len(argument) < 2 or argument[:2] != '--':\n self.error('syntax error \"{}\"'.format(argument))\n else:\n def getValueOfArgument(): return next(iterator)\n self.parseArgument(argument[2:], getValueOfArgument)","def parse_args():\n help_text = \"\"\"\n Analyzer of the frequency of use of nouns in the headings of posts on hubr.com\n \"\"\"\n parser = argparse.ArgumentParser(\n description=help_text\n )\n parser.add_argument(\n '-p',\n '--pages',\n type=int,\n dest='page_count',\n default=PAGE_COUNT,\n help=f'Number of pages to parse, default is {PAGE_COUNT}.'\n )\n parser.add_argument(\n '-s',\n '--start',\n type=int,\n default=PAGE_START,\n dest='start_page',\n help=f'Start page number, default is {PAGE_START}.',\n )\n parser.add_argument(\n '-t',\n '--top',\n type=int,\n default=TOP_SIZE,\n dest='top_size',\n help=f'The size of the top noun, default is {TOP_SIZE}.',\n )\n\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"auth\",\n help=\"authentication string for Infermedica API: \"\n \"APP_ID:APP_KEY or path to file containing it.\")\n parser.add_argument(\"--model\",\n help=\"use non-standard Infermedica model/language, \"\n \"e.g. infermedica-es\")\n args = parser.parse_args()\n return args","def parse_arguments():\n parser = argparse.ArgumentParser(description='Scraper')\n parser.add_argument('--prefix', help='Prefix for saving files', default=\"\")\n parser.add_argument('--path', help='Dir path', default=\"\")\n parser.add_argument('--urls_path', help='Url path', default=False)\n parser.add_argument('--url', help='Url', default=False)\n parser.add_argument('--disney', dest='disney', action='store_true', help=\"Choose all disney movies\")\n parser.add_argument('--ngram', help='Max ngram', default=2)\n\n args = parser.parse_args()\n return args","def parse_args():\n parser = argparse.ArgumentParser(\n description='Aggregate Elasticsearch Log data.')\n parser.add_argument(\n '--host',\n default='https://logging-es',\n type=str,\n action='store',\n help='Host name or IP of the Elasticsearch server.'\n )\n parser.add_argument(\n '--port',\n default=9200,\n type=int,\n action='store',\n help='Port number of the Elasticsearch server.'\n )\n parser.add_argument(\n '--ca_certs',\n default='secret/admin-ca',\n type=str,\n action='store',\n help='Path to the CA certificates file'\n )\n parser.add_argument(\n '--cert',\n default='secret/admin-cert',\n type=str,\n action='store',\n help='Path to the client certificate file'\n )\n parser.add_argument(\n '--key',\n default='secret/admin-key',\n type=str,\n action='store',\n help='Path to the client key file'\n )\n\n return parser.parse_args()","def get_args():\n parser = argparse.ArgumentParser(description=\"Processing tweets\")\n\n parser.add_argument(\"-db\", \"--db\", type = str, required = True, \n help = \"The Name of Database to store\")\n\n args = parser.parse_args()\n \n return args","def get_arguments():\n parser = argparse.ArgumentParser(prog=\"python3 olympics.py\",\n description=\"Search for data in olympics database\",\n epilog=\"Run -h for each positional arguments to see more details.\")\n\n subparsers = parser.add_subparsers(help='sub-command help', dest='subcommand')\n\n parser_athlete = subparsers.add_parser('athlete', \n help=\"print athletes based on different options\")\n\n parser_athlete.add_argument('-n', '--nocs', type=str, nargs='+',\n help=\"print all athletes in the given nocs in the arguments\")\n\n parser_athlete.add_argument('-a', '--name', type=str, nargs='+',\n help=\"print all athletes whose names contains the arguments\")\n\n parser_noc = subparsers.add_parser('noc', \n help=\"print nocs based on counts of medals\")\n \n parser_noc.add_argument('-m', '--medal', type=str, nargs='?', choices=['gold', 'silver', 'bronze'],\n help=\"order nocs based on the type of medal in the argument\")\n\n parser_game = subparsers.add_parser('game',\n help=\"print the country winning the most number of gold in a give year\")\n \n parser_game.add_argument('-y', '--year', type=str, nargs='?',\n help=\"print the country winning the most number of gold in a give year\")\n \n args = parser.parse_args()\n\n return args","def _parse_args(self, prepared_args):\n pass","def parse_user_arguments():\n\n ap = argparse.ArgumentParser()\n\n ap.add_argument(\"-m\", \"--method\",\n help=\"Enter the type of baseline run, \"\n \"bm_25, tf_idf or jm_qlm\", required=True)\n\n ap.add_argument(\"-j\", \"--json_fname\", help=\"Enter the path to the json \"\n \"filename containing\"\n \"all the paths to the \"\n \"test_collection\",\n required=True)\n\n return vars(ap.parse_args())","def get_args():\n parser = argparse.ArgumentParser(description='Runner for tasks')\n parser.add_argument('--db_url', help='Database url string to the db.', required=True)\n return parser.parse_args()","def argumentsParser(args):\n\targuments = []\n\tif args.find('\"') > -1:\n\t\tt_arguments = args.split('\"')\n\t\tfor a in t_arguments:\n\t\t\tif a == '' or a == ' ':\n\t\t\t\tpass\n\t\t\telif a[-1] == ' ':\n\t\t\t\targuments.append(a[:-1])\n\t\t\telse:\n\t\t\t\targuments.append(a)\n\telif args.find(\"'\") > -1:\n\t\tt_arguments = args.split(\"'\")\n\t\tfor a in t_arguments:\n\t\t\tif a == '' or a == ' ':\n\t\t\t\tpass\n\t\t\telif a[-1] == ' ':\n\t\t\t\targuments.append(a[:-1])\n\t\t\telse:\n\t\t\t\targuments.append(a)\n\telif args == ' ':\n\t\tpass\n\telse:\n\t\targuments = args.split(' ')\n\treturn arguments","def parse_args():\n\tparser = argparse.ArgumentParser(description='Show video statistics.')\n\tparser.add_argument('--sort', metavar='FIELD', choices=['views', 'likes', 'dislikes'],\n\t default='views',\n\t help='sort by the specified field. Options are views, likes and dislikes.')\n\tparser.add_argument('--max', metavar='MAX', type=int, help='show the top MAX entries only.')\n\tparser.add_argument('--csv', action='store_true', default=False,\n\t help='output the data in CSV format.')\n\tparser.add_argument('--table', action='store_true', default=False,\n\t help='output the data in an ascii table.')\n\tparser.add_argument('--workers', type=int, default=8,\n\t help='number of workers to use, 8 by default.')\n\treturn parser.parse_args()","def parse_args():\n\n\t# Define the input parser\n\tdesc = \"computes long term temperature anomaly trend for the GHNC dataset\"\n\tepilog = \"\"\"\ndatarange input argument is of the format:\n\t\t YYYY[MM[DD]][:YYYY[MM[DD]]]\nWhere the date before the optional ':'' represents the lower bound of\nthe range and the optional date after the : represents the upper\nbound. The optional elements of the date default to the lowest possible\nvalue for the lower bound and to the maximum possible for the upper\none. For example,\n\t2006 is equivalent to 2006/01/01:2006/12/31\n\t2006/02 is equivalent to 2006/02/01:2006/02/28\n\"\"\"\n\n\tparser = argparse.ArgumentParser(description=desc, epilog=epilog,\n\t\t\t\t\t\tformatter_class=argparse.RawDescriptionHelpFormatter)\n\tparser.add_argument(\"daterange\",\n\t\t\t\t\t\thelp=\"range of dates to make available locally\")\n\tparser.add_argument('-t',\"--timeseries\",nargs=2,metavar=('lon','lat'),type=float,\n\t\t\t\t\t\thelp=\"plot timeseries for the lon lat pair of coordinates\")\n\tparser.add_argument('-r',\"--recompute\",default=False,action='store_true',\n\t\t\t\t\t\thelp=\"force recompute trend\")\n\n\treturn parser.parse_args()","def Args(parser):\n parser.add_argument('appname', help='The sample app name, e.g. \"finance\".')\n\n parser.add_argument(\n '--duration',\n default='1h',\n type=arg_parsers.Duration(),\n help=('Duration of time allowed to run before stopping the workload.'))\n parser.add_argument(\n '--port', type=int, help=('Port of the running backend service.'))\n parser.add_argument(\n '--target-qps', type=int, help=('Target requests per second.'))","def Args(parser):","def get_command_line_arguments():\n parser = argparse.ArgumentParser(description=\"Build XENON1T events from the DAQ.\")\n\n parser.add_argument('--config',\n default=['eventbuilder'],\n nargs='+',\n help=\"Name(s) of the pax configuration(s) to use, default is eventbuilder. \")\n parser.add_argument('--config_path',\n default=[],\n nargs='+',\n help=\"Path(s) of the configuration file(s) to use.\")\n\n parser.add_argument('--cpus', default=1, nargs='?',\n help=\"Number of CPUs to use for event building. Default is 1; can be 'all'.\")\n parser.add_argument('--detector', default='tpc', type=str,\n help=\"Detector to build events for\")\n parser.add_argument('--log', default='INFO',\n help=\"Logging level to use, e.g. DEBUG\")\n parser.add_argument('--secret_mode', action='store_true',\n help=\"Never write anything to the runs db. Use only for testing!\")\n parser.add_argument('--wait', default=10, type=int,\n help=\"Wait time before searching for new runs again if none were found (sec). \"\n \"If 0, instead shuts down if no new runs are found.\")\n\n connection_group = parser.add_argument_group(title='MongoDB connection settings')\n connection_group.add_argument('--host', default='gw', type=str,\n help='MongoDB hostname')\n connection_group.add_argument('--port', default=27017, type=int,\n help='Port on host where MongoDB runs')\n connection_group.add_argument('--user', default='eb', type=str,\n help='User to connect to MongoDB')\n connection_group.add_argument('--password', type=str, default=os.environ.get('MONGO_PASSWORD'),\n help='Password to connect to MongoDB. '\n 'If not provided, will try to use MONGO_PASSWORD from env')\n\n single_run_group = parser.add_mutually_exclusive_group()\n single_run_group.add_argument('--run_name', type=str,\n help=\"Instead of building all waiting_to_be_processed runs, \"\n \"look for this specific run name and build it.\")\n single_run_group.add_argument('--run', type=int,\n help=\"Instead of building all waiting_to_be_processed runs, \"\n \"look for this specific run number and build it.\")\n\n trigger_group = parser.add_argument_group(title='Trigger settings',\n description='Override default settings for the trigger.')\n trigger_group.add_argument('--force_multiplicity_trigger', type=int,\n help='Forces the trigger into a more basic mode: always trigger on a signal of more than'\n 'force_multiplicity_trigger pulses, and never on smaller signals.')\n trigger_group.add_argument('--signal_separation', type=float,\n help='If no pulses start for this length of time (us),'\n 'a signal ends / a new signal can start.')\n trigger_group.add_argument('--event_separation', type=float,\n help='If there are no triggers for this length of time (us),'\n 'a new event can start.')\n trigger_group.add_argument('--left_extension', type=float,\n help=\"Minimum range before each trigger to save (us). Is abs()ed before it is used.\")\n trigger_group.add_argument('--right_extension', type=float,\n help='Minimum time after trigger to save (us).')\n\n mongoreader_group = parser.add_argument_group(title='Trigger driving / Mongo reading settings')\n mongoreader_group.add_argument('--batch_window', type=float,\n help='Length of time range (in sec, float) to get pulse data in each query.')\n mongoreader_group.add_argument('--delete_data', action='store_true',\n help=\"Delete data from the untriggered collection while triggering on it. \"\n \"Essential for running the trigger live for an extended time!\")\n mongoreader_group.add_argument('--edge_safety_margin', type=int,\n help=\"When triggering live, stay at least this many seconds \"\n \"away from the insertion edge.\")\n mongoreader_group.add_argument('--max_query_workers', type=int,\n help=\"Maximum number of parallel pulse time range queries \"\n \"to fire off in the trigger. If delete_data, this is also the maximum \"\n \"number of parallel delete queries.\")\n mongoreader_group.add_argument('--skip_ahead', type=int, default=0,\n help=\"After triggering a batch of data, skip ahead this number of batches \"\n \"without triggering. \"\n \"Use only for dealing quickly with runs that have overflown to disk!\")\n mongoreader_group.add_argument('--stop_after_sec', type=float,\n help=\"Stop the trigger after this many seconds of data have been read. \"\n \"Won't stop in the middle of a batch. Use only for testing!\")\n\n args = parser.parse_args()\n return args","def parse_arguments():\n parser = ArgumentParser(description=\"Run tests in parallel.\")\n parser.add_argument(\n \"-d\", \"--debug\", action=\"store_true\", help=\"Enable debug logging\"\n )\n parser.add_argument(\n \"-l\", \"--layer\", help=\"Greedy match test layer name.\", action=\"append\"\n )\n parser.add_argument(\n \"-m\", \"--module\", help=\"Greedy match module name.\", action=\"append\"\n )\n return parser.parse_args()","def parse_command_line():\n parser = argparse.ArgumentParser(prog='scoring')\n parser.add_argument(\"pdb_list\", help=\"list of PDB structures\")\n script_args = parser.parse_args()\n return script_args","def parse_arguments():\n\n parser = argparse.ArgumentParser()\n\n parser.add_argument(\"--accessions\", help=\"A json file with old/new family mapppings\")\n parser.add_argument(\"--add-header\", help=\"Print descriptive header\",\n action=\"store_true\", default=False)\n parser.add_argument(\"--add-links\", help=\"Creates hyperlinks to available Rfam html content\",\n action=\"store_true\", default=False)\n return parser","def command_line_arguments():\n _parser.add_argument('-l', '--list', nargs='+',\n help='<Required> Set flag', required=True)\n _parser.add_argument(\"-A\", \"--access\", required=True,\n help=\"access to host => grant/revoke\")","def parseArguments():\n parser = argparse.ArgumentParser()\n parser.add_argument('--output_folder',\n help='Path of the folder where output files should be written.')\n parser.add_argument('--partition_id',\n help='ID of the computer partition to collect data from.')\n parser.add_argument('--collector_db',\n help='The path of slapos collect database.')\n\n return parser.parse_args()"],"string":"[\n \"def parse_arguments(args):\",\n \"def arg_parse():\\n p = ap.ArgumentParser()\\n p.add_argument('column_name',\\n type=str,\\n help='column_name to search')\\n p.add_argument('operation',\\n choices=['gt', 'lt', 'eq'])\\n p.add_argument('limit',\\n type=float,\\n help='limit to search by')\\n return p.parse_args()\",\n \"def query_cmdline():\",\n \"def query(args):\\n dbh = despydb.DesDbi(args.service, args.section)\\n if args.query not in \\\"-+\\\":\\n do1Query(dbh, args.query, args)\\n elif args.query == \\\"-\\\":\\n line = sys.stdin.readline()\\n while line:\\n line = line.strip()\\n if not line or line.startswith(\\\"#\\\"):\\n pass\\n else:\\n do1Query(dbh, line, args)\\n line = sys.stdin.readline()\\n else: #if args.query == \\\"+\\\":\\n lines = sys.stdin.read()\\n do1Query(dbh, lines, args)\\n dbh.close()\",\n \"def parse_cmdline_args():\\n parser = argparse.ArgumentParser(description=\\\"Guesses the functional element for host.\\\")\\n ##\\n ## Internal options\\n ##\\n parser.add_argument(\\\"--json\\\", dest=\\\"json\\\", action='store_true', help=\\\"output in JSON\\\")\\n\\n ##\\n ## PuppetDB options\\n ##\\n pdbconf = PdbConfig()\\n pdbconf.add_standard_args(parser)\\n\\n parser.add_argument(\\\"host\\\", metavar=\\\"HOST\\\",\\n help=\\\"hostnames to query for FE\\\")\\n\\n return parser.parse_args()\",\n \"def _parse_args():\\n parser = argparse.ArgumentParser(description='main.py')\\n \\n # General system running and configuration options\\n parser.add_argument('--do_nearest_neighbor', dest='do_nearest_neighbor', default=False, action='store_true', help='run the nearest neighbor model')\\n\\n parser.add_argument('--train_path', type=str, default='data/geo_train.tsv', help='path to train data')\\n parser.add_argument('--dev_path', type=str, default='data/geo_dev.tsv', help='path to dev data')\\n parser.add_argument('--test_path', type=str, default='data/geo_test.tsv', help='path to blind test data')\\n parser.add_argument('--test_output_path', type=str, default='geo_test_output.tsv', help='path to write blind test results')\\n parser.add_argument('--domain', type=str, default='geo', help='domain (geo for geoquery)')\\n \\n # Some common arguments for your convenience\\n parser.add_argument('--seed', type=int, default=0, help='RNG seed (default = 0)')\\n parser.add_argument('--epochs', type=int, default=100, help='num epochs to train for')\\n parser.add_argument('--lr', type=float, default=.001)\\n parser.add_argument('--batch_size', type=int, default=2, help='batch size')\\n # 65 is all you need for GeoQuery\\n parser.add_argument('--decoder_len_limit', type=int, default=65, help='output length limit of the decoder')\\n\\n # Feel free to add other hyperparameters for your input dimension, etc. to control your network\\n # 50-200 might be a good range to start with for embedding and LSTM sizes\\n args = parser.parse_args()\\n return args\",\n \"def ParseCommandArguments(args):\\n\\n\\n\\n import argparse\\n from google.appengine.tools import boolean_action\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-A', '--application', required=True)\\n parser.add_argument('--api_host', default='')\\n\\n parser.add_argument('--api_port', default=8000, type=int)\\n parser.add_argument('--trusted',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n parser.add_argument('--application_root', default=None)\\n parser.add_argument('--application_host', default='localhost')\\n parser.add_argument('--application_port', default=None)\\n\\n\\n parser.add_argument('--blobstore_path', default=None)\\n\\n\\n parser.add_argument('--datastore_path', default=None)\\n\\n parser.add_argument('--auto_id_policy', default='scattered',\\n type=lambda s: s.lower(),\\n choices=(datastore_stub_util.SEQUENTIAL,\\n datastore_stub_util.SCATTERED))\\n\\n parser.add_argument('--use_sqlite',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n parser.add_argument('--high_replication',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n parser.add_argument('--require_indexes',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n parser.add_argument('--clear_datastore',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n\\n\\n parser.add_argument('--logs_path', default=None)\\n\\n\\n parser.add_argument('--enable_sendmail',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n parser.add_argument('--smtp_host', default='')\\n\\n parser.add_argument('--smtp_port', default=25, type=int)\\n parser.add_argument('--smtp_user', default='')\\n parser.add_argument('--smtp_password', default='')\\n parser.add_argument('--show_mail_body',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n\\n\\n parser.add_argument('--prospective_search_path', default=None)\\n parser.add_argument('--clear_prospective_search',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=False)\\n\\n\\n parser.add_argument('--enable_task_running',\\n action=boolean_action.BooleanAction,\\n const=True,\\n default=True)\\n\\n parser.add_argument('--task_retry_seconds', default=30, type=int)\\n\\n\\n parser.add_argument('--user_login_url', default=None)\\n parser.add_argument('--user_logout_url', default=None)\\n\\n return parser.parse_args(args)\",\n \"def main(args):\\n index = Index()\\n tag_query = keyword_query = None\\n\\n if args.get(\\\"--tag\\\"):\\n tags = [s.strip() for s in args[\\\"--tag\\\"].split(\\\",\\\")]\\n terms = [Term(\\\"tag\\\", s) for s in tags if s]\\n if terms:\\n tag_query = And(terms)\\n\\n if args.get(\\\"KEYWORD\\\"):\\n keyword_query = index.parse(\\\" \\\".join(kw for kw in args[\\\"KEYWORD\\\"]))\\n\\n if keyword_query:\\n search = index.search(keyword_query, filter=tag_query)\\n else:\\n assert tag_query # at least one should have been required by docopt\\n search = index.search(tag_query)\\n\\n with search as results:\\n for result in results:\\n print(format(result, TEMPLATE))\\n return 0\",\n \"def handle_cmdline_args():\\n\\n parser = argparse.ArgumentParser(\\n description='Generate synthetic data from a specification in a json '\\n 'file using the \\\"synth-method\\\" described in the json file. ')\\n\\n parser.add_argument(\\n '-i', dest='infile', required=True,\\n help='The input json file. Must contain a \\\"synth-method\\\" property')\\n\\n parser.add_argument(\\n '-o', dest='outfile_prefix', required=True, help='The prefix of the output paths (data json and csv), relative to the QUIPP-pipeline root directory')\\n\\n args = parser.parse_args()\\n return args\",\n \"def parseArguments():\\n parser = argparse.ArgumentParser(description='Tool run benchmarks and query database')\\n parser.add_argument('--version', action=\\\"store_true\\\", dest=\\\"version\\\", default=False, help=\\\"Print version\\\")\\n parser.add_argument(\\\"--query\\\", \\\"-q\\\", action=\\\"store_true\\\", dest=\\\"queryDataBase\\\", default=False, help=\\\"Query Data Base\\\")\\n parser.add_argument(\\\"--performance\\\", \\\"-p\\\", action=\\\"store_true\\\", dest=\\\"queryPerformance\\\", default=False, help=\\\"Query Data Base - Performance Metrics\\\")\\n parser.add_argument(\\\"--run\\\", \\\"-r\\\", action=\\\"store_true\\\", dest=\\\"runBenchmarks\\\", default=False, help=\\\"Run Benchmarks and store results in the DB\\\")\\n args = parser.parse_args()\\n return args\",\n \"def parse_command_line_arguments(argv):\\n print(\\\"reading command line arguments in...\\\")\\n\\n parser = argparse.ArgumentParser(description='Description of your program')\\n parser.add_argument('-i', '--input', help='Location of input csv file', required=True)\\n parser.add_argument('-p', '--predicting', help='The column name containing the category to predict', required=True)\\n parser.add_argument('-s', '--scoring', help='The scoring type to be used with model evaluation', required=False)\\n parser.add_argument('-c', '--scale', help='List of column names to scale values for', nargs='+', required=False)\\n args = parser.parse_args()\\n\\n return args.input, args.predicting, args.scoring, args.scale\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description='database update')\\n parser.add_argument('--host', dest='host', help='database host',\\n default=\\\"localhost\\\")\\n parser.add_argument('--database', dest='database', help='database name',\\n default='x5gon_dirty')\\n parser.add_argument('--user', dest='user', help='database user',\\n default=\\\"postgres\\\")\\n parser.add_argument('--password', dest='password', help='database password',\\n default='hayleys')\\n parser.add_argument('--procs', dest='procs', help='number of parallel processes',\\n default=10)\\n parser.add_argument('--out', dest='out', help='output file name',\\n default=\\\"output\\\")\\n parser.add_argument('--tf_conf', dest='tf_conf', help='threshold for TF similarity',\\n default=0.85)\\n parser.add_argument('--wiki_conf', dest='wiki_conf', help='threshold for WIKI similarity',\\n default=0.95)\\n arguments = parser.parse_args()\\n return arguments\",\n \"def _parse_args():\\n parser = argparse.ArgumentParser(description='main.py')\\n \\n # General system running and configuration options\\n parser.add_argument('--do_nearest_neighbor', dest='do_nearest_neighbor', default=False, action='store_true', help='run the nearest neighbor model')\\n parser.add_argument('--debug', dest='debug', default=False, action='store_true', help='set to debug mode ')\\n parser.add_argument('--num_train_sentence', dest='num_train_sentence', type=int, default=-1,\\n help='set number of sentence to train on')\\n parser.add_argument('--train_path', type=str, default='data/geo_train.tsv', help='path to train data')\\n parser.add_argument('--dev_path', type=str, default='data/geo_dev.tsv', help='path to dev data')\\n parser.add_argument('--test_path', type=str, default='data/geo_test.tsv', help='path to blind test data')\\n parser.add_argument('--test_output_path', type=str, default='geo_test_output.tsv', help='path to write blind test results')\\n parser.add_argument('--domain', type=str, default='geo', help='domain (geo for geoquery)')\\n parser.add_argument('--attn_model', type=str, default='general', help='Attention model to use: general (default), dot, concat')\\n\\n # Some common arguments for your convenience\\n parser.add_argument('--seed', type=int, default=0, help='RNG seed (default = 0)')\\n parser.add_argument('--epochs', type=int, default=100, help='num epochs to train for')\\n parser.add_argument('--lr', type=float, default=.001)\\n parser.add_argument('--batch_size', type=int, default=2, help='batch size')\\n # 65 is all you need for GeoQuery\\n parser.add_argument('--decoder_len_limit', type=int, default=65, help='output length limit of the decoder')\\n\\n # Feel free to add other hyperparameters for your input dimension, etc. to control your network\\n # 50-200 might be a good range to start with for embedding and LSTM sizes\\n args = parser.parse_args()\\n return args\",\n \"def handle_arguments(cls, *args, **kwargs):\\n connection_info = misc_utils.ConnectionInfo(\\n kwargs[\\\"dictionary\\\"], kwargs[\\\"ip_address\\\"], kwargs[\\\"port\\\"]\\n )\\n search_info = misc_utils.SearchInfo(\\n kwargs[\\\"is_printing_list\\\"],\\n kwargs[\\\"ids\\\"],\\n kwargs[\\\"components\\\"],\\n kwargs[\\\"search\\\"],\\n kwargs[\\\"json\\\"],\\n )\\n\\n cls._execute_command(\\n connection_info, search_info, kwargs[\\\"command_name\\\"], kwargs[\\\"arguments\\\"]\\n )\",\n \"def parse_parameters():\\n parser = argparse.ArgumentParser(description='Program that checks for bad evaluations.')\\n parser.usage = 'bettercorrectors [-h] client_id client_secret start_date [end_date] [--sql file]'\\n parser.add_argument('client_id', help='the client_id of your intranet application', type=str)\\n parser.add_argument('client_secret', help='the client_secret of your intra application', type=str)\\n parser.add_argument('start_date', help='the latest date in iso format', type=datetime.fromisoformat)\\n parser.add_argument('end_date', help='the closest date in iso format (optional)', type=datetime.fromisoformat,\\n default=datetime.now(), nargs='?')\\n parser.add_argument('--sql', dest='file', help='''name of the database file in case you want to save results in a \\n sqlite database''', type=str)\\n args = parser.parse_args()\\n return args\",\n \"def main():\\n args = parse_args()\\n\\n make_session = bootstrap(\\n 'sqlite:///{}'.format(DB_NAME),\\n )\\n session = make_session()\\n\\n for vase in session.query(Vase).order_by(Vase.produced_start):\\n for query_str in make_searches(vase):\\n pass\",\n \"def parse_command_line():\\n parser = ArgumentParser(description=__doc__,\\n formatter_class=RawTextHelpFormatter,\\n epilog=\\\"For a list of table formats check this page: \\\"\\n \\\"https://github.com/astanin/python-tabulate#table-format\\\"\\n )\\n requir = parser.add_argument_group(\\\"required arguments\\\")\\n requir.add_argument(\\\"-f\\\", \\\"--find\\\",\\n required=True,\\n help=\\\"Search string to identify\\\"\\n )\\n requir.add_argument(\\\"-k\\\", \\\"--client_id\\\",\\n required=True,\\n help=\\\"CrowdStrike API client ID\\\"\\n )\\n requir.add_argument(\\\"-s\\\", \\\"--client_secret\\\",\\n required=True,\\n help=\\\"CrowdStrike API client secret\\\"\\n )\\n parser.add_argument(\\\"-r\\\", \\\"--reverse\\\",\\n help=\\\"Reverse the sort.\\\",\\n default=False,\\n action=\\\"store_true\\\"\\n )\\n parser.add_argument(\\\"-t\\\", \\\"--types\\\",\\n help=\\\"Types to search (indicator, report or actor). Comma delimited.\\\"\\n )\\n parser.add_argument(\\\"-tf\\\", \\\"--table_format\\\",\\n help=\\\"Set the table format.\\\",\\n default=\\\"fancy_grid\\\"\\n )\\n parser.add_argument(\\\"-o\\\", \\\"--output_prefix\\\",\\n help=\\\"Output filename prefix for storing results (CSV format).\\\",\\n default=None\\n )\\n\\n parsed = parser.parse_args()\\n allow = [\\\"indicator\\\", \\\"report\\\", \\\"actor\\\"]\\n parsed.types = [t for t in parsed.types.split(\\\",\\\") if t in allow] if parsed.types else allow\\n\\n return parsed\",\n \"def parse_arguments(self):\\n \\n for arg in sys.argv[1:]:\\n (key, sep, value) = arg.partition(\\\"=\\\")\\n if sep != \\\"=\\\":\\n raise ProcessorError(\\\"Illegal argument '%s'\\\" % arg)\\n self.update_data(key, value)\",\n \"def parse_args():\\n parser = MyParser(description='Data processing and analytics library \\\\\\n for OpenStack Browbeat perf data')\\n\\n parser.add_argument('-s', '--summary', dest=\\\"days\\\", type=int, default=-1,\\n help='-s N summary of last N days of results')\\n\\n parser.add_argument('--summary-uuid', dest=\\\"summary_uuid\\\", type=str,\\n default=None,\\n help='--summary-uuid UUID summary of a specific uuid')\\n\\n parser.add_argument('--short-summary', dest=\\\"short_days\\\", type=int,\\n default=-1,\\n help='--short-summary N gives \\\\\\n summary of last N days of results but uses cockroach \\\\\\n db so only provides with basic summary')\\n\\n parser.add_argument('--upload-timesummary', dest=\\\"timeseries_uuid\\\",\\n type=str, default=None,\\n help='--upload-timesummary UUID \\\\\\n uploads the features computed from data obtained from\\\\\\n graphite. ')\\n\\n parser.add_argument('--upload-logsummary', dest=\\\"loggin_uuid\\\",\\n type=str, default=None,\\n help='--upload-logsummary UUID \\\\\\n uploads the log summary to crdb \\\\\\n currently just summarizes over entire timeperiod. ')\\n\\n parser.add_argument('-u', '--update-db', dest='update', type=bool,\\n default=False,\\n help='-u True pushes data to cockroach db')\\n\\n parser.add_argument('--update-clf', dest=\\\"clf_days\\\", type=int,\\n default=-1,\\n help='--update-clf 60 will update all classifiers \\\\\\n listed in config file under classifier_lists \\\\\\n using data from last 60 days')\\n\\n parser.add_argument('--test-clf', dest=\\\"test_days\\\", type=int,\\n default=-1,\\n help='--test-clf 60 will train all classifiers \\\\\\n listed in config file under classifier_lists \\\\\\n using data from last 60 days and then test it \\\\\\n and display metrics')\\n\\n parser.add_argument('-v', '--osp-version', dest='version', type=str,\\n default=None,\\n help='-v 11-tripleo only returns hits for that \\\\\\n OpenStack version, \\\\\\n only supported by summary right now')\\n\\n parser.add_argument('-c', '--config', dest='config', type=str,\\n default=pkg_resources.resource_filename('bml',\\n \\\"config.yml\\\"),\\n help='-c <config file path> use custom config file')\\n\\n args = parser.parse_args()\\n return args\",\n \"def command_line_args(parser):\\n AbyssAssembler.command_line_args(parser)\\n SpadesAssembler.command_line_args(parser)\\n TrinityAssembler.command_line_args(parser)\\n VelvetAssembler.command_line_args(parser)\",\n \"def main():\\n args = parse_args()\\n process_args(args)\",\n \"def parse_arguments():\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\n '--output',\\n type=str,\\n required=False,\\n help='GCS URL where results will be saved as a CSV.')\\n parser.add_argument(\\n '--query',\\n type=str,\\n required=True,\\n help='The SQL query to be run in BigQuery')\\n parser.add_argument(\\n '--dataset_id',\\n type=str,\\n required=True,\\n help='Dataset of the destination table.')\\n parser.add_argument(\\n '--table_id',\\n type=str,\\n required=True,\\n help='Name of the destination table.')\\n parser.add_argument(\\n '--project',\\n type=str,\\n required=True,\\n help='The GCP project to run the query.')\\n\\n args = parser.parse_args()\\n return args\",\n \"def main(args):\\n cli = CLI()\\n # Check arguments\\n cli.parse_arguments(args)\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-u', '--urls_dirpath', type=unicode)\\n parser.add_argument('-r', '--resources_dir', type=unicode)\\n parser.add_argument('-t', '--total_docs', type=int)\\n parser.add_argument('-m', '--mapping', type=unicode,\\n help='File with the yago to lkif mapping')\\n\\n return parser.parse_args()\",\n \"def parse_arguments(args):\\n \\n parser = argparse.ArgumentParser(\\n description= \\\"Join gene, pathway, or taxonomy tables\\\\n\\\",\\n formatter_class=argparse.RawTextHelpFormatter)\\n parser.add_argument(\\n \\\"-v\\\",\\\"--verbose\\\", \\n help=\\\"additional output is printed\\\\n\\\", \\n action=\\\"store_true\\\",\\n default=False)\\n parser.add_argument(\\n \\\"-i\\\",\\\"--input\\\",\\n help=\\\"the directory of tables\\\\n\\\",\\n required=True)\\n parser.add_argument(\\n \\\"-o\\\",\\\"--output\\\",\\n help=\\\"the table to write\\\\n\\\",\\n required=True)\\n parser.add_argument(\\n \\\"--file_name\\\",\\n help=\\\"only join tables with this string included in the file name\\\")\\n parser.add_argument(\\n \\\"-s\\\",\\\"--search-subdirectories\\\", \\n help=\\\"search sub-directories of input folder for files\\\\n\\\", \\n action=\\\"store_true\\\",\\n default=False)\\n\\n return parser.parse_args()\",\n \"def parse_cmdline():\\n\\tparser = ArgumentParser(prog=\\\"FastP_QC.py\\\", description=\\\"\\\"\\\"Script collects stats from fastp jsons.\\\"\\\"\\\")\\n\\tparser.add_argument(\\\"-r1\\\", \\\"--r1_stats\\\", dest=\\\"r1_stats\\\", action=\\\"store\\\", required=True, help=\\\"Text file with r1 stats, from q30.py script.\\\")\\n\\tparser.add_argument(\\\"-r2\\\", \\\"--r2_stats\\\", dest=\\\"r2_stats\\\", action=\\\"store\\\", required=True, help=\\\"Text file with r2 stats, from q30.py script.\\\")\\n\\tparser.add_argument(\\\"-n\\\", \\\"--name\\\", dest=\\\"name\\\", action=\\\"store\\\", required=True, help=\\\"Sample name\\\")\\n\\targs = parser.parse_args()\\n\\treturn args\",\n \"def get_query_params_from_command_line():\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-w', '--way',\\n help='input way type(\\\"ONE_WAY\\\" or \\\"ROUND_TRIP\\\")')\\n parser.add_argument('-d', '--dep_city',\\n help='input departure city(\\\"LIS\\\", \\\"CUN\\\", \\\"PUJ\\\")')\\n parser.add_argument('-a', '--arr_city',\\n help='input arrival city(\\\"LIS\\\", \\\"CUN\\\", \\\"PUJ\\\")')\\n parser.add_argument('-d_d', '--dep_date', help='input a departure date')\\n parser.add_argument('-r', '--ret_date', help='input a return date')\\n parser.add_argument('-n_a', '--num_adults',\\n help='input a number of adults')\\n parser.add_argument('-n_c', '--num_child',\\n help='input a number of children')\\n parser.add_argument('-n_i', '--num_infants',\\n help='input a number of infants')\\n args = parser.parse_args()\\n\\n if not check_flight_type(args.way):\\n return None\\n else:\\n args.way = args.way.upper()\\n\\n if not check_cities(args.dep_city, args.arr_city):\\n return None\\n else:\\n args.dep_city = args.dep_city.upper()\\n args.arr_city = args.arr_city.upper()\\n\\n if args.way == 'ONE_WAY':\\n args.ret_date = args.dep_date\\n if not check_dates(args.dep_date, args.ret_date):\\n return None\\n\\n if not check_passengers(args.num_adults, args.num_child, args.num_infants):\\n return None\\n\\n cl_args = {'flight_type': args.way, 'dep_city': args.dep_city, 'arr_city': args.arr_city,\\n 'dep_date': args.dep_date, 'ret_date': args.ret_date, 'adults': args.num_adults,\\n 'children': args.num_child, 'infants': args.num_infants}\\n\\n return cl_args\",\n \"def parseArgs():\\n parser = argparse.ArgumentParser(description='Runs RHEAS simulation.')\\n parser.add_argument('config', help='configuration file')\\n parser.add_argument('-d', metavar='DB', help='name of database to connect')\\n parser.add_argument('-u', help='update database', action='store_true')\\n args = parser.parse_args()\\n return args.config, args.d, args.u\",\n \"def main_parse_args():\\n parser = ArgumentParser()\\n parser.add_argument('infile', help='path to the file to be mapped.It should\\\\\\n contain one identifer on each line.')\\n parser.add_argument('-rh', '--redis_host', default=DEFAULT_REDIS_URL,\\n help='url of Redis db')\\n parser.add_argument('-rp', '--redis_port', default=DEFAULT_REDIS_PORT,\\n help='port for Redis db')\\n parser.add_argument('-rps', '--redis_pass', default=DEFAULT_REDIS_PASS,\\n help='password for Redis db')\\n parser.add_argument('-of', '--outfile', default=None,\\n help='path to the output file')\\n parser.add_argument('-sh', '--source_hint', help='suggestion for ID source \\\\\\n database used to resolve ambiguities in mapping',\\n default=DEFAULT_HINT)\\n parser.add_argument('-t', '--taxon', help='taxon id of species of all gene \\\\\\n names', default=DEFAULT_TAXON)\\n myargs = parser.parse_args()\\n return myargs\",\n \"def add_args(self): \\n self.parser.add_argument('-u', '--username',\\n default=None,\\n help='the username for mongoDB (Default: None)')\\n\\n self.parser.add_argument('-p', '--password',\\n default=None,\\n help='the password for mongoDB (Default: None)')\\n\\n self.parser.add_argument('-d', '--database',\\n default='grits',\\n help='the database for mongoDB (Default: grits)')\\n\\n self.parser.add_argument('-m', '--mongohost',\\n default='localhost',\\n help='the hostname for mongoDB (Default: localhost)')\\n\\n self.parser.add_argument('-f', '--force', \\n action='store_true',\\n help='do not require confirmation to create indexes (Default: False)')\",\n \"def parse(args, query):\\n\\n global query_type\\n\\n # Deal first with requests for definition or pronunciation\\n # 1. Make the code easier to read\\n first_word = args[0]\\n second_word = args[1] if len(args) > 1 else \\\"\\\"\\n third_word = args[2] if len(args) > 2 else \\\"\\\"\\n fourth_word = args[3] if len(args) > 3 else \\\"\\\"\\n # we use the teranary operator (this if ____ else that) to avoid an IndexError\\n # IndexError would be raised if we tried to access the second element (args[1])\\n # in a list which contained only one item (eg args == [\\\"lonely\\\"])\\n # the teranary operator (in most languages it looks like \\\"____ ? this : that\\\")\\n # returns \\\"this\\\" when the if is true and \\\"that\\\" when the if is false\\n # meaning, if len(args) is NOT greater than 1, second_word == \\\"\\\"\\n\\n # 2. Check for keywords in the list of arguments\\n # Example: nostrum defined\\n # Example: pronunciation of otolaryngology\\n if first_word == \\\"define\\\":\\n # e.g. if the first word is \\\"define\\\" we'll add the second word to the query\\n query = {\\\"sp\\\": second_word, \\\"md\\\": \\\"d\\\", \\\"max\\\": \\\"1\\\", \\\"qe\\\": \\\"sp\\\", \\\"ipa\\\": \\\"1\\\"}\\n # the query is a dictionary of GET parameters for the http request, eg\\n # https://api.datamuse.com/words?max=1&sp=SECOND_WORD_HERE&qe=sp&md=d&ipa=1\\n elif second_word == \\\"defined\\\" or second_word == \\\"definition\\\":\\n query = {\\\"sp\\\": first_word, \\\"md\\\": \\\"d\\\", \\\"max\\\": \\\"1\\\", \\\"qe\\\": \\\"sp\\\", \\\"ipa\\\": \\\"1\\\"}\\n # this one uses string interpolation (the f\\\"\\\" stuff)\\n elif f\\\"{second_word} {third_word}\\\" == \\\"means what\\\":\\n query = {\\\"sp\\\": first_word, \\\"md\\\": \\\"d\\\", \\\"max\\\": \\\"1\\\", \\\"qe\\\": \\\"sp\\\", \\\"ipa\\\": \\\"1\\\"}\\n elif f\\\"{second_word} {third_word} {fourth_word}\\\" == \\\"is said how\\\":\\n query = {\\\"sp\\\": first_word, \\\"md\\\": \\\"r\\\", \\\"max\\\": \\\"1\\\", \\\"qe\\\": \\\"sp\\\", \\\"ipa\\\": \\\"1\\\"}\\n # this one uses regular expressions -- i.e. if the second_word is \\\"of\\\" or \\\"for\\\"\\n elif first_word == \\\"definition\\\" and re.match(r'(of)|(for)',second_word):\\n query = {\\\"sp\\\": third_word, \\\"md\\\": \\\"d\\\", \\\"max\\\": \\\"1\\\", \\\"qe\\\": \\\"sp\\\", \\\"ipa\\\": \\\"1\\\"}\\n # the is_pronounced function returns true if first_word is a (mis)spelling of pronounced\\n elif re.match(r'(of)|(for)',second_word) and is_pronounced(first_word):\\n query = {\\\"sp\\\": third_word, \\\"md\\\": \\\"r\\\", \\\"max\\\": \\\"1\\\", \\\"qe\\\": \\\"sp\\\", \\\"ipa\\\": \\\"1\\\"}\\n # the ordering in the above list is not entirely random\\n # since an if-elif-else statement won't keep evaluating after it finds a match\\n # it makes sense to put the most computationally complex clauses at the end\\n # >>> import timeit\\n # >>> timeit.timeit('from word_helpers import is_pronounced; is_pronounced(\\\"pronounced\\\")', number=10000)\\n # 0.022870146989589557\\n # >>> timeit.timeit('args = [\\\"defined\\\"]; args[0] == \\\"defined\\\"', number=10000)\\n # 0.002359684993280098\\n # it takes 2 milliseconds to compare a string in a list 10,000 times\\n # -- versus 2 centiseconds to run is_pronounced 10,000 times\\n # (on my Intel Core i5 2.67GHz CPU -- obviously speed depends on the processor)\\n # it's also worth noting that readability counts more than speed optimization (most of the time!)\\n\\n # Quick way to check if any of the above if statements matched\\n if \\\"sp\\\" in query:\\n # if so, we are done in this function\\n if query[\\\"md\\\"] == \\\"r\\\": query_type = \\\"PRO\\\"\\n if query[\\\"md\\\"] == \\\"d\\\": query_type = \\\"DEF\\\"\\n return query\\n\\n # these will be useful later\\n STOP_WORDS = (\\\"and\\\", \\\"meaning\\\", \\\"means\\\", \\\"max\\\", \\\"about\\\", \\\"which\\\", \\\"that\\\")\\n\\n # Parse more complicated requests for synonyms, etc\\n # 0 is false in python, so this loop will run until we've removed all the args\\n while len(args):\\n # we must reset these vars each time the loop starts\\n # in case we've deleted items from the args list\\n first_word = args[0]\\n second_word = args[1] if len(args) > 1 else \\\"\\\"\\n third_word = args[2] if len(args) > 2 else \\\"\\\"\\n # we use the teranary operator (this if ____ else that) to avoid an IndexError\\n # IndexError would be raised if we tried to access the second element (args[1])\\n # in a list which contained only one item (eg args == [\\\"lonely\\\"])\\n # the teranary operator (in most languages it looks like \\\"____ ? this : that\\\")\\n # returns \\\"this\\\" when the if is true and \\\"that\\\" when the if is false\\n # meaning, if len(args) is NOT greater than 1, second_word == \\\"\\\"\\n\\n # Disambiguate homonym requests from spelling correction requests\\n # Example: sounding like tung\\n # Example: sounds like doe but spelled differently\\n if re.match(r'sound((s)|(ing)) like',f\\\"{first_word} {second_word}\\\"):\\n\\n # again, use len(args) to avoid an IndexError\\n if len(args) >= 6 and \\\\\\n re.match(r'((but)|(except)) spelled different(ly)?',f\\\"{args[3]} {args[4]} {args[5]}\\\"):\\n # but instead of teranary operator,\\n # use \\\"short circuit logic\\\" -- when python sees \\\"if __A__ and __B__ \\\",\\n # it knows that if A is false, the whole thing will be false\\n # (you can't have \\\"ice cream and potatoes\\\" for dinner if you don't have ice cream)\\n # and it won't waste time evaluating B, so re.match won't run and args[4]\\n # won't be accessed and no IndexError will be raised, yay!\\n # regex explained: ? means the prior thing matched zero or one times\\n # different(ly)? matches \\\"different\\\" and \\\"differently\\\"\\n query[\\\"rel_hom\\\"] = third_word\\n # now, delete 6 items from args, starting at item 0\\n del args[0:6]\\n else:\\n query[\\\"sl\\\"] = third_word\\n del args[0:3]\\n\\n # Example: spelled like 'cens?r'\\n elif re.match(r'spell((ed)|(ing)) like',f\\\"{first_word} {second_word}\\\"):\\n # two stars (**) means \\\"unpack\\\" a dictionary\\n # just like unpacking a suitcase, we've dumped the old contents of query\\n # into a new dictionary (which we are saving with the same variable name!)\\n query = {**query,\\\"sp\\\": third_word}\\n # query[\\\"sp\\\"] = third_word also works fine\\n # just showing off how to combine two dictionaries :)\\n del args[0:3]\\n\\n # Example: rhymes with culminate\\n elif len(args) > 2 and second_word == \\\"with\\\" and is_rhymes(first_word):\\n query[\\\"rel_rhy\\\"] = third_word\\n del args[0:3]\\n\\n # Example: almost rhymes with culminate\\n elif len(args) > 3 and \\\\\\n f\\\"{first_word} {third_word}\\\" == \\\"almost with\\\" and \\\\\\n is_rhymes(second_word):\\n query[\\\"rel_nry\\\"] = args[3] # fourth_word\\n del args[0:4]\\n\\n # Example: comes after sea\\n elif f\\\"{first_word} {second_word}\\\" == \\\"comes after\\\":\\n query[\\\"lc\\\"] = third_word\\n del args[0:3]\\n elif first_word == \\\"follows\\\":\\n query[\\\"lc\\\"] = second_word\\n del args[0:2]\\n elif f\\\"{first_word} {second_word}\\\" == \\\"comes before\\\":\\n query[\\\"rc\\\"] = third_word\\n del args[0:3]\\n elif first_word == \\\"preceeds\\\":\\n query[\\\"rc\\\"] = second_word\\n del args[0:2]\\n\\n # Example: describes paint\\n elif first_word == \\\"describes\\\":\\n query[\\\"rel_jjb\\\"] = second_word\\n del args[0:2]\\n\\n # Example: associated with feet\\n elif f\\\"{first_word} {second_word}\\\" == \\\"associated with\\\" or \\\\\\n f\\\"{first_word} {second_word}\\\" == \\\"triggered by\\\":\\n query[\\\"rel_trg\\\"] = third_word\\n del args[0:3]\\n\\n # Example: meaning feeling tired\\n elif first_word in [\\\"means\\\",\\\"meaning\\\",\\\"like\\\"]:\\n # get rid of first_word\\n del args[0]\\n # now short circuit logic again, plus using the tuple from ealier\\n # b/c if we have \\\"meaning deer and sounds like roe\\\" we don't want\\n # query[\\\"ml\\\"] == \\\"deer and sounds like roe\\\" -- it should be just \\\"deer\\\"\\n while len(args) and args[0] not in STOP_WORDS:\\n # teranary operator prevents KeyError if \\\"ml\\\" not already in query dictionary\\n query[\\\"ml\\\"] = f\\\"{query['ml']} {args[0]}\\\" if \\\"ml\\\" in query else args[0]\\n del args[0]\\n # an example with the previous code to make things clearer\\n # say args == [\\\"means\\\", \\\"egg\\\", \\\"beater\\\", \\\"and\\\", \\\"max\\\", \\\"35\\\"]\\n # first_word IS in [\\\"means\\\",\\\"meaning\\\",\\\"like\\\"]\\n # del first_word, args is now [\\\"egg\\\", \\\"beater\\\", \\\"and\\\", \\\"max\\\", \\\"35\\\"]\\n # len(args) == 5, args[0] is NOT in STOP_WORDS\\n # \\\"ml\\\" is NOT in query, so teranary returns args[0] (\\\"egg\\\")\\n # args[0] is copied to query[\\\"ml\\\"] (query is now {ml: \\\"egg\\\"})\\n # del args[0], args is now [\\\"beater\\\", \\\"and\\\", \\\"max\\\", \\\"35\\\"]\\n # return to top of while loop, len(args) == 4, args[0] is NOT in STOP_WORDS\\n # \\\"ml\\\" IS in query, so teranary returns f\\\"{query['ml']} {args[0]}\\\" (\\\"egg beater\\\") \\n # f\\\"{query['ml']} {args[0]}\\\" is copied to query[\\\"ml\\\"]\\n # (query is now {ml: \\\"egg beater\\\"})\\n # del args[0], args is now [\\\"and\\\", \\\"max\\\", \\\"35\\\"]\\n # return to top of while loop, len(args) == 3,\\n # args[0] IS in STOP_WORDS (args[0] == \\\"and\\\")\\n # DO NOT enter the while loop, continue past this code block\\n\\n # Discover the topic of our query\\n elif first_word == \\\"about\\\":\\n del args[0]\\n count = 0\\n # Datamuse allows a max of five topic words\\n while len(args) and args[0] not in STOP_WORDS and count <= 5:\\n query[\\\"topics\\\"] = f\\\"{query['topics']} {args[0]}\\\" if \\\"topics\\\" in query else args[0]\\n del args[0]\\n # count += 1 is the same as count = count + 1\\n count += 1\\n\\n # How many results to return (max 1000)\\n elif first_word in [\\\"max\\\", \\\"maximum\\\", \\\"only\\\"]:\\n user_max = convert_num(second_word)\\n if user_max and int(user_max) <= 1000:\\n query[\\\"max\\\"] = user_max\\n del args[0:2]\\n\\n # Remove filler words if they weren't parsed out above\\n elif first_word in [\\\"that\\\",\\\"which\\\",\\\"and\\\",\\\"like\\\",\\\"is\\\"]:\\n del args[0]\\n\\n # Add anything not otherwise parsable to the ml parameter\\n else:\\n query[\\\"ml\\\"] = f\\\"{query['ml']} {first_word}\\\" if \\\"ml\\\" in query else first_word\\n del args[0]\\n\\n # this is the bottom of that massive while loop\\n # if args is not empty by now, we'll start over from the top ^\\n\\n return query\\n # and this is the end of the \\\"def parse(args, query)\\\" function\\n # whew!\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(prog='AdapterRunner', description='Adapter Runner Application')\\n parser.add_argument('-a', '--application', action='store', dest='app_name', help='Application Name',\\n metavar='<application_name>')\\n parser.add_argument('-fi', '--fetch_interval', action='store', dest='fetch_stats_interval', help='Fetch Stats Interval',\\n metavar='<fetch_interval in seconds>')\\n return parser.parse_args()\",\n \"def parse_arguments():\\n \\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"postcode\\\", type=str, help=\\\"Postcode of current location\\\")\\n parser.add_argument(\\\"-d\\\", \\\"--debug\\\", \\n help=\\\"Turns on debug mode\\\", \\n action='store_true')\\n parser.add_argument(\\\"-fp\\\",\\\"--postcode-file\\\", \\n default=\\\"postcodes_swift_sample.csv\\\",\\n help=\\\"Location of Postcode CSV file (default postcodes_swift_sample.csv)\\\",\\n type=str)\\n parser.add_argument(\\\"-fb\\\",\\\"--pub-file\\\", \\n default=\\\"pubnames_swift_sample.csv\\\",\\n help=\\\"Location of Pub Postcode CSV file (default pubnames_swift_sample.csv)\\\",\\n type=str)\\n parser.add_argument(\\\"-l\\\",\\\"--limit\\\", \\n default=10, \\n help=\\\"Limit Number of Results (default 10)\\\",\\n type=int)\\n parser.add_argument(\\\"-m\\\",\\\"--max-distance\\\", \\n default=50, \\n help=\\\"Only return results less than this distance (default 50)\\\",\\n type=int)\\n return parser\",\n \"def main():\\n parser = argparse.ArgumentParser(description=\\\"\\\"\\\"Tester for YT Data API and different inputs\\\"\\\"\\\")\\n parser.add_argument('-a', '--analytics', help='Performs a basic analytics lookup for the user\\\\'s channel entered')\\n parser.add_argument('-c', '--comments', help='Performs a lookup of comments for the video id entered')\\n args = parser.parse_args()\\n\\n if args.analytics:\\n analytics = args.analytics\\n analyt(analytics)\\n\\n if args.comments:\\n comments = args.comments\\n get_comments(comments)\",\n \"def parse_args():\\n default_file_name = 'test.db'\\n default_table_name = 'test'\\n default_location = 'hasan_bedroom'\\n default_node_id = 'SecuritySystem_1'\\n\\n parser = argparse.ArgumentParser(\\n description='Run the SecuritySystemDB test program')\\n\\n parser.add_argument('-v',\\n '--verbose',\\n default=False,\\n action='store_true',\\n help='Print all debug logs')\\n\\n parser.add_argument('-ss',\\n '--security_system',\\n default=False,\\n action='store_true',\\n help='Run SecuritySystemDB test')\\n\\n parser.add_argument('-f',\\n '--file_name',\\n type=str,\\n default=default_file_name,\\n metavar='<file_name.db>',\\n help='Specify file name of SQL db (Relative to pwd)')\\n\\n parser.add_argument('-t',\\n '--table_name',\\n type=str,\\n default=default_table_name,\\n metavar='<test_table_name>',\\n help='Specify table name of SQL db')\\n\\n parser.add_argument('-l',\\n '--location',\\n type=str,\\n default=default_location,\\n metavar='<owner_room>',\\n help='Specify owner and room')\\n\\n parser.add_argument('-id',\\n '--node_id',\\n type=str,\\n default=default_node_id,\\n metavar='<node_id>',\\n help='Specify node ID')\\n\\n args = parser.parse_args()\\n return args\",\n \"def parse_command_line():\\n parser = argparse.ArgumentParser(description='Parses ID\\\\'s from the DDI compendium search results, and then downloads the html and puts them into a sqlite database.')\\n parser.add_argument('-f', '--file', dest='file',\\n action='store',\\n help='Filenname to be read')\\n arg_manager = parser.parse_args()\\n return arg_manager\",\n \"def command_line_arguments():\\n\\n try:\\n parser = argparse.ArgumentParser(description='Log Handler/Cleaner/Copier for Idemia DocAuth')\\n\\n # Add required arguments.\\n parser.add_argument('action', choices=['clean', 'download'], type=str, help='clean or download')\\n\\n # Parse the arguments\\n args = parser.parse_args()\\n\\n return args\\n\\n except Exception as err:\\n print(err)\\n return\",\n \"def __init__(self):\\n\\n # Set-up the parser object.\\n self.parser = argparse.ArgumentParser(description='Boolean query documents using inverted index', formatter_class=RawTextHelpFormatter)\\n\\n # Option to load the desired documents from a CSV file.\\n self.parser.add_argument('documents', type=str, help='''Constructs an inverted index from a CSV file. Required format: One document per line. First line is discarded.\\n<id>\\\\\\\\t<url>\\\\\\\\t<pub_date>\\\\\\\\t<title>\\\\\\\\t<document_content>\\\\\\\\n\\n ''')\\n\\n self.parser.add_argument('-q',metavar='query', type=str, help='Boolean query', action='append')\",\n \"def main(args):\\n options = parse_cmd_parameters_(args)\\n execute_(options)\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(\\n formatter_class=argparse.RawDescriptionHelpFormatter,\\n description='''ABX task specification\\n\\n 'database' is a text file with the '.item' extension containing an\\n index of the database and a set of labels or attributes. See input\\n format specifications at\\n http://abxpy.readthedocs.io/en/latest/FilesFormat.html#dataset\\n\\n The --on, --across, --by, --filters and --regressors arguments must\\n be defined as columns in the database (e.g. speaker or phonemes, if\\n your database contains columns defining these attributes)\\n\\nExample call:\\n\\n task.py ./my_data.item -o column1 -a column2 column3 -b column4 column5 \\\\\\\\\\n -f \\\"[attr == 0 for attr in column3_X]\\\"\\n\\n Because optional arguments can have various numbers of inputs, the\\n positional arguments ('database' and 'output') must come before the\\n mandatory ones, one being preceded by '--'. Thus, those two calls\\n are equivalent:\\n\\n task.py ./my_data.item -o column1 -a column2 column3\\n task.py -o column1 -a column2 column3 -- ./my_data.item''')\\n\\n parser.add_argument(\\n '-v', '--verbose', action='store_true',\\n help='output messages to the standard output')\\n\\n parser.add_argument(\\n '--stats-only', action='store_true',\\n help='add this flag if you only want some statistics '\\n 'about the specified task')\\n\\n parser.add_argument(\\n '--tempdir', default=None,\\n help='directory where temporary files will be stored')\\n\\n parser.add_argument(\\n '--seed', default=None, type=int,\\n help='seed used to initialize the pseudo-random number generator')\\n\\n # I/O files\\n g1 = parser.add_argument_group('I/O files')\\n g1.add_argument(\\n 'database', help='database item file used to form ABX triplets')\\n\\n g1.add_argument(\\n 'output', nargs='?', default=None,\\n help='file to write the generated ABX task, '\\n 'default to the database basename with the \\\\'.abx\\\\' extension')\\n\\n # Task specification\\n g2 = parser.add_argument_group('Task specification')\\n\\n g2.add_argument(\\n '-o', '--on', required=True, help='ON attribute')\\n\\n g2.add_argument(\\n '-a', '--across', nargs='+', default=[],\\n help='ACROSS attributes')\\n\\n g2.add_argument(\\n '-b', '--by', nargs='+', default=[],\\n help='BY attributes')\\n\\n g2.add_argument(\\n '-f', '--filters', nargs='+', default=[],\\n help='filters specification')\\n\\n g2.add_argument(\\n '-r', '--regressors', nargs='+', default=[],\\n help='regressors specification')\\n\\n g2.add_argument(\\n '-t', '--threshold', default=None, type=int,\\n help='threshold on the maximal size of a block of'\\n ' triplets sharing the same regressors')\\n\\n return parser.parse_args()\",\n \"def main(args):\",\n \"def main(args):\",\n \"def parse_command_line():\\r\\n\\r\\n parser = argparse.ArgumentParser(description='User args')\\r\\n parser.add_argument(\\\"--action\\\", choices=['train', 'predict', 'demo', 'test'], required=True, help=\\\"Choose action.\\\")\\r\\n parser.add_argument(\\\"--model\\\", choices=['vgg', 'unet', 'fpn'], required=True, help=\\\"Choose model.\\\")\\r\\n parser.add_argument(\\\"--dataset\\\", choices=['full', 'small'], required=True, help=\\\"Choose dataset.\\\")\\r\\n\\r\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(\\n description='Manage a database of Airbnb listings.',\\n usage='%(prog)s [options]')\\n parser.add_argument(\\\"-v\\\", \\\"--verbose\\\",\\n action=\\\"store_true\\\", default=False,\\n help=\\\"\\\"\\\"write verbose (debug) output to the log file\\\"\\\"\\\")\\n parser.add_argument(\\\"-c\\\", \\\"--config_file\\\",\\n metavar=\\\"config_file\\\", action=\\\"store\\\", default=None,\\n help=\\\"\\\"\\\"explicitly set configuration file, instead of\\n using the default <username>.config\\\"\\\"\\\")\\n # Only one argument!\\n group = parser.add_mutually_exclusive_group()\\n group.add_argument('-asa', '--addsearcharea',\\n metavar='search_area', action='store', default=False,\\n help=\\\"\\\"\\\"get and save the name and neighborhoods\\n for search area (city)\\\"\\\"\\\")\\n group.add_argument('-asv', '--addsurvey',\\n metavar='search_area', type=str,\\n help=\\\"\\\"\\\"add a survey entry to the database,\\n for search_area\\\"\\\"\\\")\\n group.add_argument('-dbp', '--dbping',\\n action='store_true', default=False,\\n help='Test the database connection')\\n group.add_argument('-dh', '--displayhost',\\n metavar='host_id', type=int,\\n help='display web page for host_id in browser')\\n group.add_argument('-dr', '--displayroom',\\n metavar='room_id', type=int,\\n help='display web page for room_id in browser')\\n group.add_argument('-f', '--fill', nargs='?',\\n metavar='survey_id', type=int, const=0,\\n help='fill details for rooms collected with -s')\\n group.add_argument('-lsa', '--listsearcharea',\\n metavar='search_area', type=str,\\n help=\\\"\\\"\\\"list information about this search area\\n from the database\\\"\\\"\\\")\\n group.add_argument('-lr', '--listroom',\\n metavar='room_id', type=int,\\n help='list information about room_id from the database')\\n group.add_argument('-ls', '--listsurveys',\\n action='store_true', default=False,\\n help='list the surveys in the database')\\n group.add_argument('-psa', '--printsearcharea',\\n metavar='search_area', action='store', default=False,\\n help=\\\"\\\"\\\"print the name and neighborhoods for\\n search area (city) from the Airbnb web site\\\"\\\"\\\")\\n group.add_argument('-pr', '--printroom',\\n metavar='room_id', type=int,\\n help=\\\"\\\"\\\"print room_id information\\n from the Airbnb web site\\\"\\\"\\\")\\n group.add_argument('-ps', '--printsearch',\\n metavar='survey_id', type=int,\\n help=\\\"\\\"\\\"print first page of search information\\n for survey from the Airbnb web site\\\"\\\"\\\")\\n group.add_argument('-psn', '--printsearch_by_neighborhood',\\n metavar='survey_id', type=int,\\n help=\\\"\\\"\\\"print first page of search information\\n for survey from the Airbnb web site,\\n by neighborhood\\\"\\\"\\\")\\n group.add_argument('-psz', '--printsearch_by_zipcode',\\n metavar='survey_id', type=int,\\n help=\\\"\\\"\\\"print first page of search information\\n for survey from the Airbnb web site,\\n by zipcode\\\"\\\"\\\")\\n group.add_argument('-psb', '--printsearch_by_bounding_box',\\n metavar='survey_id', type=int,\\n help=\\\"\\\"\\\"print first page of search information\\n for survey from the Airbnb web site,\\n by bounding_box\\\"\\\"\\\")\\n group.add_argument('-s', '--search',\\n metavar='survey_id', type=int,\\n help='search for rooms using survey survey_id')\\n group.add_argument('-sn', '--search_by_neighborhood',\\n metavar='survey_id', type=int,\\n help='search for rooms using survey survey_id')\\n group.add_argument('-sb', '--search_by_bounding_box',\\n metavar='survey_id', type=int,\\n help=\\\"\\\"\\\"search for rooms using survey survey_id,\\n by bounding box\\n \\\"\\\"\\\")\\n group.add_argument('-sz', '--search_by_zipcode',\\n metavar='survey_id', type=int,\\n help=\\\"\\\"\\\"search for rooms using survey_id,\\n by zipcode\\\"\\\"\\\")\\n group.add_argument('-V', '--version',\\n action='version',\\n version='%(prog)s, version ' +\\n str(SCRIPT_VERSION_NUMBER))\\n group.add_argument('-?', action='help')\\n\\n args = parser.parse_args()\\n return (parser, args)\",\n \"def set_args():\\n # Initialise argparse object\\n parser = argparse.ArgumentParser(description='Set some arguments for our script')\\n # Add some arguments, elements are: short form name, long form name, type of input expected\\n # default value if you don't set an argument, help string (shown if you run with --help)\\n # nargs is so that we can define multiple values for a single argument\\n\\n parser.add_argument('-q', '--query-terms', type=str, default='Venezuela Covid',\\n help='list of strings to search for', nargs='*')\\n\\n parser.add_argument('-p', '--page-limit', type=int,\\n help='number to limit search pages to')\\n\\n # set the argument parser and return\\n args = parser.parse_args()\\n return args\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-e\\\", \\\"--events\\\", type=str,\\n help=\\\"path to events CSV-file\\\")\\n parser.add_argument(\\\"-d\\\", \\\"--data\\\", type=str,\\n help=\\\"path to data CSV-file\\\")\\n parser.add_argument(\\\"-l\\\", \\\"--limit\\\", nargs='?', type=int, default=None,\\n help=\\\"max records to be processed\\\")\\n parser.add_argument(\\\"-t\\\", \\\"--timezone\\\", nargs='?', type=int, default=5,\\n help=\\\"date and time shift\\\")\\n parser.add_argument(\\\"-o\\\", \\\"--optimized\\\", action='store_true',\\n help=\\\"if specified, then data CSV will be processed\\\"\\n \\\" by small chunks to escape memory issues\\\")\\n parser.add_argument(\\\"-v\\\", \\\"--verbose\\\", action='store_true')\\n parser.add_argument(\\\"--output-folder\\\", nargs='?', type=str,\\n default=\\\"linked\\\")\\n return vars(parser.parse_args())\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(\\n description=\\\"Reads datapacket pcds, interpolates quaternions and generates scans from dataset in config file\\\")\\n parser.add_argument(\\\"--visualization\\\", \\\"-v\\\", action=\\\"store_true\\\", help=\\\"if generated clouds should be visualized\\\")\\n parser.add_argument(\\\"--directory\\\", \\\"-d\\\",\\n help=\\\"if only specified directory should be interpolated, e.g. 'fragments/fragment0'\\\")\\n args = parser.parse_args()\\n return args.visualization, args.directory\",\n \"def main(argv, out=print):\\n opts = parser.parse_args(argv[1:])\\n out(generate_sql(vars(opts)))\",\n \"def parse_command_line(self, argv):\\n from optparse import OptionParser\\n usage = \\\"usage: %prog [options]\\\"\\n parser = OptionParser(usage)\\n\\n (options, args) = parser.parse_args(argv)\",\n \"def __parse_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-f', '--force', action=\\\"store_true\\\", default=False,\\n help='overwrite existing database files during import')\\n parser.add_argument('-e', '--extension', action=\\\"store\\\", default='txt',\\n help='specify file extension. default is \\\"txt\\\"')\\n parser.add_argument('-d', '--delimiter', action=\\\"store\\\", default='\\\\t',\\n help='specify column delimiter. default is tab (\\\\\\\\t)')\\n parser.add_argument('-m', '--mark', action=\\\"store\\\", default='.',\\n help='specify decimal mark for numeric data. default is'\\n ' dot (.)')\\n parser.add_argument('-o', '--outformat', action=\\\"store\\\", default='npz',\\n help='specify output database format. default is \\\"npz\\\"'\\n ' for numpy database. use \\\"mat\\\" for matlab '\\n ' database format.')\\n parser.add_argument('-r', '--recursive', action=\\\"store_true\\\", default=False,\\n help='recursively walk through all sub-directories of'\\n ' current working directory')\\n parser.add_argument('-p', '--pcs', action=\\\"store_true\\\", default=True,\\n help='indicate if files are pcs files.')\\n parser.add_argument('-c', '--colheadlines', action=\\\"store\\\", default='1',\\n help='number of lines spanned by the column headers')\\n args = parser.parse_args()\\n return args\",\n \"def add_arguments(self):\\n super().add_arguments()\\n self.parser.add_argument(\\n \\\"sql_command\\\",\\n help=\\\"The SQL commmand to execute. Use <odb> to reference the filename.\\\",\\n type=str\\n )\",\n \"def parse_command_line():\\n parser = argparse.ArgumentParser(\\\"Falcon Quick Scan\\\")\\n parser.add_argument(\\\"-f\\\", \\\"--config\\\",\\n dest=\\\"config_file\\\",\\n help=\\\"Path to the configuration file\\\",\\n required=False\\n )\\n parser.add_argument(\\\"-l\\\", \\\"--log-level\\\",\\n dest=\\\"log_level\\\",\\n help=\\\"Default log level (DEBUG, WARN, INFO, ERROR)\\\",\\n required=False\\n )\\n parser.add_argument(\\\"-d\\\", \\\"--check-delay\\\",\\n dest=\\\"check_delay\\\",\\n help=\\\"Delay between checks for scan results\\\",\\n required=False\\n )\\n parser.add_argument(\\\"-p\\\", \\\"--pattern\\\",\\n dest=\\\"pattern\\\",\\n help=\\\"Target file patterns to scan (defaults to *.*)\\\",\\n required=False\\n )\\n parser.add_argument(\\\"-r\\\", \\\"--region\\\",\\n dest=\\\"region\\\",\\n help=\\\"Region the target bucket resides in\\\",\\n required=False\\n )\\n parser.add_argument(\\\"-t\\\", \\\"--target\\\",\\n dest=\\\"target\\\",\\n help=\\\"Target folder or bucket to scan. Bucket must have 's3://' prefix.\\\",\\n required=True\\n )\\n\\n return parser.parse_args()\",\n \"def handle_cmdline():\\n\\n cmdline = ArgumentParser(init_args=['address', 'arch', 'file'],\\n address_required=True, address_default=None,\\n file_required=True,\\n file_help='Flash or memory image to inspect',\\n formatter_class=RawDescriptionHelpFormatter,\\n usage=_USAGE, description=_DESCRIPTION, epilog=_EPILOG)\\n\\n cmdline.add_argument('--longhelp',\\n choices=['Y', 'N'],\\n default=None,\\n help=_LONGHELP_TEXT)\\n\\n cmdline.add_argument('--autocomplete',\\n choices=['Y', 'N'],\\n default=None,\\n help=_AUTOCOMPLETE_TEXT)\\n\\n cmdline.add_argument('--threshold',\\n type=int,\\n default=5,\\n help='Minimum table size to report. Default: 5')\\n\\n cmdline.add_argument('--subcmds',\\n action='store_true',\\n default=False,\\n help='Include sub-command tables in displayed results')\\n\\n cmdline.add_argument('--details',\\n action='store_true',\\n default=False,\\n help='Display more detailed output')\\n\\n args = cmdline.parse_args()\\n\\n if args.longhelp is not None:\\n args.longhelp = args.longhelp == 'Y'\\n\\n if args.autocomplete is not None:\\n args.autocomplete = args.autocomplete == 'Y'\\n\\n return args\",\n \"def parse_arguments():\\n parser = ArgumentParser()\\n parser.add_argument(\\\"-p\\\", \\\"--path\\\", required=True, nargs=1,\\n dest=\\\"file_path\\\", type=str, action=\\\"store\\\",\\n help=\\\"path to the root directory\\\")\\n parser.add_argument(\\\"-q\\\", \\\"--quick\\\", action=\\\"store_true\\\",\\n default=False, dest=\\\"quick\\\",\\n help=\\\"Speed up the search or not\\\")\\n return parser.parse_args()\",\n \"def parse_arguments(argv):\\n parser = argparse.ArgumentParser(\\n description='Runs Preprocessing on structured data.')\\n parser.add_argument('--output-dir',\\n type=str,\\n required=True,\\n help='Google Cloud Storage which to place outputs.')\\n\\n parser.add_argument('--schema-file',\\n type=str,\\n required=False,\\n help=('BigQuery json schema file'))\\n parser.add_argument('--input-file-pattern',\\n type=str,\\n required=False,\\n help='Input CSV file names. May contain a file pattern')\\n\\n # If using bigquery table\\n # TODO(brandondutra): maybe also support an sql input, so the table can be\\n # ad-hoc.\\n parser.add_argument('--bigquery-table',\\n type=str,\\n required=False,\\n help=('project:dataset.table_name'))\\n\\n args = parser.parse_args(args=argv[1:])\\n\\n if not args.output_dir.startswith('gs://'):\\n raise ValueError('--output-dir must point to a location on GCS')\\n\\n if args.bigquery_table:\\n if args.schema_file or args.input_file_pattern:\\n raise ValueError('If using --bigquery-table, then --schema-file and '\\n '--input-file-pattern, '\\n 'are not needed.')\\n else:\\n if not args.schema_file or not args.input_file_pattern:\\n raise ValueError('If not using --bigquery-table, then --schema-file and '\\n '--input-file-pattern '\\n 'are required.')\\n\\n if not args.input_file_pattern.startswith('gs://'):\\n raise ValueError('--input-file-pattern must point to files on GCS')\\n\\n return args\",\n \"def parse_args(self, argv):\\n\\t\\tself.argv={'user': argv[1]}\",\n \"def _parse_command_line_arguments():\\n parser = ArgumentParser(\\n description=(\\n 'Command-line tool to generate a list of unique from a TS file from FermiFAST'\\n ),\\n )\\n parser.add_argument(\\n 'ts-file',\\n type=str,\\n help=(\\n 'A file containing the TS sky map'\\n ),\\n )\\n parser.add_argument('--skiprows',\\n type=int,\\n help='number of rows to skip at the top (default 0)',\\n required=False)\\n parser.set_defaults(skiprows=0)\\n arguments = vars(parser.parse_args())\\n return arguments\",\n \"def ReadArguments():\\n\\n args = ParseArguments()\\n\\n logging.info('Command line arguments...')\\n for arg in vars(args):\\n logging.info(str(arg) + ': ' + str(getattr(args, arg)))\\n logging.info('')\\n\\n IsTest(args)\\n ProcessCacheSize(args)\\n ProcessLineSize(args)\\n ProcessMulti(args)\\n ProcessMemPattern(args)\\n ProcessMemFile(args)\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description='Create a database server to save and return key pair values')\\n parser.add_argument('--ip', type=str, required=False, default='localhost', help='IP for server to listen on')\\n parser.add_argument('--port', type=int, required=False, default=4000, help='Port for server to listen on')\\n\\n return parser.parse_args()\",\n \"def parse_command_line_arguments():\\n\\n description, epilog = __doc__.split(\\\"\\\\n\\\\n\\\", 1)\\n\\n parser = argparse.ArgumentParser(\\n formatter_class=argparse.RawDescriptionHelpFormatter,\\n description=description,\\n epilog=epilog)\\n\\n parser.add_argument('-s', '--s', dest='s', action='store', type=float, required=True,\\n help='Minimum frequency')\\n parser.add_argument('-c', '--credentials', dest='credentials', action='store',\\n default=\\\"./.tpass\\\",\\n help='File with Twitter credentials (username and password, separated by a space)')\\n\\n args = parser.parse_args()\\n \\n return args\",\n \"def parseArgs(args):\\n parser = argparse.ArgumentParser(description = \\\"Scrapes baseball-reference.com for player statistics\\\")\\n\\n parser.add_argument(\\\"-d\\\", \\\"--domain\\\", help=\\\"domain to scrape for statistics. Default is baseball-reference.com\\\", nargs=1, default=[\\\"http://www.baseball-reference.com\\\"])\\n parser.add_argument(\\\"-f\\\", \\\"--filename\\\", help=\\\"database file to store data in\\\", required=True, nargs=1, type=argparse.FileType(\\\"r+\\\"))\\n parser.add_argument(\\\"-r\\\", \\\"--reset\\\", help=\\\"removes database before scraping all data from baseball-reference. Conflicts with -u. One of -r and -u must be specified\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"-u\\\", \\\"--update\\\", help=\\\"scrapes baseball-reference and adds all new information to the database. Conflicts with -r. One of -r and -u must be specified\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"--verbose\\\", help=\\\"enables verbose output\\\", action=\\\"store_true\\\")\\n parser.add_argument(\\\"--version\\\", help=\\\"prints out version and exits\\\", action=\\\"version\\\", version=\\\"%(prog)s ({version})\\\".format(version=__version__))\\n\\n parsedArgs = parser.parse_args()\\n\\n if parsedArgs.reset == parsedArgs.update:\\n parser.error(\\\"-r and -u are conflicting flags. Exactly one must be specified\\\")\\n parser.print_help()\\n\\n return parsedArgs\",\n \"def parseArgs( argv ):\\r\\n\\r\\n parser = OptionParser()\\r\\n parser.add_option(\\\"-o\\\", \\\"--order\\\", type=\\\"choice\\\", action=\\\"store\\\", choices=[\\\"p\\\",\\\"h\\\",\\\"g\\\",\\\"c\\\"], default=\\\"p\\\", dest=\\\"orderType\\\",\\r\\n help=\\\"specify a display sorted by (p)lugin, (c)ve id, (h)ost, or just (g)enerate a hostfile\\\")\\r\\n parser.add_option(\\\"-f\\\", \\\"--odf\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"odfOutputFilename\\\",\\r\\n help=\\\"output to this file in ODF format\\\", default=\\\"\\\")\\r\\n parser.add_option(\\\"-p\\\", \\\"--portlist\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"portList\\\",\\r\\n help=\\\"specify specific ports to show\\\")\\r\\n parser.add_option(\\\"-r\\\", \\\"--riskfactors\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"riskFactorsList\\\", default=\\\"critical,high,moderate,medium,low,none\\\",\\r\\n help=\\\"specify list of allowable risk factors (default is any of critical,high,moderate,medium,low,none\\\")\\r\\n parser.add_option(\\\"-t\\\", \\\"--hostlist\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"hostList\\\",\\r\\n help=\\\"specify specific hosts to show\\\")\\r\\n parser.add_option(\\\"-s\\\", \\\"--severities\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"severityList\\\", default=\\\"critical_hole,hole,warn,note,info,openport\\\",\\r\\n help=\\\"specify specific list of severity codes to show (default is any of critical_hole,hole,warn,note,info,openport\\\")\\r\\n parser.add_option(\\\"-q\\\", \\\"--query\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"contentQuery\\\",\\r\\n help=\\\"show all results whose synopses match this regular expression\\\")\\r\\n parser.add_option(\\\"-i\\\", \\\"--idlist\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"pluginIDList\\\",\\r\\n help=\\\"display only results that match these Nessus plugin IDs\\\")\\r\\n parser.add_option(\\\"-c\\\", \\\"--csv\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"csvOutputFilename\\\", default=\\\"\\\",\\r\\n help='output CSV-friendly text delimitted by default or overriden delimiter to a given filename (use \\\"0\\\" for standard output)')\\r\\n# parser.add_option(\\\"-c\\\", \\\"--csv\\\", action=\\\"store_true\\\", dest=\\\"CSV\\\", default=False,\\r\\n# help=\\\"output CSV-friendly text delimitted by |++| (overridable with the 'd' option)\\\")\\r\\n parser.add_option(\\\"-d\\\", \\\"--delimiter\\\", type=\\\"string\\\", action=\\\"store\\\", dest=\\\"delimiter\\\", default=\\\"|++|\\\", \\r\\n help=\\\"override CSV delimiter default of |++|\\\")\\r\\n\\r\\n (options, args) = parser.parse_args() \\r\\n \\r\\n if options.orderType: options.orderType = options.orderType.lower()\\r\\n\\r\\n return (options,args)\",\n \"def _add_arguments(self):\\r\\n self._parser.add_argument(\\r\\n '-s', '--server',\\r\\n required=True,\\r\\n help=\\\"enter server name\\\")\\r\\n self._parser.add_argument(\\r\\n '-db', '--database',\\r\\n required=True,\\r\\n help='enter database name')\\r\\n self._parser.add_argument(\\r\\n '-u', '--username',\\r\\n help='enter username')\\r\\n self._parser.add_argument(\\r\\n '-p', '--password',\\r\\n help='enter password')\\r\\n #self._parser.add_argument(\\r\\n # '-h', '--help',\\r\\n # help='show this help message and exit')\\r\",\n \"def parse_arguments(raw_args=sys.argv[1:]):\\n parser = optparse.OptionParser(\\n usage=\\\"usage: %prog [OPTIONS] DOMAIN_NAME DOMAIN_CONFIG_FILE\\\",\\n description=\\\"A tool for provisioning a Khan Academy CloudSearch \\\"\\n \\\"domain.\\\")\\n\\n parser.add_option(\\\"-v\\\", \\\"--verbose\\\", action=\\\"store_true\\\", default=False,\\n help=\\\"If specified, DEBUG messages will be printed and more \\\"\\n \\\"information will be printed with each log message.\\\")\\n\\n parser.add_option(\\\"--leave-temp-dir\\\", action=\\\"store_true\\\", default=False,\\n help=\\\"If specified, the created temporary directory will not be \\\"\\n \\\"deleted when the script exits.\\\")\\n\\n parser.add_option(\\\"-n\\\", \\\"--dry-run\\\", action=\\\"store_true\\\", default=False,\\n help=\\\"If specified, no commands will actually be executed.\\\")\\n\\n parser.add_option(\\\"--no-reindex\\\", action=\\\"store_true\\\", default=False,\\n help=\\\"If specified, will only update the config, without reindexing.\\\")\\n\\n options, args = parser.parse_args(raw_args)\\n\\n if len(args) != 2:\\n parser.error(\\\"You must specify the name of the domain and a file \\\"\\n \\\"containing the domain configuration.\\\")\\n\\n return (options, args[0], args[1])\",\n \"def arguments():\\n\\tparser = argparse.ArgumentParser(description=\\\"Integrate all columns of a data file. Time is in column 0.\\\")\\n\\tparser.add_argument(\\\"-v\\\", \\\"--verbose\\\", action=\\\"store_true\\\", dest=\\\"verbose\\\", default=False, help=\\\"Print debug info.\\\")\\n\\tparser.add_argument(\\\"-k\\\", \\\"--kwh\\\", action=\\\"store_true\\\", dest=\\\"kwh\\\", default=False, help=\\\"output in kWh (instead of Ws)\\\")\\n\\tparser.add_argument(\\\"-f\\\", \\\"--file\\\", action=\\\"store\\\", dest=\\\"filename\\\", help=\\\"Path to file to read. Defaults to STDIN.\\\")\\n\\tparser.add_argument(\\\"-s\\\", \\\"--separator\\\", dest=\\\"separator\\\", default=\\\",\\\", help=\\\"Specify the separation character. Defaults to comma (,).\\\")\\n\\n\\treturn parser.parse_args()\",\n \"def get_args_from_command_line():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"--input_csv_path\\\", type=str)\\n parser.add_argument(\\\"--text_column_order\\\", type=int)\\n args = parser.parse_args()\\n return args\",\n \"def _makeParser_search() :\\n parser = argparse.ArgumentParser(\\n description = SCRIPT_DESCRIPTION_SEARCH)\\n parser.add_argument(\\\"-c\\\", \\\"--count\\\", action = \\\"store_true\\\",\\n help = \\\"Just return the number of records, no fetch\\\")\\n # Required named arguments (http://stackoverflow.com/questions/24180527/argparse-required-arguments-listed-under-optional-arguments)\\n required = parser.add_argument_group(\\\"required named arguments\\\")\\n # --email\\n required.add_argument(\\\"-e\\\", \\\"--email\\\", type = str,\\n help = \\\"User's email (required by Entrez)\\\")\\n # --listId\\n required.add_argument(\\\"-l\\\", \\\"--listId\\\", type = str,\\n help = \\\"File containing one GenBank identifier per \\\"\\n \\\"line. Use - for reading from stdin. \\\"\\n \\\"Exactly one of --listId or \\\"\\n \\\"--query must be specified, but not both.\\\")\\n # --query\\n required.add_argument(\\\"-q\\\", \\\"--query\\\", type = str,\\n help = \\\"Query string for GenBank search. \\\"\\n \\\"Exactly one of --listId or \\\"\\n \\\"--query must be specified, but not both.\\\",\\n metavar = \\\"SEARCH_TERM\\\")\\n # Download options\\n download = parser.add_argument_group(\\\"download-related options\\\")\\n # --retmax\\n download.add_argument(\\\"-r\\\", \\\"--retmax\\\", type = int, default = 0,\\n help = \\\"Maximum number of entries to retrieve from \\\"\\n \\\"GenBank, comprised between 1 and 10000. Use 0 for \\\"\\n \\\"unlimited number of returned entries. (default: 0)\\\")\\n # --download\\n download.add_argument(\\\"-d\\\", \\\"--download\\\", action = \\\"store_true\\\",\\n help = \\\"Download the full GenBank records\\\")\\n # --forceDownload\\n download.add_argument(\\\"-f\\\", \\\"--forceDownload\\\", action = \\\"store_true\\\",\\n help = \\\"Download record even if file already exists \\\"\\n \\\"(implies --download)\\\")\\n # --fullWGS\\n download.add_argument(\\\"--fullWGS\\\", action = \\\"store_true\\\",\\n help = \\\"Also download full WGS sequence data when \\\"\\n \\\"WGS trace reference is present in a GenBank record \\\"\\n \\\"(only works if the original GenBank record is to be \\\"\\n \\\"downloaded too or if --forceDownload is used)\\\")\\n # --outputDir\\n download.add_argument(\\\"-o\\\", \\\"--outputDir\\\", type = str, default = \\\".\\\",\\n help = \\\"Destination folder for downloaded records \\\"\\n \\\"(default: current directory)\\\")\\n # --batchSize\\n download.add_argument(\\\"-b\\\", \\\"--batchSize\\\", type = int, default = 5,\\n help = \\\"Batch size for full record retrieval \\\"\\n \\\"(default: 5)\\\")\\n # --delay\\n download.add_argument(\\\"--delay\\\", type = int, default = 15,\\n help = \\\"Delay in seconds between successive batch \\\"\\n \\\"retrieval of the full records (default: 15)\\\")\\n return parser\",\n \"def get_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-i\\\", \\\"--input\\\",\\n help=\\\"text file, one compound per line\\\", required=True)\\n parser.add_argument(\\\"-j\\\", \\\"--jsononto\\\",\\n help=\\\"json ontology of families\\\", required=True)\\n parser.add_argument(\\\"-o\\\", \\\"--output\\\",\\n help=\\\"output file\\\", required=True)\\n parser.add_argument(\\\"-e\\\", \\\"--encoded\\\",\\n help=\\\"identifiers are encoded\\\", action=\\\"store_true\\\", default=False)\\n\\n args = parser.parse_args()\\n\\n run_analysis(args.input, args.jsononto, args.output, args.encoded)\",\n \"def _parse_command_line(self):\\n DESCRIPTION = (\\n \\\"Application for searching PyLith .cfg parameter files.\\\"\\n )\\n\\n parser = argparse.ArgumentParser(description=DESCRIPTION,\\n formatter_class=argparse.ArgumentDefaultsHelpFormatter)\\n parser.add_argument(\\\"--path\\\", action=\\\"store\\\",\\n dest=\\\"searchpath\\\", default=\\\".\\\", help=\\\"Search path for .cfg files.\\\")\\n parser.add_argument(\\\"--display\\\", action=\\\"store\\\",\\n dest=\\\"display\\\", default=\\\"all\\\", help=\\\"List of metadata to display in search results.\\\")\\n parser.add_argument(\\\"--verbose\\\", action=\\\"store_true\\\", dest=\\\"verbose\\\",\\n help=\\\"Report missing metadata.\\\")\\n\\n parser.add_argument(\\\"--keywords\\\", action=\\\"store\\\", dest=\\\"keywords\\\",\\n help=\\\"Comma delimited list of keywords for filtering search results.\\\")\\n parser.add_argument(\\\"--features\\\", action=\\\"store\\\", dest=\\\"features\\\",\\n help=\\\"Comma delimited list of features for filtering search results.\\\")\\n parser.add_argument(\\\"--authors\\\", action=\\\"store\\\", dest=\\\"authors\\\",\\n help=\\\"Comma delimited list of authors for filtering search results.\\\")\\n parser.add_argument(\\\"--version\\\", action=\\\"store\\\", dest=\\\"version\\\",\\n help=\\\"PyLith version for filtering search results.\\\")\\n parser.add_argument(\\\"--incompatible\\\", action=\\\"store_true\\\", dest=\\\"incompatible\\\",\\n help=\\\"Filter search results to show incompatible parameter files.\\\")\\n parser.add_argument(\\\"--output-format\\\", action=\\\"store\\\", dest=\\\"output_format\\\", \\n help=\\\"Output format\\\", default=\\\"txt\\\", choices=[\\\"text\\\", \\\"markdown\\\"])\\n\\n args = parser.parse_args()\\n\\n return args\",\n \"def process_command_line_arguments() -> Namespace:\\n\\n parser = build_parser()\\n arguments = parser.parse_args()\\n\\n return arguments\",\n \"def get_input():\\n parser = argparse.ArgumentParser(description='Parameters')\\n parser.add_argument('--host', help='adress of the host')\\n parser.add_argument('--port', help='port of IPMI host')\\n parser.add_argument('--user', help='user allowed to acces IPMI')\\n parser.add_argument('--passwd', help='password for the specific user')\\n parser.add_argument('--interval', help='seconds between each data reading')\\n parser.add_argument('--nread', help='number of time to collect data')\\n parser.add_argument('--store', action='store_true',\\n help='save the data collected in a nosql db')\\n args = parser.parse_args()\\n return args, parser\",\n \"def parse_args():\\n\\n parser = argparse.ArgumentParser(description='CLI to store Actisense-NGT Gateway values to InfluxDB and publish via MQTT')\\n parser.add_argument('--config', '-c', type=str, required=True, help='JSON configuraton file with path')\\n return parser.parse_args()\",\n \"def ParseArguments():\\n\\n\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"--db_file_path\\\", required = False, help = \\\"SQLite database filename\\\", type = str, default = '')\\n parser.add_argument(\\\"--server_url\\\", required = False, help = \\\"Server's domain name\\\", type = str, default = '')\\n parser.add_argument(\\\"--substation_name\\\", required = False, help = \\\"Substation name\\\", type = str, default = '')\\n parser.add_argument(\\\"--net_interfaces\\\", required = False, help = \\\"List of network interfaces\\\", type = str)\\n parser.add_argument(\\\"--no_hostname_check\\\", required = False, help = \\\"Disable TLS certificate hostname validation (insecure)\\\", action = 'store_true')\\n parser.add_argument(\\\"--external_interval\\\", required = False, help = \\\"Interval (s) between invocations of external commands\\\", default = '3')\\n parser.add_argument(\\\"--external_timeout\\\", required = False, help = \\\"Maximum time (s) an external command is allowed to run\\\", default = None)\\n parser.add_argument(\\\"--external_command\\\", required = False, help = \\\"Periodically invoke given command to gather external data. Use repeatedly.\\\", action = 'append', default = [])\\n parser.add_argument(\\\"--uuid\\\", required = False, help = \\\"To get UUID or hostname (set by default) as an unique ID.\\\", action = 'store_true')\\n\\n argv = parser.parse_args(sys.argv[1:])\\n\\n config_data = {}\\n try:\\n if os.path.isfile('config.json'):\\n json_data_file = open('config.json', 'r')\\n config_data = json.load(json_data_file)\\n required_keys = ['db_file_path', 'server_url']\\n for key in required_keys:\\n if key not in config_data:\\n print('config.json file does not contain required key %s' % key)\\n sys.exit()\\n else:\\n print('config.json does not exist in the current directory.')\\n sys.exit()\\n except IOError:\\n sys.exit()\\n\\n config_data['no_hostname_check'] = argv.no_hostname_check or config_data.get('no_hostname_check', False)\\n\\n interval = float(argv.external_interval)\\n\\n if argv.external_timeout is None:\\n timeout = interval\\n else:\\n timeout = float(argv.external_timeout)\\n\\n if timeout > interval:\\n print('Error: External command timeout is longer than interval')\\n sys.exit()\\n\\n config_data['external_interval'] = interval\\n config_data['external_timeout'] = timeout\\n config_data['external_command'] = argv.external_command\\n config_data['substation_name'] = argv.substation_name\\n config_data['uuid'] = argv.uuid\\n\\n if argv.db_file_path == '':\\n if not config_data['db_file_path']:\\n config_data['db_file_path'] = '/var/local/agent_sqlite3.db'\\n print('SQLite3 database file is set by default: /var/local/agent_sqlite3.db')\\n else:\\n config_data['db_file_path'] = argv.db_file_path\\n\\n ifs = argv.net_interfaces or config_data.get('net_interfaces', [])\\n if isinstance(ifs, str):\\n ifs = ifs.split(',')\\n config_data['net_interfaces'] = utils.interfaces_to_ip(ifs)\\n\\n # TODO verify provided URL\\n if argv.server_url == '':\\n if not config_data['server_url']:\\n print('Please, provide server URL as an argument or in config.json file.')\\n print('It must be in this format: wss://<domain_name>:443/agent')\\n sys.exit()\\n else:\\n config_data['server_url'] = argv.server_url\\n\\n\\n return config_data\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(description='Helps analyze articles.')\\n parser.add_argument('--config', default='config.yaml',\\n help='Configuration file for the options of this script')\\n parser.add_argument('--search', default=None, type=str,\\n help='Search for text in the articles')\\n parser.add_argument('--case-sensitive', action='store_true',\\n help='Makes search case-senstive (only applicatble to --search)')\\n parser.add_argument('--list', default=None, type=str,\\n help='List [title|authors|date|word-count|author|excerpt|content] of the articles')\\n parser.add_argument('--sort', action='store_true',\\n help='Sorts output (only applicable to --list).')\\n parser.add_argument('--sort-by', default=None, type=str,\\n help='Sorts output by another attribute [title|author|date] (only applicable to --list)')\\n parser.add_argument('--statistics', action='store_true',\\n help='Gives basic statistics about the articles.')\\n parser.add_argument('--count-articles', action='store_true',\\n help='Counts the total number of articles')\\n parser.add_argument('--count-words', action='store_true',\\n help='Counts the total number of words')\\n parser.add_argument('--count-paragraphs', action='store_true',\\n help='Counts the total number of paragraphs')\\n parser.add_argument('--count-by-author', action='store_true',\\n help='Counts the number of articles by each author')\\n parser.add_argument('--count-by-year', action='store_true',\\n help='Counts the number of articles bucketed by year')\\n parser.add_argument('--count-by-months', default=None, type=int,\\n help='Counts the number of articles bucketed by number of months')\\n \\n return parser, parser.parse_args()\",\n \"def process_arguments():\\r\\n # Create ArgumentParser object. Description message will be displayed as part of help message if script is run with -h flag\\r\\n parser = argparse.ArgumentParser(description='Downloads summary of findings for given interpretation request')\\r\\n # Define the arguments that will be taken.\\r\\n parser.add_argument('--ir_id', required=True, help='Interpretation request ID')\\r\\n parser.add_argument('--ir_version', required=True, help='Interpretation request version')\\r\\n parser.add_argument('-o', '--output_file', required=True, help='Output PDF')\\r\\n parser.add_argument('--header', required=False, help='Text for header of report')\\r\\n # Return the arguments\\r\\n return parser.parse_args()\",\n \"def parse_user_arguments(*args, **kwds):\\n\\n parser = argparse.ArgumentParser(\\n description = \\\"Generates the profiles of the input drug by using a network of expansion created expanding the protein-protein interactions from the targets of the drug\\\",\\n epilog = \\\"@oliva's lab 2017\\\")\\n parser.add_argument('-d','--drug_name',dest='drug_name',action = 'store',\\n help = \\\"\\\"\\\" Name of the drug. If you do not provide targets for this drug or the number of targets is not large enough,\\n the program will use this name to search for targets in BIANA database. If targets are provided, this field will be only used\\n for naming purposes and will be completely optional.\\n If the name of the drug has more than one word or special characters (parentheses, single quotes), introduce the name between \\n double quotes. \\\"\\\"\\\")\\n parser.add_argument('-t','--targets',dest='targets',action = 'store',\\n help = 'Input file with the targets of the drug. Each target must be separated by a newline character.')\\n parser.add_argument('-pt','--proteins_type_id',dest='proteins_type_id',action = 'store', default='geneid',\\n help = 'Input the type of ID of the targets introduced / proteins of the network. It must be the same! (default is geneid).')\\n parser.add_argument('-rad','--radius',dest='radius',action = 'store',default='3',\\n help = \\\"\\\"\\\" Define the radius of expansion for the creation of the network from targets (default is 3). \\\"\\\"\\\")\\n parser.add_argument('-tax','--taxid',dest='taxid',action = 'store',default='9606',\\n help = \\\"\\\"\\\"Define the restriction of species for the creation of the network from targets using a Taxonomy ID (default is '9606' (human))\\\"\\\"\\\")\\n parser.add_argument('-res','--restriction',dest='restriction',action = 'store',\\n help = \\\"\\\"\\\"Define an experiment restriction for the creation of the network from targets.\\\\n\\n Options:\\\\n\\n - AFF: Use interactions at least described by affinity methods (i.e. Tandem Affinity Purification)\\\\n\\n - Y2H: Use interactions at least described by yeast two hybrid methods (Y2H)\\\\n\\n - eAFF: Use all interactions except those described by affinity methods (i.e. Tandem Affinity Purification)\\\\n\\n - eY2H: Use all interactions except those described by yeast two hybrid methods (Y2H)\\\\n\\n - None: Not use experiment restrictions\\n \\\"\\\"\\\")\\n parser.add_argument('-th','--threshold_list',dest='threshold_list',action = 'store',\\n help = \\\"\\\"\\\"List of percentages that will be used as cut-offs to define the profiles of the drugs. It has to be a file containing:\\n - Different numbers that will be the threshold values separated by newline characters. \\n For example, a file called \\\"top_threshold.list\\\" containing:\\n 0.1\\n 0.5\\n 1\\n 5\\n 10\\n \\\"\\\"\\\")\\n parser.add_argument('-ws','--workspace',dest='workspace',action = 'store',default=os.path.join(os.path.join(os.path.dirname(__file__), '..'), 'workspace'),\\n help = \\\"\\\"\\\"Define the workspace directory where the data directory and the results directory will be created\\\"\\\"\\\")\\n\\n options=parser.parse_args()\\n\\n return options\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description=\\\"evaluate the recovered derg by comparing with ground truth mapping file\\\")\\n parser.add_argument(\\\"-mapping\\\", action=\\\"store\\\", dest=\\\"mapping_file\\\",\\n required=True, help=\\\"path to proguard-generated mapping.txt\\\")\\n parser.add_argument(\\\"-recovered_derg\\\", action=\\\"store\\\", dest=\\\"recovered_derg\\\",\\n required=True, help=\\\"path to recovered derg\\\")\\n parser.add_argument(\\\"-nice2predict_mapping\\\", action=\\\"store\\\", dest=\\\"nice2predict_mapping_file\\\",\\n help=\\\"path to nice2predict-generated mapping.txt\\\")\\n parser.add_argument(\\\"-o\\\", action=\\\"store\\\", dest=\\\"report_dir\\\",\\n default=\\\".\\\", help=\\\"directory of report files\\\")\\n parser.add_argument(\\\"-report_name\\\", action=\\\"store\\\", dest=\\\"report_name\\\",\\n default=DEFAULT_REPORT_NAME, help=\\\"name of report file\\\")\\n parser.add_argument(\\\"-match_mode\\\", action=\\\"store\\\", dest=\\\"match_mode\\\",\\n default=MATCH_MODE_EXACT, help=\\\"match mode\\\")\\n\\n options = parser.parse_args()\\n print options\\n return options\",\n \"def run(argv=None):\\n parser = argparse.ArgumentParser(description='Query elasticsearch indices/index/documents and print them '\\n 'formatted as JSON-Objects',\\n formatter_class=argparse.RawTextHelpFormatter)\\n parser.add_argument('-server', type=str, help=\\\"use http://host:port/index/type/id.\\\\n\\\"\\n \\\"host:port - hostname or IP with port of the elasticsearch node to query\\\\n\\\"\\n \\\" default: localhost:9200\\\\n\\\"\\n \\\"index - index to query\\\\n\\\"\\n \\\" default: None → queries across all available indices\\\\n\\\"\\n \\\"type - elasticsearch doctype to use (optional)\\\\n\\\"\\n \\\"id - identifier of one specific document to query (optional)\\\",\\n default=\\\"http://127.0.0.1:9200\\\")\\n parser.add_argument('-ign-source', action=\\\"store_true\\\",\\n help='return the Document or just the Elasticsearch-Metadata')\\n parser.add_argument('-size', type=str, default=None, metavar=\\\"N[:M]\\\",\\n help='just return the first n-Records of the search,\\\\n'\\n 'or return a python slice, e.g. 2:10 returns a list\\\\n'\\n 'from the 2nd including the 9th element of the search\\\\n'\\n 'only works with the ESGenerator\\\\n'\\n 'Note: Not all slice variants may be supported')\\n parser.add_argument('-timeout', type=int, default=10,\\n help='Set the time in seconds after when a ReadTimeoutError can occur.\\\\n'\\n 'Default is 10 seconds. Raise for big/difficult querys ')\\n parser.add_argument(\\\"-includes\\\", type=str,\\n help=\\\"just include following _source field(s) in the _source object\\\")\\n parser.add_argument(\\\"-excludes\\\", type=str,\\n help=\\\"exclude following _source field(s) from the _source object\\\")\\n parser.add_argument(\\\"-headless\\\", action='store_true',\\n help=\\\"don't print Elasticsearch metadata\\\")\\n parser.add_argument('-body', type=helperscripts.jsonstring_or_file,\\n help='Elasticsearch Query object that can be in the form of\\\\n'\\n '1) a JSON string (e.g. \\\\'{\\\"query\\\": {\\\"match\\\": {\\\"name\\\": \\\"foo\\\"}}}\\\\')\\\\n'\\n '2) a file containing the upper query string')\\n parser.add_argument('-idfile', type=str,\\n help=\\\"path to a file with \\\\\\\\n-delimited IDs to process\\\")\\n parser.add_argument('-idfile_consume', type=str,\\n help=\\\"path to a file with \\\\\\\\n-delimited IDs to process\\\")\\n parser.add_argument('-missing_behaviour', type=str, choices=['print', 'yield'], default='print',\\n help=\\\"If IDs from an idfile are missing: 'print' or 'yield'\\\\n\\\"\\n \\\"and json dict containing the ID, default is 'print'\\\")\\n parser.add_argument('-pretty', action='store_true',\\n help=\\\"prettyprint the json output\\\")\\n parser.add_argument('-verbose', action='store_true',\\n help=\\\"print progress for large dumps\\\")\\n parser.add_argument('-chunksize', type=int, default=1000,\\n help=\\\"chunksize of the search window to use\\\")\\n parser.add_argument(\\\"-auth\\\", type=str, nargs=\\\"?\\\", const=\\\"ENV\\\", metavar=\\\"USER\\\",\\n help='Provide authentication, this can be done using:\\\\n'\\n '1) set environment variables E2J_USER and E2J_PASSWD. In\\\\n'\\n ' this case there is no further argument needed here\\\\n'\\n '2) as a string \\\"username\\\". The password is then asked interactively\\\\n'\\n '3) as \\\"username:password\\\" (not recommended)')\\n args = parser.parse_args(argv)\\n es_kwargs = {} # dict to collect kwargs for ESgenerator\\n #parsing server # http://server.de:1234/index/_doc/101\\n slashsplit = args.server.split(\\\"/\\\") # → [http:, , server.de:1234, index, _doc, 101]\\n es_kwargs[\\\"host\\\"] = slashsplit[2].rsplit(\\\":\\\")[0]\\n es_kwargs[\\\"port\\\"] = int(args.server.split(\\\":\\\")[2].rsplit(\\\"/\\\")[0]) # raise Error if port not castable to int\\n if len(slashsplit) > 3:\\n es_kwargs[\\\"index\\\"] = slashsplit[3]\\n if len(slashsplit) > 4:\\n es_kwargs[\\\"type_\\\"] = slashsplit[4]\\n if len(slashsplit) > 5:\\n es_kwargs[\\\"id_\\\"] = slashsplit[5]\\n\\n if args.auth:\\n raise NotImplementedError(\\\"authentication not yet implemented\\\")\\n # args.pop(\\\"auth\\\")\\n if args.auth == \\\"ENV\\\":\\n # check and use environmental username (E2J_USER) and password (E2J_PASSWD)\\n pass\\n else:\\n # parse authentication string: either \\\"username\\\" or \\\"username:password\\\"\\n pass\\n\\n if args.size:\\n \\\"\\\"\\\"\\n we build the slice() object here, if this fails because of user input,\\n the stacktrace of slice() is very informative, so we don't do our own Error handling here\\n for size-searches, we don't use a scroll since the user wants only a small searchwindow\\n \\\"\\\"\\\"\\n if isinstance(args.size, int): # oh, we got an single number, not a string with an number or even an string describing a slice\\n args.size = str(args.size)\\n if ':' in args.size:\\n es_kwargs[\\\"slice_\\\"] = slice(int(args.size.split(':')[0]), int(args.size.split(':')[1]), 1)\\n else:\\n es_kwargs[\\\"slice_\\\"] = slice(0, int(args.size), 1)\\n\\n if args.headless and args.ign_source:\\n helperscripts.eprint(\\\"ERROR! do not use -headless and -ign-source at the same Time!\\\")\\n exit(-1)\\n else:\\n es_kwargs[\\\"headless\\\"] = args.headless\\n es_kwargs[\\\"source\\\"] = not args.ign_source\\n\\n if args.pretty:\\n tabbing = 4\\n else:\\n tabbing = None\\n\\n if args.includes and isinstance(args.includes, str):\\n es_kwargs[\\\"includes\\\"] = args.includes.split(\\\",\\\")\\n if args.excludes and isinstance(args.excludes, str):\\n es_kwargs[\\\"excludes\\\"] = args.excludes.split(\\\",\\\")\\n\\n if args.chunksize:\\n es_kwargs[\\\"chunksize\\\"] = args.chunksize\\n if args.body:\\n es_kwargs[\\\"body\\\"] = args.body\\n if args.timeout:\\n es_kwargs[\\\"timeout\\\"] = args.timeout\\n if args.verbose:\\n es_kwargs[\\\"verbose\\\"] = args.verbose\\n if args.missing_behaviour and (args.idfile or args.idfile_consume):\\n es_kwargs[\\\"missing_behaviour\\\"] = args.missing_behaviour\\n if args.idfile:\\n es_kwargs[\\\"idfile\\\"] = args.idfile\\n ESGeneratorFunction = IDFile(**es_kwargs).generator()\\n elif args.idfile_consume:\\n es_kwargs[\\\"idfile\\\"] = args.idfile_consume\\n ESGeneratorFunction = IDFileConsume(**es_kwargs).generator()\\n else:\\n ESGeneratorFunction = ESGenerator(**es_kwargs).generator()\\n for json_record in ESGeneratorFunction:\\n print(json.dumps(json_record, indent=tabbing))\",\n \"def readArgs():\\n parser = argparse.ArgumentParser(description=\\n \\\"\\\"\\\"Debug script. This program is used in order to generate a summary\\n statistics for the csv files generated by the annotation_parser. Things\\n like the average amount of overlap of each window and the average deviation.\\n \\\"\\\"\\\")\\n\\n parser.add_argument('-f', '--csv-dir', metavar='',\\n dest='csv_dir',\\n action='store', default=os.path.dirname(os.path.abspath(__file__)),\\n help='Specify the csv directory.')\\n parser.add_argument('-d', '--deviation', metavar='',\\n dest='deviation', action='store',\\n default=50,\\n help='percentage set point from which evaluate the deviation from.')\\n\\n return parser.parse_args()\",\n \"def parseArguments(self):\\n iterator = iter(sys.argv[1:]) # Skip file name\\n for argument in iterator:\\n if len(argument) < 2 or argument[:2] != '--':\\n self.error('syntax error \\\"{}\\\"'.format(argument))\\n else:\\n def getValueOfArgument(): return next(iterator)\\n self.parseArgument(argument[2:], getValueOfArgument)\",\n \"def parse_args():\\n help_text = \\\"\\\"\\\"\\n Analyzer of the frequency of use of nouns in the headings of posts on hubr.com\\n \\\"\\\"\\\"\\n parser = argparse.ArgumentParser(\\n description=help_text\\n )\\n parser.add_argument(\\n '-p',\\n '--pages',\\n type=int,\\n dest='page_count',\\n default=PAGE_COUNT,\\n help=f'Number of pages to parse, default is {PAGE_COUNT}.'\\n )\\n parser.add_argument(\\n '-s',\\n '--start',\\n type=int,\\n default=PAGE_START,\\n dest='start_page',\\n help=f'Start page number, default is {PAGE_START}.',\\n )\\n parser.add_argument(\\n '-t',\\n '--top',\\n type=int,\\n default=TOP_SIZE,\\n dest='top_size',\\n help=f'The size of the top noun, default is {TOP_SIZE}.',\\n )\\n\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"auth\\\",\\n help=\\\"authentication string for Infermedica API: \\\"\\n \\\"APP_ID:APP_KEY or path to file containing it.\\\")\\n parser.add_argument(\\\"--model\\\",\\n help=\\\"use non-standard Infermedica model/language, \\\"\\n \\\"e.g. infermedica-es\\\")\\n args = parser.parse_args()\\n return args\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(description='Scraper')\\n parser.add_argument('--prefix', help='Prefix for saving files', default=\\\"\\\")\\n parser.add_argument('--path', help='Dir path', default=\\\"\\\")\\n parser.add_argument('--urls_path', help='Url path', default=False)\\n parser.add_argument('--url', help='Url', default=False)\\n parser.add_argument('--disney', dest='disney', action='store_true', help=\\\"Choose all disney movies\\\")\\n parser.add_argument('--ngram', help='Max ngram', default=2)\\n\\n args = parser.parse_args()\\n return args\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(\\n description='Aggregate Elasticsearch Log data.')\\n parser.add_argument(\\n '--host',\\n default='https://logging-es',\\n type=str,\\n action='store',\\n help='Host name or IP of the Elasticsearch server.'\\n )\\n parser.add_argument(\\n '--port',\\n default=9200,\\n type=int,\\n action='store',\\n help='Port number of the Elasticsearch server.'\\n )\\n parser.add_argument(\\n '--ca_certs',\\n default='secret/admin-ca',\\n type=str,\\n action='store',\\n help='Path to the CA certificates file'\\n )\\n parser.add_argument(\\n '--cert',\\n default='secret/admin-cert',\\n type=str,\\n action='store',\\n help='Path to the client certificate file'\\n )\\n parser.add_argument(\\n '--key',\\n default='secret/admin-key',\\n type=str,\\n action='store',\\n help='Path to the client key file'\\n )\\n\\n return parser.parse_args()\",\n \"def get_args():\\n parser = argparse.ArgumentParser(description=\\\"Processing tweets\\\")\\n\\n parser.add_argument(\\\"-db\\\", \\\"--db\\\", type = str, required = True, \\n help = \\\"The Name of Database to store\\\")\\n\\n args = parser.parse_args()\\n \\n return args\",\n \"def get_arguments():\\n parser = argparse.ArgumentParser(prog=\\\"python3 olympics.py\\\",\\n description=\\\"Search for data in olympics database\\\",\\n epilog=\\\"Run -h for each positional arguments to see more details.\\\")\\n\\n subparsers = parser.add_subparsers(help='sub-command help', dest='subcommand')\\n\\n parser_athlete = subparsers.add_parser('athlete', \\n help=\\\"print athletes based on different options\\\")\\n\\n parser_athlete.add_argument('-n', '--nocs', type=str, nargs='+',\\n help=\\\"print all athletes in the given nocs in the arguments\\\")\\n\\n parser_athlete.add_argument('-a', '--name', type=str, nargs='+',\\n help=\\\"print all athletes whose names contains the arguments\\\")\\n\\n parser_noc = subparsers.add_parser('noc', \\n help=\\\"print nocs based on counts of medals\\\")\\n \\n parser_noc.add_argument('-m', '--medal', type=str, nargs='?', choices=['gold', 'silver', 'bronze'],\\n help=\\\"order nocs based on the type of medal in the argument\\\")\\n\\n parser_game = subparsers.add_parser('game',\\n help=\\\"print the country winning the most number of gold in a give year\\\")\\n \\n parser_game.add_argument('-y', '--year', type=str, nargs='?',\\n help=\\\"print the country winning the most number of gold in a give year\\\")\\n \\n args = parser.parse_args()\\n\\n return args\",\n \"def _parse_args(self, prepared_args):\\n pass\",\n \"def parse_user_arguments():\\n\\n ap = argparse.ArgumentParser()\\n\\n ap.add_argument(\\\"-m\\\", \\\"--method\\\",\\n help=\\\"Enter the type of baseline run, \\\"\\n \\\"bm_25, tf_idf or jm_qlm\\\", required=True)\\n\\n ap.add_argument(\\\"-j\\\", \\\"--json_fname\\\", help=\\\"Enter the path to the json \\\"\\n \\\"filename containing\\\"\\n \\\"all the paths to the \\\"\\n \\\"test_collection\\\",\\n required=True)\\n\\n return vars(ap.parse_args())\",\n \"def get_args():\\n parser = argparse.ArgumentParser(description='Runner for tasks')\\n parser.add_argument('--db_url', help='Database url string to the db.', required=True)\\n return parser.parse_args()\",\n \"def argumentsParser(args):\\n\\targuments = []\\n\\tif args.find('\\\"') > -1:\\n\\t\\tt_arguments = args.split('\\\"')\\n\\t\\tfor a in t_arguments:\\n\\t\\t\\tif a == '' or a == ' ':\\n\\t\\t\\t\\tpass\\n\\t\\t\\telif a[-1] == ' ':\\n\\t\\t\\t\\targuments.append(a[:-1])\\n\\t\\t\\telse:\\n\\t\\t\\t\\targuments.append(a)\\n\\telif args.find(\\\"'\\\") > -1:\\n\\t\\tt_arguments = args.split(\\\"'\\\")\\n\\t\\tfor a in t_arguments:\\n\\t\\t\\tif a == '' or a == ' ':\\n\\t\\t\\t\\tpass\\n\\t\\t\\telif a[-1] == ' ':\\n\\t\\t\\t\\targuments.append(a[:-1])\\n\\t\\t\\telse:\\n\\t\\t\\t\\targuments.append(a)\\n\\telif args == ' ':\\n\\t\\tpass\\n\\telse:\\n\\t\\targuments = args.split(' ')\\n\\treturn arguments\",\n \"def parse_args():\\n\\tparser = argparse.ArgumentParser(description='Show video statistics.')\\n\\tparser.add_argument('--sort', metavar='FIELD', choices=['views', 'likes', 'dislikes'],\\n\\t default='views',\\n\\t help='sort by the specified field. Options are views, likes and dislikes.')\\n\\tparser.add_argument('--max', metavar='MAX', type=int, help='show the top MAX entries only.')\\n\\tparser.add_argument('--csv', action='store_true', default=False,\\n\\t help='output the data in CSV format.')\\n\\tparser.add_argument('--table', action='store_true', default=False,\\n\\t help='output the data in an ascii table.')\\n\\tparser.add_argument('--workers', type=int, default=8,\\n\\t help='number of workers to use, 8 by default.')\\n\\treturn parser.parse_args()\",\n \"def parse_args():\\n\\n\\t# Define the input parser\\n\\tdesc = \\\"computes long term temperature anomaly trend for the GHNC dataset\\\"\\n\\tepilog = \\\"\\\"\\\"\\ndatarange input argument is of the format:\\n\\t\\t YYYY[MM[DD]][:YYYY[MM[DD]]]\\nWhere the date before the optional ':'' represents the lower bound of\\nthe range and the optional date after the : represents the upper\\nbound. The optional elements of the date default to the lowest possible\\nvalue for the lower bound and to the maximum possible for the upper\\none. For example,\\n\\t2006 is equivalent to 2006/01/01:2006/12/31\\n\\t2006/02 is equivalent to 2006/02/01:2006/02/28\\n\\\"\\\"\\\"\\n\\n\\tparser = argparse.ArgumentParser(description=desc, epilog=epilog,\\n\\t\\t\\t\\t\\t\\tformatter_class=argparse.RawDescriptionHelpFormatter)\\n\\tparser.add_argument(\\\"daterange\\\",\\n\\t\\t\\t\\t\\t\\thelp=\\\"range of dates to make available locally\\\")\\n\\tparser.add_argument('-t',\\\"--timeseries\\\",nargs=2,metavar=('lon','lat'),type=float,\\n\\t\\t\\t\\t\\t\\thelp=\\\"plot timeseries for the lon lat pair of coordinates\\\")\\n\\tparser.add_argument('-r',\\\"--recompute\\\",default=False,action='store_true',\\n\\t\\t\\t\\t\\t\\thelp=\\\"force recompute trend\\\")\\n\\n\\treturn parser.parse_args()\",\n \"def Args(parser):\\n parser.add_argument('appname', help='The sample app name, e.g. \\\"finance\\\".')\\n\\n parser.add_argument(\\n '--duration',\\n default='1h',\\n type=arg_parsers.Duration(),\\n help=('Duration of time allowed to run before stopping the workload.'))\\n parser.add_argument(\\n '--port', type=int, help=('Port of the running backend service.'))\\n parser.add_argument(\\n '--target-qps', type=int, help=('Target requests per second.'))\",\n \"def Args(parser):\",\n \"def get_command_line_arguments():\\n parser = argparse.ArgumentParser(description=\\\"Build XENON1T events from the DAQ.\\\")\\n\\n parser.add_argument('--config',\\n default=['eventbuilder'],\\n nargs='+',\\n help=\\\"Name(s) of the pax configuration(s) to use, default is eventbuilder. \\\")\\n parser.add_argument('--config_path',\\n default=[],\\n nargs='+',\\n help=\\\"Path(s) of the configuration file(s) to use.\\\")\\n\\n parser.add_argument('--cpus', default=1, nargs='?',\\n help=\\\"Number of CPUs to use for event building. Default is 1; can be 'all'.\\\")\\n parser.add_argument('--detector', default='tpc', type=str,\\n help=\\\"Detector to build events for\\\")\\n parser.add_argument('--log', default='INFO',\\n help=\\\"Logging level to use, e.g. DEBUG\\\")\\n parser.add_argument('--secret_mode', action='store_true',\\n help=\\\"Never write anything to the runs db. Use only for testing!\\\")\\n parser.add_argument('--wait', default=10, type=int,\\n help=\\\"Wait time before searching for new runs again if none were found (sec). \\\"\\n \\\"If 0, instead shuts down if no new runs are found.\\\")\\n\\n connection_group = parser.add_argument_group(title='MongoDB connection settings')\\n connection_group.add_argument('--host', default='gw', type=str,\\n help='MongoDB hostname')\\n connection_group.add_argument('--port', default=27017, type=int,\\n help='Port on host where MongoDB runs')\\n connection_group.add_argument('--user', default='eb', type=str,\\n help='User to connect to MongoDB')\\n connection_group.add_argument('--password', type=str, default=os.environ.get('MONGO_PASSWORD'),\\n help='Password to connect to MongoDB. '\\n 'If not provided, will try to use MONGO_PASSWORD from env')\\n\\n single_run_group = parser.add_mutually_exclusive_group()\\n single_run_group.add_argument('--run_name', type=str,\\n help=\\\"Instead of building all waiting_to_be_processed runs, \\\"\\n \\\"look for this specific run name and build it.\\\")\\n single_run_group.add_argument('--run', type=int,\\n help=\\\"Instead of building all waiting_to_be_processed runs, \\\"\\n \\\"look for this specific run number and build it.\\\")\\n\\n trigger_group = parser.add_argument_group(title='Trigger settings',\\n description='Override default settings for the trigger.')\\n trigger_group.add_argument('--force_multiplicity_trigger', type=int,\\n help='Forces the trigger into a more basic mode: always trigger on a signal of more than'\\n 'force_multiplicity_trigger pulses, and never on smaller signals.')\\n trigger_group.add_argument('--signal_separation', type=float,\\n help='If no pulses start for this length of time (us),'\\n 'a signal ends / a new signal can start.')\\n trigger_group.add_argument('--event_separation', type=float,\\n help='If there are no triggers for this length of time (us),'\\n 'a new event can start.')\\n trigger_group.add_argument('--left_extension', type=float,\\n help=\\\"Minimum range before each trigger to save (us). Is abs()ed before it is used.\\\")\\n trigger_group.add_argument('--right_extension', type=float,\\n help='Minimum time after trigger to save (us).')\\n\\n mongoreader_group = parser.add_argument_group(title='Trigger driving / Mongo reading settings')\\n mongoreader_group.add_argument('--batch_window', type=float,\\n help='Length of time range (in sec, float) to get pulse data in each query.')\\n mongoreader_group.add_argument('--delete_data', action='store_true',\\n help=\\\"Delete data from the untriggered collection while triggering on it. \\\"\\n \\\"Essential for running the trigger live for an extended time!\\\")\\n mongoreader_group.add_argument('--edge_safety_margin', type=int,\\n help=\\\"When triggering live, stay at least this many seconds \\\"\\n \\\"away from the insertion edge.\\\")\\n mongoreader_group.add_argument('--max_query_workers', type=int,\\n help=\\\"Maximum number of parallel pulse time range queries \\\"\\n \\\"to fire off in the trigger. If delete_data, this is also the maximum \\\"\\n \\\"number of parallel delete queries.\\\")\\n mongoreader_group.add_argument('--skip_ahead', type=int, default=0,\\n help=\\\"After triggering a batch of data, skip ahead this number of batches \\\"\\n \\\"without triggering. \\\"\\n \\\"Use only for dealing quickly with runs that have overflown to disk!\\\")\\n mongoreader_group.add_argument('--stop_after_sec', type=float,\\n help=\\\"Stop the trigger after this many seconds of data have been read. \\\"\\n \\\"Won't stop in the middle of a batch. Use only for testing!\\\")\\n\\n args = parser.parse_args()\\n return args\",\n \"def parse_arguments():\\n parser = ArgumentParser(description=\\\"Run tests in parallel.\\\")\\n parser.add_argument(\\n \\\"-d\\\", \\\"--debug\\\", action=\\\"store_true\\\", help=\\\"Enable debug logging\\\"\\n )\\n parser.add_argument(\\n \\\"-l\\\", \\\"--layer\\\", help=\\\"Greedy match test layer name.\\\", action=\\\"append\\\"\\n )\\n parser.add_argument(\\n \\\"-m\\\", \\\"--module\\\", help=\\\"Greedy match module name.\\\", action=\\\"append\\\"\\n )\\n return parser.parse_args()\",\n \"def parse_command_line():\\n parser = argparse.ArgumentParser(prog='scoring')\\n parser.add_argument(\\\"pdb_list\\\", help=\\\"list of PDB structures\\\")\\n script_args = parser.parse_args()\\n return script_args\",\n \"def parse_arguments():\\n\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument(\\\"--accessions\\\", help=\\\"A json file with old/new family mapppings\\\")\\n parser.add_argument(\\\"--add-header\\\", help=\\\"Print descriptive header\\\",\\n action=\\\"store_true\\\", default=False)\\n parser.add_argument(\\\"--add-links\\\", help=\\\"Creates hyperlinks to available Rfam html content\\\",\\n action=\\\"store_true\\\", default=False)\\n return parser\",\n \"def command_line_arguments():\\n _parser.add_argument('-l', '--list', nargs='+',\\n help='<Required> Set flag', required=True)\\n _parser.add_argument(\\\"-A\\\", \\\"--access\\\", required=True,\\n help=\\\"access to host => grant/revoke\\\")\",\n \"def parseArguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('--output_folder',\\n help='Path of the folder where output files should be written.')\\n parser.add_argument('--partition_id',\\n help='ID of the computer partition to collect data from.')\\n parser.add_argument('--collector_db',\\n help='The path of slapos collect database.')\\n\\n return parser.parse_args()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7214492","0.67600626","0.6744214","0.6540915","0.65117174","0.64484125","0.6437705","0.63874245","0.63734406","0.63580865","0.63525504","0.63441116","0.6306649","0.62947834","0.6288351","0.6278856","0.6265019","0.6261954","0.6249996","0.6239955","0.62340283","0.6227418","0.6223816","0.6212814","0.62057906","0.6205073","0.6203906","0.62017006","0.6194693","0.6189743","0.6174004","0.6171964","0.6167261","0.6156257","0.61419356","0.6120674","0.6111553","0.610271","0.6100445","0.6099662","0.60816187","0.60816187","0.6073766","0.6057745","0.6044363","0.60394704","0.6037858","0.60320777","0.6027528","0.60273045","0.60270417","0.6023274","0.60109323","0.6009575","0.60093933","0.600935","0.60091466","0.59991455","0.5996934","0.5996573","0.59935397","0.59892625","0.5988562","0.59871787","0.59851485","0.59754914","0.5974879","0.5972096","0.5951576","0.595146","0.59493715","0.5947676","0.59449166","0.5924302","0.5915046","0.5913383","0.5911349","0.5906607","0.59039474","0.5903269","0.5901814","0.59010535","0.58953017","0.58943856","0.58928263","0.5891966","0.5887228","0.5886774","0.58866984","0.58778954","0.5872666","0.58705765","0.58699936","0.5868152","0.5866681","0.58653903","0.58651954","0.5865057","0.58551633","0.58536416"],"string":"[\n \"0.7214492\",\n \"0.67600626\",\n \"0.6744214\",\n \"0.6540915\",\n \"0.65117174\",\n \"0.64484125\",\n \"0.6437705\",\n \"0.63874245\",\n \"0.63734406\",\n \"0.63580865\",\n \"0.63525504\",\n \"0.63441116\",\n \"0.6306649\",\n \"0.62947834\",\n \"0.6288351\",\n \"0.6278856\",\n \"0.6265019\",\n \"0.6261954\",\n \"0.6249996\",\n \"0.6239955\",\n \"0.62340283\",\n \"0.6227418\",\n \"0.6223816\",\n \"0.6212814\",\n \"0.62057906\",\n \"0.6205073\",\n \"0.6203906\",\n \"0.62017006\",\n \"0.6194693\",\n \"0.6189743\",\n \"0.6174004\",\n \"0.6171964\",\n \"0.6167261\",\n \"0.6156257\",\n \"0.61419356\",\n \"0.6120674\",\n \"0.6111553\",\n \"0.610271\",\n \"0.6100445\",\n \"0.6099662\",\n \"0.60816187\",\n \"0.60816187\",\n \"0.6073766\",\n \"0.6057745\",\n \"0.6044363\",\n \"0.60394704\",\n \"0.6037858\",\n \"0.60320777\",\n \"0.6027528\",\n \"0.60273045\",\n \"0.60270417\",\n \"0.6023274\",\n \"0.60109323\",\n \"0.6009575\",\n \"0.60093933\",\n \"0.600935\",\n \"0.60091466\",\n \"0.59991455\",\n \"0.5996934\",\n \"0.5996573\",\n \"0.59935397\",\n \"0.59892625\",\n \"0.5988562\",\n \"0.59871787\",\n \"0.59851485\",\n \"0.59754914\",\n \"0.5974879\",\n \"0.5972096\",\n \"0.5951576\",\n \"0.595146\",\n \"0.59493715\",\n \"0.5947676\",\n \"0.59449166\",\n \"0.5924302\",\n \"0.5915046\",\n \"0.5913383\",\n \"0.5911349\",\n \"0.5906607\",\n \"0.59039474\",\n \"0.5903269\",\n \"0.5901814\",\n \"0.59010535\",\n \"0.58953017\",\n \"0.58943856\",\n \"0.58928263\",\n \"0.5891966\",\n \"0.5887228\",\n \"0.5886774\",\n \"0.58866984\",\n \"0.58778954\",\n \"0.5872666\",\n \"0.58705765\",\n \"0.58699936\",\n \"0.5868152\",\n \"0.5866681\",\n \"0.58653903\",\n \"0.58651954\",\n \"0.5865057\",\n \"0.58551633\",\n \"0.58536416\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6177763"},"document_rank":{"kind":"string","value":"30"}}},{"rowIdx":13089,"cells":{"query":{"kind":"string","value":"Initializes the VNIStatsTableEntrySchema object attributes."},"document":{"kind":"string","value":"def __init__(self, py_dict=None):\n super(VNIStatsTableEntrySchema, self).__init__()\n self.update_arp = None\n self.query_arp = None\n\n if py_dict is not None:\n self.get_object_from_py_dict(py_dict)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def InitStats(ss):\n\n ss.SumSSE = 0\n ss.SumAvgSSE = 0\n ss.SumCosDiff = 0\n ss.SumErr = 0\n ss.FirstZero = -1\n ss.NZero = 0\n\n ss.TrlErr = 0\n ss.TrlSSE = 0\n ss.TrlAvgSSE = 0\n ss.EpcSSE = 0\n ss.EpcAvgSSE = 0\n ss.EpcPctErr = 0\n ss.EpcCosDiff = 0","def _init_table(self, table: \"Table\"):\n if not self.columns:\n self.columns = table.columns\n self._data = table.data","def __init__(self):\n _snap.TTableRow_swiginit(self, _snap.new_TTableRow())","def __init__(self, schema=None):\n self._dict = {}\n self.schema = schema","def __init__(self, *args):\n _snap.TTable_swiginit(self, _snap.new_TTable(*args))","def _setup_stats(self) -> None:\n\n # Save statistics\n self.mass = np.array([0])\n self.mass_balance = np.array([0])\n self.mass_balance_trend = np.array([0])","def __init__(self, *args):\n _table.Table_swiginit(self, _table.new_Table(*args))","def __init__(self, metrics, schema, table, nid):\n\n self.id = nid\n self.metrics = metrics\n self.schema = schema\n self.table = table\n self.batch_size = 20\n self.__init_metrics()","def __init__(self):\n self.table = {}","def _initialize_table(self):\n self.table = gtk.Table()\n self.table.set_col_spacings(8)\n self.table.set_row_spacings(3)\n self.window.add(self.table)\n self._view_schedule()\n self.table.show()","def setup(self):\n self.table = prettytable.PrettyTable()\n self.table.field_names = self.titles\n if self.convert_columns:\n self.rows = self.convert_columns_to_rows(self.rows)\n if self.colour:\n self.colour = self.convert_columns_to_rows(self.colour)","def __init__(self, schema=None):\n self.schema = schema or {}","def __init__(self):\n self.buckets = 1009\n self.table = [{} for _ in range(self.buckets)]","def __init__(self, *args):\n _snap.Schema_swiginit(self, _snap.new_Schema(*args))","def __init__(self):\n super(ObjectSchema, self).__init__()\n self.is_allow_undefined = False","def __init__(self):\n self.title = None\n self.table = pd.DataFrame()\n self.column_widths = None;","def _init(self):\n self._nfields = 0\n self._converted = {}\n self._heapoffset = 0\n self._heapsize = 0\n self._col_weakrefs = weakref.WeakSet()\n self._coldefs = None\n self._gap = 0\n self._uint = False","def setup_table(self):\n\n self.setup.create_basic_table_in_dev()\n self.setup.insert_random_records_into_dev()","def __init__(self, *args, **kwargs):\n \n self.dense = True\n\n # Create table\n super().__init__(*args, **kwargs)","def __init__(self, PTableV):\n _snap.TTableIterator_swiginit(self, _snap.new_TTableIterator(PTableV))","def init_blank(self, T):\n self.headings = []\n self.table = {}\n self.rowcount = 0\n for e in T.entries:\n self.headings.append(e.name)\n self.table[e.name] = []","def process_table_init(self):\n logging.debug(\"Processing table initialization, %d entries\",\n len(self.table_initialization))\n\n for init_entry in self.table_initialization:\n for table_name, entry_desc in init_entry.items():\n self.air_table[table_name].add_entry(\n table_entry.description_to_entry(entry_desc))","def _initialise_sufficient_statistics(self):\n stats = super()._initialise_sufficient_statistics()\n\n stats['B'] = {\n 'numer': [\n np.zeros((self.n_states, self.n_features[i]))\n for i in range(self.n_emissions)\n ],\n 'denom': [\n np.zeros((self.n_states, self.n_features[i]))\n for i in range(self.n_emissions)\n ],\n }\n\n return stats","def __init__(self, table_name, cursor=None, schema=None):\n self.name = table_name\n self.tablespace_name = None\n self.table_type = None\n self.columns = {}\n self.indexes = {}\n self.constraints = {}\n self.triggers = {}\n if schema:\n self.schema = schema\n else:\n self.schema = None\n if cursor:\n self._get_table(cursor)","def __init__(self):\n self.table = {}\n self.ls = []","def setup_table(self):\n self.interface.start_transaction()\n self.interface.drop_table(_history_table)\n self.interface.drop_table(_history_stats_table)\n self.interface.create_table(_history_table)\n self.interface.create_index('index1', _history_table, [_history_table['timestamp']])\n self.interface.create_table(_history_stats_table)\n self.interface.create_index('index2', _history_stats_table, [_history_stats_table['benchmark']])\n self.interface.commit_transaction()","def __init__(self, schema ):\n self.schema = schema","def _get_table_schema(self):\n\n return {\n 'AttributeDefinitions': [\n {\n 'AttributeName': self._key_field.name,\n 'AttributeType': self._key_field.data_type\n }\n ],\n 'TableName': self.table_name,\n 'KeySchema': [\n {\n 'AttributeName': self._key_field.name,\n 'KeyType': 'HASH'\n }\n ],\n 'ProvisionedThroughput': {\n 'ReadCapacityUnits': self.read_capacity_units,\n 'WriteCapacityUnits': self.write_capacity_units\n }\n }","def _initialize(self):\n query_table = self._cursor.execute(f\"\"\"\n SELECT name\n FROM sqlite_master\n WHERE type='table' AND name='{self._table_name}';\"\"\")\n\n if not query_table.fetchone():\n self._cursor.execute(f\"\"\"\n CREATE TABLE {self._table_name} (\n id char(36),\n term TEXT,\n timestamp BIGINT\n );\"\"\")\n\n self._cursor.execute(f\"\"\"\n CREATE INDEX index_timestamp\n ON {self._table_name} (timestamp);\"\"\")\n\n self._conn.commit()","def init_widget(self):\n super(QtViewTable, self).init_widget()\n d = self.declaration\n self.set_table_model(d.table_model)\n self.set_orientation(d.orientation)","def __init__(self, DEBUG=False):\n self.DEBUG = DEBUG\n\n self.classTable = {}\n self.subroutineTable = {}\n\n self.counts = {}\n self.counts[\"STATIC\"] = 0\n self.counts[\"FIELD\"] = 0\n self.counts[\"ARG\"] = 0\n self.counts[\"VAR\"] = 0\n\n if self.DEBUG:\n print(\"DEBUG(SymbolTable): INITIALIZED SYMBOL TABLES\")","def init_structs(self):\n self.v6_struct = struct.Struct(V6_STRUCT_STRING)\n self.v5_struct = struct.Struct(V5_STRUCT_STRING)\n self.v4_struct = struct.Struct(V4_STRUCT_STRING)\n self.v3_struct = struct.Struct(V3_STRUCT_STRING)","def __init__(self, dim, connections_per_row=3):\n _table.STable_swiginit(self, _table.new_STable(dim, connections_per_row))","def __init__(self, flowchart=None, extension=None):\n logger.debug(\"Creating Table {}\".format(self))\n\n # Initialize our parent class\n super().__init__(\n flowchart=flowchart, title=\"Table\", extension=extension, logger=logger\n )\n\n # This needs to be after initializing subclasses...\n self.parameters = table_step.TableParameters()\n self.calls = 0","def report_status_init(self):\n self._update_sandesh_status(ConnectionStatus.INIT)","def _TableSetup(self):\n global _tablesetup\n global singlestarLocation\n if not _tablesetup:\n singlestar.star_setup(singlestarLocation)\n _tablesetup = True","def __init__(self):\n\n self._dict = OrderedDict(zip(const.BFHCOLS, [0] * 111))","def _initMatchTable(self):\n\n t = self.tableWidget_matched # shorthand notation\n\n ### Header population & properties\n\n t.setHorizontalHeaderLabels(self.data.col_name_list)\n\n t.horizontalHeader().setMovable(True)","def __init__(self):\n self.stats = {}\n self.stats['hits'] = 0\n self.stats['operations'] = {}\n self.stats['operations']['GetCapabilities'] = {}\n self.stats['operations']['GetCapabilities']['hits'] = 0\n self.stats['operations']['POST'] = {}\n self.stats['operations']['POST']['hits'] = 0","def __init__(self, tableFilename):\n self.h5file = h5py.File(tableFilename, 'r')\n self.tableShape = numpy.shape(self.h5file['logpress'])\n self.energy_shift = self.h5file['energy_shift'][0]\n #print self.energy_shift\n #Determine the ordering of independent variable axes by identifying with\n # the number of points for that indVar axis\n newOrdering = [None for _ in self.indVars]\n for indVar in self.indVars:\n key = 'points' + indVar.split('log')[-1]\n points = self.h5file[key][0]\n for ithAxis, ithAxesPoints in enumerate(self.tableShape):\n if ithAxesPoints == points:\n newOrdering[ithAxis] = indVar\n break\n self.indVars = tuple(newOrdering)\n self.tableShapeDict = dict([(indVar, self.tableShape[i])\n for i, indVar in enumerate(self.indVars)])","def initialize(self):\n\n cursor = self.conn.cursor()\n\n # This table can be used as a parent for a collection of runs\n cursor.execute(\n \"\"\"CREATE TABLE IF NOT EXISTS RunCollections (\n id INT AUTO_INCREMENT PRIMARY KEY,\n name VARCHAR(14) UNIQUE\n );\"\"\"\n )\n\n # This table holds in which run each appears.\n cursor.execute(\n \"\"\"CREATE TABLE IF NOT EXISTS Runs (\n id INT AUTO_INCREMENT PRIMARY KEY,\n name VARCHAR(14) UNIQUE,\n collection_id INT,\n FOREIGN KEY (collection_id) REFERENCES RunCollections (id) ON DELETE CASCADE);\"\"\"\n )\n\n # This table holds resources, which can be in multiple runs and have multiple varieties\n cursor.execute(\n \"\"\"CREATE TABLE IF NOT EXISTS Resources (\n id INT AUTO_INCREMENT PRIMARY KEY, \n extension VARCHAR(20), \n webpage VARCHAR(30),\n run_id INT NOT NULL,\n FOREIGN KEY (run_id) REFERENCES Runs (id) ON DELETE CASCADE);\"\"\"\n )\n\n cursor.execute(\n 'SELECT Table_name FROM information_schema.tables WHERE table_schema = \"vpntfg0\" AND Table_name LIKE \"%Varieties_%\" ORDER BY Table_name'\n )\n for row in cursor.fetchall():\n self.variety_tables.append(row[0])\n\n cursor.close()\n _logger.info(\"Variety tables are: %s\" % self.variety_tables)\n\n _logger.info(\"Database initialized\")","def initAttributes(self):\n CCSDS.DU.DataUnit.initAttributes(self)\n self.dataFieldHeaderFlag = 0\n self.setPacketLength()","def __init__(self, py_dict=None):\n super(EventThresholdsSchema, self).__init__()\n self.set_data_type(\"xml\")\n self.cpu = CpuSchema()\n self.memory = MemorySchema()\n self.connectionsPerSecond = CpsSchema()\n\n\n if py_dict is not None:\n self.get_object_from_py_dict(py_dict)","def __init__(self):\n with open(\"sat.json\", \"r\") as infile:\n self._sat = json.load(infile)[\"data\"]\n #Define the headers for the csv\n self._headers = [\"DBN\", \"School Name\", \"Number of Test Takers\", \"Critical Reading Mean\", \"Mathematics Mean\", \"Writing Mean\"]","def __init__(self, table_capacity=101, hash_base=31):\n\n self.table_capacity = table_capacity\n self.hash_base = hash_base\n self.array = [None] * self.table_capacity # Array initialized with 'None\" in each element.\n self.count = 0 # the number of items in the table, initially set to '0'\n self.rehash_count = 0\n self.probe_array = []","def initialize(self):\r\n if not self.context:\r\n self.context = SQLContext(self.url, self.connection, self.schema)\r\n if self.table is None:\r\n self.table = self.context.table(self.table_name)\r\n if not self.fields:\r\n self.read_fields()\r\n self.field_names = self.fields.names()","def __initStats(self):\n players = self.teamparser.getPlayers()\n try:\n stats = players[(self.team, self.position)]\n except KeyError, err:\n stats = (0, 0, 0, 0, 0, 0)\n raise TypeError, \"Invalid Team/Position: \" + self.team\n self.max = int(stats[0]) #maximum\n self.ma = int(stats[1]) #movement\n self.st = int(stats[2]) #strength\n self.ag = int(stats[3]) #agility\n self.av = int(stats[4]) #armor value\n self.costs = int(stats[5]) #costs\n self.injury = 0 #injury\n self.ssp = 0 #starplayerpoints\n self.touchdowns = 0 #touchdown\n self.completions = 0 #completions\n self.interceptions = 0 #interceptions\n self.casualties = 0 #casualties\n self.mvpawards = 0 #most valuable player awards","def initialize_statistics_collection(self):\n # Create statistics collector for testing.\n self.testing_stat_col = StatisticsCollector()\n self.add_statistics(self.testing_stat_col)\n self.problem.add_statistics(self.testing_stat_col)\n self.model.add_statistics(self.testing_stat_col)\n # Create the csv file to store the testing statistics.\n self.testing_batch_stats_file = self.testing_stat_col.initialize_csv_file(self.log_dir, 'testing_statistics.csv')\n\n # Create statistics aggregator for testing.\n self.testing_stat_agg = StatisticsAggregator()\n self.add_aggregators(self.testing_stat_agg)\n self.problem.add_aggregators(self.testing_stat_agg)\n self.model.add_aggregators(self.testing_stat_agg)\n # Create the csv file to store the testing statistic aggregations.\n # Will contain a single row with aggregated statistics.\n self.testing_set_stats_file = self.testing_stat_agg.initialize_csv_file(self.log_dir, 'testing_set_agg_statistics.csv')","def init(self):\n\t\t# Event list: time\n\t\tself.event_lst = [0, float('inf')]\n\t\t# Rate list of each edge edge->(time->rate)\n\t\t# \tRate here is the residual capacity\n\t\t#\tEnsure that there is one initial timestamp with full capacity and one infinite timestamp with no capacity\n\t\tself.rate_lst = {e:{0:self.topo.topo[e[0]][e[1]]['Capacity'], float('inf'):0} for e in self.topo.edges}","def __init__(self, *args):\n _snap.TTableContext_swiginit(self, _snap.new_TTableContext(*args))","def initTable(self):\n sql = \"\"\" ( nodeId integer PRIMARY KEY,\n nextId integer,\n childId integer,\n label text);\n \"\"\"\n self.db.createTable(self.tableName + sql)\n # Reserve the first record as the head pointer, if it's not there\n found = self.db.selectById(self.tableName, 1)\n if not found:\n record = dict(nextId=None, childId=None, label='head pointer')\n self.db.insert(self.tableName, record)","def __init__(self):\n OWSReport.__init__(self)\n self.stats['type'] = 'OGC:WFS'\n self.stats['operations']['GetFeature'] = {}\n self.stats['operations']['GetFeature']['hits'] = 0\n self.stats['operations']['GetFeature']['resource'] = {}\n self.stats['operations']['GetFeature']['resource']['param'] = 'typename'\n self.stats['operations']['GetFeature']['resource']['list'] = {}\n self.stats['operations']['DescribeFeatureType'] = {}\n self.stats['operations']['DescribeFeatureType']['hits'] = 0","def parse_migration_tables(self, tabels_schema: MigrationTablesSchema):\n try:\n self.source_table = tabels_schema.migrationTable.SourceTable.dict()\n self.destination_table = tabels_schema.migrationTable.DestinationTable.dict()\n self.columns = tabels_schema.migrationTable.MigrationColumns\n except Exception as err:\n logger.error(\"parse_migration_tables [error] -> %s\" % err)","def set_schema():\n schema = StructType([\n StructField(\"cicid\",DoubleType(),True),\n StructField(\"arrdate\",DoubleType(),True),\n StructField(\"i94cit\",DoubleType(),True),\n StructField(\"i94res\",DoubleType(),True),\n StructField(\"i94port\",StringType(),True),\n StructField(\"i94mode\",DoubleType(),True),\n StructField(\"i94addr\",StringType(),True),\n StructField(\"depdate\",DoubleType(),True), \n StructField(\"i94bir\",DoubleType(),True),\n StructField(\"i94visa\",DoubleType(),True),\n StructField(\"gender\",StringType(),True),\n StructField(\"airline\",StringType(),True),\n StructField(\"visatype\",StringType(),True)])\n return schema","def init():\n try:\n database.CONN\n except Exception:\n database.init()\n print('Database connection established.')\n inputtools.init()\n outputtools.init()\n\n global _CONN\n global _NAME\n global _TEMP_NAME\n global _SIMPLECOUNT_COLUMNS\n global _UCR_INDICATOR_DICT\n \n _CONN = database.CONN\n _NAME = 'SimpleCount'\n _TEMP_NAME = f'Temp{_NAME}' \n _SIMPLECOUNT_COLUMNS = ['fk_simplecount_indicator', 'fk_simplecount_county', 'year', 'value']\n _UCR_INDICATOR_DICT = {\n 'domestic':1100,\n 'school':1120,\n 'hate':1130,\n 'acca': 1400,\n 'acsa':1401,\n 'ahsna':1402,\n 'adpa':1403,\n 'ameth':1404,\n 'ch':1410,\n 'rape':1411,\n 'rob':1412,\n 'aggba':1413,\n 'ach':1414,\n 'arape':1415,\n 'arob':1416,\n 'aaggba':1417,\n 'theft':1420,\n 'burg':1421,\n 'mvt':1422,\n 'arson':1423,\n 'atheft':1424,\n 'aburg':1425,\n 'amvt':1426,\n 'aarson':1427,\n 'htsex':1430,\n 'htserve':1431,\n 'ahtsex':1440,\n 'ahtserve':1441,\n }","def __init__(self):\n\n self.table = []","def __init__ (self):\n self.lengths = {}\n self.lower_counts = {}\n self.upper_counts = {}\n self.digit_counts = {}\n self.symbol_counts = {}\n self.class_counts = {}\n self.word_counts = {}","def initialize(self):\n self.initialize_edges()\n self.initialize_prob()\n self.initialize_total_input_dict()\n\n self.initialize_fpmusigv_dict()","def initialize(self):\n self.tree = ROOT.TTree('tree', 'tree')\n self.simhitcount = []\n self.simhitarrays = np.array(self.simhitcount, dtype=np.int32)\n self.digitcount = []","def __init__(self):\n self.table = []","def startup(self):\n self.load_up_initial_db(TIMESTAMP_PARSE_DICT)\n self.add_numeric_cols()","def __init__(self, nrows):\n _table.DSTable_swiginit(self, _table.new_DSTable(nrows))","def init_tables(self) -> None:\n with self.table_access_condition:\n conn = self._get_connection()\n conn.execute(\"PRAGMA foreign_keys = 1\")\n c = conn.cursor()\n c.execute(tables.CREATE_STUDIES_TABLE)\n c.execute(tables.CREATE_SUBMISSIONS_TABLE)\n c.execute(tables.CREATE_REQUESTERS_TABLE)\n c.execute(tables.CREATE_UNITS_TABLE)\n c.execute(tables.CREATE_WORKERS_TABLE)\n c.execute(tables.CREATE_RUNS_TABLE)\n c.execute(tables.CREATE_RUN_MAP_TABLE)\n c.execute(tables.CREATE_PARTICIPANT_GROUPS_TABLE)\n c.execute(tables.CREATE_PARTICIPANT_GROUP_QUALIFICATIONS_MAPPING_TABLE)\n conn.commit()","def __init__(self, tablename):\n dynamodb = boto3.resource(\"dynamodb\")\n self._table = dynamodb.Table(table_name)\n super().__init__()","def create_table(self):\n pass","def __init__(self):\n\n self.tableConnString = os.environ['ENTITYTABLE_CONNECTIONSTRING'];\n self.__table = None","def __init__(self, schema):\n super().__init__(schema)\n hcs_cust = Customer.objects.filter(schema_name=schema).first()\n self._ebs_acct_num = hcs_cust.account_id\n self._org_id = hcs_cust.org_id","def reset_metric_stats(self):\n\n self.__stats_table = {}","def columns_setup(self):\n self.required = None\n self.addition = None\n self.deletion = None\n self.retention = None\n self.rename = None","def init_services(self):\n self.servicesTableWidget.clear()\n\n self.servicesTableWidget.setColumnCount(6)\n self.servicesTableWidget.setHorizontalHeaderLabels(['Title', 'Description',\n 'Created', 'Display', 'Information', 'Delete'])\n\n header = self.servicesTableWidget.horizontalHeader()\n self.servicesTableWidget.setSortingEnabled(True)\n header.setSectionResizeMode(0, QtWidgets.QHeaderView.Stretch)\n header.setSectionResizeMode(1, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(2, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(3, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(4, QtWidgets.QHeaderView.ResizeToContents)\n header.setSectionResizeMode(5, QtWidgets.QHeaderView.ResizeToContents)","def start_table(self):\n self.col_widths = []\n self.result = \"\"","def reset_metric_stats(self):\n self.__stats_table = {}","def from_schema(cls, sdict):\n\n table_schema = TableSchema()\n for name, dschema in sdict.items():\n\n schema = ColumnSchema(name=name, **dschema)\n table_schema.add_column(schema)\n\n return table_schema","def __init__(self):\n OWSReport.__init__(self)\n self.stats['type'] = 'OGC:SOS'\n self.stats['operations']['GetObservation'] = {}\n self.stats['operations']['GetObservation']['hits'] = 0\n self.stats['operations']['GetObservation']['resource'] = {}\n self.stats['operations']['GetObservation']['resource']['param'] = 'observedproperty'\n self.stats['operations']['GetObservation']['resource']['list'] = {}\n self.stats['operations']['DescribeSensor'] = {}\n self.stats['operations']['DescribeSensor']['hits'] = 0","def init_analysis_tables(self):\n cur = self.sql.cursor()\n cur.execute(\"PRAGMA foreign_keys = on\")\n cur.execute('''\n CREATE TABLE report_index (\n report_id INTEGER PRIMARY KEY AUTOINCREMENT,\n report_hash TEXT NOT NULL,\n device TEXT NOT NULL,\n timestamp INTEGER NOT NULL)''')\n cur.execute('''\n CREATE TABLE report_detail (\n route_id INTEGER PRIMARY KEY AUTOINCREMENT,\n report_hash TEXT NOT NULL,\n invalid TEXT NOT NULL,\n status TEXT NOT NULL,\n pfx TEXT NOT NULL,\n pfxlen TEXT NOT NULL,\n pfxstr_min TEXT NOT NULL,\n pfxstr_max TEXT NOT NULL,\n nexthop TEXT NOT NULL,\n metric TEXT NOT NULL,\n locpref TEXT NOT NULL,\n weight TEXT NOT NULL,\n pathbutone TEXT NOT NULL,\n orig_asn TEXT NOT NULL,\n route_orig TEXT NOT NULL)''')\n cur.execute('''\n CREATE TABLE fconstraints (\n fcons_id INTEGER PRIMARY KEY AUTOINCREMENT,\n route_id TEXT NOT NULL\n REFERENCES report_detail(route_id),\n host TEXT NOT NULL,\n port TEXT NOT NULL,\n asn TEXT NOT NULL,\n prefix TEXT NOT NULL,\n prefixlen INTEGER NOT NULL,\n max_prefixlen INTEGER NOT NULL)''')\n self.sql.commit()","def __init__(self, tableConnString):\n\n self.tableConnString = tableConnString;\n self.__table = None","def visit_table(self, node: docutils.nodes.reference) -> None:\n self.entry = {}\n self.header = {}","def _set_init(self):\n ## Main information\n self.idxs = None\n self.sp_relative_pos = None\n ## Auxiliar information\n self.ks = None\n self.iss = [0]\n ## Class structural information\n self._setted = False\n self._constant_rel_pos = False\n self.staticneighs = None\n self.staticneighs_set = None","def __init__(self, py_dict=None):\n super(StateDetailsSchema, self).__init__()\n self.sub_system_address = None\n self.sub_system_id = None\n self.state = None\n self.failure_message = None\n\n if py_dict is not None:\n self.get_object_from_py_dict(py_dict)","def __init__(\n self,\n table: \"Table\",\n use_header: bool = True,\n template: Optional[Template] = None,\n escape: bool = True,\n ):\n self.table = table\n self.escape = escape\n self.use_header = use_header\n self.template = self.get_template()\n self.context = self.get_context(table, self.use_header)","def __create_table(self):\n\n self.connection = self.db.connect()\n self.metadata = MetaData(self.connection)\n\n self.system = Table(self.table_name, self.metadata,\n Column('timestamp', DateTime(), primary_key=True, nullable=False),\n Column('vibration_sensor', Float()),\n Column('flow', Float()),\n Column('pressure', Float()),\n Column('power_consumption', Float()),\n Column('failure_times', Float()),\n Column('operational', Boolean())\n )\n\n self.metadata.create_all()","def __init__(self, py_dict=None):\n super(RuntimeNicInfoSchema, self).__init__()\n self.set_data_type('xml')\n self.index = None\n self.label = None\n self.network = NetworkSchema()\n\n if py_dict is not None:\n self.get_object_from_py_dict(py_dict)","def __init__(self, conn):\n self._table_name = \"search_history\"\n self._conn = conn\n self._cursor = conn.cursor()\n\n self._initialize()","def __init__(self, container_type, datasource=sybase.NULL_SOURCE):\n super(sytable, self).__init__(container_type,\n datasource or sybase.NULL_SOURCE)\n columns = datasource.columns()\n self._name = datasource.read_name()\n self._attributes = datasource.read_table_attributes() or {}\n self._number_of_rows = datasource.number_of_rows()\n self._columns = OrderedDict(\n (column, _column_factory(datasource, column, self._number_of_rows))\n for column in columns)\n\n self._column_attributes = dict.fromkeys(columns)\n self._dirty = False","def __init__(self):\n self.buckets = 1009\n self.table = [[] for _ in range(self.buckets)]","def __init__(self):\n # Initialise a dictionary to store arbitrary\n # attributes taken from the program logfile\n self.__dict = {}\n # List of tables\n self.__tables = []\n # List of keytexts\n self.__keytexts = []\n # For fragment retrieval\n self.set_source_file(\"\")\n self.set_startline(-1)\n self.set_endline(-1)\n # Flags\n self.__nonzero = False","def _prepare_stats_table(self, pinfos):\n\n stats_tbl = OrderedDict()\n stats_tbl[\"Title\"] = OrderedDict()\n for res in self.rsts:\n stats_tbl[res.reportid] = OrderedDict()\n\n for pinfo in pinfos:\n for colname in (pinfo[\"colname\"], pinfo[\"xcolname\"]):\n if colname in stats_tbl[\"Title\"]:\n continue\n\n # Each column name is represented by a row in the statistics table. Fill the \"Title\"\n # column.\n title_dict = stats_tbl[\"Title\"][colname] = OrderedDict()\n defs = self._refdefs.info[colname]\n\n if defs.get(\"unit\") == \"nanosecond\":\n # Convert nanoseconds to microseconds.\n unit = \"us\"\n else:\n unit = defs.get(\"short_unit\", \"\")\n\n title_dict[\"colname\"] = colname\n if unit:\n title_dict[\"colname\"] += f\", {unit}\"\n title_dict[\"coldescr\"] = defs[\"descr\"]\n\n title_dict[\"funcs\"] = OrderedDict()\n for funcname in self._stats_funcs:\n if funcname in self.rsts[0].cstats[colname]:\n title_dict[\"funcs\"][funcname] = RORawResult.get_stat_func_descr(funcname)\n\n # Now fill the values for each result.\n for res in self.rsts:\n res_dict = stats_tbl[res.reportid][colname] = OrderedDict()\n res_dict[\"funcs\"] = OrderedDict()\n\n for funcname in title_dict[\"funcs\"]:\n val = res.cstats[colname][funcname]\n fmt = \"{}\"\n if defs.get(\"unit\") == \"nanosecond\" and \"index\" not in funcname:\n val /= 1000\n fmt = \"{:.2f}\"\n if defs[\"type\"] == \"float\":\n fmt = \"{:.2f}\"\n\n fdict = res_dict[\"funcs\"][funcname] = OrderedDict()\n fdict[\"val\"] = fmt.format(val)\n fdict[\"raw_val\"] = val\n\n if self._refres.reportid == res.reportid:\n fdict[\"hovertext\"] = \"This is the reference result, other results \" \\\n \"are compared to this one.\"\n continue\n\n ref_fdict = stats_tbl[self._refres.reportid][colname][\"funcs\"][funcname]\n change = val - ref_fdict[\"raw_val\"]\n if ref_fdict[\"raw_val\"]:\n percent = (change / ref_fdict[\"raw_val\"]) * 100\n else:\n percent = change\n change = fmt.format(change) + unit\n percent = \"{:.1f}%\".format(percent)\n fdict[\"hovertext\"] = f\"Change: {change} ({percent})\"\n\n return stats_tbl","def get_stats(self):\n self.stats = self.soup.find('table', id='statsTable')","def get_table_info(self):\n epsg = None\n meta = MetaData()\n table_obj = Table(self.table, meta,\n autoload=True, autoload_with=self.engine)\n if not self.columns:\n self.columns = table_obj.columns.keys()\n geo_cols = [(col.name, col.type) for col in table_obj.columns\n if hasattr(col.type, 'srid')]\n if geo_cols:\n geo_col = geo_cols[0]\n self.geom_column = geo_col[0]\n geo_obj = geo_col[1]\n if self.geom_column not in self.columns:\n self.columns.append(self.geom_column)\n if hasattr(geo_obj, 'srid'):\n epsg = geo_obj.srid\n if epsg == -1:\n epsg = 4326\n if hasattr(geo_obj, 'geometry_type'):\n self.geometry_type = geo_obj.geometry_type\n\n self.epsg = epsg\n self.table_obj = table_obj\n self.meta = meta","def _initialize(self, chain, length):\n # If the table already exists, exit now.\n if chain != 0:\n return\n\n # Determine size\n try:\n size = len(self._getfunc())\n except TypeError:\n size = 1\n\n query = \"create table %s (recid INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT, trace int(5), %s FLOAT)\" % (self.name, ' FLOAT, '.join(['v%s' % (x+1) for x in range(size)]))\n self.db.cur.execute(query)","def __init__(self):\r\n # sample ID -> (ref individual count,\r\n # {size -> (estimate, std err, ci_low, ci_high)})\r\n self._data = {}","def __init__(self, schema_row):\n self.schema = []\n for field in schema_row['fields']:\n self.schema.append(field['type'])","def _make_tex_table(self, tabletitle):\r\n stattable = (\r\n r\"\"\"\r\n \\begin{table}[h!]\r\n \\caption{%s}\r\n \\centering\r\n \\begin{tabular}{l l l l l}\r\n \\toprule\r\n \\textbf{Statistic} & \\textbf{Inlet} & \\textbf{Outlet} \\\\\"\"\"\r\n % tabletitle\r\n )\r\n\r\n stats = [\r\n {\"name\": \"Count\", \"attribute\": \"N\", \"rule\": \"top\", \"forceint\": True},\r\n {\"name\": \"Number of NDs\", \"attribute\": \"ND\", \"forceint\": True},\r\n {\"name\": \"Min; Max\", \"attribute\": [\"min\", \"max\"], \"twoval\": True},\r\n {\"name\": \"Mean\", \"attribute\": \"mean\"},\r\n {\r\n \"name\": \"(95\\% confidence interval)\",\r\n \"attribute\": \"mean_conf_interval\",\r\n \"twoval\": True,\r\n \"ci\": True,\r\n \"rule\": \"none\",\r\n },\r\n {\"name\": \"Standard Deviation\", \"attribute\": \"std\"},\r\n {\"name\": \"Log. Mean\", \"attribute\": \"logmean\"},\r\n {\r\n \"name\": \"(95\\% confidence interval)\",\r\n \"attribute\": \"logmean_conf_interval\",\r\n \"twoval\": True,\r\n \"ci\": True,\r\n \"rule\": \"none\",\r\n },\r\n {\"name\": \"Log. Standard Deviation\", \"attribute\": \"logstd\"},\r\n {\"name\": \"Geo. Mean\", \"attribute\": \"geomean\"},\r\n {\r\n \"name\": \"(95\\% confidence interval)\",\r\n \"attribute\": \"geomean_conf_interval\",\r\n \"twoval\": True,\r\n \"ci\": True,\r\n \"rule\": \"none\",\r\n },\r\n {\"name\": \"Coeff. of Variation\", \"attribute\": \"cov\"},\r\n {\"name\": \"Skewness\", \"attribute\": \"skew\"},\r\n {\"name\": \"Median\", \"attribute\": \"median\"},\r\n {\r\n \"name\": \"(95\\% confidence interval)\",\r\n \"attribute\": \"median_conf_interval\",\r\n \"twoval\": True,\r\n \"ci\": True,\r\n \"rule\": \"none\",\r\n },\r\n {\"name\": \"Quartiles\", \"attribute\": [\"pctl25\", \"pctl75\"], \"twoval\": True},\r\n {\r\n \"name\": \"Number of Pairs\",\r\n \"attribute\": \"n_pairs\",\r\n \"rule\": \"top\",\r\n \"fromdataset\": True,\r\n \"sigfigs\": 1,\r\n \"forceint\": True,\r\n },\r\n {\r\n \"name\": \"Wilcoxon p-value\",\r\n \"attribute\": \"wilcoxon_p\",\r\n \"fromdataset\": True,\r\n \"pval\": True,\r\n \"tex\": True,\r\n },\r\n {\r\n \"name\": \"Mann-Whitney p-value\",\r\n \"attribute\": \"mannwhitney_p\",\r\n \"fromdataset\": True,\r\n \"pval\": True,\r\n \"tex\": True,\r\n },\r\n ]\r\n for s in stats:\r\n stattable += self._tex_table_row(**s)\r\n\r\n stattable += r\"\"\"\r\n \\bottomrule\r\n \\end{tabular}\r\n \\end{table}\"\"\"\r\n\r\n return stattable + \"\\n\"","def speed_table_create(self):\n\n self.__table_create(Speed)","def _generateTable(self, obj, **args):\n\n if self._script.utilities.isLayoutOnly(obj):\n return []\n\n try:\n table = obj.queryTable()\n except:\n return []\n\n return [messages.tableSize(table.nRows, table.nColumns)]","def init_statsd():\n statsd.init_statsd({\n 'STATSD_HOST': config.secrets.server('statsd.host'),\n 'STATSD_PORT': config.secrets.server('statsd.port'),\n 'STATSD_BUCKET_PREFIX': 'linkr',\n })","def __init__(self, tabletext=\"\"):\n\n # Table attributes\n self.__title = \"\"\n self.__type = \"GRAPHS\" # Default to GRAPHS\n self.__graphs = \"\"\n self.__columns = \"\"\n self.__text = \"\"\n self.__data = \"\"\n # Derived data\n self.__graph_list = []\n self.__column_list = []\n # Indicate the the object has been populated\n self.__table_parse_error = False\n self.__nonzero = False\n # The \"raw\" table data from the log file\n self.__rawtable = \"\"\n # Attempt to populate the table\n if tabletext:\n self.__rawtable = tabletext\n if not self.__buildtable(tabletext):\n # Failed to extract table\n # If it could be a title then use this\n # instead\n if str(tabletext).count(\"\\n\") == 0:\n self.settitle(tabletext)","def set_up_tables(self):\n tables = []\n tables.append({'groupname': 'metadata',\n 'tablename': 'sim_info',\n 'description': desc.SimInfoRow,\n 'tabletitle': 'Simulation Information'})\n tables.append({'groupname': 'metadata',\n 'tablename': 'sim_timeseries',\n 'description': desc.SimTimeseriesRow,\n 'tabletitle': 'Simulation Power Data'})\n tables.append({'groupname': 'th',\n 'tablename': 'th_params',\n 'description': desc.ThMetadataRow,\n 'tabletitle': 'TH Component Parameters'})\n tables.append({'groupname': 'th',\n 'tablename': 'th_timeseries',\n 'description': desc.ThTimeseriesRow,\n 'tabletitle': 'TH Timeseries'})\n tables.append({'groupname': 'neutronics',\n 'tablename': 'neutronics_timeseries',\n 'description': desc.NeutronicsTimeseriesRow,\n 'tabletitle': 'Neutronics Timeseries'})\n tables.append({'groupname': 'neutronics',\n 'tablename': 'neutronics_params',\n 'description': desc.NeutronicsParamsRow,\n 'tabletitle': 'Neutronics Metadata'})\n tables.append({'groupname': 'neutronics',\n 'tablename': 'zetas',\n 'description': desc.ZetasTimestepRow,\n 'tabletitle': 'Neutron Precursor Concentrations'})\n tables.append({'groupname': 'neutronics',\n 'tablename': 'omegas',\n 'description': desc.OmegasTimestepRow,\n 'tabletitle': 'Decay Heat Fractions'})\n return tables","def init():\n database.create_tables([Tracker])\n database.commit()","def __init__(self, table_name='casbin_rule', **kwargs):\n self.table_name = table_name\n self.dynamodb = boto3.client('dynamodb', **kwargs)\n try:\n\n self.dynamodb.create_table(\n TableName=self.table_name,\n\n AttributeDefinitions=[\n {\n 'AttributeName': 'id',\n 'AttributeType': 'S'\n }\n ],\n KeySchema=[\n {\n 'AttributeName': 'id',\n 'KeyType': 'HASH'\n },\n ],\n ProvisionedThroughput={\n 'ReadCapacityUnits': 10,\n 'WriteCapacityUnits': 10\n }\n )\n except self.dynamodb.exceptions.ResourceInUseException:\n pass"],"string":"[\n \"def InitStats(ss):\\n\\n ss.SumSSE = 0\\n ss.SumAvgSSE = 0\\n ss.SumCosDiff = 0\\n ss.SumErr = 0\\n ss.FirstZero = -1\\n ss.NZero = 0\\n\\n ss.TrlErr = 0\\n ss.TrlSSE = 0\\n ss.TrlAvgSSE = 0\\n ss.EpcSSE = 0\\n ss.EpcAvgSSE = 0\\n ss.EpcPctErr = 0\\n ss.EpcCosDiff = 0\",\n \"def _init_table(self, table: \\\"Table\\\"):\\n if not self.columns:\\n self.columns = table.columns\\n self._data = table.data\",\n \"def __init__(self):\\n _snap.TTableRow_swiginit(self, _snap.new_TTableRow())\",\n \"def __init__(self, schema=None):\\n self._dict = {}\\n self.schema = schema\",\n \"def __init__(self, *args):\\n _snap.TTable_swiginit(self, _snap.new_TTable(*args))\",\n \"def _setup_stats(self) -> None:\\n\\n # Save statistics\\n self.mass = np.array([0])\\n self.mass_balance = np.array([0])\\n self.mass_balance_trend = np.array([0])\",\n \"def __init__(self, *args):\\n _table.Table_swiginit(self, _table.new_Table(*args))\",\n \"def __init__(self, metrics, schema, table, nid):\\n\\n self.id = nid\\n self.metrics = metrics\\n self.schema = schema\\n self.table = table\\n self.batch_size = 20\\n self.__init_metrics()\",\n \"def __init__(self):\\n self.table = {}\",\n \"def _initialize_table(self):\\n self.table = gtk.Table()\\n self.table.set_col_spacings(8)\\n self.table.set_row_spacings(3)\\n self.window.add(self.table)\\n self._view_schedule()\\n self.table.show()\",\n \"def setup(self):\\n self.table = prettytable.PrettyTable()\\n self.table.field_names = self.titles\\n if self.convert_columns:\\n self.rows = self.convert_columns_to_rows(self.rows)\\n if self.colour:\\n self.colour = self.convert_columns_to_rows(self.colour)\",\n \"def __init__(self, schema=None):\\n self.schema = schema or {}\",\n \"def __init__(self):\\n self.buckets = 1009\\n self.table = [{} for _ in range(self.buckets)]\",\n \"def __init__(self, *args):\\n _snap.Schema_swiginit(self, _snap.new_Schema(*args))\",\n \"def __init__(self):\\n super(ObjectSchema, self).__init__()\\n self.is_allow_undefined = False\",\n \"def __init__(self):\\n self.title = None\\n self.table = pd.DataFrame()\\n self.column_widths = None;\",\n \"def _init(self):\\n self._nfields = 0\\n self._converted = {}\\n self._heapoffset = 0\\n self._heapsize = 0\\n self._col_weakrefs = weakref.WeakSet()\\n self._coldefs = None\\n self._gap = 0\\n self._uint = False\",\n \"def setup_table(self):\\n\\n self.setup.create_basic_table_in_dev()\\n self.setup.insert_random_records_into_dev()\",\n \"def __init__(self, *args, **kwargs):\\n \\n self.dense = True\\n\\n # Create table\\n super().__init__(*args, **kwargs)\",\n \"def __init__(self, PTableV):\\n _snap.TTableIterator_swiginit(self, _snap.new_TTableIterator(PTableV))\",\n \"def init_blank(self, T):\\n self.headings = []\\n self.table = {}\\n self.rowcount = 0\\n for e in T.entries:\\n self.headings.append(e.name)\\n self.table[e.name] = []\",\n \"def process_table_init(self):\\n logging.debug(\\\"Processing table initialization, %d entries\\\",\\n len(self.table_initialization))\\n\\n for init_entry in self.table_initialization:\\n for table_name, entry_desc in init_entry.items():\\n self.air_table[table_name].add_entry(\\n table_entry.description_to_entry(entry_desc))\",\n \"def _initialise_sufficient_statistics(self):\\n stats = super()._initialise_sufficient_statistics()\\n\\n stats['B'] = {\\n 'numer': [\\n np.zeros((self.n_states, self.n_features[i]))\\n for i in range(self.n_emissions)\\n ],\\n 'denom': [\\n np.zeros((self.n_states, self.n_features[i]))\\n for i in range(self.n_emissions)\\n ],\\n }\\n\\n return stats\",\n \"def __init__(self, table_name, cursor=None, schema=None):\\n self.name = table_name\\n self.tablespace_name = None\\n self.table_type = None\\n self.columns = {}\\n self.indexes = {}\\n self.constraints = {}\\n self.triggers = {}\\n if schema:\\n self.schema = schema\\n else:\\n self.schema = None\\n if cursor:\\n self._get_table(cursor)\",\n \"def __init__(self):\\n self.table = {}\\n self.ls = []\",\n \"def setup_table(self):\\n self.interface.start_transaction()\\n self.interface.drop_table(_history_table)\\n self.interface.drop_table(_history_stats_table)\\n self.interface.create_table(_history_table)\\n self.interface.create_index('index1', _history_table, [_history_table['timestamp']])\\n self.interface.create_table(_history_stats_table)\\n self.interface.create_index('index2', _history_stats_table, [_history_stats_table['benchmark']])\\n self.interface.commit_transaction()\",\n \"def __init__(self, schema ):\\n self.schema = schema\",\n \"def _get_table_schema(self):\\n\\n return {\\n 'AttributeDefinitions': [\\n {\\n 'AttributeName': self._key_field.name,\\n 'AttributeType': self._key_field.data_type\\n }\\n ],\\n 'TableName': self.table_name,\\n 'KeySchema': [\\n {\\n 'AttributeName': self._key_field.name,\\n 'KeyType': 'HASH'\\n }\\n ],\\n 'ProvisionedThroughput': {\\n 'ReadCapacityUnits': self.read_capacity_units,\\n 'WriteCapacityUnits': self.write_capacity_units\\n }\\n }\",\n \"def _initialize(self):\\n query_table = self._cursor.execute(f\\\"\\\"\\\"\\n SELECT name\\n FROM sqlite_master\\n WHERE type='table' AND name='{self._table_name}';\\\"\\\"\\\")\\n\\n if not query_table.fetchone():\\n self._cursor.execute(f\\\"\\\"\\\"\\n CREATE TABLE {self._table_name} (\\n id char(36),\\n term TEXT,\\n timestamp BIGINT\\n );\\\"\\\"\\\")\\n\\n self._cursor.execute(f\\\"\\\"\\\"\\n CREATE INDEX index_timestamp\\n ON {self._table_name} (timestamp);\\\"\\\"\\\")\\n\\n self._conn.commit()\",\n \"def init_widget(self):\\n super(QtViewTable, self).init_widget()\\n d = self.declaration\\n self.set_table_model(d.table_model)\\n self.set_orientation(d.orientation)\",\n \"def __init__(self, DEBUG=False):\\n self.DEBUG = DEBUG\\n\\n self.classTable = {}\\n self.subroutineTable = {}\\n\\n self.counts = {}\\n self.counts[\\\"STATIC\\\"] = 0\\n self.counts[\\\"FIELD\\\"] = 0\\n self.counts[\\\"ARG\\\"] = 0\\n self.counts[\\\"VAR\\\"] = 0\\n\\n if self.DEBUG:\\n print(\\\"DEBUG(SymbolTable): INITIALIZED SYMBOL TABLES\\\")\",\n \"def init_structs(self):\\n self.v6_struct = struct.Struct(V6_STRUCT_STRING)\\n self.v5_struct = struct.Struct(V5_STRUCT_STRING)\\n self.v4_struct = struct.Struct(V4_STRUCT_STRING)\\n self.v3_struct = struct.Struct(V3_STRUCT_STRING)\",\n \"def __init__(self, dim, connections_per_row=3):\\n _table.STable_swiginit(self, _table.new_STable(dim, connections_per_row))\",\n \"def __init__(self, flowchart=None, extension=None):\\n logger.debug(\\\"Creating Table {}\\\".format(self))\\n\\n # Initialize our parent class\\n super().__init__(\\n flowchart=flowchart, title=\\\"Table\\\", extension=extension, logger=logger\\n )\\n\\n # This needs to be after initializing subclasses...\\n self.parameters = table_step.TableParameters()\\n self.calls = 0\",\n \"def report_status_init(self):\\n self._update_sandesh_status(ConnectionStatus.INIT)\",\n \"def _TableSetup(self):\\n global _tablesetup\\n global singlestarLocation\\n if not _tablesetup:\\n singlestar.star_setup(singlestarLocation)\\n _tablesetup = True\",\n \"def __init__(self):\\n\\n self._dict = OrderedDict(zip(const.BFHCOLS, [0] * 111))\",\n \"def _initMatchTable(self):\\n\\n t = self.tableWidget_matched # shorthand notation\\n\\n ### Header population & properties\\n\\n t.setHorizontalHeaderLabels(self.data.col_name_list)\\n\\n t.horizontalHeader().setMovable(True)\",\n \"def __init__(self):\\n self.stats = {}\\n self.stats['hits'] = 0\\n self.stats['operations'] = {}\\n self.stats['operations']['GetCapabilities'] = {}\\n self.stats['operations']['GetCapabilities']['hits'] = 0\\n self.stats['operations']['POST'] = {}\\n self.stats['operations']['POST']['hits'] = 0\",\n \"def __init__(self, tableFilename):\\n self.h5file = h5py.File(tableFilename, 'r')\\n self.tableShape = numpy.shape(self.h5file['logpress'])\\n self.energy_shift = self.h5file['energy_shift'][0]\\n #print self.energy_shift\\n #Determine the ordering of independent variable axes by identifying with\\n # the number of points for that indVar axis\\n newOrdering = [None for _ in self.indVars]\\n for indVar in self.indVars:\\n key = 'points' + indVar.split('log')[-1]\\n points = self.h5file[key][0]\\n for ithAxis, ithAxesPoints in enumerate(self.tableShape):\\n if ithAxesPoints == points:\\n newOrdering[ithAxis] = indVar\\n break\\n self.indVars = tuple(newOrdering)\\n self.tableShapeDict = dict([(indVar, self.tableShape[i])\\n for i, indVar in enumerate(self.indVars)])\",\n \"def initialize(self):\\n\\n cursor = self.conn.cursor()\\n\\n # This table can be used as a parent for a collection of runs\\n cursor.execute(\\n \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS RunCollections (\\n id INT AUTO_INCREMENT PRIMARY KEY,\\n name VARCHAR(14) UNIQUE\\n );\\\"\\\"\\\"\\n )\\n\\n # This table holds in which run each appears.\\n cursor.execute(\\n \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS Runs (\\n id INT AUTO_INCREMENT PRIMARY KEY,\\n name VARCHAR(14) UNIQUE,\\n collection_id INT,\\n FOREIGN KEY (collection_id) REFERENCES RunCollections (id) ON DELETE CASCADE);\\\"\\\"\\\"\\n )\\n\\n # This table holds resources, which can be in multiple runs and have multiple varieties\\n cursor.execute(\\n \\\"\\\"\\\"CREATE TABLE IF NOT EXISTS Resources (\\n id INT AUTO_INCREMENT PRIMARY KEY, \\n extension VARCHAR(20), \\n webpage VARCHAR(30),\\n run_id INT NOT NULL,\\n FOREIGN KEY (run_id) REFERENCES Runs (id) ON DELETE CASCADE);\\\"\\\"\\\"\\n )\\n\\n cursor.execute(\\n 'SELECT Table_name FROM information_schema.tables WHERE table_schema = \\\"vpntfg0\\\" AND Table_name LIKE \\\"%Varieties_%\\\" ORDER BY Table_name'\\n )\\n for row in cursor.fetchall():\\n self.variety_tables.append(row[0])\\n\\n cursor.close()\\n _logger.info(\\\"Variety tables are: %s\\\" % self.variety_tables)\\n\\n _logger.info(\\\"Database initialized\\\")\",\n \"def initAttributes(self):\\n CCSDS.DU.DataUnit.initAttributes(self)\\n self.dataFieldHeaderFlag = 0\\n self.setPacketLength()\",\n \"def __init__(self, py_dict=None):\\n super(EventThresholdsSchema, self).__init__()\\n self.set_data_type(\\\"xml\\\")\\n self.cpu = CpuSchema()\\n self.memory = MemorySchema()\\n self.connectionsPerSecond = CpsSchema()\\n\\n\\n if py_dict is not None:\\n self.get_object_from_py_dict(py_dict)\",\n \"def __init__(self):\\n with open(\\\"sat.json\\\", \\\"r\\\") as infile:\\n self._sat = json.load(infile)[\\\"data\\\"]\\n #Define the headers for the csv\\n self._headers = [\\\"DBN\\\", \\\"School Name\\\", \\\"Number of Test Takers\\\", \\\"Critical Reading Mean\\\", \\\"Mathematics Mean\\\", \\\"Writing Mean\\\"]\",\n \"def __init__(self, table_capacity=101, hash_base=31):\\n\\n self.table_capacity = table_capacity\\n self.hash_base = hash_base\\n self.array = [None] * self.table_capacity # Array initialized with 'None\\\" in each element.\\n self.count = 0 # the number of items in the table, initially set to '0'\\n self.rehash_count = 0\\n self.probe_array = []\",\n \"def initialize(self):\\r\\n if not self.context:\\r\\n self.context = SQLContext(self.url, self.connection, self.schema)\\r\\n if self.table is None:\\r\\n self.table = self.context.table(self.table_name)\\r\\n if not self.fields:\\r\\n self.read_fields()\\r\\n self.field_names = self.fields.names()\",\n \"def __initStats(self):\\n players = self.teamparser.getPlayers()\\n try:\\n stats = players[(self.team, self.position)]\\n except KeyError, err:\\n stats = (0, 0, 0, 0, 0, 0)\\n raise TypeError, \\\"Invalid Team/Position: \\\" + self.team\\n self.max = int(stats[0]) #maximum\\n self.ma = int(stats[1]) #movement\\n self.st = int(stats[2]) #strength\\n self.ag = int(stats[3]) #agility\\n self.av = int(stats[4]) #armor value\\n self.costs = int(stats[5]) #costs\\n self.injury = 0 #injury\\n self.ssp = 0 #starplayerpoints\\n self.touchdowns = 0 #touchdown\\n self.completions = 0 #completions\\n self.interceptions = 0 #interceptions\\n self.casualties = 0 #casualties\\n self.mvpawards = 0 #most valuable player awards\",\n \"def initialize_statistics_collection(self):\\n # Create statistics collector for testing.\\n self.testing_stat_col = StatisticsCollector()\\n self.add_statistics(self.testing_stat_col)\\n self.problem.add_statistics(self.testing_stat_col)\\n self.model.add_statistics(self.testing_stat_col)\\n # Create the csv file to store the testing statistics.\\n self.testing_batch_stats_file = self.testing_stat_col.initialize_csv_file(self.log_dir, 'testing_statistics.csv')\\n\\n # Create statistics aggregator for testing.\\n self.testing_stat_agg = StatisticsAggregator()\\n self.add_aggregators(self.testing_stat_agg)\\n self.problem.add_aggregators(self.testing_stat_agg)\\n self.model.add_aggregators(self.testing_stat_agg)\\n # Create the csv file to store the testing statistic aggregations.\\n # Will contain a single row with aggregated statistics.\\n self.testing_set_stats_file = self.testing_stat_agg.initialize_csv_file(self.log_dir, 'testing_set_agg_statistics.csv')\",\n \"def init(self):\\n\\t\\t# Event list: time\\n\\t\\tself.event_lst = [0, float('inf')]\\n\\t\\t# Rate list of each edge edge->(time->rate)\\n\\t\\t# \\tRate here is the residual capacity\\n\\t\\t#\\tEnsure that there is one initial timestamp with full capacity and one infinite timestamp with no capacity\\n\\t\\tself.rate_lst = {e:{0:self.topo.topo[e[0]][e[1]]['Capacity'], float('inf'):0} for e in self.topo.edges}\",\n \"def __init__(self, *args):\\n _snap.TTableContext_swiginit(self, _snap.new_TTableContext(*args))\",\n \"def initTable(self):\\n sql = \\\"\\\"\\\" ( nodeId integer PRIMARY KEY,\\n nextId integer,\\n childId integer,\\n label text);\\n \\\"\\\"\\\"\\n self.db.createTable(self.tableName + sql)\\n # Reserve the first record as the head pointer, if it's not there\\n found = self.db.selectById(self.tableName, 1)\\n if not found:\\n record = dict(nextId=None, childId=None, label='head pointer')\\n self.db.insert(self.tableName, record)\",\n \"def __init__(self):\\n OWSReport.__init__(self)\\n self.stats['type'] = 'OGC:WFS'\\n self.stats['operations']['GetFeature'] = {}\\n self.stats['operations']['GetFeature']['hits'] = 0\\n self.stats['operations']['GetFeature']['resource'] = {}\\n self.stats['operations']['GetFeature']['resource']['param'] = 'typename'\\n self.stats['operations']['GetFeature']['resource']['list'] = {}\\n self.stats['operations']['DescribeFeatureType'] = {}\\n self.stats['operations']['DescribeFeatureType']['hits'] = 0\",\n \"def parse_migration_tables(self, tabels_schema: MigrationTablesSchema):\\n try:\\n self.source_table = tabels_schema.migrationTable.SourceTable.dict()\\n self.destination_table = tabels_schema.migrationTable.DestinationTable.dict()\\n self.columns = tabels_schema.migrationTable.MigrationColumns\\n except Exception as err:\\n logger.error(\\\"parse_migration_tables [error] -> %s\\\" % err)\",\n \"def set_schema():\\n schema = StructType([\\n StructField(\\\"cicid\\\",DoubleType(),True),\\n StructField(\\\"arrdate\\\",DoubleType(),True),\\n StructField(\\\"i94cit\\\",DoubleType(),True),\\n StructField(\\\"i94res\\\",DoubleType(),True),\\n StructField(\\\"i94port\\\",StringType(),True),\\n StructField(\\\"i94mode\\\",DoubleType(),True),\\n StructField(\\\"i94addr\\\",StringType(),True),\\n StructField(\\\"depdate\\\",DoubleType(),True), \\n StructField(\\\"i94bir\\\",DoubleType(),True),\\n StructField(\\\"i94visa\\\",DoubleType(),True),\\n StructField(\\\"gender\\\",StringType(),True),\\n StructField(\\\"airline\\\",StringType(),True),\\n StructField(\\\"visatype\\\",StringType(),True)])\\n return schema\",\n \"def init():\\n try:\\n database.CONN\\n except Exception:\\n database.init()\\n print('Database connection established.')\\n inputtools.init()\\n outputtools.init()\\n\\n global _CONN\\n global _NAME\\n global _TEMP_NAME\\n global _SIMPLECOUNT_COLUMNS\\n global _UCR_INDICATOR_DICT\\n \\n _CONN = database.CONN\\n _NAME = 'SimpleCount'\\n _TEMP_NAME = f'Temp{_NAME}' \\n _SIMPLECOUNT_COLUMNS = ['fk_simplecount_indicator', 'fk_simplecount_county', 'year', 'value']\\n _UCR_INDICATOR_DICT = {\\n 'domestic':1100,\\n 'school':1120,\\n 'hate':1130,\\n 'acca': 1400,\\n 'acsa':1401,\\n 'ahsna':1402,\\n 'adpa':1403,\\n 'ameth':1404,\\n 'ch':1410,\\n 'rape':1411,\\n 'rob':1412,\\n 'aggba':1413,\\n 'ach':1414,\\n 'arape':1415,\\n 'arob':1416,\\n 'aaggba':1417,\\n 'theft':1420,\\n 'burg':1421,\\n 'mvt':1422,\\n 'arson':1423,\\n 'atheft':1424,\\n 'aburg':1425,\\n 'amvt':1426,\\n 'aarson':1427,\\n 'htsex':1430,\\n 'htserve':1431,\\n 'ahtsex':1440,\\n 'ahtserve':1441,\\n }\",\n \"def __init__(self):\\n\\n self.table = []\",\n \"def __init__ (self):\\n self.lengths = {}\\n self.lower_counts = {}\\n self.upper_counts = {}\\n self.digit_counts = {}\\n self.symbol_counts = {}\\n self.class_counts = {}\\n self.word_counts = {}\",\n \"def initialize(self):\\n self.initialize_edges()\\n self.initialize_prob()\\n self.initialize_total_input_dict()\\n\\n self.initialize_fpmusigv_dict()\",\n \"def initialize(self):\\n self.tree = ROOT.TTree('tree', 'tree')\\n self.simhitcount = []\\n self.simhitarrays = np.array(self.simhitcount, dtype=np.int32)\\n self.digitcount = []\",\n \"def __init__(self):\\n self.table = []\",\n \"def startup(self):\\n self.load_up_initial_db(TIMESTAMP_PARSE_DICT)\\n self.add_numeric_cols()\",\n \"def __init__(self, nrows):\\n _table.DSTable_swiginit(self, _table.new_DSTable(nrows))\",\n \"def init_tables(self) -> None:\\n with self.table_access_condition:\\n conn = self._get_connection()\\n conn.execute(\\\"PRAGMA foreign_keys = 1\\\")\\n c = conn.cursor()\\n c.execute(tables.CREATE_STUDIES_TABLE)\\n c.execute(tables.CREATE_SUBMISSIONS_TABLE)\\n c.execute(tables.CREATE_REQUESTERS_TABLE)\\n c.execute(tables.CREATE_UNITS_TABLE)\\n c.execute(tables.CREATE_WORKERS_TABLE)\\n c.execute(tables.CREATE_RUNS_TABLE)\\n c.execute(tables.CREATE_RUN_MAP_TABLE)\\n c.execute(tables.CREATE_PARTICIPANT_GROUPS_TABLE)\\n c.execute(tables.CREATE_PARTICIPANT_GROUP_QUALIFICATIONS_MAPPING_TABLE)\\n conn.commit()\",\n \"def __init__(self, tablename):\\n dynamodb = boto3.resource(\\\"dynamodb\\\")\\n self._table = dynamodb.Table(table_name)\\n super().__init__()\",\n \"def create_table(self):\\n pass\",\n \"def __init__(self):\\n\\n self.tableConnString = os.environ['ENTITYTABLE_CONNECTIONSTRING'];\\n self.__table = None\",\n \"def __init__(self, schema):\\n super().__init__(schema)\\n hcs_cust = Customer.objects.filter(schema_name=schema).first()\\n self._ebs_acct_num = hcs_cust.account_id\\n self._org_id = hcs_cust.org_id\",\n \"def reset_metric_stats(self):\\n\\n self.__stats_table = {}\",\n \"def columns_setup(self):\\n self.required = None\\n self.addition = None\\n self.deletion = None\\n self.retention = None\\n self.rename = None\",\n \"def init_services(self):\\n self.servicesTableWidget.clear()\\n\\n self.servicesTableWidget.setColumnCount(6)\\n self.servicesTableWidget.setHorizontalHeaderLabels(['Title', 'Description',\\n 'Created', 'Display', 'Information', 'Delete'])\\n\\n header = self.servicesTableWidget.horizontalHeader()\\n self.servicesTableWidget.setSortingEnabled(True)\\n header.setSectionResizeMode(0, QtWidgets.QHeaderView.Stretch)\\n header.setSectionResizeMode(1, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(2, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(3, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(4, QtWidgets.QHeaderView.ResizeToContents)\\n header.setSectionResizeMode(5, QtWidgets.QHeaderView.ResizeToContents)\",\n \"def start_table(self):\\n self.col_widths = []\\n self.result = \\\"\\\"\",\n \"def reset_metric_stats(self):\\n self.__stats_table = {}\",\n \"def from_schema(cls, sdict):\\n\\n table_schema = TableSchema()\\n for name, dschema in sdict.items():\\n\\n schema = ColumnSchema(name=name, **dschema)\\n table_schema.add_column(schema)\\n\\n return table_schema\",\n \"def __init__(self):\\n OWSReport.__init__(self)\\n self.stats['type'] = 'OGC:SOS'\\n self.stats['operations']['GetObservation'] = {}\\n self.stats['operations']['GetObservation']['hits'] = 0\\n self.stats['operations']['GetObservation']['resource'] = {}\\n self.stats['operations']['GetObservation']['resource']['param'] = 'observedproperty'\\n self.stats['operations']['GetObservation']['resource']['list'] = {}\\n self.stats['operations']['DescribeSensor'] = {}\\n self.stats['operations']['DescribeSensor']['hits'] = 0\",\n \"def init_analysis_tables(self):\\n cur = self.sql.cursor()\\n cur.execute(\\\"PRAGMA foreign_keys = on\\\")\\n cur.execute('''\\n CREATE TABLE report_index (\\n report_id INTEGER PRIMARY KEY AUTOINCREMENT,\\n report_hash TEXT NOT NULL,\\n device TEXT NOT NULL,\\n timestamp INTEGER NOT NULL)''')\\n cur.execute('''\\n CREATE TABLE report_detail (\\n route_id INTEGER PRIMARY KEY AUTOINCREMENT,\\n report_hash TEXT NOT NULL,\\n invalid TEXT NOT NULL,\\n status TEXT NOT NULL,\\n pfx TEXT NOT NULL,\\n pfxlen TEXT NOT NULL,\\n pfxstr_min TEXT NOT NULL,\\n pfxstr_max TEXT NOT NULL,\\n nexthop TEXT NOT NULL,\\n metric TEXT NOT NULL,\\n locpref TEXT NOT NULL,\\n weight TEXT NOT NULL,\\n pathbutone TEXT NOT NULL,\\n orig_asn TEXT NOT NULL,\\n route_orig TEXT NOT NULL)''')\\n cur.execute('''\\n CREATE TABLE fconstraints (\\n fcons_id INTEGER PRIMARY KEY AUTOINCREMENT,\\n route_id TEXT NOT NULL\\n REFERENCES report_detail(route_id),\\n host TEXT NOT NULL,\\n port TEXT NOT NULL,\\n asn TEXT NOT NULL,\\n prefix TEXT NOT NULL,\\n prefixlen INTEGER NOT NULL,\\n max_prefixlen INTEGER NOT NULL)''')\\n self.sql.commit()\",\n \"def __init__(self, tableConnString):\\n\\n self.tableConnString = tableConnString;\\n self.__table = None\",\n \"def visit_table(self, node: docutils.nodes.reference) -> None:\\n self.entry = {}\\n self.header = {}\",\n \"def _set_init(self):\\n ## Main information\\n self.idxs = None\\n self.sp_relative_pos = None\\n ## Auxiliar information\\n self.ks = None\\n self.iss = [0]\\n ## Class structural information\\n self._setted = False\\n self._constant_rel_pos = False\\n self.staticneighs = None\\n self.staticneighs_set = None\",\n \"def __init__(self, py_dict=None):\\n super(StateDetailsSchema, self).__init__()\\n self.sub_system_address = None\\n self.sub_system_id = None\\n self.state = None\\n self.failure_message = None\\n\\n if py_dict is not None:\\n self.get_object_from_py_dict(py_dict)\",\n \"def __init__(\\n self,\\n table: \\\"Table\\\",\\n use_header: bool = True,\\n template: Optional[Template] = None,\\n escape: bool = True,\\n ):\\n self.table = table\\n self.escape = escape\\n self.use_header = use_header\\n self.template = self.get_template()\\n self.context = self.get_context(table, self.use_header)\",\n \"def __create_table(self):\\n\\n self.connection = self.db.connect()\\n self.metadata = MetaData(self.connection)\\n\\n self.system = Table(self.table_name, self.metadata,\\n Column('timestamp', DateTime(), primary_key=True, nullable=False),\\n Column('vibration_sensor', Float()),\\n Column('flow', Float()),\\n Column('pressure', Float()),\\n Column('power_consumption', Float()),\\n Column('failure_times', Float()),\\n Column('operational', Boolean())\\n )\\n\\n self.metadata.create_all()\",\n \"def __init__(self, py_dict=None):\\n super(RuntimeNicInfoSchema, self).__init__()\\n self.set_data_type('xml')\\n self.index = None\\n self.label = None\\n self.network = NetworkSchema()\\n\\n if py_dict is not None:\\n self.get_object_from_py_dict(py_dict)\",\n \"def __init__(self, conn):\\n self._table_name = \\\"search_history\\\"\\n self._conn = conn\\n self._cursor = conn.cursor()\\n\\n self._initialize()\",\n \"def __init__(self, container_type, datasource=sybase.NULL_SOURCE):\\n super(sytable, self).__init__(container_type,\\n datasource or sybase.NULL_SOURCE)\\n columns = datasource.columns()\\n self._name = datasource.read_name()\\n self._attributes = datasource.read_table_attributes() or {}\\n self._number_of_rows = datasource.number_of_rows()\\n self._columns = OrderedDict(\\n (column, _column_factory(datasource, column, self._number_of_rows))\\n for column in columns)\\n\\n self._column_attributes = dict.fromkeys(columns)\\n self._dirty = False\",\n \"def __init__(self):\\n self.buckets = 1009\\n self.table = [[] for _ in range(self.buckets)]\",\n \"def __init__(self):\\n # Initialise a dictionary to store arbitrary\\n # attributes taken from the program logfile\\n self.__dict = {}\\n # List of tables\\n self.__tables = []\\n # List of keytexts\\n self.__keytexts = []\\n # For fragment retrieval\\n self.set_source_file(\\\"\\\")\\n self.set_startline(-1)\\n self.set_endline(-1)\\n # Flags\\n self.__nonzero = False\",\n \"def _prepare_stats_table(self, pinfos):\\n\\n stats_tbl = OrderedDict()\\n stats_tbl[\\\"Title\\\"] = OrderedDict()\\n for res in self.rsts:\\n stats_tbl[res.reportid] = OrderedDict()\\n\\n for pinfo in pinfos:\\n for colname in (pinfo[\\\"colname\\\"], pinfo[\\\"xcolname\\\"]):\\n if colname in stats_tbl[\\\"Title\\\"]:\\n continue\\n\\n # Each column name is represented by a row in the statistics table. Fill the \\\"Title\\\"\\n # column.\\n title_dict = stats_tbl[\\\"Title\\\"][colname] = OrderedDict()\\n defs = self._refdefs.info[colname]\\n\\n if defs.get(\\\"unit\\\") == \\\"nanosecond\\\":\\n # Convert nanoseconds to microseconds.\\n unit = \\\"us\\\"\\n else:\\n unit = defs.get(\\\"short_unit\\\", \\\"\\\")\\n\\n title_dict[\\\"colname\\\"] = colname\\n if unit:\\n title_dict[\\\"colname\\\"] += f\\\", {unit}\\\"\\n title_dict[\\\"coldescr\\\"] = defs[\\\"descr\\\"]\\n\\n title_dict[\\\"funcs\\\"] = OrderedDict()\\n for funcname in self._stats_funcs:\\n if funcname in self.rsts[0].cstats[colname]:\\n title_dict[\\\"funcs\\\"][funcname] = RORawResult.get_stat_func_descr(funcname)\\n\\n # Now fill the values for each result.\\n for res in self.rsts:\\n res_dict = stats_tbl[res.reportid][colname] = OrderedDict()\\n res_dict[\\\"funcs\\\"] = OrderedDict()\\n\\n for funcname in title_dict[\\\"funcs\\\"]:\\n val = res.cstats[colname][funcname]\\n fmt = \\\"{}\\\"\\n if defs.get(\\\"unit\\\") == \\\"nanosecond\\\" and \\\"index\\\" not in funcname:\\n val /= 1000\\n fmt = \\\"{:.2f}\\\"\\n if defs[\\\"type\\\"] == \\\"float\\\":\\n fmt = \\\"{:.2f}\\\"\\n\\n fdict = res_dict[\\\"funcs\\\"][funcname] = OrderedDict()\\n fdict[\\\"val\\\"] = fmt.format(val)\\n fdict[\\\"raw_val\\\"] = val\\n\\n if self._refres.reportid == res.reportid:\\n fdict[\\\"hovertext\\\"] = \\\"This is the reference result, other results \\\" \\\\\\n \\\"are compared to this one.\\\"\\n continue\\n\\n ref_fdict = stats_tbl[self._refres.reportid][colname][\\\"funcs\\\"][funcname]\\n change = val - ref_fdict[\\\"raw_val\\\"]\\n if ref_fdict[\\\"raw_val\\\"]:\\n percent = (change / ref_fdict[\\\"raw_val\\\"]) * 100\\n else:\\n percent = change\\n change = fmt.format(change) + unit\\n percent = \\\"{:.1f}%\\\".format(percent)\\n fdict[\\\"hovertext\\\"] = f\\\"Change: {change} ({percent})\\\"\\n\\n return stats_tbl\",\n \"def get_stats(self):\\n self.stats = self.soup.find('table', id='statsTable')\",\n \"def get_table_info(self):\\n epsg = None\\n meta = MetaData()\\n table_obj = Table(self.table, meta,\\n autoload=True, autoload_with=self.engine)\\n if not self.columns:\\n self.columns = table_obj.columns.keys()\\n geo_cols = [(col.name, col.type) for col in table_obj.columns\\n if hasattr(col.type, 'srid')]\\n if geo_cols:\\n geo_col = geo_cols[0]\\n self.geom_column = geo_col[0]\\n geo_obj = geo_col[1]\\n if self.geom_column not in self.columns:\\n self.columns.append(self.geom_column)\\n if hasattr(geo_obj, 'srid'):\\n epsg = geo_obj.srid\\n if epsg == -1:\\n epsg = 4326\\n if hasattr(geo_obj, 'geometry_type'):\\n self.geometry_type = geo_obj.geometry_type\\n\\n self.epsg = epsg\\n self.table_obj = table_obj\\n self.meta = meta\",\n \"def _initialize(self, chain, length):\\n # If the table already exists, exit now.\\n if chain != 0:\\n return\\n\\n # Determine size\\n try:\\n size = len(self._getfunc())\\n except TypeError:\\n size = 1\\n\\n query = \\\"create table %s (recid INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT, trace int(5), %s FLOAT)\\\" % (self.name, ' FLOAT, '.join(['v%s' % (x+1) for x in range(size)]))\\n self.db.cur.execute(query)\",\n \"def __init__(self):\\r\\n # sample ID -> (ref individual count,\\r\\n # {size -> (estimate, std err, ci_low, ci_high)})\\r\\n self._data = {}\",\n \"def __init__(self, schema_row):\\n self.schema = []\\n for field in schema_row['fields']:\\n self.schema.append(field['type'])\",\n \"def _make_tex_table(self, tabletitle):\\r\\n stattable = (\\r\\n r\\\"\\\"\\\"\\r\\n \\\\begin{table}[h!]\\r\\n \\\\caption{%s}\\r\\n \\\\centering\\r\\n \\\\begin{tabular}{l l l l l}\\r\\n \\\\toprule\\r\\n \\\\textbf{Statistic} & \\\\textbf{Inlet} & \\\\textbf{Outlet} \\\\\\\\\\\"\\\"\\\"\\r\\n % tabletitle\\r\\n )\\r\\n\\r\\n stats = [\\r\\n {\\\"name\\\": \\\"Count\\\", \\\"attribute\\\": \\\"N\\\", \\\"rule\\\": \\\"top\\\", \\\"forceint\\\": True},\\r\\n {\\\"name\\\": \\\"Number of NDs\\\", \\\"attribute\\\": \\\"ND\\\", \\\"forceint\\\": True},\\r\\n {\\\"name\\\": \\\"Min; Max\\\", \\\"attribute\\\": [\\\"min\\\", \\\"max\\\"], \\\"twoval\\\": True},\\r\\n {\\\"name\\\": \\\"Mean\\\", \\\"attribute\\\": \\\"mean\\\"},\\r\\n {\\r\\n \\\"name\\\": \\\"(95\\\\% confidence interval)\\\",\\r\\n \\\"attribute\\\": \\\"mean_conf_interval\\\",\\r\\n \\\"twoval\\\": True,\\r\\n \\\"ci\\\": True,\\r\\n \\\"rule\\\": \\\"none\\\",\\r\\n },\\r\\n {\\\"name\\\": \\\"Standard Deviation\\\", \\\"attribute\\\": \\\"std\\\"},\\r\\n {\\\"name\\\": \\\"Log. Mean\\\", \\\"attribute\\\": \\\"logmean\\\"},\\r\\n {\\r\\n \\\"name\\\": \\\"(95\\\\% confidence interval)\\\",\\r\\n \\\"attribute\\\": \\\"logmean_conf_interval\\\",\\r\\n \\\"twoval\\\": True,\\r\\n \\\"ci\\\": True,\\r\\n \\\"rule\\\": \\\"none\\\",\\r\\n },\\r\\n {\\\"name\\\": \\\"Log. Standard Deviation\\\", \\\"attribute\\\": \\\"logstd\\\"},\\r\\n {\\\"name\\\": \\\"Geo. Mean\\\", \\\"attribute\\\": \\\"geomean\\\"},\\r\\n {\\r\\n \\\"name\\\": \\\"(95\\\\% confidence interval)\\\",\\r\\n \\\"attribute\\\": \\\"geomean_conf_interval\\\",\\r\\n \\\"twoval\\\": True,\\r\\n \\\"ci\\\": True,\\r\\n \\\"rule\\\": \\\"none\\\",\\r\\n },\\r\\n {\\\"name\\\": \\\"Coeff. of Variation\\\", \\\"attribute\\\": \\\"cov\\\"},\\r\\n {\\\"name\\\": \\\"Skewness\\\", \\\"attribute\\\": \\\"skew\\\"},\\r\\n {\\\"name\\\": \\\"Median\\\", \\\"attribute\\\": \\\"median\\\"},\\r\\n {\\r\\n \\\"name\\\": \\\"(95\\\\% confidence interval)\\\",\\r\\n \\\"attribute\\\": \\\"median_conf_interval\\\",\\r\\n \\\"twoval\\\": True,\\r\\n \\\"ci\\\": True,\\r\\n \\\"rule\\\": \\\"none\\\",\\r\\n },\\r\\n {\\\"name\\\": \\\"Quartiles\\\", \\\"attribute\\\": [\\\"pctl25\\\", \\\"pctl75\\\"], \\\"twoval\\\": True},\\r\\n {\\r\\n \\\"name\\\": \\\"Number of Pairs\\\",\\r\\n \\\"attribute\\\": \\\"n_pairs\\\",\\r\\n \\\"rule\\\": \\\"top\\\",\\r\\n \\\"fromdataset\\\": True,\\r\\n \\\"sigfigs\\\": 1,\\r\\n \\\"forceint\\\": True,\\r\\n },\\r\\n {\\r\\n \\\"name\\\": \\\"Wilcoxon p-value\\\",\\r\\n \\\"attribute\\\": \\\"wilcoxon_p\\\",\\r\\n \\\"fromdataset\\\": True,\\r\\n \\\"pval\\\": True,\\r\\n \\\"tex\\\": True,\\r\\n },\\r\\n {\\r\\n \\\"name\\\": \\\"Mann-Whitney p-value\\\",\\r\\n \\\"attribute\\\": \\\"mannwhitney_p\\\",\\r\\n \\\"fromdataset\\\": True,\\r\\n \\\"pval\\\": True,\\r\\n \\\"tex\\\": True,\\r\\n },\\r\\n ]\\r\\n for s in stats:\\r\\n stattable += self._tex_table_row(**s)\\r\\n\\r\\n stattable += r\\\"\\\"\\\"\\r\\n \\\\bottomrule\\r\\n \\\\end{tabular}\\r\\n \\\\end{table}\\\"\\\"\\\"\\r\\n\\r\\n return stattable + \\\"\\\\n\\\"\",\n \"def speed_table_create(self):\\n\\n self.__table_create(Speed)\",\n \"def _generateTable(self, obj, **args):\\n\\n if self._script.utilities.isLayoutOnly(obj):\\n return []\\n\\n try:\\n table = obj.queryTable()\\n except:\\n return []\\n\\n return [messages.tableSize(table.nRows, table.nColumns)]\",\n \"def init_statsd():\\n statsd.init_statsd({\\n 'STATSD_HOST': config.secrets.server('statsd.host'),\\n 'STATSD_PORT': config.secrets.server('statsd.port'),\\n 'STATSD_BUCKET_PREFIX': 'linkr',\\n })\",\n \"def __init__(self, tabletext=\\\"\\\"):\\n\\n # Table attributes\\n self.__title = \\\"\\\"\\n self.__type = \\\"GRAPHS\\\" # Default to GRAPHS\\n self.__graphs = \\\"\\\"\\n self.__columns = \\\"\\\"\\n self.__text = \\\"\\\"\\n self.__data = \\\"\\\"\\n # Derived data\\n self.__graph_list = []\\n self.__column_list = []\\n # Indicate the the object has been populated\\n self.__table_parse_error = False\\n self.__nonzero = False\\n # The \\\"raw\\\" table data from the log file\\n self.__rawtable = \\\"\\\"\\n # Attempt to populate the table\\n if tabletext:\\n self.__rawtable = tabletext\\n if not self.__buildtable(tabletext):\\n # Failed to extract table\\n # If it could be a title then use this\\n # instead\\n if str(tabletext).count(\\\"\\\\n\\\") == 0:\\n self.settitle(tabletext)\",\n \"def set_up_tables(self):\\n tables = []\\n tables.append({'groupname': 'metadata',\\n 'tablename': 'sim_info',\\n 'description': desc.SimInfoRow,\\n 'tabletitle': 'Simulation Information'})\\n tables.append({'groupname': 'metadata',\\n 'tablename': 'sim_timeseries',\\n 'description': desc.SimTimeseriesRow,\\n 'tabletitle': 'Simulation Power Data'})\\n tables.append({'groupname': 'th',\\n 'tablename': 'th_params',\\n 'description': desc.ThMetadataRow,\\n 'tabletitle': 'TH Component Parameters'})\\n tables.append({'groupname': 'th',\\n 'tablename': 'th_timeseries',\\n 'description': desc.ThTimeseriesRow,\\n 'tabletitle': 'TH Timeseries'})\\n tables.append({'groupname': 'neutronics',\\n 'tablename': 'neutronics_timeseries',\\n 'description': desc.NeutronicsTimeseriesRow,\\n 'tabletitle': 'Neutronics Timeseries'})\\n tables.append({'groupname': 'neutronics',\\n 'tablename': 'neutronics_params',\\n 'description': desc.NeutronicsParamsRow,\\n 'tabletitle': 'Neutronics Metadata'})\\n tables.append({'groupname': 'neutronics',\\n 'tablename': 'zetas',\\n 'description': desc.ZetasTimestepRow,\\n 'tabletitle': 'Neutron Precursor Concentrations'})\\n tables.append({'groupname': 'neutronics',\\n 'tablename': 'omegas',\\n 'description': desc.OmegasTimestepRow,\\n 'tabletitle': 'Decay Heat Fractions'})\\n return tables\",\n \"def init():\\n database.create_tables([Tracker])\\n database.commit()\",\n \"def __init__(self, table_name='casbin_rule', **kwargs):\\n self.table_name = table_name\\n self.dynamodb = boto3.client('dynamodb', **kwargs)\\n try:\\n\\n self.dynamodb.create_table(\\n TableName=self.table_name,\\n\\n AttributeDefinitions=[\\n {\\n 'AttributeName': 'id',\\n 'AttributeType': 'S'\\n }\\n ],\\n KeySchema=[\\n {\\n 'AttributeName': 'id',\\n 'KeyType': 'HASH'\\n },\\n ],\\n ProvisionedThroughput={\\n 'ReadCapacityUnits': 10,\\n 'WriteCapacityUnits': 10\\n }\\n )\\n except self.dynamodb.exceptions.ResourceInUseException:\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6132577","0.61266005","0.582939","0.56516737","0.56412935","0.5606859","0.5601135","0.55859405","0.5571048","0.555038","0.5544171","0.54862404","0.54842335","0.54761785","0.5465003","0.5443442","0.5419218","0.5413731","0.54091996","0.539648","0.5395933","0.538987","0.5384708","0.5361659","0.53546315","0.5330871","0.53015184","0.52919835","0.52830005","0.52745175","0.52580684","0.525231","0.5241906","0.523854","0.52340865","0.5226947","0.5193358","0.51682","0.5164554","0.5160155","0.5141596","0.51395893","0.51341456","0.51326597","0.5126145","0.51175886","0.51136845","0.51095057","0.51025796","0.50946355","0.50858945","0.50847715","0.5076044","0.5070857","0.5070636","0.5066055","0.5061418","0.5057518","0.50572616","0.5030023","0.5029843","0.50287694","0.5027658","0.5027348","0.5023851","0.5020058","0.5010241","0.5002239","0.49933016","0.4991018","0.49903432","0.49900967","0.4979688","0.49787873","0.49775887","0.49675867","0.49617532","0.4957828","0.49566156","0.49547783","0.4947909","0.49463412","0.493893","0.49313468","0.49300164","0.49298307","0.4914983","0.49127185","0.49108434","0.49035642","0.4892021","0.48878452","0.48804113","0.4872683","0.487261","0.48693037","0.4868403","0.48675704","0.48635435","0.48631445"],"string":"[\n \"0.6132577\",\n \"0.61266005\",\n \"0.582939\",\n \"0.56516737\",\n \"0.56412935\",\n \"0.5606859\",\n \"0.5601135\",\n \"0.55859405\",\n \"0.5571048\",\n \"0.555038\",\n \"0.5544171\",\n \"0.54862404\",\n \"0.54842335\",\n \"0.54761785\",\n \"0.5465003\",\n \"0.5443442\",\n \"0.5419218\",\n \"0.5413731\",\n \"0.54091996\",\n \"0.539648\",\n \"0.5395933\",\n \"0.538987\",\n \"0.5384708\",\n \"0.5361659\",\n \"0.53546315\",\n \"0.5330871\",\n \"0.53015184\",\n \"0.52919835\",\n \"0.52830005\",\n \"0.52745175\",\n \"0.52580684\",\n \"0.525231\",\n \"0.5241906\",\n \"0.523854\",\n \"0.52340865\",\n \"0.5226947\",\n \"0.5193358\",\n \"0.51682\",\n \"0.5164554\",\n \"0.5160155\",\n \"0.5141596\",\n \"0.51395893\",\n \"0.51341456\",\n \"0.51326597\",\n \"0.5126145\",\n \"0.51175886\",\n \"0.51136845\",\n \"0.51095057\",\n \"0.51025796\",\n \"0.50946355\",\n \"0.50858945\",\n \"0.50847715\",\n \"0.5076044\",\n \"0.5070857\",\n \"0.5070636\",\n \"0.5066055\",\n \"0.5061418\",\n \"0.5057518\",\n \"0.50572616\",\n \"0.5030023\",\n \"0.5029843\",\n \"0.50287694\",\n \"0.5027658\",\n \"0.5027348\",\n \"0.5023851\",\n \"0.5020058\",\n \"0.5010241\",\n \"0.5002239\",\n \"0.49933016\",\n \"0.4991018\",\n \"0.49903432\",\n \"0.49900967\",\n \"0.4979688\",\n \"0.49787873\",\n \"0.49775887\",\n \"0.49675867\",\n \"0.49617532\",\n \"0.4957828\",\n \"0.49566156\",\n \"0.49547783\",\n \"0.4947909\",\n \"0.49463412\",\n \"0.493893\",\n \"0.49313468\",\n \"0.49300164\",\n \"0.49298307\",\n \"0.4914983\",\n \"0.49127185\",\n \"0.49108434\",\n \"0.49035642\",\n \"0.4892021\",\n \"0.48878452\",\n \"0.48804113\",\n \"0.4872683\",\n \"0.487261\",\n \"0.48693037\",\n \"0.4868403\",\n \"0.48675704\",\n \"0.48635435\",\n \"0.48631445\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.70146513"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13090,"cells":{"query":{"kind":"string","value":"Search through a table and return the first [row, column] pair who's value is None."},"document":{"kind":"string","value":"def find_unassigned_table_cell(table):\n for row in range(len(table)):\n for column in range(len(table[row])):\n if table[row][column] is None:\n return row, column\n return row, column"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _get_first_element(cls, d):\n\n t = np.where(d[:, 2] > 0)[0]\n if len(t):\n return d[t[0], 0], d[t[0], 1], t[0]\n return None, None, None","def firstEmptyCell(board):\r\n for i in range(9):\r\n for j in range(9):\r\n if board[i][j] == 0:\r\n return (i, j) # row, col\r\n return None","def get_first_selection(table, column_name):\n def replace(entry):\n if pd.isnull(entry):\n return None\n else:\n return re.sub(r',.*', '', entry)\n assert (isinstance(table, Table)), \"Input not a supported type.\"\n column = table.apply(replace, column_name)\n return table.append_column(column_name, column)","def _find_empty_cell(self):\n\n for r, row in enumerate(self._board):\n for c, cell in enumerate(row):\n if cell is None:\n return r, c","def get_next_empty_cell(self):\n for row in range(len(self.grid)):\n for col in range(len(self.grid[0])):\n if self.grid[row][col] == 0:\n return (row, col)\n return None","def find_next_empty_cell(grid):\n for i, row in enumerate(grid):\n for j, col in enumerate(row):\n if col == 0:\n return (i, j)\n return None","def find_empty(bo):\n for i in range(len(bo)):\n for j in range(len(bo[0])):\n if bo[i][j] == 0:\n return (i, j)\n\n return None","def first_valid_index(self) -> Optional[Union[Scalar, Tuple[Scalar, ...]]]:\n data_spark_columns = self._internal.data_spark_columns\n\n if len(data_spark_columns) == 0:\n return None\n\n cond = reduce(lambda x, y: x & y, map(lambda x: x.isNotNull(), data_spark_columns))\n\n with sql_conf({SPARK_CONF_ARROW_ENABLED: False}):\n # Disable Arrow to keep row ordering.\n first_valid_row = (\n self._internal.spark_frame.filter(cond)\n .select(self._internal.index_spark_columns)\n .limit(1)\n .toPandas()\n )\n\n # For Empty Series or DataFrame, returns None.\n if len(first_valid_row) == 0:\n return None\n\n first_valid_row = first_valid_row.iloc[0]\n if len(first_valid_row) == 1:\n return first_valid_row.iloc[0]\n else:\n return tuple(first_valid_row)","def find_empty(grid):\n for i in range(LEN_GRID):\n for j in range(LEN_GRID):\n if grid[i][j] == 0:\n return (i, j) # row, col\n return None","def not_null(table_rows, col_name_list=[], col_num_list=[]):\n keys = col_name_list\n rst = True\n lst = []\n if(not keys): #key == [] or key == None\n keys = [table_rows[0].keys[x] for x in col_num_list]\n\n row_num = 0\n for row in table_rows:\n for key in keys:\n if(row.kv[key].strip() == \"\"):\n rst = False\n lst.append(\"(col:{0},row:{1})\".format(\n key, row_num\n ))\n row_num += 1\n return rst,\",\".join(lst)","def fetch_first(self, tablename):\n\n query = 'select * from ' + tablename + \" ASC LIMIT 1\"\n try:\n self.__cur.execute(query)\n except Exception as e:\n self.__conn.rollback()\n raise e\n fetcheddata = self.__cur.fetchall()\n if fetcheddata:\n fetcheddata = fetcheddata[0]\n fetcheddata = self.__helper._functions__rowtodict([fetcheddata])\n return fetcheddata[0]\n return None","def find_empty(board):\n for ii in range(len(board)):\n for jj in range(len(board[ii])):\n if board[ii][jj] == 0:\n print('Empty: ', (jj , ii)) # column, row\n return jj, ii # column, row\n return None","def get_first(self):\n return self.A[1][0] if self.n > 0 else None","def find_first_free_cell(board, picked_column):\n for row in reversed(range(len(board))):\n if board[row][picked_column] == 0:\n return row","def find_empty_col(slots):\n index = 0\n for i in list(zip(*list(slots.values())[::])):\n if sum([1 for j in list(i) if j]) == 0:\n return index\n index += 1\n return 6","def get_val_or_null(map, row, col):\n value = map.get(row, col)\n if map.mtype == \"CELL\" and value == CNULL:\n value = FNULL\n return value","def _first_non_none_value(items: Iterable[tuple[bool | None, str] | None]) -> tuple[bool, str]:\n for item_opt in items:\n if item_opt is not None:\n item, reason = item_opt\n if item is not None:\n return item, reason\n return False, \"default\"","def _get_none(self, x, y):\n try:\n return self[x, y]\n except ArrayError:\n return None","def row_by_value(idl_, table, column, match, default=_NO_DEFAULT):\n tab = idl_.tables[table]\n for r in tab.rows.values():\n if getattr(r, column) == match:\n return r\n if default is not _NO_DEFAULT:\n return default\n raise None","def searchColumnHeadings(self, table: Table):\n lista = []\n if table:\n for col in table.columns:\n lista.append(col.name)\n return lista\n return None","def find_index(row):\n value = row[index]\n if value in seen:\n return seen[value]\n for row_ in merged.iter_dicts(True):\n if row_[index] == value:\n seen[value] = row_[\"index\"]\n return row_[\"index\"]\n return None","def find_first_non_nan(array):\n for index, value in enumerate(array):\n if not np.isnan(value):\n return index","def is_match(cells):\n if len(cells) == 1 and \"-\" not in cells:\n return list(cells)[0]\n return None","def find(self, value):\n for row in range(self.getHeight()):\n for column in range(self.getWidth()):\n if self[row][column] == value:\n return (row, column)\n return None","def find_empty(self):\n num_rows = len(self.board)\n num_cols = len(self.board[0])\n\n for i in range(num_rows):\n for j in range(num_cols):\n if self.board[i][j] == 0:\n return (i, j)","def first_value(self):\n if not self.is_empty():\n return self.data[self.head]\n return None","def get_column(col_to_search, value_to_match, col_to_get, table, db_file):\n \n try:\n conn, c = connect_to_db(db_file) \n c.execute('SELECT {cg} FROM {t} WHERE {col}=\"{value}\"'.format(t=safe(table), \n cg=safe(col_to_get), col=safe(col_to_search), value=safe(value_to_match)))\n column = c.fetchone()\n conn.close()\n return column\n except Exception as e:\n print(\"Error when trying to fetch row in table\", table, \"in database file\", db_file)\n print(e)\n return None","def _FollowedByEmpty(row, index):\n return not any(row[index + 1:])","def _get_next_element(cls, d, idx):\n t = np.where(d[:, 2] > 0)[0]\n t = t[t > idx]\n if len(t):\n return d[t[0], 0], d[t[0], 1], t[0]\n return None, None, None","def find_empty(game_board):\n for row in range(len(game_board)):\n for col in range(len(game_board[row])):\n if len(game_board[row][col]) == 2:\n return row, col\n for row in range(len(game_board)):\n for col in range(len(game_board[row])):\n if len(game_board[row][col]) >= 3:\n return row, col\n\n return None","def find_empty_cell():\n\n for x in range(1, 38):\n if worksheet.cell((x, 1)).value == \"\":\n date_cell = worksheet.cell((x, 1))\n description_cell = worksheet.cell((x, 2))\n payment_received_cell = worksheet.cell((x, 3))\n rent_due_cell = worksheet.cell((x, 4))\n\n return date_cell, description_cell, payment_received_cell, rent_due_cell\n\n else:\n continue","def find_row(table, row):\n for idx in range(len(table)):\n if table[idx][0] == row:\n return idx\n return -1","def dbGetFirstRowOneValue(con, cmd, args=[], skipTrace=False):\n row = dbGetFirstRow(con, cmd, args, skipTrace)\n trace(\"row=\" + str(row))\n if row is not None and len(row) > 0:\n return row[0]\n return None","def where(self, column_or_label, value=None):\n column = self._get_column(column_or_label)\n if value is not None:\n column = column == value\n return self.take(np.nonzero(column)[0])","def getHeaderRowPosition(sheetData):\n for index, row in enumerate(sheetData):\n if row[1] != '':\n return index\n return 0","def _non_zero_columns_search(array):\n col_num = array.shape[1]\n non_zero_col = CArray([], dtype=int)\n for c in range(col_num):\n col = array[:, c]\n if col.any() == True:\n non_zero_col = non_zero_col.append(c)\n\n return non_zero_col","def find_col(table, col):\n return table[0].index(col)","def last_valid_index(self) -> Optional[Union[Scalar, Tuple[Scalar, ...]]]:\n data_spark_columns = self._internal.data_spark_columns\n\n if len(data_spark_columns) == 0:\n return None\n\n cond = reduce(lambda x, y: x & y, map(lambda x: x.isNotNull(), data_spark_columns))\n\n last_valid_rows = (\n self._internal.spark_frame.filter(cond)\n .select(self._internal.index_spark_columns)\n .tail(1)\n )\n\n # For Empty Series or DataFrame, returns None.\n if len(last_valid_rows) == 0:\n return None\n\n last_valid_row = last_valid_rows[0]\n\n if len(last_valid_row) == 1:\n return last_valid_row[0]\n else:\n return tuple(last_valid_row)","def null_check(cur,code,table,passvalue):\n cur.execute(code)\n result = cur.fetchall()[0][0]\n if result == passvalue:\n print(f\"Data Quality check passed. {table} doesn't have any null values.\")\n else:\n print(f\"Data quality check failed. {table} has null values.\")","def fetchone(self):\n #if self._state == self._STATE_NONE:\n # raise exc.ProgrammingError(\"No query yet\")\n\n # Sleep until we're done or we have some data to return\n #self._fetch_while(lambda: not self._data and self._state != self._STATE_FINISHED)\n if not self._data:\n return None\n elif self._rownumber >= len( self._data.rows ):\n return None\n else:\n result = self._data.rows[self._rownumber]\n\n\n correctedData = OrderedDict()\n #Insure correct field order\n for column in self._data.columns:\n correctedData[column] = result[column]\n\n #result = tuple( result.values() )\n result = tuple( correctedData.values() )\n result = tuple( correctedData.values() )\n self._rownumber += 1\n return result","def get_rows(column_to_search, value_to_match, table, db_file):\n \n try:\n conn, c = connect_to_db(db_file) \n c.execute('SELECT * FROM {t} WHERE {col}=\"{value}\"'.format(t=safe(table), \n col=safe(column_to_search), value=value_to_match))\n row = c.fetchall()\n conn.close()\n return row\n except Exception as e:\n print(\"Error when trying to get row in table\", table, \"in\", db_file)\n print(e)\n return None","def select_one(self, table, column, value):\n select_row = \"SELECT * FROM {} WHERE {}='{}' AND delete_status = FALSE;\".format(table, column, value)\n self.cursor.execute(select_row)\n row = self.cursor.fetchone()\n return row","def first(data, key):\n for i in data:\n if key(i):\n return i\n return None","def __skip_null_values(self, row, index):\n # If there is no value at the row index,\n # Return True\n # Return False if there is a value\n if row[index] == \"\":\n return True\n else:\n return False","def find_column(self, columns):\n for column in columns:\n if self.match(column):\n return column\n return None","def _find_common_cells(rows_or_columns, cell_value=1):\n\n T = np.array(rows_or_columns)\n if cell_value == 0:\n return np.where(np.logical_not(np.logical_or.reduce(T)))[0]\n else:\n return np.where(np.logical_and.reduce(T))[0]","def findFirstFalseValue( data ):\n #~ idx = np.argmin( data ); \n #~ if( data[idx] ):\n #~ return -1;\n #~ return idx;\n \n # argmin seems far less efficient than argmax... (and seems to compute all the list)\n n = len(data);\n i = 0; \n while( i < n ):\n if( not data[i] ):\n return i;\n i += 1;\n return -1;","def get_columns_with_nulls(X, columns_to_scan = \"all\", rows_to_scan=100000):\n rows_to_scan = get_rows_to_scan(rows_to_scan, X.shape[0])\n \n columns_to_scan = get_list_of_columns_to_check(columns_to_scan, X.columns)\n mask = np.array(X[columns_to_scan][:rows_to_scan].count() < rows_to_scan)\n return list(np.array(columns_to_scan)[mask])","def _check_row(self):\n match = None\n for row in self._board:\n row_string = ''.join(row)\n match = re.search(WIN_REGEX, row_string)\n if match:\n return match.group()[0]\n return None","def values(self):\n return [entry.value for entry in self.table if entry.value is not None]","def find_position(self, element):\n for row in range(self.rows):\n for col in range(self.cols):\n if self.data[row][col] == element:\n return row, col\n return None, None","def find_position(self, element):\n for row in range(self.rows):\n for col in range(self.cols):\n if self.data[row][col] == element:\n return row, col\n return None, None","def find_unsettled_spot(self):\n\t\tfor i in range(9):\n\t\t\tfor j in range(9):\n\t\t\t\tif self.grid[i][j] == 0:\n\t\t\t\t\treturn i, j\n\t\treturn","def null_values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetTableNullValueArgs']]]]:\n return pulumi.get(self, \"null_values\")","def first(self):\n try:\n data = self.get_cursor()[0]\n return self.from_(**self.prepare_data(data))\n except IndexError:\n return None","def _check_column(self):\n for column in np.transpose(self._board):\n col_string = ''.join(column)\n match = re.search(WIN_REGEX, col_string)\n if match:\n return match.group()[0]\n return None","def get_nan_idx(column, df):\n return df[df[column].isna()].index.values","def get_for_id(id,table):\n # Implement this function\n for row in range(1, len(table)):\n for col in range(len(table[0])):\n if id in table[row][col]:\n return table[row]","def find(a):\n\n a = coo_matrix(a, copy=True)\n a.sum_duplicates()\n # remove explicit zeros\n nz_mask = a.data != 0\n return a.row[nz_mask], a.col[nz_mask], a.data[nz_mask]","def find_first_none(self, properties):\n\n for drink in properties:\n iterate_drink = iter(drink)\n next(iterate_drink)\n for drink_property in iterate_drink:\n split_property = drink_property.split(\": \")[1].split(\" //\")[0]\n if split_property == \"None\":\n return drink_property\n return \"\"","def _find_first(self, ast, label):\n res = self._find_all(ast, label, max_results=1)\n if len(res):\n return res[0]\n return None","def find_empty_squares(board):\n for i in range(len(board)):\n for j in range(len(board[0])):\n if board[i][j] == 0:\n return (i,j) #row , column\n\n #if there are no blank squres\n return None","def first(self):\n return self.head and self.head.value or None","def find_column_index(self, columns):\n for i in range(len(columns)):\n if self.match(columns[i]):\n return i\n return None","def _find_min_pair(pandas_matrix):\n numpy_matrix = pandas_matrix.values\n mins = np.where(numpy_matrix == np.nanmin(numpy_matrix))\n min_col_idx = mins[0][0]\n min_row_idx = mins[1][0]\n (min_col, min_row) = (pandas_matrix.index[min_col_idx], \n pandas_matrix.columns[min_row_idx])\n\n return (min_col, min_row)","def get_next_row(table, names):\n\n if isinstance(table, list):\n if not table:\n return None, True\n else:\n return table.pop(0), False\n else:\n row = table.fetchone()\n if row is None:\n return None, True\n else:\n return dict(zip(names, row)), False","def trim_empty_rows(self, table: Table):\n self._requires_table(table)\n\n empty = []\n for idx in reversed(table.index):\n row = table[idx]\n if any(value is not None for value in row):\n break\n empty.append(idx)\n\n table.delete_rows(empty)","def get_empty_cells(grid):\n empty = []\n for j,row in enumerate(grid):\n for i,val in enumerate(row):\n if not val:\n empty.append((j,i))\n return empty","def _find_zero(board):\n for r_index, row in enumerate(board):\n for c_index, num in enumerate(row):\n if num == 0:\n return r_index, c_index","def find_first_unexplored(self, bool_matrix):\n current_spot = self.beginning\n while not (current_spot.row_num == len (self.matrix)-1\n and current_spot.col_num == len(self.matrix[0])-1):\n if bool_matrix[current_spot.row_num][current_spot.col_num] == 0:\n return (current_spot.row_num, current_spot.col_num) \n current_spot = current_spot.walk_right()#####\n if (current_spot.row_num == len (self.matrix)-1\n and current_spot.col_num == len(self.matrix[0])-1):\n if bool_matrix[current_spot.row_num][current_spot.col_num] == 0:\n return (current_spot.row_num, current_spot.col_num) \n if current_spot.character == 0:\n return (self.row_num, self.col_num)\n return False","def fakes(self, nodes):\n\n # get a view of the DataFrame without positional columns\n non_positional = self.metrics[self.metrics.columns - ['X', 'Y', 'coords', 'm_coords']].ix[nodes]\n # find rows that are all null, these are the nodes representing the connection to existing infastructure\n return non_positional[np.all(pd.isnull(non_positional) == True, axis=1)].index.values","def find_last_valid_col(row):\n last_el = len(row) - 1\n while last_el > 0:\n col = row[last_el]\n if col is None or col == \"\":\n last_el -= 1\n continue\n else:\n return last_el\n return last_el","def get_unknown_neighbours(self, row, col):\n return [cell for cell in self.get_neighbours(row, col) if cell.state == None ]","def tm_row(self) -> Optional[int]:\n for row in [1, 2, 3]:\n if self.label in PeriodicTable.transition_metals(row):\n return row\n\n return None","def get_columns_with_all_nulls(X, columns_to_check='all', rows_to_scan='all'):\n rows_to_scan = get_rows_to_scan(rows_to_scan, X.shape[0])\n columns_to_check = get_list_of_columns_to_check(columns_to_check, X.columns)\n mask = np.array(X[columns_to_check][:rows_to_scan].count() == 0)\n return list(np.array(columns_to_check)[mask])","def dt_find(search = \"\",\n row = None,\n column = None,\n tableID = \"list\",\n first = False,\n ):\n # 'todo need to fix the searching on numbers\n config = current.test_config\n browser = config.browser\n\n # Calculate the rows that need to be navigated along to find the search string\n colList = []\n rowList = []\n if row == None:\n r = 1\n while True:\n tr = \".//*[@id='%s']/tbody/tr[%s]\" % (tableID, r)\n try:\n elem = browser.find_element_by_xpath(tr)\n rowList.append(r)\n r += 1\n except:\n break\n elif isinstance(row, int):\n rowList = [row]\n else:\n rowList = row\n # Calculate the columns that need to be navigated down to find the search string\n if column == None:\n c = 1\n while True:\n td = \".//*[@id='%s']/tbody/tr[1]/td[%s]\" % (tableID, c)\n try:\n elem = browser.find_element_by_xpath(td)\n colList.append(c)\n c += 1\n except:\n break\n elif isinstance(column, int):\n colList = [column]\n else:\n colList = column\n s3_debug(\"rows %s, columns %s\" % (rowList, colList))\n # Now try and find a match\n result = []\n for r in rowList:\n for c in colList:\n td = \".//*[@id='%s']/tbody/tr[%s]/td[%s]\" % (tableID, r, c)\n try:\n elem = browser.find_element_by_xpath(td)\n s3_debug(\"got %s, needle %s\" % (elem.text, search))\n if elem.text == search:\n if first:\n return (r, c)\n else:\n result.append((r, c))\n except:\n pass\n return result","def searchColumn(self, table: Table, name: str) -> Column:\n if table:\n for col in table.columns:\n if col.name.lower() == name.lower():\n return col\n return None","def null_values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetLogTableNullValueArgs']]]]:\n return pulumi.get(self, \"null_values\")","def get_cell(self, x, y):\n x1, y1 = self.transpose_coordinates(x, y)\n if self.is_in_field(x1, y1):\n return self._cells[y1][x1]\n return None","def getNonEmptyCells(self):\n nonemptys = []\n for ri in range(self.nRow):\n for ci in range(self.nCol):\n val = self.vals[ri][ci]\n if not self.isEmpty(val):\n row = ri+1\n col = ci+1\n nonemptys.append(CellDesc(row=row, col=col, val=val))\n return nonemptys","def find_fit(candidates):\n try:\n fit = sorted(candidates.items(), key=lambda x: len(x[1])).pop(0)\n except AttributeError:\n return None\n row, col = fit[0]\n n = fit[1].pop()\n if len(fit[1]) == 0:\n return row, col, n\n return None","def find_blank_lines(f):\n df = pd.read_csv(f)\n indices = df.index[df.apply(\n lambda row: all(row.apply(lambda col: pd.isnull(col))),\n axis=1)].tolist()\n\n return [i + 1 for i in indices]","def filter_empty_rows(self, table: Table):\n self._requires_table(table)\n\n empty = []\n for idx, row in table.iter_lists():\n if all(value is None for value in row):\n empty.append(idx)\n\n table.delete_rows(empty)","def pylookup(self, col1, col2, matrix, index=3):\n\n for row in matrix:\n if col1 == row[0] and col2 == row[1]:\n return row[index]\n return None","def find(self, key):\n index = self.quadratic_probe(key)\n if index != -1:\n if self.table[index] is not None:\n return self.table[index]\n else:\n return False\n else:\n return False","def first(self):\n return self.begin and self.begin.value or None","def find_empty_space(board: list) -> tuple:\n board_length = len(board)\n for i in range(board_length):\n for j in range(board_length):\n if board[i][j] == 0:\n return (i,j)","def getBlank(self):\n return self.tiles[-1]","def find_blank_cell(self, board: list):\n cells = {}\n for i in range(9): # Iterate over rows\n for j in range(9): # Iterate over columns\n if board[i][j] == 0:\n cells[str(i) + ' ' + str(j)] = self.count_numbers(board, j, i)\n m = max(cells.values())\n for k in cells:\n if cells[k] == m:\n s = k.split()\n x, y = int(s[1]), int(s[0])\n return x, y","def nonull(val):\n return val if not pd.isnull(val) else None","def get_empty_cells(grid):\n\tempty = []\n\tfor j,row in enumerate(grid):\n\t\tfor i,val in enumerate(row):\n\t\t\tif not val:\n\t\t\t\tempty.append((j,i))\n\treturn empty","def find(self, value):\n for position in range(self.get_size()):\n if self.table[position] == value:\n return position","def findEmpty(grid):\n for x in range(len(grid.board)):\n for y in range(len(grid.board[0])):\n if grid.board[x][y] == 0:\n return [x,y]","def get_rownumber(self, first_col_val):\n\n try:\n (col_name, col_contents) = self.data[0]\n col_data = [col_name] + col_contents\n return col_data.index(first_col_val)\n except ValueError:\n return None","def find_coordinates(self, value):\n cells = {v.coordinates for v in self.cells if v.value == value}\n return cells if len(cells) > 0 else None","def peek(self):\r\n if self.point_to_head.chi == None:\r\n return None\r\n return self.point_to_head.chi.val","def find_empty_cell(d):\n for i in range(5):\n if d[i][x-1] == '.':\n y = i\n return y","def calc_null(self):\n null = 0\n for x in range(0, self.tot_col):\n for y in range(1, self.tot_rows + 1):\n if self.file_list[y][x].lower() == 'null':\n null += 1\n print('Total number of null fields: ' + str(null))\n results.append('Total number of null fields: ' + str(null))","def null_handler(df):\n \n # define ok as hue = True\n ok = np.array([~pd.isnull(df['hue'])])[0]\n \n # filter arrays\n r = df['red'][ok]\n g = df['green'][ok]\n b = df['blue'][ok]\n h = df['hue'][ok]\n s = df['saturation'][ok]\n v = df['value'][ok]\n t = df['timestamp'][ok]\n dBT = df['dBT'][ok]\n dt = df['datetime'][ok] \n \n return (r,g,b,h,s,v,t,dBT,dt)","def getFirst(self, t):\n index = self._findFirst(t)\n if index >= 0:\n return self.jobs[index]\n else:\n return None"],"string":"[\n \"def _get_first_element(cls, d):\\n\\n t = np.where(d[:, 2] > 0)[0]\\n if len(t):\\n return d[t[0], 0], d[t[0], 1], t[0]\\n return None, None, None\",\n \"def firstEmptyCell(board):\\r\\n for i in range(9):\\r\\n for j in range(9):\\r\\n if board[i][j] == 0:\\r\\n return (i, j) # row, col\\r\\n return None\",\n \"def get_first_selection(table, column_name):\\n def replace(entry):\\n if pd.isnull(entry):\\n return None\\n else:\\n return re.sub(r',.*', '', entry)\\n assert (isinstance(table, Table)), \\\"Input not a supported type.\\\"\\n column = table.apply(replace, column_name)\\n return table.append_column(column_name, column)\",\n \"def _find_empty_cell(self):\\n\\n for r, row in enumerate(self._board):\\n for c, cell in enumerate(row):\\n if cell is None:\\n return r, c\",\n \"def get_next_empty_cell(self):\\n for row in range(len(self.grid)):\\n for col in range(len(self.grid[0])):\\n if self.grid[row][col] == 0:\\n return (row, col)\\n return None\",\n \"def find_next_empty_cell(grid):\\n for i, row in enumerate(grid):\\n for j, col in enumerate(row):\\n if col == 0:\\n return (i, j)\\n return None\",\n \"def find_empty(bo):\\n for i in range(len(bo)):\\n for j in range(len(bo[0])):\\n if bo[i][j] == 0:\\n return (i, j)\\n\\n return None\",\n \"def first_valid_index(self) -> Optional[Union[Scalar, Tuple[Scalar, ...]]]:\\n data_spark_columns = self._internal.data_spark_columns\\n\\n if len(data_spark_columns) == 0:\\n return None\\n\\n cond = reduce(lambda x, y: x & y, map(lambda x: x.isNotNull(), data_spark_columns))\\n\\n with sql_conf({SPARK_CONF_ARROW_ENABLED: False}):\\n # Disable Arrow to keep row ordering.\\n first_valid_row = (\\n self._internal.spark_frame.filter(cond)\\n .select(self._internal.index_spark_columns)\\n .limit(1)\\n .toPandas()\\n )\\n\\n # For Empty Series or DataFrame, returns None.\\n if len(first_valid_row) == 0:\\n return None\\n\\n first_valid_row = first_valid_row.iloc[0]\\n if len(first_valid_row) == 1:\\n return first_valid_row.iloc[0]\\n else:\\n return tuple(first_valid_row)\",\n \"def find_empty(grid):\\n for i in range(LEN_GRID):\\n for j in range(LEN_GRID):\\n if grid[i][j] == 0:\\n return (i, j) # row, col\\n return None\",\n \"def not_null(table_rows, col_name_list=[], col_num_list=[]):\\n keys = col_name_list\\n rst = True\\n lst = []\\n if(not keys): #key == [] or key == None\\n keys = [table_rows[0].keys[x] for x in col_num_list]\\n\\n row_num = 0\\n for row in table_rows:\\n for key in keys:\\n if(row.kv[key].strip() == \\\"\\\"):\\n rst = False\\n lst.append(\\\"(col:{0},row:{1})\\\".format(\\n key, row_num\\n ))\\n row_num += 1\\n return rst,\\\",\\\".join(lst)\",\n \"def fetch_first(self, tablename):\\n\\n query = 'select * from ' + tablename + \\\" ASC LIMIT 1\\\"\\n try:\\n self.__cur.execute(query)\\n except Exception as e:\\n self.__conn.rollback()\\n raise e\\n fetcheddata = self.__cur.fetchall()\\n if fetcheddata:\\n fetcheddata = fetcheddata[0]\\n fetcheddata = self.__helper._functions__rowtodict([fetcheddata])\\n return fetcheddata[0]\\n return None\",\n \"def find_empty(board):\\n for ii in range(len(board)):\\n for jj in range(len(board[ii])):\\n if board[ii][jj] == 0:\\n print('Empty: ', (jj , ii)) # column, row\\n return jj, ii # column, row\\n return None\",\n \"def get_first(self):\\n return self.A[1][0] if self.n > 0 else None\",\n \"def find_first_free_cell(board, picked_column):\\n for row in reversed(range(len(board))):\\n if board[row][picked_column] == 0:\\n return row\",\n \"def find_empty_col(slots):\\n index = 0\\n for i in list(zip(*list(slots.values())[::])):\\n if sum([1 for j in list(i) if j]) == 0:\\n return index\\n index += 1\\n return 6\",\n \"def get_val_or_null(map, row, col):\\n value = map.get(row, col)\\n if map.mtype == \\\"CELL\\\" and value == CNULL:\\n value = FNULL\\n return value\",\n \"def _first_non_none_value(items: Iterable[tuple[bool | None, str] | None]) -> tuple[bool, str]:\\n for item_opt in items:\\n if item_opt is not None:\\n item, reason = item_opt\\n if item is not None:\\n return item, reason\\n return False, \\\"default\\\"\",\n \"def _get_none(self, x, y):\\n try:\\n return self[x, y]\\n except ArrayError:\\n return None\",\n \"def row_by_value(idl_, table, column, match, default=_NO_DEFAULT):\\n tab = idl_.tables[table]\\n for r in tab.rows.values():\\n if getattr(r, column) == match:\\n return r\\n if default is not _NO_DEFAULT:\\n return default\\n raise None\",\n \"def searchColumnHeadings(self, table: Table):\\n lista = []\\n if table:\\n for col in table.columns:\\n lista.append(col.name)\\n return lista\\n return None\",\n \"def find_index(row):\\n value = row[index]\\n if value in seen:\\n return seen[value]\\n for row_ in merged.iter_dicts(True):\\n if row_[index] == value:\\n seen[value] = row_[\\\"index\\\"]\\n return row_[\\\"index\\\"]\\n return None\",\n \"def find_first_non_nan(array):\\n for index, value in enumerate(array):\\n if not np.isnan(value):\\n return index\",\n \"def is_match(cells):\\n if len(cells) == 1 and \\\"-\\\" not in cells:\\n return list(cells)[0]\\n return None\",\n \"def find(self, value):\\n for row in range(self.getHeight()):\\n for column in range(self.getWidth()):\\n if self[row][column] == value:\\n return (row, column)\\n return None\",\n \"def find_empty(self):\\n num_rows = len(self.board)\\n num_cols = len(self.board[0])\\n\\n for i in range(num_rows):\\n for j in range(num_cols):\\n if self.board[i][j] == 0:\\n return (i, j)\",\n \"def first_value(self):\\n if not self.is_empty():\\n return self.data[self.head]\\n return None\",\n \"def get_column(col_to_search, value_to_match, col_to_get, table, db_file):\\n \\n try:\\n conn, c = connect_to_db(db_file) \\n c.execute('SELECT {cg} FROM {t} WHERE {col}=\\\"{value}\\\"'.format(t=safe(table), \\n cg=safe(col_to_get), col=safe(col_to_search), value=safe(value_to_match)))\\n column = c.fetchone()\\n conn.close()\\n return column\\n except Exception as e:\\n print(\\\"Error when trying to fetch row in table\\\", table, \\\"in database file\\\", db_file)\\n print(e)\\n return None\",\n \"def _FollowedByEmpty(row, index):\\n return not any(row[index + 1:])\",\n \"def _get_next_element(cls, d, idx):\\n t = np.where(d[:, 2] > 0)[0]\\n t = t[t > idx]\\n if len(t):\\n return d[t[0], 0], d[t[0], 1], t[0]\\n return None, None, None\",\n \"def find_empty(game_board):\\n for row in range(len(game_board)):\\n for col in range(len(game_board[row])):\\n if len(game_board[row][col]) == 2:\\n return row, col\\n for row in range(len(game_board)):\\n for col in range(len(game_board[row])):\\n if len(game_board[row][col]) >= 3:\\n return row, col\\n\\n return None\",\n \"def find_empty_cell():\\n\\n for x in range(1, 38):\\n if worksheet.cell((x, 1)).value == \\\"\\\":\\n date_cell = worksheet.cell((x, 1))\\n description_cell = worksheet.cell((x, 2))\\n payment_received_cell = worksheet.cell((x, 3))\\n rent_due_cell = worksheet.cell((x, 4))\\n\\n return date_cell, description_cell, payment_received_cell, rent_due_cell\\n\\n else:\\n continue\",\n \"def find_row(table, row):\\n for idx in range(len(table)):\\n if table[idx][0] == row:\\n return idx\\n return -1\",\n \"def dbGetFirstRowOneValue(con, cmd, args=[], skipTrace=False):\\n row = dbGetFirstRow(con, cmd, args, skipTrace)\\n trace(\\\"row=\\\" + str(row))\\n if row is not None and len(row) > 0:\\n return row[0]\\n return None\",\n \"def where(self, column_or_label, value=None):\\n column = self._get_column(column_or_label)\\n if value is not None:\\n column = column == value\\n return self.take(np.nonzero(column)[0])\",\n \"def getHeaderRowPosition(sheetData):\\n for index, row in enumerate(sheetData):\\n if row[1] != '':\\n return index\\n return 0\",\n \"def _non_zero_columns_search(array):\\n col_num = array.shape[1]\\n non_zero_col = CArray([], dtype=int)\\n for c in range(col_num):\\n col = array[:, c]\\n if col.any() == True:\\n non_zero_col = non_zero_col.append(c)\\n\\n return non_zero_col\",\n \"def find_col(table, col):\\n return table[0].index(col)\",\n \"def last_valid_index(self) -> Optional[Union[Scalar, Tuple[Scalar, ...]]]:\\n data_spark_columns = self._internal.data_spark_columns\\n\\n if len(data_spark_columns) == 0:\\n return None\\n\\n cond = reduce(lambda x, y: x & y, map(lambda x: x.isNotNull(), data_spark_columns))\\n\\n last_valid_rows = (\\n self._internal.spark_frame.filter(cond)\\n .select(self._internal.index_spark_columns)\\n .tail(1)\\n )\\n\\n # For Empty Series or DataFrame, returns None.\\n if len(last_valid_rows) == 0:\\n return None\\n\\n last_valid_row = last_valid_rows[0]\\n\\n if len(last_valid_row) == 1:\\n return last_valid_row[0]\\n else:\\n return tuple(last_valid_row)\",\n \"def null_check(cur,code,table,passvalue):\\n cur.execute(code)\\n result = cur.fetchall()[0][0]\\n if result == passvalue:\\n print(f\\\"Data Quality check passed. {table} doesn't have any null values.\\\")\\n else:\\n print(f\\\"Data quality check failed. {table} has null values.\\\")\",\n \"def fetchone(self):\\n #if self._state == self._STATE_NONE:\\n # raise exc.ProgrammingError(\\\"No query yet\\\")\\n\\n # Sleep until we're done or we have some data to return\\n #self._fetch_while(lambda: not self._data and self._state != self._STATE_FINISHED)\\n if not self._data:\\n return None\\n elif self._rownumber >= len( self._data.rows ):\\n return None\\n else:\\n result = self._data.rows[self._rownumber]\\n\\n\\n correctedData = OrderedDict()\\n #Insure correct field order\\n for column in self._data.columns:\\n correctedData[column] = result[column]\\n\\n #result = tuple( result.values() )\\n result = tuple( correctedData.values() )\\n result = tuple( correctedData.values() )\\n self._rownumber += 1\\n return result\",\n \"def get_rows(column_to_search, value_to_match, table, db_file):\\n \\n try:\\n conn, c = connect_to_db(db_file) \\n c.execute('SELECT * FROM {t} WHERE {col}=\\\"{value}\\\"'.format(t=safe(table), \\n col=safe(column_to_search), value=value_to_match))\\n row = c.fetchall()\\n conn.close()\\n return row\\n except Exception as e:\\n print(\\\"Error when trying to get row in table\\\", table, \\\"in\\\", db_file)\\n print(e)\\n return None\",\n \"def select_one(self, table, column, value):\\n select_row = \\\"SELECT * FROM {} WHERE {}='{}' AND delete_status = FALSE;\\\".format(table, column, value)\\n self.cursor.execute(select_row)\\n row = self.cursor.fetchone()\\n return row\",\n \"def first(data, key):\\n for i in data:\\n if key(i):\\n return i\\n return None\",\n \"def __skip_null_values(self, row, index):\\n # If there is no value at the row index,\\n # Return True\\n # Return False if there is a value\\n if row[index] == \\\"\\\":\\n return True\\n else:\\n return False\",\n \"def find_column(self, columns):\\n for column in columns:\\n if self.match(column):\\n return column\\n return None\",\n \"def _find_common_cells(rows_or_columns, cell_value=1):\\n\\n T = np.array(rows_or_columns)\\n if cell_value == 0:\\n return np.where(np.logical_not(np.logical_or.reduce(T)))[0]\\n else:\\n return np.where(np.logical_and.reduce(T))[0]\",\n \"def findFirstFalseValue( data ):\\n #~ idx = np.argmin( data ); \\n #~ if( data[idx] ):\\n #~ return -1;\\n #~ return idx;\\n \\n # argmin seems far less efficient than argmax... (and seems to compute all the list)\\n n = len(data);\\n i = 0; \\n while( i < n ):\\n if( not data[i] ):\\n return i;\\n i += 1;\\n return -1;\",\n \"def get_columns_with_nulls(X, columns_to_scan = \\\"all\\\", rows_to_scan=100000):\\n rows_to_scan = get_rows_to_scan(rows_to_scan, X.shape[0])\\n \\n columns_to_scan = get_list_of_columns_to_check(columns_to_scan, X.columns)\\n mask = np.array(X[columns_to_scan][:rows_to_scan].count() < rows_to_scan)\\n return list(np.array(columns_to_scan)[mask])\",\n \"def _check_row(self):\\n match = None\\n for row in self._board:\\n row_string = ''.join(row)\\n match = re.search(WIN_REGEX, row_string)\\n if match:\\n return match.group()[0]\\n return None\",\n \"def values(self):\\n return [entry.value for entry in self.table if entry.value is not None]\",\n \"def find_position(self, element):\\n for row in range(self.rows):\\n for col in range(self.cols):\\n if self.data[row][col] == element:\\n return row, col\\n return None, None\",\n \"def find_position(self, element):\\n for row in range(self.rows):\\n for col in range(self.cols):\\n if self.data[row][col] == element:\\n return row, col\\n return None, None\",\n \"def find_unsettled_spot(self):\\n\\t\\tfor i in range(9):\\n\\t\\t\\tfor j in range(9):\\n\\t\\t\\t\\tif self.grid[i][j] == 0:\\n\\t\\t\\t\\t\\treturn i, j\\n\\t\\treturn\",\n \"def null_values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetTableNullValueArgs']]]]:\\n return pulumi.get(self, \\\"null_values\\\")\",\n \"def first(self):\\n try:\\n data = self.get_cursor()[0]\\n return self.from_(**self.prepare_data(data))\\n except IndexError:\\n return None\",\n \"def _check_column(self):\\n for column in np.transpose(self._board):\\n col_string = ''.join(column)\\n match = re.search(WIN_REGEX, col_string)\\n if match:\\n return match.group()[0]\\n return None\",\n \"def get_nan_idx(column, df):\\n return df[df[column].isna()].index.values\",\n \"def get_for_id(id,table):\\n # Implement this function\\n for row in range(1, len(table)):\\n for col in range(len(table[0])):\\n if id in table[row][col]:\\n return table[row]\",\n \"def find(a):\\n\\n a = coo_matrix(a, copy=True)\\n a.sum_duplicates()\\n # remove explicit zeros\\n nz_mask = a.data != 0\\n return a.row[nz_mask], a.col[nz_mask], a.data[nz_mask]\",\n \"def find_first_none(self, properties):\\n\\n for drink in properties:\\n iterate_drink = iter(drink)\\n next(iterate_drink)\\n for drink_property in iterate_drink:\\n split_property = drink_property.split(\\\": \\\")[1].split(\\\" //\\\")[0]\\n if split_property == \\\"None\\\":\\n return drink_property\\n return \\\"\\\"\",\n \"def _find_first(self, ast, label):\\n res = self._find_all(ast, label, max_results=1)\\n if len(res):\\n return res[0]\\n return None\",\n \"def find_empty_squares(board):\\n for i in range(len(board)):\\n for j in range(len(board[0])):\\n if board[i][j] == 0:\\n return (i,j) #row , column\\n\\n #if there are no blank squres\\n return None\",\n \"def first(self):\\n return self.head and self.head.value or None\",\n \"def find_column_index(self, columns):\\n for i in range(len(columns)):\\n if self.match(columns[i]):\\n return i\\n return None\",\n \"def _find_min_pair(pandas_matrix):\\n numpy_matrix = pandas_matrix.values\\n mins = np.where(numpy_matrix == np.nanmin(numpy_matrix))\\n min_col_idx = mins[0][0]\\n min_row_idx = mins[1][0]\\n (min_col, min_row) = (pandas_matrix.index[min_col_idx], \\n pandas_matrix.columns[min_row_idx])\\n\\n return (min_col, min_row)\",\n \"def get_next_row(table, names):\\n\\n if isinstance(table, list):\\n if not table:\\n return None, True\\n else:\\n return table.pop(0), False\\n else:\\n row = table.fetchone()\\n if row is None:\\n return None, True\\n else:\\n return dict(zip(names, row)), False\",\n \"def trim_empty_rows(self, table: Table):\\n self._requires_table(table)\\n\\n empty = []\\n for idx in reversed(table.index):\\n row = table[idx]\\n if any(value is not None for value in row):\\n break\\n empty.append(idx)\\n\\n table.delete_rows(empty)\",\n \"def get_empty_cells(grid):\\n empty = []\\n for j,row in enumerate(grid):\\n for i,val in enumerate(row):\\n if not val:\\n empty.append((j,i))\\n return empty\",\n \"def _find_zero(board):\\n for r_index, row in enumerate(board):\\n for c_index, num in enumerate(row):\\n if num == 0:\\n return r_index, c_index\",\n \"def find_first_unexplored(self, bool_matrix):\\n current_spot = self.beginning\\n while not (current_spot.row_num == len (self.matrix)-1\\n and current_spot.col_num == len(self.matrix[0])-1):\\n if bool_matrix[current_spot.row_num][current_spot.col_num] == 0:\\n return (current_spot.row_num, current_spot.col_num) \\n current_spot = current_spot.walk_right()#####\\n if (current_spot.row_num == len (self.matrix)-1\\n and current_spot.col_num == len(self.matrix[0])-1):\\n if bool_matrix[current_spot.row_num][current_spot.col_num] == 0:\\n return (current_spot.row_num, current_spot.col_num) \\n if current_spot.character == 0:\\n return (self.row_num, self.col_num)\\n return False\",\n \"def fakes(self, nodes):\\n\\n # get a view of the DataFrame without positional columns\\n non_positional = self.metrics[self.metrics.columns - ['X', 'Y', 'coords', 'm_coords']].ix[nodes]\\n # find rows that are all null, these are the nodes representing the connection to existing infastructure\\n return non_positional[np.all(pd.isnull(non_positional) == True, axis=1)].index.values\",\n \"def find_last_valid_col(row):\\n last_el = len(row) - 1\\n while last_el > 0:\\n col = row[last_el]\\n if col is None or col == \\\"\\\":\\n last_el -= 1\\n continue\\n else:\\n return last_el\\n return last_el\",\n \"def get_unknown_neighbours(self, row, col):\\n return [cell for cell in self.get_neighbours(row, col) if cell.state == None ]\",\n \"def tm_row(self) -> Optional[int]:\\n for row in [1, 2, 3]:\\n if self.label in PeriodicTable.transition_metals(row):\\n return row\\n\\n return None\",\n \"def get_columns_with_all_nulls(X, columns_to_check='all', rows_to_scan='all'):\\n rows_to_scan = get_rows_to_scan(rows_to_scan, X.shape[0])\\n columns_to_check = get_list_of_columns_to_check(columns_to_check, X.columns)\\n mask = np.array(X[columns_to_check][:rows_to_scan].count() == 0)\\n return list(np.array(columns_to_check)[mask])\",\n \"def dt_find(search = \\\"\\\",\\n row = None,\\n column = None,\\n tableID = \\\"list\\\",\\n first = False,\\n ):\\n # 'todo need to fix the searching on numbers\\n config = current.test_config\\n browser = config.browser\\n\\n # Calculate the rows that need to be navigated along to find the search string\\n colList = []\\n rowList = []\\n if row == None:\\n r = 1\\n while True:\\n tr = \\\".//*[@id='%s']/tbody/tr[%s]\\\" % (tableID, r)\\n try:\\n elem = browser.find_element_by_xpath(tr)\\n rowList.append(r)\\n r += 1\\n except:\\n break\\n elif isinstance(row, int):\\n rowList = [row]\\n else:\\n rowList = row\\n # Calculate the columns that need to be navigated down to find the search string\\n if column == None:\\n c = 1\\n while True:\\n td = \\\".//*[@id='%s']/tbody/tr[1]/td[%s]\\\" % (tableID, c)\\n try:\\n elem = browser.find_element_by_xpath(td)\\n colList.append(c)\\n c += 1\\n except:\\n break\\n elif isinstance(column, int):\\n colList = [column]\\n else:\\n colList = column\\n s3_debug(\\\"rows %s, columns %s\\\" % (rowList, colList))\\n # Now try and find a match\\n result = []\\n for r in rowList:\\n for c in colList:\\n td = \\\".//*[@id='%s']/tbody/tr[%s]/td[%s]\\\" % (tableID, r, c)\\n try:\\n elem = browser.find_element_by_xpath(td)\\n s3_debug(\\\"got %s, needle %s\\\" % (elem.text, search))\\n if elem.text == search:\\n if first:\\n return (r, c)\\n else:\\n result.append((r, c))\\n except:\\n pass\\n return result\",\n \"def searchColumn(self, table: Table, name: str) -> Column:\\n if table:\\n for col in table.columns:\\n if col.name.lower() == name.lower():\\n return col\\n return None\",\n \"def null_values(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetLogTableNullValueArgs']]]]:\\n return pulumi.get(self, \\\"null_values\\\")\",\n \"def get_cell(self, x, y):\\n x1, y1 = self.transpose_coordinates(x, y)\\n if self.is_in_field(x1, y1):\\n return self._cells[y1][x1]\\n return None\",\n \"def getNonEmptyCells(self):\\n nonemptys = []\\n for ri in range(self.nRow):\\n for ci in range(self.nCol):\\n val = self.vals[ri][ci]\\n if not self.isEmpty(val):\\n row = ri+1\\n col = ci+1\\n nonemptys.append(CellDesc(row=row, col=col, val=val))\\n return nonemptys\",\n \"def find_fit(candidates):\\n try:\\n fit = sorted(candidates.items(), key=lambda x: len(x[1])).pop(0)\\n except AttributeError:\\n return None\\n row, col = fit[0]\\n n = fit[1].pop()\\n if len(fit[1]) == 0:\\n return row, col, n\\n return None\",\n \"def find_blank_lines(f):\\n df = pd.read_csv(f)\\n indices = df.index[df.apply(\\n lambda row: all(row.apply(lambda col: pd.isnull(col))),\\n axis=1)].tolist()\\n\\n return [i + 1 for i in indices]\",\n \"def filter_empty_rows(self, table: Table):\\n self._requires_table(table)\\n\\n empty = []\\n for idx, row in table.iter_lists():\\n if all(value is None for value in row):\\n empty.append(idx)\\n\\n table.delete_rows(empty)\",\n \"def pylookup(self, col1, col2, matrix, index=3):\\n\\n for row in matrix:\\n if col1 == row[0] and col2 == row[1]:\\n return row[index]\\n return None\",\n \"def find(self, key):\\n index = self.quadratic_probe(key)\\n if index != -1:\\n if self.table[index] is not None:\\n return self.table[index]\\n else:\\n return False\\n else:\\n return False\",\n \"def first(self):\\n return self.begin and self.begin.value or None\",\n \"def find_empty_space(board: list) -> tuple:\\n board_length = len(board)\\n for i in range(board_length):\\n for j in range(board_length):\\n if board[i][j] == 0:\\n return (i,j)\",\n \"def getBlank(self):\\n return self.tiles[-1]\",\n \"def find_blank_cell(self, board: list):\\n cells = {}\\n for i in range(9): # Iterate over rows\\n for j in range(9): # Iterate over columns\\n if board[i][j] == 0:\\n cells[str(i) + ' ' + str(j)] = self.count_numbers(board, j, i)\\n m = max(cells.values())\\n for k in cells:\\n if cells[k] == m:\\n s = k.split()\\n x, y = int(s[1]), int(s[0])\\n return x, y\",\n \"def nonull(val):\\n return val if not pd.isnull(val) else None\",\n \"def get_empty_cells(grid):\\n\\tempty = []\\n\\tfor j,row in enumerate(grid):\\n\\t\\tfor i,val in enumerate(row):\\n\\t\\t\\tif not val:\\n\\t\\t\\t\\tempty.append((j,i))\\n\\treturn empty\",\n \"def find(self, value):\\n for position in range(self.get_size()):\\n if self.table[position] == value:\\n return position\",\n \"def findEmpty(grid):\\n for x in range(len(grid.board)):\\n for y in range(len(grid.board[0])):\\n if grid.board[x][y] == 0:\\n return [x,y]\",\n \"def get_rownumber(self, first_col_val):\\n\\n try:\\n (col_name, col_contents) = self.data[0]\\n col_data = [col_name] + col_contents\\n return col_data.index(first_col_val)\\n except ValueError:\\n return None\",\n \"def find_coordinates(self, value):\\n cells = {v.coordinates for v in self.cells if v.value == value}\\n return cells if len(cells) > 0 else None\",\n \"def peek(self):\\r\\n if self.point_to_head.chi == None:\\r\\n return None\\r\\n return self.point_to_head.chi.val\",\n \"def find_empty_cell(d):\\n for i in range(5):\\n if d[i][x-1] == '.':\\n y = i\\n return y\",\n \"def calc_null(self):\\n null = 0\\n for x in range(0, self.tot_col):\\n for y in range(1, self.tot_rows + 1):\\n if self.file_list[y][x].lower() == 'null':\\n null += 1\\n print('Total number of null fields: ' + str(null))\\n results.append('Total number of null fields: ' + str(null))\",\n \"def null_handler(df):\\n \\n # define ok as hue = True\\n ok = np.array([~pd.isnull(df['hue'])])[0]\\n \\n # filter arrays\\n r = df['red'][ok]\\n g = df['green'][ok]\\n b = df['blue'][ok]\\n h = df['hue'][ok]\\n s = df['saturation'][ok]\\n v = df['value'][ok]\\n t = df['timestamp'][ok]\\n dBT = df['dBT'][ok]\\n dt = df['datetime'][ok] \\n \\n return (r,g,b,h,s,v,t,dBT,dt)\",\n \"def getFirst(self, t):\\n index = self._findFirst(t)\\n if index >= 0:\\n return self.jobs[index]\\n else:\\n return None\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.64960337","0.634782","0.633694","0.6331864","0.6245917","0.6233299","0.60606706","0.60600805","0.5962007","0.5913134","0.5856047","0.5801559","0.57643837","0.57631135","0.5742628","0.5713552","0.56185967","0.5603105","0.559049","0.55511755","0.54848987","0.5481309","0.54790294","0.5473898","0.54591984","0.54591745","0.54491323","0.5446869","0.5445198","0.54064846","0.5399407","0.53986686","0.5391335","0.5350845","0.5349636","0.53444886","0.53328174","0.53034276","0.52910995","0.52892596","0.52830595","0.5273274","0.5263868","0.5260696","0.52602243","0.52383584","0.5231375","0.52232766","0.5223032","0.52137154","0.5198074","0.5198074","0.5171738","0.51642984","0.5155816","0.5123798","0.5121483","0.51159304","0.5107462","0.51042736","0.5102913","0.5095624","0.5094114","0.50912625","0.50912213","0.5064257","0.5058997","0.5058718","0.50529","0.5048725","0.5040697","0.49832812","0.4979195","0.49752766","0.49722388","0.4970763","0.4970218","0.49692407","0.49630183","0.49606928","0.49509627","0.4950931","0.49453816","0.49320042","0.49291113","0.4926657","0.4926557","0.4926268","0.49262413","0.4920933","0.49200106","0.4916898","0.49147975","0.49029544","0.48926553","0.48914152","0.48864055","0.4865334","0.4859808","0.48459867"],"string":"[\n \"0.64960337\",\n \"0.634782\",\n \"0.633694\",\n \"0.6331864\",\n \"0.6245917\",\n \"0.6233299\",\n \"0.60606706\",\n \"0.60600805\",\n \"0.5962007\",\n \"0.5913134\",\n \"0.5856047\",\n \"0.5801559\",\n \"0.57643837\",\n \"0.57631135\",\n \"0.5742628\",\n \"0.5713552\",\n \"0.56185967\",\n \"0.5603105\",\n \"0.559049\",\n \"0.55511755\",\n \"0.54848987\",\n \"0.5481309\",\n \"0.54790294\",\n \"0.5473898\",\n \"0.54591984\",\n \"0.54591745\",\n \"0.54491323\",\n \"0.5446869\",\n \"0.5445198\",\n \"0.54064846\",\n \"0.5399407\",\n \"0.53986686\",\n \"0.5391335\",\n \"0.5350845\",\n \"0.5349636\",\n \"0.53444886\",\n \"0.53328174\",\n \"0.53034276\",\n \"0.52910995\",\n \"0.52892596\",\n \"0.52830595\",\n \"0.5273274\",\n \"0.5263868\",\n \"0.5260696\",\n \"0.52602243\",\n \"0.52383584\",\n \"0.5231375\",\n \"0.52232766\",\n \"0.5223032\",\n \"0.52137154\",\n \"0.5198074\",\n \"0.5198074\",\n \"0.5171738\",\n \"0.51642984\",\n \"0.5155816\",\n \"0.5123798\",\n \"0.5121483\",\n \"0.51159304\",\n \"0.5107462\",\n \"0.51042736\",\n \"0.5102913\",\n \"0.5095624\",\n \"0.5094114\",\n \"0.50912625\",\n \"0.50912213\",\n \"0.5064257\",\n \"0.5058997\",\n \"0.5058718\",\n \"0.50529\",\n \"0.5048725\",\n \"0.5040697\",\n \"0.49832812\",\n \"0.4979195\",\n \"0.49752766\",\n \"0.49722388\",\n \"0.4970763\",\n \"0.4970218\",\n \"0.49692407\",\n \"0.49630183\",\n \"0.49606928\",\n \"0.49509627\",\n \"0.4950931\",\n \"0.49453816\",\n \"0.49320042\",\n \"0.49291113\",\n \"0.4926657\",\n \"0.4926557\",\n \"0.4926268\",\n \"0.49262413\",\n \"0.4920933\",\n \"0.49200106\",\n \"0.4916898\",\n \"0.49147975\",\n \"0.49029544\",\n \"0.48926553\",\n \"0.48914152\",\n \"0.48864055\",\n \"0.4865334\",\n \"0.4859808\",\n \"0.48459867\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7773614"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13091,"cells":{"query":{"kind":"string","value":"Creates a parser and parses arguments. View help for valid flags and inputs. Make sure that subjects are aligned on the same line for all text files. For instance, if a subject's path to epi data is found on line 10 of the file containing paths to epi data, the subject's anatomical, output directory, and, optionally, subject id information should also be found on line 10 of the inputted text files."},"document":{"kind":"string","value":"def parse_args(args):\n\n parser = argparse.ArgumentParser(\n description=\"\"\"Generates and runs an afni_proc.py script to preprocess resting state fMRI data\"\"\",\n formatter_class=argparse.RawDescriptionHelpFormatter)\n\n # Optional Flags\n parser.add_argument(\"-t\", \"--trs_remove\", action=\"store\", default=5, type=int, metavar='TRs',\n help=\"\"\"number of trs to remove at the beginning of the epi data\n (default = 5 trs)\"\"\")\n parser.add_argument(\"-d\", \"--dim_voxel\", action=\"store\", default=2.0, type=float, metavar='MM',\n help=\"voxel dimensions in mm that processed epi will be resampled to (default = 2.0 mm)\")\n parser.add_argument(\"-b\", \"--bandpass\", action=\"store\", default=[0.01, 0.25], nargs=2, type=float, metavar=\"F\",\n help=\"bandpass frequencies lower and upper limits (default = 0.01 0.25)\")\n parser.add_argument(\"-v\", \"--volumes\", action=\"store\", default=0, type=int, metavar=\"V\",\n help=\"\"\"truncate the epi data to the inputted number of volumes, useful if subjects have data \n with different numbers of volumes (default = no truncation)\"\"\")\n parser.add_argument(\"-f\", \"--fwhm\", action=\"store\", default=5.0, type=float, metavar=\"MM\",\n help=\"the full width half maximum that is used when blurring (default = 5.0 mm)\")\n parser.add_argument(\"-c\", \"--cores\", action=\"store\", default=cpu_count(), type=int, metavar=\"C\",\n help=\"number of cores supplied to 3dDeconvolve (default = all cores)\")\n parser.add_argument(\"-s\", \"--subj_id\", action=\"store\", default=\"sub\", metavar=\"SUB\",\n help=\"text file of subject ids (default = sub)\")\n parser.add_argument(\"-T\", \"--time_step\", action=\"store\", default=0, type=float, metavar=\"TS\",\n help=\"set the time step for bandpassing (default = ts in header info\")\n\n parser.add_argument(\"-g\", \"--global_signal_regression\", action=\"store_false\", default=True,\n help=\"do not perform global signal regression (default = perform gsr)\")\n\n parser.add_argument(\"-r\", \"--rerun\", action=\"store_true\", default=False,\n help=\"\"\"rerun preprocessing, override and delete previous results in \n 'Processed' folder (default = don't override)\"\"\")\n parser.add_argument(\"-m\", \"--motion_param\", action=\"store_true\", default=False,\n help=\"use 12 motion parameters for regression (default = 6 motion parameters)\")\n parser.add_argument(\"-G\", \"--gm_blur\", action=\"store_true\", default=False,\n help=\"blur only in grey matter mask (default = blur in whole brain)\")\n parser.add_argument(\"-n\", \"--nl_reg\", action=\"store_true\", default=False,\n help=\"use non-linear warp between anatomical and MNI template (default = linear warp)\")\n\n # Required Inputs\n required = parser.add_argument_group(\"required arguments\")\n required.add_argument(\"-e\", \"--epi\", action=\"store\", required=True,\n help=\"text file of paths to raw epi data\")\n required.add_argument(\"-a\", \"--anat\", action=\"store\", required=True,\n help=\"text file of paths to raw anatomical data\")\n required.add_argument(\"-o\", \"--out_dir\", action=\"store\", required=True, metavar=\"OUT\",\n help=\"text file of paths to output directory\")\n result = parser.parse_args(args)\n\n # Make sure inputted parameters are legal\n assert (os.path.isfile(result.epi)), \"{} does not exist or is not a file\".format(result.epi)\n assert (os.path.isfile(result.anat)), \"{} does not exist or is not a file\".format(result.ant)\n assert (result.trs_remove >= 0), \"Cannot remove negative trs\"\n assert (result.dim_voxel >= 0), \"Cannot have a negative voxel dimension\"\n assert (np.all(np.array(result.bandpass) > 0)), \"Cannot have a negative frequency limit for bandpassing\"\n assert (result.volumes > -1), \"Number of volumes must be greater than 0\"\n assert (result.cores > 0), \"Number of cores used must be greater than 0\"\n assert (result.time_step > -1), \"Time step must be greater than 0\"\n\n return result"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def parser():\n \n \n parser = ap.ArgumentParser(description='Parsing some file names in various forms')\n group = parser.add_mutually_exclusive_group()\n group.add_argument('-f','--filepaths',dest='filepaths',metavar='PATH1,PATH2,...',type=str,\n help='Input a string or list of strings. ex. '\n '\"C:\\\\Users\\\\Matt\\\\Desktop\\\\FireEyeCodingSample\\\\learn.txt\",'\n '\"foo\\\\bar\\\\fudge\"''Note: On Unix systems, you need quotes or you need to escape your escape characters.'\n 'Otherwise, your resultant tokens may be incorrect.')\n group.add_argument('-i','--input',dest='file',metavar='TEXTFILE',type=str,\n help='Input a valid file path to a text file of '\n 'paths. ex. '\n '\"C:\\\\Users\\\\Matt\\\\Desktop\\\\FireEyeCodingSample\\\\learn.txt\"')\n \n \n args = parser.parse_args()\n\n if args.file and not os.path.isfile(args.file):\n raise OSError('This file does not exist - please input a valid file path')\n \n return args","def get_args():\n\n # Make argparse object, add description\n parser = argparse.ArgumentParser(\n formatter_class=argparse.RawTextHelpFormatter,\n description=textwrap.dedent(\n '''\n summary:\n Takes a VCF file and parses the variants to produce a tab delimited \n variant report.\n '''\n ))\n\n\n # Version info\n parser.add_argument(\n '-v', '--version', action='version', \n version=\n '%(prog)s\\nversion:\\t{}\\nlast updated:\\t{}'.format(\n __version__, __updated__\n ))\n\n\n # Arguments (see help string for full descriptions):\n # REQUIRED: VCF file input\n parser.add_argument(\n 'input', action='store', \n help='Filepath to input VCF file. REQUIRED.'\n )\n\n\n # OPTIONAL: Output folder, defaults to current directory if empty\n parser.add_argument(\n '-O', '--output', action='store', \n help=textwrap.dedent(\n '''\n Filepath to folder where output reports will be saved. \n If missing, defaults to current directory.\n \\n'''\n ))\n\n\n # OPTIONAL: List of preferred transcripts\n parser.add_argument(\n '-t', '--transcripts', action='store', \n help=textwrap.dedent(\n '''\n Filepath to preferred transcripts file. \n\n Must be a tab seperated file with preferred transcripts in the second \n column. If missing, all entries in the preferred transcript column \n will be labelled as 'Unknown'.\n \\n'''\n ))\n\n\n # OPTIONAL: Preferred transcripts strictness\n parser.add_argument(\n '-T', '--transcript_strictness', action='store', default='low', \n help=textwrap.dedent(\n '''\n Strictness of matching while annotating preferred transcripts.\n Default setting is low.\n\n Options: \n\n high - Transcripts must be an exact match. \n e.g. NM_001007553.2 and NM_001007553.1 won't match,\n NM_001007553.1 and NM_001007553.1 will.\n\n low - Transcripts will match regardless of the version number. The \n version number is after the . at the end of a transcript \n e.g. NM_001007553.2 and NM_001007553.1 will match.\n \\n'''\n ))\n\n\n # OPTIONAL: either a single BED file or a folder containing BED \n # files, only one of these can be used\n bed_files = parser.add_mutually_exclusive_group()\n\n # Single BED file\n bed_files.add_argument(\n '-b', '--bed', action='store', \n help=textwrap.dedent(\n '''\n Filepath to a single BED file. \n\n The BED file will be applied to the variant report and a seperate\n report saved with the BED file applied. This report will be saved in \n the same output folder as the original variant report, with the BED \n file name added to it.\n Cannot be used together with -B flag.\n \\n'''\n ))\n\n # Multiple BED files\n bed_files.add_argument(\n '-B', '--bed_folder', action='store', \n help=textwrap.dedent(\n '''\n Filepath to folder containing BED files. \n\n Each BED file will be applied to the variant report and a seperate\n report saved with the BED file applied. These reports will be saved in\n a new folder within the output folder, named the same as the input BED\n folder. \n The file names will be the same as the original variant report, with \n the BED file name added to them.\n Cannot be used together with -b flag.\n \\n'''\n ))\n\n\n # OPTIONAL: File containing known variants\n parser.add_argument(\n '-k', '--known_variants', action='store', \n help=textwrap.dedent(\n '''\n Filepath to known variants file. \n\n This is a VCF file containing any known variants and an associated \n classification. The classification will be added to the variant \n report. The VCF must have an annotation named 'Classification' within \n the INFO field for each variant.\n\n Key:\n 0 - Artifact\n 1 - Benign\n 2 - Likely benign\n 3 - VUS\n 4 - Likely pathogenic\n 5 - Pathogenic\n \\n'''\n ))\n\n\n # OPTIONAL: File containing the headers for the report\n parser.add_argument(\n '-c', '--config', action='store', \n help=textwrap.dedent(\n '''\n Filepath to config file. \n\n This is a tab seperated text file containing a number of rows, where \n each row specifies an annotation to be included in the variant report.\n Only annotations included in the config file will be included in the\n variant report.\n The columns in the variant report will be in the same order as the \n order in which the annotations appear in the config file.\n\n Each row contains:\n\n Column 1 - Required. Annotation headers, these must match up with how\n they appear in the VCF (case sensitive).\n\n Column 2 - Required. Location where to find the data within the VCF, \n used to select the correct parsing function.\n options: info, format, vep, filter or pref.\n\n Column 3 - Optional. Alternative name for column header.\n\n To make a config file with all available options from a VCF, run:\n vcf_parse -l path_to_input_vcf > config.txt\n \\n'''\n ))\n\n\n # OPTIONAL: Lists all headers in a vcf then exits\n parser.add_argument(\n '-l', '--config_list', action='store_true', \n help=textwrap.dedent(\n '''\n Return a list of all availabile config to the screen, then exit.\n See CONFIG section for usage.\n \\n'''\n ))\n\n\n # OPTIONAL: Filter out any variants where FILTER column is not PASS\n parser.add_argument(\n '-F', '--filter_non_pass', action='store_true', \n help=textwrap.dedent(\n '''\n Filters out any variants where the FILTER annotation is not \n PASS. If missing then there will be no fitering based on the\n FILTER annotation.\n \\n'''\n ))\n\n return parser.parse_args()","def parse_arguments(args):\n\n parser = argparse.ArgumentParser(\n description=\"Text2Text: Read input text training files, output item files and train a model\"\n )\n\n parser.add_argument(\n \"-i\",\n \"--input-text-path\",\n type=str,\n required=True,\n metavar=\"INPUT_TEXT_PATH\",\n help=\"Text input file name. Format: in each line, OUTPUT_ID1,OUTPUT_ID2,OUTPUT_ID3,...\\t INPUT_TEXT \\\n where OUTPUT_IDs are the zero-based output item indices corresponding to the line numbers of OUTPUT_ITEM_PATH. We assume utf-8 encoding for text.\",\n )\n\n parser.add_argument(\n \"-q\",\n \"--output-item-path\",\n type=str,\n required=True,\n metavar=\"OUTPUT_ITEM_PATH\",\n help=\"Output item file name. Format: each line corresponds to a representation of the output item. We assume utf-8 encoding for text.\",\n )\n\n parser.add_argument(\n \"-m\",\n \"--model-folder\",\n type=str,\n required=True,\n metavar=\"MODEL_FOLDER\",\n help=\"Output model folder name\",\n )\n\n parser.add_argument(\n \"--workspace-folder\",\n type=str,\n default=None,\n metavar=\"WORKSPACE_FOLDER\",\n help=\"A folder name for storing intermediate variables during training\",\n )\n\n vectorizer_config_group_parser = parser.add_mutually_exclusive_group()\n vectorizer_config_group_parser.add_argument(\n \"--vectorizer-config-path\",\n type=str,\n default=None,\n metavar=\"VECTORIZER_CONFIG_PATH\",\n help=\"Json file for vectorizer config (default tfidf vectorizer)\",\n )\n\n vectorizer_config_group_parser.add_argument(\n \"--vectorizer-config-json\",\n type=str,\n default='{\"type\":\"tfidf\", \"kwargs\":{}}',\n metavar=\"VECTORIZER_CONFIG_JSON\",\n help='Json-format string for vectorizer config (default {\"type\":\"tfidf\", \"kwargs\":{}})',\n )\n\n parser.add_argument(\n \"--dtype\",\n type=lambda x: np.float32 if \"32\" in x else np.float64,\n default=np.float32,\n help=\"data type for the csr matrix. float32 | float64. (default float32)\",\n )\n\n parser.add_argument(\n \"--max-leaf-size\",\n type=cli.comma_separated_type(int),\n default=[100],\n metavar=\"INT-LIST\",\n help=\"The max size of the leaf nodes of hierarchical 2-means clustering. Multiple values (separated by comma) are supported and will lead to different individual models for ensembling. (default [100])\",\n )\n\n parser.add_argument(\n \"--nr-splits\",\n type=int,\n default=2,\n metavar=\"INT\",\n help=\"number of splits used to construct hierarchy (a power of 2 is recommended, default 2)\",\n )\n\n parser.add_argument(\n \"--imbalanced-ratio\",\n type=float,\n default=0.0,\n metavar=\"FLOAT\",\n help=\"Value between 0.0 and 0.5 (inclusive). Indicates how relaxed the balancedness constraint of 2-means can be. Specifically, if an iteration of 2-means is clustering L labels, the size of the output 2 clusters will be within approx imbalanced_ratio * 2 * L of each other. (default 0.0)\",\n )\n\n parser.add_argument(\n \"--imbalanced-depth\",\n type=int,\n default=100,\n metavar=\"INT\",\n help=\"After hierarchical 2-means clustering has reached this depth, it will continue clustering as if --imbalanced-ratio is set to 0.0. (default 100)\",\n )\n\n parser.add_argument(\n \"--label-embed-type\",\n type=cli.comma_separated_type(str),\n default=\"pifa\",\n metavar=\"STR-LIST\",\n help=\"Label embedding types. (default pifa).\\\n We support pifa, pifa_lf_concat::Z=path, and pifa_lf_convex_combine::Z=path::alpha=scalar_value,\\\n where path is the additional user-porivded label embedding path and alpha is the scalar value for convex combination.\\\n Multiple values (separated by comma) are supported and will lead to different individual models for ensembling.\",\n )\n\n parser.add_argument(\n \"--indexer\",\n choices=Indexer.indexer_dict.keys(),\n default=\"hierarchicalkmeans\",\n metavar=\"STR\",\n help=f\"Indexer algorithm (default hierarchicalkmeans). Available choices are {', '.join(Indexer.indexer_dict.keys())}\",\n )\n\n parser.add_argument(\n \"--no-spherical\",\n action=\"store_true\",\n default=False,\n help=\"Do not l2-normalize cluster centers while clustering\",\n )\n\n parser.add_argument(\n \"--seed\",\n type=cli.comma_separated_type(int),\n default=[0],\n metavar=\"INT-LIST\",\n help=\"Random seeds (default 0). Multiple values (separated by comma) are supported and will lead to different individual models for ensembling.\",\n )\n\n parser.add_argument(\n \"--max-iter\",\n type=int,\n default=20,\n metavar=\"INT\",\n help=\"The max iteration for indexing (default 20)\",\n )\n\n parser.add_argument(\n \"-n\",\n \"--threads\",\n type=int,\n default=-1,\n metavar=\"INT\",\n help=\"Number of threads to use (default -1 to denote all the CPUs)\",\n )\n\n # Linear matching/ranking parameters\n parser.add_argument(\n \"-s\",\n \"--solver-type\",\n type=str,\n default=\"L2R_L2LOSS_SVC_DUAL\",\n metavar=\"STR\",\n help=\"{} (default L2R_L2LOSS_SVC_DUAL)\".format(\" | \".join(XLINEAR_SOLVERS.keys())),\n )\n\n parser.add_argument(\n \"--Cp\",\n type=float,\n default=1.0,\n metavar=\"VAL\",\n help=\"Coefficient for positive class in the loss function (default 1.0)\",\n )\n\n parser.add_argument(\n \"--Cn\",\n type=float,\n default=1.0,\n metavar=\"VAL\",\n help=\"Coefficient for negative class in the loss function (default 1.0)\",\n )\n\n parser.add_argument(\n \"--bias\", type=float, default=1.0, metavar=\"VAL\", help=\"bias term (default 1.0)\"\n )\n\n parser.add_argument(\n \"-ns\",\n \"--negative-sampling\",\n type=str,\n choices=[\"tfn\", \"man\", \"tfn+man\"],\n default=\"tfn\",\n metavar=\"STR\",\n help=\"Negative Sampling Schemes\",\n )\n\n parser.add_argument(\n \"-t\",\n \"--threshold\",\n type=float,\n default=0.1,\n metavar=\"VAL\",\n help=\"Threshold to sparsify the model weights (default 0.1)\",\n )\n\n # Prediction kwargs\n parser.add_argument(\n \"-k\",\n \"--only-topk\",\n type=int,\n default=20,\n metavar=\"INT\",\n help=\"the default number of top labels used in the prediction\",\n )\n\n parser.add_argument(\n \"-b\",\n \"--beam-size\",\n type=int,\n default=10,\n metavar=\"INT\",\n help=\"the default size of beam search used in the prediction\",\n )\n\n parser.add_argument(\n \"-pp\",\n \"--post-processor\",\n type=str,\n choices=PostProcessor.valid_list(),\n default=\"l3-hinge\",\n metavar=\"STR\",\n help=\"the default post processor used in the prediction\",\n )\n\n parser.add_argument(\n \"--verbose-level\",\n type=int,\n choices=logging_util.log_levels.keys(),\n default=1,\n metavar=\"INT\",\n help=f\"the verbose level, {', '.join([str(k) + ' for ' + logging.getLevelName(v) for k, v in logging_util.log_levels.items()])}, default 1\",\n )\n\n parsed_args = parser.parse_args(args)\n return parsed_args","def parse_args(args):\n parser = argparse.ArgumentParser(description='Parse your tophat align summary')\n parser.add_argument(\"-v\", \"--verbose\", help=\"increase output verbosity\", action='store_true')\n parser.add_argument(\"-m\", \"--mode\", help=\"input type is a directory or file\", choices=['file', 'directory'], default='directory')\n parser.add_argument(\"-i\", \"--input\", metavar='</dir> || file1,file2... ', help=\"provide a list of file or direcotry\")\n parser.add_argument(\"-o\", \"--out\", metavar='outfile.tsv', help=\"name of outputfile\")\n\n return parser.parse_args(args)","def parse_arguments():\r\n # usage = \"usage: %(prog)s [options] <message file>\" + DESCRIPTION\r\n parser = ArgumentParser()\r\n parser.add_argument('-v', '--version', action='version', version=VERSION)\r\n parser.add_argument('csv_files', nargs='+', help='setup csv files')\r\n parser.add_argument('-r', '--res_filter', metavar='string',\r\n dest=\"res_filter\", default='',\r\n help=\"filter given resources, expect main input to be a directory\")\r\n parser.add_argument('-o', '--output_filter', metavar='string',\r\n dest=\"output_filter\", default='',\r\n help=\"if non-empty, filter given resources in output\")\r\n parser.add_argument('-f', '--fixed_start', action=\"store_true\", # or stare_false\r\n dest=\"fixed_start\", default=False, # negative store value\r\n help=\"report fixed start values, start - end value #items\")\r\n parser.add_argument('-q', '--quality', action=\"store_true\", # or stare_false\r\n dest=\"quality\", default=False, # negative store value\r\n help=\"compare setup quality\")\r\n parser.add_argument('-ref', '--reference_only', action=\"store_true\", # or stare_false\r\n dest=\"reference_only\", default=False, # negative store value\r\n help=\"use only refence csv files\")\r\n parser.add_argument('-res', '--result_only', action=\"store_true\", # or stare_false\r\n dest=\"result_only\", default=False, # negative store value\r\n help=\"use only result csv files\")\r\n parser.add_argument('-c', '--compare', metavar='string',\r\n dest=\"setup_compare\", default='',\r\n help=\"if non-empty, show setup quality for given days, e.g. 10,20,30\")\r\n parser.add_argument('-s', '--short_version', action=\"store_true\", # or stare_false\r\n dest=\"short_version\", default=False, # negative store value\r\n help=\"report short version of fixed start values, start - end value #items\")\r\n parser.add_argument('-m', '--maxtrix_values', metavar='string',\r\n dest=\"matrix_values\", default='',\r\n help=\"report setup matrix values for given messagefile\")\r\n parser.add_argument('-t', '--transitions', action=\"store_true\", # or stare_false\r\n dest=\"show_transitions\", default=False, # negative store value\r\n help=\"report transitions\")\r\n \"\"\"\r\n parser.add_argument('-m', '--mat-id', metavar='string', # or stare_false\r\n dest=\"id_mat\", default='', # negative store value\r\n help=\"material id to grep\")\r\n parser.add_argument('-c', '--count', metavar='N', type=int, # or stare_false\r\n dest=\"count\", default=0, # negative store value\r\n help=\"count\")\r\n parser.add_argument('-p', '--pattern', metavar='string', # or stare_false\r\n dest=\"pattern\", default='xxx', # negative store value\r\n help=\"search pattern within logfile\")\r\n \"\"\"\r\n return parser.parse_args()","def parse_arguments():\n\n\tparser = argparse.ArgumentParser(description=\"Markdown to HTML Converter\")\n\tparser.add_argument('md_file', action='store', help='Relative path to the markdown file to convert.')\n\tparser.add_argument('-o', '--output_file', action='store', default=None,\n\t help='Specifies output filename, otherwise uses the original filename with a .html extension')\n\tparser.add_argument('-c', '--contents', action='store_true', default=False,\n\t help='Creates a dynamic contents menu based on the headings in the document.')\n\tparser.add_argument('-n', '--numbered', action='store_true', default=False,\n\t help='Numbers headings and sub headings according to their level.')\n\targs = parser.parse_args()\n\n\tmd_file = os.path.abspath(args.md_file)\n\tif not os.path.exists(md_file):\n\t\traise FileNotFoundError('Markdown file %s does not exist.' % md_file)\n\n\tif args.output_file is None:\n\t\toutput_file = md_file[:-2] + 'html'\n\telse:\n\t\toutput_file = os.path.abspath(args.output_file)\n\n\treturn md_file, output_file, not args.contents, args.numbered","def parse_arguments():\n\n parser = argparse.ArgumentParser(\n description=\"生成用户字符串识别的切分字符串\"\n )\n parser.add_argument(\n \"-o\",\n \"--output_dir\",\n type=str,\n nargs=\"?\",\n help=\"The output directory\",\n default=\"output/\"\n )\n parser.add_argument(\n \"-i\",\n \"--input_file\",\n type=str,\n nargs=\"?\",\n help=\"When set, this argument uses a specified text file as source for the text\",\n default=\"\",\n required=True\n )\n parser.add_argument(\n \"-mi\",\n \"--min_char_count\",\n type=int,\n nargs=\"?\",\n help=\"The minimum number of characters per line, Default is 3.\",\n default=3,\n\n )\n parser.add_argument(\n \"-ma\",\n \"--max_char_count\",\n type=int,\n nargs=\"?\",\n help=\"The maximum number of characters per line, Default is 20.\",\n default=20,\n )\n return parser.parse_args()","def parse_args():\n from argparse import ArgumentParser\n ap = ArgumentParser(prog=__exe__, description=__purpose__)\n ap.add_argument('session', help='Session Label')\n ap.add_argument('-sd', '--subjects_dir', help='Subjects Dir',\n default='/tmp')\n return ap.parse_args()","def make_cli_parser(self):\n usage = \"\"\"\\\npython %prog [OPTIONS] INTERACTIONS_FILE ANNOTATIONS_FILE\n\nARGUMENTS:\n INTERACTIONS_FILE: a CSV file containing interactions. The file\n should have two columns with headings \"interactor1\" and\n \"interactor2\". The file may have additional columns, which will\n be ignored.\n ANNOTATIONS_FILE: a file containing annotations. The annotations\n file may be in one of two formats:\n - GMT format: if the file ends with the extension \".gmt\", it is\n automatically parsed as a GMT-format file. The file is a\n tab-separated (TSV) format with no headers. The first column\n contains the annotation term. The second column contains a\n description. All following columns contain gene IDs for genes\n annotated by that term. Full GMT format specification is\n available from the MSigDB and GSEA website.\n - Two-column format: The file should have a column titled\n \"gene_id\" which has the gene/gene product ID, and a column\n titled \"term\" which contains the term with which the\n gene/product is annotated. The file may have additional\n columns, which will be ignored.\\\n\"\"\"\n self.cli_parser = conflictsparse.ConflictsOptionParser(usage)\n self.cli_parser.add_option('--links-outfile',\n default=LINKS_OUTFILE,\n help=(\"the file to which the links results should \"\n \"be written [default: %default]\")\n )\n self.cli_parser.add_option('--logfile',\n help=(\"the file to which information for the run will \"\n \"be logged [default: {0}]\".format(\n self.logfile_template.format('TIMESTAMP'))\n )\n )","def parse_arguments():\n description = \" \".join(__doc__.splitlines()[4:])\n\n epilog = \", \".join(__doc__.splitlines()[1:4])\n parser = argparse.ArgumentParser(description=description, epilog=epilog)\n parser.add_argument(\n \"-i\",\n type=str,\n help=\"\"\"\n the multiple sequence alignment fasta file with extension .aln to\n use in input\n \"\"\",\n metavar=\"<file>\",\n required=True,\n )\n parser.add_argument(\n \"-o\",\n metavar=\"<file>\",\n type=str,\n help=\"the file where to write the profile numpy array\",\n required=True,\n )\n\n args = parser.parse_args()\n\n return args","def parse_args(self):\n parser = argparse.ArgumentParser(description='Build PDF documentation')\n parser.add_argument('config', help='YAML config file')\n parser.add_argument('-f', '--fast', help='Do not update toc',\n action='store_true', default=False)\n parser.add_argument('-p', '--pandoc', help='Only pandoc, no latex',\n action='store_true', default=False)\n parser.add_argument('-n', '--nocache', help='Disable cache',\n action='store_true', default=False)\n parser.add_argument('-v', '--verbose', help='Enables verbose output; '\n 'repeat up to three time for more verbose output',\n action='count', default=0)\n\n self.args = parser.parse_args()","def cmdline_parser(cls):\n\n # Add arguments that user can specify and put info you can discuss what each options are \n parser = argparse.ArgumentParser(description=\"Produces a plot of a computed potential energy surface.\")\n parser.add_argument('-i', '--input', type=str, default='input.dat', help=\"Name of the input file to be read in\")\n parser.add_argument('-o', '--output', type=str, default='pes.pdf', help=\"Name of the output file to be created.\")\n\n # Store all the arguments from argparse into class variabes\n args = parser.parse_args()\n cls.infile_name = args.input\n cls.outfile_name = args.output\n\n return None","def parse_args():\n\n parser = argparse.ArgumentParser()\n\n parser.add_argument(\n \"-i\", \"--input\", required=True, action=\"store\", dest=\"f_in\", help=\"input file\"\n )\n parser.add_argument(\n \"-o\",\n \"--output\",\n required=True,\n action=\"store\",\n dest=\"f_out\",\n help=\"stem of output file\",\n )\n\n parser.add_argument(\n \"-d\",\n \"--dir\",\n required=True,\n action=\"store\",\n dest=\"dir\",\n help=\"directory to save output files\",\n )\n\n parser.add_argument(\n \"-t\",\n \"--threshold\",\n required=False,\n action=\"store\",\n dest=\"thres\",\n default=0.85,\n help=\"threshold for the scoring function\",\n )\n\n parser.add_argument(\n \"-l\",\n \"--language\",\n required=True,\n action=\"store\",\n dest=\"lang\",\n help=\"provide language in order to set stop words\",\n )\n\n parser.add_argument(\n \"-min\",\n \"--minimum\",\n required=False,\n action=\"store\",\n dest=\"min\",\n default=100,\n help=\"minimum number of occurrences to be considered as ngram\",\n )\n\n parser.add_argument(\n \"--trigram\",\n required=False,\n action=\"store_true\",\n dest=\"trigram\",\n help=\"extracting trigrams in addition to bigrams\",\n )\n\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser('Reading Comprehension on BaiduRC dataset')\n parser.add_argument('--prepare', action='store_true',\n help='create the directories, prepare the vocabulary and embeddings')\n parser.add_argument('--train', action='store_true',\n help='train the model')\n parser.add_argument('--generate', action='store_true',\n help='predict the answers for test set with trained model')\n parser.add_argument('--gentest', action='store_true',\n help='predict the answers for test set with trained model')\n parser.add_argument('--gpu', type=str, default='0',\n help='specify gpu device')\n\n train_settings = parser.add_argument_group('train settings')\n train_settings.add_argument('--optim', default='Adam',\n help='optimizer type')\n train_settings.add_argument('--learning_rate', type=float, default=0.001,\n help='learning rate')\n train_settings.add_argument('--weight_decay', type=float, default=0,\n help='weight decay')\n train_settings.add_argument('--dropout', type=float, default=0,\n help='dropout keep rate')\n train_settings.add_argument('--batch_size', type=int, default=128,\n help='train batch size')\n train_settings.add_argument('--epochs', type=int, default=10,\n help='train epochs')\n\n model_settings = parser.add_argument_group('model settings')\n model_settings.add_argument('--embed_size', type=int, default=128,\n help='size of the embeddings')\n model_settings.add_argument('--hidden_size', type=int, default=256,\n help='size of LSTM hidden units')\n model_settings.add_argument('--max_seq_len', type=int, default=50,\n help='max passage num in one sample')\n model_settings.add_argument('--max_gen_len', type=int, default=50,\n help='max length of passage')\n\n path_settings = parser.add_argument_group('path settings')\n path_settings.add_argument('--vocab_dir', default='../data/vocab/',\n help='the dir to save vocabulary')\n path_settings.add_argument('--model_dir', default='../data/models/',\n help='the dir to store models')\n path_settings.add_argument('--result_dir', default='../data/results/',\n help='the dir to output the results')\n path_settings.add_argument('--summary_dir', default='../data/summary/',\n help='the dir to write tensorboard summary')\n path_settings.add_argument('--log_path',\n help='path of the log file. If not set, logs are printed to console')\n return parser.parse_args()","def prepare_arg_parser():\n\tparser = argparse.ArgumentParser(\n\t\tdescription=\"\"\"Ajout des ponctuations réelles dans un xml de \n\t\t refbibs (NB lent: ~ 2 doc/s sur 1 thread)\"\"\",\n\t\tusage=\"\"\"ragreage.py \n\t\t -x ech/tei.xml/oup_Human_Molecular_Genetics_ddp278.xml\n\t\t -p ech/pdf/oup_Human_Molecular_Genetics_ddp278.pdf\n\t\t -m [bibzone|biblines|bibfields|authornames]\"\"\",\n\t\tepilog=\"- © 2014-15 Inist-CNRS (ISTEX) romain.loth at inist.fr -\"\n\t\t)\n\t\n\t\n\tparser.add_argument('-x','--xmlin',\n\t\tmetavar='path/to/xmlfile',\n\t\thelp=\"\"\"\n\t\tpath to a TEI.xml with citations in <biblStruct> xml format \n\t\t(perhaps to be created from native XML by a call like \n\t\t`saxonb-xslt -xsl:tools/Pub2TEI/Stylesheets/Publishers.xsl\n\t\t-s:exemples_RONI_1513/rsc_1992_C3_C39920001646.xml`)'\"\"\",\n\t\ttype=str,\n\t\trequired=True,\n\t\taction='store')\n\t\t\n\t\n\t\n\tparser.add_argument('-p','--pdfin',\n\t\tmetavar='path/to/pdffile',\n\t\thelp=\"\"\"path to a pdf file of the same text, for attempted\n\t\t pdftottext and citation regexp match\"\"\",\n\t\ttype=str,\n\t\tdefault=None , # cf juste en dessous\n\t\taction='store')\n\t\n\tparser.add_argument('-t','--txtin',\n\t\tmetavar='path/to/txtfile',\n\t\thelp=\"\"\"pdfin can be replaced by a path to a txt flow.\n\t\tThis input text must be very close to the xml content\n\t\t(or segment thereof, in accordance with a chosen -m type)\"\"\",\n\t\ttype=str,\n\t\tdefault=None , # cf juste en dessous\n\t\taction='store')\n\t\t\n\t\n\t\n\tparser.add_argument('-m','--model-type',\n\t\tmetavar='name-of-model',\n\t\thelp=\"\"\"format output as a valid tei's 'listBibl' (default)\n\t\t or tailored to a Grobid crf model pseudotei input among:\n\t\t {'bibzone', 'biblines', 'bibfields', 'authornames'}\"\"\",\n\t\ttype=str,\n\t\tdefault='listBibl' ,\n\t\taction='store')\n\t\n\t\n\tparser.add_argument('-d','--debug',\n\t\tmetavar=1,\n\t\ttype=int,\n\t\thelp='logging level for debug info in [0-3]',\n\t\tdefault=0,\n\t\taction='store')\n\t\n\t\t\n\tparser.add_argument('-r', '--remainder',\n\t\tdest='mask',\n\t\thelp='show mask after matches instead of normal output',\n\t\taction='store_true')\n\t\n\treturn parser","def parse_args():\n parser = argparse.ArgumentParser(description=_program_description)\n parser.add_argument('input_file', help=_input_file_description)\n #parser.add_argument('-v', '--verbose', action='store_true', \n # default=False, help='show progress')\n args = parser.parse_args()\n return args","def cmd_line_parser():\n usage = \"usage: %prog [options]\\n\"\n opt_parser = OptionParser(usage=usage)\n opt_parser.add_option(\"--ai\", action=\"store\", dest=\"alternative_input\",\n help=\"an alternative input file (works only with load_from_pickle)\")\n opt_parser.add_option(\"--dl\", action=\"store\", dest=\"dumped_lexicon\",\n help=\"a dumped lexicon file (works only with load_from_pickle\")\n opt_parser.add_option(\"--dotest\", action=\"store_true\", dest=\"dotest\", default=False,\n help=\"use this flag if you want to apply testing\")\n opt_parser.add_option(\"-t\", action=\"store\", dest=\"test_parses\",\n help=\"the output file for the test parses\")\n opt_parser.add_option(\"-n\", action=\"store\", dest=\"train_parses\",\n help=\"the output file for the train parses\")\n opt_parser.add_option(\"-i\", dest=\"inp_file\", default=\"trainFiles/trainPairs\",\n help=\"the input file names (with the annotated corpus)\")\n opt_parser.add_option(\"--devel\", dest=\"development_mode\", default=False, action=\"store_true\",\n help=\"development mode\")\n\n return opt_parser","def arg_parse():\n parser = argparse.ArgumentParser()\n # defines command line arguments\n parser.add_argument('-i', '--input_file', help=\"The input .txt file \" +\n \"within the current directory (the file you \" +\n \"downloaded from VEP\")\n parser.add_argument('-o', '--output_file', help=\"Name for the output \" +\n \".txt file\")\n\n return parser.parse_args()","def parse_arguments():\n #usage = \"usage: %(prog)s [options] <message file>\" + DESCRIPTION\n parser = ArgumentParser()\n parser.add_argument('-v', '--version', action='version', version=VERSION)\n parser.add_argument('source', metavar='source', help='input logfile or directory with logfiles')\n\n \"\"\"\n parser.add_argument('-m', '--mat-id', metavar='string', # or stare_false\n dest=\"id_mat\", default='', # negative store value\n help=\"material id to grep\")\n parser.add_argument('-c', '--count', metavar='N', type=int, # or stare_false\n dest=\"count\", default=0, # negative store value\n help=\"count\")\n parser.add_argument('-p', '--pattern', metavar='string', # or stare_false\n dest=\"pattern\", default='xxx', # negative store value\n help=\"search pattern within logfile\")\n \"\"\"\n return parser.parse_args()","def cmdline_parser():\n\n # http://docs.python.org/dev/howto/argparse.html\n parser = argparse.ArgumentParser(description=__doc__)\n \n parser.add_argument(\"--verbose\",\n action=\"store_true\",\n help=\"Be verbose\")\n parser.add_argument(\"--debug\",\n action=\"store_true\",\n help=\"Enable debugging\")\n parser.add_argument(\"-b\", \"--bam\",\n required=True,\n help=\"Input BAM file matching vcf\")\n parser.add_argument(\"-i\", \"--vcf\",\n help=\"Input VCF file containing variants to analyze\"\n \" (clashes with --var)\")\n parser.add_argument(\"-v\", \"--var\",\n help=\"Report reads for this variant only. Format: chr:pos:ref-alt\"\n \" (clashes with --vcf)\")\n default = 0\n parser.add_argument(\"--mq-filter\",\n dest=\"min_mq\",\n type=int,\n default=default,\n help=\"Ignore reads with mapping quality below this value (default=%d)\" % default)\n default = 5\n parser.add_argument(\"--bq-filter\",\n dest=\"min_bq\",\n type=int,\n default=default,\n help=\"Ignore reads with bases below this value (default=%d)\" % default)\n parser.add_argument(\"-a\", \"--use-orphan\",\n action=\"store_true\",\n help=\"Don't ignore orphan-reads / anomalous read-pairs\")\n\n return parser","def parse_cli_arguments():\n parser = argparse.ArgumentParser('Generates a MANIFEST file used by the '\n 'HMP2 AnADAMA2 workflows.')\n parser.add_argument('-b', '--broad-data-sheet', required=True,\n help='Broad data product status spreadsheet. '\n 'Contains entries indicating new files to be '\n 'processed.')\n parser.add_argument('-o', '--output-manifest', required=True,\n help='Path to desired output manifest file.')\n parser.add_argument('-oi', '--origin-institute', required=True,\n help='Name of institute submitting new files '\n 'to be processed.')\n parser.add_argument('-oc', '--origin-contact', required=True,\n help='Contact person for corresponding origin '\n 'institute.')\n parser.add_argument('-oe', '--origin-contact-email', required=True,\n help='Contact email for contact person.')\n parser.add_argument('-p', '--project-name', dest='project', \n required=True,\n help='Project that sequence files belong too.')\n\n return parser.parse_args()","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-f\", \"--file\", help=\"file with the cohort you want to check / fix\", type=str, required=True)\n parser.add_argument(\"-o\", \"--outdir\", help=\"where should the files and the result readme be stored?\", type=str, required=True)\n return parser.parse_args()","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument('-u', '--urls_dirpath', type=unicode)\n parser.add_argument('-r', '--resources_dir', type=unicode)\n parser.add_argument('-t', '--total_docs', type=int)\n parser.add_argument('-m', '--mapping', type=unicode,\n help='File with the yago to lkif mapping')\n\n return parser.parse_args()","def cmdline_parser():\n parser = argparse.ArgumentParser(description=\"\"\" \"\"\")\n parser.add_argument(\"-i1\",\n help=\"\"\"viral alignments\"\"\",\n dest=\"viral\",\n required=True)\n parser.add_argument(\"-i2\",\n help=\"\"\"GTA alignments\"\"\",\n dest=\"gta\",\n required=True)\n parser.add_argument(\"-o\",\n dest=\"output\",\n help=\"output image file\")\n return parser","def ParseArguments():\n\t#TODO: check input variable types!\n\t# check for integers ans strings\n\t# check for distance and distance cutoff value: ONLY CERTAIN VALUES ALLOWED\n\targ_parser = argparse.ArgumentParser(description=\"Program to get background distribution matching user input SNPs on the following parameters {MAF, distance to nearest gene, gene density}\")\n\tsubparsers = arg_parser.add_subparsers(dest='subcommand',\n\t\t\t\t\t\t\t\t\t title='subcommands in this script',\n\t\t\t\t\t\t\t\t\t description='valid subcommands. set subcommand after main program required arguments',\n\t\t\t\t\t\t\t\t\t help='You can get additional help by writing <program-name> <subcommand> --help')\n\n\t## Subparsers\n\targ_parser_annotate = subparsers.add_parser('annotate')\n\t#arg_parser_annotate.set_defaults(func=run_annotate)\n\targ_parser_match = subparsers.add_parser('match')\n\t#arg_parser_annotate.set_defaults(func=run_match)\n\n\n\targ_parser.add_argument(\"--user_snps_file\", help=\"Path to file with user-defined SNPs\", required=True) # TODO: make the program read from STDIN via '-'\n\targ_parser.add_argument(\"--output_dir\", help=\"Directory in which output files, i.e. random SNPs will be written\", required=True)\n\t#arg_parser.add_argument(\"--output_dir\", type=ArgparseAdditionalUtils.check_if_writable, help=\"Directory in which output files, i.e. random SNPs will be written\", required=True)\n\targ_parser.add_argument(\"--distance_type\", help=\"ld or kb\", required=True)\n\targ_parser.add_argument(\"--distance_cutoff\", help=\"r2, or kb distance\", required=True)\n\t# NEW: options\n\t#arg_parser.add_argument(\"--status_file\", help=\"Bool (switch, takes no value after argument); if set then logging is ENABLED.\", action='store_true')\n\t#arg_parser.add_argument(\"--status_file\", help=\"If set, a json file will be written. Value should be the a filepath.\")\n\targ_parser.add_argument(\"--web\", help=\"If set, the program will run in web mode. VALUE should be the a filepath to output (temporary) file - usually this will be the session_id. The web mode activates: 1) creating a status_obj and writing it to json file; 2) ENABLE writing a json report file;\")\n\targ_parser.add_argument(\"--NoLogger\", help=\"Bool (switch, takes no value after argument); if set then logging is DISAPLED. Logfile will be placed in outputdir.\", action='store_true')\n\n\n\t### MATCH arguments\n\targ_parser_match.add_argument(\"--N_sample_sets\", type=int, help=\"Number of matched SNPs to retrieve\", required=True) # 1000 - \"Permutations?\" TODO: change name to --n_random_snp_sets or --N\n\t#TODO: add argument that describes if ABSOLUTE of PERCENTAGE deviation should be used\n\targ_parser_match.add_argument(\"--max_freq_deviation\", type=int,help=\"Maximal deviation of SNP MAF bin [MAF +/- deviation]\", default=5) # 5\n\targ_parser_match.add_argument(\"--max_distance_deviation\", type=int, help=\"Maximal PERCENTAGE POINT deviation of distance to nearest gene [distance +/- %%deviation])\", default=5) # 20000\n\t#TODO: CHECK THAT max_distance_deviation > 1 %\n\t#TODO: WHY IS max_genes_count_deviation type float!!!!????\n\targ_parser_match.add_argument(\"--max_genes_count_deviation\", type=float, help=\"Maximal PERCENTAGE POINT deviation of genes in locus [gene_density +/- %%deviation]\", default=5) # 0.2\n\targ_parser_match.add_argument(\"--set_file\", help=\"Bool (switch, takes no value after argument); if set then write out set files to rand_set..gz. Default is false\", action='store_true')\n\n\targs = arg_parser.parse_args()\n\n\treturn args","def parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"in_fq\", help=\"The fastq file containing Hi-C reads.\")\n parser.add_argument(\n \"-r\",\n \"--reference\",\n required=True,\n help=\"Path to the reference genome, in FASTA format.\",\n )\n parser.add_argument(\n \"-p\",\n \"--nb_processors\",\n default=1,\n type=int,\n help=\"number of CPUs used for alignment.\",\n )\n parser.add_argument(\n \"-o\",\n \"--out_sam\",\n help=\"Path to the output SAM file for the alignment of in_fq.\",\n )\n parser.add_argument(\n \"-T\",\n \"--tempdir\",\n default=\".\",\n help=\"Directory to write temporary files. Defaults to current directory.\",\n )\n parser.add_argument(\n \"-m\",\n \"--minimap2\",\n default=False,\n action=\"store_true\",\n help=\"Use minimap2 instead of bowtie for the alignment.\",\n )\n parser.add_argument(\n \"-l\",\n \"--min_len\",\n type=int,\n default=20,\n help=\"Minimum length to which reads should be truncated.\",\n )\n return parser.parse_args()","def parse_args():\n help_text = \"\"\"\n Analyzer of the frequency of use of nouns in the headings of posts on hubr.com\n \"\"\"\n parser = argparse.ArgumentParser(\n description=help_text\n )\n parser.add_argument(\n '-p',\n '--pages',\n type=int,\n dest='page_count',\n default=PAGE_COUNT,\n help=f'Number of pages to parse, default is {PAGE_COUNT}.'\n )\n parser.add_argument(\n '-s',\n '--start',\n type=int,\n default=PAGE_START,\n dest='start_page',\n help=f'Start page number, default is {PAGE_START}.',\n )\n parser.add_argument(\n '-t',\n '--top',\n type=int,\n default=TOP_SIZE,\n dest='top_size',\n help=f'The size of the top noun, default is {TOP_SIZE}.',\n )\n\n return parser.parse_args()","def make_parser():\n\n parser = argparse.ArgumentParser(add_help=True)\n\n parser_grp_main = parser.add_argument_group('Arguments')\n\n parser_grp_main.add_argument\n\n parser_grp_main.add_argument(\n \"-i\",\n \"--inp-dir\",\n default = \"out/ln/alias/sst/all_samples\",\n help=\"The folder containing files to tidy.\"\n )\n\n parser_grp_main.add_argument(\n \"-x\",\n \"--xlsx\",\n type=str,\n help=\"The xlsx file containing the metadata to use to find samples and tidy them.\",\n default=\"Sequencing_summary.xlsx\",\n required=False)\n\n parser_grp_main.add_argument(\n \"-b\",\n \"--by-column\",\n nargs='+',\n type=str,\n help=\"The column names from the xlsx file to use to tidy.\",\n default=\"sample_name\",\n required=False)\n \n parser_grp_main.add_argument(\n \"-d\",\n \"--delete\",\n help=\"Delete file only this arg is used. Unsafe. Always run first without this argument and check all files listed to deletion.\",\n default=False,\n type=bool,\n )\n\n return parser","def get_parse():\n parser = argparse.ArgumentParser(description=print(mytext),\n add_help=True,\n formatter_class=argparse.RawTextHelpFormatter)\n requiredNAMED = parser.add_argument_group('required arguments')\n\n requiredNAMED.add_argument(\"-i\", \"--input\",\n required=True,\n default=None,\n dest=\"input\",\n type=str,\n help='''/path/to/VariantsToTable_output.txt\nIt is assumed that there is either a 'locus' or 'unstitched_locus' column.\nThe 'locus' column elements are the hyphen-separated\nCHROM-POS. If the 'unstitched_chrom' column is present, the code will use the\n'unstitched_locus' column for SNP names, otherwise 'CHROM' and 'locus'. The\n'unstitched_locus' elements are therefore the hyphen-separated \nunstitched_locus-unstitched_pos. FREQ columns from VarScan are also \nassumed.\n''')\n requiredNAMED.add_argument(\"-o\",\"--outdir\",\n required=True,\n default=None,\n dest=\"outdir\",\n type=str,\n help='''/path/to/cmh_test_output_dir/\nFile output from cmh_test.py will be saved in the outdir, with the original\nname of the input file, but with the suffix \"_CMH-test-results.txt\"''')\n requiredNAMED.add_argument(\"--case\",\n required=True,\n default=None,\n dest=\"case\",\n type=str,\n help='''The string present in every column for pools in \"case\" treatments.''')\n requiredNAMED.add_argument(\"--control\",\n required=True,\n default=None,\n dest=\"control\",\n type=str,\n help='''The string present in every column for pools in \"control\" treatments.''') \n requiredNAMED.add_argument(\"-p\",\"--ploidy\",\n required=True,\n default=None,\n dest=\"ploidyfile\",\n type=str,\n help='''/path/to/the/ploidy.pkl file output by the VarScan pipeline. This is a python\ndictionary with key=pool_name, value=dict with key=pop, value=ploidy. The code\nwill prompt for pool_name if necessary.''')\n requiredNAMED.add_argument(\"-e\",\"--engines\",\n required=True,\n default=None,\n dest=\"engines\",\n type=int,\n help=\"The number of ipcluster engines that will be launched.\")\n parser.add_argument(\"--ipcluster-profile\",\n required=False,\n default='default',\n dest=\"profile\",\n type=str,\n help=\"The ipcluster profile name with which to start engines. Default: 'default'\")\n parser.add_argument('--keep-engines',\n required=False,\n action='store_true',\n dest=\"keep_engines\",\n help='''Boolean: true if used, false otherwise. If you want to keep\nthe ipcluster engines alive, use this flag. Otherwise engines will be killed automatically.\n(default: False)''')\n\n # check flags\n args = parser.parse_args()\n if not op.exists(args.outdir):\n print(ColorText(f\"FAIL: the directory for the output file(s) does not exist.\").fail())\n print(ColorText(f\"FAIL: please create this directory: %s\" % args.outdir).fail())\n print(ColorText(\"exiting cmh_test.py\").fail())\n exit()\n\n # make sure input and ploidyfile exist\n nopath = []\n for x in [args.input, args.ploidyfile]: # TODO: check for $HOME or other bash vars in path\n if not op.exists(x):\n nopath.append(x)\n\n # if input or ploidy file do not exist:\n if len(nopath) > 0:\n print(ColorText(\"FAIL: The following path(s) do not exist:\").fail())\n for f in nopath:\n print(ColorText(\"\\tFAIL: %s\" % f).fail())\n print(ColorText('\\nexiting cmh_test.py').fail())\n exit()\n\n print('args = ', args)\n return args","def parseArguments():\n parser = argparse.ArgumentParser(description=__doc__.split(\"\\n\")[0])\n\n input = parser.add_argument_group(\"input\",\n description=\"Supported URL list formats.\")\n input.add_argument(\"-g\", \"--gcsv\", nargs=\"?\",\n help=\"path to Google crawl error csv file(s)\")\n input.add_argument(\"-p\", \"--plain\", nargs=\"?\",\n help=\"path to newline separated file(s)\")\n\n output = parser.add_argument_group(\"output\",\n description=\"Supported output formats.\")\n formats = {\"rack\": \"rack-rewrite 301 static redirect\",\n \"csv\": \"comma separated\"}\n output.add_argument(\"-o\", \"--output\", choices=formats.keys(),\n help=\"an output format; one of: \" + pprint.saferepr(formats) +\n \" else, a machine-readable format\")\n output.add_argument(\"-e\", \"--ext\", action=\"store_true\",\n help=\"remove file extension in redirects\")\n output.add_argument(\"-s\", \"--subdomain\", action=\"store_true\",\n help=\"remove subdomains in redirects\")\n\n files = parser.add_argument_group(\"files\",\n description=\"Heuristics regarding filename format.\")\n files.add_argument(\"-u\", \"--utc\", action=\"store_true\",\n help=\"filenames start with a date in UTC format\")\n\n search = parser.add_argument_group(\"search\",\n description=\"Fuzzy search parameters.\")\n search.add_argument(\"-c\", \"--cutoff\", default=0.32, type=float,\n help=\"fuzzy search threshold (float, defaults to: 0.32)\")\n search.add_argument(\"-m\", \"--matches\", default=1, type=int,\n help=\"number of fuzzy search matches (int, defaults to: 1)\")\n\n parser.add_argument(\"-d\", \"--dirs\", nargs=\"?\", default=\".\",\n help=\"path to directory(s) of files\")\n\n return parser.parse_args()","def parse_args(arglist):\n help = dedent(\"\"\"\n Currently this can start with ROIs defined as a surface label on\n fsaverage, labels defined on each subject's native surface, ROIs\n defined on the high-res volume in Freesurfer space, or a statistical\n volume from a subject-level analysis.\n\n You can always pass a filepath (possibly with ``subj`` and ``hemi``\n string format keys to -orig and the program will work out what to\n do from the file type and other arugments. Alternatively, if files\n are in expected places (Freesurfer data hierarchy, lyman analysis\n hierarchy) there are shortcuts for the corresponding image type.\n\n The processing is almost entirely dependent on external binaries\n from FSL and Freesurfer, so both must be availible.\n\n The resulting masks are defined in the space of the first functional\n run. This is also the target of the ``-regspace epi`` registration\n in the main lyman fmri workflows.\n\n The processing here is closely tied to these fmri workflows and requires\n subject-level preprocessing to have been performed. This program\n should be executed from a directory containing a project.py file\n that defines the relevant data and analysis paths.\n\n The script will also write a mosiac png with the mask overlaid on\n the mean functional image defining the epi space. Additionally, it\n will write a json file with the command line argument dictionary\n for provenence tracking.\n\n If an IPython cluster is running, the processing will be executed\n in parallel by default on all availible engines. This can be avoided\n by using the -serial option.\n\n Usage Details\n -------------\n\n \"\"\")\n\n parser = argparse.ArgumentParser(description=help,\n formatter_class=argparse.RawDescriptionHelpFormatter)\n\n # Necessary arguments\n parser.add_argument(\"-s\", \"-subjects\", nargs=\"*\", dest=\"subjects\",\n help=\"lyman subjects argument\")\n parser.add_argument(\"-roi\", required=True,\n help=\"will form name of output mask file\")\n\n # Optional argument (that always applies)\n parser.add_argument(\"-exp\",\n help=\"experiment (can use default from project.py)\")\n\n # Generic input\n parser.add_argument(\"-orig\",\n help=\"path to original file with subj and hemi format keys\")\n\n # Label relavent arguments\n parser.add_argument(\"-label\", help=\"label name if in Freesurfer hierachy\")\n parser.add_argument(\"-native\", action=\"store_true\",\n help=\"orig label is defined on native surface\")\n parser.add_argument(\"-hemi\", choices=[\"lh\", \"rh\"],\n help=\"hemisphere if unilateral label - otherwise combine both\")\n parser.add_argument(\"-sample\",\n choices=[\"white\", \"graymid\", \"pial\", \"cortex\"],\n help=\"shortcut for projection arguments\")\n parser.add_argument(\"-proj\", nargs=4,\n help=\"projection args passed directly mri_label2vol\")\n parser.add_argument(\"-save_native\", action=\"store_true\",\n help=\"save label file after warping from common space\")\n\n # Atlas-type image relevant images\n parser.add_argument(\"-aseg\", action=\"store_true\",\n help=\"atlas image is aseg.mgz\")\n parser.add_argument(\"-id\", type=int, nargs=\"*\",\n help=\"roi id(s) if orig is index volume\")\n\n # Thresholded statistic relevant arguments\n parser.add_argument(\"-contrast\",\n help=\"first-level contrast to binarize z-stat map\")\n parser.add_argument(\"-thresh\", help=\"z-stat threshold\")\n parser.add_argument(\"-unsmoothed\", action=\"store_true\",\n help=\"use unsmoothed fixed effects zstats\")\n parser.add_argument(\"-altmodel\",\n help=\"stat file is from alternative model\")\n\n # Generic execution relevant arguments\n parser.add_argument(\"-serial\", action=\"store_true\",\n help=\"force serial execution\")\n parser.add_argument(\"-debug\", action=\"store_true\",\n help=\"enable debug mode\")\n\n return parser.parse_args(arglist)","def parse_args():\n parser = argparse.ArgumentParser('Reading Comprehension on HOTPOT dataset')\n parser.add_argument('--prepare', action='store_true',\n help='create the directories, prepare the vocabulary and embeddings')\n parser.add_argument('--train', action='store_true',\n help='train the model')\n parser.add_argument('--evaluate', action='store_true',\n help='evaluate the model on dev set')\n parser.add_argument('--predict', action='store_true',\n help='predict the answers for test set with trained model')\n parser.add_argument('--gpu', type=str, default='0',\n help='specify gpu device')\n\n train_settings = parser.add_argument_group('train settings')\n train_settings.add_argument('--mode', type=str,\n default='D-graph',\n help='fine-tune or D-graph')\n train_settings.add_argument('--Bert_model', type=str,\n default='bert-base-uncased',\n help='model of Bert')\n train_settings.add_argument('--at_head', type=int,\n default=1,\n help='The head for graph neural network.')\n train_settings.add_argument('--propagate_count',type=int,default=3,\n help='The number of propagating in graph neural network')\n train_settings.add_argument('--optim', default='adam',\n help='optimizer type')\n train_settings.add_argument('--learning_rate', type=float, default=0.001,\n help='learning rate')\n train_settings.add_argument('--weight_decay', type=float, default=0,\n help='weight decay')\n train_settings.add_argument('--dropout_keep_prob', type=float, default=1,\n help='dropout keep rate')\n train_settings.add_argument('--batch_size', type=int, default=12,\n help='train batch size')\n train_settings.add_argument('--epochs', type=int, default=1,\n help='train epochs')\n train_settings.add_argument('--gradient_accumulation_steps', type=int, default=1,\n help='gradient accumulation steps')\n\n model_settings = parser.add_argument_group('model settings')\n model_settings.add_argument('--max_s_num', type=int, default=6,\n help='max sentence num in one paragraph')\n model_settings.add_argument('--max_p_len', type=int, default=491,\n help='max length of paragraph')\n model_settings.add_argument('--max_s_len', type=int, default=70,\n help='max length of sentence')\n\n path_settings = parser.add_argument_group('path settings')\n\n path_settings.add_argument('--train_files', nargs='+',\n default=['./data/hotpot_train_v1.1_small_refine.json'],\n help='list of files that contain the preprocessed train data')\n path_settings.add_argument('--dev_files', nargs='+',\n default=['./data/hotpot_dev_fullwiki_v1_refine.json'],\n help='list of files that contain the preprocessed dev data')\n path_settings.add_argument('--test_files', nargs='+',\n default=['./data/hotpot_test_fullwiki_v1_refine.json'],\n help='list of files that contain the preprocessed test data')\n path_settings.add_argument('--vocab_dir', default='./vocab/',\n help='the dir to save vocabulary')\n path_settings.add_argument('--model_dir', default='./models/',\n help='the dir to store models')\n path_settings.add_argument('--result_dir', default='./result/',\n help='the dir to output the results')\n path_settings.add_argument('--log_path',\n help='path of the log file. If not set, logs are printed to console')\n return parser.parse_args()","def parse_cmd_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-i\", \"--path_in\", type=str, default=\"data/main/main.csv\", help=\"Path to main.csv\")\n parser.add_argument(\"-o\", \"--path_out\", type=str, default=\"data/main/main_swiss_char.csv\",\n help=\"Path to output file\")\n parser.add_argument(\"-t\", \"--threshold\", type=int, default=80, help=\"threshold of non-swiss-characters to predict text as non-swiss-german\")\n parser.add_argument(\"-p\", \"--print_only\", default=False, action=\"store_true\",\n help=\"Do not write to file - only print non-swiss-char tweets.\")\n\n return parser.parse_args()","def process_arguments():\r\n # Create ArgumentParser object. Description message will be displayed as part of help message if script is run with -h flag\r\n parser = argparse.ArgumentParser(description='Downloads summary of findings for given interpretation request')\r\n # Define the arguments that will be taken.\r\n parser.add_argument('--ir_id', required=True, help='Interpretation request ID')\r\n parser.add_argument('--ir_version', required=True, help='Interpretation request version')\r\n parser.add_argument('-o', '--output_file', required=True, help='Output PDF')\r\n parser.add_argument('--header', required=False, help='Text for header of report')\r\n # Return the arguments\r\n return parser.parse_args()","def __parse_args(self):\n for argument in self.args:\n source_arg = re.match(\"^(--source=(([A-Z]|[a-z]|/|_|[0-9]|.)+))$\", argument)\n input_arg = re.match(\"^(--input=(([A-Z]|[a-z]|/|_|[0-9]|.)+))$\", argument)\n stats_arg = re.match(\"^(--stats=(([A-Z]|[a-z]|/|_|[0-9]|.)+))$\", argument)\n help_arg = re.match(\"^--help$\", argument)\n vars_arg = re.match(\"^--vars$\", argument)\n insts_arg = re.match(\"^--insts$\", argument)\n if source_arg:\n self.sourceFile = source_arg.group(2)\n self.passedArgs.append(\"source\")\n elif input_arg:\n self.inputFile = input_arg.group(2)\n self.passedArgs.append(\"input\")\n elif help_arg:\n print(\"napoveda\")\n sys.exit(0)\n elif stats_arg:\n self.statsFile = stats_arg.group(2)\n self.passedArgs.append(\"stats\")\n elif vars_arg:\n self.passedArgs.append(\"vars\")\n if self.first_stat_arg is None:\n self.first_stat_arg = \"vars\"\n elif insts_arg:\n self.passedArgs.append(\"insts\")\n if self.first_stat_arg is None:\n self.first_stat_arg = \"insts\"\n else:\n raise ArgError(\"Unknown argument or format of the argument! (\" + argument + \")\")","def make_parser():\n p = argparse.ArgumentParser(\n description=\"Visualize and analyze error from oblique/straight tag observations\"\n )\n\n p.add_argument(\"-n\", help=\"name of the test in the config file\")\n\n p.add_argument(\"-t\", help=\"throw out bad tags\", action=\"store_true\")\n\n p.add_argument(\"-v\", help=\"visualize data\", action=\"store_true\")\n\n p.add_argument(\"-i\", help=\"print result data\", action=\"store_true\")\n\n return p","def parse_arguments():\n\n parser = argparse.ArgumentParser()\n\n parser.add_argument(\"--accessions\", help=\"A json file with old/new family mapppings\")\n parser.add_argument(\"--add-header\", help=\"Print descriptive header\",\n action=\"store_true\", default=False)\n parser.add_argument(\"--add-links\", help=\"Creates hyperlinks to available Rfam html content\",\n action=\"store_true\", default=False)\n return parser","def parse_args():\n parser = argparse.ArgumentParser(parents=[kcs_parser],\n conflict_handler='resolve')\n parser.add_argument('percentiles', help=\"Input CSV file with CMIP distribution percentiles\")\n parser.add_argument('steering_table', help=\"Input steering table CSV file\")\n parser.add_argument('--outfile', required=True,\n help=\"Output figure filename. The extension determines the file type.\")\n parser.add_argument('--extra-data', nargs='+', help=\"Model of interest data files. Using this \"\n \"option will overplot the average of the input data.\")\n parser.add_argument('--relative', action='store_true', help=\"Indicate the model data \"\n \"should be calculated as relative change, as opposed to absolute change.\")\n parser.add_argument('--reference-period', type=int, nargs=2,\n help=\"Reference period to normalize the extra data to (if input). \"\n \"Note that this can be different than the reference epoch, that is, \"\n \"the middle of the reference-period does *not* have to correspond \"\n \"to the reference epoch.\")\n parser.add_argument('--reference-epoch', type=int, help=\"Mid-reference period year to \"\n \"which all CMIP data were normalized. If this option is not used, no \"\n \"indicator of the reference point is plotted.\")\n parser.add_argument('--xlabel', default='Year')\n parser.add_argument('--ylabel')\n parser.add_argument('--xrange', type=float, nargs=2)\n parser.add_argument('--yrange', type=float, nargs=2)\n parser.add_argument('--title')\n parser.add_argument('--legend', action='store_true')\n parser.add_argument('--grid', action='store_true')\n parser.add_argument('--extra-label', help=\"Label to indicate the extra model data.\")\n parser.add_argument('--smooth', type=int, nargs='?', const=10)\n\n args = parser.parse_args()\n read_config(args.config)\n setup_logging(args.verbosity)\n\n if args.extra_data:\n args.extra_data = map(pathlib.Path, args.extra_data)\n if not args.reference_period:\n args.reference_period = default_config['data']['extra']['control_period']\n return args","def make_cli_parser(self):\n super(ExpressionBasedArgParser, self).make_cli_parser()\n usage = \"\"\"\\\npython %prog [OPTIONS] INTERACTIONS_FILE ANNOTATIONS_FILE EXPRESSION_FILE\n\nARGUMENTS:\n INTERACTIONS_FILE: a CSV file containing interactions. The file\n should have two columns with headings \"interactor1\" and\n \"interactor2\". It may have an optional column with the heading\n \"weight\", whose values will be used as the weight or confidence\n of the interaction. The file may have additional columns, which\n will be ignored.\n ANNOTATIONS_FILE: a file containing annotations. The annotations\n file may be in one of two formats:\n - GMT format: if the file ends with the extension \".gmt\", it is\n automatically parsed as a GMT-format file. The file is a\n tab-separated (TSV) format with no headers. The first column\n contains the annotation term. The second column contains a\n description. All following columns contain gene IDs for genes\n annotated by that term. Full GMT format specification is\n available from the MSigDB and GSEA website.\n - Two-column format: The file should have a column titled\n \"gene_id\" which has the gene/gene product ID, and a column\n titled \"term\" which contains the term with which the\n gene/product is annotated. The file may have additional\n columns, which will be ignored.\n EXPRESSION_FILE: a CSV file of gene (or gene product) expression\n values. The file should have a column titled \"id\" which has the\n gene (or gene product) ID, and a column titled \"expression\"\n which gives a value for the expression level, or difference in\n expression levels.\\\n\"\"\"\n self.cli_parser.set_usage(usage)","def processArgs(printHelp=False):\n parser = OptionParser()\n\n parser.add_option('-i', '--input',\n dest='input',\n help='Name of the latex file, for example, document.tex',\n metavar='string')\n parser.add_option('-o', '--output',\n dest='output',\n help='Name of the output folder. Default is \"submit\"',\n metavar='string')\n parser.add_option('-x', '--xiv',\n dest='xiv',\n default=False,\n action='store_true',\n help='Converts the figures to PDFs for arXiv.org submission',\n metavar='boolean')\n parser.add_option('-m', '--margin',\n dest='margin',\n help='Size of the bounding box margin in case of arXiv.org submission. Default is 2.',\n metavar='integer')\n\n if printHelp:\n parser.print_help()\n else:\n return parser.parse_args()","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-i\", \"--input\", dest=\"input_file\", help=\"input file or pattern\", default=\"\")\n parser.add_argument(\"-o\", \"--output\", dest=\"output_file\", help=\"output file or pattern\", default=\"\")\n parser.add_argument(\"-d\", \"--debug\", dest=\"debug\", action='store_true')\n parser.add_argument(\"-v\", \"--verbose\", dest=\"verbose\", action='store_true')\n parser.set_defaults(verbose=False)\n parser.set_defaults(debug=False)\n return parser.parse_args()","def common_parser() -> argparse.ArgumentParser:\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-p\", \"--prefix\", type=str, default=\"scatter-\",\n help=\"The prefix of the ouput files. Output will be \"\n \"named like: <PREFIX><N>.bed, in which N is an \"\n \"incrementing number. Default 'scatter-'.\")\n parser.add_argument(\"input\", metavar=\"INPUT\", type=str,\n help=f\"The input file. The format is detected by the \"\n f\"extension. Supported extensions are: \"\n f\"{SUPPORTED_EXTENSIONS_STRING}.\")\n parser.add_argument(\"-P\", \"--print-paths\", action=\"store_true\",\n help=\"If set prints paths of the output files to \"\n \"STDOUT. This makes the program usable in \"\n \"scripts and worfklows.\")\n return parser","def parse_inputs():\n\n parser = argparse.ArgumentParser(description=\"Command line argument handler for ugaudio spectral_average program.\",\n formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n\n # a group of args for verbosity\n group = parser.add_mutually_exclusive_group()\n group.add_argument('-v', '--verbose', action='store_true')\n group.add_argument('-q', '--quiet', action='store_true')\n\n # nfiles\n help_nfiles = 'nfiles to preview (ONLY for testing)'\n parser.add_argument('-g', '--nfiles', default=DEFAULT_NFILES, type=nfiles_int, help=help_nfiles)\n\n # nfft\n help_nfft = 'Nfft'\n parser.add_argument('-n', '--nfft', default=DEFAULT_NFFT, type=nfft_int, help=help_nfft)\n\n # sample rate\n help_rate = 'sample rate (sa/sec)'\n parser.add_argument('-r', '--rate', default=DEFAULT_RATE, type=rate_str, help=help_rate)\n\n # cutoff\n help_cutoff = 'cutoff'\n parser.add_argument('-c', '--cutoff', default=DEFAULT_CUTOFF, type=cutoff_str, help=help_cutoff)\n\n # sensors\n help_sensors = 'sensors'\n parser.add_argument('-s', '--sensors', default=DEFAULT_SENSORS, type=sensors_list, help=help_sensors)\n\n # PAD directory\n help_paddir = 'PAD dir'\n parser.add_argument('-p', '--paddir', default=DEFAULT_PADDIR, type=folder_str, help=help_paddir)\n\n # output directory\n help_outdir = 'output dir'\n parser.add_argument('-o', '--outdir', default=DEFAULT_OUTDIR, type=outdir_str, help=help_outdir)\n\n # start date\n help_start = 'start date'\n parser.add_argument('-d', '--start', default=DEFAULT_START, type=dtm_date, help=help_start)\n\n # end date\n help_end = 'end date'\n parser.add_argument('-e', '--end', default=DEFAULT_END, type=dtm_date, help=help_end)\n\n # parse arguments\n module_logger.debug('calling parse_args')\n args = parser.parse_args()\n\n return args","def parseOptions():\n desc = \"Compute the likelihood of sequences coming from a list of barcodes.\"\n parser = argparse.ArgumentParser(description=desc, add_help=False)\n\n def canonicalizedFilePath(path):\n return os.path.abspath(os.path.expanduser(path))\n\n def checkInputFile(path):\n if not os.path.isfile(path):\n parser.error(\"Input file %s not found.\" % (path,))\n\n def checkOutputFile(path):\n try:\n f = open(path, \"a\")\n f.close()\n except:\n parser.error(\"Output file %s cannot be written.\" % (path,))\n\n basics = parser.add_argument_group(\"Basic required options\")\n basics.add_argument(\n \"cmpH5Filename\",\n type=canonicalizedFilePath,\n metavar=\"CMP.H5\",\n help=\"The filename of the input Bas.H5 file\")\n basics.add_argument(\n \"referenceFasta\",\n type=canonicalizedFilePath,\n metavar=\"REFERENCE_FASTA\",\n help=\"The reference sequences of interest in FASTA format\")\n basics.add_argument(\n \"basH5Fofn\",\n type=canonicalizedFilePath,\n metavar=\"BARCODE_FASTA\",\n help=\"The filename of the barcode FASTA\")\n basics.add_argument(\n \"-o\", \"--outputFilename\",\n type=str,\n default=os.path.join(os.getcwd(), \"output.csv\"),\n metavar=\"CSV\",\n help=\"The filename of the CSV to output barcode scoring data to.\")\n basics.add_argument(\n \"-m\", \"--minSize\",\n type=int,\n default=3,\n metavar=\"INT\",\n help=\"The minimum size of a homopolymer context to record\")\n\n debugging = parser.add_argument_group(\"Verbosity and debugging/profiling\")\n debugging.add_argument(\"--help\", \"-h\",\n action=\"help\")\n debugging.add_argument(\n \"--nZmws\",\n default=-1,\n type=int,\n help=\"Label only the first N ZMWs for testing purposes.\")\n debugging.add_argument(\n \"--verbose\", \"-v\",\n dest=\"verbosity\",\n action=\"count\",\n help=\"Set the verbosity level.\")\n debugging.add_argument(\n \"--quiet\",\n dest=\"quiet\",\n action=\"store_true\",\n help=\"Turn off all logging, including warnings\")\n class PrintVersionAction(argparse.Action):\n def __call__(self, parser, namespace, values, option_string=None):\n print \" RegionTools version: %s\" % __version__\n print \" h5py version: %s\" % h5py.version.version\n print \" hdf5 version: %s\" % h5py.version.hdf5_version\n sys.exit(0)\n debugging.add_argument(\"--version\",\n nargs=0,\n action=PrintVersionAction)\n\n parser.parse_args(namespace=options)\n\n for path in (options.cmpH5Filename, options.referenceFasta, options.basH5Fofn):\n if path is not None:\n checkInputFile(path)\n\n for path in (options.outputFilename,):\n if path is not None:\n checkOutputFile(path)\n\n options.shellCommand = \" \".join(sys.argv)","def prepare_optparser ():\n usage = \"\"\"usage: %prog <-t tfile> [-n name] [-g genomesize] [options]\n\nExample: %prog -t ChIP.bam -c Control.bam -f BAM -g hs -n test -B -q 0.01\n\nor example for broad peak calling: %prog -t ChIP.bam -c Control.bam --broad -g hs\n\n\"\"\"\n description = \"%prog -- Model-based Analysis for ChIP-Sequencing\"\n\n optparser = OptionParser(version=\"%prog \"+MACS_VERSION,description=description,usage=usage,add_help_option=False)\n optparser.add_option(\"-h\",\"--help\",action=\"help\",help=\"show this help message and exit.\")\n optparser.add_option(\"-t\",\"--treatment\",dest=\"tfile\",type=\"string\",\n help=\"ChIP-seq treatment file. REQUIRED.\")\n optparser.add_option(\"-c\",\"--control\",dest=\"cfile\",type=\"string\",\n help=\"Control file.\")\n optparser.add_option(\"-n\",\"--name\",dest=\"name\",type=\"string\",\n help=\"Experiment name, which will be used to generate output file names. DEFAULT: \\\"NA\\\"\",\n default=\"NA\")\n optparser.add_option(\"-f\",\"--format\",dest=\"format\",type=\"string\",\n help=\"Format of tag file, \\\"AUTO\\\", \\\"BED\\\" or \\\"ELAND\\\" or \\\"ELANDMULTI\\\" or \\\"ELANDEXPORT\\\" or \\\"SAM\\\" or \\\"BAM\\\" or \\\"BOWTIE\\\". The default AUTO option will let MACS decide which format the file is. Please check the definition in 00README file if you choose ELAND/ELANDMULTI/ELANDEXPORT/SAM/BAM/BOWTIE. DEFAULT: \\\"AUTO\\\"\",\n default=\"AUTO\")\n optparser.add_option(\"-g\",\"--gsize\",dest=\"gsize\",type=\"string\",default=\"hs\",\n help=\"Effective genome size. It can be 1.0e+9 or 1000000000, or shortcuts:'hs' for human (2.7e9), 'mm' for mouse (1.87e9), 'ce' for C. elegans (9e7) and 'dm' for fruitfly (1.2e8), Default:hs\")\n optparser.add_option(\"-s\",\"--tsize\",dest=\"tsize\",type=\"int\",default=None,\n help=\"Tag size. This will overide the auto detected tag size. DEFAULT: Not set\")\n optparser.add_option(\"--bw\",dest=\"bw\",type=\"int\",default=300,\n help=\"Band width. This value is only used while building the shifting model. DEFAULT: 300\")\n optparser.add_option(\"-q\",\"--qvalue\",dest=\"qvalue\",type=\"float\",default=0.05,\n help=\"Minimum FDR (q-value) cutoff for peak detection. DEFAULT: 0.05 \")\n optparser.add_option(\"-p\",\"--pvalue\",dest=\"pvalue\",type=\"float\",\n help=\"Pvalue cutoff for peak detection. When set (e.g. -p 0.05 or -p 1e-5), qvalue cutoff will be ignored. By default it's not set.\")\n optparser.add_option(\"-m\",\"--mfold\",dest=\"mfold\",type=\"string\",default=\"5,50\",\n help=\"Select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit. DEFAULT:5,50\")\n optparser.add_option(\"--nolambda\",dest=\"nolambda\",action=\"store_true\",\n help=\"If True, MACS will use fixed background lambda as local lambda for every peak region. Normally, MACS calculates a dynamic local lambda to reflect the local bias due to potential chromatin structure. \",\n default=False)\n optparser.add_option(\"--slocal\",dest=\"smalllocal\",type=\"int\",default=1000,\n help=\"The small nearby region in basepairs to calculate dynamic lambda. This is used to capture the bias near the peak summit region. Invalid if there is no control data. If you set this to 0, MACS will skip slocal lambda calculation. *Note* that MACS will always perform a d-size local lambda calculation. The final local bias should be the maximum of the lambda value from d, slocal, and llocal size windows. DEFAULT: 1000 \")\n optparser.add_option(\"--llocal\",dest=\"largelocal\",type=\"int\",default=10000,\n help=\"The large nearby region in basepairs to calculate dynamic lambda. This is used to capture the surround bias. If you set this to 0, MACS will skip llocal lambda calculation. *Note* that MACS will always perform a d-size local lambda calculation. The final local bias should be the maximum of the lambda value from d, slocal, and llocal size windows. DEFAULT: 10000.\")\n optparser.add_option(\"--fix-bimodal\",dest=\"onauto\",action=\"store_true\",\n help=\"Whether turn on the auto pair model process. If set, when MACS failed to build paired model, it will use the nomodel settings, the '--shiftsize' parameter to shift and extend each tags. Not to use this automate fixation is a default behavior now. DEFAULT: False\",\n default=False)\n optparser.add_option(\"--nomodel\",dest=\"nomodel\",action=\"store_true\",\n help=\"Whether or not to build the shifting model. If True, MACS will not build model. by default it means shifting size = 100, try to set shiftsize to change it. DEFAULT: False\",\n default=False)\n optparser.add_option(\"--shiftsize\",dest=\"shiftsize\",type=\"int\",default=100,\n help=\"The arbitrary shift size in bp. When nomodel is true, MACS will use this value as 1/2 of fragment size. DEFAULT: 100 \")\n optparser.add_option(\"--keep-dup\",dest=\"keepduplicates\",type=\"string\",default=\"auto\",\n help=\"It controls the MACS behavior towards duplicate tags at the exact same location -- the same coordination and the same strand. The default 'auto' option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff; and the 'all' option keeps every tags. If an integer is given, at most this number of tags will be kept at the same location. Default: auto\")\n optparser.add_option(\"--to-large\",dest=\"tolarge\",action=\"store_true\",default=False,\n help=\"When set, scale the small sample up to the bigger sample. By default, the bigger dataset will be scaled down towards the smaller dataset, which will lead to smaller p/qvalues and more specific results. Keep in mind that scaling down will bring down background noise more. DEFAULT: False\")\n optparser.add_option(\"--down-sample\",dest=\"downsample\",action=\"store_true\",default=False,\n help=\"When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. Warning: This option will make your result unstable and irreproducible since each time, random reads would be selected. Consider to use 'randsample' script instead. DEFAULT: False\")\n optparser.add_option(\"--shift-control\",dest=\"shiftcontrol\",action=\"store_true\",default=False,\n help=\"When set, control tags will be shifted just as ChIP tags according to their strand before the extension of d, slocal and llocal. By default, control tags are extended centered at their current positions regardless of strand. You may consider to turn this option on while comparing two ChIP datasets of different condition but the same factor. DEFAULT: False\")\n optparser.add_option(\"--half-ext\",dest=\"halfext\",action=\"store_true\",default=False,\n help=\"When set, MACS extends 1/2 d size for each fragment centered at its middle point. DEFAULT: False\")\n optparser.add_option(\"-B\",\"--bdg\",dest=\"store_bdg\",action=\"store_true\",\n help=\"Whether or not to save extended fragment pileup, local lambda and score tracks at every bp into a bedGraph file. DEFAULT: False\",\n default=False)\n optparser.add_option(\"--broad\",dest=\"broad\",action=\"store_true\",\n help=\"If set, MACS will try to call broad peaks by linking nearby highly enriched regions. The linking region is controlled by another cutoff through --linking-cutoff. The maximum linking region length is 4 times of d from MACS. DEFAULT: False\",default=False)\n optparser.add_option(\"--broad-cutoff\",dest=\"broadcutoff\",type=\"float\",default=0.1,\n help=\"Cutoff for broad region. This option is not available unless --broad is set. If -p is set, this is a pvalue cutoff, otherwise, it's a qvalue cutoff. DEFAULT: 0.1 \")\n optparser.add_option(\"--verbose\",dest=\"verbose\",type=\"int\",default=2,\n help=\"Set verbose level. 0: only show critical message, 1: show additional warning message, 2: show process information, 3: show debug messages. DEFAULT:2\")\n return optparser","def parseInputArgs():\n parser = argparse.ArgumentParser(description=\"Unix cut analog\", usage='%(prog)s [arguments]')\n\n # pos arg\n parser.add_argument('filename', type=str, help='input file name')\n\n # req arg\n requiredNamed = parser.add_argument_group('required arguments')\n requiredNamed.add_argument('-f', '--fields', type=str, help='list of fields, separated by comma', required=True)\n # optional args\n parser.add_argument('-s', '--separator', type=str, default='\\t', help='column separator, default tab')\n\n args = parser.parse_args()\n return args","def setup_args():\n parser = ParlaiParser(add_parlai_args=True, description=\"Render data as HTML\")\n conv_render = parser.add_argument_group('Conversation Rendering Arguments')\n conv_render.add_argument(\n \"--input\", \"-i\", help=\"Input file to read conversations from\"\n )\n conv_render.add_argument(\n \"--output\",\n \"-o\",\n help=\"Output file to write conversations to. One of [.pdf, .png, .html] only\",\n )\n conv_render.add_argument(\n \"--width\", \"-wd\", help=\"Width of output file\", type=int, default=8\n )\n conv_render.add_argument(\n \"--height\", \"-ht\", help=\"Height of output file\", type=int, default=10\n )\n conv_render.add_argument(\n \"--user-icon\",\n \"-uic\",\n help=\"Absolute Path/URL to user image icon\",\n default=HUMAN_EMOJI_IMG,\n )\n conv_render.add_argument(\n \"--alt-icon\",\n \"-aic\",\n help=\"Absolute Path/URL to alternate image icon\",\n default=ALT_EMOJI_IMG,\n )\n conv_render.add_argument(\n \"--num-examples\",\n \"-ne\",\n help=\"Number of conversations to render\",\n type=int,\n default=10,\n )\n\n return parser","def ParseArgs() -> argparse.Namespace:\n parser = argparse.ArgumentParser()\n\n parser.add_argument(\n '--input', dest='input', help='Japanese phonetic reading file')\n parser.add_argument(\n '--output_token_array',\n dest='output_token_array',\n help='Output token array file.')\n parser.add_argument(\n '--output_string_array',\n dest='output_string_array',\n help='Output string array file.')\n return parser.parse_args()","def parse_args(args):\n \n # Construct the parser (which is stored in parser)\n # Module docstring lives in __doc__\n # See http://python-forum.com/pythonforum/viewtopic.php?f=3&t=36847\n # And a formatter class so our examples in the docstring look good. Isn't it\n # convenient how we already wrapped it to 80 characters?\n # See http://docs.python.org/library/argparse.html#formatter-class\n parser = argparse.ArgumentParser(description=__doc__, \n formatter_class=argparse.RawDescriptionHelpFormatter)\n \n # General options\n parser.add_argument(\"hal\",\n help=\"HAL file to evaluate\")\n parser.add_argument(\"--truth\",\n help=\"MAF file of a true alignment for precision and recall\")\n parser.add_argument(\"--beds\", nargs=\"*\",\n help=\"BED file(s) of genes on the genomes in the HAL\")\n parser.add_argument(\"--coverage_file\", type=argparse.FileType(\"w\"),\n default = sys.stdout,\n help=\"file to save average coverage vs. the reference in (one number)\")\n parser.add_argument(\"--precision_recall_file\", type=argparse.FileType(\"w\"),\n default = sys.stdout,\n help=\"TSV file to save precision and recall in (two numbers)\")\n parser.add_argument(\"--gene_category_file\", type=argparse.FileType(\"w\"),\n default = sys.stdout,\n help=\"file to save categories and counts for genes in\")\n parser.add_argument(\"--tag\", nargs=\"*\", default=[],\n help=\"extra columns to tag all result TSV lines with at the front\")\n \n # The command line arguments start with the program name, which we don't\n # want to treat as an argument for argparse. So we remove it.\n args = args[1:]\n \n return parser.parse_args(args)","def parse_cli_args():\n\n parser = argparse.ArgumentParser(\n description='Create AMICI model and data for steadystate example.')\n\n parser.add_argument('-s', '--sbml', dest='sbml_file_name',\n required=True,\n help='SBML model filename (PEtab format)')\n\n parser.add_argument('-d', '--model-dir', dest='model_dir',\n help='Model directory containing the python module')\n\n parser.add_argument('-n', '--model-name', dest='model_name',\n required=True,\n help='Name of the AMICI model module')\n\n parser.add_argument('-m', '--measurements', dest='measurement_file_name',\n required=True,\n help='Name of measurement table (PEtab format)')\n\n parser.add_argument('-c', '--conditions', dest='condition_file_name',\n required=True,\n help='Condition table (PEtab format)')\n\n parser.add_argument('-p', '--parameters', dest='parameter_file_name',\n required=True,\n help='Condition table (PEtab format)')\n\n parser.add_argument('-o', dest='hdf5_file_name', default='data.h5',\n help='Name of HDF5 file to generate')\n\n args = parser.parse_args()\n\n return args","def parse_args():\n\n parser = argparse.ArgumentParser()\n\n parser.add_argument(\"-f\", \"--folder\", required=True, action=\"store\", dest=\"folder\", help=\"input folder\")\n parser.add_argument(\"-t\", \"--tool\", required=True, action=\"store\", dest=\"tool\", choices=[\"spacy\",\"stanford\"], help=\"NER tool\")\n parser.add_argument(\"-l\", \"--lang\", required=True, action=\"store\", dest=\"lang\", help=\"language\")\n\n return parser.parse_args()","def get_parser():\n\n parser = ArgumentParser()\n\n req_argument = parser.add_argument_group('required arguments')\n\n parser.add_argument(\"-o\", \"--outdir\", type=str, default='result',\n help=\"Path for results\")\n parser.add_argument(\"-fname\", \"--file_name\", type=str, default=\"try1\",\n help=\"The name the output file should have within the output directory\")\n parser.add_argument(\"-freq\", \"--frequency\", type=str,\n help=\"File to read the haplotype frequencies from\")\n parser.add_argument(\"-over\", \"--overlap\", type=str,\n help=\"File to read the peptide vs alleles or peptide vs haplotype data\")\n parser.add_argument(\"-o_a\", \"--overlap_allele\", type=int, default=0,\n help=\"1 if the --overlap file passed in is peptide vs alleles and 0 if it is peptide vs haplotypes and has already been binarized\")\n # parser.add_argument(\"-n\", \"--ntarget\", type=int, default=5,\n # help=\"The ntarget for max n-times coverage\")\n parser.add_argument(\"-maxpep\", \"--max_number_of_pepts\", type=int, default=30,\n help=\"The maximum number of peptides allowed in a vaccine\")\n parser.add_argument(\"-c\", \"--cut\", type=int, default=3,\n help=\"The cut value for ommitting peptides that are too similar; a value of 0 should be provided if similar peptides are not to be excluded from a vaccine design.\")\n\n\n \n return parser","def parse_command_line():\n parser = argparse.ArgumentParser()\n\n help_str = \\\n 'The collection folder to sort files into. ' \\\n 'If the folder does not exist, it will be created along with the ' \\\n 'necessary contents.'\n parser.add_argument('-c', '--collection', help=help_str)\n\n help_str = \\\n 'The source folder to import files from. Has to exist and ' \\\n 'has to be a folder.'\n parser.add_argument('-s', '--source', help=help_str, required=False)\n\n help_str = \\\n 'View the gallery in random order auto skpping after the' \\\n 'given amount of seconds'\n parser.add_argument('-v', '--view', help=help_str, required=False)\n\n return parser.parse_args()","def help():\n description = \"\"\"\n Pair-wise quantification and comparsion of domains based on two-passes Mahalanobis distance. \n\n Example:\n compareDom.py -f dom.bed -a young -b old -o youngVsOld -na Young -b Old -pcut 0.01 -gtf mm10.gtf\n \"\"\"\n parser = argparse.ArgumentParser(description=description,\n formatter_class=RawTextHelpFormatter)\n parser.add_argument(\"-f\",\n dest=\"domf\",\n required=True,\n type=str,\n help=\"Domain file in .bed format.\")\n parser.add_argument(\n \"-a\",\n dest=\"da\",\n required=True,\n type=str,\n help=\"The data directory generated by cLoops2 pre for the first sample.\"\n )\n parser.add_argument(\n \"-b\",\n dest=\"db\",\n required=True,\n type=str,\n help=\n \"The data directory generated by cLoops2 pre for the second sample.\")\n parser.add_argument(\n \"-na\",\n dest=\"na\",\n type=str,\n required=True,\n help=\n \"Name of first sample, will be shown in the output figure. Only use alphabet and numbers.\"\n )\n parser.add_argument(\n \"-nb\",\n dest=\"nb\",\n type=str,\n required=True,\n help=\"Name of second sample, will be shown in the output figure.\")\n parser.add_argument(\n \"-gtf\",\n dest=\"gtf\",\n default=\"\",\n required=True,\n type=str,\n help=\n \"GTF file annotation for genes. Significant flip/switch overlapped genes will be reported based on the gene annotation file.\"\n )\n parser.add_argument(\n \"-pcut\",\n dest=\"pcut\",\n type=float,\n default=0.01,\n help=\n \"Chi-Square p-value cutoff for detecting siginficant different compartment, default is 0.01.\"\n )\n\n parser.add_argument(\"-o\",\n dest=\"output\",\n required=True,\n type=str,\n help=\"Output prefix.\")\n parser.add_argument(\n \"-p\",\n dest=\"cpu\",\n required=False,\n type=int,\n default=4,\n help=\"How many cpus used for quantification, default is 4.\")\n parser.add_argument(\n \"-xlim\",\n dest=\"xlim\",\n required=False,\n type=str,\n default=None,\n help=\n \"X-axis limitations for the scatter plot, default is autodetermined, set as '1,-1'.\"\n )\n parser.add_argument(\n \"-ylim\",\n dest=\"ylim\",\n required=False,\n type=str,\n default=None,\n help=\n \"Y-axis limitations for the scatter plot, default is autodetermined, set as '1,-1'.\"\n )\n parser.add_argument(\"-vmin\",\n dest=\"vmin\",\n required=False,\n type=str,\n default=None,\n help=\"Minimal scale for the aggregation heatmap.\")\n parser.add_argument(\"-vmax\",\n dest=\"vmax\",\n required=False,\n type=str,\n default=None,\n help=\"Maxmal scale for the aggregation heatmap.\")\n\n op = parser.parse_args()\n return op","def parse_cmdline(cmdline_args):\n option_parser = optparse.OptionParser(usage='usage: %prog [options] <pattern>',\n description='ts short for TextSearch, Grep like tool', prog='ts', add_help_option=False) # -h is a real option\n\n option_parser.add_option('-h', '--help', action='store_true', dest='help', help='Display this information')\n option_parser.add_option('-e', '--extension', action='store', dest='extension', type='string', default=None,\n help='file extension')\n\n group_searching = optparse.OptionGroup(option_parser, 'Regexp selection and interpretation')\n group_searching.add_option('-i', '--ignore-case', action='store_true', dest='ignore_case', default=False,\n help='Ignore case distinctions in the pattern')\n group_searching.add_option('-w', '--word-regexp', action='store_true', dest='word_regexp', default=False,\n help='Force the pattern to match only whole words')\n group_searching.add_option('-l', '--literal', action='store_true', dest='literal', default=False,\n help='Quote all metacharacters; the pattern is literal')\n option_parser.add_option_group(group_searching)\n\n group_miscellaneous = optparse.OptionGroup(option_parser, 'Miscellaneous')\n group_miscellaneous.add_option('--path-only', action='store_true', dest='path_only', default=False,\n help='only print out the matching file')\n group_miscellaneous.add_option('-v', '--invert-match', action='store_true', dest='invert_match', default=False,\n help='Invert the sense of matching, to select non-matching lines.')\n option_parser.add_option_group(group_miscellaneous)\n\n group_output = optparse.OptionGroup(option_parser, 'Output control')\n group_output.add_option('-c', '--count', action='store_true', dest='count', default=False,\n help='Suppress normal output; instead print a count of matching lines for each input file.')\n group_output.add_option('-o', '--only-matching', action='store_true', dest='only_matching', default=False,\n help='Print only the matched (non-empty) parts of a matching line, with each such part on '\n 'a separate output line.')\n option_parser.add_option_group(group_output)\n\n options, args = option_parser.parse_args(cmdline_args)\n return options, args, option_parser","def parse_args():\n parser = argparse.ArgumentParser(description=__doc__)\n # If user doesn't specify an input file, read from standard input. Since\n # encodings are the worst thing, we're explicitly expecting std\n parser.add_argument('-i', '--infile',\n type=lambda x: open(x, encoding=ENCODE_IN),\n default=io.TextIOWrapper(\n sys.stdin.buffer, encoding=ENCODE_IN)\n )\n # Same thing goes with the output file.\n parser.add_argument('-o', '--outfile',\n type=lambda x: open(x, 'w', encoding=ENCODE_OUT),\n default=io.TextIOWrapper(\n sys.stdout.buffer, encoding=ENCODE_OUT)\n )\n # Set the verbosity level for the logger. The `-v` option will set it to\n # the debug level, while the `-q` will set it to the warning level.\n # Otherwise use the info level.\n verbosity = parser.add_mutually_exclusive_group()\n verbosity.add_argument('-v', '--verbose', action='store_const',\n const=logging.DEBUG, default=logging.INFO)\n verbosity.add_argument('-q', '--quiet', dest='verbose',\n action='store_const', const=logging.WARNING)\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser()\n \n parser.add_argument('--p', dest='path_in',\n action='store', type=str, required=True, default='',\n help=\"Path relative to the data/ directory, to the input ATL01, ANC13, and ANC27 files.\")\n parser.add_argument('--atl01', dest='atl01_file',\n action='store', type=str, required=False, default=None,\n help=\"Path + filename to directory of the ATL01.\")\n parser.add_argument('--anc13', dest='anc13_path',\n action='store', type=str, required=False, default=None,\n help=\"Path to outputs directory of the ANC13.\") \n parser.add_argument('--anc27', dest='anc27_path',\n action='store', type=str, required=False, default=None,\n help=\"Path to directory of the ANC27.\")\n\n args = parser.parse_args()\n \n return args","def __parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument('-f', '--force', action=\"store_true\", default=False,\n help='overwrite existing database files during import')\n parser.add_argument('-e', '--extension', action=\"store\", default='txt',\n help='specify file extension. default is \"txt\"')\n parser.add_argument('-d', '--delimiter', action=\"store\", default='\\t',\n help='specify column delimiter. default is tab (\\\\t)')\n parser.add_argument('-m', '--mark', action=\"store\", default='.',\n help='specify decimal mark for numeric data. default is'\n ' dot (.)')\n parser.add_argument('-o', '--outformat', action=\"store\", default='npz',\n help='specify output database format. default is \"npz\"'\n ' for numpy database. use \"mat\" for matlab '\n ' database format.')\n parser.add_argument('-r', '--recursive', action=\"store_true\", default=False,\n help='recursively walk through all sub-directories of'\n ' current working directory')\n parser.add_argument('-p', '--pcs', action=\"store_true\", default=True,\n help='indicate if files are pcs files.')\n parser.add_argument('-c', '--colheadlines', action=\"store\", default='1',\n help='number of lines spanned by the column headers')\n args = parser.parse_args()\n return args","def parse_arguments():\n parser = argparse.ArgumentParser(description=\"Parse Diff Exp output files\")\n parser.add_argument(\"raw_file\", help=\"DE analysis output file (.tab).\")\n parser.add_argument(\"output_json\", help=\"Output JSON\")\n parser.add_argument(\"output_file\", help=\"Output file\")\n parser.add_argument(\"--gene_id\", help=\"Gene_IDs column name\", type=str)\n parser.add_argument(\"--fdr\", help=\"FDR column name\", type=str)\n parser.add_argument(\"--pvalue\", help=\"Pvalue column name\", type=str)\n parser.add_argument(\"--fwer\", help=\"FWER column name\", type=str)\n parser.add_argument(\"--logodds\", help=\"Log Odds column name\", type=str)\n parser.add_argument(\"--logfc\", help=\"logfc column name\", type=str)\n parser.add_argument(\"--stat\", help=\"Statistics column name\", type=str)\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser(\n description='Convert CVAT XML annotations to YOLO format'\n )\n\n parser.add_argument(\n '--cvat-xml', metavar='FILE', required=True,\n help='input file with CVAT annotation in xml format'\n )\n\n parser.add_argument(\n '--image-dir', metavar='DIRECTORY', required=False,\n help='directory which contains original images'\n )\n\n parser.add_argument(\n '--output-dir', metavar='DIRECTORY', required=True,\n help='directory for output annotations in YOLO format'\n )\n\n parser.add_argument(\n '--username', metavar='USERNAME', required=False,\n help='Username from CVAT Login page, required to download images'\n )\n\n parser.add_argument(\n '--password', metavar='PASSWORD', required=False,\n help='Password from CVAT Login page, required to download images'\n )\n\n parser.add_argument(\n '--labels', metavar='ILABELS', required=False,\n help='Labels (separated by comma) to extract. Example: car,truck,motorcycle'\n )\n\n return parser.parse_args()","def make_parser():\n parser_ = argparse.ArgumentParser(\n description=\"\"\"\n A tool to retrieve history from\n (almost) any browser on (almost) any platform\n\n██████╗ ██████╗ ██████╗ ██╗ ██╗███████╗███████╗██████╗ ██╗ ██╗██╗███████╗████████╗ ██████╗ ██████╗ ██╗ ██╗\n██╔══██╗██╔══██╗██╔═══██╗██║ ██║██╔════╝██╔════╝██╔══██╗ ██║ ██║██║██╔════╝╚══██╔══╝██╔═══██╗██╔══██╗╚██╗ ██╔╝\n██████╔╝██████╔╝██║ ██║██║ █╗ ██║███████╗█████╗ ██████╔╝█████╗███████║██║███████╗ ██║ ██║ ██║██████╔╝ ╚████╔╝\n██╔══██╗██╔══██╗██║ ██║██║███╗██║╚════██║██╔══╝ ██╔══██╗╚════╝██╔══██║██║╚════██║ ██║ ██║ ██║██╔══██╗ ╚██╔╝\n██████╔╝██║ ██║╚██████╔╝╚███╔███╔╝███████║███████╗██║ ██║ ██║ ██║██║███████║ ██║ ╚██████╔╝██║ ██║ ██║\n╚═════╝ ╚═╝ ╚═╝ ╚═════╝ ╚══╝╚══╝ ╚══════╝╚══════╝╚═╝ ╚═╝ ╚═╝ ╚═╝╚═╝╚══════╝ ╚═╝ ╚═════╝ ╚═╝ ╚═╝ ╚═╝\n \"\"\", # noqa: E501\n epilog=\"\"\"\n Checkout the GitHub repo\n https://github.com/pesos/browser-history\n if you have any issues or want to help contribute\"\"\",\n formatter_class=RawDescriptionHelpFormatter,\n )\n\n parser_.add_argument(\n \"-t\",\n \"--type\",\n default=\"history\",\n help=f\"\"\"\n argument to decide whether to retrieve history or bookmarks.\n Should be one of {AVAILABLE_TYPES}.\n Default is history.\"\"\",\n )\n parser_.add_argument(\n \"-b\",\n \"--browser\",\n default=\"all\",\n help=f\"\"\"\n browser to retrieve history or bookmarks from. Should be one\n of all, default, {AVAILABLE_BROWSERS}.\n Default is all (gets history or bookmarks from all browsers).\n \"\"\",\n )\n\n parser_.add_argument(\n \"-f\",\n \"--format\",\n default=\"infer\",\n help=f\"\"\"\n Format to be used in output. Should be one of {AVAILABLE_FORMATS}.\n Default is infer (format is inferred from the output file's\n extension. If no output file (-o) is specified, it defaults to csv)\"\"\",\n )\n\n parser_.add_argument(\n \"-o\",\n \"--output\",\n default=None,\n help=\"\"\"\n File where history output or bookmark output is to be written.\n If not provided, standard output is used.\"\"\",\n )\n\n parser_.add_argument(\n \"-p\",\n \"--profile\",\n default=None,\n help=\"\"\"\n Specify the profile from which to fetch history or bookmarks. If\n not provided all profiles are fetched\n \"\"\",\n )\n\n parser_.add_argument(\n \"--show-profiles\",\n default=None,\n metavar=\"BROWSER\",\n help=f\"\"\"\n List all available profiles for a given browser where browser\n can be one of default, {AVAILABLE_BROWSERS}. The browser\n must always be provided.\n \"\"\",\n )\n\n parser_.add_argument(\n \"-v\", \"--version\", action=\"version\", version=\"%(prog)s \" + __version__\n )\n\n return parser_","def _cli_parser():\n parser = argparse.ArgumentParser()\n # Original flags\n parser.add_argument('-s', type=str, metavar='input_vol',\n help=\"Absolute path to input volume. Input should be \"\n \"in nifti format\")\n parser.add_argument('-o', type=str, metavar='output_dir',\n help=\"Absolute path to output directory\")\n parser.add_argument('-p', type=str, metavar='template_type', default='MNI152_orig',\n help=\"Type of volumetric template used in index files. \"\n \"Use MNI152_orig or Colin27_orig when -r is \"\n \"RF_ANTs. Use MNI152_norm or Colin27_norm when \"\n \"-r is RF_M3Z. Otherwise, an exception is raised. \"\n \"Ensure that the template matches the standard \"\n \"space of -i (i.e., use MNI152_* if -i is \"\n \"in MNI152-space). Default: MNI152_orig\")\n parser.add_argument('-r', type=str, metavar='RF_type', default='RF_ANTs',\n help=\"Type of Registration Fusion approaches used to \"\n \"generate the mappings (RF_M3Z or RF_ANTs). \" \n \"RF_M3Z is recommended if data was registered \" \n \"from subject's space to the volumetric atlas \" \n \"space using FreeSurfer. RF_ANTs is recommended \" \n \"if such registrations were carried out using \" \n \"other tools, especially ANTs. Default: RF_ANTs\")\n parser.add_argument('-i', type=str, metavar='interp', default='linear',\n help=\"Interpolation (linear or nearest). If \"\n \"-g is label.gii, then interpolation is always set \"\n \"to nearest and a warning is raised. Default: \"\n \"linear\")\n # New flags\n parser.add_argument('-t', type=str, metavar='out_type', default='nii.gz',\n help=\"File type of surface files. nii.gz is true to \"\n \"the original Wu et al (2018) implementation. \"\n \"Note that gifti formats, either \"\n \"func.gii or label.gii, are often preferred. \"\n \"Default: nii.gz\")\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser(\n description=\"Subscription Watch CSV file packaging script\", prog=sys.argv[0])\n\n # required args\n parser.add_argument(\"-f\", \"--filepath\", required=True,\n help=\"path to files to package\")\n parser.add_argument(\n \"-s\",\n \"--max-size\",\n type=int,\n default=DEFAULT_MAX_SIZE,\n help=f\"Maximum size of packages in MiB. (Default: {DEFAULT_MAX_SIZE} MiB)\",\n )\n parser.add_argument(\n \"-o\", \"--overwrite\", action=\"store_true\", default=False, help=\"whether to overwrite existing files.\"\n )\n parser.add_argument(\"--ocp-cluster-id\", required=True,\n help=\"OCP Cluster ID\")\n parser.add_argument(\"-v\", \"--verbosity\", action=\"count\",\n default=0, help=\"increase verbosity (up to -vvv)\")\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser(description=\"Sequence Cleaner: Remove Duplicate Sequences, etc\",\n epilog=\"example > sequence_cleaner -q INPUT -o OUTPUT\")\n parser.add_argument('-v', '--version', action='version', version='sequence_cleaner {}'.format(version))\n parser.add_argument(\"-q\", \"--query\", help=\"Path to directory with FAST(A/Q) files\", required=True)\n parser.add_argument(\"-o\", \"--output_directory\", help=\"Path to output files\", required=True)\n parser.add_argument(\"-ml\", \"--minimum_length\", help=\"Minimum length allowed (default=0 - allows all the lengths)\",\n default=\"0\")\n parser.add_argument(\"-mn\", \"--percentage_n\", help=\"Percentage of N is allowed (default=100)\", default=\"100\")\n parser.add_argument('--keep_all_duplicates', help='Keep All Duplicate Sequences', action='store_false', required=False)\n parser.add_argument('--remove_ambiguous', help='Remove any sequence with ambiguous bases', action='store_true', required=False)\n\n parser.add_argument('-l', '--log', help='Path to log file (Default: STDOUT).', required=False)\n\n return parser.parse_args()","def parser():\n fetch_all_news_codes()\n load_config_key()\n\n if not sys.argv[1:]:\n print(\"Arguments needed. Use argument --help/-h for more information.\")\n else:\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--show_all\", \"-sa\", action=\"store_true\",\n help=\"Shows all available news channel codes.\")\n parser.add_argument(\"--categories\", \"-c\", action=\"store_true\",\n help=\"Shows all available news categories.\")\n parser.add_argument(\"--show\", \"-s\", action=\"store\",\n help=\"Shows all news channel codes for a specified category.\")\n parser.add_argument(\"--news\", \"-n\", type=str, help=\"Shows news articles \"\n \"for a specified news channel code.\")\n args = parser.parse_args()\n\n if args.show_all:\n show_sources_all()\n elif args.categories:\n show_categories()\n elif args.show:\n show_sources_category(args.show)\n elif args.news:\n if args.news in news_codes:\n show_news(args.news, BASE_URL)\n else:\n print(\"Invalid news code.\")\n sys.exit(1)","def processArgs(self, argv):\n parser = OptionParser(usage=usage)\n parser.add_option(\"-a\", \"--show_ADT\", action=\"store_true\", dest=\"show_ADT\",\n default=self.show_ADT, help=\"Display ADT value if set\")\n parser.add_option(\"-f\", \"--show_file\", action=\"store_true\", dest=\"show_file\",\n default=self.show_file, help=\"Display matching filename if set\")\n parser.add_option(\"-t\", \"--show_time\", action=\"store_true\", dest=\"show_time\",\n default=self.show_time, help=\"Display message time\")\n parser.add_option(\"-v\", \"--show_visitID\", action=\"store_true\", dest=\"show_visitID\",\n default=self.show_visitID, help=\"Display visit ID\")\n parser.add_option(\"-p\", \"--show_pc\",\n action=\"store_true\",\n dest=\"show_pc\",\n default=self.show_pc,\n help=\"Display patient class\")\n\n (options, pargs) = parser.parse_args()\n if len(pargs) < 3:\n parser.error(\"incorrect number of arguments\")\n\n self.show_ADT = parser.values.show_ADT\n self.show_file = parser.values.show_file\n self.show_time = parser.values.show_time\n self.show_visitID = parser.values.show_visitID\n self.show_pc = parser.values.show_pc\n \n self.segments_of_interest = pargs.pop(0)\n if len(self.segments_of_interest) != 3:\n parser.error(\"segment '%s' looks incorrect, expected something like 'PV1'\"\n % self.segments_of_interest)\n\n try:\n nums = pargs.pop(0).split(\",\")\n for num in nums:\n if 'MSH' == self.segments_of_interest:\n num = int(num) - 1\n self.sequences.append(int(num))\n except:\n parser.error(\"sequence must be an integer, separate multiple w/ comma and no spaces\")\n\n for patternOrFile in pargs:\n for file in glob.glob(patternOrFile):\n if not os.path.isfile(file):\n parser.error(\"can't open input file %s\" % file)\n self.filelist.append(file)\n \n # Require at least one file\n if not len(self.filelist):\n parser.error(\"at least one input file is required\")","def get_cmd_line_args():\n parser = argparse.ArgumentParser(\n description=DOC, formatter_class=argparse.RawTextHelpFormatter)\n\n # Required arguments\n required = parser.add_argument_group(\"Required arguments\")\n required.add_argument(\n \"--fastq-regex\", required=True, type=is_fastq_regex, metavar=\"<regex>\",\n help=\n \"Snakemake regex used to infer the FASTQ files to process and the \"\n \"related wildcards: {sample} (mandatory), {lane} (optional) and \"\n \"{end} (mandatory if paired-end sequencing), e.g. \"\n \"/path/to/data/{sample}/{sample}_{ignore1}_{lane}_{end}_001.fastq.gz\"\n )\n required.add_argument(\n \"--outdir\", required=True, metavar=\"<dir>\", help=\"Output directory.\"\n )\n required.add_argument(\n \"--ref-build\", required=True, metavar=\"<version>\", help=\n \"Reference genome build, e.g. hg19 or mm10. Assuming the existence of \"\n \"the 3 following files in <--ref-genome-dir>: <ref build>.fa \"\n \"<ref build>.fa.fai and <ref build>.fa.dict\"\n )\n required.add_argument(\n \"--ref-genome-dir\", metavar=\"<dir>\", help=\n \"Bisulfite reference genome directory, including '<ref build>.fa', \"\n \"'<ref build>.fa.fai', '<ref build>.fa.dict' and the \"\n \"'Bisulfite_Genome' directory created by running the \"\n \"'bismark_genome_preparation' script. See README.md documentation.\"\n )\n\n\n # Optional general arguments\n optional = parser.add_argument_group(\"Optional\")\n optional.add_argument(\n \"--single-end\", action=\"store_false\", dest=\"paired_end\", help=\n \"By default paired-end sequencing is assumed, for single-end set this \"\n \"flag.\"\n )\n optional.add_argument(\n \"--rrbs\", action=\"store_true\", help=\n \"For Reduced Representation Bisulfite Sequencing (RRBS) set this flag.\"\n )\n optional.add_argument(\n \"--no-deduplication\", action=\"store_false\",\n dest=\"use_bismark_deduplicate\", help=\n \"Set this flag to not apply Bismark BAM deduplication. The deduplica\"\n \"tion removes reads with similar start/end positions on a given chromo\"\n \"some. It is not a valid PCR correction for RRBS or amplicon data. \"\n \"The deduplication is not applied if the --rrbs flag is set.\"\n )\n optional.add_argument(\n \"--non-directional-library\", action=\"store_false\",\n dest=\"directional_library\", help=\n \"By default the library is assumed to be directional, if not set this \"\n \"flag. See Bismark documentation for more information.\"\n )\n optional.add_argument(\n \"--target-bed\", type=is_file, metavar=\"<path>\", help=\n \"For targeted sequencing, the path to the BED file listing the regions\"\n \" targeted. Used only for read coverage computation. If no BED is pro\"\n \"vided the coverage will be computed on the whole reference genome.\"\n )\n optional.add_argument(\n \"--target-kit\", metavar=\"<name>\", help=\n \"For targeted sequencing, the name of the kit used to target to be \"\n \"reported in the preprocessing report. Does not affect processing.\"\n )\n optional.add_argument(\n \"--phred\", type=int, choices={33, 64}, default=DEFAULT_OF[\"phred\"],\n metavar=\"<33|64>\", help=\n \"Base quality encoding of input FASTQ files: 33|64, by default %i.\"\n % DEFAULT_OF[\"phred\"]\n )\n optional.add_argument(\n \"--r1-id\", default=DEFAULT_OF[\"r1_id\"], metavar=\"<ID>\", help=\n \"Case-insensitive ID used to identify R1 (forward) reads in paired-end\"\n \" sequencing, by default '%s'.\" % DEFAULT_OF[\"r1_id\"]\n )\n optional.add_argument(\n \"--r2-id\", default=DEFAULT_OF[\"r2_id\"], metavar=\"<ID>\", help=\n \"Case-insensitive ID used to identify R2 (reverse) reads in paired-end\"\n \" sequencing, by default '%s'.\" % DEFAULT_OF[\"r2_id\"]\n )\n optional.add_argument(\n \"--read-length\", type=int, metavar=\"<int>\", help=\n \"Length of reads (e.g. 150) to write in the HTML report. \"\n \"Does not affect the processing.\"\n )\n\n # Optional FastQC arguments\n fastqc = parser.add_argument_group(\"FastQC optional\")\n optional.add_argument(\n \"--fastqc-threads\", type=int, metavar=\"<int>\",\n default=DEFAULT_OF[\"fastqc\"][\"threads\"], help=\n \"FastQC '--threads' argument, by default %i.\"\n % DEFAULT_OF[\"fastqc\"][\"threads\"]\n )\n\n # Optional Trim Galore arguments\n trim_galore = parser.add_argument_group(\"Trim Galore optional\")\n ADAPTERS_URL = (\n \"https://support.illumina.com/bulletins/2016/12/what-sequences-do-i\"\n \"-use-for-adapter-trimming.html\")\n trim_galore.add_argument(\n \"--adapter-r1\", metavar=\"<sequence>\", help=\n \"Trim Galore '--adapter' argument: adapter sequence to be trimmed off \"\n \"read 1. Common sequences: %s\" % ADAPTERS_URL\n )\n trim_galore.add_argument(\n \"--adapter-r2\", metavar=\"<sequence>\", help=\n \"Trim Galore '--adapter2' argument: adapter sequence to be trimmed \"\n \"off read 2. Common sequences: %s\" % ADAPTERS_URL\n )\n trim_galore.add_argument(\n \"--quality\", type=int, default=DEFAULT_OF[\"trim_galore\"][\"quality\"],\n metavar=\"<int>\", help=\n \"Trim Galore '--quality' argument, by default %i.\"\n % DEFAULT_OF[\"trim_galore\"][\"quality\"]\n )\n trim_galore.add_argument(\n \"--stringency\", type=int, metavar=\"<int>\",\n default=DEFAULT_OF[\"trim_galore\"][\"stringency\"], help=\n \"Trim Galore '--stringency' argument: overlap with adapter sequence \"\n \"required to trim, by default %i (very stringent).\"\n % DEFAULT_OF[\"trim_galore\"][\"stringency\"]\n )\n trim_galore.add_argument(\n \"--min-length\", type=int, metavar=\"<int>\",\n default=DEFAULT_OF[\"trim_galore\"][\"min_length\"], help=\n \"Trim Galore '--length' argument: minimum read length after trimming \"\n \"otherwise removed, by default %i.\"\n % DEFAULT_OF[\"trim_galore\"][\"min_length\"]\n )\n trim_galore.add_argument(\n \"--error-rate\", type=float, metavar=\"<float>\",\n default=DEFAULT_OF[\"trim_galore\"][\"error_rate\"], help=\n \"Trim Galore '-e' argument: maximum allowed error rate with the \"\n \"matching region, by default {}\"\n .format(DEFAULT_OF[\"trim_galore\"][\"error_rate\"])\n )\n trim_galore.add_argument(\n \"--max-n\", type=int, metavar=\"<int>\", help=\n \"Trim Galore '--max_n' argument: Maximum number of 'N's in a read \"\n \"otherwise removed. By default not applied.\"\n )\n trim_galore.add_argument(\n \"--trim-n\", action=\"store_true\", help=\n \"Trim Galore '--trim-n' argument: remove 'N's from ends of the read.\"\n )\n trim_galore.add_argument(\n \"--clip-r1-5p\", type=int, metavar=\"<int>\", help=\n \"Trim Galore '--clip_R1' argument: remove basepairs from 5' end of \"\n \"read 1. Useful if there is a methylation bias at this end.\"\n )\n trim_galore.add_argument(\n \"--clip-r2-5p\", type=int, metavar=\"<int>\", help=\n \"Trim Galore '--clip_R2' argument: remove basepairs from 5' end of \"\n \"read 2. Useful if there is a methylation bias at this end.\"\n )\n trim_galore.add_argument(\n \"--clip-r1-3p\", type=int, metavar=\"<int>\", help=\n \"Trim Galore '--three_prime_clip_R1' argument: remove basepairs from \"\n \"3' end of read 1. Useful if there is a methylation bias at this end.\"\n )\n trim_galore.add_argument(\n \"--clip-r2-3p\", type=int, metavar=\"<int>\", help=\n \"Trim Galore '--three_prime_clip_R2' argument: remove basepairs from \"\n \"3' end of read 2. Useful if there is a methylation bias at this end.\"\n )\n\n # Optional Bismark tools arguments\n bismark = parser.add_argument_group(\"Bismark optional\")\n bismark.add_argument(\n \"--seed-mismatch\", type=int, choices=[0, 1], metavar=\"<0|1>\",\n default=DEFAULT_OF[\"bismark_bowtie2\"][\"seed_mismatch\"], help=\n \"Maximum number of mismatch allowed in a seed alignment: 0|1, \"\n \"by default %i.\" % DEFAULT_OF[\"bismark_bowtie2\"][\"seed_mismatch\"]\n )\n bismark.add_argument(\n \"--bowtie2-threads\", type=int, metavar=\"<int>\",\n default=DEFAULT_OF[\"bismark_bowtie2\"][\"threads\"], help=\n \"Bowtie2 '--threads' argument, by default %i\"\n % DEFAULT_OF[\"bismark_bowtie2\"][\"threads\"])\n bismark.add_argument(\n \"--meth-extract-threads\", type=int, metavar=\"<int>\",\n default=DEFAULT_OF[\"bismark_meth_extract\"][\"threads\"], help=\n \"bismark_methylation_extractor '--multicore' argument, by default %i.\"\n % DEFAULT_OF[\"bismark_meth_extract\"][\"threads\"]\n )\n\n # Optional Picard arguments\n picard = parser.add_argument_group(\"Picard optional\")\n picard.add_argument(\n \"--picard-jvm-args\", default=DEFAULT_OF[\"picard\"][\"jvm_args\"],\n metavar=\"<args>\", help=\n \"Java virtual machine arguments, e.g. to control starting and maximum \"\n \"heap size when running Picard, by default '%s'.\"\n % DEFAULT_OF[\"picard\"][\"jvm_args\"]\n )\n\n # Optional Samtools arguments\n samtools = parser.add_argument_group(\"Samtools optional\")\n samtools.add_argument(\n \"--samtools-threads\", type=int, metavar=\"<int>\",\n default=DEFAULT_OF[\"samtools\"][\"threads\"], help=\n \"Samtools '--threads' argument, by default %i\"\n % DEFAULT_OF[\"samtools\"][\"threads\"])\n\n # Parse the command line\n args = parser.parse_args()\n\n # For paired-end sequencing, check that the '{end}' wildcard is provided\n if args.paired_end is True and \"{end}\" not in args.fastq_regex:\n raise ValueError(\n \"The wildcard '{end}' is required in --fastq-regex argument when \"\n \"working with paired-end sequencing.\")\n\n # Set 'use_bismark_deduplicate' to False if RRBS data\n if args.rrbs is True:\n args.use_bismark_deduplicate = False\n\n # Check reference genome directory\n is_ref_genome_dir(args.ref_genome_dir, args.ref_build)\n\n # Convert the argparse object to a dict mapping <arg name> -> <val>\n kwargs = vars(args)\n\n return kwargs","def parse_args():\n from argparse import ArgumentParser\n ap = ArgumentParser(prog=__exe__, description=__purpose__)\n ap.add_argument(\n '--host', dest='host', default=None,\n help='Host for XNAT. Default: env XNAT_HOST.')\n ap.add_argument(\n '-u', '--username', dest='username', default=None,\n help='Username for XNAT.')\n ap.add_argument('project', help='Project Label')\n ap.add_argument('session', help='Session Label')\n ap.add_argument(\n 'proc_suffix', help='Proc name suffix', nargs='?', default='')\n ap.add_argument(\n '-sd', '--subjects_dir', dest='subjects_dir',\n help='Subjects Directory',\n default=os.environ.get('SUBJECTS_DIR', '/tmp'))\n return ap.parse_args()","def build_args():\n parser = argparse.ArgumentParser(description='Validates, edits, or creates a 22 XML file')\n subparsers = parser.add_subparsers(help='sub-command help')\n \n add_branch_parser(subparsers)\n add_edit_parser(subparsers)\n add_finalize_parser(subparsers)\n add_grade_parser(subparsers)\n add_new_parser(subparsers)\n add_validate_parser(subparsers)\n add_validate_document_parser(subparsers)\n \n return parser.parse_args()","def _argParser():\n parser = argparse.ArgumentParser(\n prog='modelc',\n description='Compile the given sources.')\n if FULL_INTERFACE:\n for (parameter,label) in OPTIONS:\n parser.add_argument(\n '--'+parameter,\n dest=parameter,\n const=1,\n # default=0,\n type=int,\n nargs='?',\n help='debug: control %s' % label)\n parser.add_argument(\n '-bw',\n dest='bw',\n action='store_true',\n help='black and white output',\n default=False)\n parser.add_argument(\n '-dg',\n dest='dg',\n action='store_true',\n default=False)\n parser.add_argument(\n '--issues', '-i',\n dest='issues',\n const='top',\n default='inline',\n help='choose location of issues wrt to the listing.',\n choices=['top', 'inline', 'bottom'],\n type=str,\n nargs='?')\n parser.add_argument(\n '--list', '-l',\n dest='listing',\n const='source',\n default='no',\n help='display a listing of model.',\n choices=['no', 'source', 'model'],\n type=str,\n nargs='?')\n parser.add_argument(\n '--summary', '-s',\n dest='summary',\n const='bottom',\n default='no',\n help='display a summary of model.',\n choices=['no', 'top', 'bottom'],\n type = str,\n nargs = '?')\n parser.add_argument(\n '-mode', '-m',\n dest='mode',\n const='full',\n default='full',\n help='choose the checking level.',\n choices=['justAST', 'justASTDep', 'full'],\n type=str,\n nargs='?')\n parser.add_argument(\n '--verbose', '-v',\n dest='verbose',\n action='store_true',\n default=False,\n help='make output verbose.')\n parser.add_argument(\n '--quiet', '-q',\n dest='quiet',\n action='store_true',\n help='create minimal amount of output.',\n default=False)\n parser.add_argument(\n '--version', '-V',\n dest='version',\n action='store_true',\n help='display modelscript version.',\n default=False)\n parser.add_argument(\n 'sources',\n metavar='source',\n nargs='*',\n help='A model source file or a directory.')\n return parser","def parse_arguments():\n parser = argparse.ArgumentParser(description=\n \"This script receives 'grouped_hits.txt', uses a FASTA file to get the \\\n \\nsequences, uses MAFFT to align each group, then generates a consensus \\\n \\nsequence for each group using biopython.\\n\\n \\\n Example: python {0} -g grouped_hits.txt -f sequences.fasta\".format(argv[0]),\n formatter_class = argparse.RawDescriptionHelpFormatter)\n \n requiredNamed = parser.add_argument_group('required arguments')\n\n requiredNamed.add_argument(\"-g\", \"--GROUPS\", type=str, required=True,\\\n help=\"Grouped hits file generated by group_self_BLAST.py\", action=\"store\")\n\n requiredNamed.add_argument(\"-f\", \"--FASTA\", type=str, required=True,\\\n help=\"FASTA file containing all sequences.\", action=\"store\")\n\n return parser.parse_args()","def parse_arguments(self, args):\n # Create parser for arguments\n parser = argparse.ArgumentParser(description=\"Intrusion Detection Dataset Toolkit (Core) - A toolkit for \"\n \"injecting synthetically created attacks into PCAP files.\",\n prog=\"id2t\")\n # Required arguments\n required_group = parser.add_argument_group('required arguments')\n required_args_group = required_group.add_mutually_exclusive_group(required=True)\n\n required_args_group.add_argument('-i', '--input', metavar=\"PCAP_FILE\",\n help='path to the input pcap file')\n required_args_group.add_argument('-l', '--list-attacks', action='store_true')\n\n # Optional arguments\n parser.add_argument('-c', '--config', metavar='CONFIG_FILE', help='file containing configuration parameters.',\n action=LoadFromFile, type=open)\n parser.add_argument('-e', '--export',\n help='store statistics as a \".stat\" file',\n action='store_true', default=False)\n parser.add_argument('-r', '--recalculate',\n help='recalculate statistics even if a cached version exists.',\n action='store_true', default=False)\n parser.add_argument('-s', '--statistics', help='print file statistics to stdout.', action='store_true',\n default=False)\n parser.add_argument('-p', '--plot',\n help='creates the following plots: the values distributions of TTL, MSS, Window Size, '\n 'protocol, and the novelty distributions of IP, port, TTL, MSS, Window Size,'\n ' and ToS. In addition to packets count in interval-wise.', action='append',\n nargs='?')\n parser.add_argument('-q', '--query', metavar=\"QUERY\",\n action='append', nargs='?',\n help='query the statistics database. If no query is provided, '\n 'the application enters query mode.')\n parser.add_argument('-t', '--extraTests',\n help='perform extra tests on the input pcap file, including calculating IP entropy'\n 'in interval-wise, TCP checksum, and checking payload availability.',\n action='store_true', default=False)\n parser.add_argument('-S', '--rngSeed', action='append', help='sets rng seed for testing or benchmarking',\n nargs='+', default=[])\n parser.add_argument('-T', '--time', help='measures packet generation time', action='store_true', default=False)\n parser.add_argument('-V', '--non-verbose', help='reduces terminal clutter', action='store_true', default=False)\n parser.add_argument('-o', '--output', metavar=\"PCAP_FILE\", help='path to the output pcap file')\n parser.add_argument('-ie', '--inject_empty', action='store_true',\n help='injects ATTACK into an EMPTY PCAP file, using the statistics of the input PCAP.')\n parser.add_argument('-d', '--debug', help='Runs ID2T in debug mode.', action='store_true', default=False)\n parser.add_argument('-si', '--statistics_interval', help='interval duration in seconds', action='store',\n type=float, nargs='+', default=[])\n parser.add_argument('-rd', '--recalculate-delete',\n help='recalculate statistics even if a cached version exists.'\n 'also delete old interval statistics.'\n 'surpresses (yes, no, delete) prompt.', action='store_true',\n default=False)\n parser.add_argument('-ry', '--recalculate-yes',\n help='recalculate statistics even if a cached version exists.'\n 'also recalculates old interval statistics.'\n 'surpresses (yes, no, delete) prompt.', action='store_true',\n default=False)\n parser.add_argument('-rn', '--recalculate-no',\n help='recalculate statistics even if a cached version exists.'\n 'does not recalculate old interval statistics, but keeps them.'\n 'surpresses (yes, no, delete) prompt.', action='store_true',\n default=False)\n parser.add_argument('-li', '--list-intervals', action='store_true',\n help='prints all interval statistics tables available in the database')\n parser.add_argument('--skip', action='store_true', help='skips every initialization right to query mode\\n'\n 'CAUTION: this will only work if there already is a '\n 'database')\n\n # Attack arguments\n parser.add_argument('-a', '--attack', metavar=\"ATTACK\", action='append',\n help='injects ATTACK into a PCAP file.', nargs='+')\n\n # Parse arguments\n self.args = parser.parse_args(args)\n\n self.process_arguments()","def setup_parser(self):\n parser = argparse.ArgumentParser(description=DESCRIPTION)\n parser.add_argument('words', metavar='W', nargs='+', help=POSITIONAL_HELP)\n parser.add_argument('-a','--any', dest=\"search_funct\", action=\"store_const\", \n const='any', default='all', help=SEARCH_HELP)\n parser.add_argument('-o','--only-id', action='store_true', help=ID_HELP)\n parser.add_argument('-u', '--update', action='store_true', help=UPDATE_HELP)\n return parser","def parse_args():\n parser = argparse.ArgumentParser(description=\"Reads in iClicker data from the submission \"\n \"directory, and then writes it to the given \"\n \"remote file.\")\n parser.add_argument(\"submission_directory\", type=str, help=\"Directory of submissions that \"\n \"contain a 'textbox_0.txt' file that references iClicker ID\")\n parser.add_argument(\"remote_id_file\", type=str)\n return parser.parse_args()","def _parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument('out', nargs='*', help='Create a plot for all provided'\n ' output files')\n parser.add_argument('--yscale', '-y', help='Y-axis scale',\n default='linear')\n parser.add_argument('--hits', help='Draw hits', dest='hits', action='store_true')\n parser.add_argument('--no-hits', help='Do not draw hits', dest='hits', action='store_false')\n parser.set_defaults(hits=True)\n\n parser.add_argument('--ltrim', help='Remove a number of smallest latency values from the plot', default=0, type=int)\n parser.add_argument('--rtrim', help='Remove a number of biggest latency values from the plot', default=0, type=int)\n\n parser.add_argument('--misses', help='Draw misses', dest='misses', action='store_true')\n parser.add_argument('--no-misses', help='Do not draw misses', dest='misses', action='store_false')\n parser.set_defaults(misses=True)\n\n args = parser.parse_args()\n if not args.out:\n parser.error('at least one output need to be provided')\n return args","def parse_args():\n parser = common_parser()\n parser.description = (\n \"Given a sequence dict, fasta index or a bed file, scatter over the \"\n \"defined contigs/regions. Each contig/region will be split into \"\n \"multiple overlapping regions, which will be written to a new bed \"\n \"file. Each contig will be placed in a new file, unless the length of \"\n \"the contigs/regions doesn't exceed a given number.\")\n\n parser.add_argument(\"-c\", \"--chunk-size\", type=int, default=1e6,\n metavar=\"SIZE\",\n help=\"The size of the chunks. The first chunk in a \"\n \"region or contig will be exactly length SIZE, \"\n \"subsequent chunks will SIZE + OVERLAP and the final \"\n \"chunk may be anywhere from 0.5 to 1.5 times SIZE \"\n \"plus overlap. If a region (or contig) is smaller \"\n \"than SIZE the original regions will be returned. \"\n \"Defaults to 1e6\")\n parser.add_argument(\"-m\", \"--minimum-bp-per-file\", type=int, default=45e6,\n help=\"The minimum number of bases represented within \"\n \"a single output bed file. If an input contig or \"\n \"region is smaller than this MINIMUM_BP_PER_FILE, \"\n \"then the next contigs/regions will be placed in the \"\n \"same file untill this minimum is met. Defaults to \"\n \"45e6.\")\n parser.add_argument(\"-o\", \"--overlap\", type=int, default=150,\n help=\"The number of bases which each chunk should \"\n \"overlap with the preceding one. Defaults to 150.\")\n parser.add_argument(\"-S\", \"--split-contigs\", action=\"store_true\",\n help=\"If set, contigs are allowed to be split up over \"\n \"multiple files.\")\n args = parser.parse_args()\n return args","def argument_parser(self):\n parser = argparse.ArgumentParser(\n prog='description2html',\n description=self.description,\n epilog=self.epilog)\n\n parser.add_argument(\n '--no-confirm',\n action='store_true',\n help=('Ask user for confirmation to the user. Default is True'))\n\n parser.add_argument(\n '-p', '--path',\n metavar='path',\n type=str,\n required=True,\n help=('the module path you want to apply the transformation'))\n\n parser.add_argument(\n '--pretty-style',\n action='store_true',\n help='Create the index.html file using the odoo ccs style. '\n ' Divide the README titles into visible sections.'\n ' WARNING: This functionality still beta.')\n\n argcomplete.autocomplete(parser)\n return parser.parse_args().__dict__","def parse_args():\n sentinel_dict = {}\n\n def _preprocess_sysargv(argv):\n inputs = []\n for arg in argv[1:]:\n # handles case where values contain --, otherwise they will\n # be interpreted as arguments.\n if '--,' in arg or ',--' in arg or arg == '--':\n sentinel = uuid4().hex\n key = '%s' % sentinel\n sentinel_dict[key] = arg\n inputs.append(sentinel)\n else:\n inputs.append(arg)\n return inputs\n\n def _postprocess_sysargv(v):\n if v in sentinel_dict:\n return sentinel_dict.get(v)\n else:\n return v\n\n #----- read input arguments\n for i, arg in enumerate(sys.argv):\n if (arg[0] == '-') and arg[1].isdigit(): sys.argv[i] = ' ' + arg\n parser = argparse.ArgumentParser()\n\n parser.add_argument('-u', action='store_true', dest='helpmenu',help='extended HELP MENU with examples')\n parser.add_argument('-i','--infile',action='store', dest='infile',help='name of file with SAC or mseed file(s)')\n parser.add_argument('-g','--gain',action='store', dest='sensitivity',help='Stage 0 sensitivity')\n parser.add_argument('-N','--net', action='store', dest='network',help='network')\n parser.add_argument('-S','--sta', action='store', dest='station',help='station')\n parser.add_argument('-C','--cha', action='store', dest='chantype',help='chantype')\n parser.add_argument('-s','--start', action='store', dest='startstring',help='start time YYYY-MM-DDTHH:MM:SS')\n parser.add_argument('-e','--end', action='store', dest='endstring',help='end time YYYY-MM-DDTHH:MM:SS')\n parser.add_argument('-d','--duration', action='store', dest='durationinhours',help='duration in hours')\n parser.add_argument('-dc','--dc','--datacenter', action='store', dest='datacenter',default='IRIS',help='FDSN data center (e.g. IRIS, SCEDC, NCEDC)')\n parser.add_argument('-p','--plot',action='store_true',dest='iplot',help='make plots of each hourly trace (NOTE: can be slow)')\n\n helpextended = parser.parse_args(_preprocess_sysargv(sys.argv)).helpmenu\n if ( helpextended is True ):\n print ('')\n print ('portable_pip_squeak: assess a station either using local data or to be downloaded')\n print ('')\n print ('Usage: portable_pip_squeak.py [options]')\n print ('')\n print ('EXAMPLES:')\n print ('portable_pip_squeak.py --infile my_SAC_files.txt')\n print ('portable_pip_squeak.py -N UW -S TKEY -C HH -s 2018-01-01T00:00:00 -d 2 -p')\n print ('portable_pip_squeak.py -N CI -S LEO -C HN -s 2020-01-01T00:00:00 -d 24 -dc SCEDC')\n print ('')\n print ('Inputs if supplying your own data:')\n print (' -i, --infile Name of text file with SAC/mseed file(s) of 3 (Z,N,E) traces.')\n print (' -g, --gain Gain or Stage 0 sensitivity')\n print (' ')\n print ('Inputs if downloading data:')\n print (' -s, --starttime Trace start time (YYYY-MM-DD,HH:MM:SS)')\n print ('')\n print (' One of these:')\n print (' -e, --endtime Trace end time (YYYY-MM-DD,HH:MM:SS)')\n print (' -d, --duration Duration in hours from starttime')\n print (' Note: if duration is neg, starttime becomes endtime')\n print (' N, S, C and a datacenter if other than IRIS')\n print (' -N, --net Network code')\n print (' -S, --sta Station code')\n print (' -C, --cha Channel type, e.g. EN or HH')\n print (' -dc, --datacenter Name of FDSN data center if not IRIS, e.g. SCEDC, NCEDC')\n print (' ')\n print ('Optional flags:')\n print ('-P, --plot Flag to make a figure for each hour. Note: can be slow.')\n print ('-u Print this extended help menu')\n print ('')\n\n\n return parser.parse_args(_preprocess_sysargv(sys.argv))","def createHelp():\n \n epilog_string=\"Any bug is welcome reported to fanxiaojuan@picb.ac.cn\"\n description_string='The program is going to extend the paired-end reads interval nucleotides'\n parser = argparse.ArgumentParser(description=description_string,epilog=epilog_string)\n parser.add_argument('-i', '--input file', dest='fnIn', default='plasmid.rmdup.bed', type=str,help='input file')\n parser.add_argument('-i_gtf', '--gtf', dest='gtf', default='gencode.v28lift37.annotation.gtf', type=str,help='input gencode gtf annotation file')\n parser.add_argument('-db', '--db', dest='db', default='gencode_v28lift37_comprehensive.txt', type=str,help='input file')\n parser.add_argument('-o', '--overhang', dest='o', default=0, type=int,help='input file')\n parser.add_argument('-o_anno', '--out-annotation', dest='anno', default='plasmid.fragment.rmdup.annotation.bed', type=str,help='output mature mRNA')\n op=parser.parse_args()\n return op","def parse_args():\n parser = argparser()\n args = parser.parse_args()\n\n # --------------------------------------------------------- #\n # Parse and check runtime parameters.\n # --------------------------------------------------------- #\n\n # check validity of cores selection.\n max_ppn = max_cpu() + 1\n if args.proc_per_node > max_ppn:\n warnings.warn('{0} is greater than the number of available cores ({1}). Reducing to {2}'\n .format(args.proc_per_node, max_ppn, max_ppn - 1))\n args.proc_per_node = max_ppn - 1\n\n # ensure that user has supplied fresh .bam/.bai files or a directory containing alignment files.\n if not args.bam_files and not args.bam_dir:\n raise ValueError('Must specify either --bam-files or --bam-dir.')\n\n if args.bam_files and args.bam_dir:\n raise ValueError('Both --bam-files and --bam-dir were provided! Not sure which data set to use.')\n\n # --------------------------------------------------------- #\n # Gather input RNA-Seq + genome annotation files.\n # --------------------------------------------------------- #\n\n # check validity of gene annotation file selection.\n if not args.genome_annotation:\n raise ValueError('If warm-start directory not specified, gene annotation file must be specified!')\n\n else:\n if not os.path.isfile(args.genome_annotation):\n raise FileNotFoundError('Gene annotation file {0} not found.'.format(args.genome_annotation))\n\n # check validity of file i/o selection.\n bam_files = list()\n bai_files = list()\n create_bai_files = list()\n\n # INPUT OPTION 1: a --bam-dir was specified.\n if args.bam_dir:\n\n # if user used both --bam-dir and --bam-files and/or --bai-files, yell at them. (only use one method).\n if args.bam_files is not None or args.bai_files is not None:\n raise ValueError('Do not specify both a --bam-dir and either --bam-files and/or --bai-files.'\n 'Use one input selection method or the other.')\n\n # check that the dir actually exists.\n if not os.path.isdir(args.bam_dir):\n raise NotADirectoryError('Cannot find --bam-dir {0}'.format(args.bam_dir))\n\n # scan directory for .bam files.\n for f in os.listdir(args.bam_dir):\n if f.endswith('.bam'):\n bam_files.append(os.path.join(args.bam_dir, f))\n\n # search for .bai files in the --bam-dir. If they don't exist, try to make them.\n for bam_file in bam_files:\n bai_file = re.sub('.bam$', '.bai', bam_file)\n\n # if .bai file under same basename as .bam file doesn't exist,\n # add it to list of .bai files that need to be created.\n if not os.path.isfile(bai_file):\n bai_files.append(bai_from_bam_file(bam_file))\n create_bai_files.append(bam_file)\n else:\n bai_files.append(bai_file)\n\n # INPUT OPTION 2: --bam-files and possibly --bai-files were specified.\n else:\n # ensure .bam files are actually .bam files.\n for bam_file in args.bam_files:\n if not bam_file.endswith('.bam'):\n raise ValueError('{0} is not a .bam file.'.format(bam_file))\n elif not os.path.isfile(bam_file):\n raise FileNotFoundError('Count not find .bam file {0}'.format(bam_file))\n else:\n bam_files.append(bam_file)\n\n # case where user has specified .bai files to accompany .bam files.\n if args.bai_files is not None:\n # if user has supplied an incorrect number of bai files, fail out.\n if len(args.bai_files) != len(bam_files):\n raise ValueError('Number of supplied .bai files does not match number of supplied .bam files.')\n\n # ensure .bai files are actually .bai files.\n for bai_file in args.bai_files:\n if not bai_file.endswith('.bai'):\n raise ValueError('{0} is not a .bai file.'.format(bai_file))\n elif not os.path.isfile(bai_file):\n raise FileNotFoundError('Count not find .bai file {0}'.format(bai_file))\n else:\n bai_files.append(bai_file)\n\n # if user has not supplied any bai files: look for them under the same name\n # as each of the .bam files, or create new .bai files with samtools (if possible).\n else:\n for bam_file in bam_files:\n bai_file = re.sub('.bam$', '.bai', bam_file)\n\n # if .bai file under same name as .bam file doesn't exist,\n # add it to list of .bam files for which we need to create a .bai file.\n if not os.path.isfile(bai_file):\n bai_files.append(bai_from_bam_file(bam_file))\n create_bai_files.append(bam_file)\n else:\n bai_files.append(bai_file)\n\n # ensure that input files are uniquely named.\n if len(bam_files) != len(set(bam_files)):\n raise ValueError('Supplied .bam files are not uniquely named!')\n\n # create parser attributes for bam/index files.\n args.bam_files = bam_files\n args.bai_files = bai_files\n args.create_bai_files = create_bai_files\n\n return args","def build_parser():\n def commaSplitter(str):\n \"\"\"\n Argparse a comm-seperated list\n \"\"\"\n # leave this here as a reminder of what I should do to make the argument parsing more robust\n\n # if sqrt != int(sqrt):\n # msg = \"%r is not a perfect square\" % string\n # raise argparse.ArgumentTypeError(msg)\n # return value\n return str.split(',')\n\n def existing_file(fname):\n \"\"\"\n Argparse type for an existing file\n \"\"\"\n if not os.path.isfile(fname):\n raise ValueError(\"Invalid file: \" + str(fname))\n return fname\n\n parser = argparse.ArgumentParser(description=__doc__)\n\n parser.add_argument('-p', '--prefix', help='dont really know what this does...',\n action='store', default='patient', dest='prefix')\n parser.add_argument('-d', '--date', help='dont really know what this does...',\n action='store', default='', dest='sampledate')\n parser.add_argument('template', type=argparse.FileType('r'), help='BEAST config template file')\n parser.add_argument('fasta', type=argparse.FileType('r'), help='file of sequences (in FASTA format)')\n\n return parser","def argparser():\n parser = argparse.ArgumentParser(add_help=False)\n parser.add_argument('--bam-files'\n , nargs='+'\n , default=None\n , required=False\n , help='Aligned read files (can be multiple; separate with space) in .bam format. '\n '.bam files may be for paired or single-end read experiments.')\n parser.add_argument('--bai-files'\n , nargs='+'\n , default=None\n , required=False\n , help='Input .bam index files (Can be multiple; separate with space). '\n 'Only use with --bam-files.'\n '.bai files for files passed to --bam-files. Assumed .bai file order corresponds to '\n 'supplied .bam files. If --bam-files is supplied and not --bai-files, it is assumed '\n 'that you have .bai files in the same location as --bam-files, and with the same '\n 'basename, e.g. (A01.bam, A01.bai), (sample_27.bam, sample_27.bai)')\n parser.add_argument('--bam-dir'\n , default=None\n , required=False\n , help='Input .bam/.bai data directory. Use instead of, or in addition to, specifying individual '\n '.bam files. All .bam files (and .bai files with the same basename) in this directory '\n 'will be considered covcurv input.')\n parser.add_argument('-g'\n , '--genome-annotation'\n , type=str\n , default=None\n , required=False\n , help='Genome annotation file.'\n 'Must have extension .gtf or .gff.'\n 'All non-exon regions will be removed, along with exons that appear in '\n 'multiple chromosomes and exons that overlap with multiple genes.')\n parser.add_argument('-o'\n , '--output-dir'\n , type=str\n , default=None\n , required=False\n , help='Name for a covcurv output directory.'\n 'Name an directory for storing coverage data output by covcurv. '\n 'If not specified, directory ./covcurv_[mmddyy]_[HHMMSS] will be created.')\n parser.add_argument('-u'\n , '--unique-alignments'\n , action='store_true'\n , help='Only retain reads that were uniquely aligned. All reads with '\n 'the flag \"NH:i:<x>\" with x > 1 will be dropped.')\n parser.add_argument('-p'\n , '--proc-per-node'\n , type=int\n , required=False\n , default=max_cpu()\n , help='Number of processes to spawn per node, for within-node parallelization.'\n 'Defaults to the number of available cores (on the worker node) - 1. '\n 'If too high for a given node, reduce to the node\\'s default.')\n parser.add_argument('-v'\n , '--version'\n , action='version'\n , version='covcurv version {0}'.format(pkg_resources.get_distribution('covcurv').version)\n , help='Display covcurv package version and exit.')\n parser.add_argument('-h'\n , '--help'\n , action='help'\n , default=argparse.SUPPRESS\n , help='covcurv: Per-gene read coverage matrix pipeline package.')\n\n return parser","def parseArguments():\n parser = argparse.ArgumentParser(description=\"AutoMacTC: an Automated macOS forensic triage collection framework.\", add_help=False)\n\n module_filter = parser.add_argument_group('module filter')\n mods = module_filter.add_mutually_exclusive_group(required=False)\n mods.add_argument('-m', '--include_modules', type=str, nargs='+', help='module(s) to use, use \"all\" to run all modules, space separated list only', default=[''], required=False)\n mods.add_argument('-x', '--exclude_modules', type=str, nargs='+', help='assumes you want to run all modules EXCEPT those specified here, space separated list only', default=[''], required=False)\n mods.add_argument('-l', '--list_modules', help='if flag is provided, will list available modules and exit.', default=False, action='store_true', required=False)\n\n general = parser.add_argument_group('general arguments')\n general.add_argument(\"-h\", \"--help\", action=\"help\", help=\"show this help message and exit\")\n general.add_argument(\"-v\", \"--verbose\", default=False, action='store_true', help=\"enable verbose logging\")\n general.add_argument('-i', '--inputdir', default='/', help='input directory; mount dmg with mountdmg.sh script and use -f to analyze mounted HFS or APFS Volume, use volume appended with \"Data\" (e.g. \"Macintosh HD - Data\") for 10.15+ systems', required=False)\n general.add_argument('-is', '--inputsysdir', default='', help='input system drive if using mounted drive from 10.15+ system (e.g. \"Macintosh HD\")', required=False)\n general.add_argument('-o', '--outputdir', default='./', help='output directory', required=False)\n general.add_argument('-p', '--prefix', help='prefix to append to tarball and/or output files', default='automactc-output', required=False)\n general.add_argument('-f', '--forensic_mode', help='if flag is provided, will analyze mounted volume provided as inputdir', default=False, action='store_true', required=False)\n general.add_argument('-nt', '--no_tarball', help='if flag is provided, will NOT package output files into tarball', default=False, action='store_true', required=False)\n general.add_argument('-nl', '--no_logfile', help='if flag is provided, will NOT generate logfile on disk', default=False, action='store_true', required=False)\n general.add_argument('-fmt', '--output_format', help='toggle between csv and json output, defaults to csv', default='csv', action='store', required=False, choices=['csv', 'json'])\n general.add_argument('-np', '--no_low_priority', help='if flag is provided, will NOT run automactc with highest niceness (lowest CPU priority). high niceness is default', default=False, action='store_true', required=False)\n general.add_argument('-b', '--multiprocessing', help='if flag is provided, WILL multiprocess modules [WARNING: Experimental!]', default=False, action='store_true', required=False)\n general.add_argument('-O', '--override_mount', help='if flag is provided, WILL bypass error where inputdir does not contain expected subdirs', default=False, action='store_true', required=False)\n\n console_log_args = parser.add_argument_group('console logging verbosity')\n console_logging_args = console_log_args.add_mutually_exclusive_group(required=False)\n console_logging_args.add_argument('-q', '--quiet', help='if flag is provided, will NOT output to console at all', default=False, action='store_true', required=False)\n console_logging_args.add_argument('-r', '--rtr', help='reduce verbosity to display nicely on RTR console', default=False, action='store_true', required=False)\n console_logging_args.add_argument('-d', '--debug', help='enable debug logging to console', default=False, action='store_true', required=False)\n\n dirlist_args = parser.add_argument_group('specific module arguments')\n dirlist_args.add_argument('-K', '--dir_include_dirs', type=str, nargs='+', help='directory inclusion filter for dirlist module, defaults to volume root, space separated list only', default=[''], required=False)\n dirlist_args.add_argument('-E', '--dir_exclude_dirs', type=str, nargs='+', help='directory and file exclusion filter for dirlist module. defaults are specified in README. space separated list only. \\\n put \\'no-defaults\\' as first item to overwrite default exclusions and then provide your own exclusions', default=[''], required=False)\n dirlist_args.add_argument('-H', '--dir_hash_alg', nargs='+', help='either sha256 or md5 or both or none, at least one is recommended, defaults to sha256. also applies to autoruns module', default='sha256', required=False)\n dirlist_args.add_argument('-S', '--dir_hash_size_limit', type=int, help='file size filter for which files to hash, in megabytes, defaults to 10MB. also applies to autoruns module', default=10, required=False)\n dirlist_args.add_argument('-R', '--dir_recurse_bundles', help='will fully recurse app bundles if flag is provided. this takes much more time and space', default=False, action='store_true', required=False)\n dirlist_args.add_argument('-NC', '--dir_no_code_signatures', help='if flag is provided, will NOT check code signatures for app and kext files. also applies to autoruns module', default=False, action='store_true', required=False)\n dirlist_args.add_argument('-NM', '--dir_no_multithreading', help='if flag is provided, will NOT multithread the dirlist module', default=False, action='store_true', required=False)\n args = parser.parse_args()\n\n return args","def handle_program_options():\n parser = argparse.ArgumentParser(description=\"Gather numeric information \\\n about the processed sequence data in an \\\n MG-RAST project.\")\n parser.add_argument('project_id',\n help=\"The project identifier (MG-RAST ID)\")\n parser.add_argument('-a', '--auth_key',\n help=\"An MG-RAST API authorization key. This is \\\n necessary to access projects marked as private.\")\n parser.add_argument('-g', '--group_by', action='append',\n help=\"A string that matches some part of the \\\n 'Metagenome Name' field. All matching project \\\n metagenomes will be grouped by this identifier \\\n and their stats will be summed. This option can \\\n be specified multiple times to create multiple \\\n groups. All non-matching metagenomes will \\\n appear separately in the table. NOTE: \\\n Strings will be matched longest first. This \\\n allows for matching names that might be a \\\n substring of another match. For example: -g S \\\n -g NS. The name field will first be matched \\\n against the longest string (NS) first and then \\\n each smaller string in order.\")\n parser.add_argument('-o', '--output_filename', default='meta_stats.txt',\n help=\"The name of the file the project summary \\\n information will be written to.\")\n\n# parser.add_argument('-v', '--verbose', action='store_true')\n\n return parser.parse_args()","def arg_parse():\n\n parser = argparse.ArgumentParser()\n\n parser.add_argument(\n \"-f\",\n \"--fpath\",\n type=str,\n required=True,\n help=\"Path to files to generate test data from e.g. /badc/cmip5/data/cmip5/output1/MOHC/HadGEM2-ES/rcp85/mon/atmos/Amon/r1i1p1/latest/tas\",\n )\n\n parser.add_argument(\n \"-t\",\n \"--time_only\",\n default=False,\n help=\"Only generate one time step of this dataset\",\n action=\"store_true\",\n )\n\n parser.add_argument(\n \"-s\",\n \"--step\",\n type=int,\n default=100,\n help=\"Step to select latitude/longitude by. Only relevant when time_only is False\",\n )\n\n parser.add_argument(\n \"-n\",\n \"--number\",\n type=int,\n default=0,\n help=\"Number of files to generate. Default is all files. Only relevant when time_only is False\",\n )\n\n parser.add_argument(\n \"-l\",\n \"--level\",\n type=int,\n default=-1,\n help=\"Number of levels to extract, starting with index 0.\",\n )\n\n parser.add_argument(\n \"-c\", \"--compress\", help=\"Compress the files.\", action=\"store_true\"\n )\n\n return parser.parse_args()","def parse_cmdline():\n\tparser = ArgumentParser(prog=\"FastP_QC.py\", description=\"\"\"Script collects stats from fastp jsons.\"\"\")\n\tparser.add_argument(\"-r1\", \"--r1_stats\", dest=\"r1_stats\", action=\"store\", required=True, help=\"Text file with r1 stats, from q30.py script.\")\n\tparser.add_argument(\"-r2\", \"--r2_stats\", dest=\"r2_stats\", action=\"store\", required=True, help=\"Text file with r2 stats, from q30.py script.\")\n\tparser.add_argument(\"-n\", \"--name\", dest=\"name\", action=\"store\", required=True, help=\"Sample name\")\n\targs = parser.parse_args()\n\treturn args","def parse_arguments():\n parser = argparse.ArgumentParser(description='Arguments get parsed via --commands')\n \n parser.add_argument('-in', dest='input', type=str, \n help=\"Specify the RTStruct file read.\")\n parser.add_argument('--out', dest='output', type=str, default=\"RTSS_info.json\",\n help=\"Specify the RTStruct file read.\")\n \n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser()\n argparse.ArgumentParser(argument_default=False)\n parser.add_argument('-r', type=str, required=True, metavar='[reference.fa]', help=\"Reference file in fasta format\")\n parser.add_argument('-s', type=int, metavar='number of SNPs', help=\"Number of SNPs to introduce\")\n parser.add_argument('-i', type=int, metavar='number of indels', help=\"Number of small indels to introduce. Indel sizes randomly sampled between 1-100bp with a ratio of 9:1 for size being < 11bp\")\n parser.add_argument('-d', type=int, metavar='number of large deletions', help=\"Number of large deletions to introduce. Deletion size randomly sampled between 100-5000bp\")\n parser.add_argument('-t', type=int, metavar='number of translocations', help=\"number of translocations, regions will be randomly selected ranging between 500-5000bp in size\")\n parser.add_argument('-nc', type=bool, default=False, metavar='add at least one non-conserved translocation', help=\"True/False add one non-conserved translocation. Deletion occurs from end of the translocation. Default=False\")\n parser.add_argument('-f', type=str, required=True, metavar='output fasta filename', help=\"Output fasta filename and file path\")\n parser.add_argument('-v', type=str, required=True, metavar='output vcf file of mutations', help=\"Output vcf filename and file path\")\n\n return parser.parse_args()","def getOptions():\n\tdescription=\"\"\"This script takes an input fasta file of fusions and identifies all of the identical fusions.\"\"\"\n\tparser = argparse.ArgumentParser(description=description)\n\tparser.add_argument(\"-bowtie\", \"--bowtie_log_names\", dest=\"bowtie\", action='store', required=False, nargs = '*', help=\"bowtie log file names [Optional]\")\n\tparser.add_argument(\"-last\", \"--last_log_names\", dest=\"last\", action='store', required=False, help=\"LAST log file names [Optional]\")\n\tparser.add_argument(\"-treatment\",\"--treatment_name\",dest=\"treatment\",action='store',required=True,nargs= '*', help=\"Treatment variables [Required]\")\n\tparser.add_argument(\"-o\",\"--output_file\",dest=\"output\",action='store',required=True,help=\"Output file name [Required]\")\n\targs = parser.parse_args()\n\tif not args.bowtie and not args.last: #The user should give at least one bowtie or last log argument; otherwise the program does nothing\n\t parser.error('No input logs given; add -bowtie or -last')\n\treturn(args)","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument('--vec',\n help='Name of the output file containing the positive'\n ' samples for training.')\n parser.add_argument('--pos',\n help='Positive samples file name.', required=True)\n parser.add_argument('--bg',\n help='Background description file; contains a list of '\n 'images which are used as a background for randomly '\n 'distorted versions of the object.', required=True)\n parser.add_argument('--num', type=int,\n help='Number of positive samples to generate.',\n required=True)\n parser.add_argument('--bgcolor',\n help='Background color (currently grayscale images are '\n 'assumed); the background color denotes the transparent'\n ' color. Since there might be artifacts, the'\n ' amount of color tolerance can be specified by '\n '-bgthresh. All pixels withing bgcolor-bgthresh and '\n 'bgcolor+bgthresh range are interpreted as '\n 'transparent. <0>')\n parser.add_argument('--bgthresh',\n help='Background color threshold.<80>')\n parser.add_argument('--inv',\n help='If specified, colors will be inverted.',\n action='store_true')\n parser.add_argument('--randinv',\n help='If specified, colors will be inverted.',\n action='store_true')\n parser.add_argument('--out-img-folder',\n help='Save all created images in a folder.')\n parser.add_argument('--maxidev',\n help='Maximal intensity deviation of pixels in '\n 'foreground samples. <40>')\n parser.add_argument('--maxzangle', type=float,\n help='Maximum rotation in angle Z must be given in '\n 'radians. <0.50000>')\n parser.add_argument('--maxxangle', type=float,\n help='Maximum rotation in angle X must be given in '\n 'radians. <1.10000>')\n parser.add_argument('--maxyangle', type=float,\n help='Maximum rotation in angle Y must be given in '\n 'radians. <1.10000>')\n parser.add_argument('--height',\n help='Height (in pixels) of the output samples. <24>',\n default='24')\n parser.add_argument('--width',\n help='Width (in pixels) of the output samples. <24>',\n default='24')\n\n return parser.parse_args()","def process_arguments():\n # Create ArgumentParser object. Description message will be displayed as part of help message if script is run with -h flag\n parser = argparse.ArgumentParser(description='Prints tier 1 and 2 variant details to stdout for a given 100k case')\n # Define the arguments that will be taken.\n parser.add_argument('-i', '--ir_id', required=True, help='GeL Interpretation Request ID in format 12345-1')\n parser.add_argument('-p', '--proband_id', required=True, help='GeL participant ID for proband')\n # Return the arguments\n return parser.parse_args()","def parse_args():\n parser = argparse.ArgumentParser(\n description=\"Trim spaces at the end of every lines.\"\n )\n parser.add_argument(\"-R\", \"-r\", action=\"store_true\", help=\"Whether to recursive\")\n parser.add_argument(\"-y\", \"--yes\", action=\"store_true\", help=\"No ask\")\n parser.add_argument(\n \"-t\", \"--type\", default=\"*\", help=\"Filter file type(Example: *.py)\"\n )\n parser.add_argument(\"-d\", \"--dir\", default=\"\", help=\"The directory path\")\n parser.add_argument(\n \"files\",\n nargs=\"+\",\n default=[],\n metavar=\"*.py\",\n help=\"files or directories\",\n )\n return parser.parse_args()","def parse_arguments():\n parser = argparse.ArgumentParser()\n parser.add_argument(\n \"--obs_len\",\n default=20,\n type=int,\n help=\"Directory where the sequences (csv files) are saved\",\n )\n parser.add_argument(\n \"--data_dir\",\n default=\"\",\n type=str,\n help=\"Directory where the sequences (csv files) are saved\",\n )\n parser.add_argument(\n \"--feature_dir\",\n default=\"\",\n type=str,\n help=\"Directory where the computed features are saved\",\n )\n parser.add_argument(\"--mode\",\n required=True,\n type=str,\n help=\"train/val/test/compute_all/lanes_only\")\n parser.add_argument(\n \"--sequence_num\",\n default=-1,\n type=int,\n help=\"Specify a specific sequence to visualize.\",\n )\n parser.add_argument(\n \"--batch_start\",\n default=0,\n type=int,\n help=\"Specify the starting row of features to visualize.\",\n )\n parser.add_argument(\n \"--batch_end\",\n default=-1,\n type=int,\n help=\"Specify the last row to visualize, -1 to visualize till end.\",\n )\n parser.add_argument(\n \"--single_figure\",\n default=False,\n action=\"store_true\",\n help=\"Plot all candidates for a scenein one figure.\",\n )\n return parser.parse_args()","def parse_arguments():\n p = argparse.ArgumentParser(description='Prepare the dataset for use by neural models.')\n p.add_argument(\"json_file\", type=argparse.FileType('r'), help=\"json file with all the data\")\n p.add_argument(\"prefix\", type=str, help=\"prefix for all the generated files\")\n p.add_argument(\"data_type\", type=str, choices=[\"names\", \"comments\", \"nc\"],\n default=\"nc\", help=\"type of the information recorded in the dataset\")\n p.add_argument(\"labels\", type=str, choices=[\"PROG\", \"ALL\", \"TOP\"],\n default=\"PROG\", help=\"method by which to choose the labels for the dataset\")\n p.add_argument(\"-other_label\", type=str, required=False, default=\"\",\n help=\"label to use instead of all infrequent labels. \"\n \"This can be left blank to ignore infrequent labels altogether\")\n p.add_argument(\"-label_num\", type=int, default=100, required=False,\n help=\"Number of most frequent labels to keep. Works with label_choice=TOP\")\n p.add_argument(\"-min_prog_labels\", type=int, default=5, required=False,\n help=\"Minimal number of programs a label has to appear in for it to be included \"\n \"in the dataset. Works with label_choice=PROG\")\n p.add_argument(\"-test_prog_list\", type=argparse.FileType('r'), default=None, required=False,\n help=\"file with the list of programs in the test set (optional)\")\n\n return p.parse_args(sys.argv[1:])","def setup_cmd_args():\n parser = argparse.ArgumentParser(description=\"Translate XLS files to appropriate XML format for ingestion in FEDEO.\", formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\"xlsfile\", help=\"The XLS file to parse\")\n parser.add_argument('-outputdir', help=\"directory to output the XML file\", default='output')\n parser.add_argument('-j', action='store_true', help=\"Also export JSON file\")\n parser.add_argument('-p', action='store_true', help=\"Pretty print XML file\")\n parser.add_argument('-o', action='store_true', help=\"Overwrite output XML file\")\n parser.add_argument('-l', action='store_true', help=\"Skip I_G_LN as mandatory field\", default=False)\n return parser.parse_args()","def parse_commandlineargs():\n\n parser = argparse.ArgumentParser(\n description='Perform generic fitting operations on Multinomial' +\n 'Processing Trees (MPTs).')\n\n # Mandatory arguments\n parser.add_argument(\n 'model_path',\n metavar='model',\n type=str,\n help='Path to the MPT model specification file.')\n\n parser.add_argument(\n 'data_path',\n metavar='data',\n type=str,\n help='Path to the data file in CSV format.')\n\n # Optional arguments\n n_default = 10\n parser.add_argument(\n '-n',\n '--n_optim',\n metavar='N',\n type=int,\n default=n_default,\n help='Number of fitting repetitions to evade local maxima. (Default={})'.\n format(n_default))\n\n s_default = ','\n parser.add_argument(\n '-s',\n '--sep',\n metavar='S',\n type=str,\n default=s_default,\n help=\"Data table column separator. (Default='{}')\".format(s_default))\n\n parser.add_argument(\n '--header',\n action='store_true',\n help=\"Is the first not-commented line a header?\")\n\n parser.add_argument(\n '--llik',\n action='store_true'\n )\n\n parser.add_argument(\n '-i',\n '--ignore',\n type=str,\n nargs='+',\n help='Set of Parameter names which are not to be modified, ALL for all \\\n parameters'\n )\n\n args = parser.parse_args()\n return vars(args)","def parse_options():\r\n # Get options\r\n options = get_options()\r\n (opts, args) = options.parse_args()\r\n\r\n # The meta will store all information about the arguments passed #\r\n meta = {\r\n 'casename': opts.casename,\r\n 'reportqueries': opts.report_queries,\r\n 'sourcetype': opts.sourcetype,\r\n 'source': opts.source,\r\n 'outdir': opts.outdir\r\n }\r\n\r\n # Print help if no options are provided\r\n if len(sys.argv[1:]) == 0:\r\n options.print_help()\r\n sys.exit(1)\r\n # Test required arguments\r\n if meta['source'] is False or meta['outdir'] is False or meta['sourcetype'] is False:\r\n options.error('Unable to proceed. The following parameters '\r\n 'are required:\\n-s SOURCE\\n-o OUTDIR\\n-t SOURCETYPE')\r\n\r\n if not os.path.exists(meta['source']):\r\n options.error(\"Unable to proceed. \\n\\n%s does not exist.\\n\" % meta['source'])\r\n\r\n if not os.path.exists(meta['outdir']):\r\n options.error(\"Unable to proceed. \\n\\n%s does not exist.\\n\" % meta['outdir'])\r\n \r\n if meta['reportqueries'] and not os.path.exists(meta['reportqueries']):\r\n options.error(\"Unable to proceed. \\n\\n%s does not exist.\\n\" % meta['reportqueries'])\r\n\r\n if meta['sourcetype'].lower() != 'folder' and meta['sourcetype'].lower() != 'image':\r\n options.error(\r\n 'Unable to proceed. \\n\\nIncorrect source type provided: \"%s\". The following are valid options:\\\r\n \\n -t folder\\n -t image\\n' % (meta['sourcetype']))\r\n\r\n if meta['sourcetype'] == 'image' and DFVFS_IMPORT is False:\r\n options.error(IMPORT_ERROR)\r\n\r\n if meta['reportqueries'] ==False:\r\n print('[Info]: Report queries file not specified using the -q option. Custom reports will not be generated.')\r\n \r\n if meta['casename'] is False:\r\n print('[Info]: No casename specified using -c. Defaulting to \"FSE_Reports\".')\r\n meta['casename'] = 'FSE_Reports'\r\n\r\n # Return meta to caller #\r\n return meta","def parse_args(arglist):\n help = dedent(\"\"\"\n Run FIR model on subject data\n \"\"\")\n parser = tools.parser\n parser.description = help\n parser.formatter_class = argparse.RawDescriptionHelpFormatter\n parser.add_argument(\"-extract_info\", help=\"info for experiment to extract\")\n parser.add_argument(\"-mask_type\", help=\"mask or func?\")\n parser.add_argument(\"-mask_name\", help=\"name of mask in sub's mask directory\")\n return parser.parse_args(arglist)","def setup_args():\n parser = ParlaiParser()\n parser.add_argument(\n '-n',\n '--num-episodes',\n default=-1,\n type=int,\n help='Total number of episodes to convert, -1 to convert all examples',\n )\n parser.add_argument(\n '-of',\n '--outfile',\n default=None,\n type=str,\n help='Output file where to save, by default will be created in /tmp',\n )\n parser.add_argument(\n '-s1id', '--speaker-0-id', type=str, help='Speaker id of agent who speaks first'\n )\n parser.add_argument(\n '-s1id',\n '--speaker-1-id',\n type=str,\n help='Speaker id of agent who speaks second',\n )\n parser.add_argument(\n '--prepended-context',\n type='bool',\n default=False,\n help='specify if the context is prepended to the first act',\n )\n parser.add_argument('-ltim', '--log-every-n-secs', type=float, default=10)\n parser.set_defaults(datatype='train:ordered')\n\n return parser","def parse_args():\n parser = ArgumentParser(description='Count lines.')\n\n parser.add_argument(\n 'path',\n metavar='PATH')\n\n parser.add_argument(\n 'patterns',\n metavar='PATTERN',\n nargs='*')\n\n parser.add_argument(\n '-a', '--absolute',\n dest='absolute',\n action='store_true',\n help='show absolute paths in details (overrides `-r`)')\n\n parser.add_argument(\n '-d', '--details',\n dest='details',\n action='store_true',\n help='show details for each file')\n\n parser.add_argument(\n '-r', '--relative',\n dest='relative',\n action='store_true',\n help='show relative paths in details')\n\n return parser.parse_args()","def _init_argparser():\n desc = 'SES status and metrics reporting utility (part of sasutils).'\n parser = argparse.ArgumentParser(description=desc)\n parser.add_argument('-d', '--debug', action=\"store_true\",\n help='enable debugging')\n\n group = parser.add_mutually_exclusive_group(required=True)\n group.add_argument('-c', '--carbon', action='store_true',\n help='output SES Element descriptors metrics in a '\n 'format suitable for Carbon/Graphite')\n group.add_argument('-s', '--status', action='store_true',\n help='output status found in SES Element descriptors')\n\n group = parser.add_argument_group('output options')\n group.add_argument('--prefix', action='store',\n default='sasutils.ses_report',\n help='carbon prefix (example: \"datacenter.cluster\",'\n ' default is \"sasutils.ses_report\")')\n group.add_argument('-j', '--json', action='store_true',\n help='alternative JSON output mode')\n return parser.parse_args()"],"string":"[\n \"def parser():\\n \\n \\n parser = ap.ArgumentParser(description='Parsing some file names in various forms')\\n group = parser.add_mutually_exclusive_group()\\n group.add_argument('-f','--filepaths',dest='filepaths',metavar='PATH1,PATH2,...',type=str,\\n help='Input a string or list of strings. ex. '\\n '\\\"C:\\\\\\\\Users\\\\\\\\Matt\\\\\\\\Desktop\\\\\\\\FireEyeCodingSample\\\\\\\\learn.txt\\\",'\\n '\\\"foo\\\\\\\\bar\\\\\\\\fudge\\\"''Note: On Unix systems, you need quotes or you need to escape your escape characters.'\\n 'Otherwise, your resultant tokens may be incorrect.')\\n group.add_argument('-i','--input',dest='file',metavar='TEXTFILE',type=str,\\n help='Input a valid file path to a text file of '\\n 'paths. ex. '\\n '\\\"C:\\\\\\\\Users\\\\\\\\Matt\\\\\\\\Desktop\\\\\\\\FireEyeCodingSample\\\\\\\\learn.txt\\\"')\\n \\n \\n args = parser.parse_args()\\n\\n if args.file and not os.path.isfile(args.file):\\n raise OSError('This file does not exist - please input a valid file path')\\n \\n return args\",\n \"def get_args():\\n\\n # Make argparse object, add description\\n parser = argparse.ArgumentParser(\\n formatter_class=argparse.RawTextHelpFormatter,\\n description=textwrap.dedent(\\n '''\\n summary:\\n Takes a VCF file and parses the variants to produce a tab delimited \\n variant report.\\n '''\\n ))\\n\\n\\n # Version info\\n parser.add_argument(\\n '-v', '--version', action='version', \\n version=\\n '%(prog)s\\\\nversion:\\\\t{}\\\\nlast updated:\\\\t{}'.format(\\n __version__, __updated__\\n ))\\n\\n\\n # Arguments (see help string for full descriptions):\\n # REQUIRED: VCF file input\\n parser.add_argument(\\n 'input', action='store', \\n help='Filepath to input VCF file. REQUIRED.'\\n )\\n\\n\\n # OPTIONAL: Output folder, defaults to current directory if empty\\n parser.add_argument(\\n '-O', '--output', action='store', \\n help=textwrap.dedent(\\n '''\\n Filepath to folder where output reports will be saved. \\n If missing, defaults to current directory.\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: List of preferred transcripts\\n parser.add_argument(\\n '-t', '--transcripts', action='store', \\n help=textwrap.dedent(\\n '''\\n Filepath to preferred transcripts file. \\n\\n Must be a tab seperated file with preferred transcripts in the second \\n column. If missing, all entries in the preferred transcript column \\n will be labelled as 'Unknown'.\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: Preferred transcripts strictness\\n parser.add_argument(\\n '-T', '--transcript_strictness', action='store', default='low', \\n help=textwrap.dedent(\\n '''\\n Strictness of matching while annotating preferred transcripts.\\n Default setting is low.\\n\\n Options: \\n\\n high - Transcripts must be an exact match. \\n e.g. NM_001007553.2 and NM_001007553.1 won't match,\\n NM_001007553.1 and NM_001007553.1 will.\\n\\n low - Transcripts will match regardless of the version number. The \\n version number is after the . at the end of a transcript \\n e.g. NM_001007553.2 and NM_001007553.1 will match.\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: either a single BED file or a folder containing BED \\n # files, only one of these can be used\\n bed_files = parser.add_mutually_exclusive_group()\\n\\n # Single BED file\\n bed_files.add_argument(\\n '-b', '--bed', action='store', \\n help=textwrap.dedent(\\n '''\\n Filepath to a single BED file. \\n\\n The BED file will be applied to the variant report and a seperate\\n report saved with the BED file applied. This report will be saved in \\n the same output folder as the original variant report, with the BED \\n file name added to it.\\n Cannot be used together with -B flag.\\n \\\\n'''\\n ))\\n\\n # Multiple BED files\\n bed_files.add_argument(\\n '-B', '--bed_folder', action='store', \\n help=textwrap.dedent(\\n '''\\n Filepath to folder containing BED files. \\n\\n Each BED file will be applied to the variant report and a seperate\\n report saved with the BED file applied. These reports will be saved in\\n a new folder within the output folder, named the same as the input BED\\n folder. \\n The file names will be the same as the original variant report, with \\n the BED file name added to them.\\n Cannot be used together with -b flag.\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: File containing known variants\\n parser.add_argument(\\n '-k', '--known_variants', action='store', \\n help=textwrap.dedent(\\n '''\\n Filepath to known variants file. \\n\\n This is a VCF file containing any known variants and an associated \\n classification. The classification will be added to the variant \\n report. The VCF must have an annotation named 'Classification' within \\n the INFO field for each variant.\\n\\n Key:\\n 0 - Artifact\\n 1 - Benign\\n 2 - Likely benign\\n 3 - VUS\\n 4 - Likely pathogenic\\n 5 - Pathogenic\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: File containing the headers for the report\\n parser.add_argument(\\n '-c', '--config', action='store', \\n help=textwrap.dedent(\\n '''\\n Filepath to config file. \\n\\n This is a tab seperated text file containing a number of rows, where \\n each row specifies an annotation to be included in the variant report.\\n Only annotations included in the config file will be included in the\\n variant report.\\n The columns in the variant report will be in the same order as the \\n order in which the annotations appear in the config file.\\n\\n Each row contains:\\n\\n Column 1 - Required. Annotation headers, these must match up with how\\n they appear in the VCF (case sensitive).\\n\\n Column 2 - Required. Location where to find the data within the VCF, \\n used to select the correct parsing function.\\n options: info, format, vep, filter or pref.\\n\\n Column 3 - Optional. Alternative name for column header.\\n\\n To make a config file with all available options from a VCF, run:\\n vcf_parse -l path_to_input_vcf > config.txt\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: Lists all headers in a vcf then exits\\n parser.add_argument(\\n '-l', '--config_list', action='store_true', \\n help=textwrap.dedent(\\n '''\\n Return a list of all availabile config to the screen, then exit.\\n See CONFIG section for usage.\\n \\\\n'''\\n ))\\n\\n\\n # OPTIONAL: Filter out any variants where FILTER column is not PASS\\n parser.add_argument(\\n '-F', '--filter_non_pass', action='store_true', \\n help=textwrap.dedent(\\n '''\\n Filters out any variants where the FILTER annotation is not \\n PASS. If missing then there will be no fitering based on the\\n FILTER annotation.\\n \\\\n'''\\n ))\\n\\n return parser.parse_args()\",\n \"def parse_arguments(args):\\n\\n parser = argparse.ArgumentParser(\\n description=\\\"Text2Text: Read input text training files, output item files and train a model\\\"\\n )\\n\\n parser.add_argument(\\n \\\"-i\\\",\\n \\\"--input-text-path\\\",\\n type=str,\\n required=True,\\n metavar=\\\"INPUT_TEXT_PATH\\\",\\n help=\\\"Text input file name. Format: in each line, OUTPUT_ID1,OUTPUT_ID2,OUTPUT_ID3,...\\\\t INPUT_TEXT \\\\\\n where OUTPUT_IDs are the zero-based output item indices corresponding to the line numbers of OUTPUT_ITEM_PATH. We assume utf-8 encoding for text.\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-q\\\",\\n \\\"--output-item-path\\\",\\n type=str,\\n required=True,\\n metavar=\\\"OUTPUT_ITEM_PATH\\\",\\n help=\\\"Output item file name. Format: each line corresponds to a representation of the output item. We assume utf-8 encoding for text.\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-m\\\",\\n \\\"--model-folder\\\",\\n type=str,\\n required=True,\\n metavar=\\\"MODEL_FOLDER\\\",\\n help=\\\"Output model folder name\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--workspace-folder\\\",\\n type=str,\\n default=None,\\n metavar=\\\"WORKSPACE_FOLDER\\\",\\n help=\\\"A folder name for storing intermediate variables during training\\\",\\n )\\n\\n vectorizer_config_group_parser = parser.add_mutually_exclusive_group()\\n vectorizer_config_group_parser.add_argument(\\n \\\"--vectorizer-config-path\\\",\\n type=str,\\n default=None,\\n metavar=\\\"VECTORIZER_CONFIG_PATH\\\",\\n help=\\\"Json file for vectorizer config (default tfidf vectorizer)\\\",\\n )\\n\\n vectorizer_config_group_parser.add_argument(\\n \\\"--vectorizer-config-json\\\",\\n type=str,\\n default='{\\\"type\\\":\\\"tfidf\\\", \\\"kwargs\\\":{}}',\\n metavar=\\\"VECTORIZER_CONFIG_JSON\\\",\\n help='Json-format string for vectorizer config (default {\\\"type\\\":\\\"tfidf\\\", \\\"kwargs\\\":{}})',\\n )\\n\\n parser.add_argument(\\n \\\"--dtype\\\",\\n type=lambda x: np.float32 if \\\"32\\\" in x else np.float64,\\n default=np.float32,\\n help=\\\"data type for the csr matrix. float32 | float64. (default float32)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--max-leaf-size\\\",\\n type=cli.comma_separated_type(int),\\n default=[100],\\n metavar=\\\"INT-LIST\\\",\\n help=\\\"The max size of the leaf nodes of hierarchical 2-means clustering. Multiple values (separated by comma) are supported and will lead to different individual models for ensembling. (default [100])\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--nr-splits\\\",\\n type=int,\\n default=2,\\n metavar=\\\"INT\\\",\\n help=\\\"number of splits used to construct hierarchy (a power of 2 is recommended, default 2)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--imbalanced-ratio\\\",\\n type=float,\\n default=0.0,\\n metavar=\\\"FLOAT\\\",\\n help=\\\"Value between 0.0 and 0.5 (inclusive). Indicates how relaxed the balancedness constraint of 2-means can be. Specifically, if an iteration of 2-means is clustering L labels, the size of the output 2 clusters will be within approx imbalanced_ratio * 2 * L of each other. (default 0.0)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--imbalanced-depth\\\",\\n type=int,\\n default=100,\\n metavar=\\\"INT\\\",\\n help=\\\"After hierarchical 2-means clustering has reached this depth, it will continue clustering as if --imbalanced-ratio is set to 0.0. (default 100)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--label-embed-type\\\",\\n type=cli.comma_separated_type(str),\\n default=\\\"pifa\\\",\\n metavar=\\\"STR-LIST\\\",\\n help=\\\"Label embedding types. (default pifa).\\\\\\n We support pifa, pifa_lf_concat::Z=path, and pifa_lf_convex_combine::Z=path::alpha=scalar_value,\\\\\\n where path is the additional user-porivded label embedding path and alpha is the scalar value for convex combination.\\\\\\n Multiple values (separated by comma) are supported and will lead to different individual models for ensembling.\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--indexer\\\",\\n choices=Indexer.indexer_dict.keys(),\\n default=\\\"hierarchicalkmeans\\\",\\n metavar=\\\"STR\\\",\\n help=f\\\"Indexer algorithm (default hierarchicalkmeans). Available choices are {', '.join(Indexer.indexer_dict.keys())}\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--no-spherical\\\",\\n action=\\\"store_true\\\",\\n default=False,\\n help=\\\"Do not l2-normalize cluster centers while clustering\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--seed\\\",\\n type=cli.comma_separated_type(int),\\n default=[0],\\n metavar=\\\"INT-LIST\\\",\\n help=\\\"Random seeds (default 0). Multiple values (separated by comma) are supported and will lead to different individual models for ensembling.\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--max-iter\\\",\\n type=int,\\n default=20,\\n metavar=\\\"INT\\\",\\n help=\\\"The max iteration for indexing (default 20)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-n\\\",\\n \\\"--threads\\\",\\n type=int,\\n default=-1,\\n metavar=\\\"INT\\\",\\n help=\\\"Number of threads to use (default -1 to denote all the CPUs)\\\",\\n )\\n\\n # Linear matching/ranking parameters\\n parser.add_argument(\\n \\\"-s\\\",\\n \\\"--solver-type\\\",\\n type=str,\\n default=\\\"L2R_L2LOSS_SVC_DUAL\\\",\\n metavar=\\\"STR\\\",\\n help=\\\"{} (default L2R_L2LOSS_SVC_DUAL)\\\".format(\\\" | \\\".join(XLINEAR_SOLVERS.keys())),\\n )\\n\\n parser.add_argument(\\n \\\"--Cp\\\",\\n type=float,\\n default=1.0,\\n metavar=\\\"VAL\\\",\\n help=\\\"Coefficient for positive class in the loss function (default 1.0)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--Cn\\\",\\n type=float,\\n default=1.0,\\n metavar=\\\"VAL\\\",\\n help=\\\"Coefficient for negative class in the loss function (default 1.0)\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--bias\\\", type=float, default=1.0, metavar=\\\"VAL\\\", help=\\\"bias term (default 1.0)\\\"\\n )\\n\\n parser.add_argument(\\n \\\"-ns\\\",\\n \\\"--negative-sampling\\\",\\n type=str,\\n choices=[\\\"tfn\\\", \\\"man\\\", \\\"tfn+man\\\"],\\n default=\\\"tfn\\\",\\n metavar=\\\"STR\\\",\\n help=\\\"Negative Sampling Schemes\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-t\\\",\\n \\\"--threshold\\\",\\n type=float,\\n default=0.1,\\n metavar=\\\"VAL\\\",\\n help=\\\"Threshold to sparsify the model weights (default 0.1)\\\",\\n )\\n\\n # Prediction kwargs\\n parser.add_argument(\\n \\\"-k\\\",\\n \\\"--only-topk\\\",\\n type=int,\\n default=20,\\n metavar=\\\"INT\\\",\\n help=\\\"the default number of top labels used in the prediction\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-b\\\",\\n \\\"--beam-size\\\",\\n type=int,\\n default=10,\\n metavar=\\\"INT\\\",\\n help=\\\"the default size of beam search used in the prediction\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-pp\\\",\\n \\\"--post-processor\\\",\\n type=str,\\n choices=PostProcessor.valid_list(),\\n default=\\\"l3-hinge\\\",\\n metavar=\\\"STR\\\",\\n help=\\\"the default post processor used in the prediction\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--verbose-level\\\",\\n type=int,\\n choices=logging_util.log_levels.keys(),\\n default=1,\\n metavar=\\\"INT\\\",\\n help=f\\\"the verbose level, {', '.join([str(k) + ' for ' + logging.getLevelName(v) for k, v in logging_util.log_levels.items()])}, default 1\\\",\\n )\\n\\n parsed_args = parser.parse_args(args)\\n return parsed_args\",\n \"def parse_args(args):\\n parser = argparse.ArgumentParser(description='Parse your tophat align summary')\\n parser.add_argument(\\\"-v\\\", \\\"--verbose\\\", help=\\\"increase output verbosity\\\", action='store_true')\\n parser.add_argument(\\\"-m\\\", \\\"--mode\\\", help=\\\"input type is a directory or file\\\", choices=['file', 'directory'], default='directory')\\n parser.add_argument(\\\"-i\\\", \\\"--input\\\", metavar='</dir> || file1,file2... ', help=\\\"provide a list of file or direcotry\\\")\\n parser.add_argument(\\\"-o\\\", \\\"--out\\\", metavar='outfile.tsv', help=\\\"name of outputfile\\\")\\n\\n return parser.parse_args(args)\",\n \"def parse_arguments():\\r\\n # usage = \\\"usage: %(prog)s [options] <message file>\\\" + DESCRIPTION\\r\\n parser = ArgumentParser()\\r\\n parser.add_argument('-v', '--version', action='version', version=VERSION)\\r\\n parser.add_argument('csv_files', nargs='+', help='setup csv files')\\r\\n parser.add_argument('-r', '--res_filter', metavar='string',\\r\\n dest=\\\"res_filter\\\", default='',\\r\\n help=\\\"filter given resources, expect main input to be a directory\\\")\\r\\n parser.add_argument('-o', '--output_filter', metavar='string',\\r\\n dest=\\\"output_filter\\\", default='',\\r\\n help=\\\"if non-empty, filter given resources in output\\\")\\r\\n parser.add_argument('-f', '--fixed_start', action=\\\"store_true\\\", # or stare_false\\r\\n dest=\\\"fixed_start\\\", default=False, # negative store value\\r\\n help=\\\"report fixed start values, start - end value #items\\\")\\r\\n parser.add_argument('-q', '--quality', action=\\\"store_true\\\", # or stare_false\\r\\n dest=\\\"quality\\\", default=False, # negative store value\\r\\n help=\\\"compare setup quality\\\")\\r\\n parser.add_argument('-ref', '--reference_only', action=\\\"store_true\\\", # or stare_false\\r\\n dest=\\\"reference_only\\\", default=False, # negative store value\\r\\n help=\\\"use only refence csv files\\\")\\r\\n parser.add_argument('-res', '--result_only', action=\\\"store_true\\\", # or stare_false\\r\\n dest=\\\"result_only\\\", default=False, # negative store value\\r\\n help=\\\"use only result csv files\\\")\\r\\n parser.add_argument('-c', '--compare', metavar='string',\\r\\n dest=\\\"setup_compare\\\", default='',\\r\\n help=\\\"if non-empty, show setup quality for given days, e.g. 10,20,30\\\")\\r\\n parser.add_argument('-s', '--short_version', action=\\\"store_true\\\", # or stare_false\\r\\n dest=\\\"short_version\\\", default=False, # negative store value\\r\\n help=\\\"report short version of fixed start values, start - end value #items\\\")\\r\\n parser.add_argument('-m', '--maxtrix_values', metavar='string',\\r\\n dest=\\\"matrix_values\\\", default='',\\r\\n help=\\\"report setup matrix values for given messagefile\\\")\\r\\n parser.add_argument('-t', '--transitions', action=\\\"store_true\\\", # or stare_false\\r\\n dest=\\\"show_transitions\\\", default=False, # negative store value\\r\\n help=\\\"report transitions\\\")\\r\\n \\\"\\\"\\\"\\r\\n parser.add_argument('-m', '--mat-id', metavar='string', # or stare_false\\r\\n dest=\\\"id_mat\\\", default='', # negative store value\\r\\n help=\\\"material id to grep\\\")\\r\\n parser.add_argument('-c', '--count', metavar='N', type=int, # or stare_false\\r\\n dest=\\\"count\\\", default=0, # negative store value\\r\\n help=\\\"count\\\")\\r\\n parser.add_argument('-p', '--pattern', metavar='string', # or stare_false\\r\\n dest=\\\"pattern\\\", default='xxx', # negative store value\\r\\n help=\\\"search pattern within logfile\\\")\\r\\n \\\"\\\"\\\"\\r\\n return parser.parse_args()\",\n \"def parse_arguments():\\n\\n\\tparser = argparse.ArgumentParser(description=\\\"Markdown to HTML Converter\\\")\\n\\tparser.add_argument('md_file', action='store', help='Relative path to the markdown file to convert.')\\n\\tparser.add_argument('-o', '--output_file', action='store', default=None,\\n\\t help='Specifies output filename, otherwise uses the original filename with a .html extension')\\n\\tparser.add_argument('-c', '--contents', action='store_true', default=False,\\n\\t help='Creates a dynamic contents menu based on the headings in the document.')\\n\\tparser.add_argument('-n', '--numbered', action='store_true', default=False,\\n\\t help='Numbers headings and sub headings according to their level.')\\n\\targs = parser.parse_args()\\n\\n\\tmd_file = os.path.abspath(args.md_file)\\n\\tif not os.path.exists(md_file):\\n\\t\\traise FileNotFoundError('Markdown file %s does not exist.' % md_file)\\n\\n\\tif args.output_file is None:\\n\\t\\toutput_file = md_file[:-2] + 'html'\\n\\telse:\\n\\t\\toutput_file = os.path.abspath(args.output_file)\\n\\n\\treturn md_file, output_file, not args.contents, args.numbered\",\n \"def parse_arguments():\\n\\n parser = argparse.ArgumentParser(\\n description=\\\"生成用户字符串识别的切分字符串\\\"\\n )\\n parser.add_argument(\\n \\\"-o\\\",\\n \\\"--output_dir\\\",\\n type=str,\\n nargs=\\\"?\\\",\\n help=\\\"The output directory\\\",\\n default=\\\"output/\\\"\\n )\\n parser.add_argument(\\n \\\"-i\\\",\\n \\\"--input_file\\\",\\n type=str,\\n nargs=\\\"?\\\",\\n help=\\\"When set, this argument uses a specified text file as source for the text\\\",\\n default=\\\"\\\",\\n required=True\\n )\\n parser.add_argument(\\n \\\"-mi\\\",\\n \\\"--min_char_count\\\",\\n type=int,\\n nargs=\\\"?\\\",\\n help=\\\"The minimum number of characters per line, Default is 3.\\\",\\n default=3,\\n\\n )\\n parser.add_argument(\\n \\\"-ma\\\",\\n \\\"--max_char_count\\\",\\n type=int,\\n nargs=\\\"?\\\",\\n help=\\\"The maximum number of characters per line, Default is 20.\\\",\\n default=20,\\n )\\n return parser.parse_args()\",\n \"def parse_args():\\n from argparse import ArgumentParser\\n ap = ArgumentParser(prog=__exe__, description=__purpose__)\\n ap.add_argument('session', help='Session Label')\\n ap.add_argument('-sd', '--subjects_dir', help='Subjects Dir',\\n default='/tmp')\\n return ap.parse_args()\",\n \"def make_cli_parser(self):\\n usage = \\\"\\\"\\\"\\\\\\npython %prog [OPTIONS] INTERACTIONS_FILE ANNOTATIONS_FILE\\n\\nARGUMENTS:\\n INTERACTIONS_FILE: a CSV file containing interactions. The file\\n should have two columns with headings \\\"interactor1\\\" and\\n \\\"interactor2\\\". The file may have additional columns, which will\\n be ignored.\\n ANNOTATIONS_FILE: a file containing annotations. The annotations\\n file may be in one of two formats:\\n - GMT format: if the file ends with the extension \\\".gmt\\\", it is\\n automatically parsed as a GMT-format file. The file is a\\n tab-separated (TSV) format with no headers. The first column\\n contains the annotation term. The second column contains a\\n description. All following columns contain gene IDs for genes\\n annotated by that term. Full GMT format specification is\\n available from the MSigDB and GSEA website.\\n - Two-column format: The file should have a column titled\\n \\\"gene_id\\\" which has the gene/gene product ID, and a column\\n titled \\\"term\\\" which contains the term with which the\\n gene/product is annotated. The file may have additional\\n columns, which will be ignored.\\\\\\n\\\"\\\"\\\"\\n self.cli_parser = conflictsparse.ConflictsOptionParser(usage)\\n self.cli_parser.add_option('--links-outfile',\\n default=LINKS_OUTFILE,\\n help=(\\\"the file to which the links results should \\\"\\n \\\"be written [default: %default]\\\")\\n )\\n self.cli_parser.add_option('--logfile',\\n help=(\\\"the file to which information for the run will \\\"\\n \\\"be logged [default: {0}]\\\".format(\\n self.logfile_template.format('TIMESTAMP'))\\n )\\n )\",\n \"def parse_arguments():\\n description = \\\" \\\".join(__doc__.splitlines()[4:])\\n\\n epilog = \\\", \\\".join(__doc__.splitlines()[1:4])\\n parser = argparse.ArgumentParser(description=description, epilog=epilog)\\n parser.add_argument(\\n \\\"-i\\\",\\n type=str,\\n help=\\\"\\\"\\\"\\n the multiple sequence alignment fasta file with extension .aln to\\n use in input\\n \\\"\\\"\\\",\\n metavar=\\\"<file>\\\",\\n required=True,\\n )\\n parser.add_argument(\\n \\\"-o\\\",\\n metavar=\\\"<file>\\\",\\n type=str,\\n help=\\\"the file where to write the profile numpy array\\\",\\n required=True,\\n )\\n\\n args = parser.parse_args()\\n\\n return args\",\n \"def parse_args(self):\\n parser = argparse.ArgumentParser(description='Build PDF documentation')\\n parser.add_argument('config', help='YAML config file')\\n parser.add_argument('-f', '--fast', help='Do not update toc',\\n action='store_true', default=False)\\n parser.add_argument('-p', '--pandoc', help='Only pandoc, no latex',\\n action='store_true', default=False)\\n parser.add_argument('-n', '--nocache', help='Disable cache',\\n action='store_true', default=False)\\n parser.add_argument('-v', '--verbose', help='Enables verbose output; '\\n 'repeat up to three time for more verbose output',\\n action='count', default=0)\\n\\n self.args = parser.parse_args()\",\n \"def cmdline_parser(cls):\\n\\n # Add arguments that user can specify and put info you can discuss what each options are \\n parser = argparse.ArgumentParser(description=\\\"Produces a plot of a computed potential energy surface.\\\")\\n parser.add_argument('-i', '--input', type=str, default='input.dat', help=\\\"Name of the input file to be read in\\\")\\n parser.add_argument('-o', '--output', type=str, default='pes.pdf', help=\\\"Name of the output file to be created.\\\")\\n\\n # Store all the arguments from argparse into class variabes\\n args = parser.parse_args()\\n cls.infile_name = args.input\\n cls.outfile_name = args.output\\n\\n return None\",\n \"def parse_args():\\n\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument(\\n \\\"-i\\\", \\\"--input\\\", required=True, action=\\\"store\\\", dest=\\\"f_in\\\", help=\\\"input file\\\"\\n )\\n parser.add_argument(\\n \\\"-o\\\",\\n \\\"--output\\\",\\n required=True,\\n action=\\\"store\\\",\\n dest=\\\"f_out\\\",\\n help=\\\"stem of output file\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-d\\\",\\n \\\"--dir\\\",\\n required=True,\\n action=\\\"store\\\",\\n dest=\\\"dir\\\",\\n help=\\\"directory to save output files\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-t\\\",\\n \\\"--threshold\\\",\\n required=False,\\n action=\\\"store\\\",\\n dest=\\\"thres\\\",\\n default=0.85,\\n help=\\\"threshold for the scoring function\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-l\\\",\\n \\\"--language\\\",\\n required=True,\\n action=\\\"store\\\",\\n dest=\\\"lang\\\",\\n help=\\\"provide language in order to set stop words\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-min\\\",\\n \\\"--minimum\\\",\\n required=False,\\n action=\\\"store\\\",\\n dest=\\\"min\\\",\\n default=100,\\n help=\\\"minimum number of occurrences to be considered as ngram\\\",\\n )\\n\\n parser.add_argument(\\n \\\"--trigram\\\",\\n required=False,\\n action=\\\"store_true\\\",\\n dest=\\\"trigram\\\",\\n help=\\\"extracting trigrams in addition to bigrams\\\",\\n )\\n\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser('Reading Comprehension on BaiduRC dataset')\\n parser.add_argument('--prepare', action='store_true',\\n help='create the directories, prepare the vocabulary and embeddings')\\n parser.add_argument('--train', action='store_true',\\n help='train the model')\\n parser.add_argument('--generate', action='store_true',\\n help='predict the answers for test set with trained model')\\n parser.add_argument('--gentest', action='store_true',\\n help='predict the answers for test set with trained model')\\n parser.add_argument('--gpu', type=str, default='0',\\n help='specify gpu device')\\n\\n train_settings = parser.add_argument_group('train settings')\\n train_settings.add_argument('--optim', default='Adam',\\n help='optimizer type')\\n train_settings.add_argument('--learning_rate', type=float, default=0.001,\\n help='learning rate')\\n train_settings.add_argument('--weight_decay', type=float, default=0,\\n help='weight decay')\\n train_settings.add_argument('--dropout', type=float, default=0,\\n help='dropout keep rate')\\n train_settings.add_argument('--batch_size', type=int, default=128,\\n help='train batch size')\\n train_settings.add_argument('--epochs', type=int, default=10,\\n help='train epochs')\\n\\n model_settings = parser.add_argument_group('model settings')\\n model_settings.add_argument('--embed_size', type=int, default=128,\\n help='size of the embeddings')\\n model_settings.add_argument('--hidden_size', type=int, default=256,\\n help='size of LSTM hidden units')\\n model_settings.add_argument('--max_seq_len', type=int, default=50,\\n help='max passage num in one sample')\\n model_settings.add_argument('--max_gen_len', type=int, default=50,\\n help='max length of passage')\\n\\n path_settings = parser.add_argument_group('path settings')\\n path_settings.add_argument('--vocab_dir', default='../data/vocab/',\\n help='the dir to save vocabulary')\\n path_settings.add_argument('--model_dir', default='../data/models/',\\n help='the dir to store models')\\n path_settings.add_argument('--result_dir', default='../data/results/',\\n help='the dir to output the results')\\n path_settings.add_argument('--summary_dir', default='../data/summary/',\\n help='the dir to write tensorboard summary')\\n path_settings.add_argument('--log_path',\\n help='path of the log file. If not set, logs are printed to console')\\n return parser.parse_args()\",\n \"def prepare_arg_parser():\\n\\tparser = argparse.ArgumentParser(\\n\\t\\tdescription=\\\"\\\"\\\"Ajout des ponctuations réelles dans un xml de \\n\\t\\t refbibs (NB lent: ~ 2 doc/s sur 1 thread)\\\"\\\"\\\",\\n\\t\\tusage=\\\"\\\"\\\"ragreage.py \\n\\t\\t -x ech/tei.xml/oup_Human_Molecular_Genetics_ddp278.xml\\n\\t\\t -p ech/pdf/oup_Human_Molecular_Genetics_ddp278.pdf\\n\\t\\t -m [bibzone|biblines|bibfields|authornames]\\\"\\\"\\\",\\n\\t\\tepilog=\\\"- © 2014-15 Inist-CNRS (ISTEX) romain.loth at inist.fr -\\\"\\n\\t\\t)\\n\\t\\n\\t\\n\\tparser.add_argument('-x','--xmlin',\\n\\t\\tmetavar='path/to/xmlfile',\\n\\t\\thelp=\\\"\\\"\\\"\\n\\t\\tpath to a TEI.xml with citations in <biblStruct> xml format \\n\\t\\t(perhaps to be created from native XML by a call like \\n\\t\\t`saxonb-xslt -xsl:tools/Pub2TEI/Stylesheets/Publishers.xsl\\n\\t\\t-s:exemples_RONI_1513/rsc_1992_C3_C39920001646.xml`)'\\\"\\\"\\\",\\n\\t\\ttype=str,\\n\\t\\trequired=True,\\n\\t\\taction='store')\\n\\t\\t\\n\\t\\n\\t\\n\\tparser.add_argument('-p','--pdfin',\\n\\t\\tmetavar='path/to/pdffile',\\n\\t\\thelp=\\\"\\\"\\\"path to a pdf file of the same text, for attempted\\n\\t\\t pdftottext and citation regexp match\\\"\\\"\\\",\\n\\t\\ttype=str,\\n\\t\\tdefault=None , # cf juste en dessous\\n\\t\\taction='store')\\n\\t\\n\\tparser.add_argument('-t','--txtin',\\n\\t\\tmetavar='path/to/txtfile',\\n\\t\\thelp=\\\"\\\"\\\"pdfin can be replaced by a path to a txt flow.\\n\\t\\tThis input text must be very close to the xml content\\n\\t\\t(or segment thereof, in accordance with a chosen -m type)\\\"\\\"\\\",\\n\\t\\ttype=str,\\n\\t\\tdefault=None , # cf juste en dessous\\n\\t\\taction='store')\\n\\t\\t\\n\\t\\n\\t\\n\\tparser.add_argument('-m','--model-type',\\n\\t\\tmetavar='name-of-model',\\n\\t\\thelp=\\\"\\\"\\\"format output as a valid tei's 'listBibl' (default)\\n\\t\\t or tailored to a Grobid crf model pseudotei input among:\\n\\t\\t {'bibzone', 'biblines', 'bibfields', 'authornames'}\\\"\\\"\\\",\\n\\t\\ttype=str,\\n\\t\\tdefault='listBibl' ,\\n\\t\\taction='store')\\n\\t\\n\\t\\n\\tparser.add_argument('-d','--debug',\\n\\t\\tmetavar=1,\\n\\t\\ttype=int,\\n\\t\\thelp='logging level for debug info in [0-3]',\\n\\t\\tdefault=0,\\n\\t\\taction='store')\\n\\t\\n\\t\\t\\n\\tparser.add_argument('-r', '--remainder',\\n\\t\\tdest='mask',\\n\\t\\thelp='show mask after matches instead of normal output',\\n\\t\\taction='store_true')\\n\\t\\n\\treturn parser\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description=_program_description)\\n parser.add_argument('input_file', help=_input_file_description)\\n #parser.add_argument('-v', '--verbose', action='store_true', \\n # default=False, help='show progress')\\n args = parser.parse_args()\\n return args\",\n \"def cmd_line_parser():\\n usage = \\\"usage: %prog [options]\\\\n\\\"\\n opt_parser = OptionParser(usage=usage)\\n opt_parser.add_option(\\\"--ai\\\", action=\\\"store\\\", dest=\\\"alternative_input\\\",\\n help=\\\"an alternative input file (works only with load_from_pickle)\\\")\\n opt_parser.add_option(\\\"--dl\\\", action=\\\"store\\\", dest=\\\"dumped_lexicon\\\",\\n help=\\\"a dumped lexicon file (works only with load_from_pickle\\\")\\n opt_parser.add_option(\\\"--dotest\\\", action=\\\"store_true\\\", dest=\\\"dotest\\\", default=False,\\n help=\\\"use this flag if you want to apply testing\\\")\\n opt_parser.add_option(\\\"-t\\\", action=\\\"store\\\", dest=\\\"test_parses\\\",\\n help=\\\"the output file for the test parses\\\")\\n opt_parser.add_option(\\\"-n\\\", action=\\\"store\\\", dest=\\\"train_parses\\\",\\n help=\\\"the output file for the train parses\\\")\\n opt_parser.add_option(\\\"-i\\\", dest=\\\"inp_file\\\", default=\\\"trainFiles/trainPairs\\\",\\n help=\\\"the input file names (with the annotated corpus)\\\")\\n opt_parser.add_option(\\\"--devel\\\", dest=\\\"development_mode\\\", default=False, action=\\\"store_true\\\",\\n help=\\\"development mode\\\")\\n\\n return opt_parser\",\n \"def arg_parse():\\n parser = argparse.ArgumentParser()\\n # defines command line arguments\\n parser.add_argument('-i', '--input_file', help=\\\"The input .txt file \\\" +\\n \\\"within the current directory (the file you \\\" +\\n \\\"downloaded from VEP\\\")\\n parser.add_argument('-o', '--output_file', help=\\\"Name for the output \\\" +\\n \\\".txt file\\\")\\n\\n return parser.parse_args()\",\n \"def parse_arguments():\\n #usage = \\\"usage: %(prog)s [options] <message file>\\\" + DESCRIPTION\\n parser = ArgumentParser()\\n parser.add_argument('-v', '--version', action='version', version=VERSION)\\n parser.add_argument('source', metavar='source', help='input logfile or directory with logfiles')\\n\\n \\\"\\\"\\\"\\n parser.add_argument('-m', '--mat-id', metavar='string', # or stare_false\\n dest=\\\"id_mat\\\", default='', # negative store value\\n help=\\\"material id to grep\\\")\\n parser.add_argument('-c', '--count', metavar='N', type=int, # or stare_false\\n dest=\\\"count\\\", default=0, # negative store value\\n help=\\\"count\\\")\\n parser.add_argument('-p', '--pattern', metavar='string', # or stare_false\\n dest=\\\"pattern\\\", default='xxx', # negative store value\\n help=\\\"search pattern within logfile\\\")\\n \\\"\\\"\\\"\\n return parser.parse_args()\",\n \"def cmdline_parser():\\n\\n # http://docs.python.org/dev/howto/argparse.html\\n parser = argparse.ArgumentParser(description=__doc__)\\n \\n parser.add_argument(\\\"--verbose\\\",\\n action=\\\"store_true\\\",\\n help=\\\"Be verbose\\\")\\n parser.add_argument(\\\"--debug\\\",\\n action=\\\"store_true\\\",\\n help=\\\"Enable debugging\\\")\\n parser.add_argument(\\\"-b\\\", \\\"--bam\\\",\\n required=True,\\n help=\\\"Input BAM file matching vcf\\\")\\n parser.add_argument(\\\"-i\\\", \\\"--vcf\\\",\\n help=\\\"Input VCF file containing variants to analyze\\\"\\n \\\" (clashes with --var)\\\")\\n parser.add_argument(\\\"-v\\\", \\\"--var\\\",\\n help=\\\"Report reads for this variant only. Format: chr:pos:ref-alt\\\"\\n \\\" (clashes with --vcf)\\\")\\n default = 0\\n parser.add_argument(\\\"--mq-filter\\\",\\n dest=\\\"min_mq\\\",\\n type=int,\\n default=default,\\n help=\\\"Ignore reads with mapping quality below this value (default=%d)\\\" % default)\\n default = 5\\n parser.add_argument(\\\"--bq-filter\\\",\\n dest=\\\"min_bq\\\",\\n type=int,\\n default=default,\\n help=\\\"Ignore reads with bases below this value (default=%d)\\\" % default)\\n parser.add_argument(\\\"-a\\\", \\\"--use-orphan\\\",\\n action=\\\"store_true\\\",\\n help=\\\"Don't ignore orphan-reads / anomalous read-pairs\\\")\\n\\n return parser\",\n \"def parse_cli_arguments():\\n parser = argparse.ArgumentParser('Generates a MANIFEST file used by the '\\n 'HMP2 AnADAMA2 workflows.')\\n parser.add_argument('-b', '--broad-data-sheet', required=True,\\n help='Broad data product status spreadsheet. '\\n 'Contains entries indicating new files to be '\\n 'processed.')\\n parser.add_argument('-o', '--output-manifest', required=True,\\n help='Path to desired output manifest file.')\\n parser.add_argument('-oi', '--origin-institute', required=True,\\n help='Name of institute submitting new files '\\n 'to be processed.')\\n parser.add_argument('-oc', '--origin-contact', required=True,\\n help='Contact person for corresponding origin '\\n 'institute.')\\n parser.add_argument('-oe', '--origin-contact-email', required=True,\\n help='Contact email for contact person.')\\n parser.add_argument('-p', '--project-name', dest='project', \\n required=True,\\n help='Project that sequence files belong too.')\\n\\n return parser.parse_args()\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-f\\\", \\\"--file\\\", help=\\\"file with the cohort you want to check / fix\\\", type=str, required=True)\\n parser.add_argument(\\\"-o\\\", \\\"--outdir\\\", help=\\\"where should the files and the result readme be stored?\\\", type=str, required=True)\\n return parser.parse_args()\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-u', '--urls_dirpath', type=unicode)\\n parser.add_argument('-r', '--resources_dir', type=unicode)\\n parser.add_argument('-t', '--total_docs', type=int)\\n parser.add_argument('-m', '--mapping', type=unicode,\\n help='File with the yago to lkif mapping')\\n\\n return parser.parse_args()\",\n \"def cmdline_parser():\\n parser = argparse.ArgumentParser(description=\\\"\\\"\\\" \\\"\\\"\\\")\\n parser.add_argument(\\\"-i1\\\",\\n help=\\\"\\\"\\\"viral alignments\\\"\\\"\\\",\\n dest=\\\"viral\\\",\\n required=True)\\n parser.add_argument(\\\"-i2\\\",\\n help=\\\"\\\"\\\"GTA alignments\\\"\\\"\\\",\\n dest=\\\"gta\\\",\\n required=True)\\n parser.add_argument(\\\"-o\\\",\\n dest=\\\"output\\\",\\n help=\\\"output image file\\\")\\n return parser\",\n \"def ParseArguments():\\n\\t#TODO: check input variable types!\\n\\t# check for integers ans strings\\n\\t# check for distance and distance cutoff value: ONLY CERTAIN VALUES ALLOWED\\n\\targ_parser = argparse.ArgumentParser(description=\\\"Program to get background distribution matching user input SNPs on the following parameters {MAF, distance to nearest gene, gene density}\\\")\\n\\tsubparsers = arg_parser.add_subparsers(dest='subcommand',\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t title='subcommands in this script',\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t description='valid subcommands. set subcommand after main program required arguments',\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t help='You can get additional help by writing <program-name> <subcommand> --help')\\n\\n\\t## Subparsers\\n\\targ_parser_annotate = subparsers.add_parser('annotate')\\n\\t#arg_parser_annotate.set_defaults(func=run_annotate)\\n\\targ_parser_match = subparsers.add_parser('match')\\n\\t#arg_parser_annotate.set_defaults(func=run_match)\\n\\n\\n\\targ_parser.add_argument(\\\"--user_snps_file\\\", help=\\\"Path to file with user-defined SNPs\\\", required=True) # TODO: make the program read from STDIN via '-'\\n\\targ_parser.add_argument(\\\"--output_dir\\\", help=\\\"Directory in which output files, i.e. random SNPs will be written\\\", required=True)\\n\\t#arg_parser.add_argument(\\\"--output_dir\\\", type=ArgparseAdditionalUtils.check_if_writable, help=\\\"Directory in which output files, i.e. random SNPs will be written\\\", required=True)\\n\\targ_parser.add_argument(\\\"--distance_type\\\", help=\\\"ld or kb\\\", required=True)\\n\\targ_parser.add_argument(\\\"--distance_cutoff\\\", help=\\\"r2, or kb distance\\\", required=True)\\n\\t# NEW: options\\n\\t#arg_parser.add_argument(\\\"--status_file\\\", help=\\\"Bool (switch, takes no value after argument); if set then logging is ENABLED.\\\", action='store_true')\\n\\t#arg_parser.add_argument(\\\"--status_file\\\", help=\\\"If set, a json file will be written. Value should be the a filepath.\\\")\\n\\targ_parser.add_argument(\\\"--web\\\", help=\\\"If set, the program will run in web mode. VALUE should be the a filepath to output (temporary) file - usually this will be the session_id. The web mode activates: 1) creating a status_obj and writing it to json file; 2) ENABLE writing a json report file;\\\")\\n\\targ_parser.add_argument(\\\"--NoLogger\\\", help=\\\"Bool (switch, takes no value after argument); if set then logging is DISAPLED. Logfile will be placed in outputdir.\\\", action='store_true')\\n\\n\\n\\t### MATCH arguments\\n\\targ_parser_match.add_argument(\\\"--N_sample_sets\\\", type=int, help=\\\"Number of matched SNPs to retrieve\\\", required=True) # 1000 - \\\"Permutations?\\\" TODO: change name to --n_random_snp_sets or --N\\n\\t#TODO: add argument that describes if ABSOLUTE of PERCENTAGE deviation should be used\\n\\targ_parser_match.add_argument(\\\"--max_freq_deviation\\\", type=int,help=\\\"Maximal deviation of SNP MAF bin [MAF +/- deviation]\\\", default=5) # 5\\n\\targ_parser_match.add_argument(\\\"--max_distance_deviation\\\", type=int, help=\\\"Maximal PERCENTAGE POINT deviation of distance to nearest gene [distance +/- %%deviation])\\\", default=5) # 20000\\n\\t#TODO: CHECK THAT max_distance_deviation > 1 %\\n\\t#TODO: WHY IS max_genes_count_deviation type float!!!!????\\n\\targ_parser_match.add_argument(\\\"--max_genes_count_deviation\\\", type=float, help=\\\"Maximal PERCENTAGE POINT deviation of genes in locus [gene_density +/- %%deviation]\\\", default=5) # 0.2\\n\\targ_parser_match.add_argument(\\\"--set_file\\\", help=\\\"Bool (switch, takes no value after argument); if set then write out set files to rand_set..gz. Default is false\\\", action='store_true')\\n\\n\\targs = arg_parser.parse_args()\\n\\n\\treturn args\",\n \"def parse_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"in_fq\\\", help=\\\"The fastq file containing Hi-C reads.\\\")\\n parser.add_argument(\\n \\\"-r\\\",\\n \\\"--reference\\\",\\n required=True,\\n help=\\\"Path to the reference genome, in FASTA format.\\\",\\n )\\n parser.add_argument(\\n \\\"-p\\\",\\n \\\"--nb_processors\\\",\\n default=1,\\n type=int,\\n help=\\\"number of CPUs used for alignment.\\\",\\n )\\n parser.add_argument(\\n \\\"-o\\\",\\n \\\"--out_sam\\\",\\n help=\\\"Path to the output SAM file for the alignment of in_fq.\\\",\\n )\\n parser.add_argument(\\n \\\"-T\\\",\\n \\\"--tempdir\\\",\\n default=\\\".\\\",\\n help=\\\"Directory to write temporary files. Defaults to current directory.\\\",\\n )\\n parser.add_argument(\\n \\\"-m\\\",\\n \\\"--minimap2\\\",\\n default=False,\\n action=\\\"store_true\\\",\\n help=\\\"Use minimap2 instead of bowtie for the alignment.\\\",\\n )\\n parser.add_argument(\\n \\\"-l\\\",\\n \\\"--min_len\\\",\\n type=int,\\n default=20,\\n help=\\\"Minimum length to which reads should be truncated.\\\",\\n )\\n return parser.parse_args()\",\n \"def parse_args():\\n help_text = \\\"\\\"\\\"\\n Analyzer of the frequency of use of nouns in the headings of posts on hubr.com\\n \\\"\\\"\\\"\\n parser = argparse.ArgumentParser(\\n description=help_text\\n )\\n parser.add_argument(\\n '-p',\\n '--pages',\\n type=int,\\n dest='page_count',\\n default=PAGE_COUNT,\\n help=f'Number of pages to parse, default is {PAGE_COUNT}.'\\n )\\n parser.add_argument(\\n '-s',\\n '--start',\\n type=int,\\n default=PAGE_START,\\n dest='start_page',\\n help=f'Start page number, default is {PAGE_START}.',\\n )\\n parser.add_argument(\\n '-t',\\n '--top',\\n type=int,\\n default=TOP_SIZE,\\n dest='top_size',\\n help=f'The size of the top noun, default is {TOP_SIZE}.',\\n )\\n\\n return parser.parse_args()\",\n \"def make_parser():\\n\\n parser = argparse.ArgumentParser(add_help=True)\\n\\n parser_grp_main = parser.add_argument_group('Arguments')\\n\\n parser_grp_main.add_argument\\n\\n parser_grp_main.add_argument(\\n \\\"-i\\\",\\n \\\"--inp-dir\\\",\\n default = \\\"out/ln/alias/sst/all_samples\\\",\\n help=\\\"The folder containing files to tidy.\\\"\\n )\\n\\n parser_grp_main.add_argument(\\n \\\"-x\\\",\\n \\\"--xlsx\\\",\\n type=str,\\n help=\\\"The xlsx file containing the metadata to use to find samples and tidy them.\\\",\\n default=\\\"Sequencing_summary.xlsx\\\",\\n required=False)\\n\\n parser_grp_main.add_argument(\\n \\\"-b\\\",\\n \\\"--by-column\\\",\\n nargs='+',\\n type=str,\\n help=\\\"The column names from the xlsx file to use to tidy.\\\",\\n default=\\\"sample_name\\\",\\n required=False)\\n \\n parser_grp_main.add_argument(\\n \\\"-d\\\",\\n \\\"--delete\\\",\\n help=\\\"Delete file only this arg is used. Unsafe. Always run first without this argument and check all files listed to deletion.\\\",\\n default=False,\\n type=bool,\\n )\\n\\n return parser\",\n \"def get_parse():\\n parser = argparse.ArgumentParser(description=print(mytext),\\n add_help=True,\\n formatter_class=argparse.RawTextHelpFormatter)\\n requiredNAMED = parser.add_argument_group('required arguments')\\n\\n requiredNAMED.add_argument(\\\"-i\\\", \\\"--input\\\",\\n required=True,\\n default=None,\\n dest=\\\"input\\\",\\n type=str,\\n help='''/path/to/VariantsToTable_output.txt\\nIt is assumed that there is either a 'locus' or 'unstitched_locus' column.\\nThe 'locus' column elements are the hyphen-separated\\nCHROM-POS. If the 'unstitched_chrom' column is present, the code will use the\\n'unstitched_locus' column for SNP names, otherwise 'CHROM' and 'locus'. The\\n'unstitched_locus' elements are therefore the hyphen-separated \\nunstitched_locus-unstitched_pos. FREQ columns from VarScan are also \\nassumed.\\n''')\\n requiredNAMED.add_argument(\\\"-o\\\",\\\"--outdir\\\",\\n required=True,\\n default=None,\\n dest=\\\"outdir\\\",\\n type=str,\\n help='''/path/to/cmh_test_output_dir/\\nFile output from cmh_test.py will be saved in the outdir, with the original\\nname of the input file, but with the suffix \\\"_CMH-test-results.txt\\\"''')\\n requiredNAMED.add_argument(\\\"--case\\\",\\n required=True,\\n default=None,\\n dest=\\\"case\\\",\\n type=str,\\n help='''The string present in every column for pools in \\\"case\\\" treatments.''')\\n requiredNAMED.add_argument(\\\"--control\\\",\\n required=True,\\n default=None,\\n dest=\\\"control\\\",\\n type=str,\\n help='''The string present in every column for pools in \\\"control\\\" treatments.''') \\n requiredNAMED.add_argument(\\\"-p\\\",\\\"--ploidy\\\",\\n required=True,\\n default=None,\\n dest=\\\"ploidyfile\\\",\\n type=str,\\n help='''/path/to/the/ploidy.pkl file output by the VarScan pipeline. This is a python\\ndictionary with key=pool_name, value=dict with key=pop, value=ploidy. The code\\nwill prompt for pool_name if necessary.''')\\n requiredNAMED.add_argument(\\\"-e\\\",\\\"--engines\\\",\\n required=True,\\n default=None,\\n dest=\\\"engines\\\",\\n type=int,\\n help=\\\"The number of ipcluster engines that will be launched.\\\")\\n parser.add_argument(\\\"--ipcluster-profile\\\",\\n required=False,\\n default='default',\\n dest=\\\"profile\\\",\\n type=str,\\n help=\\\"The ipcluster profile name with which to start engines. Default: 'default'\\\")\\n parser.add_argument('--keep-engines',\\n required=False,\\n action='store_true',\\n dest=\\\"keep_engines\\\",\\n help='''Boolean: true if used, false otherwise. If you want to keep\\nthe ipcluster engines alive, use this flag. Otherwise engines will be killed automatically.\\n(default: False)''')\\n\\n # check flags\\n args = parser.parse_args()\\n if not op.exists(args.outdir):\\n print(ColorText(f\\\"FAIL: the directory for the output file(s) does not exist.\\\").fail())\\n print(ColorText(f\\\"FAIL: please create this directory: %s\\\" % args.outdir).fail())\\n print(ColorText(\\\"exiting cmh_test.py\\\").fail())\\n exit()\\n\\n # make sure input and ploidyfile exist\\n nopath = []\\n for x in [args.input, args.ploidyfile]: # TODO: check for $HOME or other bash vars in path\\n if not op.exists(x):\\n nopath.append(x)\\n\\n # if input or ploidy file do not exist:\\n if len(nopath) > 0:\\n print(ColorText(\\\"FAIL: The following path(s) do not exist:\\\").fail())\\n for f in nopath:\\n print(ColorText(\\\"\\\\tFAIL: %s\\\" % f).fail())\\n print(ColorText('\\\\nexiting cmh_test.py').fail())\\n exit()\\n\\n print('args = ', args)\\n return args\",\n \"def parseArguments():\\n parser = argparse.ArgumentParser(description=__doc__.split(\\\"\\\\n\\\")[0])\\n\\n input = parser.add_argument_group(\\\"input\\\",\\n description=\\\"Supported URL list formats.\\\")\\n input.add_argument(\\\"-g\\\", \\\"--gcsv\\\", nargs=\\\"?\\\",\\n help=\\\"path to Google crawl error csv file(s)\\\")\\n input.add_argument(\\\"-p\\\", \\\"--plain\\\", nargs=\\\"?\\\",\\n help=\\\"path to newline separated file(s)\\\")\\n\\n output = parser.add_argument_group(\\\"output\\\",\\n description=\\\"Supported output formats.\\\")\\n formats = {\\\"rack\\\": \\\"rack-rewrite 301 static redirect\\\",\\n \\\"csv\\\": \\\"comma separated\\\"}\\n output.add_argument(\\\"-o\\\", \\\"--output\\\", choices=formats.keys(),\\n help=\\\"an output format; one of: \\\" + pprint.saferepr(formats) +\\n \\\" else, a machine-readable format\\\")\\n output.add_argument(\\\"-e\\\", \\\"--ext\\\", action=\\\"store_true\\\",\\n help=\\\"remove file extension in redirects\\\")\\n output.add_argument(\\\"-s\\\", \\\"--subdomain\\\", action=\\\"store_true\\\",\\n help=\\\"remove subdomains in redirects\\\")\\n\\n files = parser.add_argument_group(\\\"files\\\",\\n description=\\\"Heuristics regarding filename format.\\\")\\n files.add_argument(\\\"-u\\\", \\\"--utc\\\", action=\\\"store_true\\\",\\n help=\\\"filenames start with a date in UTC format\\\")\\n\\n search = parser.add_argument_group(\\\"search\\\",\\n description=\\\"Fuzzy search parameters.\\\")\\n search.add_argument(\\\"-c\\\", \\\"--cutoff\\\", default=0.32, type=float,\\n help=\\\"fuzzy search threshold (float, defaults to: 0.32)\\\")\\n search.add_argument(\\\"-m\\\", \\\"--matches\\\", default=1, type=int,\\n help=\\\"number of fuzzy search matches (int, defaults to: 1)\\\")\\n\\n parser.add_argument(\\\"-d\\\", \\\"--dirs\\\", nargs=\\\"?\\\", default=\\\".\\\",\\n help=\\\"path to directory(s) of files\\\")\\n\\n return parser.parse_args()\",\n \"def parse_args(arglist):\\n help = dedent(\\\"\\\"\\\"\\n Currently this can start with ROIs defined as a surface label on\\n fsaverage, labels defined on each subject's native surface, ROIs\\n defined on the high-res volume in Freesurfer space, or a statistical\\n volume from a subject-level analysis.\\n\\n You can always pass a filepath (possibly with ``subj`` and ``hemi``\\n string format keys to -orig and the program will work out what to\\n do from the file type and other arugments. Alternatively, if files\\n are in expected places (Freesurfer data hierarchy, lyman analysis\\n hierarchy) there are shortcuts for the corresponding image type.\\n\\n The processing is almost entirely dependent on external binaries\\n from FSL and Freesurfer, so both must be availible.\\n\\n The resulting masks are defined in the space of the first functional\\n run. This is also the target of the ``-regspace epi`` registration\\n in the main lyman fmri workflows.\\n\\n The processing here is closely tied to these fmri workflows and requires\\n subject-level preprocessing to have been performed. This program\\n should be executed from a directory containing a project.py file\\n that defines the relevant data and analysis paths.\\n\\n The script will also write a mosiac png with the mask overlaid on\\n the mean functional image defining the epi space. Additionally, it\\n will write a json file with the command line argument dictionary\\n for provenence tracking.\\n\\n If an IPython cluster is running, the processing will be executed\\n in parallel by default on all availible engines. This can be avoided\\n by using the -serial option.\\n\\n Usage Details\\n -------------\\n\\n \\\"\\\"\\\")\\n\\n parser = argparse.ArgumentParser(description=help,\\n formatter_class=argparse.RawDescriptionHelpFormatter)\\n\\n # Necessary arguments\\n parser.add_argument(\\\"-s\\\", \\\"-subjects\\\", nargs=\\\"*\\\", dest=\\\"subjects\\\",\\n help=\\\"lyman subjects argument\\\")\\n parser.add_argument(\\\"-roi\\\", required=True,\\n help=\\\"will form name of output mask file\\\")\\n\\n # Optional argument (that always applies)\\n parser.add_argument(\\\"-exp\\\",\\n help=\\\"experiment (can use default from project.py)\\\")\\n\\n # Generic input\\n parser.add_argument(\\\"-orig\\\",\\n help=\\\"path to original file with subj and hemi format keys\\\")\\n\\n # Label relavent arguments\\n parser.add_argument(\\\"-label\\\", help=\\\"label name if in Freesurfer hierachy\\\")\\n parser.add_argument(\\\"-native\\\", action=\\\"store_true\\\",\\n help=\\\"orig label is defined on native surface\\\")\\n parser.add_argument(\\\"-hemi\\\", choices=[\\\"lh\\\", \\\"rh\\\"],\\n help=\\\"hemisphere if unilateral label - otherwise combine both\\\")\\n parser.add_argument(\\\"-sample\\\",\\n choices=[\\\"white\\\", \\\"graymid\\\", \\\"pial\\\", \\\"cortex\\\"],\\n help=\\\"shortcut for projection arguments\\\")\\n parser.add_argument(\\\"-proj\\\", nargs=4,\\n help=\\\"projection args passed directly mri_label2vol\\\")\\n parser.add_argument(\\\"-save_native\\\", action=\\\"store_true\\\",\\n help=\\\"save label file after warping from common space\\\")\\n\\n # Atlas-type image relevant images\\n parser.add_argument(\\\"-aseg\\\", action=\\\"store_true\\\",\\n help=\\\"atlas image is aseg.mgz\\\")\\n parser.add_argument(\\\"-id\\\", type=int, nargs=\\\"*\\\",\\n help=\\\"roi id(s) if orig is index volume\\\")\\n\\n # Thresholded statistic relevant arguments\\n parser.add_argument(\\\"-contrast\\\",\\n help=\\\"first-level contrast to binarize z-stat map\\\")\\n parser.add_argument(\\\"-thresh\\\", help=\\\"z-stat threshold\\\")\\n parser.add_argument(\\\"-unsmoothed\\\", action=\\\"store_true\\\",\\n help=\\\"use unsmoothed fixed effects zstats\\\")\\n parser.add_argument(\\\"-altmodel\\\",\\n help=\\\"stat file is from alternative model\\\")\\n\\n # Generic execution relevant arguments\\n parser.add_argument(\\\"-serial\\\", action=\\\"store_true\\\",\\n help=\\\"force serial execution\\\")\\n parser.add_argument(\\\"-debug\\\", action=\\\"store_true\\\",\\n help=\\\"enable debug mode\\\")\\n\\n return parser.parse_args(arglist)\",\n \"def parse_args():\\n parser = argparse.ArgumentParser('Reading Comprehension on HOTPOT dataset')\\n parser.add_argument('--prepare', action='store_true',\\n help='create the directories, prepare the vocabulary and embeddings')\\n parser.add_argument('--train', action='store_true',\\n help='train the model')\\n parser.add_argument('--evaluate', action='store_true',\\n help='evaluate the model on dev set')\\n parser.add_argument('--predict', action='store_true',\\n help='predict the answers for test set with trained model')\\n parser.add_argument('--gpu', type=str, default='0',\\n help='specify gpu device')\\n\\n train_settings = parser.add_argument_group('train settings')\\n train_settings.add_argument('--mode', type=str,\\n default='D-graph',\\n help='fine-tune or D-graph')\\n train_settings.add_argument('--Bert_model', type=str,\\n default='bert-base-uncased',\\n help='model of Bert')\\n train_settings.add_argument('--at_head', type=int,\\n default=1,\\n help='The head for graph neural network.')\\n train_settings.add_argument('--propagate_count',type=int,default=3,\\n help='The number of propagating in graph neural network')\\n train_settings.add_argument('--optim', default='adam',\\n help='optimizer type')\\n train_settings.add_argument('--learning_rate', type=float, default=0.001,\\n help='learning rate')\\n train_settings.add_argument('--weight_decay', type=float, default=0,\\n help='weight decay')\\n train_settings.add_argument('--dropout_keep_prob', type=float, default=1,\\n help='dropout keep rate')\\n train_settings.add_argument('--batch_size', type=int, default=12,\\n help='train batch size')\\n train_settings.add_argument('--epochs', type=int, default=1,\\n help='train epochs')\\n train_settings.add_argument('--gradient_accumulation_steps', type=int, default=1,\\n help='gradient accumulation steps')\\n\\n model_settings = parser.add_argument_group('model settings')\\n model_settings.add_argument('--max_s_num', type=int, default=6,\\n help='max sentence num in one paragraph')\\n model_settings.add_argument('--max_p_len', type=int, default=491,\\n help='max length of paragraph')\\n model_settings.add_argument('--max_s_len', type=int, default=70,\\n help='max length of sentence')\\n\\n path_settings = parser.add_argument_group('path settings')\\n\\n path_settings.add_argument('--train_files', nargs='+',\\n default=['./data/hotpot_train_v1.1_small_refine.json'],\\n help='list of files that contain the preprocessed train data')\\n path_settings.add_argument('--dev_files', nargs='+',\\n default=['./data/hotpot_dev_fullwiki_v1_refine.json'],\\n help='list of files that contain the preprocessed dev data')\\n path_settings.add_argument('--test_files', nargs='+',\\n default=['./data/hotpot_test_fullwiki_v1_refine.json'],\\n help='list of files that contain the preprocessed test data')\\n path_settings.add_argument('--vocab_dir', default='./vocab/',\\n help='the dir to save vocabulary')\\n path_settings.add_argument('--model_dir', default='./models/',\\n help='the dir to store models')\\n path_settings.add_argument('--result_dir', default='./result/',\\n help='the dir to output the results')\\n path_settings.add_argument('--log_path',\\n help='path of the log file. If not set, logs are printed to console')\\n return parser.parse_args()\",\n \"def parse_cmd_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-i\\\", \\\"--path_in\\\", type=str, default=\\\"data/main/main.csv\\\", help=\\\"Path to main.csv\\\")\\n parser.add_argument(\\\"-o\\\", \\\"--path_out\\\", type=str, default=\\\"data/main/main_swiss_char.csv\\\",\\n help=\\\"Path to output file\\\")\\n parser.add_argument(\\\"-t\\\", \\\"--threshold\\\", type=int, default=80, help=\\\"threshold of non-swiss-characters to predict text as non-swiss-german\\\")\\n parser.add_argument(\\\"-p\\\", \\\"--print_only\\\", default=False, action=\\\"store_true\\\",\\n help=\\\"Do not write to file - only print non-swiss-char tweets.\\\")\\n\\n return parser.parse_args()\",\n \"def process_arguments():\\r\\n # Create ArgumentParser object. Description message will be displayed as part of help message if script is run with -h flag\\r\\n parser = argparse.ArgumentParser(description='Downloads summary of findings for given interpretation request')\\r\\n # Define the arguments that will be taken.\\r\\n parser.add_argument('--ir_id', required=True, help='Interpretation request ID')\\r\\n parser.add_argument('--ir_version', required=True, help='Interpretation request version')\\r\\n parser.add_argument('-o', '--output_file', required=True, help='Output PDF')\\r\\n parser.add_argument('--header', required=False, help='Text for header of report')\\r\\n # Return the arguments\\r\\n return parser.parse_args()\",\n \"def __parse_args(self):\\n for argument in self.args:\\n source_arg = re.match(\\\"^(--source=(([A-Z]|[a-z]|/|_|[0-9]|.)+))$\\\", argument)\\n input_arg = re.match(\\\"^(--input=(([A-Z]|[a-z]|/|_|[0-9]|.)+))$\\\", argument)\\n stats_arg = re.match(\\\"^(--stats=(([A-Z]|[a-z]|/|_|[0-9]|.)+))$\\\", argument)\\n help_arg = re.match(\\\"^--help$\\\", argument)\\n vars_arg = re.match(\\\"^--vars$\\\", argument)\\n insts_arg = re.match(\\\"^--insts$\\\", argument)\\n if source_arg:\\n self.sourceFile = source_arg.group(2)\\n self.passedArgs.append(\\\"source\\\")\\n elif input_arg:\\n self.inputFile = input_arg.group(2)\\n self.passedArgs.append(\\\"input\\\")\\n elif help_arg:\\n print(\\\"napoveda\\\")\\n sys.exit(0)\\n elif stats_arg:\\n self.statsFile = stats_arg.group(2)\\n self.passedArgs.append(\\\"stats\\\")\\n elif vars_arg:\\n self.passedArgs.append(\\\"vars\\\")\\n if self.first_stat_arg is None:\\n self.first_stat_arg = \\\"vars\\\"\\n elif insts_arg:\\n self.passedArgs.append(\\\"insts\\\")\\n if self.first_stat_arg is None:\\n self.first_stat_arg = \\\"insts\\\"\\n else:\\n raise ArgError(\\\"Unknown argument or format of the argument! (\\\" + argument + \\\")\\\")\",\n \"def make_parser():\\n p = argparse.ArgumentParser(\\n description=\\\"Visualize and analyze error from oblique/straight tag observations\\\"\\n )\\n\\n p.add_argument(\\\"-n\\\", help=\\\"name of the test in the config file\\\")\\n\\n p.add_argument(\\\"-t\\\", help=\\\"throw out bad tags\\\", action=\\\"store_true\\\")\\n\\n p.add_argument(\\\"-v\\\", help=\\\"visualize data\\\", action=\\\"store_true\\\")\\n\\n p.add_argument(\\\"-i\\\", help=\\\"print result data\\\", action=\\\"store_true\\\")\\n\\n return p\",\n \"def parse_arguments():\\n\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument(\\\"--accessions\\\", help=\\\"A json file with old/new family mapppings\\\")\\n parser.add_argument(\\\"--add-header\\\", help=\\\"Print descriptive header\\\",\\n action=\\\"store_true\\\", default=False)\\n parser.add_argument(\\\"--add-links\\\", help=\\\"Creates hyperlinks to available Rfam html content\\\",\\n action=\\\"store_true\\\", default=False)\\n return parser\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(parents=[kcs_parser],\\n conflict_handler='resolve')\\n parser.add_argument('percentiles', help=\\\"Input CSV file with CMIP distribution percentiles\\\")\\n parser.add_argument('steering_table', help=\\\"Input steering table CSV file\\\")\\n parser.add_argument('--outfile', required=True,\\n help=\\\"Output figure filename. The extension determines the file type.\\\")\\n parser.add_argument('--extra-data', nargs='+', help=\\\"Model of interest data files. Using this \\\"\\n \\\"option will overplot the average of the input data.\\\")\\n parser.add_argument('--relative', action='store_true', help=\\\"Indicate the model data \\\"\\n \\\"should be calculated as relative change, as opposed to absolute change.\\\")\\n parser.add_argument('--reference-period', type=int, nargs=2,\\n help=\\\"Reference period to normalize the extra data to (if input). \\\"\\n \\\"Note that this can be different than the reference epoch, that is, \\\"\\n \\\"the middle of the reference-period does *not* have to correspond \\\"\\n \\\"to the reference epoch.\\\")\\n parser.add_argument('--reference-epoch', type=int, help=\\\"Mid-reference period year to \\\"\\n \\\"which all CMIP data were normalized. If this option is not used, no \\\"\\n \\\"indicator of the reference point is plotted.\\\")\\n parser.add_argument('--xlabel', default='Year')\\n parser.add_argument('--ylabel')\\n parser.add_argument('--xrange', type=float, nargs=2)\\n parser.add_argument('--yrange', type=float, nargs=2)\\n parser.add_argument('--title')\\n parser.add_argument('--legend', action='store_true')\\n parser.add_argument('--grid', action='store_true')\\n parser.add_argument('--extra-label', help=\\\"Label to indicate the extra model data.\\\")\\n parser.add_argument('--smooth', type=int, nargs='?', const=10)\\n\\n args = parser.parse_args()\\n read_config(args.config)\\n setup_logging(args.verbosity)\\n\\n if args.extra_data:\\n args.extra_data = map(pathlib.Path, args.extra_data)\\n if not args.reference_period:\\n args.reference_period = default_config['data']['extra']['control_period']\\n return args\",\n \"def make_cli_parser(self):\\n super(ExpressionBasedArgParser, self).make_cli_parser()\\n usage = \\\"\\\"\\\"\\\\\\npython %prog [OPTIONS] INTERACTIONS_FILE ANNOTATIONS_FILE EXPRESSION_FILE\\n\\nARGUMENTS:\\n INTERACTIONS_FILE: a CSV file containing interactions. The file\\n should have two columns with headings \\\"interactor1\\\" and\\n \\\"interactor2\\\". It may have an optional column with the heading\\n \\\"weight\\\", whose values will be used as the weight or confidence\\n of the interaction. The file may have additional columns, which\\n will be ignored.\\n ANNOTATIONS_FILE: a file containing annotations. The annotations\\n file may be in one of two formats:\\n - GMT format: if the file ends with the extension \\\".gmt\\\", it is\\n automatically parsed as a GMT-format file. The file is a\\n tab-separated (TSV) format with no headers. The first column\\n contains the annotation term. The second column contains a\\n description. All following columns contain gene IDs for genes\\n annotated by that term. Full GMT format specification is\\n available from the MSigDB and GSEA website.\\n - Two-column format: The file should have a column titled\\n \\\"gene_id\\\" which has the gene/gene product ID, and a column\\n titled \\\"term\\\" which contains the term with which the\\n gene/product is annotated. The file may have additional\\n columns, which will be ignored.\\n EXPRESSION_FILE: a CSV file of gene (or gene product) expression\\n values. The file should have a column titled \\\"id\\\" which has the\\n gene (or gene product) ID, and a column titled \\\"expression\\\"\\n which gives a value for the expression level, or difference in\\n expression levels.\\\\\\n\\\"\\\"\\\"\\n self.cli_parser.set_usage(usage)\",\n \"def processArgs(printHelp=False):\\n parser = OptionParser()\\n\\n parser.add_option('-i', '--input',\\n dest='input',\\n help='Name of the latex file, for example, document.tex',\\n metavar='string')\\n parser.add_option('-o', '--output',\\n dest='output',\\n help='Name of the output folder. Default is \\\"submit\\\"',\\n metavar='string')\\n parser.add_option('-x', '--xiv',\\n dest='xiv',\\n default=False,\\n action='store_true',\\n help='Converts the figures to PDFs for arXiv.org submission',\\n metavar='boolean')\\n parser.add_option('-m', '--margin',\\n dest='margin',\\n help='Size of the bounding box margin in case of arXiv.org submission. Default is 2.',\\n metavar='integer')\\n\\n if printHelp:\\n parser.print_help()\\n else:\\n return parser.parse_args()\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-i\\\", \\\"--input\\\", dest=\\\"input_file\\\", help=\\\"input file or pattern\\\", default=\\\"\\\")\\n parser.add_argument(\\\"-o\\\", \\\"--output\\\", dest=\\\"output_file\\\", help=\\\"output file or pattern\\\", default=\\\"\\\")\\n parser.add_argument(\\\"-d\\\", \\\"--debug\\\", dest=\\\"debug\\\", action='store_true')\\n parser.add_argument(\\\"-v\\\", \\\"--verbose\\\", dest=\\\"verbose\\\", action='store_true')\\n parser.set_defaults(verbose=False)\\n parser.set_defaults(debug=False)\\n return parser.parse_args()\",\n \"def common_parser() -> argparse.ArgumentParser:\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"-p\\\", \\\"--prefix\\\", type=str, default=\\\"scatter-\\\",\\n help=\\\"The prefix of the ouput files. Output will be \\\"\\n \\\"named like: <PREFIX><N>.bed, in which N is an \\\"\\n \\\"incrementing number. Default 'scatter-'.\\\")\\n parser.add_argument(\\\"input\\\", metavar=\\\"INPUT\\\", type=str,\\n help=f\\\"The input file. The format is detected by the \\\"\\n f\\\"extension. Supported extensions are: \\\"\\n f\\\"{SUPPORTED_EXTENSIONS_STRING}.\\\")\\n parser.add_argument(\\\"-P\\\", \\\"--print-paths\\\", action=\\\"store_true\\\",\\n help=\\\"If set prints paths of the output files to \\\"\\n \\\"STDOUT. This makes the program usable in \\\"\\n \\\"scripts and worfklows.\\\")\\n return parser\",\n \"def parse_inputs():\\n\\n parser = argparse.ArgumentParser(description=\\\"Command line argument handler for ugaudio spectral_average program.\\\",\\n formatter_class=argparse.ArgumentDefaultsHelpFormatter)\\n\\n # a group of args for verbosity\\n group = parser.add_mutually_exclusive_group()\\n group.add_argument('-v', '--verbose', action='store_true')\\n group.add_argument('-q', '--quiet', action='store_true')\\n\\n # nfiles\\n help_nfiles = 'nfiles to preview (ONLY for testing)'\\n parser.add_argument('-g', '--nfiles', default=DEFAULT_NFILES, type=nfiles_int, help=help_nfiles)\\n\\n # nfft\\n help_nfft = 'Nfft'\\n parser.add_argument('-n', '--nfft', default=DEFAULT_NFFT, type=nfft_int, help=help_nfft)\\n\\n # sample rate\\n help_rate = 'sample rate (sa/sec)'\\n parser.add_argument('-r', '--rate', default=DEFAULT_RATE, type=rate_str, help=help_rate)\\n\\n # cutoff\\n help_cutoff = 'cutoff'\\n parser.add_argument('-c', '--cutoff', default=DEFAULT_CUTOFF, type=cutoff_str, help=help_cutoff)\\n\\n # sensors\\n help_sensors = 'sensors'\\n parser.add_argument('-s', '--sensors', default=DEFAULT_SENSORS, type=sensors_list, help=help_sensors)\\n\\n # PAD directory\\n help_paddir = 'PAD dir'\\n parser.add_argument('-p', '--paddir', default=DEFAULT_PADDIR, type=folder_str, help=help_paddir)\\n\\n # output directory\\n help_outdir = 'output dir'\\n parser.add_argument('-o', '--outdir', default=DEFAULT_OUTDIR, type=outdir_str, help=help_outdir)\\n\\n # start date\\n help_start = 'start date'\\n parser.add_argument('-d', '--start', default=DEFAULT_START, type=dtm_date, help=help_start)\\n\\n # end date\\n help_end = 'end date'\\n parser.add_argument('-e', '--end', default=DEFAULT_END, type=dtm_date, help=help_end)\\n\\n # parse arguments\\n module_logger.debug('calling parse_args')\\n args = parser.parse_args()\\n\\n return args\",\n \"def parseOptions():\\n desc = \\\"Compute the likelihood of sequences coming from a list of barcodes.\\\"\\n parser = argparse.ArgumentParser(description=desc, add_help=False)\\n\\n def canonicalizedFilePath(path):\\n return os.path.abspath(os.path.expanduser(path))\\n\\n def checkInputFile(path):\\n if not os.path.isfile(path):\\n parser.error(\\\"Input file %s not found.\\\" % (path,))\\n\\n def checkOutputFile(path):\\n try:\\n f = open(path, \\\"a\\\")\\n f.close()\\n except:\\n parser.error(\\\"Output file %s cannot be written.\\\" % (path,))\\n\\n basics = parser.add_argument_group(\\\"Basic required options\\\")\\n basics.add_argument(\\n \\\"cmpH5Filename\\\",\\n type=canonicalizedFilePath,\\n metavar=\\\"CMP.H5\\\",\\n help=\\\"The filename of the input Bas.H5 file\\\")\\n basics.add_argument(\\n \\\"referenceFasta\\\",\\n type=canonicalizedFilePath,\\n metavar=\\\"REFERENCE_FASTA\\\",\\n help=\\\"The reference sequences of interest in FASTA format\\\")\\n basics.add_argument(\\n \\\"basH5Fofn\\\",\\n type=canonicalizedFilePath,\\n metavar=\\\"BARCODE_FASTA\\\",\\n help=\\\"The filename of the barcode FASTA\\\")\\n basics.add_argument(\\n \\\"-o\\\", \\\"--outputFilename\\\",\\n type=str,\\n default=os.path.join(os.getcwd(), \\\"output.csv\\\"),\\n metavar=\\\"CSV\\\",\\n help=\\\"The filename of the CSV to output barcode scoring data to.\\\")\\n basics.add_argument(\\n \\\"-m\\\", \\\"--minSize\\\",\\n type=int,\\n default=3,\\n metavar=\\\"INT\\\",\\n help=\\\"The minimum size of a homopolymer context to record\\\")\\n\\n debugging = parser.add_argument_group(\\\"Verbosity and debugging/profiling\\\")\\n debugging.add_argument(\\\"--help\\\", \\\"-h\\\",\\n action=\\\"help\\\")\\n debugging.add_argument(\\n \\\"--nZmws\\\",\\n default=-1,\\n type=int,\\n help=\\\"Label only the first N ZMWs for testing purposes.\\\")\\n debugging.add_argument(\\n \\\"--verbose\\\", \\\"-v\\\",\\n dest=\\\"verbosity\\\",\\n action=\\\"count\\\",\\n help=\\\"Set the verbosity level.\\\")\\n debugging.add_argument(\\n \\\"--quiet\\\",\\n dest=\\\"quiet\\\",\\n action=\\\"store_true\\\",\\n help=\\\"Turn off all logging, including warnings\\\")\\n class PrintVersionAction(argparse.Action):\\n def __call__(self, parser, namespace, values, option_string=None):\\n print \\\" RegionTools version: %s\\\" % __version__\\n print \\\" h5py version: %s\\\" % h5py.version.version\\n print \\\" hdf5 version: %s\\\" % h5py.version.hdf5_version\\n sys.exit(0)\\n debugging.add_argument(\\\"--version\\\",\\n nargs=0,\\n action=PrintVersionAction)\\n\\n parser.parse_args(namespace=options)\\n\\n for path in (options.cmpH5Filename, options.referenceFasta, options.basH5Fofn):\\n if path is not None:\\n checkInputFile(path)\\n\\n for path in (options.outputFilename,):\\n if path is not None:\\n checkOutputFile(path)\\n\\n options.shellCommand = \\\" \\\".join(sys.argv)\",\n \"def prepare_optparser ():\\n usage = \\\"\\\"\\\"usage: %prog <-t tfile> [-n name] [-g genomesize] [options]\\n\\nExample: %prog -t ChIP.bam -c Control.bam -f BAM -g hs -n test -B -q 0.01\\n\\nor example for broad peak calling: %prog -t ChIP.bam -c Control.bam --broad -g hs\\n\\n\\\"\\\"\\\"\\n description = \\\"%prog -- Model-based Analysis for ChIP-Sequencing\\\"\\n\\n optparser = OptionParser(version=\\\"%prog \\\"+MACS_VERSION,description=description,usage=usage,add_help_option=False)\\n optparser.add_option(\\\"-h\\\",\\\"--help\\\",action=\\\"help\\\",help=\\\"show this help message and exit.\\\")\\n optparser.add_option(\\\"-t\\\",\\\"--treatment\\\",dest=\\\"tfile\\\",type=\\\"string\\\",\\n help=\\\"ChIP-seq treatment file. REQUIRED.\\\")\\n optparser.add_option(\\\"-c\\\",\\\"--control\\\",dest=\\\"cfile\\\",type=\\\"string\\\",\\n help=\\\"Control file.\\\")\\n optparser.add_option(\\\"-n\\\",\\\"--name\\\",dest=\\\"name\\\",type=\\\"string\\\",\\n help=\\\"Experiment name, which will be used to generate output file names. DEFAULT: \\\\\\\"NA\\\\\\\"\\\",\\n default=\\\"NA\\\")\\n optparser.add_option(\\\"-f\\\",\\\"--format\\\",dest=\\\"format\\\",type=\\\"string\\\",\\n help=\\\"Format of tag file, \\\\\\\"AUTO\\\\\\\", \\\\\\\"BED\\\\\\\" or \\\\\\\"ELAND\\\\\\\" or \\\\\\\"ELANDMULTI\\\\\\\" or \\\\\\\"ELANDEXPORT\\\\\\\" or \\\\\\\"SAM\\\\\\\" or \\\\\\\"BAM\\\\\\\" or \\\\\\\"BOWTIE\\\\\\\". The default AUTO option will let MACS decide which format the file is. Please check the definition in 00README file if you choose ELAND/ELANDMULTI/ELANDEXPORT/SAM/BAM/BOWTIE. DEFAULT: \\\\\\\"AUTO\\\\\\\"\\\",\\n default=\\\"AUTO\\\")\\n optparser.add_option(\\\"-g\\\",\\\"--gsize\\\",dest=\\\"gsize\\\",type=\\\"string\\\",default=\\\"hs\\\",\\n help=\\\"Effective genome size. It can be 1.0e+9 or 1000000000, or shortcuts:'hs' for human (2.7e9), 'mm' for mouse (1.87e9), 'ce' for C. elegans (9e7) and 'dm' for fruitfly (1.2e8), Default:hs\\\")\\n optparser.add_option(\\\"-s\\\",\\\"--tsize\\\",dest=\\\"tsize\\\",type=\\\"int\\\",default=None,\\n help=\\\"Tag size. This will overide the auto detected tag size. DEFAULT: Not set\\\")\\n optparser.add_option(\\\"--bw\\\",dest=\\\"bw\\\",type=\\\"int\\\",default=300,\\n help=\\\"Band width. This value is only used while building the shifting model. DEFAULT: 300\\\")\\n optparser.add_option(\\\"-q\\\",\\\"--qvalue\\\",dest=\\\"qvalue\\\",type=\\\"float\\\",default=0.05,\\n help=\\\"Minimum FDR (q-value) cutoff for peak detection. DEFAULT: 0.05 \\\")\\n optparser.add_option(\\\"-p\\\",\\\"--pvalue\\\",dest=\\\"pvalue\\\",type=\\\"float\\\",\\n help=\\\"Pvalue cutoff for peak detection. When set (e.g. -p 0.05 or -p 1e-5), qvalue cutoff will be ignored. By default it's not set.\\\")\\n optparser.add_option(\\\"-m\\\",\\\"--mfold\\\",dest=\\\"mfold\\\",type=\\\"string\\\",default=\\\"5,50\\\",\\n help=\\\"Select the regions within MFOLD range of high-confidence enrichment ratio against background to build model. The regions must be lower than upper limit, and higher than the lower limit. DEFAULT:5,50\\\")\\n optparser.add_option(\\\"--nolambda\\\",dest=\\\"nolambda\\\",action=\\\"store_true\\\",\\n help=\\\"If True, MACS will use fixed background lambda as local lambda for every peak region. Normally, MACS calculates a dynamic local lambda to reflect the local bias due to potential chromatin structure. \\\",\\n default=False)\\n optparser.add_option(\\\"--slocal\\\",dest=\\\"smalllocal\\\",type=\\\"int\\\",default=1000,\\n help=\\\"The small nearby region in basepairs to calculate dynamic lambda. This is used to capture the bias near the peak summit region. Invalid if there is no control data. If you set this to 0, MACS will skip slocal lambda calculation. *Note* that MACS will always perform a d-size local lambda calculation. The final local bias should be the maximum of the lambda value from d, slocal, and llocal size windows. DEFAULT: 1000 \\\")\\n optparser.add_option(\\\"--llocal\\\",dest=\\\"largelocal\\\",type=\\\"int\\\",default=10000,\\n help=\\\"The large nearby region in basepairs to calculate dynamic lambda. This is used to capture the surround bias. If you set this to 0, MACS will skip llocal lambda calculation. *Note* that MACS will always perform a d-size local lambda calculation. The final local bias should be the maximum of the lambda value from d, slocal, and llocal size windows. DEFAULT: 10000.\\\")\\n optparser.add_option(\\\"--fix-bimodal\\\",dest=\\\"onauto\\\",action=\\\"store_true\\\",\\n help=\\\"Whether turn on the auto pair model process. If set, when MACS failed to build paired model, it will use the nomodel settings, the '--shiftsize' parameter to shift and extend each tags. Not to use this automate fixation is a default behavior now. DEFAULT: False\\\",\\n default=False)\\n optparser.add_option(\\\"--nomodel\\\",dest=\\\"nomodel\\\",action=\\\"store_true\\\",\\n help=\\\"Whether or not to build the shifting model. If True, MACS will not build model. by default it means shifting size = 100, try to set shiftsize to change it. DEFAULT: False\\\",\\n default=False)\\n optparser.add_option(\\\"--shiftsize\\\",dest=\\\"shiftsize\\\",type=\\\"int\\\",default=100,\\n help=\\\"The arbitrary shift size in bp. When nomodel is true, MACS will use this value as 1/2 of fragment size. DEFAULT: 100 \\\")\\n optparser.add_option(\\\"--keep-dup\\\",dest=\\\"keepduplicates\\\",type=\\\"string\\\",default=\\\"auto\\\",\\n help=\\\"It controls the MACS behavior towards duplicate tags at the exact same location -- the same coordination and the same strand. The default 'auto' option makes MACS calculate the maximum tags at the exact same location based on binomal distribution using 1e-5 as pvalue cutoff; and the 'all' option keeps every tags. If an integer is given, at most this number of tags will be kept at the same location. Default: auto\\\")\\n optparser.add_option(\\\"--to-large\\\",dest=\\\"tolarge\\\",action=\\\"store_true\\\",default=False,\\n help=\\\"When set, scale the small sample up to the bigger sample. By default, the bigger dataset will be scaled down towards the smaller dataset, which will lead to smaller p/qvalues and more specific results. Keep in mind that scaling down will bring down background noise more. DEFAULT: False\\\")\\n optparser.add_option(\\\"--down-sample\\\",dest=\\\"downsample\\\",action=\\\"store_true\\\",default=False,\\n help=\\\"When set, random sampling method will scale down the bigger sample. By default, MACS uses linear scaling. Warning: This option will make your result unstable and irreproducible since each time, random reads would be selected. Consider to use 'randsample' script instead. DEFAULT: False\\\")\\n optparser.add_option(\\\"--shift-control\\\",dest=\\\"shiftcontrol\\\",action=\\\"store_true\\\",default=False,\\n help=\\\"When set, control tags will be shifted just as ChIP tags according to their strand before the extension of d, slocal and llocal. By default, control tags are extended centered at their current positions regardless of strand. You may consider to turn this option on while comparing two ChIP datasets of different condition but the same factor. DEFAULT: False\\\")\\n optparser.add_option(\\\"--half-ext\\\",dest=\\\"halfext\\\",action=\\\"store_true\\\",default=False,\\n help=\\\"When set, MACS extends 1/2 d size for each fragment centered at its middle point. DEFAULT: False\\\")\\n optparser.add_option(\\\"-B\\\",\\\"--bdg\\\",dest=\\\"store_bdg\\\",action=\\\"store_true\\\",\\n help=\\\"Whether or not to save extended fragment pileup, local lambda and score tracks at every bp into a bedGraph file. DEFAULT: False\\\",\\n default=False)\\n optparser.add_option(\\\"--broad\\\",dest=\\\"broad\\\",action=\\\"store_true\\\",\\n help=\\\"If set, MACS will try to call broad peaks by linking nearby highly enriched regions. The linking region is controlled by another cutoff through --linking-cutoff. The maximum linking region length is 4 times of d from MACS. DEFAULT: False\\\",default=False)\\n optparser.add_option(\\\"--broad-cutoff\\\",dest=\\\"broadcutoff\\\",type=\\\"float\\\",default=0.1,\\n help=\\\"Cutoff for broad region. This option is not available unless --broad is set. If -p is set, this is a pvalue cutoff, otherwise, it's a qvalue cutoff. DEFAULT: 0.1 \\\")\\n optparser.add_option(\\\"--verbose\\\",dest=\\\"verbose\\\",type=\\\"int\\\",default=2,\\n help=\\\"Set verbose level. 0: only show critical message, 1: show additional warning message, 2: show process information, 3: show debug messages. DEFAULT:2\\\")\\n return optparser\",\n \"def parseInputArgs():\\n parser = argparse.ArgumentParser(description=\\\"Unix cut analog\\\", usage='%(prog)s [arguments]')\\n\\n # pos arg\\n parser.add_argument('filename', type=str, help='input file name')\\n\\n # req arg\\n requiredNamed = parser.add_argument_group('required arguments')\\n requiredNamed.add_argument('-f', '--fields', type=str, help='list of fields, separated by comma', required=True)\\n # optional args\\n parser.add_argument('-s', '--separator', type=str, default='\\\\t', help='column separator, default tab')\\n\\n args = parser.parse_args()\\n return args\",\n \"def setup_args():\\n parser = ParlaiParser(add_parlai_args=True, description=\\\"Render data as HTML\\\")\\n conv_render = parser.add_argument_group('Conversation Rendering Arguments')\\n conv_render.add_argument(\\n \\\"--input\\\", \\\"-i\\\", help=\\\"Input file to read conversations from\\\"\\n )\\n conv_render.add_argument(\\n \\\"--output\\\",\\n \\\"-o\\\",\\n help=\\\"Output file to write conversations to. One of [.pdf, .png, .html] only\\\",\\n )\\n conv_render.add_argument(\\n \\\"--width\\\", \\\"-wd\\\", help=\\\"Width of output file\\\", type=int, default=8\\n )\\n conv_render.add_argument(\\n \\\"--height\\\", \\\"-ht\\\", help=\\\"Height of output file\\\", type=int, default=10\\n )\\n conv_render.add_argument(\\n \\\"--user-icon\\\",\\n \\\"-uic\\\",\\n help=\\\"Absolute Path/URL to user image icon\\\",\\n default=HUMAN_EMOJI_IMG,\\n )\\n conv_render.add_argument(\\n \\\"--alt-icon\\\",\\n \\\"-aic\\\",\\n help=\\\"Absolute Path/URL to alternate image icon\\\",\\n default=ALT_EMOJI_IMG,\\n )\\n conv_render.add_argument(\\n \\\"--num-examples\\\",\\n \\\"-ne\\\",\\n help=\\\"Number of conversations to render\\\",\\n type=int,\\n default=10,\\n )\\n\\n return parser\",\n \"def ParseArgs() -> argparse.Namespace:\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument(\\n '--input', dest='input', help='Japanese phonetic reading file')\\n parser.add_argument(\\n '--output_token_array',\\n dest='output_token_array',\\n help='Output token array file.')\\n parser.add_argument(\\n '--output_string_array',\\n dest='output_string_array',\\n help='Output string array file.')\\n return parser.parse_args()\",\n \"def parse_args(args):\\n \\n # Construct the parser (which is stored in parser)\\n # Module docstring lives in __doc__\\n # See http://python-forum.com/pythonforum/viewtopic.php?f=3&t=36847\\n # And a formatter class so our examples in the docstring look good. Isn't it\\n # convenient how we already wrapped it to 80 characters?\\n # See http://docs.python.org/library/argparse.html#formatter-class\\n parser = argparse.ArgumentParser(description=__doc__, \\n formatter_class=argparse.RawDescriptionHelpFormatter)\\n \\n # General options\\n parser.add_argument(\\\"hal\\\",\\n help=\\\"HAL file to evaluate\\\")\\n parser.add_argument(\\\"--truth\\\",\\n help=\\\"MAF file of a true alignment for precision and recall\\\")\\n parser.add_argument(\\\"--beds\\\", nargs=\\\"*\\\",\\n help=\\\"BED file(s) of genes on the genomes in the HAL\\\")\\n parser.add_argument(\\\"--coverage_file\\\", type=argparse.FileType(\\\"w\\\"),\\n default = sys.stdout,\\n help=\\\"file to save average coverage vs. the reference in (one number)\\\")\\n parser.add_argument(\\\"--precision_recall_file\\\", type=argparse.FileType(\\\"w\\\"),\\n default = sys.stdout,\\n help=\\\"TSV file to save precision and recall in (two numbers)\\\")\\n parser.add_argument(\\\"--gene_category_file\\\", type=argparse.FileType(\\\"w\\\"),\\n default = sys.stdout,\\n help=\\\"file to save categories and counts for genes in\\\")\\n parser.add_argument(\\\"--tag\\\", nargs=\\\"*\\\", default=[],\\n help=\\\"extra columns to tag all result TSV lines with at the front\\\")\\n \\n # The command line arguments start with the program name, which we don't\\n # want to treat as an argument for argparse. So we remove it.\\n args = args[1:]\\n \\n return parser.parse_args(args)\",\n \"def parse_cli_args():\\n\\n parser = argparse.ArgumentParser(\\n description='Create AMICI model and data for steadystate example.')\\n\\n parser.add_argument('-s', '--sbml', dest='sbml_file_name',\\n required=True,\\n help='SBML model filename (PEtab format)')\\n\\n parser.add_argument('-d', '--model-dir', dest='model_dir',\\n help='Model directory containing the python module')\\n\\n parser.add_argument('-n', '--model-name', dest='model_name',\\n required=True,\\n help='Name of the AMICI model module')\\n\\n parser.add_argument('-m', '--measurements', dest='measurement_file_name',\\n required=True,\\n help='Name of measurement table (PEtab format)')\\n\\n parser.add_argument('-c', '--conditions', dest='condition_file_name',\\n required=True,\\n help='Condition table (PEtab format)')\\n\\n parser.add_argument('-p', '--parameters', dest='parameter_file_name',\\n required=True,\\n help='Condition table (PEtab format)')\\n\\n parser.add_argument('-o', dest='hdf5_file_name', default='data.h5',\\n help='Name of HDF5 file to generate')\\n\\n args = parser.parse_args()\\n\\n return args\",\n \"def parse_args():\\n\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument(\\\"-f\\\", \\\"--folder\\\", required=True, action=\\\"store\\\", dest=\\\"folder\\\", help=\\\"input folder\\\")\\n parser.add_argument(\\\"-t\\\", \\\"--tool\\\", required=True, action=\\\"store\\\", dest=\\\"tool\\\", choices=[\\\"spacy\\\",\\\"stanford\\\"], help=\\\"NER tool\\\")\\n parser.add_argument(\\\"-l\\\", \\\"--lang\\\", required=True, action=\\\"store\\\", dest=\\\"lang\\\", help=\\\"language\\\")\\n\\n return parser.parse_args()\",\n \"def get_parser():\\n\\n parser = ArgumentParser()\\n\\n req_argument = parser.add_argument_group('required arguments')\\n\\n parser.add_argument(\\\"-o\\\", \\\"--outdir\\\", type=str, default='result',\\n help=\\\"Path for results\\\")\\n parser.add_argument(\\\"-fname\\\", \\\"--file_name\\\", type=str, default=\\\"try1\\\",\\n help=\\\"The name the output file should have within the output directory\\\")\\n parser.add_argument(\\\"-freq\\\", \\\"--frequency\\\", type=str,\\n help=\\\"File to read the haplotype frequencies from\\\")\\n parser.add_argument(\\\"-over\\\", \\\"--overlap\\\", type=str,\\n help=\\\"File to read the peptide vs alleles or peptide vs haplotype data\\\")\\n parser.add_argument(\\\"-o_a\\\", \\\"--overlap_allele\\\", type=int, default=0,\\n help=\\\"1 if the --overlap file passed in is peptide vs alleles and 0 if it is peptide vs haplotypes and has already been binarized\\\")\\n # parser.add_argument(\\\"-n\\\", \\\"--ntarget\\\", type=int, default=5,\\n # help=\\\"The ntarget for max n-times coverage\\\")\\n parser.add_argument(\\\"-maxpep\\\", \\\"--max_number_of_pepts\\\", type=int, default=30,\\n help=\\\"The maximum number of peptides allowed in a vaccine\\\")\\n parser.add_argument(\\\"-c\\\", \\\"--cut\\\", type=int, default=3,\\n help=\\\"The cut value for ommitting peptides that are too similar; a value of 0 should be provided if similar peptides are not to be excluded from a vaccine design.\\\")\\n\\n\\n \\n return parser\",\n \"def parse_command_line():\\n parser = argparse.ArgumentParser()\\n\\n help_str = \\\\\\n 'The collection folder to sort files into. ' \\\\\\n 'If the folder does not exist, it will be created along with the ' \\\\\\n 'necessary contents.'\\n parser.add_argument('-c', '--collection', help=help_str)\\n\\n help_str = \\\\\\n 'The source folder to import files from. Has to exist and ' \\\\\\n 'has to be a folder.'\\n parser.add_argument('-s', '--source', help=help_str, required=False)\\n\\n help_str = \\\\\\n 'View the gallery in random order auto skpping after the' \\\\\\n 'given amount of seconds'\\n parser.add_argument('-v', '--view', help=help_str, required=False)\\n\\n return parser.parse_args()\",\n \"def help():\\n description = \\\"\\\"\\\"\\n Pair-wise quantification and comparsion of domains based on two-passes Mahalanobis distance. \\n\\n Example:\\n compareDom.py -f dom.bed -a young -b old -o youngVsOld -na Young -b Old -pcut 0.01 -gtf mm10.gtf\\n \\\"\\\"\\\"\\n parser = argparse.ArgumentParser(description=description,\\n formatter_class=RawTextHelpFormatter)\\n parser.add_argument(\\\"-f\\\",\\n dest=\\\"domf\\\",\\n required=True,\\n type=str,\\n help=\\\"Domain file in .bed format.\\\")\\n parser.add_argument(\\n \\\"-a\\\",\\n dest=\\\"da\\\",\\n required=True,\\n type=str,\\n help=\\\"The data directory generated by cLoops2 pre for the first sample.\\\"\\n )\\n parser.add_argument(\\n \\\"-b\\\",\\n dest=\\\"db\\\",\\n required=True,\\n type=str,\\n help=\\n \\\"The data directory generated by cLoops2 pre for the second sample.\\\")\\n parser.add_argument(\\n \\\"-na\\\",\\n dest=\\\"na\\\",\\n type=str,\\n required=True,\\n help=\\n \\\"Name of first sample, will be shown in the output figure. Only use alphabet and numbers.\\\"\\n )\\n parser.add_argument(\\n \\\"-nb\\\",\\n dest=\\\"nb\\\",\\n type=str,\\n required=True,\\n help=\\\"Name of second sample, will be shown in the output figure.\\\")\\n parser.add_argument(\\n \\\"-gtf\\\",\\n dest=\\\"gtf\\\",\\n default=\\\"\\\",\\n required=True,\\n type=str,\\n help=\\n \\\"GTF file annotation for genes. Significant flip/switch overlapped genes will be reported based on the gene annotation file.\\\"\\n )\\n parser.add_argument(\\n \\\"-pcut\\\",\\n dest=\\\"pcut\\\",\\n type=float,\\n default=0.01,\\n help=\\n \\\"Chi-Square p-value cutoff for detecting siginficant different compartment, default is 0.01.\\\"\\n )\\n\\n parser.add_argument(\\\"-o\\\",\\n dest=\\\"output\\\",\\n required=True,\\n type=str,\\n help=\\\"Output prefix.\\\")\\n parser.add_argument(\\n \\\"-p\\\",\\n dest=\\\"cpu\\\",\\n required=False,\\n type=int,\\n default=4,\\n help=\\\"How many cpus used for quantification, default is 4.\\\")\\n parser.add_argument(\\n \\\"-xlim\\\",\\n dest=\\\"xlim\\\",\\n required=False,\\n type=str,\\n default=None,\\n help=\\n \\\"X-axis limitations for the scatter plot, default is autodetermined, set as '1,-1'.\\\"\\n )\\n parser.add_argument(\\n \\\"-ylim\\\",\\n dest=\\\"ylim\\\",\\n required=False,\\n type=str,\\n default=None,\\n help=\\n \\\"Y-axis limitations for the scatter plot, default is autodetermined, set as '1,-1'.\\\"\\n )\\n parser.add_argument(\\\"-vmin\\\",\\n dest=\\\"vmin\\\",\\n required=False,\\n type=str,\\n default=None,\\n help=\\\"Minimal scale for the aggregation heatmap.\\\")\\n parser.add_argument(\\\"-vmax\\\",\\n dest=\\\"vmax\\\",\\n required=False,\\n type=str,\\n default=None,\\n help=\\\"Maxmal scale for the aggregation heatmap.\\\")\\n\\n op = parser.parse_args()\\n return op\",\n \"def parse_cmdline(cmdline_args):\\n option_parser = optparse.OptionParser(usage='usage: %prog [options] <pattern>',\\n description='ts short for TextSearch, Grep like tool', prog='ts', add_help_option=False) # -h is a real option\\n\\n option_parser.add_option('-h', '--help', action='store_true', dest='help', help='Display this information')\\n option_parser.add_option('-e', '--extension', action='store', dest='extension', type='string', default=None,\\n help='file extension')\\n\\n group_searching = optparse.OptionGroup(option_parser, 'Regexp selection and interpretation')\\n group_searching.add_option('-i', '--ignore-case', action='store_true', dest='ignore_case', default=False,\\n help='Ignore case distinctions in the pattern')\\n group_searching.add_option('-w', '--word-regexp', action='store_true', dest='word_regexp', default=False,\\n help='Force the pattern to match only whole words')\\n group_searching.add_option('-l', '--literal', action='store_true', dest='literal', default=False,\\n help='Quote all metacharacters; the pattern is literal')\\n option_parser.add_option_group(group_searching)\\n\\n group_miscellaneous = optparse.OptionGroup(option_parser, 'Miscellaneous')\\n group_miscellaneous.add_option('--path-only', action='store_true', dest='path_only', default=False,\\n help='only print out the matching file')\\n group_miscellaneous.add_option('-v', '--invert-match', action='store_true', dest='invert_match', default=False,\\n help='Invert the sense of matching, to select non-matching lines.')\\n option_parser.add_option_group(group_miscellaneous)\\n\\n group_output = optparse.OptionGroup(option_parser, 'Output control')\\n group_output.add_option('-c', '--count', action='store_true', dest='count', default=False,\\n help='Suppress normal output; instead print a count of matching lines for each input file.')\\n group_output.add_option('-o', '--only-matching', action='store_true', dest='only_matching', default=False,\\n help='Print only the matched (non-empty) parts of a matching line, with each such part on '\\n 'a separate output line.')\\n option_parser.add_option_group(group_output)\\n\\n options, args = option_parser.parse_args(cmdline_args)\\n return options, args, option_parser\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description=__doc__)\\n # If user doesn't specify an input file, read from standard input. Since\\n # encodings are the worst thing, we're explicitly expecting std\\n parser.add_argument('-i', '--infile',\\n type=lambda x: open(x, encoding=ENCODE_IN),\\n default=io.TextIOWrapper(\\n sys.stdin.buffer, encoding=ENCODE_IN)\\n )\\n # Same thing goes with the output file.\\n parser.add_argument('-o', '--outfile',\\n type=lambda x: open(x, 'w', encoding=ENCODE_OUT),\\n default=io.TextIOWrapper(\\n sys.stdout.buffer, encoding=ENCODE_OUT)\\n )\\n # Set the verbosity level for the logger. The `-v` option will set it to\\n # the debug level, while the `-q` will set it to the warning level.\\n # Otherwise use the info level.\\n verbosity = parser.add_mutually_exclusive_group()\\n verbosity.add_argument('-v', '--verbose', action='store_const',\\n const=logging.DEBUG, default=logging.INFO)\\n verbosity.add_argument('-q', '--quiet', dest='verbose',\\n action='store_const', const=logging.WARNING)\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser()\\n \\n parser.add_argument('--p', dest='path_in',\\n action='store', type=str, required=True, default='',\\n help=\\\"Path relative to the data/ directory, to the input ATL01, ANC13, and ANC27 files.\\\")\\n parser.add_argument('--atl01', dest='atl01_file',\\n action='store', type=str, required=False, default=None,\\n help=\\\"Path + filename to directory of the ATL01.\\\")\\n parser.add_argument('--anc13', dest='anc13_path',\\n action='store', type=str, required=False, default=None,\\n help=\\\"Path to outputs directory of the ANC13.\\\") \\n parser.add_argument('--anc27', dest='anc27_path',\\n action='store', type=str, required=False, default=None,\\n help=\\\"Path to directory of the ANC27.\\\")\\n\\n args = parser.parse_args()\\n \\n return args\",\n \"def __parse_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('-f', '--force', action=\\\"store_true\\\", default=False,\\n help='overwrite existing database files during import')\\n parser.add_argument('-e', '--extension', action=\\\"store\\\", default='txt',\\n help='specify file extension. default is \\\"txt\\\"')\\n parser.add_argument('-d', '--delimiter', action=\\\"store\\\", default='\\\\t',\\n help='specify column delimiter. default is tab (\\\\\\\\t)')\\n parser.add_argument('-m', '--mark', action=\\\"store\\\", default='.',\\n help='specify decimal mark for numeric data. default is'\\n ' dot (.)')\\n parser.add_argument('-o', '--outformat', action=\\\"store\\\", default='npz',\\n help='specify output database format. default is \\\"npz\\\"'\\n ' for numpy database. use \\\"mat\\\" for matlab '\\n ' database format.')\\n parser.add_argument('-r', '--recursive', action=\\\"store_true\\\", default=False,\\n help='recursively walk through all sub-directories of'\\n ' current working directory')\\n parser.add_argument('-p', '--pcs', action=\\\"store_true\\\", default=True,\\n help='indicate if files are pcs files.')\\n parser.add_argument('-c', '--colheadlines', action=\\\"store\\\", default='1',\\n help='number of lines spanned by the column headers')\\n args = parser.parse_args()\\n return args\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(description=\\\"Parse Diff Exp output files\\\")\\n parser.add_argument(\\\"raw_file\\\", help=\\\"DE analysis output file (.tab).\\\")\\n parser.add_argument(\\\"output_json\\\", help=\\\"Output JSON\\\")\\n parser.add_argument(\\\"output_file\\\", help=\\\"Output file\\\")\\n parser.add_argument(\\\"--gene_id\\\", help=\\\"Gene_IDs column name\\\", type=str)\\n parser.add_argument(\\\"--fdr\\\", help=\\\"FDR column name\\\", type=str)\\n parser.add_argument(\\\"--pvalue\\\", help=\\\"Pvalue column name\\\", type=str)\\n parser.add_argument(\\\"--fwer\\\", help=\\\"FWER column name\\\", type=str)\\n parser.add_argument(\\\"--logodds\\\", help=\\\"Log Odds column name\\\", type=str)\\n parser.add_argument(\\\"--logfc\\\", help=\\\"logfc column name\\\", type=str)\\n parser.add_argument(\\\"--stat\\\", help=\\\"Statistics column name\\\", type=str)\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(\\n description='Convert CVAT XML annotations to YOLO format'\\n )\\n\\n parser.add_argument(\\n '--cvat-xml', metavar='FILE', required=True,\\n help='input file with CVAT annotation in xml format'\\n )\\n\\n parser.add_argument(\\n '--image-dir', metavar='DIRECTORY', required=False,\\n help='directory which contains original images'\\n )\\n\\n parser.add_argument(\\n '--output-dir', metavar='DIRECTORY', required=True,\\n help='directory for output annotations in YOLO format'\\n )\\n\\n parser.add_argument(\\n '--username', metavar='USERNAME', required=False,\\n help='Username from CVAT Login page, required to download images'\\n )\\n\\n parser.add_argument(\\n '--password', metavar='PASSWORD', required=False,\\n help='Password from CVAT Login page, required to download images'\\n )\\n\\n parser.add_argument(\\n '--labels', metavar='ILABELS', required=False,\\n help='Labels (separated by comma) to extract. Example: car,truck,motorcycle'\\n )\\n\\n return parser.parse_args()\",\n \"def make_parser():\\n parser_ = argparse.ArgumentParser(\\n description=\\\"\\\"\\\"\\n A tool to retrieve history from\\n (almost) any browser on (almost) any platform\\n\\n██████╗ ██████╗ ██████╗ ██╗ ██╗███████╗███████╗██████╗ ██╗ ██╗██╗███████╗████████╗ ██████╗ ██████╗ ██╗ ██╗\\n██╔══██╗██╔══██╗██╔═══██╗██║ ██║██╔════╝██╔════╝██╔══██╗ ██║ ██║██║██╔════╝╚══██╔══╝██╔═══██╗██╔══██╗╚██╗ ██╔╝\\n██████╔╝██████╔╝██║ ██║██║ █╗ ██║███████╗█████╗ ██████╔╝█████╗███████║██║███████╗ ██║ ██║ ██║██████╔╝ ╚████╔╝\\n██╔══██╗██╔══██╗██║ ██║██║███╗██║╚════██║██╔══╝ ██╔══██╗╚════╝██╔══██║██║╚════██║ ██║ ██║ ██║██╔══██╗ ╚██╔╝\\n██████╔╝██║ ██║╚██████╔╝╚███╔███╔╝███████║███████╗██║ ██║ ██║ ██║██║███████║ ██║ ╚██████╔╝██║ ██║ ██║\\n╚═════╝ ╚═╝ ╚═╝ ╚═════╝ ╚══╝╚══╝ ╚══════╝╚══════╝╚═╝ ╚═╝ ╚═╝ ╚═╝╚═╝╚══════╝ ╚═╝ ╚═════╝ ╚═╝ ╚═╝ ╚═╝\\n \\\"\\\"\\\", # noqa: E501\\n epilog=\\\"\\\"\\\"\\n Checkout the GitHub repo\\n https://github.com/pesos/browser-history\\n if you have any issues or want to help contribute\\\"\\\"\\\",\\n formatter_class=RawDescriptionHelpFormatter,\\n )\\n\\n parser_.add_argument(\\n \\\"-t\\\",\\n \\\"--type\\\",\\n default=\\\"history\\\",\\n help=f\\\"\\\"\\\"\\n argument to decide whether to retrieve history or bookmarks.\\n Should be one of {AVAILABLE_TYPES}.\\n Default is history.\\\"\\\"\\\",\\n )\\n parser_.add_argument(\\n \\\"-b\\\",\\n \\\"--browser\\\",\\n default=\\\"all\\\",\\n help=f\\\"\\\"\\\"\\n browser to retrieve history or bookmarks from. Should be one\\n of all, default, {AVAILABLE_BROWSERS}.\\n Default is all (gets history or bookmarks from all browsers).\\n \\\"\\\"\\\",\\n )\\n\\n parser_.add_argument(\\n \\\"-f\\\",\\n \\\"--format\\\",\\n default=\\\"infer\\\",\\n help=f\\\"\\\"\\\"\\n Format to be used in output. Should be one of {AVAILABLE_FORMATS}.\\n Default is infer (format is inferred from the output file's\\n extension. If no output file (-o) is specified, it defaults to csv)\\\"\\\"\\\",\\n )\\n\\n parser_.add_argument(\\n \\\"-o\\\",\\n \\\"--output\\\",\\n default=None,\\n help=\\\"\\\"\\\"\\n File where history output or bookmark output is to be written.\\n If not provided, standard output is used.\\\"\\\"\\\",\\n )\\n\\n parser_.add_argument(\\n \\\"-p\\\",\\n \\\"--profile\\\",\\n default=None,\\n help=\\\"\\\"\\\"\\n Specify the profile from which to fetch history or bookmarks. If\\n not provided all profiles are fetched\\n \\\"\\\"\\\",\\n )\\n\\n parser_.add_argument(\\n \\\"--show-profiles\\\",\\n default=None,\\n metavar=\\\"BROWSER\\\",\\n help=f\\\"\\\"\\\"\\n List all available profiles for a given browser where browser\\n can be one of default, {AVAILABLE_BROWSERS}. The browser\\n must always be provided.\\n \\\"\\\"\\\",\\n )\\n\\n parser_.add_argument(\\n \\\"-v\\\", \\\"--version\\\", action=\\\"version\\\", version=\\\"%(prog)s \\\" + __version__\\n )\\n\\n return parser_\",\n \"def _cli_parser():\\n parser = argparse.ArgumentParser()\\n # Original flags\\n parser.add_argument('-s', type=str, metavar='input_vol',\\n help=\\\"Absolute path to input volume. Input should be \\\"\\n \\\"in nifti format\\\")\\n parser.add_argument('-o', type=str, metavar='output_dir',\\n help=\\\"Absolute path to output directory\\\")\\n parser.add_argument('-p', type=str, metavar='template_type', default='MNI152_orig',\\n help=\\\"Type of volumetric template used in index files. \\\"\\n \\\"Use MNI152_orig or Colin27_orig when -r is \\\"\\n \\\"RF_ANTs. Use MNI152_norm or Colin27_norm when \\\"\\n \\\"-r is RF_M3Z. Otherwise, an exception is raised. \\\"\\n \\\"Ensure that the template matches the standard \\\"\\n \\\"space of -i (i.e., use MNI152_* if -i is \\\"\\n \\\"in MNI152-space). Default: MNI152_orig\\\")\\n parser.add_argument('-r', type=str, metavar='RF_type', default='RF_ANTs',\\n help=\\\"Type of Registration Fusion approaches used to \\\"\\n \\\"generate the mappings (RF_M3Z or RF_ANTs). \\\" \\n \\\"RF_M3Z is recommended if data was registered \\\" \\n \\\"from subject's space to the volumetric atlas \\\" \\n \\\"space using FreeSurfer. RF_ANTs is recommended \\\" \\n \\\"if such registrations were carried out using \\\" \\n \\\"other tools, especially ANTs. Default: RF_ANTs\\\")\\n parser.add_argument('-i', type=str, metavar='interp', default='linear',\\n help=\\\"Interpolation (linear or nearest). If \\\"\\n \\\"-g is label.gii, then interpolation is always set \\\"\\n \\\"to nearest and a warning is raised. Default: \\\"\\n \\\"linear\\\")\\n # New flags\\n parser.add_argument('-t', type=str, metavar='out_type', default='nii.gz',\\n help=\\\"File type of surface files. nii.gz is true to \\\"\\n \\\"the original Wu et al (2018) implementation. \\\"\\n \\\"Note that gifti formats, either \\\"\\n \\\"func.gii or label.gii, are often preferred. \\\"\\n \\\"Default: nii.gz\\\")\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(\\n description=\\\"Subscription Watch CSV file packaging script\\\", prog=sys.argv[0])\\n\\n # required args\\n parser.add_argument(\\\"-f\\\", \\\"--filepath\\\", required=True,\\n help=\\\"path to files to package\\\")\\n parser.add_argument(\\n \\\"-s\\\",\\n \\\"--max-size\\\",\\n type=int,\\n default=DEFAULT_MAX_SIZE,\\n help=f\\\"Maximum size of packages in MiB. (Default: {DEFAULT_MAX_SIZE} MiB)\\\",\\n )\\n parser.add_argument(\\n \\\"-o\\\", \\\"--overwrite\\\", action=\\\"store_true\\\", default=False, help=\\\"whether to overwrite existing files.\\\"\\n )\\n parser.add_argument(\\\"--ocp-cluster-id\\\", required=True,\\n help=\\\"OCP Cluster ID\\\")\\n parser.add_argument(\\\"-v\\\", \\\"--verbosity\\\", action=\\\"count\\\",\\n default=0, help=\\\"increase verbosity (up to -vvv)\\\")\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description=\\\"Sequence Cleaner: Remove Duplicate Sequences, etc\\\",\\n epilog=\\\"example > sequence_cleaner -q INPUT -o OUTPUT\\\")\\n parser.add_argument('-v', '--version', action='version', version='sequence_cleaner {}'.format(version))\\n parser.add_argument(\\\"-q\\\", \\\"--query\\\", help=\\\"Path to directory with FAST(A/Q) files\\\", required=True)\\n parser.add_argument(\\\"-o\\\", \\\"--output_directory\\\", help=\\\"Path to output files\\\", required=True)\\n parser.add_argument(\\\"-ml\\\", \\\"--minimum_length\\\", help=\\\"Minimum length allowed (default=0 - allows all the lengths)\\\",\\n default=\\\"0\\\")\\n parser.add_argument(\\\"-mn\\\", \\\"--percentage_n\\\", help=\\\"Percentage of N is allowed (default=100)\\\", default=\\\"100\\\")\\n parser.add_argument('--keep_all_duplicates', help='Keep All Duplicate Sequences', action='store_false', required=False)\\n parser.add_argument('--remove_ambiguous', help='Remove any sequence with ambiguous bases', action='store_true', required=False)\\n\\n parser.add_argument('-l', '--log', help='Path to log file (Default: STDOUT).', required=False)\\n\\n return parser.parse_args()\",\n \"def parser():\\n fetch_all_news_codes()\\n load_config_key()\\n\\n if not sys.argv[1:]:\\n print(\\\"Arguments needed. Use argument --help/-h for more information.\\\")\\n else:\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\\"--show_all\\\", \\\"-sa\\\", action=\\\"store_true\\\",\\n help=\\\"Shows all available news channel codes.\\\")\\n parser.add_argument(\\\"--categories\\\", \\\"-c\\\", action=\\\"store_true\\\",\\n help=\\\"Shows all available news categories.\\\")\\n parser.add_argument(\\\"--show\\\", \\\"-s\\\", action=\\\"store\\\",\\n help=\\\"Shows all news channel codes for a specified category.\\\")\\n parser.add_argument(\\\"--news\\\", \\\"-n\\\", type=str, help=\\\"Shows news articles \\\"\\n \\\"for a specified news channel code.\\\")\\n args = parser.parse_args()\\n\\n if args.show_all:\\n show_sources_all()\\n elif args.categories:\\n show_categories()\\n elif args.show:\\n show_sources_category(args.show)\\n elif args.news:\\n if args.news in news_codes:\\n show_news(args.news, BASE_URL)\\n else:\\n print(\\\"Invalid news code.\\\")\\n sys.exit(1)\",\n \"def processArgs(self, argv):\\n parser = OptionParser(usage=usage)\\n parser.add_option(\\\"-a\\\", \\\"--show_ADT\\\", action=\\\"store_true\\\", dest=\\\"show_ADT\\\",\\n default=self.show_ADT, help=\\\"Display ADT value if set\\\")\\n parser.add_option(\\\"-f\\\", \\\"--show_file\\\", action=\\\"store_true\\\", dest=\\\"show_file\\\",\\n default=self.show_file, help=\\\"Display matching filename if set\\\")\\n parser.add_option(\\\"-t\\\", \\\"--show_time\\\", action=\\\"store_true\\\", dest=\\\"show_time\\\",\\n default=self.show_time, help=\\\"Display message time\\\")\\n parser.add_option(\\\"-v\\\", \\\"--show_visitID\\\", action=\\\"store_true\\\", dest=\\\"show_visitID\\\",\\n default=self.show_visitID, help=\\\"Display visit ID\\\")\\n parser.add_option(\\\"-p\\\", \\\"--show_pc\\\",\\n action=\\\"store_true\\\",\\n dest=\\\"show_pc\\\",\\n default=self.show_pc,\\n help=\\\"Display patient class\\\")\\n\\n (options, pargs) = parser.parse_args()\\n if len(pargs) < 3:\\n parser.error(\\\"incorrect number of arguments\\\")\\n\\n self.show_ADT = parser.values.show_ADT\\n self.show_file = parser.values.show_file\\n self.show_time = parser.values.show_time\\n self.show_visitID = parser.values.show_visitID\\n self.show_pc = parser.values.show_pc\\n \\n self.segments_of_interest = pargs.pop(0)\\n if len(self.segments_of_interest) != 3:\\n parser.error(\\\"segment '%s' looks incorrect, expected something like 'PV1'\\\"\\n % self.segments_of_interest)\\n\\n try:\\n nums = pargs.pop(0).split(\\\",\\\")\\n for num in nums:\\n if 'MSH' == self.segments_of_interest:\\n num = int(num) - 1\\n self.sequences.append(int(num))\\n except:\\n parser.error(\\\"sequence must be an integer, separate multiple w/ comma and no spaces\\\")\\n\\n for patternOrFile in pargs:\\n for file in glob.glob(patternOrFile):\\n if not os.path.isfile(file):\\n parser.error(\\\"can't open input file %s\\\" % file)\\n self.filelist.append(file)\\n \\n # Require at least one file\\n if not len(self.filelist):\\n parser.error(\\\"at least one input file is required\\\")\",\n \"def get_cmd_line_args():\\n parser = argparse.ArgumentParser(\\n description=DOC, formatter_class=argparse.RawTextHelpFormatter)\\n\\n # Required arguments\\n required = parser.add_argument_group(\\\"Required arguments\\\")\\n required.add_argument(\\n \\\"--fastq-regex\\\", required=True, type=is_fastq_regex, metavar=\\\"<regex>\\\",\\n help=\\n \\\"Snakemake regex used to infer the FASTQ files to process and the \\\"\\n \\\"related wildcards: {sample} (mandatory), {lane} (optional) and \\\"\\n \\\"{end} (mandatory if paired-end sequencing), e.g. \\\"\\n \\\"/path/to/data/{sample}/{sample}_{ignore1}_{lane}_{end}_001.fastq.gz\\\"\\n )\\n required.add_argument(\\n \\\"--outdir\\\", required=True, metavar=\\\"<dir>\\\", help=\\\"Output directory.\\\"\\n )\\n required.add_argument(\\n \\\"--ref-build\\\", required=True, metavar=\\\"<version>\\\", help=\\n \\\"Reference genome build, e.g. hg19 or mm10. Assuming the existence of \\\"\\n \\\"the 3 following files in <--ref-genome-dir>: <ref build>.fa \\\"\\n \\\"<ref build>.fa.fai and <ref build>.fa.dict\\\"\\n )\\n required.add_argument(\\n \\\"--ref-genome-dir\\\", metavar=\\\"<dir>\\\", help=\\n \\\"Bisulfite reference genome directory, including '<ref build>.fa', \\\"\\n \\\"'<ref build>.fa.fai', '<ref build>.fa.dict' and the \\\"\\n \\\"'Bisulfite_Genome' directory created by running the \\\"\\n \\\"'bismark_genome_preparation' script. See README.md documentation.\\\"\\n )\\n\\n\\n # Optional general arguments\\n optional = parser.add_argument_group(\\\"Optional\\\")\\n optional.add_argument(\\n \\\"--single-end\\\", action=\\\"store_false\\\", dest=\\\"paired_end\\\", help=\\n \\\"By default paired-end sequencing is assumed, for single-end set this \\\"\\n \\\"flag.\\\"\\n )\\n optional.add_argument(\\n \\\"--rrbs\\\", action=\\\"store_true\\\", help=\\n \\\"For Reduced Representation Bisulfite Sequencing (RRBS) set this flag.\\\"\\n )\\n optional.add_argument(\\n \\\"--no-deduplication\\\", action=\\\"store_false\\\",\\n dest=\\\"use_bismark_deduplicate\\\", help=\\n \\\"Set this flag to not apply Bismark BAM deduplication. The deduplica\\\"\\n \\\"tion removes reads with similar start/end positions on a given chromo\\\"\\n \\\"some. It is not a valid PCR correction for RRBS or amplicon data. \\\"\\n \\\"The deduplication is not applied if the --rrbs flag is set.\\\"\\n )\\n optional.add_argument(\\n \\\"--non-directional-library\\\", action=\\\"store_false\\\",\\n dest=\\\"directional_library\\\", help=\\n \\\"By default the library is assumed to be directional, if not set this \\\"\\n \\\"flag. See Bismark documentation for more information.\\\"\\n )\\n optional.add_argument(\\n \\\"--target-bed\\\", type=is_file, metavar=\\\"<path>\\\", help=\\n \\\"For targeted sequencing, the path to the BED file listing the regions\\\"\\n \\\" targeted. Used only for read coverage computation. If no BED is pro\\\"\\n \\\"vided the coverage will be computed on the whole reference genome.\\\"\\n )\\n optional.add_argument(\\n \\\"--target-kit\\\", metavar=\\\"<name>\\\", help=\\n \\\"For targeted sequencing, the name of the kit used to target to be \\\"\\n \\\"reported in the preprocessing report. Does not affect processing.\\\"\\n )\\n optional.add_argument(\\n \\\"--phred\\\", type=int, choices={33, 64}, default=DEFAULT_OF[\\\"phred\\\"],\\n metavar=\\\"<33|64>\\\", help=\\n \\\"Base quality encoding of input FASTQ files: 33|64, by default %i.\\\"\\n % DEFAULT_OF[\\\"phred\\\"]\\n )\\n optional.add_argument(\\n \\\"--r1-id\\\", default=DEFAULT_OF[\\\"r1_id\\\"], metavar=\\\"<ID>\\\", help=\\n \\\"Case-insensitive ID used to identify R1 (forward) reads in paired-end\\\"\\n \\\" sequencing, by default '%s'.\\\" % DEFAULT_OF[\\\"r1_id\\\"]\\n )\\n optional.add_argument(\\n \\\"--r2-id\\\", default=DEFAULT_OF[\\\"r2_id\\\"], metavar=\\\"<ID>\\\", help=\\n \\\"Case-insensitive ID used to identify R2 (reverse) reads in paired-end\\\"\\n \\\" sequencing, by default '%s'.\\\" % DEFAULT_OF[\\\"r2_id\\\"]\\n )\\n optional.add_argument(\\n \\\"--read-length\\\", type=int, metavar=\\\"<int>\\\", help=\\n \\\"Length of reads (e.g. 150) to write in the HTML report. \\\"\\n \\\"Does not affect the processing.\\\"\\n )\\n\\n # Optional FastQC arguments\\n fastqc = parser.add_argument_group(\\\"FastQC optional\\\")\\n optional.add_argument(\\n \\\"--fastqc-threads\\\", type=int, metavar=\\\"<int>\\\",\\n default=DEFAULT_OF[\\\"fastqc\\\"][\\\"threads\\\"], help=\\n \\\"FastQC '--threads' argument, by default %i.\\\"\\n % DEFAULT_OF[\\\"fastqc\\\"][\\\"threads\\\"]\\n )\\n\\n # Optional Trim Galore arguments\\n trim_galore = parser.add_argument_group(\\\"Trim Galore optional\\\")\\n ADAPTERS_URL = (\\n \\\"https://support.illumina.com/bulletins/2016/12/what-sequences-do-i\\\"\\n \\\"-use-for-adapter-trimming.html\\\")\\n trim_galore.add_argument(\\n \\\"--adapter-r1\\\", metavar=\\\"<sequence>\\\", help=\\n \\\"Trim Galore '--adapter' argument: adapter sequence to be trimmed off \\\"\\n \\\"read 1. Common sequences: %s\\\" % ADAPTERS_URL\\n )\\n trim_galore.add_argument(\\n \\\"--adapter-r2\\\", metavar=\\\"<sequence>\\\", help=\\n \\\"Trim Galore '--adapter2' argument: adapter sequence to be trimmed \\\"\\n \\\"off read 2. Common sequences: %s\\\" % ADAPTERS_URL\\n )\\n trim_galore.add_argument(\\n \\\"--quality\\\", type=int, default=DEFAULT_OF[\\\"trim_galore\\\"][\\\"quality\\\"],\\n metavar=\\\"<int>\\\", help=\\n \\\"Trim Galore '--quality' argument, by default %i.\\\"\\n % DEFAULT_OF[\\\"trim_galore\\\"][\\\"quality\\\"]\\n )\\n trim_galore.add_argument(\\n \\\"--stringency\\\", type=int, metavar=\\\"<int>\\\",\\n default=DEFAULT_OF[\\\"trim_galore\\\"][\\\"stringency\\\"], help=\\n \\\"Trim Galore '--stringency' argument: overlap with adapter sequence \\\"\\n \\\"required to trim, by default %i (very stringent).\\\"\\n % DEFAULT_OF[\\\"trim_galore\\\"][\\\"stringency\\\"]\\n )\\n trim_galore.add_argument(\\n \\\"--min-length\\\", type=int, metavar=\\\"<int>\\\",\\n default=DEFAULT_OF[\\\"trim_galore\\\"][\\\"min_length\\\"], help=\\n \\\"Trim Galore '--length' argument: minimum read length after trimming \\\"\\n \\\"otherwise removed, by default %i.\\\"\\n % DEFAULT_OF[\\\"trim_galore\\\"][\\\"min_length\\\"]\\n )\\n trim_galore.add_argument(\\n \\\"--error-rate\\\", type=float, metavar=\\\"<float>\\\",\\n default=DEFAULT_OF[\\\"trim_galore\\\"][\\\"error_rate\\\"], help=\\n \\\"Trim Galore '-e' argument: maximum allowed error rate with the \\\"\\n \\\"matching region, by default {}\\\"\\n .format(DEFAULT_OF[\\\"trim_galore\\\"][\\\"error_rate\\\"])\\n )\\n trim_galore.add_argument(\\n \\\"--max-n\\\", type=int, metavar=\\\"<int>\\\", help=\\n \\\"Trim Galore '--max_n' argument: Maximum number of 'N's in a read \\\"\\n \\\"otherwise removed. By default not applied.\\\"\\n )\\n trim_galore.add_argument(\\n \\\"--trim-n\\\", action=\\\"store_true\\\", help=\\n \\\"Trim Galore '--trim-n' argument: remove 'N's from ends of the read.\\\"\\n )\\n trim_galore.add_argument(\\n \\\"--clip-r1-5p\\\", type=int, metavar=\\\"<int>\\\", help=\\n \\\"Trim Galore '--clip_R1' argument: remove basepairs from 5' end of \\\"\\n \\\"read 1. Useful if there is a methylation bias at this end.\\\"\\n )\\n trim_galore.add_argument(\\n \\\"--clip-r2-5p\\\", type=int, metavar=\\\"<int>\\\", help=\\n \\\"Trim Galore '--clip_R2' argument: remove basepairs from 5' end of \\\"\\n \\\"read 2. Useful if there is a methylation bias at this end.\\\"\\n )\\n trim_galore.add_argument(\\n \\\"--clip-r1-3p\\\", type=int, metavar=\\\"<int>\\\", help=\\n \\\"Trim Galore '--three_prime_clip_R1' argument: remove basepairs from \\\"\\n \\\"3' end of read 1. Useful if there is a methylation bias at this end.\\\"\\n )\\n trim_galore.add_argument(\\n \\\"--clip-r2-3p\\\", type=int, metavar=\\\"<int>\\\", help=\\n \\\"Trim Galore '--three_prime_clip_R2' argument: remove basepairs from \\\"\\n \\\"3' end of read 2. Useful if there is a methylation bias at this end.\\\"\\n )\\n\\n # Optional Bismark tools arguments\\n bismark = parser.add_argument_group(\\\"Bismark optional\\\")\\n bismark.add_argument(\\n \\\"--seed-mismatch\\\", type=int, choices=[0, 1], metavar=\\\"<0|1>\\\",\\n default=DEFAULT_OF[\\\"bismark_bowtie2\\\"][\\\"seed_mismatch\\\"], help=\\n \\\"Maximum number of mismatch allowed in a seed alignment: 0|1, \\\"\\n \\\"by default %i.\\\" % DEFAULT_OF[\\\"bismark_bowtie2\\\"][\\\"seed_mismatch\\\"]\\n )\\n bismark.add_argument(\\n \\\"--bowtie2-threads\\\", type=int, metavar=\\\"<int>\\\",\\n default=DEFAULT_OF[\\\"bismark_bowtie2\\\"][\\\"threads\\\"], help=\\n \\\"Bowtie2 '--threads' argument, by default %i\\\"\\n % DEFAULT_OF[\\\"bismark_bowtie2\\\"][\\\"threads\\\"])\\n bismark.add_argument(\\n \\\"--meth-extract-threads\\\", type=int, metavar=\\\"<int>\\\",\\n default=DEFAULT_OF[\\\"bismark_meth_extract\\\"][\\\"threads\\\"], help=\\n \\\"bismark_methylation_extractor '--multicore' argument, by default %i.\\\"\\n % DEFAULT_OF[\\\"bismark_meth_extract\\\"][\\\"threads\\\"]\\n )\\n\\n # Optional Picard arguments\\n picard = parser.add_argument_group(\\\"Picard optional\\\")\\n picard.add_argument(\\n \\\"--picard-jvm-args\\\", default=DEFAULT_OF[\\\"picard\\\"][\\\"jvm_args\\\"],\\n metavar=\\\"<args>\\\", help=\\n \\\"Java virtual machine arguments, e.g. to control starting and maximum \\\"\\n \\\"heap size when running Picard, by default '%s'.\\\"\\n % DEFAULT_OF[\\\"picard\\\"][\\\"jvm_args\\\"]\\n )\\n\\n # Optional Samtools arguments\\n samtools = parser.add_argument_group(\\\"Samtools optional\\\")\\n samtools.add_argument(\\n \\\"--samtools-threads\\\", type=int, metavar=\\\"<int>\\\",\\n default=DEFAULT_OF[\\\"samtools\\\"][\\\"threads\\\"], help=\\n \\\"Samtools '--threads' argument, by default %i\\\"\\n % DEFAULT_OF[\\\"samtools\\\"][\\\"threads\\\"])\\n\\n # Parse the command line\\n args = parser.parse_args()\\n\\n # For paired-end sequencing, check that the '{end}' wildcard is provided\\n if args.paired_end is True and \\\"{end}\\\" not in args.fastq_regex:\\n raise ValueError(\\n \\\"The wildcard '{end}' is required in --fastq-regex argument when \\\"\\n \\\"working with paired-end sequencing.\\\")\\n\\n # Set 'use_bismark_deduplicate' to False if RRBS data\\n if args.rrbs is True:\\n args.use_bismark_deduplicate = False\\n\\n # Check reference genome directory\\n is_ref_genome_dir(args.ref_genome_dir, args.ref_build)\\n\\n # Convert the argparse object to a dict mapping <arg name> -> <val>\\n kwargs = vars(args)\\n\\n return kwargs\",\n \"def parse_args():\\n from argparse import ArgumentParser\\n ap = ArgumentParser(prog=__exe__, description=__purpose__)\\n ap.add_argument(\\n '--host', dest='host', default=None,\\n help='Host for XNAT. Default: env XNAT_HOST.')\\n ap.add_argument(\\n '-u', '--username', dest='username', default=None,\\n help='Username for XNAT.')\\n ap.add_argument('project', help='Project Label')\\n ap.add_argument('session', help='Session Label')\\n ap.add_argument(\\n 'proc_suffix', help='Proc name suffix', nargs='?', default='')\\n ap.add_argument(\\n '-sd', '--subjects_dir', dest='subjects_dir',\\n help='Subjects Directory',\\n default=os.environ.get('SUBJECTS_DIR', '/tmp'))\\n return ap.parse_args()\",\n \"def build_args():\\n parser = argparse.ArgumentParser(description='Validates, edits, or creates a 22 XML file')\\n subparsers = parser.add_subparsers(help='sub-command help')\\n \\n add_branch_parser(subparsers)\\n add_edit_parser(subparsers)\\n add_finalize_parser(subparsers)\\n add_grade_parser(subparsers)\\n add_new_parser(subparsers)\\n add_validate_parser(subparsers)\\n add_validate_document_parser(subparsers)\\n \\n return parser.parse_args()\",\n \"def _argParser():\\n parser = argparse.ArgumentParser(\\n prog='modelc',\\n description='Compile the given sources.')\\n if FULL_INTERFACE:\\n for (parameter,label) in OPTIONS:\\n parser.add_argument(\\n '--'+parameter,\\n dest=parameter,\\n const=1,\\n # default=0,\\n type=int,\\n nargs='?',\\n help='debug: control %s' % label)\\n parser.add_argument(\\n '-bw',\\n dest='bw',\\n action='store_true',\\n help='black and white output',\\n default=False)\\n parser.add_argument(\\n '-dg',\\n dest='dg',\\n action='store_true',\\n default=False)\\n parser.add_argument(\\n '--issues', '-i',\\n dest='issues',\\n const='top',\\n default='inline',\\n help='choose location of issues wrt to the listing.',\\n choices=['top', 'inline', 'bottom'],\\n type=str,\\n nargs='?')\\n parser.add_argument(\\n '--list', '-l',\\n dest='listing',\\n const='source',\\n default='no',\\n help='display a listing of model.',\\n choices=['no', 'source', 'model'],\\n type=str,\\n nargs='?')\\n parser.add_argument(\\n '--summary', '-s',\\n dest='summary',\\n const='bottom',\\n default='no',\\n help='display a summary of model.',\\n choices=['no', 'top', 'bottom'],\\n type = str,\\n nargs = '?')\\n parser.add_argument(\\n '-mode', '-m',\\n dest='mode',\\n const='full',\\n default='full',\\n help='choose the checking level.',\\n choices=['justAST', 'justASTDep', 'full'],\\n type=str,\\n nargs='?')\\n parser.add_argument(\\n '--verbose', '-v',\\n dest='verbose',\\n action='store_true',\\n default=False,\\n help='make output verbose.')\\n parser.add_argument(\\n '--quiet', '-q',\\n dest='quiet',\\n action='store_true',\\n help='create minimal amount of output.',\\n default=False)\\n parser.add_argument(\\n '--version', '-V',\\n dest='version',\\n action='store_true',\\n help='display modelscript version.',\\n default=False)\\n parser.add_argument(\\n 'sources',\\n metavar='source',\\n nargs='*',\\n help='A model source file or a directory.')\\n return parser\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(description=\\n \\\"This script receives 'grouped_hits.txt', uses a FASTA file to get the \\\\\\n \\\\nsequences, uses MAFFT to align each group, then generates a consensus \\\\\\n \\\\nsequence for each group using biopython.\\\\n\\\\n \\\\\\n Example: python {0} -g grouped_hits.txt -f sequences.fasta\\\".format(argv[0]),\\n formatter_class = argparse.RawDescriptionHelpFormatter)\\n \\n requiredNamed = parser.add_argument_group('required arguments')\\n\\n requiredNamed.add_argument(\\\"-g\\\", \\\"--GROUPS\\\", type=str, required=True,\\\\\\n help=\\\"Grouped hits file generated by group_self_BLAST.py\\\", action=\\\"store\\\")\\n\\n requiredNamed.add_argument(\\\"-f\\\", \\\"--FASTA\\\", type=str, required=True,\\\\\\n help=\\\"FASTA file containing all sequences.\\\", action=\\\"store\\\")\\n\\n return parser.parse_args()\",\n \"def parse_arguments(self, args):\\n # Create parser for arguments\\n parser = argparse.ArgumentParser(description=\\\"Intrusion Detection Dataset Toolkit (Core) - A toolkit for \\\"\\n \\\"injecting synthetically created attacks into PCAP files.\\\",\\n prog=\\\"id2t\\\")\\n # Required arguments\\n required_group = parser.add_argument_group('required arguments')\\n required_args_group = required_group.add_mutually_exclusive_group(required=True)\\n\\n required_args_group.add_argument('-i', '--input', metavar=\\\"PCAP_FILE\\\",\\n help='path to the input pcap file')\\n required_args_group.add_argument('-l', '--list-attacks', action='store_true')\\n\\n # Optional arguments\\n parser.add_argument('-c', '--config', metavar='CONFIG_FILE', help='file containing configuration parameters.',\\n action=LoadFromFile, type=open)\\n parser.add_argument('-e', '--export',\\n help='store statistics as a \\\".stat\\\" file',\\n action='store_true', default=False)\\n parser.add_argument('-r', '--recalculate',\\n help='recalculate statistics even if a cached version exists.',\\n action='store_true', default=False)\\n parser.add_argument('-s', '--statistics', help='print file statistics to stdout.', action='store_true',\\n default=False)\\n parser.add_argument('-p', '--plot',\\n help='creates the following plots: the values distributions of TTL, MSS, Window Size, '\\n 'protocol, and the novelty distributions of IP, port, TTL, MSS, Window Size,'\\n ' and ToS. In addition to packets count in interval-wise.', action='append',\\n nargs='?')\\n parser.add_argument('-q', '--query', metavar=\\\"QUERY\\\",\\n action='append', nargs='?',\\n help='query the statistics database. If no query is provided, '\\n 'the application enters query mode.')\\n parser.add_argument('-t', '--extraTests',\\n help='perform extra tests on the input pcap file, including calculating IP entropy'\\n 'in interval-wise, TCP checksum, and checking payload availability.',\\n action='store_true', default=False)\\n parser.add_argument('-S', '--rngSeed', action='append', help='sets rng seed for testing or benchmarking',\\n nargs='+', default=[])\\n parser.add_argument('-T', '--time', help='measures packet generation time', action='store_true', default=False)\\n parser.add_argument('-V', '--non-verbose', help='reduces terminal clutter', action='store_true', default=False)\\n parser.add_argument('-o', '--output', metavar=\\\"PCAP_FILE\\\", help='path to the output pcap file')\\n parser.add_argument('-ie', '--inject_empty', action='store_true',\\n help='injects ATTACK into an EMPTY PCAP file, using the statistics of the input PCAP.')\\n parser.add_argument('-d', '--debug', help='Runs ID2T in debug mode.', action='store_true', default=False)\\n parser.add_argument('-si', '--statistics_interval', help='interval duration in seconds', action='store',\\n type=float, nargs='+', default=[])\\n parser.add_argument('-rd', '--recalculate-delete',\\n help='recalculate statistics even if a cached version exists.'\\n 'also delete old interval statistics.'\\n 'surpresses (yes, no, delete) prompt.', action='store_true',\\n default=False)\\n parser.add_argument('-ry', '--recalculate-yes',\\n help='recalculate statistics even if a cached version exists.'\\n 'also recalculates old interval statistics.'\\n 'surpresses (yes, no, delete) prompt.', action='store_true',\\n default=False)\\n parser.add_argument('-rn', '--recalculate-no',\\n help='recalculate statistics even if a cached version exists.'\\n 'does not recalculate old interval statistics, but keeps them.'\\n 'surpresses (yes, no, delete) prompt.', action='store_true',\\n default=False)\\n parser.add_argument('-li', '--list-intervals', action='store_true',\\n help='prints all interval statistics tables available in the database')\\n parser.add_argument('--skip', action='store_true', help='skips every initialization right to query mode\\\\n'\\n 'CAUTION: this will only work if there already is a '\\n 'database')\\n\\n # Attack arguments\\n parser.add_argument('-a', '--attack', metavar=\\\"ATTACK\\\", action='append',\\n help='injects ATTACK into a PCAP file.', nargs='+')\\n\\n # Parse arguments\\n self.args = parser.parse_args(args)\\n\\n self.process_arguments()\",\n \"def setup_parser(self):\\n parser = argparse.ArgumentParser(description=DESCRIPTION)\\n parser.add_argument('words', metavar='W', nargs='+', help=POSITIONAL_HELP)\\n parser.add_argument('-a','--any', dest=\\\"search_funct\\\", action=\\\"store_const\\\", \\n const='any', default='all', help=SEARCH_HELP)\\n parser.add_argument('-o','--only-id', action='store_true', help=ID_HELP)\\n parser.add_argument('-u', '--update', action='store_true', help=UPDATE_HELP)\\n return parser\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(description=\\\"Reads in iClicker data from the submission \\\"\\n \\\"directory, and then writes it to the given \\\"\\n \\\"remote file.\\\")\\n parser.add_argument(\\\"submission_directory\\\", type=str, help=\\\"Directory of submissions that \\\"\\n \\\"contain a 'textbox_0.txt' file that references iClicker ID\\\")\\n parser.add_argument(\\\"remote_id_file\\\", type=str)\\n return parser.parse_args()\",\n \"def _parse_args():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('out', nargs='*', help='Create a plot for all provided'\\n ' output files')\\n parser.add_argument('--yscale', '-y', help='Y-axis scale',\\n default='linear')\\n parser.add_argument('--hits', help='Draw hits', dest='hits', action='store_true')\\n parser.add_argument('--no-hits', help='Do not draw hits', dest='hits', action='store_false')\\n parser.set_defaults(hits=True)\\n\\n parser.add_argument('--ltrim', help='Remove a number of smallest latency values from the plot', default=0, type=int)\\n parser.add_argument('--rtrim', help='Remove a number of biggest latency values from the plot', default=0, type=int)\\n\\n parser.add_argument('--misses', help='Draw misses', dest='misses', action='store_true')\\n parser.add_argument('--no-misses', help='Do not draw misses', dest='misses', action='store_false')\\n parser.set_defaults(misses=True)\\n\\n args = parser.parse_args()\\n if not args.out:\\n parser.error('at least one output need to be provided')\\n return args\",\n \"def parse_args():\\n parser = common_parser()\\n parser.description = (\\n \\\"Given a sequence dict, fasta index or a bed file, scatter over the \\\"\\n \\\"defined contigs/regions. Each contig/region will be split into \\\"\\n \\\"multiple overlapping regions, which will be written to a new bed \\\"\\n \\\"file. Each contig will be placed in a new file, unless the length of \\\"\\n \\\"the contigs/regions doesn't exceed a given number.\\\")\\n\\n parser.add_argument(\\\"-c\\\", \\\"--chunk-size\\\", type=int, default=1e6,\\n metavar=\\\"SIZE\\\",\\n help=\\\"The size of the chunks. The first chunk in a \\\"\\n \\\"region or contig will be exactly length SIZE, \\\"\\n \\\"subsequent chunks will SIZE + OVERLAP and the final \\\"\\n \\\"chunk may be anywhere from 0.5 to 1.5 times SIZE \\\"\\n \\\"plus overlap. If a region (or contig) is smaller \\\"\\n \\\"than SIZE the original regions will be returned. \\\"\\n \\\"Defaults to 1e6\\\")\\n parser.add_argument(\\\"-m\\\", \\\"--minimum-bp-per-file\\\", type=int, default=45e6,\\n help=\\\"The minimum number of bases represented within \\\"\\n \\\"a single output bed file. If an input contig or \\\"\\n \\\"region is smaller than this MINIMUM_BP_PER_FILE, \\\"\\n \\\"then the next contigs/regions will be placed in the \\\"\\n \\\"same file untill this minimum is met. Defaults to \\\"\\n \\\"45e6.\\\")\\n parser.add_argument(\\\"-o\\\", \\\"--overlap\\\", type=int, default=150,\\n help=\\\"The number of bases which each chunk should \\\"\\n \\\"overlap with the preceding one. Defaults to 150.\\\")\\n parser.add_argument(\\\"-S\\\", \\\"--split-contigs\\\", action=\\\"store_true\\\",\\n help=\\\"If set, contigs are allowed to be split up over \\\"\\n \\\"multiple files.\\\")\\n args = parser.parse_args()\\n return args\",\n \"def argument_parser(self):\\n parser = argparse.ArgumentParser(\\n prog='description2html',\\n description=self.description,\\n epilog=self.epilog)\\n\\n parser.add_argument(\\n '--no-confirm',\\n action='store_true',\\n help=('Ask user for confirmation to the user. Default is True'))\\n\\n parser.add_argument(\\n '-p', '--path',\\n metavar='path',\\n type=str,\\n required=True,\\n help=('the module path you want to apply the transformation'))\\n\\n parser.add_argument(\\n '--pretty-style',\\n action='store_true',\\n help='Create the index.html file using the odoo ccs style. '\\n ' Divide the README titles into visible sections.'\\n ' WARNING: This functionality still beta.')\\n\\n argcomplete.autocomplete(parser)\\n return parser.parse_args().__dict__\",\n \"def parse_args():\\n sentinel_dict = {}\\n\\n def _preprocess_sysargv(argv):\\n inputs = []\\n for arg in argv[1:]:\\n # handles case where values contain --, otherwise they will\\n # be interpreted as arguments.\\n if '--,' in arg or ',--' in arg or arg == '--':\\n sentinel = uuid4().hex\\n key = '%s' % sentinel\\n sentinel_dict[key] = arg\\n inputs.append(sentinel)\\n else:\\n inputs.append(arg)\\n return inputs\\n\\n def _postprocess_sysargv(v):\\n if v in sentinel_dict:\\n return sentinel_dict.get(v)\\n else:\\n return v\\n\\n #----- read input arguments\\n for i, arg in enumerate(sys.argv):\\n if (arg[0] == '-') and arg[1].isdigit(): sys.argv[i] = ' ' + arg\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument('-u', action='store_true', dest='helpmenu',help='extended HELP MENU with examples')\\n parser.add_argument('-i','--infile',action='store', dest='infile',help='name of file with SAC or mseed file(s)')\\n parser.add_argument('-g','--gain',action='store', dest='sensitivity',help='Stage 0 sensitivity')\\n parser.add_argument('-N','--net', action='store', dest='network',help='network')\\n parser.add_argument('-S','--sta', action='store', dest='station',help='station')\\n parser.add_argument('-C','--cha', action='store', dest='chantype',help='chantype')\\n parser.add_argument('-s','--start', action='store', dest='startstring',help='start time YYYY-MM-DDTHH:MM:SS')\\n parser.add_argument('-e','--end', action='store', dest='endstring',help='end time YYYY-MM-DDTHH:MM:SS')\\n parser.add_argument('-d','--duration', action='store', dest='durationinhours',help='duration in hours')\\n parser.add_argument('-dc','--dc','--datacenter', action='store', dest='datacenter',default='IRIS',help='FDSN data center (e.g. IRIS, SCEDC, NCEDC)')\\n parser.add_argument('-p','--plot',action='store_true',dest='iplot',help='make plots of each hourly trace (NOTE: can be slow)')\\n\\n helpextended = parser.parse_args(_preprocess_sysargv(sys.argv)).helpmenu\\n if ( helpextended is True ):\\n print ('')\\n print ('portable_pip_squeak: assess a station either using local data or to be downloaded')\\n print ('')\\n print ('Usage: portable_pip_squeak.py [options]')\\n print ('')\\n print ('EXAMPLES:')\\n print ('portable_pip_squeak.py --infile my_SAC_files.txt')\\n print ('portable_pip_squeak.py -N UW -S TKEY -C HH -s 2018-01-01T00:00:00 -d 2 -p')\\n print ('portable_pip_squeak.py -N CI -S LEO -C HN -s 2020-01-01T00:00:00 -d 24 -dc SCEDC')\\n print ('')\\n print ('Inputs if supplying your own data:')\\n print (' -i, --infile Name of text file with SAC/mseed file(s) of 3 (Z,N,E) traces.')\\n print (' -g, --gain Gain or Stage 0 sensitivity')\\n print (' ')\\n print ('Inputs if downloading data:')\\n print (' -s, --starttime Trace start time (YYYY-MM-DD,HH:MM:SS)')\\n print ('')\\n print (' One of these:')\\n print (' -e, --endtime Trace end time (YYYY-MM-DD,HH:MM:SS)')\\n print (' -d, --duration Duration in hours from starttime')\\n print (' Note: if duration is neg, starttime becomes endtime')\\n print (' N, S, C and a datacenter if other than IRIS')\\n print (' -N, --net Network code')\\n print (' -S, --sta Station code')\\n print (' -C, --cha Channel type, e.g. EN or HH')\\n print (' -dc, --datacenter Name of FDSN data center if not IRIS, e.g. SCEDC, NCEDC')\\n print (' ')\\n print ('Optional flags:')\\n print ('-P, --plot Flag to make a figure for each hour. Note: can be slow.')\\n print ('-u Print this extended help menu')\\n print ('')\\n\\n\\n return parser.parse_args(_preprocess_sysargv(sys.argv))\",\n \"def createHelp():\\n \\n epilog_string=\\\"Any bug is welcome reported to fanxiaojuan@picb.ac.cn\\\"\\n description_string='The program is going to extend the paired-end reads interval nucleotides'\\n parser = argparse.ArgumentParser(description=description_string,epilog=epilog_string)\\n parser.add_argument('-i', '--input file', dest='fnIn', default='plasmid.rmdup.bed', type=str,help='input file')\\n parser.add_argument('-i_gtf', '--gtf', dest='gtf', default='gencode.v28lift37.annotation.gtf', type=str,help='input gencode gtf annotation file')\\n parser.add_argument('-db', '--db', dest='db', default='gencode_v28lift37_comprehensive.txt', type=str,help='input file')\\n parser.add_argument('-o', '--overhang', dest='o', default=0, type=int,help='input file')\\n parser.add_argument('-o_anno', '--out-annotation', dest='anno', default='plasmid.fragment.rmdup.annotation.bed', type=str,help='output mature mRNA')\\n op=parser.parse_args()\\n return op\",\n \"def parse_args():\\n parser = argparser()\\n args = parser.parse_args()\\n\\n # --------------------------------------------------------- #\\n # Parse and check runtime parameters.\\n # --------------------------------------------------------- #\\n\\n # check validity of cores selection.\\n max_ppn = max_cpu() + 1\\n if args.proc_per_node > max_ppn:\\n warnings.warn('{0} is greater than the number of available cores ({1}). Reducing to {2}'\\n .format(args.proc_per_node, max_ppn, max_ppn - 1))\\n args.proc_per_node = max_ppn - 1\\n\\n # ensure that user has supplied fresh .bam/.bai files or a directory containing alignment files.\\n if not args.bam_files and not args.bam_dir:\\n raise ValueError('Must specify either --bam-files or --bam-dir.')\\n\\n if args.bam_files and args.bam_dir:\\n raise ValueError('Both --bam-files and --bam-dir were provided! Not sure which data set to use.')\\n\\n # --------------------------------------------------------- #\\n # Gather input RNA-Seq + genome annotation files.\\n # --------------------------------------------------------- #\\n\\n # check validity of gene annotation file selection.\\n if not args.genome_annotation:\\n raise ValueError('If warm-start directory not specified, gene annotation file must be specified!')\\n\\n else:\\n if not os.path.isfile(args.genome_annotation):\\n raise FileNotFoundError('Gene annotation file {0} not found.'.format(args.genome_annotation))\\n\\n # check validity of file i/o selection.\\n bam_files = list()\\n bai_files = list()\\n create_bai_files = list()\\n\\n # INPUT OPTION 1: a --bam-dir was specified.\\n if args.bam_dir:\\n\\n # if user used both --bam-dir and --bam-files and/or --bai-files, yell at them. (only use one method).\\n if args.bam_files is not None or args.bai_files is not None:\\n raise ValueError('Do not specify both a --bam-dir and either --bam-files and/or --bai-files.'\\n 'Use one input selection method or the other.')\\n\\n # check that the dir actually exists.\\n if not os.path.isdir(args.bam_dir):\\n raise NotADirectoryError('Cannot find --bam-dir {0}'.format(args.bam_dir))\\n\\n # scan directory for .bam files.\\n for f in os.listdir(args.bam_dir):\\n if f.endswith('.bam'):\\n bam_files.append(os.path.join(args.bam_dir, f))\\n\\n # search for .bai files in the --bam-dir. If they don't exist, try to make them.\\n for bam_file in bam_files:\\n bai_file = re.sub('.bam$', '.bai', bam_file)\\n\\n # if .bai file under same basename as .bam file doesn't exist,\\n # add it to list of .bai files that need to be created.\\n if not os.path.isfile(bai_file):\\n bai_files.append(bai_from_bam_file(bam_file))\\n create_bai_files.append(bam_file)\\n else:\\n bai_files.append(bai_file)\\n\\n # INPUT OPTION 2: --bam-files and possibly --bai-files were specified.\\n else:\\n # ensure .bam files are actually .bam files.\\n for bam_file in args.bam_files:\\n if not bam_file.endswith('.bam'):\\n raise ValueError('{0} is not a .bam file.'.format(bam_file))\\n elif not os.path.isfile(bam_file):\\n raise FileNotFoundError('Count not find .bam file {0}'.format(bam_file))\\n else:\\n bam_files.append(bam_file)\\n\\n # case where user has specified .bai files to accompany .bam files.\\n if args.bai_files is not None:\\n # if user has supplied an incorrect number of bai files, fail out.\\n if len(args.bai_files) != len(bam_files):\\n raise ValueError('Number of supplied .bai files does not match number of supplied .bam files.')\\n\\n # ensure .bai files are actually .bai files.\\n for bai_file in args.bai_files:\\n if not bai_file.endswith('.bai'):\\n raise ValueError('{0} is not a .bai file.'.format(bai_file))\\n elif not os.path.isfile(bai_file):\\n raise FileNotFoundError('Count not find .bai file {0}'.format(bai_file))\\n else:\\n bai_files.append(bai_file)\\n\\n # if user has not supplied any bai files: look for them under the same name\\n # as each of the .bam files, or create new .bai files with samtools (if possible).\\n else:\\n for bam_file in bam_files:\\n bai_file = re.sub('.bam$', '.bai', bam_file)\\n\\n # if .bai file under same name as .bam file doesn't exist,\\n # add it to list of .bam files for which we need to create a .bai file.\\n if not os.path.isfile(bai_file):\\n bai_files.append(bai_from_bam_file(bam_file))\\n create_bai_files.append(bam_file)\\n else:\\n bai_files.append(bai_file)\\n\\n # ensure that input files are uniquely named.\\n if len(bam_files) != len(set(bam_files)):\\n raise ValueError('Supplied .bam files are not uniquely named!')\\n\\n # create parser attributes for bam/index files.\\n args.bam_files = bam_files\\n args.bai_files = bai_files\\n args.create_bai_files = create_bai_files\\n\\n return args\",\n \"def build_parser():\\n def commaSplitter(str):\\n \\\"\\\"\\\"\\n Argparse a comm-seperated list\\n \\\"\\\"\\\"\\n # leave this here as a reminder of what I should do to make the argument parsing more robust\\n\\n # if sqrt != int(sqrt):\\n # msg = \\\"%r is not a perfect square\\\" % string\\n # raise argparse.ArgumentTypeError(msg)\\n # return value\\n return str.split(',')\\n\\n def existing_file(fname):\\n \\\"\\\"\\\"\\n Argparse type for an existing file\\n \\\"\\\"\\\"\\n if not os.path.isfile(fname):\\n raise ValueError(\\\"Invalid file: \\\" + str(fname))\\n return fname\\n\\n parser = argparse.ArgumentParser(description=__doc__)\\n\\n parser.add_argument('-p', '--prefix', help='dont really know what this does...',\\n action='store', default='patient', dest='prefix')\\n parser.add_argument('-d', '--date', help='dont really know what this does...',\\n action='store', default='', dest='sampledate')\\n parser.add_argument('template', type=argparse.FileType('r'), help='BEAST config template file')\\n parser.add_argument('fasta', type=argparse.FileType('r'), help='file of sequences (in FASTA format)')\\n\\n return parser\",\n \"def argparser():\\n parser = argparse.ArgumentParser(add_help=False)\\n parser.add_argument('--bam-files'\\n , nargs='+'\\n , default=None\\n , required=False\\n , help='Aligned read files (can be multiple; separate with space) in .bam format. '\\n '.bam files may be for paired or single-end read experiments.')\\n parser.add_argument('--bai-files'\\n , nargs='+'\\n , default=None\\n , required=False\\n , help='Input .bam index files (Can be multiple; separate with space). '\\n 'Only use with --bam-files.'\\n '.bai files for files passed to --bam-files. Assumed .bai file order corresponds to '\\n 'supplied .bam files. If --bam-files is supplied and not --bai-files, it is assumed '\\n 'that you have .bai files in the same location as --bam-files, and with the same '\\n 'basename, e.g. (A01.bam, A01.bai), (sample_27.bam, sample_27.bai)')\\n parser.add_argument('--bam-dir'\\n , default=None\\n , required=False\\n , help='Input .bam/.bai data directory. Use instead of, or in addition to, specifying individual '\\n '.bam files. All .bam files (and .bai files with the same basename) in this directory '\\n 'will be considered covcurv input.')\\n parser.add_argument('-g'\\n , '--genome-annotation'\\n , type=str\\n , default=None\\n , required=False\\n , help='Genome annotation file.'\\n 'Must have extension .gtf or .gff.'\\n 'All non-exon regions will be removed, along with exons that appear in '\\n 'multiple chromosomes and exons that overlap with multiple genes.')\\n parser.add_argument('-o'\\n , '--output-dir'\\n , type=str\\n , default=None\\n , required=False\\n , help='Name for a covcurv output directory.'\\n 'Name an directory for storing coverage data output by covcurv. '\\n 'If not specified, directory ./covcurv_[mmddyy]_[HHMMSS] will be created.')\\n parser.add_argument('-u'\\n , '--unique-alignments'\\n , action='store_true'\\n , help='Only retain reads that were uniquely aligned. All reads with '\\n 'the flag \\\"NH:i:<x>\\\" with x > 1 will be dropped.')\\n parser.add_argument('-p'\\n , '--proc-per-node'\\n , type=int\\n , required=False\\n , default=max_cpu()\\n , help='Number of processes to spawn per node, for within-node parallelization.'\\n 'Defaults to the number of available cores (on the worker node) - 1. '\\n 'If too high for a given node, reduce to the node\\\\'s default.')\\n parser.add_argument('-v'\\n , '--version'\\n , action='version'\\n , version='covcurv version {0}'.format(pkg_resources.get_distribution('covcurv').version)\\n , help='Display covcurv package version and exit.')\\n parser.add_argument('-h'\\n , '--help'\\n , action='help'\\n , default=argparse.SUPPRESS\\n , help='covcurv: Per-gene read coverage matrix pipeline package.')\\n\\n return parser\",\n \"def parseArguments():\\n parser = argparse.ArgumentParser(description=\\\"AutoMacTC: an Automated macOS forensic triage collection framework.\\\", add_help=False)\\n\\n module_filter = parser.add_argument_group('module filter')\\n mods = module_filter.add_mutually_exclusive_group(required=False)\\n mods.add_argument('-m', '--include_modules', type=str, nargs='+', help='module(s) to use, use \\\"all\\\" to run all modules, space separated list only', default=[''], required=False)\\n mods.add_argument('-x', '--exclude_modules', type=str, nargs='+', help='assumes you want to run all modules EXCEPT those specified here, space separated list only', default=[''], required=False)\\n mods.add_argument('-l', '--list_modules', help='if flag is provided, will list available modules and exit.', default=False, action='store_true', required=False)\\n\\n general = parser.add_argument_group('general arguments')\\n general.add_argument(\\\"-h\\\", \\\"--help\\\", action=\\\"help\\\", help=\\\"show this help message and exit\\\")\\n general.add_argument(\\\"-v\\\", \\\"--verbose\\\", default=False, action='store_true', help=\\\"enable verbose logging\\\")\\n general.add_argument('-i', '--inputdir', default='/', help='input directory; mount dmg with mountdmg.sh script and use -f to analyze mounted HFS or APFS Volume, use volume appended with \\\"Data\\\" (e.g. \\\"Macintosh HD - Data\\\") for 10.15+ systems', required=False)\\n general.add_argument('-is', '--inputsysdir', default='', help='input system drive if using mounted drive from 10.15+ system (e.g. \\\"Macintosh HD\\\")', required=False)\\n general.add_argument('-o', '--outputdir', default='./', help='output directory', required=False)\\n general.add_argument('-p', '--prefix', help='prefix to append to tarball and/or output files', default='automactc-output', required=False)\\n general.add_argument('-f', '--forensic_mode', help='if flag is provided, will analyze mounted volume provided as inputdir', default=False, action='store_true', required=False)\\n general.add_argument('-nt', '--no_tarball', help='if flag is provided, will NOT package output files into tarball', default=False, action='store_true', required=False)\\n general.add_argument('-nl', '--no_logfile', help='if flag is provided, will NOT generate logfile on disk', default=False, action='store_true', required=False)\\n general.add_argument('-fmt', '--output_format', help='toggle between csv and json output, defaults to csv', default='csv', action='store', required=False, choices=['csv', 'json'])\\n general.add_argument('-np', '--no_low_priority', help='if flag is provided, will NOT run automactc with highest niceness (lowest CPU priority). high niceness is default', default=False, action='store_true', required=False)\\n general.add_argument('-b', '--multiprocessing', help='if flag is provided, WILL multiprocess modules [WARNING: Experimental!]', default=False, action='store_true', required=False)\\n general.add_argument('-O', '--override_mount', help='if flag is provided, WILL bypass error where inputdir does not contain expected subdirs', default=False, action='store_true', required=False)\\n\\n console_log_args = parser.add_argument_group('console logging verbosity')\\n console_logging_args = console_log_args.add_mutually_exclusive_group(required=False)\\n console_logging_args.add_argument('-q', '--quiet', help='if flag is provided, will NOT output to console at all', default=False, action='store_true', required=False)\\n console_logging_args.add_argument('-r', '--rtr', help='reduce verbosity to display nicely on RTR console', default=False, action='store_true', required=False)\\n console_logging_args.add_argument('-d', '--debug', help='enable debug logging to console', default=False, action='store_true', required=False)\\n\\n dirlist_args = parser.add_argument_group('specific module arguments')\\n dirlist_args.add_argument('-K', '--dir_include_dirs', type=str, nargs='+', help='directory inclusion filter for dirlist module, defaults to volume root, space separated list only', default=[''], required=False)\\n dirlist_args.add_argument('-E', '--dir_exclude_dirs', type=str, nargs='+', help='directory and file exclusion filter for dirlist module. defaults are specified in README. space separated list only. \\\\\\n put \\\\'no-defaults\\\\' as first item to overwrite default exclusions and then provide your own exclusions', default=[''], required=False)\\n dirlist_args.add_argument('-H', '--dir_hash_alg', nargs='+', help='either sha256 or md5 or both or none, at least one is recommended, defaults to sha256. also applies to autoruns module', default='sha256', required=False)\\n dirlist_args.add_argument('-S', '--dir_hash_size_limit', type=int, help='file size filter for which files to hash, in megabytes, defaults to 10MB. also applies to autoruns module', default=10, required=False)\\n dirlist_args.add_argument('-R', '--dir_recurse_bundles', help='will fully recurse app bundles if flag is provided. this takes much more time and space', default=False, action='store_true', required=False)\\n dirlist_args.add_argument('-NC', '--dir_no_code_signatures', help='if flag is provided, will NOT check code signatures for app and kext files. also applies to autoruns module', default=False, action='store_true', required=False)\\n dirlist_args.add_argument('-NM', '--dir_no_multithreading', help='if flag is provided, will NOT multithread the dirlist module', default=False, action='store_true', required=False)\\n args = parser.parse_args()\\n\\n return args\",\n \"def handle_program_options():\\n parser = argparse.ArgumentParser(description=\\\"Gather numeric information \\\\\\n about the processed sequence data in an \\\\\\n MG-RAST project.\\\")\\n parser.add_argument('project_id',\\n help=\\\"The project identifier (MG-RAST ID)\\\")\\n parser.add_argument('-a', '--auth_key',\\n help=\\\"An MG-RAST API authorization key. This is \\\\\\n necessary to access projects marked as private.\\\")\\n parser.add_argument('-g', '--group_by', action='append',\\n help=\\\"A string that matches some part of the \\\\\\n 'Metagenome Name' field. All matching project \\\\\\n metagenomes will be grouped by this identifier \\\\\\n and their stats will be summed. This option can \\\\\\n be specified multiple times to create multiple \\\\\\n groups. All non-matching metagenomes will \\\\\\n appear separately in the table. NOTE: \\\\\\n Strings will be matched longest first. This \\\\\\n allows for matching names that might be a \\\\\\n substring of another match. For example: -g S \\\\\\n -g NS. The name field will first be matched \\\\\\n against the longest string (NS) first and then \\\\\\n each smaller string in order.\\\")\\n parser.add_argument('-o', '--output_filename', default='meta_stats.txt',\\n help=\\\"The name of the file the project summary \\\\\\n information will be written to.\\\")\\n\\n# parser.add_argument('-v', '--verbose', action='store_true')\\n\\n return parser.parse_args()\",\n \"def arg_parse():\\n\\n parser = argparse.ArgumentParser()\\n\\n parser.add_argument(\\n \\\"-f\\\",\\n \\\"--fpath\\\",\\n type=str,\\n required=True,\\n help=\\\"Path to files to generate test data from e.g. /badc/cmip5/data/cmip5/output1/MOHC/HadGEM2-ES/rcp85/mon/atmos/Amon/r1i1p1/latest/tas\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-t\\\",\\n \\\"--time_only\\\",\\n default=False,\\n help=\\\"Only generate one time step of this dataset\\\",\\n action=\\\"store_true\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-s\\\",\\n \\\"--step\\\",\\n type=int,\\n default=100,\\n help=\\\"Step to select latitude/longitude by. Only relevant when time_only is False\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-n\\\",\\n \\\"--number\\\",\\n type=int,\\n default=0,\\n help=\\\"Number of files to generate. Default is all files. Only relevant when time_only is False\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-l\\\",\\n \\\"--level\\\",\\n type=int,\\n default=-1,\\n help=\\\"Number of levels to extract, starting with index 0.\\\",\\n )\\n\\n parser.add_argument(\\n \\\"-c\\\", \\\"--compress\\\", help=\\\"Compress the files.\\\", action=\\\"store_true\\\"\\n )\\n\\n return parser.parse_args()\",\n \"def parse_cmdline():\\n\\tparser = ArgumentParser(prog=\\\"FastP_QC.py\\\", description=\\\"\\\"\\\"Script collects stats from fastp jsons.\\\"\\\"\\\")\\n\\tparser.add_argument(\\\"-r1\\\", \\\"--r1_stats\\\", dest=\\\"r1_stats\\\", action=\\\"store\\\", required=True, help=\\\"Text file with r1 stats, from q30.py script.\\\")\\n\\tparser.add_argument(\\\"-r2\\\", \\\"--r2_stats\\\", dest=\\\"r2_stats\\\", action=\\\"store\\\", required=True, help=\\\"Text file with r2 stats, from q30.py script.\\\")\\n\\tparser.add_argument(\\\"-n\\\", \\\"--name\\\", dest=\\\"name\\\", action=\\\"store\\\", required=True, help=\\\"Sample name\\\")\\n\\targs = parser.parse_args()\\n\\treturn args\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser(description='Arguments get parsed via --commands')\\n \\n parser.add_argument('-in', dest='input', type=str, \\n help=\\\"Specify the RTStruct file read.\\\")\\n parser.add_argument('--out', dest='output', type=str, default=\\\"RTSS_info.json\\\",\\n help=\\\"Specify the RTStruct file read.\\\")\\n \\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser()\\n argparse.ArgumentParser(argument_default=False)\\n parser.add_argument('-r', type=str, required=True, metavar='[reference.fa]', help=\\\"Reference file in fasta format\\\")\\n parser.add_argument('-s', type=int, metavar='number of SNPs', help=\\\"Number of SNPs to introduce\\\")\\n parser.add_argument('-i', type=int, metavar='number of indels', help=\\\"Number of small indels to introduce. Indel sizes randomly sampled between 1-100bp with a ratio of 9:1 for size being < 11bp\\\")\\n parser.add_argument('-d', type=int, metavar='number of large deletions', help=\\\"Number of large deletions to introduce. Deletion size randomly sampled between 100-5000bp\\\")\\n parser.add_argument('-t', type=int, metavar='number of translocations', help=\\\"number of translocations, regions will be randomly selected ranging between 500-5000bp in size\\\")\\n parser.add_argument('-nc', type=bool, default=False, metavar='add at least one non-conserved translocation', help=\\\"True/False add one non-conserved translocation. Deletion occurs from end of the translocation. Default=False\\\")\\n parser.add_argument('-f', type=str, required=True, metavar='output fasta filename', help=\\\"Output fasta filename and file path\\\")\\n parser.add_argument('-v', type=str, required=True, metavar='output vcf file of mutations', help=\\\"Output vcf filename and file path\\\")\\n\\n return parser.parse_args()\",\n \"def getOptions():\\n\\tdescription=\\\"\\\"\\\"This script takes an input fasta file of fusions and identifies all of the identical fusions.\\\"\\\"\\\"\\n\\tparser = argparse.ArgumentParser(description=description)\\n\\tparser.add_argument(\\\"-bowtie\\\", \\\"--bowtie_log_names\\\", dest=\\\"bowtie\\\", action='store', required=False, nargs = '*', help=\\\"bowtie log file names [Optional]\\\")\\n\\tparser.add_argument(\\\"-last\\\", \\\"--last_log_names\\\", dest=\\\"last\\\", action='store', required=False, help=\\\"LAST log file names [Optional]\\\")\\n\\tparser.add_argument(\\\"-treatment\\\",\\\"--treatment_name\\\",dest=\\\"treatment\\\",action='store',required=True,nargs= '*', help=\\\"Treatment variables [Required]\\\")\\n\\tparser.add_argument(\\\"-o\\\",\\\"--output_file\\\",dest=\\\"output\\\",action='store',required=True,help=\\\"Output file name [Required]\\\")\\n\\targs = parser.parse_args()\\n\\tif not args.bowtie and not args.last: #The user should give at least one bowtie or last log argument; otherwise the program does nothing\\n\\t parser.error('No input logs given; add -bowtie or -last')\\n\\treturn(args)\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument('--vec',\\n help='Name of the output file containing the positive'\\n ' samples for training.')\\n parser.add_argument('--pos',\\n help='Positive samples file name.', required=True)\\n parser.add_argument('--bg',\\n help='Background description file; contains a list of '\\n 'images which are used as a background for randomly '\\n 'distorted versions of the object.', required=True)\\n parser.add_argument('--num', type=int,\\n help='Number of positive samples to generate.',\\n required=True)\\n parser.add_argument('--bgcolor',\\n help='Background color (currently grayscale images are '\\n 'assumed); the background color denotes the transparent'\\n ' color. Since there might be artifacts, the'\\n ' amount of color tolerance can be specified by '\\n '-bgthresh. All pixels withing bgcolor-bgthresh and '\\n 'bgcolor+bgthresh range are interpreted as '\\n 'transparent. <0>')\\n parser.add_argument('--bgthresh',\\n help='Background color threshold.<80>')\\n parser.add_argument('--inv',\\n help='If specified, colors will be inverted.',\\n action='store_true')\\n parser.add_argument('--randinv',\\n help='If specified, colors will be inverted.',\\n action='store_true')\\n parser.add_argument('--out-img-folder',\\n help='Save all created images in a folder.')\\n parser.add_argument('--maxidev',\\n help='Maximal intensity deviation of pixels in '\\n 'foreground samples. <40>')\\n parser.add_argument('--maxzangle', type=float,\\n help='Maximum rotation in angle Z must be given in '\\n 'radians. <0.50000>')\\n parser.add_argument('--maxxangle', type=float,\\n help='Maximum rotation in angle X must be given in '\\n 'radians. <1.10000>')\\n parser.add_argument('--maxyangle', type=float,\\n help='Maximum rotation in angle Y must be given in '\\n 'radians. <1.10000>')\\n parser.add_argument('--height',\\n help='Height (in pixels) of the output samples. <24>',\\n default='24')\\n parser.add_argument('--width',\\n help='Width (in pixels) of the output samples. <24>',\\n default='24')\\n\\n return parser.parse_args()\",\n \"def process_arguments():\\n # Create ArgumentParser object. Description message will be displayed as part of help message if script is run with -h flag\\n parser = argparse.ArgumentParser(description='Prints tier 1 and 2 variant details to stdout for a given 100k case')\\n # Define the arguments that will be taken.\\n parser.add_argument('-i', '--ir_id', required=True, help='GeL Interpretation Request ID in format 12345-1')\\n parser.add_argument('-p', '--proband_id', required=True, help='GeL participant ID for proband')\\n # Return the arguments\\n return parser.parse_args()\",\n \"def parse_args():\\n parser = argparse.ArgumentParser(\\n description=\\\"Trim spaces at the end of every lines.\\\"\\n )\\n parser.add_argument(\\\"-R\\\", \\\"-r\\\", action=\\\"store_true\\\", help=\\\"Whether to recursive\\\")\\n parser.add_argument(\\\"-y\\\", \\\"--yes\\\", action=\\\"store_true\\\", help=\\\"No ask\\\")\\n parser.add_argument(\\n \\\"-t\\\", \\\"--type\\\", default=\\\"*\\\", help=\\\"Filter file type(Example: *.py)\\\"\\n )\\n parser.add_argument(\\\"-d\\\", \\\"--dir\\\", default=\\\"\\\", help=\\\"The directory path\\\")\\n parser.add_argument(\\n \\\"files\\\",\\n nargs=\\\"+\\\",\\n default=[],\\n metavar=\\\"*.py\\\",\\n help=\\\"files or directories\\\",\\n )\\n return parser.parse_args()\",\n \"def parse_arguments():\\n parser = argparse.ArgumentParser()\\n parser.add_argument(\\n \\\"--obs_len\\\",\\n default=20,\\n type=int,\\n help=\\\"Directory where the sequences (csv files) are saved\\\",\\n )\\n parser.add_argument(\\n \\\"--data_dir\\\",\\n default=\\\"\\\",\\n type=str,\\n help=\\\"Directory where the sequences (csv files) are saved\\\",\\n )\\n parser.add_argument(\\n \\\"--feature_dir\\\",\\n default=\\\"\\\",\\n type=str,\\n help=\\\"Directory where the computed features are saved\\\",\\n )\\n parser.add_argument(\\\"--mode\\\",\\n required=True,\\n type=str,\\n help=\\\"train/val/test/compute_all/lanes_only\\\")\\n parser.add_argument(\\n \\\"--sequence_num\\\",\\n default=-1,\\n type=int,\\n help=\\\"Specify a specific sequence to visualize.\\\",\\n )\\n parser.add_argument(\\n \\\"--batch_start\\\",\\n default=0,\\n type=int,\\n help=\\\"Specify the starting row of features to visualize.\\\",\\n )\\n parser.add_argument(\\n \\\"--batch_end\\\",\\n default=-1,\\n type=int,\\n help=\\\"Specify the last row to visualize, -1 to visualize till end.\\\",\\n )\\n parser.add_argument(\\n \\\"--single_figure\\\",\\n default=False,\\n action=\\\"store_true\\\",\\n help=\\\"Plot all candidates for a scenein one figure.\\\",\\n )\\n return parser.parse_args()\",\n \"def parse_arguments():\\n p = argparse.ArgumentParser(description='Prepare the dataset for use by neural models.')\\n p.add_argument(\\\"json_file\\\", type=argparse.FileType('r'), help=\\\"json file with all the data\\\")\\n p.add_argument(\\\"prefix\\\", type=str, help=\\\"prefix for all the generated files\\\")\\n p.add_argument(\\\"data_type\\\", type=str, choices=[\\\"names\\\", \\\"comments\\\", \\\"nc\\\"],\\n default=\\\"nc\\\", help=\\\"type of the information recorded in the dataset\\\")\\n p.add_argument(\\\"labels\\\", type=str, choices=[\\\"PROG\\\", \\\"ALL\\\", \\\"TOP\\\"],\\n default=\\\"PROG\\\", help=\\\"method by which to choose the labels for the dataset\\\")\\n p.add_argument(\\\"-other_label\\\", type=str, required=False, default=\\\"\\\",\\n help=\\\"label to use instead of all infrequent labels. \\\"\\n \\\"This can be left blank to ignore infrequent labels altogether\\\")\\n p.add_argument(\\\"-label_num\\\", type=int, default=100, required=False,\\n help=\\\"Number of most frequent labels to keep. Works with label_choice=TOP\\\")\\n p.add_argument(\\\"-min_prog_labels\\\", type=int, default=5, required=False,\\n help=\\\"Minimal number of programs a label has to appear in for it to be included \\\"\\n \\\"in the dataset. Works with label_choice=PROG\\\")\\n p.add_argument(\\\"-test_prog_list\\\", type=argparse.FileType('r'), default=None, required=False,\\n help=\\\"file with the list of programs in the test set (optional)\\\")\\n\\n return p.parse_args(sys.argv[1:])\",\n \"def setup_cmd_args():\\n parser = argparse.ArgumentParser(description=\\\"Translate XLS files to appropriate XML format for ingestion in FEDEO.\\\", formatter_class=argparse.ArgumentDefaultsHelpFormatter)\\n parser.add_argument(\\\"xlsfile\\\", help=\\\"The XLS file to parse\\\")\\n parser.add_argument('-outputdir', help=\\\"directory to output the XML file\\\", default='output')\\n parser.add_argument('-j', action='store_true', help=\\\"Also export JSON file\\\")\\n parser.add_argument('-p', action='store_true', help=\\\"Pretty print XML file\\\")\\n parser.add_argument('-o', action='store_true', help=\\\"Overwrite output XML file\\\")\\n parser.add_argument('-l', action='store_true', help=\\\"Skip I_G_LN as mandatory field\\\", default=False)\\n return parser.parse_args()\",\n \"def parse_commandlineargs():\\n\\n parser = argparse.ArgumentParser(\\n description='Perform generic fitting operations on Multinomial' +\\n 'Processing Trees (MPTs).')\\n\\n # Mandatory arguments\\n parser.add_argument(\\n 'model_path',\\n metavar='model',\\n type=str,\\n help='Path to the MPT model specification file.')\\n\\n parser.add_argument(\\n 'data_path',\\n metavar='data',\\n type=str,\\n help='Path to the data file in CSV format.')\\n\\n # Optional arguments\\n n_default = 10\\n parser.add_argument(\\n '-n',\\n '--n_optim',\\n metavar='N',\\n type=int,\\n default=n_default,\\n help='Number of fitting repetitions to evade local maxima. (Default={})'.\\n format(n_default))\\n\\n s_default = ','\\n parser.add_argument(\\n '-s',\\n '--sep',\\n metavar='S',\\n type=str,\\n default=s_default,\\n help=\\\"Data table column separator. (Default='{}')\\\".format(s_default))\\n\\n parser.add_argument(\\n '--header',\\n action='store_true',\\n help=\\\"Is the first not-commented line a header?\\\")\\n\\n parser.add_argument(\\n '--llik',\\n action='store_true'\\n )\\n\\n parser.add_argument(\\n '-i',\\n '--ignore',\\n type=str,\\n nargs='+',\\n help='Set of Parameter names which are not to be modified, ALL for all \\\\\\n parameters'\\n )\\n\\n args = parser.parse_args()\\n return vars(args)\",\n \"def parse_options():\\r\\n # Get options\\r\\n options = get_options()\\r\\n (opts, args) = options.parse_args()\\r\\n\\r\\n # The meta will store all information about the arguments passed #\\r\\n meta = {\\r\\n 'casename': opts.casename,\\r\\n 'reportqueries': opts.report_queries,\\r\\n 'sourcetype': opts.sourcetype,\\r\\n 'source': opts.source,\\r\\n 'outdir': opts.outdir\\r\\n }\\r\\n\\r\\n # Print help if no options are provided\\r\\n if len(sys.argv[1:]) == 0:\\r\\n options.print_help()\\r\\n sys.exit(1)\\r\\n # Test required arguments\\r\\n if meta['source'] is False or meta['outdir'] is False or meta['sourcetype'] is False:\\r\\n options.error('Unable to proceed. The following parameters '\\r\\n 'are required:\\\\n-s SOURCE\\\\n-o OUTDIR\\\\n-t SOURCETYPE')\\r\\n\\r\\n if not os.path.exists(meta['source']):\\r\\n options.error(\\\"Unable to proceed. \\\\n\\\\n%s does not exist.\\\\n\\\" % meta['source'])\\r\\n\\r\\n if not os.path.exists(meta['outdir']):\\r\\n options.error(\\\"Unable to proceed. \\\\n\\\\n%s does not exist.\\\\n\\\" % meta['outdir'])\\r\\n \\r\\n if meta['reportqueries'] and not os.path.exists(meta['reportqueries']):\\r\\n options.error(\\\"Unable to proceed. \\\\n\\\\n%s does not exist.\\\\n\\\" % meta['reportqueries'])\\r\\n\\r\\n if meta['sourcetype'].lower() != 'folder' and meta['sourcetype'].lower() != 'image':\\r\\n options.error(\\r\\n 'Unable to proceed. \\\\n\\\\nIncorrect source type provided: \\\"%s\\\". The following are valid options:\\\\\\r\\n \\\\n -t folder\\\\n -t image\\\\n' % (meta['sourcetype']))\\r\\n\\r\\n if meta['sourcetype'] == 'image' and DFVFS_IMPORT is False:\\r\\n options.error(IMPORT_ERROR)\\r\\n\\r\\n if meta['reportqueries'] ==False:\\r\\n print('[Info]: Report queries file not specified using the -q option. Custom reports will not be generated.')\\r\\n \\r\\n if meta['casename'] is False:\\r\\n print('[Info]: No casename specified using -c. Defaulting to \\\"FSE_Reports\\\".')\\r\\n meta['casename'] = 'FSE_Reports'\\r\\n\\r\\n # Return meta to caller #\\r\\n return meta\",\n \"def parse_args(arglist):\\n help = dedent(\\\"\\\"\\\"\\n Run FIR model on subject data\\n \\\"\\\"\\\")\\n parser = tools.parser\\n parser.description = help\\n parser.formatter_class = argparse.RawDescriptionHelpFormatter\\n parser.add_argument(\\\"-extract_info\\\", help=\\\"info for experiment to extract\\\")\\n parser.add_argument(\\\"-mask_type\\\", help=\\\"mask or func?\\\")\\n parser.add_argument(\\\"-mask_name\\\", help=\\\"name of mask in sub's mask directory\\\")\\n return parser.parse_args(arglist)\",\n \"def setup_args():\\n parser = ParlaiParser()\\n parser.add_argument(\\n '-n',\\n '--num-episodes',\\n default=-1,\\n type=int,\\n help='Total number of episodes to convert, -1 to convert all examples',\\n )\\n parser.add_argument(\\n '-of',\\n '--outfile',\\n default=None,\\n type=str,\\n help='Output file where to save, by default will be created in /tmp',\\n )\\n parser.add_argument(\\n '-s1id', '--speaker-0-id', type=str, help='Speaker id of agent who speaks first'\\n )\\n parser.add_argument(\\n '-s1id',\\n '--speaker-1-id',\\n type=str,\\n help='Speaker id of agent who speaks second',\\n )\\n parser.add_argument(\\n '--prepended-context',\\n type='bool',\\n default=False,\\n help='specify if the context is prepended to the first act',\\n )\\n parser.add_argument('-ltim', '--log-every-n-secs', type=float, default=10)\\n parser.set_defaults(datatype='train:ordered')\\n\\n return parser\",\n \"def parse_args():\\n parser = ArgumentParser(description='Count lines.')\\n\\n parser.add_argument(\\n 'path',\\n metavar='PATH')\\n\\n parser.add_argument(\\n 'patterns',\\n metavar='PATTERN',\\n nargs='*')\\n\\n parser.add_argument(\\n '-a', '--absolute',\\n dest='absolute',\\n action='store_true',\\n help='show absolute paths in details (overrides `-r`)')\\n\\n parser.add_argument(\\n '-d', '--details',\\n dest='details',\\n action='store_true',\\n help='show details for each file')\\n\\n parser.add_argument(\\n '-r', '--relative',\\n dest='relative',\\n action='store_true',\\n help='show relative paths in details')\\n\\n return parser.parse_args()\",\n \"def _init_argparser():\\n desc = 'SES status and metrics reporting utility (part of sasutils).'\\n parser = argparse.ArgumentParser(description=desc)\\n parser.add_argument('-d', '--debug', action=\\\"store_true\\\",\\n help='enable debugging')\\n\\n group = parser.add_mutually_exclusive_group(required=True)\\n group.add_argument('-c', '--carbon', action='store_true',\\n help='output SES Element descriptors metrics in a '\\n 'format suitable for Carbon/Graphite')\\n group.add_argument('-s', '--status', action='store_true',\\n help='output status found in SES Element descriptors')\\n\\n group = parser.add_argument_group('output options')\\n group.add_argument('--prefix', action='store',\\n default='sasutils.ses_report',\\n help='carbon prefix (example: \\\"datacenter.cluster\\\",'\\n ' default is \\\"sasutils.ses_report\\\")')\\n group.add_argument('-j', '--json', action='store_true',\\n help='alternative JSON output mode')\\n return parser.parse_args()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6712574","0.6688427","0.66874635","0.66772443","0.66594255","0.6603691","0.6600838","0.6586496","0.6582369","0.6565811","0.65460694","0.65405774","0.65191436","0.6493583","0.6438784","0.64371055","0.6433585","0.6426523","0.6417857","0.6408057","0.64075786","0.6404059","0.6398166","0.6385624","0.6384458","0.6380815","0.63714194","0.63705474","0.6367784","0.6351767","0.6350656","0.634793","0.6344758","0.63323283","0.6320142","0.63136137","0.63113207","0.6309821","0.63076025","0.63036805","0.630072","0.62977344","0.6295755","0.6293911","0.62927854","0.6290217","0.62740695","0.62735647","0.6269655","0.6268894","0.6267389","0.624759","0.6246597","0.624395","0.6238059","0.623709","0.6234926","0.6234444","0.6230609","0.62258214","0.62208277","0.6216605","0.62133306","0.6209648","0.6209437","0.620907","0.62076217","0.6202426","0.6202116","0.62019145","0.62000066","0.6197133","0.61968184","0.617985","0.6179344","0.61740476","0.6172929","0.6167605","0.6166746","0.61648387","0.6164835","0.61630344","0.6161777","0.61601835","0.61583686","0.6153565","0.6153507","0.61522275","0.6151456","0.6149973","0.6149932","0.6147062","0.6144224","0.6134519","0.6133343","0.6129983","0.6129166","0.61277336","0.6124111","0.61229575","0.6120724"],"string":"[\n \"0.6712574\",\n \"0.6688427\",\n \"0.66874635\",\n \"0.66772443\",\n \"0.66594255\",\n \"0.6603691\",\n \"0.6600838\",\n \"0.6586496\",\n \"0.6582369\",\n \"0.6565811\",\n \"0.65460694\",\n \"0.65405774\",\n \"0.65191436\",\n \"0.6493583\",\n \"0.6438784\",\n \"0.64371055\",\n \"0.6433585\",\n \"0.6426523\",\n \"0.6417857\",\n \"0.6408057\",\n \"0.64075786\",\n \"0.6404059\",\n \"0.6398166\",\n \"0.6385624\",\n \"0.6384458\",\n \"0.6380815\",\n \"0.63714194\",\n \"0.63705474\",\n \"0.6367784\",\n \"0.6351767\",\n \"0.6350656\",\n \"0.634793\",\n \"0.6344758\",\n \"0.63323283\",\n \"0.6320142\",\n \"0.63136137\",\n \"0.63113207\",\n \"0.6309821\",\n \"0.63076025\",\n \"0.63036805\",\n \"0.630072\",\n \"0.62977344\",\n \"0.6295755\",\n \"0.6293911\",\n \"0.62927854\",\n \"0.6290217\",\n \"0.62740695\",\n \"0.62735647\",\n \"0.6269655\",\n \"0.6268894\",\n \"0.6267389\",\n \"0.624759\",\n \"0.6246597\",\n \"0.624395\",\n \"0.6238059\",\n \"0.623709\",\n \"0.6234926\",\n \"0.6234444\",\n \"0.6230609\",\n \"0.62258214\",\n \"0.62208277\",\n \"0.6216605\",\n \"0.62133306\",\n \"0.6209648\",\n \"0.6209437\",\n \"0.620907\",\n \"0.62076217\",\n \"0.6202426\",\n \"0.6202116\",\n \"0.62019145\",\n \"0.62000066\",\n \"0.6197133\",\n \"0.61968184\",\n \"0.617985\",\n \"0.6179344\",\n \"0.61740476\",\n \"0.6172929\",\n \"0.6167605\",\n \"0.6166746\",\n \"0.61648387\",\n \"0.6164835\",\n \"0.61630344\",\n \"0.6161777\",\n \"0.61601835\",\n \"0.61583686\",\n \"0.6153565\",\n \"0.6153507\",\n \"0.61522275\",\n \"0.6151456\",\n \"0.6149973\",\n \"0.6149932\",\n \"0.6147062\",\n \"0.6144224\",\n \"0.6134519\",\n \"0.6133343\",\n \"0.6129983\",\n \"0.6129166\",\n \"0.61277336\",\n \"0.6124111\",\n \"0.61229575\",\n \"0.6120724\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13092,"cells":{"query":{"kind":"string","value":"Trigger the recompute of the taxes if the pricelist is changed on the invoice."},"document":{"kind":"string","value":"def _compute_tax_id(self):\n for inv in self:\n for line in inv.invoice_line_ids:\n line.tax_ids = line._get_computed_taxes()\n\n inv._recompute_dynamic_lines(recompute_all_taxes=True, recompute_tax_base_amount=True)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _compute_taxed_lst_price2(self):\n company_id = self._context.get(\n 'company_id', self.env.user.company_id.id)\n for product in self:\n product.taxed_lst_price = product.taxes_id.filtered(\n lambda x: x.company_id.id == company_id).compute_all(\n product.lst_price,\n self.env.user.company_id.currency_id,\n product=product)['total_included']","def _compute_taxed_lst_price2(self):\n company_id = self._context.get(\n 'company_id', self.env.user.company_id.id)\n for product in self:\n product.taxed_lst_price2 = product.taxes_id.filtered(\n lambda x: x.company_id.id == company_id).compute_all(\n product.list_price2,\n self.env.user.company_id.currency_id,\n product=product)['total_included']","def _compute_tax(self):\n for line in self:\n line.tax = (line.amount_untaxed * 14) / 100","def _compute_amount(self):\n for line in self:\n price = line.price_unit * (1 - (line.discount or 0.0) / 100.0)\n new_price = price\n if line.lot_id and line.product_id.tracking in ['lot','serial']:\n lot_id = self.env['stock.production.lot'].search([('name', '=', line.lot_id), ('product_id', '=', line.product_id.id)])\n if lot_id.tax_ids.filtered(lambda tax: tax.amount_type == 'based_on_margin'):\n if lot_id.cost_price:\n new_price -= lot_id.cost_price\n sh_tax = line.tax_id.filtered(lambda tax: tax.amount_type =='based_on_margin').compute_all(new_price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\n taxes = line.tax_id.filtered(lambda tax: tax.amount_type !='based_on_margin').compute_all(price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\n print(taxes)\n line.update({\n 'price_tax': sum(t.get('amount', 0.0) for t in taxes.get('taxes', [])) + sum(t.get('amount', 0.0) for t in sh_tax.get('taxes', [])),\n 'price_total': taxes['total_included'],\n 'price_subtotal': taxes['total_excluded'],\n })\n if self.env.context.get('import_file', False) and not self.env.user.user_has_groups('account.group_account_manager'):\n line.tax_id.invalidate_cache(['invoice_repartition_line_ids'], [line.tax_id.id])","def _onchange_price(self):\n self.price_subtotal = self.price","def _onchange_price_subtotal(self):\n self.price = self.price_subtotal","def pay_tax(self):\n\t\t# the money comes from nowhere, settlers seem to have an infinite amount of money.\n\t\t# see http://wiki.unknown-horizons.org/index.php/DD/Economy/Settler_taxing\n\t\thappiness_tax_modifier = (float(self.happiness)-50)/200 + 1\n\t\ttaxes = self.tax_base * happiness_tax_modifier * self.inhabitants * self.settlement.tax_setting\n\t\ttaxes = int(round(taxes))\n\t\tself.settlement.owner.inventory.alter(RES.GOLD_ID, taxes)\n\t\tself.last_tax_payed = taxes\n\n\t\t# decrease happiness\n\t\thappiness_decrease = taxes + self.tax_base + ((self.settlement.tax_setting-1)*10)\n\t\thappiness_decrease = int(round(happiness_decrease))\n\t\tself.inventory.alter(RES.HAPPINESS_ID, -happiness_decrease)\n\t\tself._changed()\n\t\tself.log.debug(\"%s: pays %s taxes, -happy: %s new happiness: %s\", self, taxes, \\\n\t\t\t\t\t\t\t\t\t happiness_decrease, self.happiness)","def test_client_tax_information_update(self):\n pass","def on_taxes_change(origin_matrix, changes_on_taxes):\n new_taxes = origin_matrix[TAXES_IDX]\n for idx in range(len(origin_matrix[0])):\n if changes_on_taxes[idx] != None:\n new_taxes[idx] = changes_on_taxes[idx]\n return new_taxes","def price_incl_tax(self, price_incl_tax):\n\n self._price_incl_tax = price_incl_tax","def check_for_energy_tax_update(self):\n\t\tisChanged = False\n\t\t# TODO: discuss the validity of such approach when checking on the global optimality\n\t\t# if self.currentEnergy < self._globalMinimumEnergy and self.currentTax == 0:\n\t\tif self.currentEnergy < self._globalMinimumEnergy and self.contains_several_vertices(self.currentState):\n\t\t\toutput(\"\\t New global optimum registered: old value = {}, new value = {}, state = {}\"\\\n\t\t\t\t\t .format(str(self._globalMinimumEnergy),str(self.currentEnergy),self.getCurrentState()),isDebug=False)\n\t\t\tself._globalMinimumEnergy = self.currentEnergy\n\t\t\tself._globalMinimumState = copy(self.currentState)\n\t\t\tisChanged = True\n\t\tif self.currentEnergy < self.localMinimumEnergy and not self.isAllZeros(self.currentState): #should we update global as well? Now I do it\n\t\t\toutput(\"\\t New local optimum registered: old value = {}, new value = {}, state = {}\"\\\n\t\t\t\t\t .format(self.localMinimumEnergy,self.currentEnergy,self.getCurrentState()),isDebug=False)\n\t\t\tself.localMinimumEnergy = self.currentEnergy\n\t\t\tself.localMinimumState = copy(self.currentState)\n\t\t\tself.localMinimumTax = self.currentTax\n\t\t\tisChanged = True\n\t\treturn isChanged","def compute_all(self, price_unit, currency=None, quantity=1.0, product=None, partner=None, margin=0.0):\n\n non_margin_taxes = self.filtered(lambda t: not t.on_margin)\n\n result = super(AccountTax, non_margin_taxes).compute_all(\n price_unit,\n currency=currency,\n quantity=quantity,\n product=product,\n partner=partner\n )\n\n margin_taxes = self - non_margin_taxes\n if not margin_taxes:\n return result\n\n if len(self) == 0:\n company_id = self.env.user.company_id\n else:\n company_id = self[0].company_id\n\n if not currency:\n currency = company_id.currency_id\n\n prec = currency.decimal_places\n\n round_tax = False if company_id.tax_calculation_rounding_method == 'round_globally' else True\n if 'round' in self.env.context:\n round_tax = bool(self.env.context['round'])\n\n if not round_tax:\n prec += 5\n\n for tax in margin_taxes:\n\n tax_amount = tax._compute_amount(\n margin,\n price_unit,\n quantity=quantity,\n product=product,\n partner=partner\n )\n if not round_tax:\n tax_amount = round(tax_amount, prec)\n else:\n tax_amount = currency.round(tax_amount)\n\n result['taxes'].append({\n 'id': tax.id,\n 'name': tax.with_context(**{'lang': partner.lang} if partner else {}).name,\n 'amount': tax_amount,\n 'base': margin,\n 'on_margin': True,\n 'sequence': tax.sequence,\n 'account_id': tax.account_id.id,\n 'refund_account_id': tax.refund_account_id.id,\n 'analytic': tax.analytic,\n 'price_include': tax.price_include,\n 'tax_exigibility': tax.tax_exigibility\n })\n\n return result","def update_totals(self, commit=False):\n sub_total = 0.0\n tax = 0.0\n for item in self.invoice_items:\n sub_total += float(item.total if item.total else 0)\n tax += float(item.tax if item.tax else 0)\n\n self.tax = tax\n self.sub_total = sub_total\n self.total = float(self.tax) + float(self.sub_total)\n\n if commit:\n db.session.add(self)\n db.session.commit()\n return True","def count_taxes(self):\n\t\tfor i in range (self._size):\n\t\t\ttmpState = copy(self.currentState)\n\t\t\ttmpState[i] = 1 - tmpState[i]\n\t\t\tself._taxes[i] = self.count_tax(state=tmpState)","def _tick(self):\n\t\tself.pay_tax()\n\t\tself.inhabitant_check()\n\t\tself.level_check()","def change_price(self, value): \n value = self.price","def save_tax(request):\n if request.method == \"POST\":\n initial_data, data = process_request(request)\n return render(request,\n \"invoice/invoice_create.html\",\n {\n \"form\": InvoiceForm,\n \"stage\": \"3\",\n \"prev_data\": data,\n \"initial_data\": initial_data\n })","def action_update_total(self):\n for order in self:\n amount_untaxed = 0.0\n for line in order.order_line_ids:\n amount_untaxed += line.price_subtotal\n order.price_subtotal = amount_untaxed","def update_taxes(origin_matrix, tax_percent_fees, tax_percent_interest):\n new_taxes = np.zeros(len(origin_matrix[0]))\n fees_paid = origin_matrix[FEES_IDX]\n interest_paid_arr = origin_matrix[INTEREST_PAID_IDX]\n taxes_on_fee = fees_paid * tax_percent_fees\n taxes_on_interest = interest_paid_arr * tax_percent_interest\n new_taxes = taxes_on_fee + taxes_on_interest\n return new_taxes","def test_client_tax_information_partial_update(self):\n pass","def onchange_on_margin(self):\n\n for tax in self:\n\n tax.amount_type = 'margin' if tax.on_margin else 'percent'\n tax.price_include = tax.on_margin\n tax.type_tax_use = 'sale' if tax.on_margin else 'none'\n\n if tax.on_margin:\n tax.include_base_amount = False","def base_price_incl_tax(self, base_price_incl_tax):\n\n self._base_price_incl_tax = base_price_incl_tax","def m_ps_FieldsUpdated(self, sender, e):\r\n ltp = e.Fields.GetLastTradedPriceField()\r\n ltq = e.Fields.GetLastTradedQuantityField()\r\n print(\"ltp and ltq success...\")\r\n if ltp.HasChanged or ltq.HasChanged:\r\n print(ltp.Value, ltq.Value)\r\n ltp = ltp.Value\r\n ltpi = int(ltp.ToTicks())\r\n self.process_row({'time' :pd.datetime.now(), 'close' : ltpi}, key = \"nk\")","def _compute_tax_id(self):\n for order in self:\n order.order_line._compute_tax_id()","def calculate_taxes(self, proforma, technologies):\n tax_calcs = copy.deepcopy(proforma)\n # 1) Redistribute capital cost according to the DER's MACRS value to get depreciation\n for der_inst in technologies:\n tax_contribution = der_inst.tax_contribution(self.macrs_depreciation,\n tax_calcs.index, self.start_year)\n if tax_contribution is not None:\n tax_calcs = pd.concat([tax_calcs, tax_contribution], axis=1)\n # 2) calculate yearly_net (taking into account the taxable contribution of each technology\n # asset)\n yearly_net = tax_calcs.sum(axis=1)\n tax_calcs['Taxable Yearly Net'] = yearly_net\n\n # 3) Calculate State tax based on the net cash flows in each year\n tax_calcs['State Tax Burden'] = yearly_net * -self.state_tax_rate\n\n # 4) Calculate Federal tax based on the net cash flow in each year minus State taxes\n # from that year\n yearly_net_post_state_tax = yearly_net + tax_calcs['State Tax Burden']\n tax_calcs['Federal Tax Burden'] = yearly_net_post_state_tax * -self.federal_tax_rate\n\n # 5) Add the overall tax burden (= state tax + federal tax) to proforma\n tax_calcs['Overall Tax Burden'] = tax_calcs['State Tax Burden'] + tax_calcs['Federal Tax Burden']\n proforma['State Tax Burden'] = tax_calcs['State Tax Burden']\n proforma['Federal Tax Burden'] = tax_calcs['Federal Tax Burden']\n proforma['Overall Tax Burden'] = tax_calcs['Overall Tax Burden']\n self.tax_calculations = tax_calcs\n return proforma","def after_tax_profit(self):\n _after_tax_profit = self.before_tax_profit() * (1 - self.tax_rate)\n return _after_tax_profit","def apply_tax(order_obj):\n tax_rule = taxes.get()\n all_credits = order_obj.credits\n other_credit = filter(lambda x: x[\"coll_name\"] != taxes.TaxRule.coll_name(), all_credits)\n\n if tax_rule is not None:\n order_obj.credits = other_credit + [{\n \"obj_id\": tax_rule._id,\n \"coll_name\": taxes.TaxRule.coll_name(),\n \"amount\": taxes.amount(tax_rule, order_obj),\n }]\n else:\n order_obj.credits = other_credit","def calculate_and_save(self):\n # Calculate the quotation price\n self.quotationPrice = self.compute_quotation_price()\n self.save()","def _compute_amount(self):\n for line in self:\n price = line.price_unit * (1 - (line.discount or 0.0) / 100.0)\n taxes = line.tax_id.compute_all(price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\n line.update({\n 'price_tax': sum(t.get('amount', 0.0) for t in taxes.get('taxes', [])),\n 'price_total': taxes['total_included'],\n 'price_subtotal': taxes['total_excluded'],\n })\n if(line.is_discount_allow and line.price_subtotal > 100):\n line.price_subtotal = line.price_subtotal - 100","def _compute_amount(self):\n for line in self:\n price = line.price_unit\n taxes = line.tax_id.compute_all(price, line.order_id.currency_id, line.product_uom_qty,\n product=line.product_id, partner=line.order_id.partner_shipping_id)\n self_price_subtotal = taxes['total_excluded']\n if not line.discount_fixed_percent:\n self_price_subtotal = self_price_subtotal\n if line.discount_fixed_percent == 'Percent':\n self_price_subtotal = self_price_subtotal * (1 - (line.discount or 0.0) / 100.0)\n if line.discount_fixed_percent == 'Fixed':\n self_price_subtotal = self_price_subtotal - line.discount_value\n line.update({\n 'price_tax': sum(t.get('amount', 0.0) for t in taxes.get('taxes', [])),\n 'price_total': taxes['total_included'],\n 'price_subtotal': self_price_subtotal,\n })","def default_get(self, cr, uid, fields_list, context=None):\n\t\tif context is None:\n\t\t\tcontext = {}\n\t\tdate_start = datetime.date.today().strftime('%Y-01-01')\n\t\tdate_end = datetime.date.today().strftime('%Y-%m-%d')\n\n\t\tvalues = super(wizard_add_taxes, self).default_get(cr, uid, fields_list, context=context)\n\t\ttax_ids = []\n\t\tif (context.get('active_id',False)):\n\t\t\ttax_payment = self.pool.get('account.tax.payment').browse(cr,uid,context.get('active_id',False))\n\t\t\tcompany_id = tax_payment.company_id and tax_payment.company_id.id or False\n\t\t\ttax_ids = [t.id for t in tax_payment.tax_type]\n\t\t\tdate_end = tax_payment.date_end\n\t\telse:\n\t\t\tuser = self.pool.get('res.users').browse(cr,uid,uid,context)\n\t\t\tcompany_id = user.company_id and user.company_id.id or False\n\t\t\ttax_ids=self.pool.get('account.tax').search(cr,uid,[('company_id','=',company_id)],context=context)\n\t\ttax_account_ids=[]\n\t\ttax_not_returned=[]\n\t\ttax_code_account_ids = []\n\t\ttax_code_unreturned = []\n\t\tfor tax in self.pool.get('account.tax').browse(cr,uid,tax_ids,context):\n\t\t\tif not tax.inside_berikat and not tax.reported_unreturned:\n\t\t\t\tif tax.account_collected_id and tax.account_collected_id.id:\n\t\t\t\t\ttax_account_ids.append(tax.account_collected_id.id)\n\t\t\t\tif tax.account_paid_id and tax.account_paid_id.id:\n\t\t\t\t\ttax_account_ids.append(tax.account_paid_id and tax.account_paid_id.id)\n\t\t\t\tif tax.tax_code_id and tax.tax_code_id.id:\n\t\t\t\t\ttax_code_account_ids.append(tax.tax_code_id.id)\n\t\t\t\tif tax.ref_tax_code_id and tax.ref_tax_code_id.id:\n\t\t\t\t\ttax_code_account_ids.append(tax.ref_tax_code_id.id)\n\t\t\telse:\n\t\t\t\tif tax.account_collected_id and tax.account_collected_id.id:\n\t\t\t\t\ttax_not_returned.append(tax.account_collected_id and tax.account_collected_id.id)\n\t\t\t\tif tax.account_paid_id and tax.account_paid_id.id:\n\t\t\t\t\ttax_not_returned.append(tax.account_paid_id and tax.account_paid_id.id)\n\t\t\t\tif tax.tax_code_id and tax.tax_code_id.id:\n\t\t\t\t\ttax_code_unreturned.append(tax.tax_code_id and tax.tax_code_id.id)\n\t\t\t\tif tax.ref_tax_code_id and tax.ref_tax_code_id.id:\n\t\t\t\t\ttax_code_unreturned.append(tax.ref_tax_code_id and tax.ref_tax_code_id.id)\n\t\t\t\t#print \"tax_not_returned==============\",tax_not_returned\n\t\ttax_account_ids = list(set(tax_account_ids))\n\t\ttax_not_returned = list(set(tax_not_returned))\n\t\ttax_code_account_ids = list(set(tax_code_account_ids))\n\t\ttax_code_unreturned = list(set(tax_code_unreturned))\n\t\tcompany = self.pool.get('res.company').browse(cr,uid,company_id,context)\n\t\tif tax_account_ids or tax_not_returned:\n\t\t\tmove_id = self.pool.get('account.move').search(cr,uid,[('state','=','posted'),('date',\">=\",date_start),('date',\"<=\",date_end)])\n\t\t\texisting_payment_line_ids = self.pool.get('account.tax.payment.line').search(cr,uid,[],context=context)\n\t\t\texisting_payment_lines = [epm.move_line_id.id for epm in self.pool.get('account.tax.payment.line').browse(cr,uid,existing_payment_line_ids)]\n\t\t\texisting_statement_ids = self.pool.get('account.tax.payment').search(cr,uid,[],context=context)\n\t\t\texisting_statements_move = [esm.move_id.id for esm in self.pool.get('account.tax.payment').browse(cr,uid,existing_statement_ids)]\n\t\t\texisting_statement_move_lines = self.pool.get('account.move.line').search(cr,uid,[('move_id','in',existing_statements_move)])\n\t\t\texisting_payment_lines += existing_statement_move_lines\n\n\n\t\ttax_lines_value=[]\n\n\n\t\tif context.get('type',False) == 'tax_lines_cr':\n\t\t\tmove_lines = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\n\t\t\t\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_account_ids),('account_id','in',tax_account_ids),\\\n\t\t\t\t('state','=','valid'),('move_id','in',move_id),('debit','=',0.0),('credit',\">=\",0.0)])\n\t\t\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines,context=context):\n\t\t\t\tmoves = line.move_id\n\t\t\t\tinvoice_id=False\n\t\t\t\tfor move_line in line.move_id.line_id:\n\t\t\t\t\tif move_line.invoice and move_line.invoice.id:\n\t\t\t\t\t\tinvoice_id=move_line.invoice.id\n\t\t\t\ttax_lines={\n\t\t\t\t\t\"name\"\t\t\t\t: line.name or line.ref or '/',\n\t\t\t\t\t\"move_line_id\"\t\t: line.id,\n\t\t\t\t\t\"invoice_id\"\t\t: invoice_id,\n\t\t\t\t\t\"amount\"\t\t\t: line.debit or line.credit or 0.0,\n\t\t\t\t\t\"currency_id\"\t\t: line.currency_id and line.currency_id.id or False,\n\t\t\t\t\t\"amount_currency\"\t: line.amount_currency or 0.0,\n\t\t\t\t\t\"effective_date\"\t: line.date or False,\n\t\t\t\t\t\"partner_id\"\t\t: line.partner_id and line.partner_id.id or False,\n\t\t\t\t\t}\n\t\t\t\ttax_lines_value.append(tax_lines)\n\t\telif context.get('type',False) == 'tax_lines_dr':\n\t\t\tmove_lines = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\n\t\t\t\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_account_ids),('account_id','in',tax_account_ids),\\\n\t\t\t\t('state','=','valid'),('move_id','in',move_id),('debit','>=',0.0),('credit',\"=\",0.0)])\n\n\t\t\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines,context=context):\n\t\t\t\tmoves = line.move_id\n\t\t\t\tinvoice_id=False\n\t\t\t\tfor move_line in line.move_id.line_id:\n\t\t\t\t\tif move_line.invoice and move_line.invoice.id:\n\t\t\t\t\t\tinvoice_id=move_line.invoice.id\n\t\t\t\ttax_lines={\n\t\t\t\t\t\"name\"\t\t\t\t: line.name or line.ref or '/',\n\t\t\t\t\t\"move_line_id\"\t\t: line.id,\n\t\t\t\t\t\"invoice_id\"\t\t: invoice_id,\n\t\t\t\t\t\"amount\"\t\t\t: line.debit or line.credit or 0.0,\n\t\t\t\t\t\"currency_id\"\t\t: line.currency_id and line.currency_id.id or False,\n\t\t\t\t\t\"amount_currency\"\t: line.amount_currency or 0.0,\n\t\t\t\t\t\"effective_date\"\t: line.date or False,\n\t\t\t\t\t\"partner_id\"\t\t: line.partner_id and line.partner_id.id or False,\n\t\t\t\t\t}\n\t\t\t\ttax_lines_value.append(tax_lines)\n\t\telif context.get('type',False) == 'tax_lines_cr_unr':\n\t\t\tmove_lines_unreturned = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\n\t\t\t\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_unreturned),('account_id','in',tax_not_returned),\\\n\t\t\t\t('state','=','valid'),('move_id','in',move_id),('debit','=',0.0),('credit',\">=\",0.0)])\n\t\t\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines_unreturned,context=context):\n\t\t\t\tmoves = line.move_id\n\t\t\t\tinvoice_id=False\n\t\t\t\tfor move_line in line.move_id.line_id:\n\t\t\t\t\tif move_line.invoice and move_line.invoice.id:\n\t\t\t\t\t\tinvoice_id=move_line.invoice.id\n\t\t\t\ttax_lines={\n\t\t\t\t\t\"name\"\t\t\t\t: line.name or line.ref or '/',\n\t\t\t\t\t\"move_line_id\"\t\t: line.id,\n\t\t\t\t\t\"invoice_id\"\t\t: invoice_id,\n\t\t\t\t\t\"amount\"\t\t\t: line.debit or line.credit or 0.0,\n\t\t\t\t\t\"currency_id\"\t\t: line.currency_id and line.currency_id.id or False,\n\t\t\t\t\t\"amount_currency\"\t: line.amount_currency or 0.0,\n\t\t\t\t\t\"effective_date\"\t: line.date or False,\n\t\t\t\t\t\"partner_id\"\t\t: line.partner_id and line.partner_id.id or False,\n\t\t\t\t\t}\n\t\t\t\ttax_lines_value.append(tax_lines)\n\t\telif context.get('type',False) == 'tax_lines_dr_unr':\n\t\t\t#move_lines = self.pool.get('account.move.line').search(cr,uid,[('account_id','not in',tax_not_returned),('id','not in',existing_payment_lines),('credit',\"=\",0.0),('debit',\">=\",0.0),('date',\">=\",date_start),('date',\"<=\",date_end),(\"account_id\",'in',tax_account_ids),('move_id.state','=','posted'),('state','=','valid')],context=context)\n\t\t\t#move_lines_unreturned = self.pool.get('account.move.line').search(cr,uid,[('account_id','in',tax_not_returned),('id','not in',existing_payment_lines),('credit',\"=\",0.0),('debit',\">=\",0.0),('date',\">=\",date_start),('date',\"<=\",date_end),(\"account_id\",'in',tax_account_ids),('move_id.state','=','posted'),('state','=','valid')],context=context)\n\t\t\tmove_lines_unreturned = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\n\t\t\t\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_unreturned),('account_id','in',tax_not_returned),\\\n\t\t\t\t('state','=','valid'),('move_id','in',move_id),('debit','>=',0.0),('credit',\"=\",0.0)])\n\n\t\t\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines_unreturned,context=context):\n\t\t\t\tmoves = line.move_id\n\t\t\t\tinvoice_id=False\n\t\t\t\tfor move_line in line.move_id.line_id:\n\t\t\t\t\tif move_line.invoice and move_line.invoice.id:\n\t\t\t\t\t\tinvoice_id=move_line.invoice.id\n\t\t\t\ttax_lines={\n\t\t\t\t\t\"name\"\t\t\t\t: line.name or line.ref or '/',\n\t\t\t\t\t\"move_line_id\"\t\t: line.id,\n\t\t\t\t\t\"invoice_id\"\t\t: invoice_id,\n\t\t\t\t\t\"amount\"\t\t\t: line.debit or line.credit or 0.0,\n\t\t\t\t\t\"currency_id\"\t\t: line.currency_id and line.currency_id.id or False,\n\t\t\t\t\t\"amount_currency\"\t: line.amount_currency or 0.0,\n\t\t\t\t\t\"effective_date\"\t: line.date or False,\n\t\t\t\t\t\"partner_id\"\t\t: line.partner_id and line.partner_id.id or False,\n\t\t\t\t\t}\n\t\t\t\ttax_lines_value.append(tax_lines)\n\t\tvalues.update({'tax_move_line_ids':tax_lines_value})\t\n\t\t\n\t\treturn values","def update_on_save(sender, instance, created, **kwargs):\n instance.order.update_grand_total()","def updatePrice(self, isinkey, field, data, qtype):\r\n isin = isinkey[0:12]\r\n bond = regsToBondName[isin]\r\n if qtype == BloombergQuery.BID:\r\n # 1/ WE CACHE THE OLD PRICE\r\n self.updateCell(bond, 'OLDBID', self.df.at[bond, 'BID'])\r\n self.updateCell(bond, 'OLDASK', self.df.at[bond, 'ASK'])\r\n # 2/ WE CHECK IF PRICE CHANGED\r\n if bond in self.rfbonds:\r\n self.blptsAnalytics.get(isin + '@CBBT' + ' Corp', self.bbgPriceRFQuery)\r\n else:\r\n self.blptsPriceOnly.get(isin + BBGHand + ' Corp', self.bbgPriceOnlyQuery)\r\n elif qtype == BloombergQuery.PRICEONLY:\r\n data = data.astype(float)\r\n # for item, value in data.iteritems():\r\n # self.updateCell(bond,bbgToBdmDic[item],value)\r\n self.lock.acquire()\r\n for item, value in data.iteritems():\r\n self.df.at[bond, bbgToBdmDic[item]] = value\r\n self.lock.release()\r\n if (data['BID'] != self.df.at[bond, 'OLDBID']) or (data['ASK'] != self.df.at[bond, 'OLDASK']):\r\n if bond in SPECIALBONDS:\r\n self.blptsAnalytics.get(isin + BBGHand + ' Corp', self.bbgPriceSpecialQuery)\r\n else:\r\n self.blptsAnalytics.get(isin + BBGHand + ' Corp', self.bbgPriceQuery)\r\n # try:\r\n # self.blptsAnalytics.get(isin + BBGHand + ' Corp', self.bbgPriceQuery)\r\n # except:\r\n # print 'error asking analytics for ' + bond\r\n else:\r\n # print 'Update event without a price change for ' + bond\r\n pub.sendMessage('BOND_PRICE_UPDATE', message=MessageContainer(self.df.loc[bond]))\r\n elif qtype == BloombergQuery.RTGACC:\r\n for item, value in data.iteritems():\r\n self.updateCell(bond,bbgToBdmDic[item],value)\r\n else:#'ANALYTICS' or 'FIRSTPASS'\r\n data = data.astype(float)\r\n # try:\r\n # for item, value in data.iteritems():\r\n # self.updateCell(bond,bbgToBdmDic[item],value)\r\n # except:\r\n # print data\r\n self.lock.acquire()\r\n try:\r\n for item, value in data.iteritems():\r\n self.df.at[bond, bbgToBdmDic[item]] = value\r\n except:\r\n self.lock.release()\r\n print data\r\n self.lock.release()\r\n if bond in SINKABLEBONDS:\r\n #self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=data['BID'])\r\n self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=self.df.at[bond, 'BID'])\r\n self.bbgSinkRequest.get()\r\n self.updateCell(bond, 'ZB', float(self.bbgSinkRequest.output.values[0,0]))\r\n #self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=data['ASK'])\r\n # self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=self.df.at[bond, 'ASK'])\r\n # self.bbgSinkRequest.get() \r\n # self.updateCell(bond, 'ZA', float(self.bbgSinkRequest.output.values[0,0]))\r\n if qtype == BloombergQuery.ANALYTICS:\r\n self.updateStaticAnalytics(bond)","def tax(subtotal, discount):\n return (subtotal - discount) * 0.12","def Update(self, prices):\n \n if self._bdaqmid != None:\n # check that we got new prices for this market this tick.\n if (self._bdaqmid in prices[const.BDAQID] and\n self._bfmid in prices[const.BFID]):\n self._bdaqsels = [prices[const.BDAQID][self._bdaqmid][i]\n for i in [s.id for s in self._bdaqsels]]\n self._bfsels = [prices[const.BFID][self._bfmid][i]\n for i in [s.id for s in self._bfsels]]\n\n # call the listener functions.\n self.UpdateViews()","def compute_all(self, price_unit, currency=None, quantity=1.0, product=None, partner=None):\n if len(self) == 0:\n company_id = self.env.user.company_id\n else:\n company_id = self[0].company_id\n if not currency:\n currency = company_id.currency_id\n taxes = []\n # By default, for each tax, tax amount will first be computed\n # and rounded at the 'Account' decimal precision for each\n # PO/SO/invoice line and then these rounded amounts will be\n # summed, leading to the total amount for that tax. But, if the\n # company has tax_calculation_rounding_method = round_globally,\n # we still follow the same method, but we use a much larger\n # precision when we round the tax amount for each line (we use\n # the 'Account' decimal precision + 5), and that way it's like\n # rounding after the sum of the tax amounts of each line\n prec = currency.decimal_places\n\n # In some cases, it is necessary to force/prevent the rounding of the tax and the total\n # amounts. For example, in SO/PO line, we don't want to round the price unit at the\n # precision of the currency.\n # The context key 'round' allows to force the standard behavior.\n round_tax = False if company_id.tax_calculation_rounding_method == 'round_globally' else True\n round_total = True\n if 'round' in self.env.context:\n round_tax = bool(self.env.context['round'])\n round_total = bool(self.env.context['round'])\n\n if not round_tax:\n prec += 5\n\n base_values = self.env.context.get('base_values')\n if not base_values:\n total_excluded = total_included = base = round(price_unit * quantity, prec)\n else:\n total_excluded, total_included, base = base_values\n\n # Sorting key is mandatory in this case. When no key is provided, sorted() will perform a\n # search. However, the search method is overridden in account.tax in order to add a domain\n # depending on the context. This domain might filter out some taxes from self, e.g. in the\n # case of group taxes.\n for tax in self.sorted(key=lambda r: r.sequence):\n # Allow forcing price_include/include_base_amount through the context for the reconciliation widget.\n # See task 24014.\n price_include = self._context.get('force_price_include', tax.price_include)\n\n if tax.amount_type == 'group':\n children = tax.children_tax_ids.with_context(base_values=(total_excluded, total_included, base))\n ret = children.compute_all(price_unit, currency, quantity, product, partner)\n total_excluded = ret['total_excluded']\n base = ret['base'] if tax.include_base_amount else base\n total_included = ret['total_included']\n tax_amount = total_included - total_excluded\n taxes += ret['taxes']\n continue\n\n tax_amount = tax._compute_amount(base, price_unit, quantity, product, partner)\n if not round_tax:\n tax_amount = round(tax_amount, prec)\n else:\n tax_amount = currency.round(tax_amount)\n\n if price_include:\n total_excluded -= tax_amount\n base -= tax_amount\n else:\n total_included += tax_amount\n\n # Keep base amount used for the current tax\n tax_base = base\n\n if tax.include_base_amount:\n base += tax_amount\n\n taxes.append({\n 'id': tax.id,\n 'name': tax.with_context(**{'lang': partner.lang} if partner else {}).name,\n 'amount': tax_amount,\n 'base': tax_base,\n 'sequence': tax.sequence,\n 'account_id': tax.account_id.id,\n 'refund_account_id': tax.refund_account_id.id,\n 'analytic': tax.analytic,\n 'price_include': tax.price_include,\n 'tax_exigibility': tax.tax_exigibility,\n })\n\n return {\n 'taxes': sorted(taxes, key=lambda k: k['sequence']),\n 'total_excluded': currency.round(total_excluded) if round_total else total_excluded,\n 'total_included': currency.round(total_included) if round_total else total_included,\n 'base': base,\n }","def calculateSingleTax(monthlyIncome):\n pass","def m_ts_OrderUpdated(self, sender, e):\r\n print(\"Order was updated with price of {0}.\".format(e.NewOrder.LimitPrice))","def lineitem_post_save(**kwargs):\n lineitem = kwargs['instance']\n bill = lineitem.bill\n bill.update_cached_totals()","def tax(bill):\r\n bill *= 1.08\r\n print(\"With tax: %f\" % bill)\r\n return bill","def _amount_all(self):\r\n for order in self:\r\n amount_untaxed = amount_tax = amount_discount = timbre = 0.0\r\n for line in order.order_line:\r\n amount_untaxed += line.price_subtotal\r\n if line.product_id.timbre_fiscal:\r\n amount_tax += line.price_tax - 0.60\r\n timbre = 0.60\r\n else :\r\n amount_tax += line.price_tax\r\n amount_discount += (line.product_uom_qty * line.price_unit * line.discount)/100\r\n order.update({\r\n 'amount_untaxed': order.pricelist_id.currency_id.round(amount_untaxed),\r\n 'amount_tax': order.pricelist_id.currency_id.round(amount_tax),\r\n 'amount_discount': order.pricelist_id.currency_id.round(amount_discount),\r\n 'price_total_no_discount': amount_untaxed + amount_discount,\r\n 'timbre': timbre,\r\n 'amount_total': amount_untaxed + amount_tax + timbre,\r\n })","def test_updating_the_supply_price(self):\n self.assertEqual(self.po.id, 1)\n self.assertEqual(self.po.items.count(), 1)\n item = self.po.items.all()[0]\n self.assertEqual(item.id, 1)\n self.assertEqual(item.unit_cost, Decimal('12.11'))\n self.assertEqual(Log.objects.all().count(), 0)\n \n modified_po = copy.deepcopy(base_purchase_order)\n modified_po['items'][0]['unit_cost'] = Decimal('10.05')\n modified_po['items'][0]['id'] = 1\n modified_po['status'] = 'PROCESSED'\n del modified_po['items'][1]\n resp = self.client.put('/api/v1/purchase-order/1/',\n format='json',\n data=modified_po)\n self.assertEqual(resp.status_code, 200, msg=resp)\n resp_obj = resp.data\n self.assertEqual(resp_obj['revision'], 1)\n #Check the new pdf\n #webbrowser.get(\"open -a /Applications/Google\\ Chrome.app %s\").open(resp_obj['pdf']['url'])\n \n self.assertEqual(resp_obj['id'], 1)\n self.assertEqual(resp_obj['supplier']['id'], 1)\n self.assertEqual(resp_obj['vat'], 7)\n self.assertEqual(resp_obj['discount'], 0)\n self.assertEqual(resp_obj['revision'], 1)\n self.assertEqual(Decimal(resp_obj['grand_total']), Decimal('107.54'))\n self.assertEqual(len(resp_obj['items']), 1)\n item1 = resp_obj['items'][0]\n self.assertEqual(item1['id'], 1)\n self.assertEqual(item1['quantity'], Decimal('10.0000000000'))\n self.assertEqual(Decimal(item1['unit_cost']), Decimal('10.05'))\n self.assertEqual(Decimal(item1['total']), Decimal('100.50'))\n \n #Confirm cost change for item and supply in the database\n po = PurchaseOrder.objects.get(pk=1)\n self.assertEqual(po.grand_total, Decimal('107.54'))\n item1 = po.items.order_by('id').all()[0]\n self.assertEqual(item1.id, 1)\n self.assertEqual(item1.quantity, 10)\n self.assertEqual(item1.unit_cost, Decimal('10.05'))\n supply = item1.supply\n supply.supplier = po.supplier\n self.assertEqual(supply.cost, Decimal('10.05'))\n \n self.assertEqual(Log.objects.all().count(), 1)\n log = Log.objects.all()[0]\n self.assertEqual(log.cost, Decimal('10.05'))\n self.assertEqual(log.supply, supply)\n self.assertEqual(log.supplier, po.supplier)\n self.assertEqual(log.message, \"Price change from 12.11USD to 10.05USD for Pattern: Maxx, Col: Blue [Supplier: Zipper World]\")\n\n # Confirm that there is still only one product for this supply and supplier\n # in the database\n products = Product.objects.filter(supply=supply, supplier=po.supplier)\n self.assertEqual(len(products), 1)","def tax(bill):\n bill *= 1.08\n print \"With tax: %f\" % bill\n return bill","def tax(bill):\n bill *= 1.08\n print \"With tax: %f\" % bill\n return bill","def validate(cls, prices):\n super(GiftCardPrice, cls).validate(prices)\n\n for price in prices:\n price.check_price()","def updatePriceOfExistingStocks(self):\n currentDate = str(datetime.now().strftime(\"%Y-%m-%d\"))\n listOfStocks = self.retrieveAllDistinctStocks()\n isPercentageChangeUpdated = self.checkIfPercentageChangesUpdated(\n currentDate)\n\n if not isPercentageChangeUpdated:\n print(\"PercentageChanges not updated. Commencing update now...\")\n for stockSymbol, stockExchange in listOfStocks:\n latestPercentageChange = self.getLatestPercentageChange(\n stockSymbol, stockExchange, currentDate)\n if latestPercentageChange is not None:\n self.storeLatestPercentageChange(\n stockSymbol, stockExchange, currentDate, latestPercentageChange)\n print(\"{} updated.\".format(stockSymbol))\n print(\"Update complete.\")\n else:\n print(\"Prices are already up to date.\")","def do_change_standard_price(self, cr, uid, ids, new_price, context=None):\n location_obj = self.pool.get('stock.location')\n move_obj = self.pool.get('account.move')\n move_line_obj = self.pool.get('account.move.line')\n if context is None:\n context = {}\n user_company_id = self.pool.get('res.users').browse(cr,\n uid, uid,\n context=context).\\\n company_id.id\n loc_ids = location_obj.search(cr, uid,\n [('usage', '=', 'internal'),\n ('company_id', '=', user_company_id)])\n for rec_id in ids:\n datas = self.get_product_accounts(cr, uid, rec_id, context=context)\n for location in location_obj.browse(cr, uid, loc_ids,\n context=context):\n contextc = context.copy()\n contextc.update({'location': location.id,\n 'compute_child': False})\n product = self.browse(cr, uid, rec_id, context=contextc)\n\n diff = product.standard_price - new_price\n if not diff:\n continue\n for prod_variant in product.product_variant_ids:\n qty = prod_variant.qty_available\n if qty:\n # Accounting Entries\n ref = '[{code}] {name}'.\\\n format(code=prod_variant.default_code,\n name=prod_variant.name)\n move_vals = {\n 'journal_id': datas['stock_journal'],\n 'company_id': location.company_id.id,\n 'ref': ref,\n }\n move_id = move_obj.create(cr, uid, move_vals,\n context=context)\n\n if diff * qty > 0:\n amount_diff = qty * diff\n debit_account_id = \\\n datas['property_difference_price_account_id']\n credit_account_id = \\\n datas['property_stock_valuation_account_id']\n\n else:\n amount_diff = qty * -diff\n debit_account_id = \\\n datas['property_stock_valuation_account_id']\n credit_account_id = \\\n datas['property_difference_price_account_id']\n\n move_line_obj.create(cr, uid, {\n 'name': _('Standard Price changed'),\n 'account_id': debit_account_id,\n 'debit': amount_diff,\n 'ref': ref,\n 'credit': 0,\n 'move_id': move_id, }, context=context)\n move_line_obj.create(cr, uid, {\n 'name': _('Standard Price changed'),\n 'account_id': credit_account_id,\n 'debit': 0,\n 'ref': ref,\n 'credit': amount_diff,\n 'move_id': move_id\n }, context=context)\n self.write(cr, uid, rec_id, {'standard_price': new_price})\n return True","def create_or_find_b2b_invoices_and_process_ept(self, row, sale_order, invoice_date, tax):\n\n vat_number = row.get('Buyer Tax Registration', False)\n invoice_number = row.get('VAT Invoice Number', False)\n\n invoices = sale_order.invoice_ids.filtered(\n lambda x: x.type == 'out_invoice' and x.state != 'cancel')\n if not invoices:\n lines = sale_order.order_line.filtered(lambda line: line.qty_to_invoice > 0)\n if not lines:\n return False\n invoices = sale_order._create_invoices()\n self.write({'invoice_ids': [(4, invoices and invoices.id)]})\n\n for invoice in invoices:\n if not invoice.partner_id.vat:\n invoice.partner_id.vat = vat_number\n\n payments_lines = []\n if invoice.invoice_payments_widget != 'false':\n payments_dict = json.loads(invoice.invoice_payments_widget)\n payments_content = payments_dict.get('content', [])\n for line in payments_content:\n payments_lines.append(line.get('payment_id', False))\n\n invoice_line = invoice.mapped('invoice_line_ids').filtered(\\\n lambda line: line.tax_ids != tax)\n if invoice_line:\n invoice.button_draft()\n invoice.write({'ref': invoice_number, 'date': invoice_date})\n\n if len(invoice_line) > 1:\n for line in invoice_line:\n line.with_context({'check_move_validity': False}).write( \\\n {'tax_ids': [(6, 0, [tax.id])]})\n else:\n invoice_line.with_context({'check_move_validity': False}).write( \\\n {'tax_ids': [(6, 0, [tax.id])]})\n\n invoice.with_context({'check_move_validity': False})._recompute_tax_lines( \\\n recompute_tax_base_amount=True)\n invoice.action_post()\n for line in payments_lines:\n invoice.js_assign_outstanding_line(line)\n\n return True","def _amount_all(self):\n for order in self:\n amount_untaxed = 0.0\n for line in order.order_items_ids:\n amount_untaxed += line.price_subtotal\n order.update({\n 'amount_untaxed': amount_untaxed,\n })","def _compute_amount_subtotal(self):\n for lines in self:\n lines.price_subtotal = lines.price_unit * lines.order_qty","def auto_process_vcs_tax_report(self, args={}):\n seller_id = args.get('seller_id', False)\n if seller_id:\n seller = self.env['amazon.seller.ept'].search([('id', '=', seller_id)])\n vcs_reports = self.search(\n [('seller_id', '=', seller.id), ('state', 'in', ['_SUBMITTED_', '_IN_PROGRESS_'])])\n if vcs_reports:\n total_length = len(vcs_reports.ids)\n for x in range(0, total_length, 20):\n reports = vcs_reports[x:x + 20]\n for report in reports:\n report.get_report_request_list()\n if report.filtered(lambda r: r.state == '_DONE_' and r.report_id != False):\n try:\n report.get_report()\n\n except Exception as e:\n raise UserError(e)\n time.sleep(2)\n report.process_vcs_tax_report_file()\n self._cr.commit()\n time.sleep(3)\n\n else:\n reports = self.search([('seller_id', '=', seller.id),\n ('state', '=', '_DONE_'),\n ], order='id asc')\n for report in reports:\n if not report.attachment_id:\n while True:\n try:\n report.get_report()\n break\n except Exception as e:\n raise UserError(e)\n try:\n report.process_vcs_tax_report_file()\n self._cr.commit()\n except:\n continue\n time.sleep(3)\n return True","def tax_override(self, tax_override):\n\n self._tax_override = tax_override","def update_on_delete(sender, instance, **kwargs):\n instance.order.update_grand_total()","def sub_tax_cost_transfer_pricing(manager, df_fields, seq_recs, seq_reservas):\n # df_hotel = manager.get_dataframe(tables[\"dwc_bok_t_canco_hotel\"])\n # df_circuit = manager.get_dataframe(tables[\"dwc_bok_t_canco_hotel_circuit\"])\n # df_other = manager.get_dataframe(tables[\"dwc_bok_t_canco_other\"])\n # df_transfer = manager.get_dataframe(tables[\"dwc_bok_t_canco_transfer\"])\n # df_endow = manager.get_dataframe(tables[\"dwc_bok_t_canco_endowments\"])\n # df_extra = manager.get_dataframe(tables[\"dwc_bok_t_canco_extra\"])\n\n df_aux = df_fields.select(\"operative_incoming\", \"booking_id\", \"invoicing_company\", \"creation_date\",\n \"booking_currency\")\n\n df_hotel = sub_tax_cost_transfer_pricing_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\n df_circuit = sub_tax_cost_transfer_pricing_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\n df_other = sub_tax_cost_transfer_pricing_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\n df_transfer = sub_tax_cost_transfer_pricing_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\n df_endow = sub_tax_cost_transfer_pricing_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\n df_extra = sub_tax_cost_transfer_pricing_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\n\n df_impuesto_canco = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\n df_extra)\n\n df_impuesto_canco = df_impuesto_canco.groupBy(\"operative_incoming\", \"booking_id\") \\\n .agg({'impuesto_canco': 'sum'}).withColumnRenamed(\"SUM(impuesto_canco)\", \"impuesto_canco\")\n\n df_impuesto_canco = df_impuesto_canco.withColumnRenamed(\"operative_incoming\", \"seq_rec\") \\\n .withColumnRenamed(\"booking_id\", \"seq_res\")\n\n # add impuesto_canco\n df_fields = df_fields.join(df_impuesto_canco, [df_fields.operative_incoming == df_impuesto_canco.seq_rec,\n df_fields.booking_id == df_impuesto_canco.seq_res],\n 'left_outer').drop(\"seq_rec\", \"seq_res\")\n\n df_addcanco = sub_transfer_pricing_aux_add_canco(manager, df_fields, seq_recs, seq_reservas)\n\n df_addcanco = df_addcanco.withColumnRenamed(\"operative_incoming\", \"seq_rec\") \\\n .withColumnRenamed(\"booking_id\", \"seq_res\")\n\n # add add_impuesto_canco\n df_fields = df_fields.join(df_addcanco, [df_fields.operative_incoming == df_addcanco.seq_rec,\n df_fields.booking_id == df_addcanco.seq_res],\n \"left_outer\").drop(df_addcanco.seq_rec).drop(df_addcanco.seq_res)\n\n df_fields = df_fields.na.fill({'impuesto_canco': 0, 'add_impuesto_canco': 0})\n\n df_fields = df_fields.withColumn(\"Tax_Cost_Transfer_pricing\",\n df_fields.impuesto_canco + df_fields.add_impuesto_canco) \\\n .drop(\"impuesto_canco\", \"add_impuesto_canco\")\n\n df_fields = df_fields.withColumn(\"Tax_Cost_Transfer_pricing\", udf_round_ccy(df_fields.Tax_Cost_Transfer_pricing,\n df_fields.booking_currency))\n\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canco, df_addcanco, df_aux\n\n return df_fields","def save_change(self):\n try:\n self.customer.budget.income = abs(float(self.incomeItem.text()))\n self.incomeItem.setText(f\"{self.customer.budget.income}\")\n fixed_expenses = {\n \"rent\": abs(float(self.listOfExpensesSEK.item(4).text())),\n \"subscription\": abs(float(self.listOfExpensesSEK.item(2).text())),\n \"insurance\": abs(float(self.listOfExpensesSEK.item(3).text())),\n \"others\": abs(float(self.listOfExpensesSEK.item(5).text()))\n }\n variable_expenses = {\n \"food\": abs(float(self.listOfExpensesSEK.item(11).text())),\n \"bills\": abs(float(self.listOfExpensesSEK.item(12).text())),\n \"transportation\": abs(float(self.listOfExpensesSEK.item(13).text())),\n \"hygien\": abs(float(self.listOfExpensesSEK.item(14).text())),\n \"clothes\": abs(float(self.listOfExpensesSEK.item(15).text())),\n \"entertainment\": abs(float(self.listOfExpensesSEK.item(16).text())),\n \"others\": abs(float(self.listOfExpensesSEK.item(17).text()))\n }\n self.customer.budget.set_budget(self.customer.budget.income,\n variable_expenses, fixed_expenses)\n # update instead of set\n DB.update_variable_expenses(self.customer.email, variable_expenses)\n DB.update_fixed_expenses(self.customer.email, fixed_expenses)\n DB.update_income(self.customer.budget.income, self.customer.email)\n total_fix, total_var = self.customer.budget.get_expenses()\n self.listOfExpensesSEK.item(1).setText(total_fix)\n self.listOfExpensesSEK.item(10).setText(total_var)\n self.customer.budget.set_buffert(abs(float(\n self.listOfExpensesSEK.item(20).text()\n )))\n DB.update_buffert(self.customer.email, abs(float(self.listOfExpensesSEK.item(20).text())))\n self.label_3.setText(str(self.customer.budget.income -\n self.customer.budget.get_total_expenses())\n )\n except Exception:\n self.popUp.exec_()","def re_process_vcs_tax_report_file(self):\n log_line_obj = self.env['common.log.lines.ept']\n model_id = log_line_obj.get_model_id('amazon.vcs.tax.report.ept')\n records = log_line_obj.search([('model_id', '=', model_id), ('res_id', '=', self.id)])\n records.unlink()\n self.process_vcs_tax_report_file()\n return True","def sub_tax_cost_transfer_pricing_eur(manager, df_fields, seq_recs, seq_reservas):\n # df_hotel = manager.get_dataframe(tables[\"dwc_bok_t_canco_hotel\"])\n # df_circuit = manager.get_dataframe(tables[\"dwc_bok_t_canco_hotel_circuit\"])\n # df_other = manager.get_dataframe(tables[\"dwc_bok_t_canco_other\"])\n # df_transfer = manager.get_dataframe(tables[\"dwc_bok_t_canco_transfer\"])\n # df_endow = manager.get_dataframe(tables[\"dwc_bok_t_canco_endowments\"])\n # df_extra = manager.get_dataframe(tables[\"dwc_bok_t_canco_extra\"])\n\n df_aux = df_fields.select(\"operative_incoming\", \"booking_id\", \"invoicing_company\", \"creation_date\",\n \"booking_currency\")\n\n df_hotel = sub_tax_transfer_pricing_eur_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\n df_circuit = sub_tax_transfer_pricing_eur_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\n df_other = sub_tax_transfer_pricing_eur_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\n df_transfer = sub_tax_transfer_pricing_eur_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\n df_endow = sub_tax_transfer_pricing_eur_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\n df_extra = sub_tax_transfer_pricing_eur_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\n\n df_impuesto_canco = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\n df_extra)\n\n df_impuesto_canco = df_impuesto_canco.groupBy(\"operative_incoming\", \"booking_id\") \\\n .agg({'impuesto_canco': 'sum'}).withColumnRenamed(\"SUM(impuesto_canco)\", \"impuesto_canco\")\n\n df_impuesto_canco = df_impuesto_canco.withColumnRenamed(\"operative_incoming\", \"seq_rec\") \\\n .withColumnRenamed(\"booking_id\", \"seq_res\")\n\n df_fields = df_fields.join(df_impuesto_canco, [df_fields.operative_incoming == df_impuesto_canco.seq_rec,\n df_fields.booking_id == df_impuesto_canco.seq_res],\n 'left_outer').drop(\"seq_rec\", \"seq_res\")\n\n df_addcanco = sub_transfer_pricing_aux_add_canco(manager, df_fields, seq_recs, seq_reservas, EUR)\n\n df_addcanco = df_addcanco.withColumnRenamed(\"operative_incoming\", \"seq_rec\") \\\n .withColumnRenamed(\"booking_id\", \"seq_res\")\n\n # add add_impuesto_canco\n df_fields = df_fields.join(df_addcanco, [df_fields.operative_incoming == df_addcanco.seq_rec,\n df_fields.booking_id == df_addcanco.seq_res],\n \"left_outer\").drop(df_addcanco.seq_rec).drop(df_addcanco.seq_res)\n\n df_fields = df_fields.na.fill({'impuesto_canco': 0, 'add_impuesto_canco': 0})\n\n df_fields = df_fields.withColumn(\"Tax_Cost_Transfer_pricing_EUR\",\n df_fields.impuesto_canco + df_fields.add_impuesto_canco) \\\n .drop(\"impuesto_canco\", \"add_impuesto_canco\")\n\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canco, df_addcanco\n\n return df_fields","def sub_tax_transfer_pricing_eur(manager, df_fields, seq_recs, seq_reservas):\n # df_hotel = manager.get_dataframe(tables[\"dwc_bok_t_canco_hotel\"])\n # df_circuit = manager.get_dataframe(tables[\"dwc_bok_t_canco_hotel_circuit\"])\n # df_other = manager.get_dataframe(tables[\"dwc_bok_t_canco_other\"])\n # df_transfer = manager.get_dataframe(tables[\"dwc_bok_t_canco_transfer\"])\n # df_endow = manager.get_dataframe(tables[\"dwc_bok_t_canco_endowments\"])\n # df_extra = manager.get_dataframe(tables[\"dwc_bok_t_canco_extra\"])\n\n df_aux = df_fields.select(\"operative_incoming\", \"booking_id\", \"invoicing_company\", \"creation_date\",\n \"booking_currency\")\n\n df_hotel = sub_tax_transfer_pricing_eur_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\n df_circuit = sub_tax_transfer_pricing_eur_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\n df_other = sub_tax_transfer_pricing_eur_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\n df_transfer = sub_tax_transfer_pricing_eur_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\n df_endow = sub_tax_transfer_pricing_eur_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\n df_extra = sub_tax_transfer_pricing_eur_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\n\n df_impuesto_canco = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\n df_extra)\n\n df_impuesto_canco = df_impuesto_canco.groupBy(\"operative_incoming\", \"booking_id\") \\\n .agg({'impuesto_canco': 'sum'}).withColumnRenamed(\"SUM(impuesto_canco)\", \"impuesto_canco\")\n\n df_impuesto_canco = df_impuesto_canco.withColumnRenamed(\"operative_incoming\", \"seq_rec\") \\\n .withColumnRenamed(\"booking_id\", \"seq_res\")\n\n df_fields = df_fields.join(df_impuesto_canco, [df_fields.operative_incoming == df_impuesto_canco.seq_rec,\n df_fields.booking_id == df_impuesto_canco.seq_res],\n 'left_outer').drop(\"seq_rec\", \"seq_res\")\n\n df_addcanco = sub_transfer_pricing_aux_add_canco(manager, df_fields, seq_recs, seq_reservas, EUR)\n\n df_addcanco = df_addcanco.withColumnRenamed(\"operative_incoming\", \"seq_rec\") \\\n .withColumnRenamed(\"booking_id\", \"seq_res\")\n\n # add add_impuesto_canco\n df_fields = df_fields.join(df_addcanco, [df_fields.operative_incoming == df_addcanco.seq_rec,\n df_fields.booking_id == df_addcanco.seq_res],\n \"left_outer\").drop(df_addcanco.seq_rec).drop(df_addcanco.seq_res)\n\n df_fields = df_fields.na.fill({'impuesto_canco': 0, 'add_impuesto_canco': 0})\n\n df_fields = df_fields.withColumn(\"Tax_Transfer_pricing_EUR\",\n df_fields.impuesto_canco + df_fields.add_impuesto_canco) \\\n .drop(\"impuesto_canco\", \"add_impuesto_canco\")\n\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canco, df_addcanco\n\n return df_fields","def _compute_amount(self):\n for line in self:\n line.update({\n 'price_subtotal': line.price_unit * line.quantity,\n })","def tax(bill):\n bill *= 1.08\n print \"With tax: %.2f\" % bill\n return bill","def tax(self):\n\n self.x = self.a\n self.set_zn(self.x)","def trend_price_up(self):\n raise NotImplementedError()","def before_tax_profit(self):\n\n _before_tax_profit = self.net_revenue() - self.depreciation()\n return _before_tax_profit","def updatePrices(self,dd):\n for key in dd:\n self.DoS[key].updatePrice(dd[key])","def price_bound(self, price_bound):\n\n self._price_bound = price_bound","def my_rebalance(context, data):\n freq_month = 3\n context.counter += 1\n if context.counter == freq_month:\n for stock, weight in context.weights.iteritems():\n context.counter = 0\n if data.can_trade(stock):\n order_target_percent(stock, weight)","def calculate_tax(subtotal):\n return \"TAX: \"+format_usd(0.0875*subtotal)","def calculate_tax_for_old_regime(income,\n savings_80c=0,\n savings_80ccd=0,\n savings_80d=0,\n age=25,\n parent_age=55\n ):\n tax_amount = 0\n savings_80c = min(savings_limit['80C'], savings_80c)\n savings_80ccd = min(savings_limit['80CCD'], savings_80c)\n savings_limit_80d = savings_limit['80D'] * (2 if age > 60 else 1)\n savings_limit_80d += savings_limit['80D'] * (2 if parent_age > 60 else 1)\n savings_80d = min(savings_limit_80d, savings_80d)\n\n total_savings = savings_80c + savings_80ccd + savings_80d\n print(\"Total savings: {}\".format(total_savings))\n\n deducted_income = income - total_savings\n init_income = deducted_income\n\n slab_breaks = sorted(old_tax_regime.keys(), reverse=True)\n\n for upper_tax_slab in slab_breaks:\n if deducted_income > upper_tax_slab:\n curr_tax = old_tax_regime[upper_tax_slab] * (deducted_income - upper_tax_slab)\n tax_amount += curr_tax\n print(\"Tax slab: {}\\tAmount in the slab: {}\\tTax amount: {}\".format(upper_tax_slab, (deducted_income - upper_tax_slab), curr_tax))\n deducted_income = upper_tax_slab\n\n if init_income <= 500000:\n rebate = -1 * tax_amount\n print(\"Rebate: {}\".format(rebate))\n tax_amount += rebate\n\n health_ed_cess = 0.04 * tax_amount # 4% health and education cess on the tax amount\n print(\"Cess: {}\".format(health_ed_cess))\n tax_amount += health_ed_cess\n\n return tax_amount","def modify_price(self, price):\n if price is not None and self.is_cancellable:\n log.info(\"bo#%s: modify price (pending) order \" % self.ticket)\n not_implemented_error(\"Can't modify price for now (only for pending orders which wasn't triggered\")\n order_id = self.order_id_master\n cancel_order(order_id) # DANGEROUS! it should be atomic operation!\n #style = self.style\n #if self.is_limit:\n #elif self.is_stop:\n #elif self.is_stop_limit\n #order_id = order(self.symbol, self.volume, style=new_style))\n \n else:\n return","def payment_post_save(**kwargs):\n payment = kwargs['instance']\n bill = payment.bill\n bill.update_cached_totals()","def add_tax(self,tax):\n return self.price + (self.price * tax)","def m_ps_FieldsUpdated(self, sender, e):\r\n if e.Error == None:\r\n # Make sure that there is a valid bid\r\n if e.Fields.GetBestBidPriceField().HasValidValue:\r\n if self.m_orderKey == \"\":\r\n # If there is no order working, submit one through the first valid order feed.\r\n # You should use the order feed that is valid for your purposes.\r\n op = ttapi.OrderProfile(e.Fields.Instrument.GetValidOrderFeeds()[0], e.Fields.Instrument)\r\n op.BuySell = ttapi.BuySell.Buy\r\n op.AccountName = \"12345678\"\r\n op.AccountType = ttapi.AccountType.A1\r\n op.OrderQuantity = ttapi.Quantity.FromInt(e.Fields.Instrument, 1)\r\n op.OrderType = ttapi.OrderType.Limit\r\n op.LimitPrice = e.Fields.GetBestBidPriceField().Value\r\n if not self.m_ts.SendOrder(op):\r\n print(\"Send new order failed. {0}\".format(op.RoutingStatus.Message))\r\n self.Dispose()\r\n else:\r\n self.m_orderKey = op.SiteOrderKey\r\n print(\"Send new order succeeded.\")\r\n elif self.m_ts.Orders.ContainsKey(self.m_orderKey) and self.m_ts.Orders[self.m_orderKey].LimitPrice != e.Fields.GetBestBidPriceField().Value:\r\n # If there is a working order, reprice it if its price is not the same as the bid\r\n op = self.m_ts.Orders[self.m_orderKey].GetOrderProfile()\r\n op.LimitPrice = e.Fields.GetBestBidPriceField().Value\r\n op.Action = ttapi.OrderAction.Change\r\n if not self.m_ts.SendOrder(op):\r\n print(\"Send change order failed. {0}\".format(op.RoutingStatus.Message))\r\n else:\r\n print(\"Send change order succeeded.\")\r\n else:\r\n if e.Error.IsRecoverableError == False:\r\n print(\"Unrecoverable price subscription error: {0}\".format(e.Error.Message))\r\n self.Dispose()","def _amount_all(self):\n for order in self:\n amount_untaxed = amount_tax = 0.0\n order_amount_total = 0.0\n for line in order.order_line:\n amount_untaxed += line.price_subtotal\n amount_tax += line.price_tax\n self_amount_total = amount_untaxed + amount_tax\n if not order.discount_fixed_percent:\n order_amount_total = self_amount_total\n if order.discount_fixed_percent == 'Percent':\n order_amount_total = self_amount_total * (1 - (order.discount or 0.0) / 100.0)\n if order.discount_fixed_percent == 'Fixed':\n order_amount_total = self_amount_total - order.discount_value\n order.update({\n 'amount_untaxed': order.pricelist_id.currency_id.round(amount_untaxed),\n 'amount_tax': order.pricelist_id.currency_id.round(amount_tax),\n 'amount_before_disc': amount_untaxed + amount_tax,\n 'amount_total': order_amount_total,\n })","def pre_approve(self, cr, uid, ids, context={}):\n \tfor voucher in self.browse(cr, uid, ids, context=context):\n \t if not voucher.department_id.analytic_account_id:\n \t raise osv.except_osv(_('Configration Check!'), _(\"Please add cost center for your department!\"))\n \t periods = self.pool.get('account.period').search(cr, uid, [('date_start','<=',voucher.date),('date_stop','>=',voucher.date),('company_id','=',voucher.company_id.id)], context=context)\n\n\n res=0.0\n if voucher.purpose:\n if not voucher.purpose.account_id: raise osv.except_osv(_('Warning!'), _('Please configure account for this purpose!')) \n voucher_line = {\n \t\t'voucher_id': voucher.id,\n \t\t'partner_id': voucher.partner_id.id,\n \t\t'untax_amount': voucher.amount,\n \t\t'amount': voucher.amount,\n 'name': voucher.narration,\n \t\t'type': 'dr',\n \t\t'account_analytic_id': voucher.department_id.analytic_account_id and voucher.department_id.analytic_account_id.id,\n 'account_id': voucher.purpose.account_id.id,\n \t }\n new_amount = res and res or voucher.amount \n voucher_line.update({'amount':new_amount,'untax_amount':new_amount})\n \t if voucher.line_ids :\n for line in voucher.line_ids:\n \t\t self.pool.get('account.voucher.line').write(cr, uid, line.id, {\n \t\t'voucher_id': voucher.id,\n \t\t'partner_id': voucher.partner_id.id,\n \t\t'untax_amount': res or line.amount,\n \t\t'amount': line.amount,\n 'name': voucher.narration,\n \t\t'type': 'dr',\n \t\t'account_analytic_id': line.account_analytic_id and line.account_analytic_id.id or voucher.department_id.analytic_account_id.id,\n 'account_id': voucher.purpose.account_id.id or line.account_id.id,\n \t }, context=context)\n \t else:\n\n \t\t new_voucher_line = self.pool.get('account.voucher.line').create(cr, uid, voucher_line, context=context)\n context.update({'purchase':True})\n self.create_budget_confirmation(cr, uid, [voucher.id], context)\n \tself.write(cr, uid, ids,{'state': 'preapprove','type':'purchase','ratification':True}, context=context)\n #cxt = context.copy()\n #cxt.update({'type':'ratification'})\n if not super(account_voucher, self).create_budget_confirmation(cr, uid, ids, context=context):\n self.write(cr, uid, ids, {'state': 'approved'}, context=context)\n\n \t'''self.write(cr, uid, ids, {'state': 'preapprove'})\n if not super(account_voucher, self).create_budget_confirmation(cr, uid, ids, context=context):\n self.write(cr, uid, ids, {'state': 'approve','type':'purchase','ratification':True}, context=context)'''\n return True","def percent_changes(self):\n\n # close_t = float(val[\"klines\"][\"1m\"].get(self.mw.cfg_manager.pair, {})[-5][4])\n klines_data = self.mw.klines.get(\"1m\")\n coin_data = klines_data.get(self.mw.cfg_manager.pair)\n\n if isinstance(coin_data, list):\n close_5m = float(self.mw.klines[\"1m\"][self.mw.cfg_manager.pair][-5][4])\n close_15m = float(self.mw.klines[\"1m\"][self.mw.cfg_manager.pair][-15][4])\n # close_30m = float(self.mw.klines[\"1m\"][self.mw.cfg_manager.pair][-30][4])\n close_1h = float(self.mw.klines[\"1m\"][self.mw.cfg_manager.pair][-60][4])\n close_4h = float(self.mw.klines[\"1m\"][self.mw.cfg_manager.pair][-240][4])\n\n change_5m_value = ((float(val[\"tickers\"][self.mw.cfg_manager.pair][\"lastPrice\"]) / float(close_5m)) - 1) * 100\n change_15m_value = ((float(val[\"tickers\"][self.mw.cfg_manager.pair][\"lastPrice\"]) / float(close_15m)) - 1) * 100\n # change_30m_value = ((float(val[\"tickers\"][self.mw.cfg_manager.pair][\"lastPrice\"]) / float(close_30m)) - 1) * 100\n change_1h_value = ((float(val[\"tickers\"][self.mw.cfg_manager.pair][\"lastPrice\"]) / float(close_1h)) - 1) * 100\n change_4h_value = ((float(val[\"tickers\"][self.mw.cfg_manager.pair][\"lastPrice\"]) / float(close_4h)) - 1) * 100\n\n change_1d_value = float(val[\"tickers\"][self.mw.cfg_manager.pair][\"priceChangePercent\"])\n\n\n changes = [self.mw.change_5m, self.mw.change_15m, self.mw.change_1h, self.mw.change_4h, self.mw.change_1d]\n change_values = [change_5m_value, change_15m_value, change_1h_value, change_4h_value, change_1d_value]\n\n for i, change in enumerate(changes):\n if change_values[i] > 0:\n operator = \"+\"\n color = Colors.color_green\n elif change_values[i] < 0:\n operator = \"\"\n color = Colors.color_pink\n else:\n operator = \"\"\n color = Colors.color_grey\n\n # print(str(change))\n change.setText(\"<span style='color: \" + color + \"'>\" + operator + \"{0:.2f}\".format(change_values[i]) + \"%</span\")","def modify(request, invoice_number):\n if request.method == \"POST\":\n n = Invoice.objects.filter(number=request.POST[\"invoice_number\"])\n items = n.get().items\n\n for i, item in enumerate(items):\n item[\"short_description\"] = request.POST[str(i + 1) + \"_short_description\"]\n item[\"particulars\"] = request.POST[str(i + 1) + \"_particulars\"]\n item[\"quantity\"] = request.POST[str(i + 1) + \"_quantity\"]\n item[\"unit\"] = request.POST[str(i + 1) + \"_unit\"]\n item[\"unit_price\"] = request.POST[str(i + 1) + \"_unit_price\"]\n item[\"total_cost\"] = request.POST[str(i + 1) + \"_total_cost\"]\n\n n.update(\n number=request.POST[\"invoice_number\"],\n invoice_date=request.POST[\"invoice_date\"],\n reference_number=request.POST[\"reference_number\"],\n reference_date=request.POST[\"reference_date\"],\n addressed_to=request.POST[\"addressed_to\"],\n party_gst=request.POST[\"party_gst\"],\n items=items,\n c_gst=request.POST[\"c_gst\"],\n s_gst=request.POST[\"s_gst\"],\n other_charges=request.POST[\"other_charges\"],\n notes=request.POST[\"additional_notes\"],\n total=request.POST[\"total\"],\n modified_at=datetime.datetime.now()\n )\n return redirect(\"index_page\")\n\n data = Invoice.objects.get(number=invoice_number)\n\n sub_total = sum([a.get(\"total_cost\") for a in data.items])\n\n return render(request,\n \"invoice/invoice_modify.html\",\n {\n \"invoice\": data,\n \"sub_total\": sub_total\n })","def test_fetch_order_prices_when_tax_exemption_and_include_taxes_in_prices(\n plugins_manager,\n fetch_kwargs,\n order_with_lines,\n tax_data,\n):\n # given\n currency = order_with_lines.currency\n discount_amount = Decimal(\"3.00\")\n order_with_lines.discounts.create(\n value=discount_amount,\n amount_value=discount_amount,\n currency=order_with_lines.currency,\n )\n order_with_lines.total_net_amount = Decimal(\"0.00\")\n order_with_lines.total_gross_amount = Decimal(\"0.00\")\n order_with_lines.undiscounted_total_net_amount = Decimal(\"0.00\")\n order_with_lines.undiscounted_total_gross_amount = Decimal(\"0.00\")\n order_with_lines.tax_exemption = True\n order_with_lines.save()\n plugins_manager.get_taxes_for_order = Mock(return_value=tax_data)\n\n # when\n calculations.fetch_order_prices_if_expired(**fetch_kwargs)\n\n # then\n order_with_lines.refresh_from_db()\n shipping_price = get_taxed_money(\n tax_data, \"shipping_price\", currency, exempt_taxes=True\n )\n assert order_with_lines.shipping_price == shipping_price\n assert order_with_lines.shipping_tax_rate == Decimal(\"0.00\")\n subtotal = zero_taxed_money(currency)\n undiscounted_subtotal = zero_taxed_money(currency)\n\n for order_line, tax_line in zip(order_with_lines.lines.all(), tax_data.lines):\n line_total = get_taxed_money(tax_line, \"total\", currency, exempt_taxes=True)\n subtotal += line_total\n undiscounted_subtotal += order_line.undiscounted_total_price\n assert order_line.total_price == line_total\n assert order_line.unit_price == line_total / order_line.quantity\n assert order_line.tax_rate == Decimal(\"0.00\")\n\n assert (\n order_with_lines.undiscounted_total\n == undiscounted_subtotal + shipping_price.net\n )\n assert order_with_lines.total == subtotal + shipping_price","def _compute_amount(self, base_amount, price_unit, quantity=1.0, product=None, partner=None):\n\n self.ensure_one()\n\n if self.amount_type != 'margin':\n return super(AccountTax, self)._compute_amount(\n base_amount,\n price_unit,\n quantity=quantity,\n product=product,\n partner=partner\n )\n\n return base_amount - (base_amount / (1 + self.amount / 100))","def recalc_for_bird(self, early_bird):\n \n if early_bird.eb_discount and early_bird.eb_expanding:\n rates_eb = self.get_rates()\n if early_bird.discount_type == 1:\n if rates_eb:\n rates = []\n for rate in rates_eb:\n if early_bird.eb_discount > 0:\n rate *= Decimal(str(early_bird.eb_discount)) / 100\n else:\n rate += rate * Decimal(str(early_bird.eb_discount)) / 100\n rates.append(str(rate))\n self.rates = u';'.join(rates)\n\n if early_bird.discount_type == 0:\n if rates_eb:\n rates = []\n for rate in rates_eb:\n rate += Decimal(str(early_bird.eb_discount))\n rates.append(str(rate))\n self.rates = u';'.join(rates)\n return self.rates","def trade(self, trigger_function, trigger_point, **trigger_function_kwargs):\n for date in self.tc.dates[1:]:\n # If the previous-day close allocation is out of tolerance..\n if trigger_function(self.df.shift(1).loc[date, 'allocations'].values, self.target_weights,\n **trigger_function_kwargs) > trigger_point:\n # then rebalance the portfolio\n trade = self.rebalance(date)\n self.trades.loc[date] = trade\n # When the trading is finished, we update the daily returns of the portfolio\n self.df['returns'] = self.df['values'].sum(axis=1).pct_change(1).fillna(0)","def test_companies_company_id_data_tax_rates_get(self):\n pass","def update_order_undiscounted_price(apps, schema_editor):\n\n def on_migrations_complete(sender=None, **kwargs):\n order_ids = list(kwargs.get(\"updated_orders_pks\"))\n send_order_updated.delay(order_ids)\n\n Order = apps.get_model(\"order\", \"Order\")\n OrderLine = apps.get_model(\"order\", \"OrderLine\")\n\n # Take orders that has applied lines voucher discounts, but the discount is\n # not visible in undiscounted price.\n orders_to_update = Order.objects.filter(\n Exists(\n OrderLine.objects.filter(\n order_id=OuterRef(\"id\"), voucher_code__isnull=False\n )\n ),\n total_gross_amount=F(\"undiscounted_total_gross_amount\"),\n ).order_by(\"id\")\n\n updated_orders_pks = []\n for batch_pks in queryset_in_batches(orders_to_update):\n orders = Order.objects.filter(pk__in=batch_pks)\n lines = OrderLine.objects.filter(order_id__in=orders.values(\"id\")).values(\n \"order_id\",\n \"undiscounted_total_price_gross_amount\",\n \"total_price_gross_amount\",\n \"undiscounted_total_price_net_amount\",\n \"total_price_net_amount\",\n )\n lines_discount_data = defaultdict(lambda: (0, 0))\n for data in lines:\n discount_amount_gross = (\n data[\"undiscounted_total_price_gross_amount\"]\n - data[\"total_price_gross_amount\"]\n )\n discount_amount_net = (\n data[\"undiscounted_total_price_net_amount\"]\n - data[\"total_price_net_amount\"]\n )\n current_discount_gross, current_discount_net = lines_discount_data[\n data[\"order_id\"]\n ]\n lines_discount_data[data[\"order_id\"]] = (\n current_discount_gross + discount_amount_gross,\n current_discount_net + discount_amount_net,\n )\n\n for order in orders:\n discount_amount_gross, discount_amount_net = lines_discount_data.get(\n order.id\n )\n if discount_amount_gross > 0 or discount_amount_net > 0:\n order.undiscounted_total_gross_amount += discount_amount_gross\n order.undiscounted_total_net_amount += discount_amount_net\n\n updated_orders_pks.append(order.id)\n\n Order.objects.bulk_update(\n orders,\n [\n \"undiscounted_total_gross_amount\",\n \"undiscounted_total_net_amount\",\n ],\n )\n\n # If we updated any order we should trigger `order_updated` after migrations\n if updated_orders_pks:\n updated_orders_pks = set(updated_orders_pks)\n sender = registry.get_app_config(\"order\")\n post_migrate.connect(\n partial(on_migrations_complete, updated_orders_pks=updated_orders_pks),\n weak=False,\n dispatch_uid=\"send_order_updated\",\n sender=sender,\n )","def _dynamic_price(self):\n adjust = PriceAdjustmentCalc(self)\n signals.satchmo_price_query.send(self, adjustment=adjust,\n slug=self.product.slug, discountable=self.product.is_discountable)\n return adjust.final_price()","def update_forces(self):\n\n pass","def tax_amount(self, tax_amount):\n\n self._tax_amount = tax_amount","def tax_amount(self, tax_amount):\n\n self._tax_amount = tax_amount","def sub_tax_sales_transfer_pricing(manager, df_fields, seq_recs, seq_reservas):\n # df_hotel = manager.get_dataframe(tables['dwc_bok_t_canco_hotel'])\n # df_circuit = manager.get_dataframe(tables['dwc_bok_t_canco_hotel_circuit'])\n # df_other = manager.get_dataframe(tables['dwc_bok_t_canco_other'])\n # df_transfer = manager.get_dataframe(tables['dwc_bok_t_canco_transfer'])\n # df_endow = manager.get_dataframe(tables['dwc_bok_t_canco_endowments'])\n # df_extra = manager.get_dataframe(tables['dwc_bok_t_canco_extra'])\n\n df_aux = df_fields.select(\"operative_incoming\", \"booking_id\")\n\n df_hotel = sub_tax_sales_transfer_pricing_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\n df_circuit = sub_tax_sales_transfer_pricing_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\n df_other = sub_tax_sales_transfer_pricing_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\n df_transfer = sub_tax_sales_transfer_pricing_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\n df_endow = sub_tax_sales_transfer_pricing_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\n df_extra = sub_tax_sales_transfer_pricing_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\n\n df_impuesto_canal = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\n df_extra)\n\n df_impuesto_canal = df_impuesto_canal.groupBy(\"seq_rec\", \"seq_reserva\") \\\n .agg({'impuesto_canal': 'sum'}).withColumnRenamed(\"SUM(impuesto_canal)\", \"Tax_Sales_Transfer_pricing\")\n\n df_fields = df_fields.join(df_impuesto_canal, [df_fields.operative_incoming == df_impuesto_canal.seq_rec,\n df_fields.booking_id == df_impuesto_canal.seq_reserva],\n 'left_outer').drop(df_impuesto_canal.seq_rec).drop(df_impuesto_canal.seq_reserva)\n\n df_fields = df_fields.na.fill({\"Tax_Sales_Transfer_pricing\": 0})\n\n df_fields = df_fields.withColumn(\"Tax_Sales_Transfer_pricing\",\n udf_round_ccy(df_fields.Tax_Sales_Transfer_pricing,\n df_fields.booking_currency))\n\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canal\n\n return df_fields","def compare(self):\n self.PotTax_increase = self.PotTax_intervention - self.PotTax_reference\n self.PotTax_percentage = (\n (self.PotTax_increase / self.PotTax_reference) * 100)\n \"\"\"\n # this sets the PotTax_percentage to actual percentages.\n self.PotTax_percentage['TFI'] = pd.Series(\n [\"{0:.2f}%\".format(val * 100) for val in\n self.PotTax_percentage['TFI']],\n index = self.PotTax_percentage.index)\n \"\"\"\n return","def updateLastPrice(self):\n dt = datetime.now(tz=pytz.UTC).replace(microsecond=0)\n\n dt_central = dt.astimezone(\n pytz.timezone('US/Central')).strftime(\"%H:%M\")\n\n # UPDATE POSITION LAST PRICE AND UPDATE HIGH PRICE\n open_positions = self.open_positions.find(\n {\"Trader\": self.user[\"Name\"], \"Asset_Type\": self.asset_type, \"Account_ID\": self.account_id})\n\n open_positions_list = []\n\n for position in open_positions:\n\n symbol = position[\"Symbol\"]\n\n if symbol not in open_positions_list:\n\n open_positions_list.append(symbol)\n\n if len(open_positions_list) > 0:\n\n resp = self.tdameritrade.getQuotes(open_positions_list)\n\n if resp:\n\n for key, value in resp.items():\n\n symbol = key\n\n last_price = value[\"lastPrice\"]\n\n self.open_positions.update_many({\"Trader\": self.user[\"Name\"], \"Symbol\": symbol, \"Asset_Type\": self.asset_type, \"Account_ID\": self.account_id}, {\n \"$set\": {\"Last_Price\": last_price}})\n\n if dt_central == \"15:00\":\n\n self.open_positions.update_many({\"Trader\": self.user[\"Name\"], \"Symbol\": symbol, \"Asset_Type\": self.asset_type, \"Account_ID\": self.account_id}, {\n \"$set\": {\"Opening_Price\": last_price}})\n\n # UPDATE QUEUE LAST PRICE\n queues = self.queue.find(\n {\"Trader\": self.user[\"Name\"], \"Asset_Type\": self.asset_type})\n\n queues_list = []\n\n for queue in queues:\n\n if self.asset_type == \"EQUITY\":\n\n symbol = queue[\"Symbol\"]\n\n elif self.asset_type == \"OPTION\":\n\n symbol = queue[\"Pre_Symbol\"]\n\n if symbol not in queues_list:\n\n queues_list.append(symbol)\n\n if len(queues_list) > 0:\n\n resp = self.tdameritrade.getQuotes(queues_list)\n\n for key, value in resp.items():\n\n symbol = key\n\n last_price = value[\"lastPrice\"]\n\n if self.asset_type == \"EQUITY\":\n\n self.queue.update_many({\"Trader\": self.user[\"Name\"], \"Symbol\": symbol, \"Asset_Type\": self.asset_type, \"Account_ID\": self.account_id}, {\n \"$set\": {\"Last_Price\": last_price}})\n\n elif self.asset_type == \"OPTION\":\n\n self.queue.update_many({\"Trader\": self.user[\"Name\"], \"Pre_Symbol\": symbol, \"Asset_Type\": self.asset_type, \"Account_ID\": self.account_id}, {\n \"$set\": {\"Last_Price\": last_price}})","def test_increasing_trend_is_true_if_price_increase_for_3_updates(self):\n self.given_a_series_of_prices([8, 10, 12])\n self.assertTrue(self.goog.is_increasing_trend())","def update_price_signals(self, monthly_data, time_series_data):\n if self.combined_market:\n try:\n fr_price = time_series_data.loc[:, 'FR Price ($/kW)']\n except KeyError:\n pass\n else:\n self.p_regu = np.divide(fr_price, 2)\n self.p_regd = np.divide(fr_price, 2)\n\n try:\n self.price = time_series_data.loc[:, 'DA Price ($/kWh)']\n except KeyError:\n pass\n else:\n try:\n self.p_regu = time_series_data.loc[:, 'Reg Up Price ($/kW)']\n except KeyError:\n pass\n\n try:\n self.p_regd = time_series_data.loc[:, 'Reg Down Price ($/kW)']\n except KeyError:\n pass\n\n try:\n self.price = time_series_data.loc[:, 'DA Price ($/kWh)']\n except KeyError:\n pass","def recompute_billing_lines(self, cr, uid, ids, partner_id, journal_id, price, currency_id, date, context=None):\n def _remove_noise_in_o2m():\n \"\"\"if the line is partially reconciled, then we must pay attention to display it only once and\n in the good o2m.\n This function returns True if the line is considered as noise and should not be displayed\n \"\"\"\n if line.reconcile_partial_id:\n sign = 1\n if currency_id == line.currency_id.id:\n if line.amount_residual_currency * sign <= 0:\n return True\n else:\n if line.amount_residual * sign <= 0:\n return True\n return False\n\n if context is None:\n context = {}\n billing_date_condition = context.get('billing_date_condition', [])\n context_multi_currency = context.copy()\n if date:\n context_multi_currency.update({'date': date})\n\n currency_pool = self.pool.get('res.currency')\n move_line_pool = self.pool.get('account.move.line')\n partner_pool = self.pool.get('res.partner')\n journal_pool = self.pool.get('account.journal')\n line_pool = self.pool.get('account.billing.line')\n\n #set default values\n default = {\n 'value': {'line_cr_ids': [] },\n }\n\n #drop existing lines\n line_ids = ids and line_pool.search(cr, uid, [('billing_id', '=', ids[0])]) or False\n if line_ids:\n line_pool.unlink(cr, uid, line_ids)\n\n if not partner_id or not journal_id:\n return default\n\n journal = journal_pool.browse(cr, uid, journal_id, context=context)\n partner = partner_pool.browse(cr, uid, partner_id, context=context)\n currency_id = currency_id or journal.company_id.currency_id.id\n account_id = False\n if journal.type in ('sale','sale_refund'):\n account_id = partner.property_account_receivable.id\n elif journal.type in ('purchase', 'purchase_refund','expense'):\n account_id = partner.property_account_payable.id\n else:\n account_id = journal.default_credit_account_id.id or journal.default_debit_account_id.id\n\n default['value']['account_id'] = account_id\n\n if journal.type not in ('cash', 'bank'):\n return default\n\n total_credit = price or 0.0\n account_type = 'receivable'\n\n if not context.get('move_line_ids', False):\n ids = move_line_pool.search(cr, uid, \n [('state','=','valid'), ('account_id.type', '=', account_type), ('reconcile_id', '=', False), ('partner_id', '=', partner_id), \n ] + billing_date_condition, \n context=context)\n else:\n ids = context['move_line_ids']\n invoice_id = context.get('invoice_id', False)\n company_currency = journal.company_id.currency_id.id\n move_line_found = False\n\n #order the lines by most old first\n ids.reverse()\n account_move_lines = move_line_pool.browse(cr, uid, ids, context=context)\n\n #compute the total debit/credit and look for a matching open amount or invoice\n for line in account_move_lines:\n if _remove_noise_in_o2m():\n continue\n\n if invoice_id:\n if line.invoice.id == invoice_id:\n #if the invoice linked to the billing line is equal to the invoice_id in context\n #then we assign the amount on that line, whatever the other billing lines\n move_line_found = line.id\n break\n elif currency_id == company_currency:\n #otherwise treatments is the same but with other field names\n if line.amount_residual == price:\n #if the amount residual is equal the amount billing, we assign it to that billing\n #line, whatever the other billing lines\n move_line_found = line.id\n break\n #otherwise we will split the billing amount on each line (by most old first)\n total_credit += line.credit or 0.0\n elif currency_id == line.currency_id.id:\n if line.amount_residual_currency == price:\n move_line_found = line.id\n break\n total_credit += line.credit and line.amount_currency or 0.0\n\n #billing line creation\n for line in account_move_lines:\n\n if _remove_noise_in_o2m():\n continue\n\n if line.currency_id and currency_id==line.currency_id.id:\n amount_original = abs(line.amount_currency)\n amount_unreconciled = abs(line.amount_residual_currency)\n else:\n amount_original = currency_pool.compute(cr, uid, company_currency, currency_id, line.credit or 0.0)\n amount_unreconciled = currency_pool.compute(cr, uid, company_currency, currency_id, abs(line.amount_residual))\n line_currency_id = line.currency_id and line.currency_id.id or company_currency\n rs = {\n 'move_line_id':line.id,\n 'type': line.credit and 'dr' or 'cr',\n 'reference':line.invoice.reference,\n 'account_id':line.account_id.id,\n 'amount_original': amount_original,\n 'amount': (move_line_found == line.id) and min(abs(price), amount_unreconciled) or amount_unreconciled,\n 'date_original':line.date,\n 'date_due':line.date_maturity,\n 'amount_unreconciled': amount_unreconciled,\n 'currency_id': line_currency_id,\n }\n \n # Negate DR records\n if rs['type'] == 'dr':\n rs['amount_original'] = - rs['amount_original']\n rs['amount'] = - rs['amount']\n rs['amount_unreconciled'] = - rs['amount_unreconciled']\n\n if rs['amount_unreconciled'] == rs['amount']:\n rs['reconcile'] = True\n else:\n rs['reconcile'] = False\n\n default['value']['line_cr_ids'].append(rs)\n\n# if ttype == 'payment' and len(default['value']['line_cr_ids']) > 0:\n# default['value']['pre_line'] = 1\n# elif ttype == 'receipt' and len(default['value']['line_dr_ids']) > 0:\n# default['value']['pre_line'] = 1\n default['value']['billing_amount'] = self._compute_billing_amount(cr, uid, default['value']['line_cr_ids'], price)\n return default","def recalcRelativeRates(self):\n #---+----|----+----|----+----|----+----|----+----|----+----|----+----|\n TreeLikelihoodBase.recalcRelativeRates(self)","def generate_orders(self, cr, uid, ids, context=None):\n voucher_pool = self.pool.get('account.voucher')\n payment_term_obj = self.pool.get('account.payment.term')\n account_budget_confirmation_obj = self.pool.get('account.budget.confirmation')\n period_obj = self.pool.get('account.period')\n if context is None:\n context = {}\n for order in self.browse(cr, uid, ids, context=context):\n #################################to remind\n total_fixed = total_percent = 0\n for line in order.payment_term.line_ids:\n if line.value == 'fixed':\n total_fixed += line.value_amount\n if line.value == 'procent':\n total_percent += line.value_amount\n total_fixed = (total_fixed * 100) / (order.amount or 1.0)\n if (total_fixed + total_percent) > 100:\n raise orm.except_orm(_('Error!'), _(\"Can not create the payments !\\n\\\n The related payment term is probably miss configured as it gives a computed amount greater than the total permanent payment amount. \\\n The latest line of your payment term must be of type 'balance' to avoid rounding issues.\"))\n # create one move line for the total and possibly adjust the other lines amount\n totlines1 = []\n for o in order.line_ids:\n totlines1 += payment_term_obj.compute(cr, uid, order.payment_term.id, o.amount, order.date or False, context=context)\n \n d = {}\n for k, v in totlines1:\n d.setdefault(k, [k]).append(v)\n totlines = map(tuple, d.values())\n\n for t in totlines :\n #to substract date from the interval number \n order_date = t[0]\n entered_date = datetime.datetime.strptime(order_date, '%Y-%m-%d')\n entered_date = entered_date.date()\n account_id = (order.partner_id.property_account_payable and order.partner_id.property_account_payable.id) or \\\n (order.journal_id.default_credit_account_id and order.journal_id.default_credit_account_id.id)\n period_id = period_obj.find(cr, uid, t[0], context=context)[0]\n\n list_confirm = [conf.id for conf in o.confirmation_ids]\n confirmations = account_budget_confirmation_obj.search(cr, uid, [('id','in', list_confirm),('period_id','=', period_id)], context=context) #('date','=',t[0]),\n\n for confirm in confirmations:\n confirm_id = confirm\n\n voucher_lines = [(0, 0, {'name':ol.name, 'account_id':ol.account_id.id, 'type':'dr',\n 'amount':t[count + 1], 'account_analytic_id':ol.account_analytic_id.id, 'budget_confirm_id': confirm_id })\n for count, ol in enumerate(order.line_ids)]\n res = voucher_pool.onchange_price(cr, uid, 0, voucher_lines, [], partner_id=order.partner_id.id, context=context).get(\"value\", {})\n voucher_dict = {\n 'partner_id' : order.partner_id.id,\n 'account_id': account_id,\n 'company_id' : order.company_id.id,\n 'journal_id' : order.journal_id.id,\n 'period_id': order.period_id.id,\n 'type':'purchase',\n 'date' : t[0],\n 'reference': order.name,\n 'payment_permanent_voucher_id': order.id,\n 'line_ids':voucher_lines,\n 'amount':res.get(\"amount\", 0.0)\n }\n voucher_pool.create(cr, uid, voucher_dict, context=context)\n return self.write(cr, uid, ids, {'state':'done'}, context=context)","def total(self) -> float:\n\n remained_to_be_taxed = self.income\n # taxed = list()\n self.tax_amounts = []\n start_tax_range = 0\n end_tax_range = self.bracket\n\n for i, b in enumerate(self.bracket):\n\n amount_to_tax = b.end - start_tax_range\n t = Taxed(min(amount_to_tax, remained_to_be_taxed), b.rate,\n min(amount_to_tax, remained_to_be_taxed) * b.rate)\n self.tax_amounts.append(t)\n # print(i, start_t ax_range, b.end, amount_to_tax, b.rate)\n\n remained_to_be_taxed -= amount_to_tax\n # print(remained_to_be_taxed)\n\n if b.end > self.income:\n break\n\n start_tax_range = b.end\n\n # print(taxed)\n return sum([t.tax for t in self.tax_amounts])","def vat_change_fiscal_requirements(self, cr, uid, ids, value, context=None):\n if context is None:\n context={}\n if not value:\n return super(res_partner,self).vat_change(cr, uid, ids, value, context=context)\n res = self.search(cr, uid, [('vat', 'ilike', value)])\n if res:\n rp = self.browse(cr, uid, res[0],context=context)\n return {'warning': {\n 'title':_('Vat Error !'),\n 'message':_('The VAT [%s] looks like '%value + \n '[%s] which is'%rp.vat.upper()+\n ' already being used by: %s'%rp.name.upper())\n }\n }\n else:\n return super(res_partner,self).vat_change(cr, uid, ids, value, context=context)","def recalc_for_bird(self, early_bird):\n\n if early_bird.cs_discount and early_bird.cs_expanding:\n rates_cs = self.get_rates()\n if early_bird.discount_type == 1:\n if rates_cs:\n rates = []\n for rate in rates_cs:\n if early_bird.cs_discount > 0:\n rate *= Decimal(str(early_bird.cs_discount)) / 100\n else:\n rate += rate * Decimal(str(early_bird.cs_discount)) / 100\n rates.append(str(rate))\n self.rates = u';'.join(rates)\n\n if early_bird.discount_type == 0:\n if rates_cs:\n rates = []\n for rate in rates_cs:\n rate += Decimal(str(early_bird.cs_discount))\n rates.append(str(rate))\n self.rates = u';'.join(rates)\n return self.rates","def recalc_for_bird(self, early_bird):\n\n if early_bird.cs_discount and early_bird.cs_expanding:\n rates_cs = self.get_rates()\n if early_bird.discount_type == 1:\n if rates_cs:\n rates = []\n for rate in rates_cs:\n if early_bird.cs_discount > 0:\n rate *= Decimal(str(early_bird.cs_discount)) / 100\n else:\n rate += rate * Decimal(str(early_bird.cs_discount)) / 100\n rates.append(str(rate))\n self.rates = u';'.join(rates)\n\n if early_bird.discount_type == 0:\n if rates_cs:\n rates = []\n for rate in rates_cs:\n rate += Decimal(str(early_bird.cs_discount))\n rates.append(str(rate))\n self.rates = u';'.join(rates)\n return self.rates","def onchange_invoice(self):\n self.product_id = False\n self.date = self.invoice.date_invoice\n self.name = (self.invoice and self.invoice.reference) or ''\n self.analytic_account_id = False\n self.unit_amount = self.invoice.residual\n self.quantity = 1\n self.total_amount = self.unit_amount","def _update_quote(self):\n # If this is the first quote or a price is outside current price ladder,\n # reset the price ladder.\n if (self._quotes_row == 0 or (\n self._quotes_df.loc[self._quotes_row, 'ask_price'] > \\\n self._price_ladder[0] + .5 * self._config['tick_size']) or (\n self._quotes_df.loc[self._quotes_row, 'bid_price'] < \\\n self._price_ladder[-1] - .5 * self._config['tick_size'])):\n max_price = (self._quotes_df.loc[self._quotes_row, 'ask_price'] +\n self._config['tick_size'] * np.floor(\n (self._config['row_count'] - 1) / 2))\n self._price_ladder = np.linspace(\n max_price,\n max_price - (\n self._config['row_count'] - 1) * self._config['tick_size'],\n self._config['row_count'])\n self._price_ladder_df.iloc[:, [0, 1, 3, 4]] = ''\n self._price_ladder_df.iloc[:, 2] = [self._config[\n 'price_format'].format(x) for x in self._price_ladder]\n\n # Populate price ladder dataframe and update table cells.\n for i in range(self._config['row_count']):\n if math.isclose(self._price_ladder[i],\n self._quotes_df.loc[self._quotes_row, 'ask_price']):\n self._price_ladder_df.iloc[i, 3] = str(\n self._quotes_df.loc[self._quotes_row, 'ask_size'])\n else:\n self._price_ladder_df.iloc[i, 3] = ''\n if math.isclose(self._price_ladder[i],\n self._quotes_df.loc[self._quotes_row, 'bid_price']):\n self._price_ladder_df.iloc[i, 1] = str(\n self._quotes_df.loc[self._quotes_row, 'bid_size'])\n else:\n self._price_ladder_df.iloc[i, 1] = ''\n\n # Print this quote row and update counter.\n print(self._quotes_df.iloc[self._quotes_row, ].values)\n self._quotes_row += 1"],"string":"[\n \"def _compute_taxed_lst_price2(self):\\n company_id = self._context.get(\\n 'company_id', self.env.user.company_id.id)\\n for product in self:\\n product.taxed_lst_price = product.taxes_id.filtered(\\n lambda x: x.company_id.id == company_id).compute_all(\\n product.lst_price,\\n self.env.user.company_id.currency_id,\\n product=product)['total_included']\",\n \"def _compute_taxed_lst_price2(self):\\n company_id = self._context.get(\\n 'company_id', self.env.user.company_id.id)\\n for product in self:\\n product.taxed_lst_price2 = product.taxes_id.filtered(\\n lambda x: x.company_id.id == company_id).compute_all(\\n product.list_price2,\\n self.env.user.company_id.currency_id,\\n product=product)['total_included']\",\n \"def _compute_tax(self):\\n for line in self:\\n line.tax = (line.amount_untaxed * 14) / 100\",\n \"def _compute_amount(self):\\n for line in self:\\n price = line.price_unit * (1 - (line.discount or 0.0) / 100.0)\\n new_price = price\\n if line.lot_id and line.product_id.tracking in ['lot','serial']:\\n lot_id = self.env['stock.production.lot'].search([('name', '=', line.lot_id), ('product_id', '=', line.product_id.id)])\\n if lot_id.tax_ids.filtered(lambda tax: tax.amount_type == 'based_on_margin'):\\n if lot_id.cost_price:\\n new_price -= lot_id.cost_price\\n sh_tax = line.tax_id.filtered(lambda tax: tax.amount_type =='based_on_margin').compute_all(new_price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\\n taxes = line.tax_id.filtered(lambda tax: tax.amount_type !='based_on_margin').compute_all(price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\\n print(taxes)\\n line.update({\\n 'price_tax': sum(t.get('amount', 0.0) for t in taxes.get('taxes', [])) + sum(t.get('amount', 0.0) for t in sh_tax.get('taxes', [])),\\n 'price_total': taxes['total_included'],\\n 'price_subtotal': taxes['total_excluded'],\\n })\\n if self.env.context.get('import_file', False) and not self.env.user.user_has_groups('account.group_account_manager'):\\n line.tax_id.invalidate_cache(['invoice_repartition_line_ids'], [line.tax_id.id])\",\n \"def _onchange_price(self):\\n self.price_subtotal = self.price\",\n \"def _onchange_price_subtotal(self):\\n self.price = self.price_subtotal\",\n \"def pay_tax(self):\\n\\t\\t# the money comes from nowhere, settlers seem to have an infinite amount of money.\\n\\t\\t# see http://wiki.unknown-horizons.org/index.php/DD/Economy/Settler_taxing\\n\\t\\thappiness_tax_modifier = (float(self.happiness)-50)/200 + 1\\n\\t\\ttaxes = self.tax_base * happiness_tax_modifier * self.inhabitants * self.settlement.tax_setting\\n\\t\\ttaxes = int(round(taxes))\\n\\t\\tself.settlement.owner.inventory.alter(RES.GOLD_ID, taxes)\\n\\t\\tself.last_tax_payed = taxes\\n\\n\\t\\t# decrease happiness\\n\\t\\thappiness_decrease = taxes + self.tax_base + ((self.settlement.tax_setting-1)*10)\\n\\t\\thappiness_decrease = int(round(happiness_decrease))\\n\\t\\tself.inventory.alter(RES.HAPPINESS_ID, -happiness_decrease)\\n\\t\\tself._changed()\\n\\t\\tself.log.debug(\\\"%s: pays %s taxes, -happy: %s new happiness: %s\\\", self, taxes, \\\\\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t happiness_decrease, self.happiness)\",\n \"def test_client_tax_information_update(self):\\n pass\",\n \"def on_taxes_change(origin_matrix, changes_on_taxes):\\n new_taxes = origin_matrix[TAXES_IDX]\\n for idx in range(len(origin_matrix[0])):\\n if changes_on_taxes[idx] != None:\\n new_taxes[idx] = changes_on_taxes[idx]\\n return new_taxes\",\n \"def price_incl_tax(self, price_incl_tax):\\n\\n self._price_incl_tax = price_incl_tax\",\n \"def check_for_energy_tax_update(self):\\n\\t\\tisChanged = False\\n\\t\\t# TODO: discuss the validity of such approach when checking on the global optimality\\n\\t\\t# if self.currentEnergy < self._globalMinimumEnergy and self.currentTax == 0:\\n\\t\\tif self.currentEnergy < self._globalMinimumEnergy and self.contains_several_vertices(self.currentState):\\n\\t\\t\\toutput(\\\"\\\\t New global optimum registered: old value = {}, new value = {}, state = {}\\\"\\\\\\n\\t\\t\\t\\t\\t .format(str(self._globalMinimumEnergy),str(self.currentEnergy),self.getCurrentState()),isDebug=False)\\n\\t\\t\\tself._globalMinimumEnergy = self.currentEnergy\\n\\t\\t\\tself._globalMinimumState = copy(self.currentState)\\n\\t\\t\\tisChanged = True\\n\\t\\tif self.currentEnergy < self.localMinimumEnergy and not self.isAllZeros(self.currentState): #should we update global as well? Now I do it\\n\\t\\t\\toutput(\\\"\\\\t New local optimum registered: old value = {}, new value = {}, state = {}\\\"\\\\\\n\\t\\t\\t\\t\\t .format(self.localMinimumEnergy,self.currentEnergy,self.getCurrentState()),isDebug=False)\\n\\t\\t\\tself.localMinimumEnergy = self.currentEnergy\\n\\t\\t\\tself.localMinimumState = copy(self.currentState)\\n\\t\\t\\tself.localMinimumTax = self.currentTax\\n\\t\\t\\tisChanged = True\\n\\t\\treturn isChanged\",\n \"def compute_all(self, price_unit, currency=None, quantity=1.0, product=None, partner=None, margin=0.0):\\n\\n non_margin_taxes = self.filtered(lambda t: not t.on_margin)\\n\\n result = super(AccountTax, non_margin_taxes).compute_all(\\n price_unit,\\n currency=currency,\\n quantity=quantity,\\n product=product,\\n partner=partner\\n )\\n\\n margin_taxes = self - non_margin_taxes\\n if not margin_taxes:\\n return result\\n\\n if len(self) == 0:\\n company_id = self.env.user.company_id\\n else:\\n company_id = self[0].company_id\\n\\n if not currency:\\n currency = company_id.currency_id\\n\\n prec = currency.decimal_places\\n\\n round_tax = False if company_id.tax_calculation_rounding_method == 'round_globally' else True\\n if 'round' in self.env.context:\\n round_tax = bool(self.env.context['round'])\\n\\n if not round_tax:\\n prec += 5\\n\\n for tax in margin_taxes:\\n\\n tax_amount = tax._compute_amount(\\n margin,\\n price_unit,\\n quantity=quantity,\\n product=product,\\n partner=partner\\n )\\n if not round_tax:\\n tax_amount = round(tax_amount, prec)\\n else:\\n tax_amount = currency.round(tax_amount)\\n\\n result['taxes'].append({\\n 'id': tax.id,\\n 'name': tax.with_context(**{'lang': partner.lang} if partner else {}).name,\\n 'amount': tax_amount,\\n 'base': margin,\\n 'on_margin': True,\\n 'sequence': tax.sequence,\\n 'account_id': tax.account_id.id,\\n 'refund_account_id': tax.refund_account_id.id,\\n 'analytic': tax.analytic,\\n 'price_include': tax.price_include,\\n 'tax_exigibility': tax.tax_exigibility\\n })\\n\\n return result\",\n \"def update_totals(self, commit=False):\\n sub_total = 0.0\\n tax = 0.0\\n for item in self.invoice_items:\\n sub_total += float(item.total if item.total else 0)\\n tax += float(item.tax if item.tax else 0)\\n\\n self.tax = tax\\n self.sub_total = sub_total\\n self.total = float(self.tax) + float(self.sub_total)\\n\\n if commit:\\n db.session.add(self)\\n db.session.commit()\\n return True\",\n \"def count_taxes(self):\\n\\t\\tfor i in range (self._size):\\n\\t\\t\\ttmpState = copy(self.currentState)\\n\\t\\t\\ttmpState[i] = 1 - tmpState[i]\\n\\t\\t\\tself._taxes[i] = self.count_tax(state=tmpState)\",\n \"def _tick(self):\\n\\t\\tself.pay_tax()\\n\\t\\tself.inhabitant_check()\\n\\t\\tself.level_check()\",\n \"def change_price(self, value): \\n value = self.price\",\n \"def save_tax(request):\\n if request.method == \\\"POST\\\":\\n initial_data, data = process_request(request)\\n return render(request,\\n \\\"invoice/invoice_create.html\\\",\\n {\\n \\\"form\\\": InvoiceForm,\\n \\\"stage\\\": \\\"3\\\",\\n \\\"prev_data\\\": data,\\n \\\"initial_data\\\": initial_data\\n })\",\n \"def action_update_total(self):\\n for order in self:\\n amount_untaxed = 0.0\\n for line in order.order_line_ids:\\n amount_untaxed += line.price_subtotal\\n order.price_subtotal = amount_untaxed\",\n \"def update_taxes(origin_matrix, tax_percent_fees, tax_percent_interest):\\n new_taxes = np.zeros(len(origin_matrix[0]))\\n fees_paid = origin_matrix[FEES_IDX]\\n interest_paid_arr = origin_matrix[INTEREST_PAID_IDX]\\n taxes_on_fee = fees_paid * tax_percent_fees\\n taxes_on_interest = interest_paid_arr * tax_percent_interest\\n new_taxes = taxes_on_fee + taxes_on_interest\\n return new_taxes\",\n \"def test_client_tax_information_partial_update(self):\\n pass\",\n \"def onchange_on_margin(self):\\n\\n for tax in self:\\n\\n tax.amount_type = 'margin' if tax.on_margin else 'percent'\\n tax.price_include = tax.on_margin\\n tax.type_tax_use = 'sale' if tax.on_margin else 'none'\\n\\n if tax.on_margin:\\n tax.include_base_amount = False\",\n \"def base_price_incl_tax(self, base_price_incl_tax):\\n\\n self._base_price_incl_tax = base_price_incl_tax\",\n \"def m_ps_FieldsUpdated(self, sender, e):\\r\\n ltp = e.Fields.GetLastTradedPriceField()\\r\\n ltq = e.Fields.GetLastTradedQuantityField()\\r\\n print(\\\"ltp and ltq success...\\\")\\r\\n if ltp.HasChanged or ltq.HasChanged:\\r\\n print(ltp.Value, ltq.Value)\\r\\n ltp = ltp.Value\\r\\n ltpi = int(ltp.ToTicks())\\r\\n self.process_row({'time' :pd.datetime.now(), 'close' : ltpi}, key = \\\"nk\\\")\",\n \"def _compute_tax_id(self):\\n for order in self:\\n order.order_line._compute_tax_id()\",\n \"def calculate_taxes(self, proforma, technologies):\\n tax_calcs = copy.deepcopy(proforma)\\n # 1) Redistribute capital cost according to the DER's MACRS value to get depreciation\\n for der_inst in technologies:\\n tax_contribution = der_inst.tax_contribution(self.macrs_depreciation,\\n tax_calcs.index, self.start_year)\\n if tax_contribution is not None:\\n tax_calcs = pd.concat([tax_calcs, tax_contribution], axis=1)\\n # 2) calculate yearly_net (taking into account the taxable contribution of each technology\\n # asset)\\n yearly_net = tax_calcs.sum(axis=1)\\n tax_calcs['Taxable Yearly Net'] = yearly_net\\n\\n # 3) Calculate State tax based on the net cash flows in each year\\n tax_calcs['State Tax Burden'] = yearly_net * -self.state_tax_rate\\n\\n # 4) Calculate Federal tax based on the net cash flow in each year minus State taxes\\n # from that year\\n yearly_net_post_state_tax = yearly_net + tax_calcs['State Tax Burden']\\n tax_calcs['Federal Tax Burden'] = yearly_net_post_state_tax * -self.federal_tax_rate\\n\\n # 5) Add the overall tax burden (= state tax + federal tax) to proforma\\n tax_calcs['Overall Tax Burden'] = tax_calcs['State Tax Burden'] + tax_calcs['Federal Tax Burden']\\n proforma['State Tax Burden'] = tax_calcs['State Tax Burden']\\n proforma['Federal Tax Burden'] = tax_calcs['Federal Tax Burden']\\n proforma['Overall Tax Burden'] = tax_calcs['Overall Tax Burden']\\n self.tax_calculations = tax_calcs\\n return proforma\",\n \"def after_tax_profit(self):\\n _after_tax_profit = self.before_tax_profit() * (1 - self.tax_rate)\\n return _after_tax_profit\",\n \"def apply_tax(order_obj):\\n tax_rule = taxes.get()\\n all_credits = order_obj.credits\\n other_credit = filter(lambda x: x[\\\"coll_name\\\"] != taxes.TaxRule.coll_name(), all_credits)\\n\\n if tax_rule is not None:\\n order_obj.credits = other_credit + [{\\n \\\"obj_id\\\": tax_rule._id,\\n \\\"coll_name\\\": taxes.TaxRule.coll_name(),\\n \\\"amount\\\": taxes.amount(tax_rule, order_obj),\\n }]\\n else:\\n order_obj.credits = other_credit\",\n \"def calculate_and_save(self):\\n # Calculate the quotation price\\n self.quotationPrice = self.compute_quotation_price()\\n self.save()\",\n \"def _compute_amount(self):\\n for line in self:\\n price = line.price_unit * (1 - (line.discount or 0.0) / 100.0)\\n taxes = line.tax_id.compute_all(price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\\n line.update({\\n 'price_tax': sum(t.get('amount', 0.0) for t in taxes.get('taxes', [])),\\n 'price_total': taxes['total_included'],\\n 'price_subtotal': taxes['total_excluded'],\\n })\\n if(line.is_discount_allow and line.price_subtotal > 100):\\n line.price_subtotal = line.price_subtotal - 100\",\n \"def _compute_amount(self):\\n for line in self:\\n price = line.price_unit\\n taxes = line.tax_id.compute_all(price, line.order_id.currency_id, line.product_uom_qty,\\n product=line.product_id, partner=line.order_id.partner_shipping_id)\\n self_price_subtotal = taxes['total_excluded']\\n if not line.discount_fixed_percent:\\n self_price_subtotal = self_price_subtotal\\n if line.discount_fixed_percent == 'Percent':\\n self_price_subtotal = self_price_subtotal * (1 - (line.discount or 0.0) / 100.0)\\n if line.discount_fixed_percent == 'Fixed':\\n self_price_subtotal = self_price_subtotal - line.discount_value\\n line.update({\\n 'price_tax': sum(t.get('amount', 0.0) for t in taxes.get('taxes', [])),\\n 'price_total': taxes['total_included'],\\n 'price_subtotal': self_price_subtotal,\\n })\",\n \"def default_get(self, cr, uid, fields_list, context=None):\\n\\t\\tif context is None:\\n\\t\\t\\tcontext = {}\\n\\t\\tdate_start = datetime.date.today().strftime('%Y-01-01')\\n\\t\\tdate_end = datetime.date.today().strftime('%Y-%m-%d')\\n\\n\\t\\tvalues = super(wizard_add_taxes, self).default_get(cr, uid, fields_list, context=context)\\n\\t\\ttax_ids = []\\n\\t\\tif (context.get('active_id',False)):\\n\\t\\t\\ttax_payment = self.pool.get('account.tax.payment').browse(cr,uid,context.get('active_id',False))\\n\\t\\t\\tcompany_id = tax_payment.company_id and tax_payment.company_id.id or False\\n\\t\\t\\ttax_ids = [t.id for t in tax_payment.tax_type]\\n\\t\\t\\tdate_end = tax_payment.date_end\\n\\t\\telse:\\n\\t\\t\\tuser = self.pool.get('res.users').browse(cr,uid,uid,context)\\n\\t\\t\\tcompany_id = user.company_id and user.company_id.id or False\\n\\t\\t\\ttax_ids=self.pool.get('account.tax').search(cr,uid,[('company_id','=',company_id)],context=context)\\n\\t\\ttax_account_ids=[]\\n\\t\\ttax_not_returned=[]\\n\\t\\ttax_code_account_ids = []\\n\\t\\ttax_code_unreturned = []\\n\\t\\tfor tax in self.pool.get('account.tax').browse(cr,uid,tax_ids,context):\\n\\t\\t\\tif not tax.inside_berikat and not tax.reported_unreturned:\\n\\t\\t\\t\\tif tax.account_collected_id and tax.account_collected_id.id:\\n\\t\\t\\t\\t\\ttax_account_ids.append(tax.account_collected_id.id)\\n\\t\\t\\t\\tif tax.account_paid_id and tax.account_paid_id.id:\\n\\t\\t\\t\\t\\ttax_account_ids.append(tax.account_paid_id and tax.account_paid_id.id)\\n\\t\\t\\t\\tif tax.tax_code_id and tax.tax_code_id.id:\\n\\t\\t\\t\\t\\ttax_code_account_ids.append(tax.tax_code_id.id)\\n\\t\\t\\t\\tif tax.ref_tax_code_id and tax.ref_tax_code_id.id:\\n\\t\\t\\t\\t\\ttax_code_account_ids.append(tax.ref_tax_code_id.id)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tif tax.account_collected_id and tax.account_collected_id.id:\\n\\t\\t\\t\\t\\ttax_not_returned.append(tax.account_collected_id and tax.account_collected_id.id)\\n\\t\\t\\t\\tif tax.account_paid_id and tax.account_paid_id.id:\\n\\t\\t\\t\\t\\ttax_not_returned.append(tax.account_paid_id and tax.account_paid_id.id)\\n\\t\\t\\t\\tif tax.tax_code_id and tax.tax_code_id.id:\\n\\t\\t\\t\\t\\ttax_code_unreturned.append(tax.tax_code_id and tax.tax_code_id.id)\\n\\t\\t\\t\\tif tax.ref_tax_code_id and tax.ref_tax_code_id.id:\\n\\t\\t\\t\\t\\ttax_code_unreturned.append(tax.ref_tax_code_id and tax.ref_tax_code_id.id)\\n\\t\\t\\t\\t#print \\\"tax_not_returned==============\\\",tax_not_returned\\n\\t\\ttax_account_ids = list(set(tax_account_ids))\\n\\t\\ttax_not_returned = list(set(tax_not_returned))\\n\\t\\ttax_code_account_ids = list(set(tax_code_account_ids))\\n\\t\\ttax_code_unreturned = list(set(tax_code_unreturned))\\n\\t\\tcompany = self.pool.get('res.company').browse(cr,uid,company_id,context)\\n\\t\\tif tax_account_ids or tax_not_returned:\\n\\t\\t\\tmove_id = self.pool.get('account.move').search(cr,uid,[('state','=','posted'),('date',\\\">=\\\",date_start),('date',\\\"<=\\\",date_end)])\\n\\t\\t\\texisting_payment_line_ids = self.pool.get('account.tax.payment.line').search(cr,uid,[],context=context)\\n\\t\\t\\texisting_payment_lines = [epm.move_line_id.id for epm in self.pool.get('account.tax.payment.line').browse(cr,uid,existing_payment_line_ids)]\\n\\t\\t\\texisting_statement_ids = self.pool.get('account.tax.payment').search(cr,uid,[],context=context)\\n\\t\\t\\texisting_statements_move = [esm.move_id.id for esm in self.pool.get('account.tax.payment').browse(cr,uid,existing_statement_ids)]\\n\\t\\t\\texisting_statement_move_lines = self.pool.get('account.move.line').search(cr,uid,[('move_id','in',existing_statements_move)])\\n\\t\\t\\texisting_payment_lines += existing_statement_move_lines\\n\\n\\n\\t\\ttax_lines_value=[]\\n\\n\\n\\t\\tif context.get('type',False) == 'tax_lines_cr':\\n\\t\\t\\tmove_lines = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\\\\n\\t\\t\\t\\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_account_ids),('account_id','in',tax_account_ids),\\\\\\n\\t\\t\\t\\t('state','=','valid'),('move_id','in',move_id),('debit','=',0.0),('credit',\\\">=\\\",0.0)])\\n\\t\\t\\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines,context=context):\\n\\t\\t\\t\\tmoves = line.move_id\\n\\t\\t\\t\\tinvoice_id=False\\n\\t\\t\\t\\tfor move_line in line.move_id.line_id:\\n\\t\\t\\t\\t\\tif move_line.invoice and move_line.invoice.id:\\n\\t\\t\\t\\t\\t\\tinvoice_id=move_line.invoice.id\\n\\t\\t\\t\\ttax_lines={\\n\\t\\t\\t\\t\\t\\\"name\\\"\\t\\t\\t\\t: line.name or line.ref or '/',\\n\\t\\t\\t\\t\\t\\\"move_line_id\\\"\\t\\t: line.id,\\n\\t\\t\\t\\t\\t\\\"invoice_id\\\"\\t\\t: invoice_id,\\n\\t\\t\\t\\t\\t\\\"amount\\\"\\t\\t\\t: line.debit or line.credit or 0.0,\\n\\t\\t\\t\\t\\t\\\"currency_id\\\"\\t\\t: line.currency_id and line.currency_id.id or False,\\n\\t\\t\\t\\t\\t\\\"amount_currency\\\"\\t: line.amount_currency or 0.0,\\n\\t\\t\\t\\t\\t\\\"effective_date\\\"\\t: line.date or False,\\n\\t\\t\\t\\t\\t\\\"partner_id\\\"\\t\\t: line.partner_id and line.partner_id.id or False,\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\ttax_lines_value.append(tax_lines)\\n\\t\\telif context.get('type',False) == 'tax_lines_dr':\\n\\t\\t\\tmove_lines = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\\\\n\\t\\t\\t\\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_account_ids),('account_id','in',tax_account_ids),\\\\\\n\\t\\t\\t\\t('state','=','valid'),('move_id','in',move_id),('debit','>=',0.0),('credit',\\\"=\\\",0.0)])\\n\\n\\t\\t\\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines,context=context):\\n\\t\\t\\t\\tmoves = line.move_id\\n\\t\\t\\t\\tinvoice_id=False\\n\\t\\t\\t\\tfor move_line in line.move_id.line_id:\\n\\t\\t\\t\\t\\tif move_line.invoice and move_line.invoice.id:\\n\\t\\t\\t\\t\\t\\tinvoice_id=move_line.invoice.id\\n\\t\\t\\t\\ttax_lines={\\n\\t\\t\\t\\t\\t\\\"name\\\"\\t\\t\\t\\t: line.name or line.ref or '/',\\n\\t\\t\\t\\t\\t\\\"move_line_id\\\"\\t\\t: line.id,\\n\\t\\t\\t\\t\\t\\\"invoice_id\\\"\\t\\t: invoice_id,\\n\\t\\t\\t\\t\\t\\\"amount\\\"\\t\\t\\t: line.debit or line.credit or 0.0,\\n\\t\\t\\t\\t\\t\\\"currency_id\\\"\\t\\t: line.currency_id and line.currency_id.id or False,\\n\\t\\t\\t\\t\\t\\\"amount_currency\\\"\\t: line.amount_currency or 0.0,\\n\\t\\t\\t\\t\\t\\\"effective_date\\\"\\t: line.date or False,\\n\\t\\t\\t\\t\\t\\\"partner_id\\\"\\t\\t: line.partner_id and line.partner_id.id or False,\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\ttax_lines_value.append(tax_lines)\\n\\t\\telif context.get('type',False) == 'tax_lines_cr_unr':\\n\\t\\t\\tmove_lines_unreturned = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\\\\n\\t\\t\\t\\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_unreturned),('account_id','in',tax_not_returned),\\\\\\n\\t\\t\\t\\t('state','=','valid'),('move_id','in',move_id),('debit','=',0.0),('credit',\\\">=\\\",0.0)])\\n\\t\\t\\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines_unreturned,context=context):\\n\\t\\t\\t\\tmoves = line.move_id\\n\\t\\t\\t\\tinvoice_id=False\\n\\t\\t\\t\\tfor move_line in line.move_id.line_id:\\n\\t\\t\\t\\t\\tif move_line.invoice and move_line.invoice.id:\\n\\t\\t\\t\\t\\t\\tinvoice_id=move_line.invoice.id\\n\\t\\t\\t\\ttax_lines={\\n\\t\\t\\t\\t\\t\\\"name\\\"\\t\\t\\t\\t: line.name or line.ref or '/',\\n\\t\\t\\t\\t\\t\\\"move_line_id\\\"\\t\\t: line.id,\\n\\t\\t\\t\\t\\t\\\"invoice_id\\\"\\t\\t: invoice_id,\\n\\t\\t\\t\\t\\t\\\"amount\\\"\\t\\t\\t: line.debit or line.credit or 0.0,\\n\\t\\t\\t\\t\\t\\\"currency_id\\\"\\t\\t: line.currency_id and line.currency_id.id or False,\\n\\t\\t\\t\\t\\t\\\"amount_currency\\\"\\t: line.amount_currency or 0.0,\\n\\t\\t\\t\\t\\t\\\"effective_date\\\"\\t: line.date or False,\\n\\t\\t\\t\\t\\t\\\"partner_id\\\"\\t\\t: line.partner_id and line.partner_id.id or False,\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\ttax_lines_value.append(tax_lines)\\n\\t\\telif context.get('type',False) == 'tax_lines_dr_unr':\\n\\t\\t\\t#move_lines = self.pool.get('account.move.line').search(cr,uid,[('account_id','not in',tax_not_returned),('id','not in',existing_payment_lines),('credit',\\\"=\\\",0.0),('debit',\\\">=\\\",0.0),('date',\\\">=\\\",date_start),('date',\\\"<=\\\",date_end),(\\\"account_id\\\",'in',tax_account_ids),('move_id.state','=','posted'),('state','=','valid')],context=context)\\n\\t\\t\\t#move_lines_unreturned = self.pool.get('account.move.line').search(cr,uid,[('account_id','in',tax_not_returned),('id','not in',existing_payment_lines),('credit',\\\"=\\\",0.0),('debit',\\\">=\\\",0.0),('date',\\\">=\\\",date_start),('date',\\\"<=\\\",date_end),(\\\"account_id\\\",'in',tax_account_ids),('move_id.state','=','posted'),('state','=','valid')],context=context)\\n\\t\\t\\tmove_lines_unreturned = self.pool.get('account.move.line').search(cr,uid,[('id','not in',existing_payment_lines),\\\\\\n\\t\\t\\t\\t('date','>=',date_start),('date','<=',date_end),('tax_code_id','in',tax_code_unreturned),('account_id','in',tax_not_returned),\\\\\\n\\t\\t\\t\\t('state','=','valid'),('move_id','in',move_id),('debit','>=',0.0),('credit',\\\"=\\\",0.0)])\\n\\n\\t\\t\\tfor line in self.pool.get('account.move.line').browse(cr,uid,move_lines_unreturned,context=context):\\n\\t\\t\\t\\tmoves = line.move_id\\n\\t\\t\\t\\tinvoice_id=False\\n\\t\\t\\t\\tfor move_line in line.move_id.line_id:\\n\\t\\t\\t\\t\\tif move_line.invoice and move_line.invoice.id:\\n\\t\\t\\t\\t\\t\\tinvoice_id=move_line.invoice.id\\n\\t\\t\\t\\ttax_lines={\\n\\t\\t\\t\\t\\t\\\"name\\\"\\t\\t\\t\\t: line.name or line.ref or '/',\\n\\t\\t\\t\\t\\t\\\"move_line_id\\\"\\t\\t: line.id,\\n\\t\\t\\t\\t\\t\\\"invoice_id\\\"\\t\\t: invoice_id,\\n\\t\\t\\t\\t\\t\\\"amount\\\"\\t\\t\\t: line.debit or line.credit or 0.0,\\n\\t\\t\\t\\t\\t\\\"currency_id\\\"\\t\\t: line.currency_id and line.currency_id.id or False,\\n\\t\\t\\t\\t\\t\\\"amount_currency\\\"\\t: line.amount_currency or 0.0,\\n\\t\\t\\t\\t\\t\\\"effective_date\\\"\\t: line.date or False,\\n\\t\\t\\t\\t\\t\\\"partner_id\\\"\\t\\t: line.partner_id and line.partner_id.id or False,\\n\\t\\t\\t\\t\\t}\\n\\t\\t\\t\\ttax_lines_value.append(tax_lines)\\n\\t\\tvalues.update({'tax_move_line_ids':tax_lines_value})\\t\\n\\t\\t\\n\\t\\treturn values\",\n \"def update_on_save(sender, instance, created, **kwargs):\\n instance.order.update_grand_total()\",\n \"def updatePrice(self, isinkey, field, data, qtype):\\r\\n isin = isinkey[0:12]\\r\\n bond = regsToBondName[isin]\\r\\n if qtype == BloombergQuery.BID:\\r\\n # 1/ WE CACHE THE OLD PRICE\\r\\n self.updateCell(bond, 'OLDBID', self.df.at[bond, 'BID'])\\r\\n self.updateCell(bond, 'OLDASK', self.df.at[bond, 'ASK'])\\r\\n # 2/ WE CHECK IF PRICE CHANGED\\r\\n if bond in self.rfbonds:\\r\\n self.blptsAnalytics.get(isin + '@CBBT' + ' Corp', self.bbgPriceRFQuery)\\r\\n else:\\r\\n self.blptsPriceOnly.get(isin + BBGHand + ' Corp', self.bbgPriceOnlyQuery)\\r\\n elif qtype == BloombergQuery.PRICEONLY:\\r\\n data = data.astype(float)\\r\\n # for item, value in data.iteritems():\\r\\n # self.updateCell(bond,bbgToBdmDic[item],value)\\r\\n self.lock.acquire()\\r\\n for item, value in data.iteritems():\\r\\n self.df.at[bond, bbgToBdmDic[item]] = value\\r\\n self.lock.release()\\r\\n if (data['BID'] != self.df.at[bond, 'OLDBID']) or (data['ASK'] != self.df.at[bond, 'OLDASK']):\\r\\n if bond in SPECIALBONDS:\\r\\n self.blptsAnalytics.get(isin + BBGHand + ' Corp', self.bbgPriceSpecialQuery)\\r\\n else:\\r\\n self.blptsAnalytics.get(isin + BBGHand + ' Corp', self.bbgPriceQuery)\\r\\n # try:\\r\\n # self.blptsAnalytics.get(isin + BBGHand + ' Corp', self.bbgPriceQuery)\\r\\n # except:\\r\\n # print 'error asking analytics for ' + bond\\r\\n else:\\r\\n # print 'Update event without a price change for ' + bond\\r\\n pub.sendMessage('BOND_PRICE_UPDATE', message=MessageContainer(self.df.loc[bond]))\\r\\n elif qtype == BloombergQuery.RTGACC:\\r\\n for item, value in data.iteritems():\\r\\n self.updateCell(bond,bbgToBdmDic[item],value)\\r\\n else:#'ANALYTICS' or 'FIRSTPASS'\\r\\n data = data.astype(float)\\r\\n # try:\\r\\n # for item, value in data.iteritems():\\r\\n # self.updateCell(bond,bbgToBdmDic[item],value)\\r\\n # except:\\r\\n # print data\\r\\n self.lock.acquire()\\r\\n try:\\r\\n for item, value in data.iteritems():\\r\\n self.df.at[bond, bbgToBdmDic[item]] = value\\r\\n except:\\r\\n self.lock.release()\\r\\n print data\\r\\n self.lock.release()\\r\\n if bond in SINKABLEBONDS:\\r\\n #self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=data['BID'])\\r\\n self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=self.df.at[bond, 'BID'])\\r\\n self.bbgSinkRequest.get()\\r\\n self.updateCell(bond, 'ZB', float(self.bbgSinkRequest.output.values[0,0]))\\r\\n #self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=data['ASK'])\\r\\n # self.bbgSinkRequest.fillRequest(isin + ' Corp', ['YAS_ZSPREAD'], strOverrideField='YAS_BOND_PX', strOverrideValue=self.df.at[bond, 'ASK'])\\r\\n # self.bbgSinkRequest.get() \\r\\n # self.updateCell(bond, 'ZA', float(self.bbgSinkRequest.output.values[0,0]))\\r\\n if qtype == BloombergQuery.ANALYTICS:\\r\\n self.updateStaticAnalytics(bond)\",\n \"def tax(subtotal, discount):\\n return (subtotal - discount) * 0.12\",\n \"def Update(self, prices):\\n \\n if self._bdaqmid != None:\\n # check that we got new prices for this market this tick.\\n if (self._bdaqmid in prices[const.BDAQID] and\\n self._bfmid in prices[const.BFID]):\\n self._bdaqsels = [prices[const.BDAQID][self._bdaqmid][i]\\n for i in [s.id for s in self._bdaqsels]]\\n self._bfsels = [prices[const.BFID][self._bfmid][i]\\n for i in [s.id for s in self._bfsels]]\\n\\n # call the listener functions.\\n self.UpdateViews()\",\n \"def compute_all(self, price_unit, currency=None, quantity=1.0, product=None, partner=None):\\n if len(self) == 0:\\n company_id = self.env.user.company_id\\n else:\\n company_id = self[0].company_id\\n if not currency:\\n currency = company_id.currency_id\\n taxes = []\\n # By default, for each tax, tax amount will first be computed\\n # and rounded at the 'Account' decimal precision for each\\n # PO/SO/invoice line and then these rounded amounts will be\\n # summed, leading to the total amount for that tax. But, if the\\n # company has tax_calculation_rounding_method = round_globally,\\n # we still follow the same method, but we use a much larger\\n # precision when we round the tax amount for each line (we use\\n # the 'Account' decimal precision + 5), and that way it's like\\n # rounding after the sum of the tax amounts of each line\\n prec = currency.decimal_places\\n\\n # In some cases, it is necessary to force/prevent the rounding of the tax and the total\\n # amounts. For example, in SO/PO line, we don't want to round the price unit at the\\n # precision of the currency.\\n # The context key 'round' allows to force the standard behavior.\\n round_tax = False if company_id.tax_calculation_rounding_method == 'round_globally' else True\\n round_total = True\\n if 'round' in self.env.context:\\n round_tax = bool(self.env.context['round'])\\n round_total = bool(self.env.context['round'])\\n\\n if not round_tax:\\n prec += 5\\n\\n base_values = self.env.context.get('base_values')\\n if not base_values:\\n total_excluded = total_included = base = round(price_unit * quantity, prec)\\n else:\\n total_excluded, total_included, base = base_values\\n\\n # Sorting key is mandatory in this case. When no key is provided, sorted() will perform a\\n # search. However, the search method is overridden in account.tax in order to add a domain\\n # depending on the context. This domain might filter out some taxes from self, e.g. in the\\n # case of group taxes.\\n for tax in self.sorted(key=lambda r: r.sequence):\\n # Allow forcing price_include/include_base_amount through the context for the reconciliation widget.\\n # See task 24014.\\n price_include = self._context.get('force_price_include', tax.price_include)\\n\\n if tax.amount_type == 'group':\\n children = tax.children_tax_ids.with_context(base_values=(total_excluded, total_included, base))\\n ret = children.compute_all(price_unit, currency, quantity, product, partner)\\n total_excluded = ret['total_excluded']\\n base = ret['base'] if tax.include_base_amount else base\\n total_included = ret['total_included']\\n tax_amount = total_included - total_excluded\\n taxes += ret['taxes']\\n continue\\n\\n tax_amount = tax._compute_amount(base, price_unit, quantity, product, partner)\\n if not round_tax:\\n tax_amount = round(tax_amount, prec)\\n else:\\n tax_amount = currency.round(tax_amount)\\n\\n if price_include:\\n total_excluded -= tax_amount\\n base -= tax_amount\\n else:\\n total_included += tax_amount\\n\\n # Keep base amount used for the current tax\\n tax_base = base\\n\\n if tax.include_base_amount:\\n base += tax_amount\\n\\n taxes.append({\\n 'id': tax.id,\\n 'name': tax.with_context(**{'lang': partner.lang} if partner else {}).name,\\n 'amount': tax_amount,\\n 'base': tax_base,\\n 'sequence': tax.sequence,\\n 'account_id': tax.account_id.id,\\n 'refund_account_id': tax.refund_account_id.id,\\n 'analytic': tax.analytic,\\n 'price_include': tax.price_include,\\n 'tax_exigibility': tax.tax_exigibility,\\n })\\n\\n return {\\n 'taxes': sorted(taxes, key=lambda k: k['sequence']),\\n 'total_excluded': currency.round(total_excluded) if round_total else total_excluded,\\n 'total_included': currency.round(total_included) if round_total else total_included,\\n 'base': base,\\n }\",\n \"def calculateSingleTax(monthlyIncome):\\n pass\",\n \"def m_ts_OrderUpdated(self, sender, e):\\r\\n print(\\\"Order was updated with price of {0}.\\\".format(e.NewOrder.LimitPrice))\",\n \"def lineitem_post_save(**kwargs):\\n lineitem = kwargs['instance']\\n bill = lineitem.bill\\n bill.update_cached_totals()\",\n \"def tax(bill):\\r\\n bill *= 1.08\\r\\n print(\\\"With tax: %f\\\" % bill)\\r\\n return bill\",\n \"def _amount_all(self):\\r\\n for order in self:\\r\\n amount_untaxed = amount_tax = amount_discount = timbre = 0.0\\r\\n for line in order.order_line:\\r\\n amount_untaxed += line.price_subtotal\\r\\n if line.product_id.timbre_fiscal:\\r\\n amount_tax += line.price_tax - 0.60\\r\\n timbre = 0.60\\r\\n else :\\r\\n amount_tax += line.price_tax\\r\\n amount_discount += (line.product_uom_qty * line.price_unit * line.discount)/100\\r\\n order.update({\\r\\n 'amount_untaxed': order.pricelist_id.currency_id.round(amount_untaxed),\\r\\n 'amount_tax': order.pricelist_id.currency_id.round(amount_tax),\\r\\n 'amount_discount': order.pricelist_id.currency_id.round(amount_discount),\\r\\n 'price_total_no_discount': amount_untaxed + amount_discount,\\r\\n 'timbre': timbre,\\r\\n 'amount_total': amount_untaxed + amount_tax + timbre,\\r\\n })\",\n \"def test_updating_the_supply_price(self):\\n self.assertEqual(self.po.id, 1)\\n self.assertEqual(self.po.items.count(), 1)\\n item = self.po.items.all()[0]\\n self.assertEqual(item.id, 1)\\n self.assertEqual(item.unit_cost, Decimal('12.11'))\\n self.assertEqual(Log.objects.all().count(), 0)\\n \\n modified_po = copy.deepcopy(base_purchase_order)\\n modified_po['items'][0]['unit_cost'] = Decimal('10.05')\\n modified_po['items'][0]['id'] = 1\\n modified_po['status'] = 'PROCESSED'\\n del modified_po['items'][1]\\n resp = self.client.put('/api/v1/purchase-order/1/',\\n format='json',\\n data=modified_po)\\n self.assertEqual(resp.status_code, 200, msg=resp)\\n resp_obj = resp.data\\n self.assertEqual(resp_obj['revision'], 1)\\n #Check the new pdf\\n #webbrowser.get(\\\"open -a /Applications/Google\\\\ Chrome.app %s\\\").open(resp_obj['pdf']['url'])\\n \\n self.assertEqual(resp_obj['id'], 1)\\n self.assertEqual(resp_obj['supplier']['id'], 1)\\n self.assertEqual(resp_obj['vat'], 7)\\n self.assertEqual(resp_obj['discount'], 0)\\n self.assertEqual(resp_obj['revision'], 1)\\n self.assertEqual(Decimal(resp_obj['grand_total']), Decimal('107.54'))\\n self.assertEqual(len(resp_obj['items']), 1)\\n item1 = resp_obj['items'][0]\\n self.assertEqual(item1['id'], 1)\\n self.assertEqual(item1['quantity'], Decimal('10.0000000000'))\\n self.assertEqual(Decimal(item1['unit_cost']), Decimal('10.05'))\\n self.assertEqual(Decimal(item1['total']), Decimal('100.50'))\\n \\n #Confirm cost change for item and supply in the database\\n po = PurchaseOrder.objects.get(pk=1)\\n self.assertEqual(po.grand_total, Decimal('107.54'))\\n item1 = po.items.order_by('id').all()[0]\\n self.assertEqual(item1.id, 1)\\n self.assertEqual(item1.quantity, 10)\\n self.assertEqual(item1.unit_cost, Decimal('10.05'))\\n supply = item1.supply\\n supply.supplier = po.supplier\\n self.assertEqual(supply.cost, Decimal('10.05'))\\n \\n self.assertEqual(Log.objects.all().count(), 1)\\n log = Log.objects.all()[0]\\n self.assertEqual(log.cost, Decimal('10.05'))\\n self.assertEqual(log.supply, supply)\\n self.assertEqual(log.supplier, po.supplier)\\n self.assertEqual(log.message, \\\"Price change from 12.11USD to 10.05USD for Pattern: Maxx, Col: Blue [Supplier: Zipper World]\\\")\\n\\n # Confirm that there is still only one product for this supply and supplier\\n # in the database\\n products = Product.objects.filter(supply=supply, supplier=po.supplier)\\n self.assertEqual(len(products), 1)\",\n \"def tax(bill):\\n bill *= 1.08\\n print \\\"With tax: %f\\\" % bill\\n return bill\",\n \"def tax(bill):\\n bill *= 1.08\\n print \\\"With tax: %f\\\" % bill\\n return bill\",\n \"def validate(cls, prices):\\n super(GiftCardPrice, cls).validate(prices)\\n\\n for price in prices:\\n price.check_price()\",\n \"def updatePriceOfExistingStocks(self):\\n currentDate = str(datetime.now().strftime(\\\"%Y-%m-%d\\\"))\\n listOfStocks = self.retrieveAllDistinctStocks()\\n isPercentageChangeUpdated = self.checkIfPercentageChangesUpdated(\\n currentDate)\\n\\n if not isPercentageChangeUpdated:\\n print(\\\"PercentageChanges not updated. Commencing update now...\\\")\\n for stockSymbol, stockExchange in listOfStocks:\\n latestPercentageChange = self.getLatestPercentageChange(\\n stockSymbol, stockExchange, currentDate)\\n if latestPercentageChange is not None:\\n self.storeLatestPercentageChange(\\n stockSymbol, stockExchange, currentDate, latestPercentageChange)\\n print(\\\"{} updated.\\\".format(stockSymbol))\\n print(\\\"Update complete.\\\")\\n else:\\n print(\\\"Prices are already up to date.\\\")\",\n \"def do_change_standard_price(self, cr, uid, ids, new_price, context=None):\\n location_obj = self.pool.get('stock.location')\\n move_obj = self.pool.get('account.move')\\n move_line_obj = self.pool.get('account.move.line')\\n if context is None:\\n context = {}\\n user_company_id = self.pool.get('res.users').browse(cr,\\n uid, uid,\\n context=context).\\\\\\n company_id.id\\n loc_ids = location_obj.search(cr, uid,\\n [('usage', '=', 'internal'),\\n ('company_id', '=', user_company_id)])\\n for rec_id in ids:\\n datas = self.get_product_accounts(cr, uid, rec_id, context=context)\\n for location in location_obj.browse(cr, uid, loc_ids,\\n context=context):\\n contextc = context.copy()\\n contextc.update({'location': location.id,\\n 'compute_child': False})\\n product = self.browse(cr, uid, rec_id, context=contextc)\\n\\n diff = product.standard_price - new_price\\n if not diff:\\n continue\\n for prod_variant in product.product_variant_ids:\\n qty = prod_variant.qty_available\\n if qty:\\n # Accounting Entries\\n ref = '[{code}] {name}'.\\\\\\n format(code=prod_variant.default_code,\\n name=prod_variant.name)\\n move_vals = {\\n 'journal_id': datas['stock_journal'],\\n 'company_id': location.company_id.id,\\n 'ref': ref,\\n }\\n move_id = move_obj.create(cr, uid, move_vals,\\n context=context)\\n\\n if diff * qty > 0:\\n amount_diff = qty * diff\\n debit_account_id = \\\\\\n datas['property_difference_price_account_id']\\n credit_account_id = \\\\\\n datas['property_stock_valuation_account_id']\\n\\n else:\\n amount_diff = qty * -diff\\n debit_account_id = \\\\\\n datas['property_stock_valuation_account_id']\\n credit_account_id = \\\\\\n datas['property_difference_price_account_id']\\n\\n move_line_obj.create(cr, uid, {\\n 'name': _('Standard Price changed'),\\n 'account_id': debit_account_id,\\n 'debit': amount_diff,\\n 'ref': ref,\\n 'credit': 0,\\n 'move_id': move_id, }, context=context)\\n move_line_obj.create(cr, uid, {\\n 'name': _('Standard Price changed'),\\n 'account_id': credit_account_id,\\n 'debit': 0,\\n 'ref': ref,\\n 'credit': amount_diff,\\n 'move_id': move_id\\n }, context=context)\\n self.write(cr, uid, rec_id, {'standard_price': new_price})\\n return True\",\n \"def create_or_find_b2b_invoices_and_process_ept(self, row, sale_order, invoice_date, tax):\\n\\n vat_number = row.get('Buyer Tax Registration', False)\\n invoice_number = row.get('VAT Invoice Number', False)\\n\\n invoices = sale_order.invoice_ids.filtered(\\n lambda x: x.type == 'out_invoice' and x.state != 'cancel')\\n if not invoices:\\n lines = sale_order.order_line.filtered(lambda line: line.qty_to_invoice > 0)\\n if not lines:\\n return False\\n invoices = sale_order._create_invoices()\\n self.write({'invoice_ids': [(4, invoices and invoices.id)]})\\n\\n for invoice in invoices:\\n if not invoice.partner_id.vat:\\n invoice.partner_id.vat = vat_number\\n\\n payments_lines = []\\n if invoice.invoice_payments_widget != 'false':\\n payments_dict = json.loads(invoice.invoice_payments_widget)\\n payments_content = payments_dict.get('content', [])\\n for line in payments_content:\\n payments_lines.append(line.get('payment_id', False))\\n\\n invoice_line = invoice.mapped('invoice_line_ids').filtered(\\\\\\n lambda line: line.tax_ids != tax)\\n if invoice_line:\\n invoice.button_draft()\\n invoice.write({'ref': invoice_number, 'date': invoice_date})\\n\\n if len(invoice_line) > 1:\\n for line in invoice_line:\\n line.with_context({'check_move_validity': False}).write( \\\\\\n {'tax_ids': [(6, 0, [tax.id])]})\\n else:\\n invoice_line.with_context({'check_move_validity': False}).write( \\\\\\n {'tax_ids': [(6, 0, [tax.id])]})\\n\\n invoice.with_context({'check_move_validity': False})._recompute_tax_lines( \\\\\\n recompute_tax_base_amount=True)\\n invoice.action_post()\\n for line in payments_lines:\\n invoice.js_assign_outstanding_line(line)\\n\\n return True\",\n \"def _amount_all(self):\\n for order in self:\\n amount_untaxed = 0.0\\n for line in order.order_items_ids:\\n amount_untaxed += line.price_subtotal\\n order.update({\\n 'amount_untaxed': amount_untaxed,\\n })\",\n \"def _compute_amount_subtotal(self):\\n for lines in self:\\n lines.price_subtotal = lines.price_unit * lines.order_qty\",\n \"def auto_process_vcs_tax_report(self, args={}):\\n seller_id = args.get('seller_id', False)\\n if seller_id:\\n seller = self.env['amazon.seller.ept'].search([('id', '=', seller_id)])\\n vcs_reports = self.search(\\n [('seller_id', '=', seller.id), ('state', 'in', ['_SUBMITTED_', '_IN_PROGRESS_'])])\\n if vcs_reports:\\n total_length = len(vcs_reports.ids)\\n for x in range(0, total_length, 20):\\n reports = vcs_reports[x:x + 20]\\n for report in reports:\\n report.get_report_request_list()\\n if report.filtered(lambda r: r.state == '_DONE_' and r.report_id != False):\\n try:\\n report.get_report()\\n\\n except Exception as e:\\n raise UserError(e)\\n time.sleep(2)\\n report.process_vcs_tax_report_file()\\n self._cr.commit()\\n time.sleep(3)\\n\\n else:\\n reports = self.search([('seller_id', '=', seller.id),\\n ('state', '=', '_DONE_'),\\n ], order='id asc')\\n for report in reports:\\n if not report.attachment_id:\\n while True:\\n try:\\n report.get_report()\\n break\\n except Exception as e:\\n raise UserError(e)\\n try:\\n report.process_vcs_tax_report_file()\\n self._cr.commit()\\n except:\\n continue\\n time.sleep(3)\\n return True\",\n \"def tax_override(self, tax_override):\\n\\n self._tax_override = tax_override\",\n \"def update_on_delete(sender, instance, **kwargs):\\n instance.order.update_grand_total()\",\n \"def sub_tax_cost_transfer_pricing(manager, df_fields, seq_recs, seq_reservas):\\n # df_hotel = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_hotel\\\"])\\n # df_circuit = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_hotel_circuit\\\"])\\n # df_other = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_other\\\"])\\n # df_transfer = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_transfer\\\"])\\n # df_endow = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_endowments\\\"])\\n # df_extra = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_extra\\\"])\\n\\n df_aux = df_fields.select(\\\"operative_incoming\\\", \\\"booking_id\\\", \\\"invoicing_company\\\", \\\"creation_date\\\",\\n \\\"booking_currency\\\")\\n\\n df_hotel = sub_tax_cost_transfer_pricing_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\\n df_circuit = sub_tax_cost_transfer_pricing_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\\n df_other = sub_tax_cost_transfer_pricing_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\\n df_transfer = sub_tax_cost_transfer_pricing_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\\n df_endow = sub_tax_cost_transfer_pricing_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\\n df_extra = sub_tax_cost_transfer_pricing_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\\n\\n df_impuesto_canco = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\\n df_extra)\\n\\n df_impuesto_canco = df_impuesto_canco.groupBy(\\\"operative_incoming\\\", \\\"booking_id\\\") \\\\\\n .agg({'impuesto_canco': 'sum'}).withColumnRenamed(\\\"SUM(impuesto_canco)\\\", \\\"impuesto_canco\\\")\\n\\n df_impuesto_canco = df_impuesto_canco.withColumnRenamed(\\\"operative_incoming\\\", \\\"seq_rec\\\") \\\\\\n .withColumnRenamed(\\\"booking_id\\\", \\\"seq_res\\\")\\n\\n # add impuesto_canco\\n df_fields = df_fields.join(df_impuesto_canco, [df_fields.operative_incoming == df_impuesto_canco.seq_rec,\\n df_fields.booking_id == df_impuesto_canco.seq_res],\\n 'left_outer').drop(\\\"seq_rec\\\", \\\"seq_res\\\")\\n\\n df_addcanco = sub_transfer_pricing_aux_add_canco(manager, df_fields, seq_recs, seq_reservas)\\n\\n df_addcanco = df_addcanco.withColumnRenamed(\\\"operative_incoming\\\", \\\"seq_rec\\\") \\\\\\n .withColumnRenamed(\\\"booking_id\\\", \\\"seq_res\\\")\\n\\n # add add_impuesto_canco\\n df_fields = df_fields.join(df_addcanco, [df_fields.operative_incoming == df_addcanco.seq_rec,\\n df_fields.booking_id == df_addcanco.seq_res],\\n \\\"left_outer\\\").drop(df_addcanco.seq_rec).drop(df_addcanco.seq_res)\\n\\n df_fields = df_fields.na.fill({'impuesto_canco': 0, 'add_impuesto_canco': 0})\\n\\n df_fields = df_fields.withColumn(\\\"Tax_Cost_Transfer_pricing\\\",\\n df_fields.impuesto_canco + df_fields.add_impuesto_canco) \\\\\\n .drop(\\\"impuesto_canco\\\", \\\"add_impuesto_canco\\\")\\n\\n df_fields = df_fields.withColumn(\\\"Tax_Cost_Transfer_pricing\\\", udf_round_ccy(df_fields.Tax_Cost_Transfer_pricing,\\n df_fields.booking_currency))\\n\\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canco, df_addcanco, df_aux\\n\\n return df_fields\",\n \"def save_change(self):\\n try:\\n self.customer.budget.income = abs(float(self.incomeItem.text()))\\n self.incomeItem.setText(f\\\"{self.customer.budget.income}\\\")\\n fixed_expenses = {\\n \\\"rent\\\": abs(float(self.listOfExpensesSEK.item(4).text())),\\n \\\"subscription\\\": abs(float(self.listOfExpensesSEK.item(2).text())),\\n \\\"insurance\\\": abs(float(self.listOfExpensesSEK.item(3).text())),\\n \\\"others\\\": abs(float(self.listOfExpensesSEK.item(5).text()))\\n }\\n variable_expenses = {\\n \\\"food\\\": abs(float(self.listOfExpensesSEK.item(11).text())),\\n \\\"bills\\\": abs(float(self.listOfExpensesSEK.item(12).text())),\\n \\\"transportation\\\": abs(float(self.listOfExpensesSEK.item(13).text())),\\n \\\"hygien\\\": abs(float(self.listOfExpensesSEK.item(14).text())),\\n \\\"clothes\\\": abs(float(self.listOfExpensesSEK.item(15).text())),\\n \\\"entertainment\\\": abs(float(self.listOfExpensesSEK.item(16).text())),\\n \\\"others\\\": abs(float(self.listOfExpensesSEK.item(17).text()))\\n }\\n self.customer.budget.set_budget(self.customer.budget.income,\\n variable_expenses, fixed_expenses)\\n # update instead of set\\n DB.update_variable_expenses(self.customer.email, variable_expenses)\\n DB.update_fixed_expenses(self.customer.email, fixed_expenses)\\n DB.update_income(self.customer.budget.income, self.customer.email)\\n total_fix, total_var = self.customer.budget.get_expenses()\\n self.listOfExpensesSEK.item(1).setText(total_fix)\\n self.listOfExpensesSEK.item(10).setText(total_var)\\n self.customer.budget.set_buffert(abs(float(\\n self.listOfExpensesSEK.item(20).text()\\n )))\\n DB.update_buffert(self.customer.email, abs(float(self.listOfExpensesSEK.item(20).text())))\\n self.label_3.setText(str(self.customer.budget.income -\\n self.customer.budget.get_total_expenses())\\n )\\n except Exception:\\n self.popUp.exec_()\",\n \"def re_process_vcs_tax_report_file(self):\\n log_line_obj = self.env['common.log.lines.ept']\\n model_id = log_line_obj.get_model_id('amazon.vcs.tax.report.ept')\\n records = log_line_obj.search([('model_id', '=', model_id), ('res_id', '=', self.id)])\\n records.unlink()\\n self.process_vcs_tax_report_file()\\n return True\",\n \"def sub_tax_cost_transfer_pricing_eur(manager, df_fields, seq_recs, seq_reservas):\\n # df_hotel = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_hotel\\\"])\\n # df_circuit = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_hotel_circuit\\\"])\\n # df_other = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_other\\\"])\\n # df_transfer = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_transfer\\\"])\\n # df_endow = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_endowments\\\"])\\n # df_extra = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_extra\\\"])\\n\\n df_aux = df_fields.select(\\\"operative_incoming\\\", \\\"booking_id\\\", \\\"invoicing_company\\\", \\\"creation_date\\\",\\n \\\"booking_currency\\\")\\n\\n df_hotel = sub_tax_transfer_pricing_eur_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\\n df_circuit = sub_tax_transfer_pricing_eur_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\\n df_other = sub_tax_transfer_pricing_eur_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\\n df_transfer = sub_tax_transfer_pricing_eur_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\\n df_endow = sub_tax_transfer_pricing_eur_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\\n df_extra = sub_tax_transfer_pricing_eur_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\\n\\n df_impuesto_canco = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\\n df_extra)\\n\\n df_impuesto_canco = df_impuesto_canco.groupBy(\\\"operative_incoming\\\", \\\"booking_id\\\") \\\\\\n .agg({'impuesto_canco': 'sum'}).withColumnRenamed(\\\"SUM(impuesto_canco)\\\", \\\"impuesto_canco\\\")\\n\\n df_impuesto_canco = df_impuesto_canco.withColumnRenamed(\\\"operative_incoming\\\", \\\"seq_rec\\\") \\\\\\n .withColumnRenamed(\\\"booking_id\\\", \\\"seq_res\\\")\\n\\n df_fields = df_fields.join(df_impuesto_canco, [df_fields.operative_incoming == df_impuesto_canco.seq_rec,\\n df_fields.booking_id == df_impuesto_canco.seq_res],\\n 'left_outer').drop(\\\"seq_rec\\\", \\\"seq_res\\\")\\n\\n df_addcanco = sub_transfer_pricing_aux_add_canco(manager, df_fields, seq_recs, seq_reservas, EUR)\\n\\n df_addcanco = df_addcanco.withColumnRenamed(\\\"operative_incoming\\\", \\\"seq_rec\\\") \\\\\\n .withColumnRenamed(\\\"booking_id\\\", \\\"seq_res\\\")\\n\\n # add add_impuesto_canco\\n df_fields = df_fields.join(df_addcanco, [df_fields.operative_incoming == df_addcanco.seq_rec,\\n df_fields.booking_id == df_addcanco.seq_res],\\n \\\"left_outer\\\").drop(df_addcanco.seq_rec).drop(df_addcanco.seq_res)\\n\\n df_fields = df_fields.na.fill({'impuesto_canco': 0, 'add_impuesto_canco': 0})\\n\\n df_fields = df_fields.withColumn(\\\"Tax_Cost_Transfer_pricing_EUR\\\",\\n df_fields.impuesto_canco + df_fields.add_impuesto_canco) \\\\\\n .drop(\\\"impuesto_canco\\\", \\\"add_impuesto_canco\\\")\\n\\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canco, df_addcanco\\n\\n return df_fields\",\n \"def sub_tax_transfer_pricing_eur(manager, df_fields, seq_recs, seq_reservas):\\n # df_hotel = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_hotel\\\"])\\n # df_circuit = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_hotel_circuit\\\"])\\n # df_other = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_other\\\"])\\n # df_transfer = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_transfer\\\"])\\n # df_endow = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_endowments\\\"])\\n # df_extra = manager.get_dataframe(tables[\\\"dwc_bok_t_canco_extra\\\"])\\n\\n df_aux = df_fields.select(\\\"operative_incoming\\\", \\\"booking_id\\\", \\\"invoicing_company\\\", \\\"creation_date\\\",\\n \\\"booking_currency\\\")\\n\\n df_hotel = sub_tax_transfer_pricing_eur_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\\n df_circuit = sub_tax_transfer_pricing_eur_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\\n df_other = sub_tax_transfer_pricing_eur_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\\n df_transfer = sub_tax_transfer_pricing_eur_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\\n df_endow = sub_tax_transfer_pricing_eur_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\\n df_extra = sub_tax_transfer_pricing_eur_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\\n\\n df_impuesto_canco = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\\n df_extra)\\n\\n df_impuesto_canco = df_impuesto_canco.groupBy(\\\"operative_incoming\\\", \\\"booking_id\\\") \\\\\\n .agg({'impuesto_canco': 'sum'}).withColumnRenamed(\\\"SUM(impuesto_canco)\\\", \\\"impuesto_canco\\\")\\n\\n df_impuesto_canco = df_impuesto_canco.withColumnRenamed(\\\"operative_incoming\\\", \\\"seq_rec\\\") \\\\\\n .withColumnRenamed(\\\"booking_id\\\", \\\"seq_res\\\")\\n\\n df_fields = df_fields.join(df_impuesto_canco, [df_fields.operative_incoming == df_impuesto_canco.seq_rec,\\n df_fields.booking_id == df_impuesto_canco.seq_res],\\n 'left_outer').drop(\\\"seq_rec\\\", \\\"seq_res\\\")\\n\\n df_addcanco = sub_transfer_pricing_aux_add_canco(manager, df_fields, seq_recs, seq_reservas, EUR)\\n\\n df_addcanco = df_addcanco.withColumnRenamed(\\\"operative_incoming\\\", \\\"seq_rec\\\") \\\\\\n .withColumnRenamed(\\\"booking_id\\\", \\\"seq_res\\\")\\n\\n # add add_impuesto_canco\\n df_fields = df_fields.join(df_addcanco, [df_fields.operative_incoming == df_addcanco.seq_rec,\\n df_fields.booking_id == df_addcanco.seq_res],\\n \\\"left_outer\\\").drop(df_addcanco.seq_rec).drop(df_addcanco.seq_res)\\n\\n df_fields = df_fields.na.fill({'impuesto_canco': 0, 'add_impuesto_canco': 0})\\n\\n df_fields = df_fields.withColumn(\\\"Tax_Transfer_pricing_EUR\\\",\\n df_fields.impuesto_canco + df_fields.add_impuesto_canco) \\\\\\n .drop(\\\"impuesto_canco\\\", \\\"add_impuesto_canco\\\")\\n\\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canco, df_addcanco\\n\\n return df_fields\",\n \"def _compute_amount(self):\\n for line in self:\\n line.update({\\n 'price_subtotal': line.price_unit * line.quantity,\\n })\",\n \"def tax(bill):\\n bill *= 1.08\\n print \\\"With tax: %.2f\\\" % bill\\n return bill\",\n \"def tax(self):\\n\\n self.x = self.a\\n self.set_zn(self.x)\",\n \"def trend_price_up(self):\\n raise NotImplementedError()\",\n \"def before_tax_profit(self):\\n\\n _before_tax_profit = self.net_revenue() - self.depreciation()\\n return _before_tax_profit\",\n \"def updatePrices(self,dd):\\n for key in dd:\\n self.DoS[key].updatePrice(dd[key])\",\n \"def price_bound(self, price_bound):\\n\\n self._price_bound = price_bound\",\n \"def my_rebalance(context, data):\\n freq_month = 3\\n context.counter += 1\\n if context.counter == freq_month:\\n for stock, weight in context.weights.iteritems():\\n context.counter = 0\\n if data.can_trade(stock):\\n order_target_percent(stock, weight)\",\n \"def calculate_tax(subtotal):\\n return \\\"TAX: \\\"+format_usd(0.0875*subtotal)\",\n \"def calculate_tax_for_old_regime(income,\\n savings_80c=0,\\n savings_80ccd=0,\\n savings_80d=0,\\n age=25,\\n parent_age=55\\n ):\\n tax_amount = 0\\n savings_80c = min(savings_limit['80C'], savings_80c)\\n savings_80ccd = min(savings_limit['80CCD'], savings_80c)\\n savings_limit_80d = savings_limit['80D'] * (2 if age > 60 else 1)\\n savings_limit_80d += savings_limit['80D'] * (2 if parent_age > 60 else 1)\\n savings_80d = min(savings_limit_80d, savings_80d)\\n\\n total_savings = savings_80c + savings_80ccd + savings_80d\\n print(\\\"Total savings: {}\\\".format(total_savings))\\n\\n deducted_income = income - total_savings\\n init_income = deducted_income\\n\\n slab_breaks = sorted(old_tax_regime.keys(), reverse=True)\\n\\n for upper_tax_slab in slab_breaks:\\n if deducted_income > upper_tax_slab:\\n curr_tax = old_tax_regime[upper_tax_slab] * (deducted_income - upper_tax_slab)\\n tax_amount += curr_tax\\n print(\\\"Tax slab: {}\\\\tAmount in the slab: {}\\\\tTax amount: {}\\\".format(upper_tax_slab, (deducted_income - upper_tax_slab), curr_tax))\\n deducted_income = upper_tax_slab\\n\\n if init_income <= 500000:\\n rebate = -1 * tax_amount\\n print(\\\"Rebate: {}\\\".format(rebate))\\n tax_amount += rebate\\n\\n health_ed_cess = 0.04 * tax_amount # 4% health and education cess on the tax amount\\n print(\\\"Cess: {}\\\".format(health_ed_cess))\\n tax_amount += health_ed_cess\\n\\n return tax_amount\",\n \"def modify_price(self, price):\\n if price is not None and self.is_cancellable:\\n log.info(\\\"bo#%s: modify price (pending) order \\\" % self.ticket)\\n not_implemented_error(\\\"Can't modify price for now (only for pending orders which wasn't triggered\\\")\\n order_id = self.order_id_master\\n cancel_order(order_id) # DANGEROUS! it should be atomic operation!\\n #style = self.style\\n #if self.is_limit:\\n #elif self.is_stop:\\n #elif self.is_stop_limit\\n #order_id = order(self.symbol, self.volume, style=new_style))\\n \\n else:\\n return\",\n \"def payment_post_save(**kwargs):\\n payment = kwargs['instance']\\n bill = payment.bill\\n bill.update_cached_totals()\",\n \"def add_tax(self,tax):\\n return self.price + (self.price * tax)\",\n \"def m_ps_FieldsUpdated(self, sender, e):\\r\\n if e.Error == None:\\r\\n # Make sure that there is a valid bid\\r\\n if e.Fields.GetBestBidPriceField().HasValidValue:\\r\\n if self.m_orderKey == \\\"\\\":\\r\\n # If there is no order working, submit one through the first valid order feed.\\r\\n # You should use the order feed that is valid for your purposes.\\r\\n op = ttapi.OrderProfile(e.Fields.Instrument.GetValidOrderFeeds()[0], e.Fields.Instrument)\\r\\n op.BuySell = ttapi.BuySell.Buy\\r\\n op.AccountName = \\\"12345678\\\"\\r\\n op.AccountType = ttapi.AccountType.A1\\r\\n op.OrderQuantity = ttapi.Quantity.FromInt(e.Fields.Instrument, 1)\\r\\n op.OrderType = ttapi.OrderType.Limit\\r\\n op.LimitPrice = e.Fields.GetBestBidPriceField().Value\\r\\n if not self.m_ts.SendOrder(op):\\r\\n print(\\\"Send new order failed. {0}\\\".format(op.RoutingStatus.Message))\\r\\n self.Dispose()\\r\\n else:\\r\\n self.m_orderKey = op.SiteOrderKey\\r\\n print(\\\"Send new order succeeded.\\\")\\r\\n elif self.m_ts.Orders.ContainsKey(self.m_orderKey) and self.m_ts.Orders[self.m_orderKey].LimitPrice != e.Fields.GetBestBidPriceField().Value:\\r\\n # If there is a working order, reprice it if its price is not the same as the bid\\r\\n op = self.m_ts.Orders[self.m_orderKey].GetOrderProfile()\\r\\n op.LimitPrice = e.Fields.GetBestBidPriceField().Value\\r\\n op.Action = ttapi.OrderAction.Change\\r\\n if not self.m_ts.SendOrder(op):\\r\\n print(\\\"Send change order failed. {0}\\\".format(op.RoutingStatus.Message))\\r\\n else:\\r\\n print(\\\"Send change order succeeded.\\\")\\r\\n else:\\r\\n if e.Error.IsRecoverableError == False:\\r\\n print(\\\"Unrecoverable price subscription error: {0}\\\".format(e.Error.Message))\\r\\n self.Dispose()\",\n \"def _amount_all(self):\\n for order in self:\\n amount_untaxed = amount_tax = 0.0\\n order_amount_total = 0.0\\n for line in order.order_line:\\n amount_untaxed += line.price_subtotal\\n amount_tax += line.price_tax\\n self_amount_total = amount_untaxed + amount_tax\\n if not order.discount_fixed_percent:\\n order_amount_total = self_amount_total\\n if order.discount_fixed_percent == 'Percent':\\n order_amount_total = self_amount_total * (1 - (order.discount or 0.0) / 100.0)\\n if order.discount_fixed_percent == 'Fixed':\\n order_amount_total = self_amount_total - order.discount_value\\n order.update({\\n 'amount_untaxed': order.pricelist_id.currency_id.round(amount_untaxed),\\n 'amount_tax': order.pricelist_id.currency_id.round(amount_tax),\\n 'amount_before_disc': amount_untaxed + amount_tax,\\n 'amount_total': order_amount_total,\\n })\",\n \"def pre_approve(self, cr, uid, ids, context={}):\\n \\tfor voucher in self.browse(cr, uid, ids, context=context):\\n \\t if not voucher.department_id.analytic_account_id:\\n \\t raise osv.except_osv(_('Configration Check!'), _(\\\"Please add cost center for your department!\\\"))\\n \\t periods = self.pool.get('account.period').search(cr, uid, [('date_start','<=',voucher.date),('date_stop','>=',voucher.date),('company_id','=',voucher.company_id.id)], context=context)\\n\\n\\n res=0.0\\n if voucher.purpose:\\n if not voucher.purpose.account_id: raise osv.except_osv(_('Warning!'), _('Please configure account for this purpose!')) \\n voucher_line = {\\n \\t\\t'voucher_id': voucher.id,\\n \\t\\t'partner_id': voucher.partner_id.id,\\n \\t\\t'untax_amount': voucher.amount,\\n \\t\\t'amount': voucher.amount,\\n 'name': voucher.narration,\\n \\t\\t'type': 'dr',\\n \\t\\t'account_analytic_id': voucher.department_id.analytic_account_id and voucher.department_id.analytic_account_id.id,\\n 'account_id': voucher.purpose.account_id.id,\\n \\t }\\n new_amount = res and res or voucher.amount \\n voucher_line.update({'amount':new_amount,'untax_amount':new_amount})\\n \\t if voucher.line_ids :\\n for line in voucher.line_ids:\\n \\t\\t self.pool.get('account.voucher.line').write(cr, uid, line.id, {\\n \\t\\t'voucher_id': voucher.id,\\n \\t\\t'partner_id': voucher.partner_id.id,\\n \\t\\t'untax_amount': res or line.amount,\\n \\t\\t'amount': line.amount,\\n 'name': voucher.narration,\\n \\t\\t'type': 'dr',\\n \\t\\t'account_analytic_id': line.account_analytic_id and line.account_analytic_id.id or voucher.department_id.analytic_account_id.id,\\n 'account_id': voucher.purpose.account_id.id or line.account_id.id,\\n \\t }, context=context)\\n \\t else:\\n\\n \\t\\t new_voucher_line = self.pool.get('account.voucher.line').create(cr, uid, voucher_line, context=context)\\n context.update({'purchase':True})\\n self.create_budget_confirmation(cr, uid, [voucher.id], context)\\n \\tself.write(cr, uid, ids,{'state': 'preapprove','type':'purchase','ratification':True}, context=context)\\n #cxt = context.copy()\\n #cxt.update({'type':'ratification'})\\n if not super(account_voucher, self).create_budget_confirmation(cr, uid, ids, context=context):\\n self.write(cr, uid, ids, {'state': 'approved'}, context=context)\\n\\n \\t'''self.write(cr, uid, ids, {'state': 'preapprove'})\\n if not super(account_voucher, self).create_budget_confirmation(cr, uid, ids, context=context):\\n self.write(cr, uid, ids, {'state': 'approve','type':'purchase','ratification':True}, context=context)'''\\n return True\",\n \"def percent_changes(self):\\n\\n # close_t = float(val[\\\"klines\\\"][\\\"1m\\\"].get(self.mw.cfg_manager.pair, {})[-5][4])\\n klines_data = self.mw.klines.get(\\\"1m\\\")\\n coin_data = klines_data.get(self.mw.cfg_manager.pair)\\n\\n if isinstance(coin_data, list):\\n close_5m = float(self.mw.klines[\\\"1m\\\"][self.mw.cfg_manager.pair][-5][4])\\n close_15m = float(self.mw.klines[\\\"1m\\\"][self.mw.cfg_manager.pair][-15][4])\\n # close_30m = float(self.mw.klines[\\\"1m\\\"][self.mw.cfg_manager.pair][-30][4])\\n close_1h = float(self.mw.klines[\\\"1m\\\"][self.mw.cfg_manager.pair][-60][4])\\n close_4h = float(self.mw.klines[\\\"1m\\\"][self.mw.cfg_manager.pair][-240][4])\\n\\n change_5m_value = ((float(val[\\\"tickers\\\"][self.mw.cfg_manager.pair][\\\"lastPrice\\\"]) / float(close_5m)) - 1) * 100\\n change_15m_value = ((float(val[\\\"tickers\\\"][self.mw.cfg_manager.pair][\\\"lastPrice\\\"]) / float(close_15m)) - 1) * 100\\n # change_30m_value = ((float(val[\\\"tickers\\\"][self.mw.cfg_manager.pair][\\\"lastPrice\\\"]) / float(close_30m)) - 1) * 100\\n change_1h_value = ((float(val[\\\"tickers\\\"][self.mw.cfg_manager.pair][\\\"lastPrice\\\"]) / float(close_1h)) - 1) * 100\\n change_4h_value = ((float(val[\\\"tickers\\\"][self.mw.cfg_manager.pair][\\\"lastPrice\\\"]) / float(close_4h)) - 1) * 100\\n\\n change_1d_value = float(val[\\\"tickers\\\"][self.mw.cfg_manager.pair][\\\"priceChangePercent\\\"])\\n\\n\\n changes = [self.mw.change_5m, self.mw.change_15m, self.mw.change_1h, self.mw.change_4h, self.mw.change_1d]\\n change_values = [change_5m_value, change_15m_value, change_1h_value, change_4h_value, change_1d_value]\\n\\n for i, change in enumerate(changes):\\n if change_values[i] > 0:\\n operator = \\\"+\\\"\\n color = Colors.color_green\\n elif change_values[i] < 0:\\n operator = \\\"\\\"\\n color = Colors.color_pink\\n else:\\n operator = \\\"\\\"\\n color = Colors.color_grey\\n\\n # print(str(change))\\n change.setText(\\\"<span style='color: \\\" + color + \\\"'>\\\" + operator + \\\"{0:.2f}\\\".format(change_values[i]) + \\\"%</span\\\")\",\n \"def modify(request, invoice_number):\\n if request.method == \\\"POST\\\":\\n n = Invoice.objects.filter(number=request.POST[\\\"invoice_number\\\"])\\n items = n.get().items\\n\\n for i, item in enumerate(items):\\n item[\\\"short_description\\\"] = request.POST[str(i + 1) + \\\"_short_description\\\"]\\n item[\\\"particulars\\\"] = request.POST[str(i + 1) + \\\"_particulars\\\"]\\n item[\\\"quantity\\\"] = request.POST[str(i + 1) + \\\"_quantity\\\"]\\n item[\\\"unit\\\"] = request.POST[str(i + 1) + \\\"_unit\\\"]\\n item[\\\"unit_price\\\"] = request.POST[str(i + 1) + \\\"_unit_price\\\"]\\n item[\\\"total_cost\\\"] = request.POST[str(i + 1) + \\\"_total_cost\\\"]\\n\\n n.update(\\n number=request.POST[\\\"invoice_number\\\"],\\n invoice_date=request.POST[\\\"invoice_date\\\"],\\n reference_number=request.POST[\\\"reference_number\\\"],\\n reference_date=request.POST[\\\"reference_date\\\"],\\n addressed_to=request.POST[\\\"addressed_to\\\"],\\n party_gst=request.POST[\\\"party_gst\\\"],\\n items=items,\\n c_gst=request.POST[\\\"c_gst\\\"],\\n s_gst=request.POST[\\\"s_gst\\\"],\\n other_charges=request.POST[\\\"other_charges\\\"],\\n notes=request.POST[\\\"additional_notes\\\"],\\n total=request.POST[\\\"total\\\"],\\n modified_at=datetime.datetime.now()\\n )\\n return redirect(\\\"index_page\\\")\\n\\n data = Invoice.objects.get(number=invoice_number)\\n\\n sub_total = sum([a.get(\\\"total_cost\\\") for a in data.items])\\n\\n return render(request,\\n \\\"invoice/invoice_modify.html\\\",\\n {\\n \\\"invoice\\\": data,\\n \\\"sub_total\\\": sub_total\\n })\",\n \"def test_fetch_order_prices_when_tax_exemption_and_include_taxes_in_prices(\\n plugins_manager,\\n fetch_kwargs,\\n order_with_lines,\\n tax_data,\\n):\\n # given\\n currency = order_with_lines.currency\\n discount_amount = Decimal(\\\"3.00\\\")\\n order_with_lines.discounts.create(\\n value=discount_amount,\\n amount_value=discount_amount,\\n currency=order_with_lines.currency,\\n )\\n order_with_lines.total_net_amount = Decimal(\\\"0.00\\\")\\n order_with_lines.total_gross_amount = Decimal(\\\"0.00\\\")\\n order_with_lines.undiscounted_total_net_amount = Decimal(\\\"0.00\\\")\\n order_with_lines.undiscounted_total_gross_amount = Decimal(\\\"0.00\\\")\\n order_with_lines.tax_exemption = True\\n order_with_lines.save()\\n plugins_manager.get_taxes_for_order = Mock(return_value=tax_data)\\n\\n # when\\n calculations.fetch_order_prices_if_expired(**fetch_kwargs)\\n\\n # then\\n order_with_lines.refresh_from_db()\\n shipping_price = get_taxed_money(\\n tax_data, \\\"shipping_price\\\", currency, exempt_taxes=True\\n )\\n assert order_with_lines.shipping_price == shipping_price\\n assert order_with_lines.shipping_tax_rate == Decimal(\\\"0.00\\\")\\n subtotal = zero_taxed_money(currency)\\n undiscounted_subtotal = zero_taxed_money(currency)\\n\\n for order_line, tax_line in zip(order_with_lines.lines.all(), tax_data.lines):\\n line_total = get_taxed_money(tax_line, \\\"total\\\", currency, exempt_taxes=True)\\n subtotal += line_total\\n undiscounted_subtotal += order_line.undiscounted_total_price\\n assert order_line.total_price == line_total\\n assert order_line.unit_price == line_total / order_line.quantity\\n assert order_line.tax_rate == Decimal(\\\"0.00\\\")\\n\\n assert (\\n order_with_lines.undiscounted_total\\n == undiscounted_subtotal + shipping_price.net\\n )\\n assert order_with_lines.total == subtotal + shipping_price\",\n \"def _compute_amount(self, base_amount, price_unit, quantity=1.0, product=None, partner=None):\\n\\n self.ensure_one()\\n\\n if self.amount_type != 'margin':\\n return super(AccountTax, self)._compute_amount(\\n base_amount,\\n price_unit,\\n quantity=quantity,\\n product=product,\\n partner=partner\\n )\\n\\n return base_amount - (base_amount / (1 + self.amount / 100))\",\n \"def recalc_for_bird(self, early_bird):\\n \\n if early_bird.eb_discount and early_bird.eb_expanding:\\n rates_eb = self.get_rates()\\n if early_bird.discount_type == 1:\\n if rates_eb:\\n rates = []\\n for rate in rates_eb:\\n if early_bird.eb_discount > 0:\\n rate *= Decimal(str(early_bird.eb_discount)) / 100\\n else:\\n rate += rate * Decimal(str(early_bird.eb_discount)) / 100\\n rates.append(str(rate))\\n self.rates = u';'.join(rates)\\n\\n if early_bird.discount_type == 0:\\n if rates_eb:\\n rates = []\\n for rate in rates_eb:\\n rate += Decimal(str(early_bird.eb_discount))\\n rates.append(str(rate))\\n self.rates = u';'.join(rates)\\n return self.rates\",\n \"def trade(self, trigger_function, trigger_point, **trigger_function_kwargs):\\n for date in self.tc.dates[1:]:\\n # If the previous-day close allocation is out of tolerance..\\n if trigger_function(self.df.shift(1).loc[date, 'allocations'].values, self.target_weights,\\n **trigger_function_kwargs) > trigger_point:\\n # then rebalance the portfolio\\n trade = self.rebalance(date)\\n self.trades.loc[date] = trade\\n # When the trading is finished, we update the daily returns of the portfolio\\n self.df['returns'] = self.df['values'].sum(axis=1).pct_change(1).fillna(0)\",\n \"def test_companies_company_id_data_tax_rates_get(self):\\n pass\",\n \"def update_order_undiscounted_price(apps, schema_editor):\\n\\n def on_migrations_complete(sender=None, **kwargs):\\n order_ids = list(kwargs.get(\\\"updated_orders_pks\\\"))\\n send_order_updated.delay(order_ids)\\n\\n Order = apps.get_model(\\\"order\\\", \\\"Order\\\")\\n OrderLine = apps.get_model(\\\"order\\\", \\\"OrderLine\\\")\\n\\n # Take orders that has applied lines voucher discounts, but the discount is\\n # not visible in undiscounted price.\\n orders_to_update = Order.objects.filter(\\n Exists(\\n OrderLine.objects.filter(\\n order_id=OuterRef(\\\"id\\\"), voucher_code__isnull=False\\n )\\n ),\\n total_gross_amount=F(\\\"undiscounted_total_gross_amount\\\"),\\n ).order_by(\\\"id\\\")\\n\\n updated_orders_pks = []\\n for batch_pks in queryset_in_batches(orders_to_update):\\n orders = Order.objects.filter(pk__in=batch_pks)\\n lines = OrderLine.objects.filter(order_id__in=orders.values(\\\"id\\\")).values(\\n \\\"order_id\\\",\\n \\\"undiscounted_total_price_gross_amount\\\",\\n \\\"total_price_gross_amount\\\",\\n \\\"undiscounted_total_price_net_amount\\\",\\n \\\"total_price_net_amount\\\",\\n )\\n lines_discount_data = defaultdict(lambda: (0, 0))\\n for data in lines:\\n discount_amount_gross = (\\n data[\\\"undiscounted_total_price_gross_amount\\\"]\\n - data[\\\"total_price_gross_amount\\\"]\\n )\\n discount_amount_net = (\\n data[\\\"undiscounted_total_price_net_amount\\\"]\\n - data[\\\"total_price_net_amount\\\"]\\n )\\n current_discount_gross, current_discount_net = lines_discount_data[\\n data[\\\"order_id\\\"]\\n ]\\n lines_discount_data[data[\\\"order_id\\\"]] = (\\n current_discount_gross + discount_amount_gross,\\n current_discount_net + discount_amount_net,\\n )\\n\\n for order in orders:\\n discount_amount_gross, discount_amount_net = lines_discount_data.get(\\n order.id\\n )\\n if discount_amount_gross > 0 or discount_amount_net > 0:\\n order.undiscounted_total_gross_amount += discount_amount_gross\\n order.undiscounted_total_net_amount += discount_amount_net\\n\\n updated_orders_pks.append(order.id)\\n\\n Order.objects.bulk_update(\\n orders,\\n [\\n \\\"undiscounted_total_gross_amount\\\",\\n \\\"undiscounted_total_net_amount\\\",\\n ],\\n )\\n\\n # If we updated any order we should trigger `order_updated` after migrations\\n if updated_orders_pks:\\n updated_orders_pks = set(updated_orders_pks)\\n sender = registry.get_app_config(\\\"order\\\")\\n post_migrate.connect(\\n partial(on_migrations_complete, updated_orders_pks=updated_orders_pks),\\n weak=False,\\n dispatch_uid=\\\"send_order_updated\\\",\\n sender=sender,\\n )\",\n \"def _dynamic_price(self):\\n adjust = PriceAdjustmentCalc(self)\\n signals.satchmo_price_query.send(self, adjustment=adjust,\\n slug=self.product.slug, discountable=self.product.is_discountable)\\n return adjust.final_price()\",\n \"def update_forces(self):\\n\\n pass\",\n \"def tax_amount(self, tax_amount):\\n\\n self._tax_amount = tax_amount\",\n \"def tax_amount(self, tax_amount):\\n\\n self._tax_amount = tax_amount\",\n \"def sub_tax_sales_transfer_pricing(manager, df_fields, seq_recs, seq_reservas):\\n # df_hotel = manager.get_dataframe(tables['dwc_bok_t_canco_hotel'])\\n # df_circuit = manager.get_dataframe(tables['dwc_bok_t_canco_hotel_circuit'])\\n # df_other = manager.get_dataframe(tables['dwc_bok_t_canco_other'])\\n # df_transfer = manager.get_dataframe(tables['dwc_bok_t_canco_transfer'])\\n # df_endow = manager.get_dataframe(tables['dwc_bok_t_canco_endowments'])\\n # df_extra = manager.get_dataframe(tables['dwc_bok_t_canco_extra'])\\n\\n df_aux = df_fields.select(\\\"operative_incoming\\\", \\\"booking_id\\\")\\n\\n df_hotel = sub_tax_sales_transfer_pricing_aux(manager, df_hotelt, seq_recs, seq_reservas, df_aux)\\n df_circuit = sub_tax_sales_transfer_pricing_aux(manager, df_circuitt, seq_recs, seq_reservas, df_aux)\\n df_other = sub_tax_sales_transfer_pricing_aux(manager, df_othert, seq_recs, seq_reservas, df_aux)\\n df_transfer = sub_tax_sales_transfer_pricing_aux(manager, df_transfert, seq_recs, seq_reservas, df_aux)\\n df_endow = sub_tax_sales_transfer_pricing_aux(manager, df_endowt, seq_recs, seq_reservas, df_aux)\\n df_extra = sub_tax_sales_transfer_pricing_aux_extra(manager, df_extrat, seq_recs, seq_reservas, df_aux)\\n\\n df_impuesto_canal = df_hotel.union(df_circuit).union(df_other).union(df_transfer).union(df_endow).union(\\n df_extra)\\n\\n df_impuesto_canal = df_impuesto_canal.groupBy(\\\"seq_rec\\\", \\\"seq_reserva\\\") \\\\\\n .agg({'impuesto_canal': 'sum'}).withColumnRenamed(\\\"SUM(impuesto_canal)\\\", \\\"Tax_Sales_Transfer_pricing\\\")\\n\\n df_fields = df_fields.join(df_impuesto_canal, [df_fields.operative_incoming == df_impuesto_canal.seq_rec,\\n df_fields.booking_id == df_impuesto_canal.seq_reserva],\\n 'left_outer').drop(df_impuesto_canal.seq_rec).drop(df_impuesto_canal.seq_reserva)\\n\\n df_fields = df_fields.na.fill({\\\"Tax_Sales_Transfer_pricing\\\": 0})\\n\\n df_fields = df_fields.withColumn(\\\"Tax_Sales_Transfer_pricing\\\",\\n udf_round_ccy(df_fields.Tax_Sales_Transfer_pricing,\\n df_fields.booking_currency))\\n\\n del df_hotel, df_circuit, df_other, df_transfer, df_endow, df_extra, df_impuesto_canal\\n\\n return df_fields\",\n \"def compare(self):\\n self.PotTax_increase = self.PotTax_intervention - self.PotTax_reference\\n self.PotTax_percentage = (\\n (self.PotTax_increase / self.PotTax_reference) * 100)\\n \\\"\\\"\\\"\\n # this sets the PotTax_percentage to actual percentages.\\n self.PotTax_percentage['TFI'] = pd.Series(\\n [\\\"{0:.2f}%\\\".format(val * 100) for val in\\n self.PotTax_percentage['TFI']],\\n index = self.PotTax_percentage.index)\\n \\\"\\\"\\\"\\n return\",\n \"def updateLastPrice(self):\\n dt = datetime.now(tz=pytz.UTC).replace(microsecond=0)\\n\\n dt_central = dt.astimezone(\\n pytz.timezone('US/Central')).strftime(\\\"%H:%M\\\")\\n\\n # UPDATE POSITION LAST PRICE AND UPDATE HIGH PRICE\\n open_positions = self.open_positions.find(\\n {\\\"Trader\\\": self.user[\\\"Name\\\"], \\\"Asset_Type\\\": self.asset_type, \\\"Account_ID\\\": self.account_id})\\n\\n open_positions_list = []\\n\\n for position in open_positions:\\n\\n symbol = position[\\\"Symbol\\\"]\\n\\n if symbol not in open_positions_list:\\n\\n open_positions_list.append(symbol)\\n\\n if len(open_positions_list) > 0:\\n\\n resp = self.tdameritrade.getQuotes(open_positions_list)\\n\\n if resp:\\n\\n for key, value in resp.items():\\n\\n symbol = key\\n\\n last_price = value[\\\"lastPrice\\\"]\\n\\n self.open_positions.update_many({\\\"Trader\\\": self.user[\\\"Name\\\"], \\\"Symbol\\\": symbol, \\\"Asset_Type\\\": self.asset_type, \\\"Account_ID\\\": self.account_id}, {\\n \\\"$set\\\": {\\\"Last_Price\\\": last_price}})\\n\\n if dt_central == \\\"15:00\\\":\\n\\n self.open_positions.update_many({\\\"Trader\\\": self.user[\\\"Name\\\"], \\\"Symbol\\\": symbol, \\\"Asset_Type\\\": self.asset_type, \\\"Account_ID\\\": self.account_id}, {\\n \\\"$set\\\": {\\\"Opening_Price\\\": last_price}})\\n\\n # UPDATE QUEUE LAST PRICE\\n queues = self.queue.find(\\n {\\\"Trader\\\": self.user[\\\"Name\\\"], \\\"Asset_Type\\\": self.asset_type})\\n\\n queues_list = []\\n\\n for queue in queues:\\n\\n if self.asset_type == \\\"EQUITY\\\":\\n\\n symbol = queue[\\\"Symbol\\\"]\\n\\n elif self.asset_type == \\\"OPTION\\\":\\n\\n symbol = queue[\\\"Pre_Symbol\\\"]\\n\\n if symbol not in queues_list:\\n\\n queues_list.append(symbol)\\n\\n if len(queues_list) > 0:\\n\\n resp = self.tdameritrade.getQuotes(queues_list)\\n\\n for key, value in resp.items():\\n\\n symbol = key\\n\\n last_price = value[\\\"lastPrice\\\"]\\n\\n if self.asset_type == \\\"EQUITY\\\":\\n\\n self.queue.update_many({\\\"Trader\\\": self.user[\\\"Name\\\"], \\\"Symbol\\\": symbol, \\\"Asset_Type\\\": self.asset_type, \\\"Account_ID\\\": self.account_id}, {\\n \\\"$set\\\": {\\\"Last_Price\\\": last_price}})\\n\\n elif self.asset_type == \\\"OPTION\\\":\\n\\n self.queue.update_many({\\\"Trader\\\": self.user[\\\"Name\\\"], \\\"Pre_Symbol\\\": symbol, \\\"Asset_Type\\\": self.asset_type, \\\"Account_ID\\\": self.account_id}, {\\n \\\"$set\\\": {\\\"Last_Price\\\": last_price}})\",\n \"def test_increasing_trend_is_true_if_price_increase_for_3_updates(self):\\n self.given_a_series_of_prices([8, 10, 12])\\n self.assertTrue(self.goog.is_increasing_trend())\",\n \"def update_price_signals(self, monthly_data, time_series_data):\\n if self.combined_market:\\n try:\\n fr_price = time_series_data.loc[:, 'FR Price ($/kW)']\\n except KeyError:\\n pass\\n else:\\n self.p_regu = np.divide(fr_price, 2)\\n self.p_regd = np.divide(fr_price, 2)\\n\\n try:\\n self.price = time_series_data.loc[:, 'DA Price ($/kWh)']\\n except KeyError:\\n pass\\n else:\\n try:\\n self.p_regu = time_series_data.loc[:, 'Reg Up Price ($/kW)']\\n except KeyError:\\n pass\\n\\n try:\\n self.p_regd = time_series_data.loc[:, 'Reg Down Price ($/kW)']\\n except KeyError:\\n pass\\n\\n try:\\n self.price = time_series_data.loc[:, 'DA Price ($/kWh)']\\n except KeyError:\\n pass\",\n \"def recompute_billing_lines(self, cr, uid, ids, partner_id, journal_id, price, currency_id, date, context=None):\\n def _remove_noise_in_o2m():\\n \\\"\\\"\\\"if the line is partially reconciled, then we must pay attention to display it only once and\\n in the good o2m.\\n This function returns True if the line is considered as noise and should not be displayed\\n \\\"\\\"\\\"\\n if line.reconcile_partial_id:\\n sign = 1\\n if currency_id == line.currency_id.id:\\n if line.amount_residual_currency * sign <= 0:\\n return True\\n else:\\n if line.amount_residual * sign <= 0:\\n return True\\n return False\\n\\n if context is None:\\n context = {}\\n billing_date_condition = context.get('billing_date_condition', [])\\n context_multi_currency = context.copy()\\n if date:\\n context_multi_currency.update({'date': date})\\n\\n currency_pool = self.pool.get('res.currency')\\n move_line_pool = self.pool.get('account.move.line')\\n partner_pool = self.pool.get('res.partner')\\n journal_pool = self.pool.get('account.journal')\\n line_pool = self.pool.get('account.billing.line')\\n\\n #set default values\\n default = {\\n 'value': {'line_cr_ids': [] },\\n }\\n\\n #drop existing lines\\n line_ids = ids and line_pool.search(cr, uid, [('billing_id', '=', ids[0])]) or False\\n if line_ids:\\n line_pool.unlink(cr, uid, line_ids)\\n\\n if not partner_id or not journal_id:\\n return default\\n\\n journal = journal_pool.browse(cr, uid, journal_id, context=context)\\n partner = partner_pool.browse(cr, uid, partner_id, context=context)\\n currency_id = currency_id or journal.company_id.currency_id.id\\n account_id = False\\n if journal.type in ('sale','sale_refund'):\\n account_id = partner.property_account_receivable.id\\n elif journal.type in ('purchase', 'purchase_refund','expense'):\\n account_id = partner.property_account_payable.id\\n else:\\n account_id = journal.default_credit_account_id.id or journal.default_debit_account_id.id\\n\\n default['value']['account_id'] = account_id\\n\\n if journal.type not in ('cash', 'bank'):\\n return default\\n\\n total_credit = price or 0.0\\n account_type = 'receivable'\\n\\n if not context.get('move_line_ids', False):\\n ids = move_line_pool.search(cr, uid, \\n [('state','=','valid'), ('account_id.type', '=', account_type), ('reconcile_id', '=', False), ('partner_id', '=', partner_id), \\n ] + billing_date_condition, \\n context=context)\\n else:\\n ids = context['move_line_ids']\\n invoice_id = context.get('invoice_id', False)\\n company_currency = journal.company_id.currency_id.id\\n move_line_found = False\\n\\n #order the lines by most old first\\n ids.reverse()\\n account_move_lines = move_line_pool.browse(cr, uid, ids, context=context)\\n\\n #compute the total debit/credit and look for a matching open amount or invoice\\n for line in account_move_lines:\\n if _remove_noise_in_o2m():\\n continue\\n\\n if invoice_id:\\n if line.invoice.id == invoice_id:\\n #if the invoice linked to the billing line is equal to the invoice_id in context\\n #then we assign the amount on that line, whatever the other billing lines\\n move_line_found = line.id\\n break\\n elif currency_id == company_currency:\\n #otherwise treatments is the same but with other field names\\n if line.amount_residual == price:\\n #if the amount residual is equal the amount billing, we assign it to that billing\\n #line, whatever the other billing lines\\n move_line_found = line.id\\n break\\n #otherwise we will split the billing amount on each line (by most old first)\\n total_credit += line.credit or 0.0\\n elif currency_id == line.currency_id.id:\\n if line.amount_residual_currency == price:\\n move_line_found = line.id\\n break\\n total_credit += line.credit and line.amount_currency or 0.0\\n\\n #billing line creation\\n for line in account_move_lines:\\n\\n if _remove_noise_in_o2m():\\n continue\\n\\n if line.currency_id and currency_id==line.currency_id.id:\\n amount_original = abs(line.amount_currency)\\n amount_unreconciled = abs(line.amount_residual_currency)\\n else:\\n amount_original = currency_pool.compute(cr, uid, company_currency, currency_id, line.credit or 0.0)\\n amount_unreconciled = currency_pool.compute(cr, uid, company_currency, currency_id, abs(line.amount_residual))\\n line_currency_id = line.currency_id and line.currency_id.id or company_currency\\n rs = {\\n 'move_line_id':line.id,\\n 'type': line.credit and 'dr' or 'cr',\\n 'reference':line.invoice.reference,\\n 'account_id':line.account_id.id,\\n 'amount_original': amount_original,\\n 'amount': (move_line_found == line.id) and min(abs(price), amount_unreconciled) or amount_unreconciled,\\n 'date_original':line.date,\\n 'date_due':line.date_maturity,\\n 'amount_unreconciled': amount_unreconciled,\\n 'currency_id': line_currency_id,\\n }\\n \\n # Negate DR records\\n if rs['type'] == 'dr':\\n rs['amount_original'] = - rs['amount_original']\\n rs['amount'] = - rs['amount']\\n rs['amount_unreconciled'] = - rs['amount_unreconciled']\\n\\n if rs['amount_unreconciled'] == rs['amount']:\\n rs['reconcile'] = True\\n else:\\n rs['reconcile'] = False\\n\\n default['value']['line_cr_ids'].append(rs)\\n\\n# if ttype == 'payment' and len(default['value']['line_cr_ids']) > 0:\\n# default['value']['pre_line'] = 1\\n# elif ttype == 'receipt' and len(default['value']['line_dr_ids']) > 0:\\n# default['value']['pre_line'] = 1\\n default['value']['billing_amount'] = self._compute_billing_amount(cr, uid, default['value']['line_cr_ids'], price)\\n return default\",\n \"def recalcRelativeRates(self):\\n #---+----|----+----|----+----|----+----|----+----|----+----|----+----|\\n TreeLikelihoodBase.recalcRelativeRates(self)\",\n \"def generate_orders(self, cr, uid, ids, context=None):\\n voucher_pool = self.pool.get('account.voucher')\\n payment_term_obj = self.pool.get('account.payment.term')\\n account_budget_confirmation_obj = self.pool.get('account.budget.confirmation')\\n period_obj = self.pool.get('account.period')\\n if context is None:\\n context = {}\\n for order in self.browse(cr, uid, ids, context=context):\\n #################################to remind\\n total_fixed = total_percent = 0\\n for line in order.payment_term.line_ids:\\n if line.value == 'fixed':\\n total_fixed += line.value_amount\\n if line.value == 'procent':\\n total_percent += line.value_amount\\n total_fixed = (total_fixed * 100) / (order.amount or 1.0)\\n if (total_fixed + total_percent) > 100:\\n raise orm.except_orm(_('Error!'), _(\\\"Can not create the payments !\\\\n\\\\\\n The related payment term is probably miss configured as it gives a computed amount greater than the total permanent payment amount. \\\\\\n The latest line of your payment term must be of type 'balance' to avoid rounding issues.\\\"))\\n # create one move line for the total and possibly adjust the other lines amount\\n totlines1 = []\\n for o in order.line_ids:\\n totlines1 += payment_term_obj.compute(cr, uid, order.payment_term.id, o.amount, order.date or False, context=context)\\n \\n d = {}\\n for k, v in totlines1:\\n d.setdefault(k, [k]).append(v)\\n totlines = map(tuple, d.values())\\n\\n for t in totlines :\\n #to substract date from the interval number \\n order_date = t[0]\\n entered_date = datetime.datetime.strptime(order_date, '%Y-%m-%d')\\n entered_date = entered_date.date()\\n account_id = (order.partner_id.property_account_payable and order.partner_id.property_account_payable.id) or \\\\\\n (order.journal_id.default_credit_account_id and order.journal_id.default_credit_account_id.id)\\n period_id = period_obj.find(cr, uid, t[0], context=context)[0]\\n\\n list_confirm = [conf.id for conf in o.confirmation_ids]\\n confirmations = account_budget_confirmation_obj.search(cr, uid, [('id','in', list_confirm),('period_id','=', period_id)], context=context) #('date','=',t[0]),\\n\\n for confirm in confirmations:\\n confirm_id = confirm\\n\\n voucher_lines = [(0, 0, {'name':ol.name, 'account_id':ol.account_id.id, 'type':'dr',\\n 'amount':t[count + 1], 'account_analytic_id':ol.account_analytic_id.id, 'budget_confirm_id': confirm_id })\\n for count, ol in enumerate(order.line_ids)]\\n res = voucher_pool.onchange_price(cr, uid, 0, voucher_lines, [], partner_id=order.partner_id.id, context=context).get(\\\"value\\\", {})\\n voucher_dict = {\\n 'partner_id' : order.partner_id.id,\\n 'account_id': account_id,\\n 'company_id' : order.company_id.id,\\n 'journal_id' : order.journal_id.id,\\n 'period_id': order.period_id.id,\\n 'type':'purchase',\\n 'date' : t[0],\\n 'reference': order.name,\\n 'payment_permanent_voucher_id': order.id,\\n 'line_ids':voucher_lines,\\n 'amount':res.get(\\\"amount\\\", 0.0)\\n }\\n voucher_pool.create(cr, uid, voucher_dict, context=context)\\n return self.write(cr, uid, ids, {'state':'done'}, context=context)\",\n \"def total(self) -> float:\\n\\n remained_to_be_taxed = self.income\\n # taxed = list()\\n self.tax_amounts = []\\n start_tax_range = 0\\n end_tax_range = self.bracket\\n\\n for i, b in enumerate(self.bracket):\\n\\n amount_to_tax = b.end - start_tax_range\\n t = Taxed(min(amount_to_tax, remained_to_be_taxed), b.rate,\\n min(amount_to_tax, remained_to_be_taxed) * b.rate)\\n self.tax_amounts.append(t)\\n # print(i, start_t ax_range, b.end, amount_to_tax, b.rate)\\n\\n remained_to_be_taxed -= amount_to_tax\\n # print(remained_to_be_taxed)\\n\\n if b.end > self.income:\\n break\\n\\n start_tax_range = b.end\\n\\n # print(taxed)\\n return sum([t.tax for t in self.tax_amounts])\",\n \"def vat_change_fiscal_requirements(self, cr, uid, ids, value, context=None):\\n if context is None:\\n context={}\\n if not value:\\n return super(res_partner,self).vat_change(cr, uid, ids, value, context=context)\\n res = self.search(cr, uid, [('vat', 'ilike', value)])\\n if res:\\n rp = self.browse(cr, uid, res[0],context=context)\\n return {'warning': {\\n 'title':_('Vat Error !'),\\n 'message':_('The VAT [%s] looks like '%value + \\n '[%s] which is'%rp.vat.upper()+\\n ' already being used by: %s'%rp.name.upper())\\n }\\n }\\n else:\\n return super(res_partner,self).vat_change(cr, uid, ids, value, context=context)\",\n \"def recalc_for_bird(self, early_bird):\\n\\n if early_bird.cs_discount and early_bird.cs_expanding:\\n rates_cs = self.get_rates()\\n if early_bird.discount_type == 1:\\n if rates_cs:\\n rates = []\\n for rate in rates_cs:\\n if early_bird.cs_discount > 0:\\n rate *= Decimal(str(early_bird.cs_discount)) / 100\\n else:\\n rate += rate * Decimal(str(early_bird.cs_discount)) / 100\\n rates.append(str(rate))\\n self.rates = u';'.join(rates)\\n\\n if early_bird.discount_type == 0:\\n if rates_cs:\\n rates = []\\n for rate in rates_cs:\\n rate += Decimal(str(early_bird.cs_discount))\\n rates.append(str(rate))\\n self.rates = u';'.join(rates)\\n return self.rates\",\n \"def recalc_for_bird(self, early_bird):\\n\\n if early_bird.cs_discount and early_bird.cs_expanding:\\n rates_cs = self.get_rates()\\n if early_bird.discount_type == 1:\\n if rates_cs:\\n rates = []\\n for rate in rates_cs:\\n if early_bird.cs_discount > 0:\\n rate *= Decimal(str(early_bird.cs_discount)) / 100\\n else:\\n rate += rate * Decimal(str(early_bird.cs_discount)) / 100\\n rates.append(str(rate))\\n self.rates = u';'.join(rates)\\n\\n if early_bird.discount_type == 0:\\n if rates_cs:\\n rates = []\\n for rate in rates_cs:\\n rate += Decimal(str(early_bird.cs_discount))\\n rates.append(str(rate))\\n self.rates = u';'.join(rates)\\n return self.rates\",\n \"def onchange_invoice(self):\\n self.product_id = False\\n self.date = self.invoice.date_invoice\\n self.name = (self.invoice and self.invoice.reference) or ''\\n self.analytic_account_id = False\\n self.unit_amount = self.invoice.residual\\n self.quantity = 1\\n self.total_amount = self.unit_amount\",\n \"def _update_quote(self):\\n # If this is the first quote or a price is outside current price ladder,\\n # reset the price ladder.\\n if (self._quotes_row == 0 or (\\n self._quotes_df.loc[self._quotes_row, 'ask_price'] > \\\\\\n self._price_ladder[0] + .5 * self._config['tick_size']) or (\\n self._quotes_df.loc[self._quotes_row, 'bid_price'] < \\\\\\n self._price_ladder[-1] - .5 * self._config['tick_size'])):\\n max_price = (self._quotes_df.loc[self._quotes_row, 'ask_price'] +\\n self._config['tick_size'] * np.floor(\\n (self._config['row_count'] - 1) / 2))\\n self._price_ladder = np.linspace(\\n max_price,\\n max_price - (\\n self._config['row_count'] - 1) * self._config['tick_size'],\\n self._config['row_count'])\\n self._price_ladder_df.iloc[:, [0, 1, 3, 4]] = ''\\n self._price_ladder_df.iloc[:, 2] = [self._config[\\n 'price_format'].format(x) for x in self._price_ladder]\\n\\n # Populate price ladder dataframe and update table cells.\\n for i in range(self._config['row_count']):\\n if math.isclose(self._price_ladder[i],\\n self._quotes_df.loc[self._quotes_row, 'ask_price']):\\n self._price_ladder_df.iloc[i, 3] = str(\\n self._quotes_df.loc[self._quotes_row, 'ask_size'])\\n else:\\n self._price_ladder_df.iloc[i, 3] = ''\\n if math.isclose(self._price_ladder[i],\\n self._quotes_df.loc[self._quotes_row, 'bid_price']):\\n self._price_ladder_df.iloc[i, 1] = str(\\n self._quotes_df.loc[self._quotes_row, 'bid_size'])\\n else:\\n self._price_ladder_df.iloc[i, 1] = ''\\n\\n # Print this quote row and update counter.\\n print(self._quotes_df.iloc[self._quotes_row, ].values)\\n self._quotes_row += 1\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.653335","0.6431408","0.6352757","0.6336871","0.6145967","0.59902364","0.5716785","0.56393623","0.56122774","0.55956626","0.5582768","0.553678","0.5504171","0.54466707","0.5415386","0.5409386","0.5396369","0.53878236","0.53794277","0.5378179","0.5345203","0.5331043","0.53259367","0.5307158","0.53043395","0.5269143","0.52533394","0.52194005","0.52115613","0.5178443","0.5177503","0.51339245","0.5117321","0.5101365","0.5098104","0.5090539","0.50508845","0.504451","0.5043557","0.5041141","0.5013209","0.50096995","0.49886718","0.49886718","0.49852523","0.49804297","0.49798962","0.4960304","0.49511838","0.49501657","0.4943179","0.49118915","0.49073744","0.489945","0.4895241","0.4882445","0.4879","0.4872242","0.48700035","0.48667273","0.48627943","0.48549333","0.48534313","0.4845914","0.4844839","0.4844826","0.48411196","0.48370466","0.4836705","0.48253566","0.4820393","0.4815391","0.48092598","0.48035273","0.48004436","0.47983745","0.47862527","0.47838238","0.47796184","0.47791433","0.4771134","0.47511312","0.47454718","0.47399017","0.4736323","0.4736323","0.47265276","0.4724201","0.4722293","0.47124943","0.47113773","0.47078452","0.47048512","0.46841323","0.46701217","0.46698296","0.4667975","0.4667975","0.46675208","0.46495566"],"string":"[\n \"0.653335\",\n \"0.6431408\",\n \"0.6352757\",\n \"0.6336871\",\n \"0.6145967\",\n \"0.59902364\",\n \"0.5716785\",\n \"0.56393623\",\n \"0.56122774\",\n \"0.55956626\",\n \"0.5582768\",\n \"0.553678\",\n \"0.5504171\",\n \"0.54466707\",\n \"0.5415386\",\n \"0.5409386\",\n \"0.5396369\",\n \"0.53878236\",\n \"0.53794277\",\n \"0.5378179\",\n \"0.5345203\",\n \"0.5331043\",\n \"0.53259367\",\n \"0.5307158\",\n \"0.53043395\",\n \"0.5269143\",\n \"0.52533394\",\n \"0.52194005\",\n \"0.52115613\",\n \"0.5178443\",\n \"0.5177503\",\n \"0.51339245\",\n \"0.5117321\",\n \"0.5101365\",\n \"0.5098104\",\n \"0.5090539\",\n \"0.50508845\",\n \"0.504451\",\n \"0.5043557\",\n \"0.5041141\",\n \"0.5013209\",\n \"0.50096995\",\n \"0.49886718\",\n \"0.49886718\",\n \"0.49852523\",\n \"0.49804297\",\n \"0.49798962\",\n \"0.4960304\",\n \"0.49511838\",\n \"0.49501657\",\n \"0.4943179\",\n \"0.49118915\",\n \"0.49073744\",\n \"0.489945\",\n \"0.4895241\",\n \"0.4882445\",\n \"0.4879\",\n \"0.4872242\",\n \"0.48700035\",\n \"0.48667273\",\n \"0.48627943\",\n \"0.48549333\",\n \"0.48534313\",\n \"0.4845914\",\n \"0.4844839\",\n \"0.4844826\",\n \"0.48411196\",\n \"0.48370466\",\n \"0.4836705\",\n \"0.48253566\",\n \"0.4820393\",\n \"0.4815391\",\n \"0.48092598\",\n \"0.48035273\",\n \"0.48004436\",\n \"0.47983745\",\n \"0.47862527\",\n \"0.47838238\",\n \"0.47796184\",\n \"0.47791433\",\n \"0.4771134\",\n \"0.47511312\",\n \"0.47454718\",\n \"0.47399017\",\n \"0.4736323\",\n \"0.4736323\",\n \"0.47265276\",\n \"0.4724201\",\n \"0.4722293\",\n \"0.47124943\",\n \"0.47113773\",\n \"0.47078452\",\n \"0.47048512\",\n \"0.46841323\",\n \"0.46701217\",\n \"0.46698296\",\n \"0.4667975\",\n \"0.4667975\",\n \"0.46675208\",\n \"0.46495566\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.59978676"},"document_rank":{"kind":"string","value":"5"}}},{"rowIdx":13093,"cells":{"query":{"kind":"string","value":"Delete old files from FS, nullify path value in DB"},"document":{"kind":"string","value":"def remove_files(max_age_sec):\n with session_transaction() as session:\n nb_deleted = File.remove_old_files(max_age_sec, session)\n log.debug(\"Max_age_sec: %s Nb_deleted: %s\", max_age_sec, nb_deleted)\n return nb_deleted"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def delete_path():\n #TODO delete path from database\n pass","def clear_outdated_files():\n for f in os.listdir(MEDIA_ROOT):\n file_path = os.path.join(MEDIA_ROOT, f)\n if os.path.isfile(file_path) and os.stat(file_path).st_mtime < time.time() - STORE_PDF_DAYS * 86400:\n os.remove(file_path)","def cleanup(self):\n files = self.nlst()\n latest = self.latest_filename\n for filename in files:\n if filename != latest:\n result = self.delete(filename)\n logger.info(f\"Deleted old export from FTP: {result}\")","def unlink ( self, fspath ):\n return","def remove(path):","def unlink(self, path: PathLike):","def auto_delete_file_on_delete(sender, instance, **kwargs):\r\n if instance.path:\r\n if os.path.isfile(instance.path.path):\r\n os.remove(instance.path.path)","def remove_file(self, path):\n pass","def cleanUp(self, f):\n os.system('rm ' + f)","def remove(self, path):\n path = path.decode('utf8')\n cursor = self._dbcon.cursor()\n filename = os.path.basename(path)\n dirname = os.path.dirname(path)\n t = (dirname, filename)\n sql = u\"delete from books where path = ? and filename = ?\"\n cursor.execute(sql, t)\n self._dbcon.commit()\n cursor.close()","def delete(self, filename):\n pass","def clean(self):\n if os.path.exists(self.initial):\n if os.path.exists(self.path) and os.stat(self.path).st_size == os.stat(\n self.initial).st_size:\n os.remove(self.initial)\n else:\n # if it doesn't match, something probably crashed; rename the temporary file and\n # it'll get uploaded at some point\n self.auto_filename()\n self.rename()\n self.connect()\n os.remove(self.initial)\n if os.path.exists(self.path):\n os.remove(self.path)\n self.filename_set = False","def delete_leftovers(self):\n for each_file, artist in self.past_songs_db_data:\n if os.path.isfile(each_file): \n os.remove(each_file)\n print \"Deleted \" + each_file\n\n for each_file in os.listdir(\".\"):\n if each_file.endswith(\".jpg\"):\n os.remove(each_file)","def auto_delete_file_on_delete(sender, instance, **kwargs):\r\n if instance.image:\r\n if pathlib.Path(instance.image.path).is_file():\r\n pathlib.Path(instance.image.path).unlink()","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(mapper, connection, target):\n if target.filename and app.config['CLEANUP_FILES']:\n try:\n os.remove(join(app.config['FILE_PATH'], str(target.talk.id),\n str(target.version), target.filename))\n except OSError:\n # We don't care if wasn't deleted because it does not exist\n pass","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.document:\n if os.path.isfile(instance.document.path):\n os.remove(instance.document.path)","def clear_old_files(self):\n self.logger.logMsg(\"Clearing Old Files.....\")\n try:\n for files in os.listdir(self.download_path):\n path = os.path.join(self.download_path, files)\n os.remove(path)\n for files in os.listdir(self.outpath):\n path = os.path.join(self.outpath, files)\n os.remove(path)\n except Exception as e:\n self.logger.logError(\"Error Creating Old Files {}.....\".format(str(e)))\n raise Exception('Error in Clearing Old Files')\n\n self.logger.logMsg(\"Done Clearing Old Files.....\")","def auto_delete_file_on_change(sender, instance, **kwargs):\n if not instance.pk:\n return False\n\n try:\n old_file = SkyLabFile.objects.get(pk=instance.pk).file\n except SkyLabFile.DoesNotExist:\n return False\n\n if old_file:\n new_file = instance.file\n if not old_file == new_file:\n if os.path.isfile(old_file.path):\n os.remove(old_file.path)","def delete_db(self):\n import os.path\n os.remove(self.filepath)","def cleanup_files(self):\n\n self.backup_files()\n self.delete_files()","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.file:\n if os.path.isfile(instance.file.path):\n os.remove(instance.file.path)","def purge_outdated(self):\n todelete = []\n sql = \"select rowid, path, mtime from pictures\"\n cur = self.con.execute(sql)\n for rowid, path_str, mtime in cur:\n if mtime and op.exists(path_str):\n picture_mtime = os.stat(path_str).st_mtime\n if int(picture_mtime) <= mtime:\n # not outdated\n continue\n todelete.append(rowid)\n if todelete:\n sql = \"delete from pictures where rowid in (%s)\" % ','.join(map(str, todelete))\n self.con.execute(sql)","def clean_old_data():\n logger.info('Cleaning standalone files on disk...')\n for absolute_path in glob.glob(MEDIA_URL + '*'):\n file_name = os.path.basename(absolute_path)\n try:\n relative_path = os.path.join(AUDIOS_URL, file_name)\n audio = Audio.objects.get(filename=relative_path)\n if audio.get_type() == 'episode':\n try:\n # If there are inactive audios on its being\n for e in audio.podcast.episode_set.exclude(pk=audio.podcast.active_episode.pk):\n if not e.is_active():\n logger.info('Inactive audio found in podcast set. Erasing files.')\n e.delete_files()\n except Exception, e:\n logger.exception(e.message)\n except ObjectDoesNotExist, e:\n logger.info('A file with no audio registered in database')\n if os.path.isfile(relative_path):\n logger.info('Erasing: %s' % relative_path)\n os.remove(relative_path)\n logger.info('... Done.')","def remove_file(path):\n pyCMD('hdfs', ['dfs', '-rm', '-skipTrash', path]).execute()","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete(self):\n if os.path.exists(self.file_path):\n os.remove(self.file_path)","def remove_expired_files():\n from models import FlowFile\n FlowFile.objects.filter(\n state__in=[FlowFile.STATE_UPLOADING, FlowFile.STATE_UPLOAD_ERROR],\n updated__lte=datetime.datetime.date() - datetime.timedelta(days=FLOWJS_EXPIRATION_DAYS)\n ).delete()","def cleanUp(self):\r\n remove_files(self._db_files_to_remove, error_on_missing=False)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n\n if instance.file:\n if os.path.isfile(instance.file.path):\n os.remove(instance.file.path)","def flow_file_delete(sender, instance, **kwargs):\n if FLOWJS_REMOVE_FILES_ON_DELETE:\n try:\n default_storage.delete(instance.path)\n except NotImplementedError:\n pass","def del_files_from_disk(path):\n\n shutil.rmtree(path) #,ignore_errors=True)","def cleanup_file(name: str):\n if os.path.exists(name) and os.path.isfile(name): # h5\n os.remove(name)\n elif os.path.exists(name) and os.path.isdir(name): # tf\n shutil.rmtree(name)","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete(self):\n if not pdbox._args.get(\"dryrun\"):\n result = execute(pdbox.dbx.files_delete_v2, self.path)\n pdbox.debug(\"Metadata response: %s\" % result.metadata)\n pdbox.info(\"Deleted %s\" % self.uri)","def test_file_deleted(self):\n try:\n with get_temp_file() as (fd, name):\n os.unlink(name)\n except Exception as err:\n self.fail('Failed with exception \"{}\"'.format(err))","def delete_old():\n folder = '../build/data/vtk'\n for the_file in os.listdir(folder):\n file_path = os.path.join(folder, the_file)\n try:\n if os.path.isfile(file_path):\n os.unlink(file_path)\n elif os.path.isdir(file_path):\n shutil.rmtree(file_path) # subdirs\n except Exception as e:\n print(e)\n folder = '../build/log'\n for the_file in os.listdir(folder):\n file_path = os.path.join(folder, the_file)\n try:\n if os.path.isfile(file_path):\n os.unlink(file_path)\n # elif os.path.isdir(file_path): shutil.rmtree(file_path) #subdirs\n except Exception as e:\n print(e)","def erase_files(self):\n self.ofile_handle()\n self.efile_handle()\n\n os.remove(self.ofile_name())\n os.remove(self.efile_name())\n return None","def delete_file(self, lfile):\n raise NotImplementedError('delete_file')","def db_remove():\n\n db.session.close()\n db.drop_all()\n\n path = current_app.config['SNER_VAR']\n for file_object in os.listdir(path):\n file_object_path = os.path.join(path, file_object)\n if os.path.isdir(file_object_path):\n shutil.rmtree(file_object_path)\n else:\n os.unlink(file_object_path)","def clean_filesystem(files=[]):\n remove_files(files + find_cache_files())","def rm(self, path):\n try:\n basedir, item = os.path.split(path)\n postdata = codecs.encode(json.dumps({ 'baseDir': basedir, 'items': [ item ] }), 'utf-8')\n self._urlopen('/api/fileops/delete', postdata).read()\n except HTTPError as err:\n raise RuntimeError(\"Unable to delete '{}'\".format(path))","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.img:\n if os.path.isfile(instance.img.path):\n os.remove(instance.img.path)","def del_files(rels_fl, last_fl, path):\n for i in rels_fl:\n if i[:-5] not in last_fl:\n os.remove(f'{path}/{i}')\n return","def _delete_data (self, path):\n head, tail = os.path.split(path)\n for subdir, dirs, files in os.walk(head):\n for file in files:\n if tail in file:\n os.remove(os.path.join(subdir, file))","def delete_previous_files():\n def delete(root: Path):\n shutil.rmtree(root / 'output', ignore_errors=True)\n for p in root.iterdir():\n if str(p).endswith(('.log', 'jobs.csv', 'csv.lock', '.yaml')):\n p.unlink()\n\n delete(wt_registration_dir)\n delete(mut_registration_dir)","def clean_temp_storage_dir(self, filenames):\n for fn in filenames:\n try:\n pathlib.Path(pathlib.PurePath(self.temp_storage_dir, fn)).unlink()\n except FileNotFoundError:\n pass","def delete(self):\n os.remove(self.file_path)\n super(VideoFile, self).delete()","def __del__(self):\n for filename in self.files:\n unlink(filename)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n to_delete = [\n instance.photo,\n instance.photo2,\n instance.photo3\n ]\n for photo in to_delete:\n if photo:\n if os.path.isfile(photo.path):\n os.remove(photo.path)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.env_pdf:\n if os.path.isfile(instance.env_pdf.path):\n os.remove(instance.env_pdf.path)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.evntf_xls:\n if os.path.isfile(instance.evntf_xls.path):\n os.remove(instance.evntf_xls.path)","def delete_file(self, instance, sender, **kwargs):\n super(AutoImageField, self).delete_file(instance, sender)\n if getattr(instance, self.attname):\n # Get full path and the base directory that contains the file\n file_name = getattr(instance,self.name).name\n basedir = os.path.dirname(file_name)\n \n # Look for thumbnails created from filters for the current filename\n # and delete the files\n mask = add_to_basename(file_name, '_*')\n [os.remove(os.path.join(basedir, f)) for f in glob.glob(mask)]","def auto_delete_file_on_delete(sender, instance, **kwargs):\n\n if instance.image:\n if os.path.isfile(instance.image.path):\n os.remove(instance.image.path)","def delete(self, *args, **kwargs):\n self.file.storage.delete(self.file.name)\n super().delete(*args, **kwargs)","def delete_previous_files(schema_name, path_template, path_static):\n list_file_static = listdir(path_static)\n list_file_template = listdir(path_template)\n if schema_name in list_file_static:\n tree_path = path.join(path_static, schema_name)\n rmtree(tree_path, ignore_errors=True)\n html_file_name = \"wrap_\" + schema_name + \".html\"\n if html_file_name in list_file_template:\n html_file_path = path.join(path_template, html_file_name)\n remove(html_file_path)","def delete(self):\n\n try:\n remove(self.file)\n except OSError:\n pass","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(file_id):\n file_obj = Data.objects.get(id=file_id)\n print(\"Removing file: \", file_obj.name)\n print(file_obj.file.path)\n file_dir = file_obj.file.path\n os.remove(file_dir)\n print(\"Done.\")","def _delete_file(self, path):\n if not self.mount():\n return False\n uri = self.path_to_uri(path)\n return self.gvfs.delete_file(uri)","def delete(self):\n\t\t#self.log.info(\"Deleting file {}\".format(self._filepath))\n\t\tos.remove(self._filepath)","def remove_previously_scanned(path):\n query = db_session.query(MediaFiles) \\\n .filter(MediaFiles.path.like(f'{path}%'))\n query.delete(synchronize_session='fetch')\n db_session.commit()\n return query.count()","def file_delete(self, path):\n params = {'root': self.session.root, 'path': format_path(path)}\n\n url, params, headers = self.request(\"/fileops/delete\", params)\n\n return self.rest_client.POST(url, params, headers)","def delete(self):\n\n del self.parent_mirror_dir[self.cvs_path]","def test_file_update_delete_conflict(self):\n dir0, dir1 = self.make_temp_dirs(2)\n self.write_file(dir0, \"foo\", \"bar\")\n self.sync_all()\n\n self.write_file(dir0, \"foo\", \"baz\")\n self.delete_file(dir1, \"foo\")\n self.sync_all()\n self.assertFileAbsent(dir0, \"foo\")\n self.assertFileAbsent(dir1, \"foo\")","def clear_files_paths(self):\n del self.__files_paths[:]","def cleanup(self):\r\n for f in [i for d in self.data.values() for i in d[\"filenames\"]]:\r\n try:\r\n os.unlink(f)\r\n except Exception: pass\r\n self.Destroy()","def _remove(path, force):\n if not os.path.exists(path):\n return\n elif os.path.isfile(path) and force:\n os.remove(path) # remove the file\n elif os.path.isdir(path) and force:\n import shutil\n shutil.rmtree(path) # remove dir and all contains\n else:\n print('Logdir contains data. Please, set `force` flag to overwrite it.')\n import sys\n sys.exit(0)","def delFiles(self):\r\n \r\n logStr = \"{0:s}.{1:s}: \".format(self.__class__.__name__, sys._getframe().f_code.co_name)\r\n logger.debug(\"{0:s}{1:s}\".format(logStr,'Start.')) \r\n \r\n try: \r\n if os.path.exists(self.h5File): \r\n os.remove(self.h5File) \r\n logger.debug(\"{0:s} File {1:s} deleted.\".format(logStr,self.h5File)) \r\n except XmError:\r\n raise \r\n except Exception as e:\r\n logStrFinal=\"{:s}Exception: Line: {:d}: {!s:s}: {:s}\".format(logStr,sys.exc_info()[-1].tb_lineno,type(e),str(e))\r\n logger.error(logStrFinal) \r\n raise XmError(logStrFinal) \r\n finally:\r\n logger.debug(\"{0:s}{1:s}\".format(logStr,'_Done.'))","def auto_delete_file_on_change(sender, instance, **kwargs):\n if not instance.pk:\n return False\n try:\n old_file = EnvCondFile.objects.get(pk=instance.pk).env_pdf\n except EnvCondFile.DoesNotExist:\n return False\n new_file = instance.env_pdf\n if old_file and not old_file == new_file:\n if os.path.isfile(old_file.path):\n os.remove(old_file.path)","def clean():\n clean_files()","def delete_file(path):\n return files.delete_file(path)","def delete(self, host, file):","def delete_file(self, hash):\n self.tree.delete(hash)\n query = \"delete from files where hash='%s'\"%hash\n self.connection.execute(query)\n self.connection.commit()","def delete(self) -> None:\n try:\n self._logger.debug('Delete old metadata file %s.', self._path)\n os.remove(self._path)\n except OSError as ex:\n if ex.errno != errno.ENOENT:\n msg = 'Failed to delete old metadata file. {}'.format(ex.strerror)\n raise MetaFileError(msg)","def auto_delete_file_on_change(sender, instance, **kwargs):\r\n if not instance.pk:\r\n return False\r\n\r\n try:\r\n old_file = Attachment.objects.get(pk=instance.pk).path\r\n except Attachment.DoesNotExist:\r\n return False\r\n\r\n new_file = instance.path\r\n if not old_file == new_file:\r\n if os.path.isfile(old_file.path):\r\n os.remove(old_file.path)","def delete(self, filename):\n raise NotImplementedError","def delete( self ):\n if os.path.exists(self.filename):\n os.remove(self.filename)","def photo_edit_file_cleanup(sender, **kwargs):\n instance = kwargs.get('instance')\n filename = instance.upload.url[1:]\n if os.path.exists(filename):\n os.remove(filename)","def delete(path, recursive=False):\n fs.delete(path, recursive)","def rm(path):\n abs_path = navigate.get_abs_path(path)\n parent, name = navigate.split_path(abs_path)\n access_token = db.get_access_to_file(parent, name)\n if access_token is not None:\n dbox_path = '/' + name\n client = dropbox.client.DropboxClient(access_token)\n client.file_delete(dbox_path)\n db.remove_file(access_token, parent, name)","def delete_data_file(path):\n cprint(f\"### Function Name:-> {inspect.stack()[0][3]} ###\", 'yellow', 'on_grey', attrs=['bold'])\n try:\n os.remove(path)\n except FileNotFoundError:\n pass","def delete(self):\n with self.locked():\n self.path.delete()","def delete(self):\n with self.locked():\n self.path.delete()","def delete_file(input_fn):\r\n if os.path.isfile(input_fn):\r\n os.remove(input_fn)","def rm_f(path):\n try:\n os.unlink(path)\n except OSError as e:\n if e.errno != errno.ENOENT:\n raise","def remove_dataset_file(sender, instance, **kwargs):\n if instance.original_file:\n if os.path.isfile(instance.original_file.path):\n os.remove(instance.original_file.path)","def rem_file(self, key):\n del self.fileList[key]\n\n path = os.path.join(self.file_path, '%s.xoj' % key)\n try:\n os.remove( path )\n except:\n print \"Unable to remove\", path\n self.save()","def fs_remove_entry(self, path):\n\t\treturn Job(SDK.PrlSrv_FsRemoveEntry(self.handle, path)[0])","def photo_file_cleanup(sender, **kwargs):\n instance = kwargs.get('instance')\n filename = instance.path.url[1:]\n if os.path.exists(filename):\n os.remove(filename)","def refresh(path):\n if os.path.exists(path):\n os.remove(path)\n return path","def cleanStamps(self, criteria):\n dirEmpty = True\n for s in self.iterStamps():\n if criteria(s):\n os.unlink(self.getFile(s))\n else:\n dirEmpty = False\n try:\n os.rmdir(self.path)\n except OSError:\n pass","def remove_file(path: str) -> None:\n\tremove(path)","def clean_files(self):\n self.filenames.clear()","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.protf_pdf:\n if os.path.isfile(instance.protf_pdf.path):\n os.remove(instance.protf_pdf.path)","def auto_delete_file_on_change(sender, instance, **kwargs):\n if not instance.pk:\n return False\n\n try:\n old_file = ReportTemplates.objects.get(pk=instance.pk).document\n except ReportTemplates.DoesNotExist:\n return False\n\n new_file = instance.document\n if not old_file == new_file:\n if os.path.isfile(old_file.path):\n os.remove(old_file.path)","def cleanup_callback(self, job: Job):\n from projects.models.files import File\n\n File.objects.filter(project=self, current=True).update(current=False)","def on_deleted(self, event):\n super(myEventHandler,self).on_deleted(event)\n #print \"Removed: \" + event.src_path\n if self.onedir.cookies is None or not self.onedir.autosyncstatus():\n return\n\n source = event.src_path\n if event.is_directory:\n try:\n pathtoonedir = self.onedir.getonedirrectory()\n relpath = source.replace(pathtoonedir ,\"\")\n self.onedir.deldirectory(relpath)\n except Exception as e:\n print \"Error syncing directory\" + e\n exit(1)\n else:\n try:\n #use os.path.split to get file name and path\n splitpath = split(source)\n file = splitpath[1]\n pathtoonedir = self.onedir.getonedirrectory()\n #print pathtoonedir\n #print \"truncated path:\"\n relpath = splitpath[0].replace(pathtoonedir ,\"\")\n self.onedir.deletefile(file, relpath)\n except OSError as e:\n print \"Error copying file! \" + e.strerror\n exit(1)\n except IOError as e:\n print \"IOerror creating file \" + e.strerror\n exit(1)","def svn_fs_delete_fs(*args):\r\n return _fs.svn_fs_delete_fs(*args)","def rm_file(file_):\n Path(file_).unlink(missing_ok=True)"],"string":"[\n \"def delete_path():\\n #TODO delete path from database\\n pass\",\n \"def clear_outdated_files():\\n for f in os.listdir(MEDIA_ROOT):\\n file_path = os.path.join(MEDIA_ROOT, f)\\n if os.path.isfile(file_path) and os.stat(file_path).st_mtime < time.time() - STORE_PDF_DAYS * 86400:\\n os.remove(file_path)\",\n \"def cleanup(self):\\n files = self.nlst()\\n latest = self.latest_filename\\n for filename in files:\\n if filename != latest:\\n result = self.delete(filename)\\n logger.info(f\\\"Deleted old export from FTP: {result}\\\")\",\n \"def unlink ( self, fspath ):\\n return\",\n \"def remove(path):\",\n \"def unlink(self, path: PathLike):\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\r\\n if instance.path:\\r\\n if os.path.isfile(instance.path.path):\\r\\n os.remove(instance.path.path)\",\n \"def remove_file(self, path):\\n pass\",\n \"def cleanUp(self, f):\\n os.system('rm ' + f)\",\n \"def remove(self, path):\\n path = path.decode('utf8')\\n cursor = self._dbcon.cursor()\\n filename = os.path.basename(path)\\n dirname = os.path.dirname(path)\\n t = (dirname, filename)\\n sql = u\\\"delete from books where path = ? and filename = ?\\\"\\n cursor.execute(sql, t)\\n self._dbcon.commit()\\n cursor.close()\",\n \"def delete(self, filename):\\n pass\",\n \"def clean(self):\\n if os.path.exists(self.initial):\\n if os.path.exists(self.path) and os.stat(self.path).st_size == os.stat(\\n self.initial).st_size:\\n os.remove(self.initial)\\n else:\\n # if it doesn't match, something probably crashed; rename the temporary file and\\n # it'll get uploaded at some point\\n self.auto_filename()\\n self.rename()\\n self.connect()\\n os.remove(self.initial)\\n if os.path.exists(self.path):\\n os.remove(self.path)\\n self.filename_set = False\",\n \"def delete_leftovers(self):\\n for each_file, artist in self.past_songs_db_data:\\n if os.path.isfile(each_file): \\n os.remove(each_file)\\n print \\\"Deleted \\\" + each_file\\n\\n for each_file in os.listdir(\\\".\\\"):\\n if each_file.endswith(\\\".jpg\\\"):\\n os.remove(each_file)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\r\\n if instance.image:\\r\\n if pathlib.Path(instance.image.path).is_file():\\r\\n pathlib.Path(instance.image.path).unlink()\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(mapper, connection, target):\\n if target.filename and app.config['CLEANUP_FILES']:\\n try:\\n os.remove(join(app.config['FILE_PATH'], str(target.talk.id),\\n str(target.version), target.filename))\\n except OSError:\\n # We don't care if wasn't deleted because it does not exist\\n pass\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.document:\\n if os.path.isfile(instance.document.path):\\n os.remove(instance.document.path)\",\n \"def clear_old_files(self):\\n self.logger.logMsg(\\\"Clearing Old Files.....\\\")\\n try:\\n for files in os.listdir(self.download_path):\\n path = os.path.join(self.download_path, files)\\n os.remove(path)\\n for files in os.listdir(self.outpath):\\n path = os.path.join(self.outpath, files)\\n os.remove(path)\\n except Exception as e:\\n self.logger.logError(\\\"Error Creating Old Files {}.....\\\".format(str(e)))\\n raise Exception('Error in Clearing Old Files')\\n\\n self.logger.logMsg(\\\"Done Clearing Old Files.....\\\")\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\n if not instance.pk:\\n return False\\n\\n try:\\n old_file = SkyLabFile.objects.get(pk=instance.pk).file\\n except SkyLabFile.DoesNotExist:\\n return False\\n\\n if old_file:\\n new_file = instance.file\\n if not old_file == new_file:\\n if os.path.isfile(old_file.path):\\n os.remove(old_file.path)\",\n \"def delete_db(self):\\n import os.path\\n os.remove(self.filepath)\",\n \"def cleanup_files(self):\\n\\n self.backup_files()\\n self.delete_files()\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.file:\\n if os.path.isfile(instance.file.path):\\n os.remove(instance.file.path)\",\n \"def purge_outdated(self):\\n todelete = []\\n sql = \\\"select rowid, path, mtime from pictures\\\"\\n cur = self.con.execute(sql)\\n for rowid, path_str, mtime in cur:\\n if mtime and op.exists(path_str):\\n picture_mtime = os.stat(path_str).st_mtime\\n if int(picture_mtime) <= mtime:\\n # not outdated\\n continue\\n todelete.append(rowid)\\n if todelete:\\n sql = \\\"delete from pictures where rowid in (%s)\\\" % ','.join(map(str, todelete))\\n self.con.execute(sql)\",\n \"def clean_old_data():\\n logger.info('Cleaning standalone files on disk...')\\n for absolute_path in glob.glob(MEDIA_URL + '*'):\\n file_name = os.path.basename(absolute_path)\\n try:\\n relative_path = os.path.join(AUDIOS_URL, file_name)\\n audio = Audio.objects.get(filename=relative_path)\\n if audio.get_type() == 'episode':\\n try:\\n # If there are inactive audios on its being\\n for e in audio.podcast.episode_set.exclude(pk=audio.podcast.active_episode.pk):\\n if not e.is_active():\\n logger.info('Inactive audio found in podcast set. Erasing files.')\\n e.delete_files()\\n except Exception, e:\\n logger.exception(e.message)\\n except ObjectDoesNotExist, e:\\n logger.info('A file with no audio registered in database')\\n if os.path.isfile(relative_path):\\n logger.info('Erasing: %s' % relative_path)\\n os.remove(relative_path)\\n logger.info('... Done.')\",\n \"def remove_file(path):\\n pyCMD('hdfs', ['dfs', '-rm', '-skipTrash', path]).execute()\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete(self):\\n if os.path.exists(self.file_path):\\n os.remove(self.file_path)\",\n \"def remove_expired_files():\\n from models import FlowFile\\n FlowFile.objects.filter(\\n state__in=[FlowFile.STATE_UPLOADING, FlowFile.STATE_UPLOAD_ERROR],\\n updated__lte=datetime.datetime.date() - datetime.timedelta(days=FLOWJS_EXPIRATION_DAYS)\\n ).delete()\",\n \"def cleanUp(self):\\r\\n remove_files(self._db_files_to_remove, error_on_missing=False)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n\\n if instance.file:\\n if os.path.isfile(instance.file.path):\\n os.remove(instance.file.path)\",\n \"def flow_file_delete(sender, instance, **kwargs):\\n if FLOWJS_REMOVE_FILES_ON_DELETE:\\n try:\\n default_storage.delete(instance.path)\\n except NotImplementedError:\\n pass\",\n \"def del_files_from_disk(path):\\n\\n shutil.rmtree(path) #,ignore_errors=True)\",\n \"def cleanup_file(name: str):\\n if os.path.exists(name) and os.path.isfile(name): # h5\\n os.remove(name)\\n elif os.path.exists(name) and os.path.isdir(name): # tf\\n shutil.rmtree(name)\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete(self):\\n if not pdbox._args.get(\\\"dryrun\\\"):\\n result = execute(pdbox.dbx.files_delete_v2, self.path)\\n pdbox.debug(\\\"Metadata response: %s\\\" % result.metadata)\\n pdbox.info(\\\"Deleted %s\\\" % self.uri)\",\n \"def test_file_deleted(self):\\n try:\\n with get_temp_file() as (fd, name):\\n os.unlink(name)\\n except Exception as err:\\n self.fail('Failed with exception \\\"{}\\\"'.format(err))\",\n \"def delete_old():\\n folder = '../build/data/vtk'\\n for the_file in os.listdir(folder):\\n file_path = os.path.join(folder, the_file)\\n try:\\n if os.path.isfile(file_path):\\n os.unlink(file_path)\\n elif os.path.isdir(file_path):\\n shutil.rmtree(file_path) # subdirs\\n except Exception as e:\\n print(e)\\n folder = '../build/log'\\n for the_file in os.listdir(folder):\\n file_path = os.path.join(folder, the_file)\\n try:\\n if os.path.isfile(file_path):\\n os.unlink(file_path)\\n # elif os.path.isdir(file_path): shutil.rmtree(file_path) #subdirs\\n except Exception as e:\\n print(e)\",\n \"def erase_files(self):\\n self.ofile_handle()\\n self.efile_handle()\\n\\n os.remove(self.ofile_name())\\n os.remove(self.efile_name())\\n return None\",\n \"def delete_file(self, lfile):\\n raise NotImplementedError('delete_file')\",\n \"def db_remove():\\n\\n db.session.close()\\n db.drop_all()\\n\\n path = current_app.config['SNER_VAR']\\n for file_object in os.listdir(path):\\n file_object_path = os.path.join(path, file_object)\\n if os.path.isdir(file_object_path):\\n shutil.rmtree(file_object_path)\\n else:\\n os.unlink(file_object_path)\",\n \"def clean_filesystem(files=[]):\\n remove_files(files + find_cache_files())\",\n \"def rm(self, path):\\n try:\\n basedir, item = os.path.split(path)\\n postdata = codecs.encode(json.dumps({ 'baseDir': basedir, 'items': [ item ] }), 'utf-8')\\n self._urlopen('/api/fileops/delete', postdata).read()\\n except HTTPError as err:\\n raise RuntimeError(\\\"Unable to delete '{}'\\\".format(path))\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.img:\\n if os.path.isfile(instance.img.path):\\n os.remove(instance.img.path)\",\n \"def del_files(rels_fl, last_fl, path):\\n for i in rels_fl:\\n if i[:-5] not in last_fl:\\n os.remove(f'{path}/{i}')\\n return\",\n \"def _delete_data (self, path):\\n head, tail = os.path.split(path)\\n for subdir, dirs, files in os.walk(head):\\n for file in files:\\n if tail in file:\\n os.remove(os.path.join(subdir, file))\",\n \"def delete_previous_files():\\n def delete(root: Path):\\n shutil.rmtree(root / 'output', ignore_errors=True)\\n for p in root.iterdir():\\n if str(p).endswith(('.log', 'jobs.csv', 'csv.lock', '.yaml')):\\n p.unlink()\\n\\n delete(wt_registration_dir)\\n delete(mut_registration_dir)\",\n \"def clean_temp_storage_dir(self, filenames):\\n for fn in filenames:\\n try:\\n pathlib.Path(pathlib.PurePath(self.temp_storage_dir, fn)).unlink()\\n except FileNotFoundError:\\n pass\",\n \"def delete(self):\\n os.remove(self.file_path)\\n super(VideoFile, self).delete()\",\n \"def __del__(self):\\n for filename in self.files:\\n unlink(filename)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n to_delete = [\\n instance.photo,\\n instance.photo2,\\n instance.photo3\\n ]\\n for photo in to_delete:\\n if photo:\\n if os.path.isfile(photo.path):\\n os.remove(photo.path)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.env_pdf:\\n if os.path.isfile(instance.env_pdf.path):\\n os.remove(instance.env_pdf.path)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.evntf_xls:\\n if os.path.isfile(instance.evntf_xls.path):\\n os.remove(instance.evntf_xls.path)\",\n \"def delete_file(self, instance, sender, **kwargs):\\n super(AutoImageField, self).delete_file(instance, sender)\\n if getattr(instance, self.attname):\\n # Get full path and the base directory that contains the file\\n file_name = getattr(instance,self.name).name\\n basedir = os.path.dirname(file_name)\\n \\n # Look for thumbnails created from filters for the current filename\\n # and delete the files\\n mask = add_to_basename(file_name, '_*')\\n [os.remove(os.path.join(basedir, f)) for f in glob.glob(mask)]\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n\\n if instance.image:\\n if os.path.isfile(instance.image.path):\\n os.remove(instance.image.path)\",\n \"def delete(self, *args, **kwargs):\\n self.file.storage.delete(self.file.name)\\n super().delete(*args, **kwargs)\",\n \"def delete_previous_files(schema_name, path_template, path_static):\\n list_file_static = listdir(path_static)\\n list_file_template = listdir(path_template)\\n if schema_name in list_file_static:\\n tree_path = path.join(path_static, schema_name)\\n rmtree(tree_path, ignore_errors=True)\\n html_file_name = \\\"wrap_\\\" + schema_name + \\\".html\\\"\\n if html_file_name in list_file_template:\\n html_file_path = path.join(path_template, html_file_name)\\n remove(html_file_path)\",\n \"def delete(self):\\n\\n try:\\n remove(self.file)\\n except OSError:\\n pass\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(file_id):\\n file_obj = Data.objects.get(id=file_id)\\n print(\\\"Removing file: \\\", file_obj.name)\\n print(file_obj.file.path)\\n file_dir = file_obj.file.path\\n os.remove(file_dir)\\n print(\\\"Done.\\\")\",\n \"def _delete_file(self, path):\\n if not self.mount():\\n return False\\n uri = self.path_to_uri(path)\\n return self.gvfs.delete_file(uri)\",\n \"def delete(self):\\n\\t\\t#self.log.info(\\\"Deleting file {}\\\".format(self._filepath))\\n\\t\\tos.remove(self._filepath)\",\n \"def remove_previously_scanned(path):\\n query = db_session.query(MediaFiles) \\\\\\n .filter(MediaFiles.path.like(f'{path}%'))\\n query.delete(synchronize_session='fetch')\\n db_session.commit()\\n return query.count()\",\n \"def file_delete(self, path):\\n params = {'root': self.session.root, 'path': format_path(path)}\\n\\n url, params, headers = self.request(\\\"/fileops/delete\\\", params)\\n\\n return self.rest_client.POST(url, params, headers)\",\n \"def delete(self):\\n\\n del self.parent_mirror_dir[self.cvs_path]\",\n \"def test_file_update_delete_conflict(self):\\n dir0, dir1 = self.make_temp_dirs(2)\\n self.write_file(dir0, \\\"foo\\\", \\\"bar\\\")\\n self.sync_all()\\n\\n self.write_file(dir0, \\\"foo\\\", \\\"baz\\\")\\n self.delete_file(dir1, \\\"foo\\\")\\n self.sync_all()\\n self.assertFileAbsent(dir0, \\\"foo\\\")\\n self.assertFileAbsent(dir1, \\\"foo\\\")\",\n \"def clear_files_paths(self):\\n del self.__files_paths[:]\",\n \"def cleanup(self):\\r\\n for f in [i for d in self.data.values() for i in d[\\\"filenames\\\"]]:\\r\\n try:\\r\\n os.unlink(f)\\r\\n except Exception: pass\\r\\n self.Destroy()\",\n \"def _remove(path, force):\\n if not os.path.exists(path):\\n return\\n elif os.path.isfile(path) and force:\\n os.remove(path) # remove the file\\n elif os.path.isdir(path) and force:\\n import shutil\\n shutil.rmtree(path) # remove dir and all contains\\n else:\\n print('Logdir contains data. Please, set `force` flag to overwrite it.')\\n import sys\\n sys.exit(0)\",\n \"def delFiles(self):\\r\\n \\r\\n logStr = \\\"{0:s}.{1:s}: \\\".format(self.__class__.__name__, sys._getframe().f_code.co_name)\\r\\n logger.debug(\\\"{0:s}{1:s}\\\".format(logStr,'Start.')) \\r\\n \\r\\n try: \\r\\n if os.path.exists(self.h5File): \\r\\n os.remove(self.h5File) \\r\\n logger.debug(\\\"{0:s} File {1:s} deleted.\\\".format(logStr,self.h5File)) \\r\\n except XmError:\\r\\n raise \\r\\n except Exception as e:\\r\\n logStrFinal=\\\"{:s}Exception: Line: {:d}: {!s:s}: {:s}\\\".format(logStr,sys.exc_info()[-1].tb_lineno,type(e),str(e))\\r\\n logger.error(logStrFinal) \\r\\n raise XmError(logStrFinal) \\r\\n finally:\\r\\n logger.debug(\\\"{0:s}{1:s}\\\".format(logStr,'_Done.'))\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\n if not instance.pk:\\n return False\\n try:\\n old_file = EnvCondFile.objects.get(pk=instance.pk).env_pdf\\n except EnvCondFile.DoesNotExist:\\n return False\\n new_file = instance.env_pdf\\n if old_file and not old_file == new_file:\\n if os.path.isfile(old_file.path):\\n os.remove(old_file.path)\",\n \"def clean():\\n clean_files()\",\n \"def delete_file(path):\\n return files.delete_file(path)\",\n \"def delete(self, host, file):\",\n \"def delete_file(self, hash):\\n self.tree.delete(hash)\\n query = \\\"delete from files where hash='%s'\\\"%hash\\n self.connection.execute(query)\\n self.connection.commit()\",\n \"def delete(self) -> None:\\n try:\\n self._logger.debug('Delete old metadata file %s.', self._path)\\n os.remove(self._path)\\n except OSError as ex:\\n if ex.errno != errno.ENOENT:\\n msg = 'Failed to delete old metadata file. {}'.format(ex.strerror)\\n raise MetaFileError(msg)\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\r\\n if not instance.pk:\\r\\n return False\\r\\n\\r\\n try:\\r\\n old_file = Attachment.objects.get(pk=instance.pk).path\\r\\n except Attachment.DoesNotExist:\\r\\n return False\\r\\n\\r\\n new_file = instance.path\\r\\n if not old_file == new_file:\\r\\n if os.path.isfile(old_file.path):\\r\\n os.remove(old_file.path)\",\n \"def delete(self, filename):\\n raise NotImplementedError\",\n \"def delete( self ):\\n if os.path.exists(self.filename):\\n os.remove(self.filename)\",\n \"def photo_edit_file_cleanup(sender, **kwargs):\\n instance = kwargs.get('instance')\\n filename = instance.upload.url[1:]\\n if os.path.exists(filename):\\n os.remove(filename)\",\n \"def delete(path, recursive=False):\\n fs.delete(path, recursive)\",\n \"def rm(path):\\n abs_path = navigate.get_abs_path(path)\\n parent, name = navigate.split_path(abs_path)\\n access_token = db.get_access_to_file(parent, name)\\n if access_token is not None:\\n dbox_path = '/' + name\\n client = dropbox.client.DropboxClient(access_token)\\n client.file_delete(dbox_path)\\n db.remove_file(access_token, parent, name)\",\n \"def delete_data_file(path):\\n cprint(f\\\"### Function Name:-> {inspect.stack()[0][3]} ###\\\", 'yellow', 'on_grey', attrs=['bold'])\\n try:\\n os.remove(path)\\n except FileNotFoundError:\\n pass\",\n \"def delete(self):\\n with self.locked():\\n self.path.delete()\",\n \"def delete(self):\\n with self.locked():\\n self.path.delete()\",\n \"def delete_file(input_fn):\\r\\n if os.path.isfile(input_fn):\\r\\n os.remove(input_fn)\",\n \"def rm_f(path):\\n try:\\n os.unlink(path)\\n except OSError as e:\\n if e.errno != errno.ENOENT:\\n raise\",\n \"def remove_dataset_file(sender, instance, **kwargs):\\n if instance.original_file:\\n if os.path.isfile(instance.original_file.path):\\n os.remove(instance.original_file.path)\",\n \"def rem_file(self, key):\\n del self.fileList[key]\\n\\n path = os.path.join(self.file_path, '%s.xoj' % key)\\n try:\\n os.remove( path )\\n except:\\n print \\\"Unable to remove\\\", path\\n self.save()\",\n \"def fs_remove_entry(self, path):\\n\\t\\treturn Job(SDK.PrlSrv_FsRemoveEntry(self.handle, path)[0])\",\n \"def photo_file_cleanup(sender, **kwargs):\\n instance = kwargs.get('instance')\\n filename = instance.path.url[1:]\\n if os.path.exists(filename):\\n os.remove(filename)\",\n \"def refresh(path):\\n if os.path.exists(path):\\n os.remove(path)\\n return path\",\n \"def cleanStamps(self, criteria):\\n dirEmpty = True\\n for s in self.iterStamps():\\n if criteria(s):\\n os.unlink(self.getFile(s))\\n else:\\n dirEmpty = False\\n try:\\n os.rmdir(self.path)\\n except OSError:\\n pass\",\n \"def remove_file(path: str) -> None:\\n\\tremove(path)\",\n \"def clean_files(self):\\n self.filenames.clear()\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.protf_pdf:\\n if os.path.isfile(instance.protf_pdf.path):\\n os.remove(instance.protf_pdf.path)\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\n if not instance.pk:\\n return False\\n\\n try:\\n old_file = ReportTemplates.objects.get(pk=instance.pk).document\\n except ReportTemplates.DoesNotExist:\\n return False\\n\\n new_file = instance.document\\n if not old_file == new_file:\\n if os.path.isfile(old_file.path):\\n os.remove(old_file.path)\",\n \"def cleanup_callback(self, job: Job):\\n from projects.models.files import File\\n\\n File.objects.filter(project=self, current=True).update(current=False)\",\n \"def on_deleted(self, event):\\n super(myEventHandler,self).on_deleted(event)\\n #print \\\"Removed: \\\" + event.src_path\\n if self.onedir.cookies is None or not self.onedir.autosyncstatus():\\n return\\n\\n source = event.src_path\\n if event.is_directory:\\n try:\\n pathtoonedir = self.onedir.getonedirrectory()\\n relpath = source.replace(pathtoonedir ,\\\"\\\")\\n self.onedir.deldirectory(relpath)\\n except Exception as e:\\n print \\\"Error syncing directory\\\" + e\\n exit(1)\\n else:\\n try:\\n #use os.path.split to get file name and path\\n splitpath = split(source)\\n file = splitpath[1]\\n pathtoonedir = self.onedir.getonedirrectory()\\n #print pathtoonedir\\n #print \\\"truncated path:\\\"\\n relpath = splitpath[0].replace(pathtoonedir ,\\\"\\\")\\n self.onedir.deletefile(file, relpath)\\n except OSError as e:\\n print \\\"Error copying file! \\\" + e.strerror\\n exit(1)\\n except IOError as e:\\n print \\\"IOerror creating file \\\" + e.strerror\\n exit(1)\",\n \"def svn_fs_delete_fs(*args):\\r\\n return _fs.svn_fs_delete_fs(*args)\",\n \"def rm_file(file_):\\n Path(file_).unlink(missing_ok=True)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.71850747","0.6885767","0.6821727","0.68192995","0.6756899","0.6753063","0.67357886","0.6704431","0.6660613","0.65907323","0.6541612","0.6512646","0.6490424","0.64857215","0.64697266","0.6452348","0.64341843","0.64337134","0.6421972","0.64179254","0.64138323","0.64116454","0.64085406","0.64055234","0.6402121","0.6385266","0.6385266","0.6378883","0.63680345","0.63608","0.63574564","0.6341553","0.63358545","0.63262635","0.63146496","0.630185","0.62974143","0.6290939","0.62758595","0.6275699","0.6274745","0.6272239","0.6271692","0.62703145","0.6269267","0.62615633","0.6233939","0.62298214","0.6224983","0.62221307","0.6212859","0.62124205","0.62106234","0.6205937","0.62027776","0.6200041","0.6189073","0.6186495","0.6180966","0.617889","0.6173629","0.61633027","0.6161804","0.6155666","0.61550146","0.61532706","0.6150393","0.61478734","0.6147375","0.61460215","0.61446303","0.6130369","0.61209434","0.6115923","0.6115417","0.61107934","0.61054325","0.6097067","0.6096262","0.609498","0.6092246","0.6089567","0.60874826","0.6076841","0.6076841","0.60720015","0.60679275","0.6065674","0.606122","0.60596234","0.605652","0.6053947","0.6046274","0.60438824","0.60398895","0.6038567","0.60333425","0.6032486","0.6025922","0.6025434","0.6022207"],"string":"[\n \"0.71850747\",\n \"0.6885767\",\n \"0.6821727\",\n \"0.68192995\",\n \"0.6756899\",\n \"0.6753063\",\n \"0.67357886\",\n \"0.6704431\",\n \"0.6660613\",\n \"0.65907323\",\n \"0.6541612\",\n \"0.6512646\",\n \"0.6490424\",\n \"0.64857215\",\n \"0.64697266\",\n \"0.6452348\",\n \"0.64341843\",\n \"0.64337134\",\n \"0.6421972\",\n \"0.64179254\",\n \"0.64138323\",\n \"0.64116454\",\n \"0.64085406\",\n \"0.64055234\",\n \"0.6402121\",\n \"0.6385266\",\n \"0.6385266\",\n \"0.6378883\",\n \"0.63680345\",\n \"0.63608\",\n \"0.63574564\",\n \"0.6341553\",\n \"0.63358545\",\n \"0.63262635\",\n \"0.63146496\",\n \"0.630185\",\n \"0.62974143\",\n \"0.6290939\",\n \"0.62758595\",\n \"0.6275699\",\n \"0.6274745\",\n \"0.6272239\",\n \"0.6271692\",\n \"0.62703145\",\n \"0.6269267\",\n \"0.62615633\",\n \"0.6233939\",\n \"0.62298214\",\n \"0.6224983\",\n \"0.62221307\",\n \"0.6212859\",\n \"0.62124205\",\n \"0.62106234\",\n \"0.6205937\",\n \"0.62027776\",\n \"0.6200041\",\n \"0.6189073\",\n \"0.6186495\",\n \"0.6180966\",\n \"0.617889\",\n \"0.6173629\",\n \"0.61633027\",\n \"0.6161804\",\n \"0.6155666\",\n \"0.61550146\",\n \"0.61532706\",\n \"0.6150393\",\n \"0.61478734\",\n \"0.6147375\",\n \"0.61460215\",\n \"0.61446303\",\n \"0.6130369\",\n \"0.61209434\",\n \"0.6115923\",\n \"0.6115417\",\n \"0.61107934\",\n \"0.61054325\",\n \"0.6097067\",\n \"0.6096262\",\n \"0.609498\",\n \"0.6092246\",\n \"0.6089567\",\n \"0.60874826\",\n \"0.6076841\",\n \"0.6076841\",\n \"0.60720015\",\n \"0.60679275\",\n \"0.6065674\",\n \"0.606122\",\n \"0.60596234\",\n \"0.605652\",\n \"0.6053947\",\n \"0.6046274\",\n \"0.60438824\",\n \"0.60398895\",\n \"0.6038567\",\n \"0.60333425\",\n \"0.6032486\",\n \"0.6025922\",\n \"0.6025434\",\n \"0.6022207\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13094,"cells":{"query":{"kind":"string","value":"Delete old files from FS, nullify path value in DB"},"document":{"kind":"string","value":"def remove_files_size(max_size):\n with session_transaction() as session:\n nb_deleted = File.remove_files_max_size(max_size, session)\n log.debug(\"Max_size: %s Nb_deleted: %s\", max_size, nb_deleted)\n return nb_deleted"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def delete_path():\n #TODO delete path from database\n pass","def clear_outdated_files():\n for f in os.listdir(MEDIA_ROOT):\n file_path = os.path.join(MEDIA_ROOT, f)\n if os.path.isfile(file_path) and os.stat(file_path).st_mtime < time.time() - STORE_PDF_DAYS * 86400:\n os.remove(file_path)","def cleanup(self):\n files = self.nlst()\n latest = self.latest_filename\n for filename in files:\n if filename != latest:\n result = self.delete(filename)\n logger.info(f\"Deleted old export from FTP: {result}\")","def unlink ( self, fspath ):\n return","def remove(path):","def unlink(self, path: PathLike):","def auto_delete_file_on_delete(sender, instance, **kwargs):\r\n if instance.path:\r\n if os.path.isfile(instance.path.path):\r\n os.remove(instance.path.path)","def remove_file(self, path):\n pass","def cleanUp(self, f):\n os.system('rm ' + f)","def remove(self, path):\n path = path.decode('utf8')\n cursor = self._dbcon.cursor()\n filename = os.path.basename(path)\n dirname = os.path.dirname(path)\n t = (dirname, filename)\n sql = u\"delete from books where path = ? and filename = ?\"\n cursor.execute(sql, t)\n self._dbcon.commit()\n cursor.close()","def delete(self, filename):\n pass","def clean(self):\n if os.path.exists(self.initial):\n if os.path.exists(self.path) and os.stat(self.path).st_size == os.stat(\n self.initial).st_size:\n os.remove(self.initial)\n else:\n # if it doesn't match, something probably crashed; rename the temporary file and\n # it'll get uploaded at some point\n self.auto_filename()\n self.rename()\n self.connect()\n os.remove(self.initial)\n if os.path.exists(self.path):\n os.remove(self.path)\n self.filename_set = False","def delete_leftovers(self):\n for each_file, artist in self.past_songs_db_data:\n if os.path.isfile(each_file): \n os.remove(each_file)\n print \"Deleted \" + each_file\n\n for each_file in os.listdir(\".\"):\n if each_file.endswith(\".jpg\"):\n os.remove(each_file)","def auto_delete_file_on_delete(sender, instance, **kwargs):\r\n if instance.image:\r\n if pathlib.Path(instance.image.path).is_file():\r\n pathlib.Path(instance.image.path).unlink()","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(mapper, connection, target):\n if target.filename and app.config['CLEANUP_FILES']:\n try:\n os.remove(join(app.config['FILE_PATH'], str(target.talk.id),\n str(target.version), target.filename))\n except OSError:\n # We don't care if wasn't deleted because it does not exist\n pass","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.document:\n if os.path.isfile(instance.document.path):\n os.remove(instance.document.path)","def clear_old_files(self):\n self.logger.logMsg(\"Clearing Old Files.....\")\n try:\n for files in os.listdir(self.download_path):\n path = os.path.join(self.download_path, files)\n os.remove(path)\n for files in os.listdir(self.outpath):\n path = os.path.join(self.outpath, files)\n os.remove(path)\n except Exception as e:\n self.logger.logError(\"Error Creating Old Files {}.....\".format(str(e)))\n raise Exception('Error in Clearing Old Files')\n\n self.logger.logMsg(\"Done Clearing Old Files.....\")","def auto_delete_file_on_change(sender, instance, **kwargs):\n if not instance.pk:\n return False\n\n try:\n old_file = SkyLabFile.objects.get(pk=instance.pk).file\n except SkyLabFile.DoesNotExist:\n return False\n\n if old_file:\n new_file = instance.file\n if not old_file == new_file:\n if os.path.isfile(old_file.path):\n os.remove(old_file.path)","def delete_db(self):\n import os.path\n os.remove(self.filepath)","def cleanup_files(self):\n\n self.backup_files()\n self.delete_files()","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.file:\n if os.path.isfile(instance.file.path):\n os.remove(instance.file.path)","def purge_outdated(self):\n todelete = []\n sql = \"select rowid, path, mtime from pictures\"\n cur = self.con.execute(sql)\n for rowid, path_str, mtime in cur:\n if mtime and op.exists(path_str):\n picture_mtime = os.stat(path_str).st_mtime\n if int(picture_mtime) <= mtime:\n # not outdated\n continue\n todelete.append(rowid)\n if todelete:\n sql = \"delete from pictures where rowid in (%s)\" % ','.join(map(str, todelete))\n self.con.execute(sql)","def clean_old_data():\n logger.info('Cleaning standalone files on disk...')\n for absolute_path in glob.glob(MEDIA_URL + '*'):\n file_name = os.path.basename(absolute_path)\n try:\n relative_path = os.path.join(AUDIOS_URL, file_name)\n audio = Audio.objects.get(filename=relative_path)\n if audio.get_type() == 'episode':\n try:\n # If there are inactive audios on its being\n for e in audio.podcast.episode_set.exclude(pk=audio.podcast.active_episode.pk):\n if not e.is_active():\n logger.info('Inactive audio found in podcast set. Erasing files.')\n e.delete_files()\n except Exception, e:\n logger.exception(e.message)\n except ObjectDoesNotExist, e:\n logger.info('A file with no audio registered in database')\n if os.path.isfile(relative_path):\n logger.info('Erasing: %s' % relative_path)\n os.remove(relative_path)\n logger.info('... Done.')","def remove_file(path):\n pyCMD('hdfs', ['dfs', '-rm', '-skipTrash', path]).execute()","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def _delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete(self):\n if os.path.exists(self.file_path):\n os.remove(self.file_path)","def remove_expired_files():\n from models import FlowFile\n FlowFile.objects.filter(\n state__in=[FlowFile.STATE_UPLOADING, FlowFile.STATE_UPLOAD_ERROR],\n updated__lte=datetime.datetime.date() - datetime.timedelta(days=FLOWJS_EXPIRATION_DAYS)\n ).delete()","def cleanUp(self):\r\n remove_files(self._db_files_to_remove, error_on_missing=False)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n\n if instance.file:\n if os.path.isfile(instance.file.path):\n os.remove(instance.file.path)","def flow_file_delete(sender, instance, **kwargs):\n if FLOWJS_REMOVE_FILES_ON_DELETE:\n try:\n default_storage.delete(instance.path)\n except NotImplementedError:\n pass","def del_files_from_disk(path):\n\n shutil.rmtree(path) #,ignore_errors=True)","def cleanup_file(name: str):\n if os.path.exists(name) and os.path.isfile(name): # h5\n os.remove(name)\n elif os.path.exists(name) and os.path.isdir(name): # tf\n shutil.rmtree(name)","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete(self):\n if not pdbox._args.get(\"dryrun\"):\n result = execute(pdbox.dbx.files_delete_v2, self.path)\n pdbox.debug(\"Metadata response: %s\" % result.metadata)\n pdbox.info(\"Deleted %s\" % self.uri)","def test_file_deleted(self):\n try:\n with get_temp_file() as (fd, name):\n os.unlink(name)\n except Exception as err:\n self.fail('Failed with exception \"{}\"'.format(err))","def delete_old():\n folder = '../build/data/vtk'\n for the_file in os.listdir(folder):\n file_path = os.path.join(folder, the_file)\n try:\n if os.path.isfile(file_path):\n os.unlink(file_path)\n elif os.path.isdir(file_path):\n shutil.rmtree(file_path) # subdirs\n except Exception as e:\n print(e)\n folder = '../build/log'\n for the_file in os.listdir(folder):\n file_path = os.path.join(folder, the_file)\n try:\n if os.path.isfile(file_path):\n os.unlink(file_path)\n # elif os.path.isdir(file_path): shutil.rmtree(file_path) #subdirs\n except Exception as e:\n print(e)","def delete_file(self, lfile):\n raise NotImplementedError('delete_file')","def erase_files(self):\n self.ofile_handle()\n self.efile_handle()\n\n os.remove(self.ofile_name())\n os.remove(self.efile_name())\n return None","def db_remove():\n\n db.session.close()\n db.drop_all()\n\n path = current_app.config['SNER_VAR']\n for file_object in os.listdir(path):\n file_object_path = os.path.join(path, file_object)\n if os.path.isdir(file_object_path):\n shutil.rmtree(file_object_path)\n else:\n os.unlink(file_object_path)","def clean_filesystem(files=[]):\n remove_files(files + find_cache_files())","def rm(self, path):\n try:\n basedir, item = os.path.split(path)\n postdata = codecs.encode(json.dumps({ 'baseDir': basedir, 'items': [ item ] }), 'utf-8')\n self._urlopen('/api/fileops/delete', postdata).read()\n except HTTPError as err:\n raise RuntimeError(\"Unable to delete '{}'\".format(path))","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.img:\n if os.path.isfile(instance.img.path):\n os.remove(instance.img.path)","def del_files(rels_fl, last_fl, path):\n for i in rels_fl:\n if i[:-5] not in last_fl:\n os.remove(f'{path}/{i}')\n return","def _delete_data (self, path):\n head, tail = os.path.split(path)\n for subdir, dirs, files in os.walk(head):\n for file in files:\n if tail in file:\n os.remove(os.path.join(subdir, file))","def delete_previous_files():\n def delete(root: Path):\n shutil.rmtree(root / 'output', ignore_errors=True)\n for p in root.iterdir():\n if str(p).endswith(('.log', 'jobs.csv', 'csv.lock', '.yaml')):\n p.unlink()\n\n delete(wt_registration_dir)\n delete(mut_registration_dir)","def clean_temp_storage_dir(self, filenames):\n for fn in filenames:\n try:\n pathlib.Path(pathlib.PurePath(self.temp_storage_dir, fn)).unlink()\n except FileNotFoundError:\n pass","def delete(self):\n os.remove(self.file_path)\n super(VideoFile, self).delete()","def __del__(self):\n for filename in self.files:\n unlink(filename)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.env_pdf:\n if os.path.isfile(instance.env_pdf.path):\n os.remove(instance.env_pdf.path)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n to_delete = [\n instance.photo,\n instance.photo2,\n instance.photo3\n ]\n for photo in to_delete:\n if photo:\n if os.path.isfile(photo.path):\n os.remove(photo.path)","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.evntf_xls:\n if os.path.isfile(instance.evntf_xls.path):\n os.remove(instance.evntf_xls.path)","def delete_file(self, instance, sender, **kwargs):\n super(AutoImageField, self).delete_file(instance, sender)\n if getattr(instance, self.attname):\n # Get full path and the base directory that contains the file\n file_name = getattr(instance,self.name).name\n basedir = os.path.dirname(file_name)\n \n # Look for thumbnails created from filters for the current filename\n # and delete the files\n mask = add_to_basename(file_name, '_*')\n [os.remove(os.path.join(basedir, f)) for f in glob.glob(mask)]","def auto_delete_file_on_delete(sender, instance, **kwargs):\n\n if instance.image:\n if os.path.isfile(instance.image.path):\n os.remove(instance.image.path)","def delete(self, *args, **kwargs):\n self.file.storage.delete(self.file.name)\n super().delete(*args, **kwargs)","def delete_previous_files(schema_name, path_template, path_static):\n list_file_static = listdir(path_static)\n list_file_template = listdir(path_template)\n if schema_name in list_file_static:\n tree_path = path.join(path_static, schema_name)\n rmtree(tree_path, ignore_errors=True)\n html_file_name = \"wrap_\" + schema_name + \".html\"\n if html_file_name in list_file_template:\n html_file_path = path.join(path_template, html_file_name)\n remove(html_file_path)","def delete(self):\n\n try:\n remove(self.file)\n except OSError:\n pass","def delete_file(path):\n if os.path.isfile(path):\n os.remove(path)","def delete_file(file_id):\n file_obj = Data.objects.get(id=file_id)\n print(\"Removing file: \", file_obj.name)\n print(file_obj.file.path)\n file_dir = file_obj.file.path\n os.remove(file_dir)\n print(\"Done.\")","def _delete_file(self, path):\n if not self.mount():\n return False\n uri = self.path_to_uri(path)\n return self.gvfs.delete_file(uri)","def delete(self):\n\t\t#self.log.info(\"Deleting file {}\".format(self._filepath))\n\t\tos.remove(self._filepath)","def remove_previously_scanned(path):\n query = db_session.query(MediaFiles) \\\n .filter(MediaFiles.path.like(f'{path}%'))\n query.delete(synchronize_session='fetch')\n db_session.commit()\n return query.count()","def file_delete(self, path):\n params = {'root': self.session.root, 'path': format_path(path)}\n\n url, params, headers = self.request(\"/fileops/delete\", params)\n\n return self.rest_client.POST(url, params, headers)","def delete(self):\n\n del self.parent_mirror_dir[self.cvs_path]","def test_file_update_delete_conflict(self):\n dir0, dir1 = self.make_temp_dirs(2)\n self.write_file(dir0, \"foo\", \"bar\")\n self.sync_all()\n\n self.write_file(dir0, \"foo\", \"baz\")\n self.delete_file(dir1, \"foo\")\n self.sync_all()\n self.assertFileAbsent(dir0, \"foo\")\n self.assertFileAbsent(dir1, \"foo\")","def clear_files_paths(self):\n del self.__files_paths[:]","def cleanup(self):\r\n for f in [i for d in self.data.values() for i in d[\"filenames\"]]:\r\n try:\r\n os.unlink(f)\r\n except Exception: pass\r\n self.Destroy()","def _remove(path, force):\n if not os.path.exists(path):\n return\n elif os.path.isfile(path) and force:\n os.remove(path) # remove the file\n elif os.path.isdir(path) and force:\n import shutil\n shutil.rmtree(path) # remove dir and all contains\n else:\n print('Logdir contains data. Please, set `force` flag to overwrite it.')\n import sys\n sys.exit(0)","def auto_delete_file_on_change(sender, instance, **kwargs):\n if not instance.pk:\n return False\n try:\n old_file = EnvCondFile.objects.get(pk=instance.pk).env_pdf\n except EnvCondFile.DoesNotExist:\n return False\n new_file = instance.env_pdf\n if old_file and not old_file == new_file:\n if os.path.isfile(old_file.path):\n os.remove(old_file.path)","def delFiles(self):\r\n \r\n logStr = \"{0:s}.{1:s}: \".format(self.__class__.__name__, sys._getframe().f_code.co_name)\r\n logger.debug(\"{0:s}{1:s}\".format(logStr,'Start.')) \r\n \r\n try: \r\n if os.path.exists(self.h5File): \r\n os.remove(self.h5File) \r\n logger.debug(\"{0:s} File {1:s} deleted.\".format(logStr,self.h5File)) \r\n except XmError:\r\n raise \r\n except Exception as e:\r\n logStrFinal=\"{:s}Exception: Line: {:d}: {!s:s}: {:s}\".format(logStr,sys.exc_info()[-1].tb_lineno,type(e),str(e))\r\n logger.error(logStrFinal) \r\n raise XmError(logStrFinal) \r\n finally:\r\n logger.debug(\"{0:s}{1:s}\".format(logStr,'_Done.'))","def clean():\n clean_files()","def delete_file(path):\n return files.delete_file(path)","def delete(self, host, file):","def delete_file(self, hash):\n self.tree.delete(hash)\n query = \"delete from files where hash='%s'\"%hash\n self.connection.execute(query)\n self.connection.commit()","def delete(self) -> None:\n try:\n self._logger.debug('Delete old metadata file %s.', self._path)\n os.remove(self._path)\n except OSError as ex:\n if ex.errno != errno.ENOENT:\n msg = 'Failed to delete old metadata file. {}'.format(ex.strerror)\n raise MetaFileError(msg)","def auto_delete_file_on_change(sender, instance, **kwargs):\r\n if not instance.pk:\r\n return False\r\n\r\n try:\r\n old_file = Attachment.objects.get(pk=instance.pk).path\r\n except Attachment.DoesNotExist:\r\n return False\r\n\r\n new_file = instance.path\r\n if not old_file == new_file:\r\n if os.path.isfile(old_file.path):\r\n os.remove(old_file.path)","def delete(self, filename):\n raise NotImplementedError","def delete( self ):\n if os.path.exists(self.filename):\n os.remove(self.filename)","def photo_edit_file_cleanup(sender, **kwargs):\n instance = kwargs.get('instance')\n filename = instance.upload.url[1:]\n if os.path.exists(filename):\n os.remove(filename)","def delete(path, recursive=False):\n fs.delete(path, recursive)","def rm(path):\n abs_path = navigate.get_abs_path(path)\n parent, name = navigate.split_path(abs_path)\n access_token = db.get_access_to_file(parent, name)\n if access_token is not None:\n dbox_path = '/' + name\n client = dropbox.client.DropboxClient(access_token)\n client.file_delete(dbox_path)\n db.remove_file(access_token, parent, name)","def delete_data_file(path):\n cprint(f\"### Function Name:-> {inspect.stack()[0][3]} ###\", 'yellow', 'on_grey', attrs=['bold'])\n try:\n os.remove(path)\n except FileNotFoundError:\n pass","def delete(self):\n with self.locked():\n self.path.delete()","def delete(self):\n with self.locked():\n self.path.delete()","def delete_file(input_fn):\r\n if os.path.isfile(input_fn):\r\n os.remove(input_fn)","def rm_f(path):\n try:\n os.unlink(path)\n except OSError as e:\n if e.errno != errno.ENOENT:\n raise","def remove_dataset_file(sender, instance, **kwargs):\n if instance.original_file:\n if os.path.isfile(instance.original_file.path):\n os.remove(instance.original_file.path)","def rem_file(self, key):\n del self.fileList[key]\n\n path = os.path.join(self.file_path, '%s.xoj' % key)\n try:\n os.remove( path )\n except:\n print \"Unable to remove\", path\n self.save()","def fs_remove_entry(self, path):\n\t\treturn Job(SDK.PrlSrv_FsRemoveEntry(self.handle, path)[0])","def photo_file_cleanup(sender, **kwargs):\n instance = kwargs.get('instance')\n filename = instance.path.url[1:]\n if os.path.exists(filename):\n os.remove(filename)","def refresh(path):\n if os.path.exists(path):\n os.remove(path)\n return path","def cleanStamps(self, criteria):\n dirEmpty = True\n for s in self.iterStamps():\n if criteria(s):\n os.unlink(self.getFile(s))\n else:\n dirEmpty = False\n try:\n os.rmdir(self.path)\n except OSError:\n pass","def remove_file(path: str) -> None:\n\tremove(path)","def clean_files(self):\n self.filenames.clear()","def auto_delete_file_on_delete(sender, instance, **kwargs):\n if instance.protf_pdf:\n if os.path.isfile(instance.protf_pdf.path):\n os.remove(instance.protf_pdf.path)","def auto_delete_file_on_change(sender, instance, **kwargs):\n if not instance.pk:\n return False\n\n try:\n old_file = ReportTemplates.objects.get(pk=instance.pk).document\n except ReportTemplates.DoesNotExist:\n return False\n\n new_file = instance.document\n if not old_file == new_file:\n if os.path.isfile(old_file.path):\n os.remove(old_file.path)","def cleanup_callback(self, job: Job):\n from projects.models.files import File\n\n File.objects.filter(project=self, current=True).update(current=False)","def on_deleted(self, event):\n super(myEventHandler,self).on_deleted(event)\n #print \"Removed: \" + event.src_path\n if self.onedir.cookies is None or not self.onedir.autosyncstatus():\n return\n\n source = event.src_path\n if event.is_directory:\n try:\n pathtoonedir = self.onedir.getonedirrectory()\n relpath = source.replace(pathtoonedir ,\"\")\n self.onedir.deldirectory(relpath)\n except Exception as e:\n print \"Error syncing directory\" + e\n exit(1)\n else:\n try:\n #use os.path.split to get file name and path\n splitpath = split(source)\n file = splitpath[1]\n pathtoonedir = self.onedir.getonedirrectory()\n #print pathtoonedir\n #print \"truncated path:\"\n relpath = splitpath[0].replace(pathtoonedir ,\"\")\n self.onedir.deletefile(file, relpath)\n except OSError as e:\n print \"Error copying file! \" + e.strerror\n exit(1)\n except IOError as e:\n print \"IOerror creating file \" + e.strerror\n exit(1)","def svn_fs_delete_fs(*args):\r\n return _fs.svn_fs_delete_fs(*args)","def truncate(self):\n for file_name in os.listdir(self.path):\n if file_name[0:4] == 'data':\n os.remove(self.path + '/' + file_name)\n self.current_row = 0"],"string":"[\n \"def delete_path():\\n #TODO delete path from database\\n pass\",\n \"def clear_outdated_files():\\n for f in os.listdir(MEDIA_ROOT):\\n file_path = os.path.join(MEDIA_ROOT, f)\\n if os.path.isfile(file_path) and os.stat(file_path).st_mtime < time.time() - STORE_PDF_DAYS * 86400:\\n os.remove(file_path)\",\n \"def cleanup(self):\\n files = self.nlst()\\n latest = self.latest_filename\\n for filename in files:\\n if filename != latest:\\n result = self.delete(filename)\\n logger.info(f\\\"Deleted old export from FTP: {result}\\\")\",\n \"def unlink ( self, fspath ):\\n return\",\n \"def remove(path):\",\n \"def unlink(self, path: PathLike):\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\r\\n if instance.path:\\r\\n if os.path.isfile(instance.path.path):\\r\\n os.remove(instance.path.path)\",\n \"def remove_file(self, path):\\n pass\",\n \"def cleanUp(self, f):\\n os.system('rm ' + f)\",\n \"def remove(self, path):\\n path = path.decode('utf8')\\n cursor = self._dbcon.cursor()\\n filename = os.path.basename(path)\\n dirname = os.path.dirname(path)\\n t = (dirname, filename)\\n sql = u\\\"delete from books where path = ? and filename = ?\\\"\\n cursor.execute(sql, t)\\n self._dbcon.commit()\\n cursor.close()\",\n \"def delete(self, filename):\\n pass\",\n \"def clean(self):\\n if os.path.exists(self.initial):\\n if os.path.exists(self.path) and os.stat(self.path).st_size == os.stat(\\n self.initial).st_size:\\n os.remove(self.initial)\\n else:\\n # if it doesn't match, something probably crashed; rename the temporary file and\\n # it'll get uploaded at some point\\n self.auto_filename()\\n self.rename()\\n self.connect()\\n os.remove(self.initial)\\n if os.path.exists(self.path):\\n os.remove(self.path)\\n self.filename_set = False\",\n \"def delete_leftovers(self):\\n for each_file, artist in self.past_songs_db_data:\\n if os.path.isfile(each_file): \\n os.remove(each_file)\\n print \\\"Deleted \\\" + each_file\\n\\n for each_file in os.listdir(\\\".\\\"):\\n if each_file.endswith(\\\".jpg\\\"):\\n os.remove(each_file)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\r\\n if instance.image:\\r\\n if pathlib.Path(instance.image.path).is_file():\\r\\n pathlib.Path(instance.image.path).unlink()\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(mapper, connection, target):\\n if target.filename and app.config['CLEANUP_FILES']:\\n try:\\n os.remove(join(app.config['FILE_PATH'], str(target.talk.id),\\n str(target.version), target.filename))\\n except OSError:\\n # We don't care if wasn't deleted because it does not exist\\n pass\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.document:\\n if os.path.isfile(instance.document.path):\\n os.remove(instance.document.path)\",\n \"def clear_old_files(self):\\n self.logger.logMsg(\\\"Clearing Old Files.....\\\")\\n try:\\n for files in os.listdir(self.download_path):\\n path = os.path.join(self.download_path, files)\\n os.remove(path)\\n for files in os.listdir(self.outpath):\\n path = os.path.join(self.outpath, files)\\n os.remove(path)\\n except Exception as e:\\n self.logger.logError(\\\"Error Creating Old Files {}.....\\\".format(str(e)))\\n raise Exception('Error in Clearing Old Files')\\n\\n self.logger.logMsg(\\\"Done Clearing Old Files.....\\\")\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\n if not instance.pk:\\n return False\\n\\n try:\\n old_file = SkyLabFile.objects.get(pk=instance.pk).file\\n except SkyLabFile.DoesNotExist:\\n return False\\n\\n if old_file:\\n new_file = instance.file\\n if not old_file == new_file:\\n if os.path.isfile(old_file.path):\\n os.remove(old_file.path)\",\n \"def delete_db(self):\\n import os.path\\n os.remove(self.filepath)\",\n \"def cleanup_files(self):\\n\\n self.backup_files()\\n self.delete_files()\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.file:\\n if os.path.isfile(instance.file.path):\\n os.remove(instance.file.path)\",\n \"def purge_outdated(self):\\n todelete = []\\n sql = \\\"select rowid, path, mtime from pictures\\\"\\n cur = self.con.execute(sql)\\n for rowid, path_str, mtime in cur:\\n if mtime and op.exists(path_str):\\n picture_mtime = os.stat(path_str).st_mtime\\n if int(picture_mtime) <= mtime:\\n # not outdated\\n continue\\n todelete.append(rowid)\\n if todelete:\\n sql = \\\"delete from pictures where rowid in (%s)\\\" % ','.join(map(str, todelete))\\n self.con.execute(sql)\",\n \"def clean_old_data():\\n logger.info('Cleaning standalone files on disk...')\\n for absolute_path in glob.glob(MEDIA_URL + '*'):\\n file_name = os.path.basename(absolute_path)\\n try:\\n relative_path = os.path.join(AUDIOS_URL, file_name)\\n audio = Audio.objects.get(filename=relative_path)\\n if audio.get_type() == 'episode':\\n try:\\n # If there are inactive audios on its being\\n for e in audio.podcast.episode_set.exclude(pk=audio.podcast.active_episode.pk):\\n if not e.is_active():\\n logger.info('Inactive audio found in podcast set. Erasing files.')\\n e.delete_files()\\n except Exception, e:\\n logger.exception(e.message)\\n except ObjectDoesNotExist, e:\\n logger.info('A file with no audio registered in database')\\n if os.path.isfile(relative_path):\\n logger.info('Erasing: %s' % relative_path)\\n os.remove(relative_path)\\n logger.info('... Done.')\",\n \"def remove_file(path):\\n pyCMD('hdfs', ['dfs', '-rm', '-skipTrash', path]).execute()\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def _delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete(self):\\n if os.path.exists(self.file_path):\\n os.remove(self.file_path)\",\n \"def remove_expired_files():\\n from models import FlowFile\\n FlowFile.objects.filter(\\n state__in=[FlowFile.STATE_UPLOADING, FlowFile.STATE_UPLOAD_ERROR],\\n updated__lte=datetime.datetime.date() - datetime.timedelta(days=FLOWJS_EXPIRATION_DAYS)\\n ).delete()\",\n \"def cleanUp(self):\\r\\n remove_files(self._db_files_to_remove, error_on_missing=False)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n\\n if instance.file:\\n if os.path.isfile(instance.file.path):\\n os.remove(instance.file.path)\",\n \"def flow_file_delete(sender, instance, **kwargs):\\n if FLOWJS_REMOVE_FILES_ON_DELETE:\\n try:\\n default_storage.delete(instance.path)\\n except NotImplementedError:\\n pass\",\n \"def del_files_from_disk(path):\\n\\n shutil.rmtree(path) #,ignore_errors=True)\",\n \"def cleanup_file(name: str):\\n if os.path.exists(name) and os.path.isfile(name): # h5\\n os.remove(name)\\n elif os.path.exists(name) and os.path.isdir(name): # tf\\n shutil.rmtree(name)\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete(self):\\n if not pdbox._args.get(\\\"dryrun\\\"):\\n result = execute(pdbox.dbx.files_delete_v2, self.path)\\n pdbox.debug(\\\"Metadata response: %s\\\" % result.metadata)\\n pdbox.info(\\\"Deleted %s\\\" % self.uri)\",\n \"def test_file_deleted(self):\\n try:\\n with get_temp_file() as (fd, name):\\n os.unlink(name)\\n except Exception as err:\\n self.fail('Failed with exception \\\"{}\\\"'.format(err))\",\n \"def delete_old():\\n folder = '../build/data/vtk'\\n for the_file in os.listdir(folder):\\n file_path = os.path.join(folder, the_file)\\n try:\\n if os.path.isfile(file_path):\\n os.unlink(file_path)\\n elif os.path.isdir(file_path):\\n shutil.rmtree(file_path) # subdirs\\n except Exception as e:\\n print(e)\\n folder = '../build/log'\\n for the_file in os.listdir(folder):\\n file_path = os.path.join(folder, the_file)\\n try:\\n if os.path.isfile(file_path):\\n os.unlink(file_path)\\n # elif os.path.isdir(file_path): shutil.rmtree(file_path) #subdirs\\n except Exception as e:\\n print(e)\",\n \"def delete_file(self, lfile):\\n raise NotImplementedError('delete_file')\",\n \"def erase_files(self):\\n self.ofile_handle()\\n self.efile_handle()\\n\\n os.remove(self.ofile_name())\\n os.remove(self.efile_name())\\n return None\",\n \"def db_remove():\\n\\n db.session.close()\\n db.drop_all()\\n\\n path = current_app.config['SNER_VAR']\\n for file_object in os.listdir(path):\\n file_object_path = os.path.join(path, file_object)\\n if os.path.isdir(file_object_path):\\n shutil.rmtree(file_object_path)\\n else:\\n os.unlink(file_object_path)\",\n \"def clean_filesystem(files=[]):\\n remove_files(files + find_cache_files())\",\n \"def rm(self, path):\\n try:\\n basedir, item = os.path.split(path)\\n postdata = codecs.encode(json.dumps({ 'baseDir': basedir, 'items': [ item ] }), 'utf-8')\\n self._urlopen('/api/fileops/delete', postdata).read()\\n except HTTPError as err:\\n raise RuntimeError(\\\"Unable to delete '{}'\\\".format(path))\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.img:\\n if os.path.isfile(instance.img.path):\\n os.remove(instance.img.path)\",\n \"def del_files(rels_fl, last_fl, path):\\n for i in rels_fl:\\n if i[:-5] not in last_fl:\\n os.remove(f'{path}/{i}')\\n return\",\n \"def _delete_data (self, path):\\n head, tail = os.path.split(path)\\n for subdir, dirs, files in os.walk(head):\\n for file in files:\\n if tail in file:\\n os.remove(os.path.join(subdir, file))\",\n \"def delete_previous_files():\\n def delete(root: Path):\\n shutil.rmtree(root / 'output', ignore_errors=True)\\n for p in root.iterdir():\\n if str(p).endswith(('.log', 'jobs.csv', 'csv.lock', '.yaml')):\\n p.unlink()\\n\\n delete(wt_registration_dir)\\n delete(mut_registration_dir)\",\n \"def clean_temp_storage_dir(self, filenames):\\n for fn in filenames:\\n try:\\n pathlib.Path(pathlib.PurePath(self.temp_storage_dir, fn)).unlink()\\n except FileNotFoundError:\\n pass\",\n \"def delete(self):\\n os.remove(self.file_path)\\n super(VideoFile, self).delete()\",\n \"def __del__(self):\\n for filename in self.files:\\n unlink(filename)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.env_pdf:\\n if os.path.isfile(instance.env_pdf.path):\\n os.remove(instance.env_pdf.path)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n to_delete = [\\n instance.photo,\\n instance.photo2,\\n instance.photo3\\n ]\\n for photo in to_delete:\\n if photo:\\n if os.path.isfile(photo.path):\\n os.remove(photo.path)\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.evntf_xls:\\n if os.path.isfile(instance.evntf_xls.path):\\n os.remove(instance.evntf_xls.path)\",\n \"def delete_file(self, instance, sender, **kwargs):\\n super(AutoImageField, self).delete_file(instance, sender)\\n if getattr(instance, self.attname):\\n # Get full path and the base directory that contains the file\\n file_name = getattr(instance,self.name).name\\n basedir = os.path.dirname(file_name)\\n \\n # Look for thumbnails created from filters for the current filename\\n # and delete the files\\n mask = add_to_basename(file_name, '_*')\\n [os.remove(os.path.join(basedir, f)) for f in glob.glob(mask)]\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n\\n if instance.image:\\n if os.path.isfile(instance.image.path):\\n os.remove(instance.image.path)\",\n \"def delete(self, *args, **kwargs):\\n self.file.storage.delete(self.file.name)\\n super().delete(*args, **kwargs)\",\n \"def delete_previous_files(schema_name, path_template, path_static):\\n list_file_static = listdir(path_static)\\n list_file_template = listdir(path_template)\\n if schema_name in list_file_static:\\n tree_path = path.join(path_static, schema_name)\\n rmtree(tree_path, ignore_errors=True)\\n html_file_name = \\\"wrap_\\\" + schema_name + \\\".html\\\"\\n if html_file_name in list_file_template:\\n html_file_path = path.join(path_template, html_file_name)\\n remove(html_file_path)\",\n \"def delete(self):\\n\\n try:\\n remove(self.file)\\n except OSError:\\n pass\",\n \"def delete_file(path):\\n if os.path.isfile(path):\\n os.remove(path)\",\n \"def delete_file(file_id):\\n file_obj = Data.objects.get(id=file_id)\\n print(\\\"Removing file: \\\", file_obj.name)\\n print(file_obj.file.path)\\n file_dir = file_obj.file.path\\n os.remove(file_dir)\\n print(\\\"Done.\\\")\",\n \"def _delete_file(self, path):\\n if not self.mount():\\n return False\\n uri = self.path_to_uri(path)\\n return self.gvfs.delete_file(uri)\",\n \"def delete(self):\\n\\t\\t#self.log.info(\\\"Deleting file {}\\\".format(self._filepath))\\n\\t\\tos.remove(self._filepath)\",\n \"def remove_previously_scanned(path):\\n query = db_session.query(MediaFiles) \\\\\\n .filter(MediaFiles.path.like(f'{path}%'))\\n query.delete(synchronize_session='fetch')\\n db_session.commit()\\n return query.count()\",\n \"def file_delete(self, path):\\n params = {'root': self.session.root, 'path': format_path(path)}\\n\\n url, params, headers = self.request(\\\"/fileops/delete\\\", params)\\n\\n return self.rest_client.POST(url, params, headers)\",\n \"def delete(self):\\n\\n del self.parent_mirror_dir[self.cvs_path]\",\n \"def test_file_update_delete_conflict(self):\\n dir0, dir1 = self.make_temp_dirs(2)\\n self.write_file(dir0, \\\"foo\\\", \\\"bar\\\")\\n self.sync_all()\\n\\n self.write_file(dir0, \\\"foo\\\", \\\"baz\\\")\\n self.delete_file(dir1, \\\"foo\\\")\\n self.sync_all()\\n self.assertFileAbsent(dir0, \\\"foo\\\")\\n self.assertFileAbsent(dir1, \\\"foo\\\")\",\n \"def clear_files_paths(self):\\n del self.__files_paths[:]\",\n \"def cleanup(self):\\r\\n for f in [i for d in self.data.values() for i in d[\\\"filenames\\\"]]:\\r\\n try:\\r\\n os.unlink(f)\\r\\n except Exception: pass\\r\\n self.Destroy()\",\n \"def _remove(path, force):\\n if not os.path.exists(path):\\n return\\n elif os.path.isfile(path) and force:\\n os.remove(path) # remove the file\\n elif os.path.isdir(path) and force:\\n import shutil\\n shutil.rmtree(path) # remove dir and all contains\\n else:\\n print('Logdir contains data. Please, set `force` flag to overwrite it.')\\n import sys\\n sys.exit(0)\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\n if not instance.pk:\\n return False\\n try:\\n old_file = EnvCondFile.objects.get(pk=instance.pk).env_pdf\\n except EnvCondFile.DoesNotExist:\\n return False\\n new_file = instance.env_pdf\\n if old_file and not old_file == new_file:\\n if os.path.isfile(old_file.path):\\n os.remove(old_file.path)\",\n \"def delFiles(self):\\r\\n \\r\\n logStr = \\\"{0:s}.{1:s}: \\\".format(self.__class__.__name__, sys._getframe().f_code.co_name)\\r\\n logger.debug(\\\"{0:s}{1:s}\\\".format(logStr,'Start.')) \\r\\n \\r\\n try: \\r\\n if os.path.exists(self.h5File): \\r\\n os.remove(self.h5File) \\r\\n logger.debug(\\\"{0:s} File {1:s} deleted.\\\".format(logStr,self.h5File)) \\r\\n except XmError:\\r\\n raise \\r\\n except Exception as e:\\r\\n logStrFinal=\\\"{:s}Exception: Line: {:d}: {!s:s}: {:s}\\\".format(logStr,sys.exc_info()[-1].tb_lineno,type(e),str(e))\\r\\n logger.error(logStrFinal) \\r\\n raise XmError(logStrFinal) \\r\\n finally:\\r\\n logger.debug(\\\"{0:s}{1:s}\\\".format(logStr,'_Done.'))\",\n \"def clean():\\n clean_files()\",\n \"def delete_file(path):\\n return files.delete_file(path)\",\n \"def delete(self, host, file):\",\n \"def delete_file(self, hash):\\n self.tree.delete(hash)\\n query = \\\"delete from files where hash='%s'\\\"%hash\\n self.connection.execute(query)\\n self.connection.commit()\",\n \"def delete(self) -> None:\\n try:\\n self._logger.debug('Delete old metadata file %s.', self._path)\\n os.remove(self._path)\\n except OSError as ex:\\n if ex.errno != errno.ENOENT:\\n msg = 'Failed to delete old metadata file. {}'.format(ex.strerror)\\n raise MetaFileError(msg)\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\r\\n if not instance.pk:\\r\\n return False\\r\\n\\r\\n try:\\r\\n old_file = Attachment.objects.get(pk=instance.pk).path\\r\\n except Attachment.DoesNotExist:\\r\\n return False\\r\\n\\r\\n new_file = instance.path\\r\\n if not old_file == new_file:\\r\\n if os.path.isfile(old_file.path):\\r\\n os.remove(old_file.path)\",\n \"def delete(self, filename):\\n raise NotImplementedError\",\n \"def delete( self ):\\n if os.path.exists(self.filename):\\n os.remove(self.filename)\",\n \"def photo_edit_file_cleanup(sender, **kwargs):\\n instance = kwargs.get('instance')\\n filename = instance.upload.url[1:]\\n if os.path.exists(filename):\\n os.remove(filename)\",\n \"def delete(path, recursive=False):\\n fs.delete(path, recursive)\",\n \"def rm(path):\\n abs_path = navigate.get_abs_path(path)\\n parent, name = navigate.split_path(abs_path)\\n access_token = db.get_access_to_file(parent, name)\\n if access_token is not None:\\n dbox_path = '/' + name\\n client = dropbox.client.DropboxClient(access_token)\\n client.file_delete(dbox_path)\\n db.remove_file(access_token, parent, name)\",\n \"def delete_data_file(path):\\n cprint(f\\\"### Function Name:-> {inspect.stack()[0][3]} ###\\\", 'yellow', 'on_grey', attrs=['bold'])\\n try:\\n os.remove(path)\\n except FileNotFoundError:\\n pass\",\n \"def delete(self):\\n with self.locked():\\n self.path.delete()\",\n \"def delete(self):\\n with self.locked():\\n self.path.delete()\",\n \"def delete_file(input_fn):\\r\\n if os.path.isfile(input_fn):\\r\\n os.remove(input_fn)\",\n \"def rm_f(path):\\n try:\\n os.unlink(path)\\n except OSError as e:\\n if e.errno != errno.ENOENT:\\n raise\",\n \"def remove_dataset_file(sender, instance, **kwargs):\\n if instance.original_file:\\n if os.path.isfile(instance.original_file.path):\\n os.remove(instance.original_file.path)\",\n \"def rem_file(self, key):\\n del self.fileList[key]\\n\\n path = os.path.join(self.file_path, '%s.xoj' % key)\\n try:\\n os.remove( path )\\n except:\\n print \\\"Unable to remove\\\", path\\n self.save()\",\n \"def fs_remove_entry(self, path):\\n\\t\\treturn Job(SDK.PrlSrv_FsRemoveEntry(self.handle, path)[0])\",\n \"def photo_file_cleanup(sender, **kwargs):\\n instance = kwargs.get('instance')\\n filename = instance.path.url[1:]\\n if os.path.exists(filename):\\n os.remove(filename)\",\n \"def refresh(path):\\n if os.path.exists(path):\\n os.remove(path)\\n return path\",\n \"def cleanStamps(self, criteria):\\n dirEmpty = True\\n for s in self.iterStamps():\\n if criteria(s):\\n os.unlink(self.getFile(s))\\n else:\\n dirEmpty = False\\n try:\\n os.rmdir(self.path)\\n except OSError:\\n pass\",\n \"def remove_file(path: str) -> None:\\n\\tremove(path)\",\n \"def clean_files(self):\\n self.filenames.clear()\",\n \"def auto_delete_file_on_delete(sender, instance, **kwargs):\\n if instance.protf_pdf:\\n if os.path.isfile(instance.protf_pdf.path):\\n os.remove(instance.protf_pdf.path)\",\n \"def auto_delete_file_on_change(sender, instance, **kwargs):\\n if not instance.pk:\\n return False\\n\\n try:\\n old_file = ReportTemplates.objects.get(pk=instance.pk).document\\n except ReportTemplates.DoesNotExist:\\n return False\\n\\n new_file = instance.document\\n if not old_file == new_file:\\n if os.path.isfile(old_file.path):\\n os.remove(old_file.path)\",\n \"def cleanup_callback(self, job: Job):\\n from projects.models.files import File\\n\\n File.objects.filter(project=self, current=True).update(current=False)\",\n \"def on_deleted(self, event):\\n super(myEventHandler,self).on_deleted(event)\\n #print \\\"Removed: \\\" + event.src_path\\n if self.onedir.cookies is None or not self.onedir.autosyncstatus():\\n return\\n\\n source = event.src_path\\n if event.is_directory:\\n try:\\n pathtoonedir = self.onedir.getonedirrectory()\\n relpath = source.replace(pathtoonedir ,\\\"\\\")\\n self.onedir.deldirectory(relpath)\\n except Exception as e:\\n print \\\"Error syncing directory\\\" + e\\n exit(1)\\n else:\\n try:\\n #use os.path.split to get file name and path\\n splitpath = split(source)\\n file = splitpath[1]\\n pathtoonedir = self.onedir.getonedirrectory()\\n #print pathtoonedir\\n #print \\\"truncated path:\\\"\\n relpath = splitpath[0].replace(pathtoonedir ,\\\"\\\")\\n self.onedir.deletefile(file, relpath)\\n except OSError as e:\\n print \\\"Error copying file! \\\" + e.strerror\\n exit(1)\\n except IOError as e:\\n print \\\"IOerror creating file \\\" + e.strerror\\n exit(1)\",\n \"def svn_fs_delete_fs(*args):\\r\\n return _fs.svn_fs_delete_fs(*args)\",\n \"def truncate(self):\\n for file_name in os.listdir(self.path):\\n if file_name[0:4] == 'data':\\n os.remove(self.path + '/' + file_name)\\n self.current_row = 0\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7185494","0.68854076","0.682105","0.6820686","0.6756345","0.6754087","0.67368037","0.67044604","0.6659871","0.65905446","0.654088","0.6512677","0.64891416","0.6486032","0.646998","0.64524764","0.64349043","0.6433434","0.64230174","0.64174724","0.6413873","0.6412182","0.6407385","0.6404638","0.6402329","0.638558","0.638558","0.637801","0.6367208","0.6359385","0.63579625","0.6341263","0.6335247","0.6325488","0.6314511","0.63008356","0.6297244","0.6289926","0.62754804","0.62748915","0.6273467","0.62712216","0.6270963","0.62704456","0.62690735","0.62610376","0.62334824","0.622866","0.62243265","0.6220621","0.62128216","0.62123543","0.62108576","0.62059045","0.620291","0.61995786","0.61887103","0.61852556","0.61808664","0.6178047","0.6174561","0.61626554","0.6161043","0.61558115","0.6154667","0.61539507","0.615008","0.61466753","0.6146207","0.614548","0.61447453","0.61288023","0.6121054","0.61161524","0.61145544","0.6110058","0.61069614","0.6096291","0.609542","0.6095159","0.60915834","0.6089158","0.6087494","0.6076804","0.6076804","0.60721356","0.60678273","0.6066004","0.6061179","0.60594666","0.6056508","0.60554075","0.6044543","0.6043798","0.603884","0.60387474","0.6034391","0.6032932","0.6026231","0.6024789","0.60218716"],"string":"[\n \"0.7185494\",\n \"0.68854076\",\n \"0.682105\",\n \"0.6820686\",\n \"0.6756345\",\n \"0.6754087\",\n \"0.67368037\",\n \"0.67044604\",\n \"0.6659871\",\n \"0.65905446\",\n \"0.654088\",\n \"0.6512677\",\n \"0.64891416\",\n \"0.6486032\",\n \"0.646998\",\n \"0.64524764\",\n \"0.64349043\",\n \"0.6433434\",\n \"0.64230174\",\n \"0.64174724\",\n \"0.6413873\",\n \"0.6412182\",\n \"0.6407385\",\n \"0.6404638\",\n \"0.6402329\",\n \"0.638558\",\n \"0.638558\",\n \"0.637801\",\n \"0.6367208\",\n \"0.6359385\",\n \"0.63579625\",\n \"0.6341263\",\n \"0.6335247\",\n \"0.6325488\",\n \"0.6314511\",\n \"0.63008356\",\n \"0.6297244\",\n \"0.6289926\",\n \"0.62754804\",\n \"0.62748915\",\n \"0.6273467\",\n \"0.62712216\",\n \"0.6270963\",\n \"0.62704456\",\n \"0.62690735\",\n \"0.62610376\",\n \"0.62334824\",\n \"0.622866\",\n \"0.62243265\",\n \"0.6220621\",\n \"0.62128216\",\n \"0.62123543\",\n \"0.62108576\",\n \"0.62059045\",\n \"0.620291\",\n \"0.61995786\",\n \"0.61887103\",\n \"0.61852556\",\n \"0.61808664\",\n \"0.6178047\",\n \"0.6174561\",\n \"0.61626554\",\n \"0.6161043\",\n \"0.61558115\",\n \"0.6154667\",\n \"0.61539507\",\n \"0.615008\",\n \"0.61466753\",\n \"0.6146207\",\n \"0.614548\",\n \"0.61447453\",\n \"0.61288023\",\n \"0.6121054\",\n \"0.61161524\",\n \"0.61145544\",\n \"0.6110058\",\n \"0.61069614\",\n \"0.6096291\",\n \"0.609542\",\n \"0.6095159\",\n \"0.60915834\",\n \"0.6089158\",\n \"0.6087494\",\n \"0.6076804\",\n \"0.6076804\",\n \"0.60721356\",\n \"0.60678273\",\n \"0.6066004\",\n \"0.6061179\",\n \"0.60594666\",\n \"0.6056508\",\n \"0.60554075\",\n \"0.6044543\",\n \"0.6043798\",\n \"0.603884\",\n \"0.60387474\",\n \"0.6034391\",\n \"0.6032932\",\n \"0.6026231\",\n \"0.6024789\",\n \"0.60218716\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13095,"cells":{"query":{"kind":"string","value":"Create mock input block."},"document":{"kind":"string","value":"def fixture_input_block():\n return Mock()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def mockRawInput(mock):\n original_raw_input = __builtin__.raw_input\n __builtin__.raw_input = lambda _: mock\n yield\n __builtin__.raw_input = original_raw_input","def get_input_mock(inputs=None): # Use this mock if a contest requires interactive input.\n stdin_mock = MagicMock()\n stdin_mock.side_effect = inputs # You can emulate standard input lines by using this list.\n return stdin_mock","def fixture_output_block():\n return Mock()","def make_an_xblock(cls, **kw):\n course_id = SlashSeparatedCourseKey('foo', 'bar', 'baz')\n runtime = Mock(course_id=course_id)\n scope_ids = Mock()\n field_data = DictFieldData(kw)\n xblock = AdaptiveNumericInput(runtime, field_data, scope_ids)\n xblock.xmodule_runtime = runtime\n return xblock","def fake_input(inputs):\n it = iter(inputs)\n def mock_input(prompt=''):\n try:\n return next(it)\n except StopIteration as e:\n raise EOFError('No more inputs given') from e\n\n return patch('builtins.input', mock_input)","def test_raw_input_ex(input_output):\n with mock.patch.object(builtins, 'input', lambda _: input_output):\n assert GC.raw_input_ex() == input_output","def parse_input_mocked_metadata(monkeypatch):\n\n def _parse_input(text, cwd=None):\n \"\"\"The parser fixture accepts a blackbird string to parse\"\"\"\n text = \"name mockname\\nversion 1.0\\n\" + text\n lexer = blackbirdLexer(antlr4.InputStream(text))\n stream = antlr4.CommonTokenStream(lexer)\n parser = blackbirdParser(stream)\n\n tree = parser.start()\n\n bb = BlackbirdListener(cwd=cwd)\n walker = antlr4.ParseTreeWalker()\n walker.walk(bb, tree)\n\n return bb.program\n\n return _parse_input","def mock_inputs(inputs):\n def inner(test_func):\n @wraps(test_func)\n def wrapped(*args):\n replier = Replier(inputs)\n old_input = createsuperuser.input\n createsuperuser.input = replier\n createtenant.raw_input = replier\n\n old_getpass = createsuperuser.getpass\n createsuperuser.getpass = GetPass(replier)\n\n try:\n test_func(*args)\n finally:\n createsuperuser.input = old_input\n createtenant.raw_input = raw_input\n createsuperuser.getpass = old_getpass\n return wrapped\n return inner","def make_block(self, in_size, out_size, **kwargs):\n raise NotImplementedError(\"Abstract\")","async def test_is_block_momentary_input(mock_block_device, monkeypatch) -> None:\n monkeypatch.setattr(mock_block_device.blocks[DEVICE_BLOCK_ID], \"type\", \"relay\")\n\n monkeypatch.setitem(mock_block_device.settings, \"mode\", \"roller\")\n monkeypatch.setitem(\n mock_block_device.settings, \"rollers\", [{\"button_type\": \"detached\"}]\n )\n assert (\n is_block_momentary_input(\n mock_block_device.settings,\n mock_block_device.blocks[DEVICE_BLOCK_ID],\n )\n is False\n )\n assert (\n is_block_momentary_input(\n mock_block_device.settings, mock_block_device.blocks[DEVICE_BLOCK_ID], True\n )\n is True\n )\n\n monkeypatch.setitem(mock_block_device.settings, \"mode\", \"relay\")\n monkeypatch.setitem(mock_block_device.settings[\"device\"], \"type\", \"SHSW-L\")\n assert (\n is_block_momentary_input(\n mock_block_device.settings, mock_block_device.blocks[DEVICE_BLOCK_ID], True\n )\n is False\n )\n\n monkeypatch.delitem(mock_block_device.settings, \"relays\")\n monkeypatch.delitem(mock_block_device.settings, \"rollers\")\n assert (\n is_block_momentary_input(\n mock_block_device.settings,\n mock_block_device.blocks[DEVICE_BLOCK_ID],\n )\n is False\n )\n\n monkeypatch.setitem(mock_block_device.settings[\"device\"], \"type\", \"SHBTN-2\")\n\n assert (\n is_block_momentary_input(\n mock_block_device.settings,\n mock_block_device.blocks[DEVICE_BLOCK_ID],\n )\n is True\n )","def part1_test_input():\n return \"\"\"\"\"\"","def test(self, parent, block):\r\n pass","def test_prompt_setInput_default_valid(self):\n self.prompt.setInput()\n\n self.assertEquals(\n self.prompt._instr,\n '/dev/tty'\n )\n\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\n result = self.prompt._prompt({}, {\n 'say': 'test',\n 'ask': 'varname'\n })\n\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')","def __init__(self, meta_model, input_spec):\r\n\r\n # Check if the input specifications are correct\r\n RM.check_if_type(input_spec, list, 'The input specifications')\r\n for i in range(len(input_spec)):\r\n RM.check_if_type(input_spec[i], str, 'Input specification %x' % i)\r\n RM.check_if_poss_input_spec(input_spec[i], i)\r\n\r\n InputDecorator.__init__(self, meta_model)\r\n\r\n self.input_spec = input_spec","def create_input_element(self, **kwargs):\r\n return None","def mock_workflow():\n\n workflow = DockerBuildWorkflow(\"mock:default_built\", source=SOURCE)\n workflow.source = StubSource()\n builder = StubInsideBuilder().for_workflow(workflow)\n builder.set_df_path('/mock-path')\n base_image_name = ImageName.parse(\"mock:tag\")\n builder.parent_images[ImageName.parse(\"mock:base\")] = base_image_name\n builder.base_image = base_image_name\n builder.tasker = flexmock()\n workflow.builder = flexmock(builder)\n\n return workflow","def open_input(name=None):\n return Input(name)","def dummy_input(request, tmpdir_factory):\n # Init variables\n\n input_path = tmpdir_factory.mktemp(\"input_data\").join(\"datasink_test_s3.txt\")\n\n # Create input file\n input_path.write_binary(b\"ABCD1234\")\n\n # Return path\n return str(input_path)","def part2_test_input():\n return \"\"\"\"\"\"","def sample_input(self, loader, is_test=False):\n pass","def test_exit_on_input_signal_error(input_block, kwargs):\n input_block.side_effect = Exception()\n with pytest.raises(SystemExit) as exc_info:\n create_flow(**kwargs)\n assert exc_info.value.code == 1","def test_prompt_setInput_stringio_valid(self):\n instr = StringIO.StringIO()\n self.prompt.setInput(instr)\n\n self.assertEquals(instr, self.prompt._instr)\n self.assertEquals(instr.getvalue(), \"\")\n\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\n result = self.prompt._prompt({}, {\n 'say': 'test',\n 'ask': 'varname'\n })\n\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')","def test0_init(self):\n print(\"\\nTest 0: Initialization\")\n builder = StaticBuilder()\n in1_name = builder.addInput(10)\n in1 = builder.input_nodes[in1_name]\n \n print('Node keys in builder:', list(builder.input_nodes.keys()))\n self.assertEqual(in1.label, 0, \"The label has not been assigned correctly\")\n self.assertEqual(builder.num_nodes, 1, \"The number of nodes has not been \"\n \"assigned correctly\")\n self.assertEqual(in1.num_declared_outputs, 0, \"The number of outputs of \"\n \"the InputNode has not been assigned correctly\")\n self.assertEqual(in1.num_declared_inputs, 0, \"The number of outputs of \"\n \"the InputNode has not been assigned correctly\")","def MockArbitraryBuffer( filetype ):\n\n # Arbitrary, but valid, single buffer open.\n current_buffer = VimBuffer( os.path.realpath( 'TEST_BUFFER' ),\n filetype = filetype )\n\n with MockVimBuffers( [ current_buffer ], [ current_buffer ] ):\n yield","def test_default_creation_2():\n actual = os.path.join('.', 'test_files', 'rc_test_default.input')\n times = list(range(0, 30, 5))\n params = {\"names\": ['V'],\n \"values\": [\n [1],\n [0],\n [-1],\n [0],\n [1]\n ]\n }\n input_creator = InputCreator(None, times, params)\n f_out = input_creator.default_creation_2()\n with open(actual) as f_actual:\n actual_content = f_actual.read()\n\n content = f_out.getvalue()\n\n assert_equal(content, actual_content)","def createMemoryBlock(self, name: unicode, start: ghidra.program.model.address.Address, input: java.io.InputStream, length: long, overlay: bool) -> ghidra.program.model.mem.MemoryBlock:\n ...","def test_dummy():\n dummyblock = DummyBlockNode(\n name=\"None\",\n parameters=(),\n ancestor=None,\n dirty=False,\n filepath=\"/some/random/path\"\n )\n dummydirective = DummyDirectiveNode(\n name=\"Name\",\n ancestor=None,\n filepath=\"/another/path\"\n )\n dummycomment = DummyCommentNode(\n comment=\"Comment\",\n ancestor=dummyblock,\n filepath=\"/some/file\"\n )","def test_execute_job_with_inline_input_values(self):\n cwl = {\n \"cwlVersion\": \"v1.0\",\n \"class\": \"CommandLineTool\",\n \"baseCommand\": [\"python3\", \"script.py\"],\n \"inputs\": {\n \"stringInput\": \"string\",\n \"integerInput\": \"int\",\n \"doubleInput\": \"float\",\n \"stringArrayInput\": {\"type\": {\"type\": \"array\", \"items\": \"string\"}},\n \"integerArrayInput\": {\"type\": {\"type\": \"array\", \"items\": \"int\"}},\n \"floatArrayInput\": {\"type\": {\"type\": \"array\", \"items\": \"float\"}},\n \"measureStringInput\": \"string\",\n \"measureIntegerInput\": \"int\",\n \"measureFloatInput\": \"float\",\n \"measureFileInput\": \"File\"\n },\n \"requirements\": {\n CWL_REQUIREMENT_APP_DOCKER: {\n \"dockerPull\": \"python:3.7-alpine\"\n },\n CWL_REQUIREMENT_INIT_WORKDIR: {\n \"listing\": [\n {\n \"entryname\": \"script.py\",\n \"entry\": cleandoc(\"\"\"\n import json\n import os\n import ast\n input = $(inputs)\n try:\n for key, value in input.items():\n if isinstance(value, dict):\n path_ = value.get(\"path\")\n if path_ and os.path.exists(path_):\n with open (path_, \"r\") as file_:\n file_data = file_.read()\n input[key] = ast.literal_eval(file_data.upper())\n json.dump(input, open(\"./tmp.txt\", \"w\"))\n except Exception as exc:\n print(exc)\n raise\n \"\"\")\n }\n ]\n }\n },\n \"outputs\": [{\"id\": \"output_test\", \"type\": \"File\", \"outputBinding\": {\"glob\": \"tmp.txt\"}}],\n }\n body = {\n \"processDescription\": {\n \"process\": {\n \"id\": self._testMethodName,\n \"title\": \"some title\",\n \"abstract\": \"this is a test\",\n },\n },\n \"deploymentProfileName\": \"http://www.opengis.net/profiles/eoc/wpsApplication\",\n \"executionUnit\": [{\"unit\": cwl}],\n }\n try:\n desc, _ = self.deploy_process(body, describe_schema=\"OLD\")\n except colander.Invalid:\n self.fail(\"Test\")\n\n assert desc[\"process\"] is not None\n\n with contextlib.ExitStack() as stack_exec:\n for mock_exec in mocked_execute_process():\n stack_exec.enter_context(mock_exec)\n tmp_file = stack_exec.enter_context(tempfile.NamedTemporaryFile(mode=\"w\", suffix=\".json\")) # noqa\n tmp_file.write(json.dumps({\"value\": {\"ref\": 1, \"measurement\": 10.3, \"uom\": \"m\"}}))\n tmp_file.seek(0)\n\n exec_body = {\n \"mode\": EXECUTE_MODE_ASYNC,\n \"response\": EXECUTE_RESPONSE_DOCUMENT,\n \"inputs\": {\n \"stringInput\": \"string_test\",\n \"integerInput\": 10,\n \"doubleInput\": 3.14159,\n \"stringArrayInput\": [\"1\", \"2\", \"3\", \"4\", \"5\", \"6\"],\n \"integerArrayInput\": [1, 2, 3, 4, 5, 6],\n \"floatArrayInput\": [1.45, 2.65, 3.5322, 4.86, 5.57, 6.02],\n \"measureStringInput\": {\n \"value\": \"this is a test\"\n },\n \"measureIntegerInput\": {\n \"value\": 45\n },\n \"measureFloatInput\": {\n \"value\": 10.2\n },\n \"measureFileInput\": {\n \"href\": \"file://{}\".format(tmp_file.name)\n }\n },\n \"outputs\": [\n {\"id\": \"output_test\", \"type\": \"File\"},\n ]\n }\n\n proc_url = \"/processes/{}/jobs\".format(self._testMethodName)\n resp = mocked_sub_requests(self.app, \"post_json\", proc_url, timeout=5,\n data=exec_body, headers=self.json_headers, only_local=True)\n assert resp.status_code in [200, 201], \"Failed with: [{}]\\nReason:\\n{}\".format(resp.status_code, resp.json)\n status_url = resp.json.get(\"location\")\n\n results = self.monitor_job(status_url)\n\n job_output_path = results.get(\"output_test\")[\"href\"].split(self.settings[\"weaver.wps_output_path\"])[-1]\n tmp_file = \"{}/{}\".format(self.settings[\"weaver.wps_output_dir\"], job_output_path)\n\n try:\n with open(tmp_file, \"r\") as f:\n processed_values = json.load(f)\n except FileNotFoundError:\n self.fail(\"Output file [{}] was not found where it was expected to resume test\".format(tmp_file))\n except Exception as exception:\n self.fail(\"An error occurred during the reading of the file: {}\".format(exception))\n assert processed_values[\"stringInput\"] == \"string_test\"\n assert processed_values[\"integerInput\"] == 10\n assert processed_values[\"doubleInput\"] == 3.14159\n assert processed_values[\"stringArrayInput\"] == [\"1\", \"2\", \"3\", \"4\", \"5\", \"6\"]\n assert processed_values[\"integerArrayInput\"] == [1, 2, 3, 4, 5, 6]\n assert processed_values[\"floatArrayInput\"] == [1.45, 2.65, 3.5322, 4.86, 5.57, 6.02]\n assert processed_values[\"measureStringInput\"] == \"this is a test\"\n assert processed_values[\"measureIntegerInput\"] == 45\n assert processed_values[\"measureFloatInput\"] == 10.2\n assert processed_values[\"measureFileInput\"] == {\"VALUE\": {\"REF\": 1, \"MEASUREMENT\": 10.3, \"UOM\": \"M\"}}","async def test_get_block_input_triggers(mock_block_device, monkeypatch) -> None:\n monkeypatch.setattr(\n mock_block_device.blocks[DEVICE_BLOCK_ID],\n \"sensor_ids\",\n {\"inputEvent\": \"S\", \"inputEventCnt\": 0},\n )\n monkeypatch.setitem(\n mock_block_device.settings, \"rollers\", [{\"button_type\": \"detached\"}]\n )\n assert set(\n get_block_input_triggers(\n mock_block_device, mock_block_device.blocks[DEVICE_BLOCK_ID]\n )\n ) == {(\"long\", \"button\"), (\"single\", \"button\")}\n\n monkeypatch.setitem(mock_block_device.settings[\"device\"], \"type\", \"SHBTN-1\")\n assert set(\n get_block_input_triggers(\n mock_block_device, mock_block_device.blocks[DEVICE_BLOCK_ID]\n )\n ) == {\n (\"long\", \"button\"),\n (\"double\", \"button\"),\n (\"single\", \"button\"),\n (\"triple\", \"button\"),\n }\n\n monkeypatch.setitem(mock_block_device.settings[\"device\"], \"type\", \"SHIX3-1\")\n assert set(\n get_block_input_triggers(\n mock_block_device, mock_block_device.blocks[DEVICE_BLOCK_ID]\n )\n ) == {\n (\"long_single\", \"button\"),\n (\"single_long\", \"button\"),\n (\"triple\", \"button\"),\n (\"long\", \"button\"),\n (\"single\", \"button\"),\n (\"double\", \"button\"),\n }","def dummy_code_block() -> CodeBlock:\n return make_dummy_code_block()","def create_initialised_input(self):\n input_creator = InputCreator(self.times, self.inputs,\n params=self.params, outputs=self.outputs)\n f_out = input_creator.initialised_creation(self.burn_in)\n\n if self.debug:\n print(f_out.getvalue(), file=sys.stderr)\n f_out.seek(0)\n\n self.input_file = f_out.getvalue()\n pprint.pprint(self.input_file)\n return self.input_file","def test_add_new_electric(self):\n input_vars = ['5', 'Shaver', '1', 'n', 'y', 'Norelco', '110']\n inventory = {}\n with patch('builtins.input', side_effect=input_vars):\n main.add_new_item(inventory)\n self.assertEqual(inventory['5'],\n {\n 'product_code': '5',\n 'description': 'Shaver',\n 'market_price': 24,\n 'rental_price': '1',\n 'brand': 'Norelco',\n 'voltage': '110'\n })","def simulate_block():\n return '''\n```sh\n# In build directory\n./simulate\n```'''","def mock_camera_fetch_input():\n def fetch_input(self):\n return np.random.randint(\n low=0,\n high=255,\n size=(256, 256, 3),\n dtype=np.uint8\n )\n\n CameraDataProvider.fetch_input = fetch_input\n CameraDataProvider.prepare = lambda self: None\n CameraDataProvider.detach_from_source = lambda self: None","def createStandardInput(self):\n\t\traise NotImplementedError(\"\")","def create_next_block(\n self,\n input_constants: Dict,\n prev_block: FullBlock,\n timestamp: uint64,\n difficulty: uint64,\n ips: uint64,\n seed: bytes = b\"\",\n ) -> FullBlock:\n test_constants: Dict[str, Any] = constants.copy()\n for key, value in input_constants.items():\n test_constants[key] = value\n\n assert prev_block.header_block.challenge\n\n return self._create_block(\n test_constants,\n prev_block.header_block.challenge.get_hash(),\n uint32(prev_block.height + 1),\n prev_block.header_hash,\n prev_block.header_block.challenge.total_iters,\n prev_block.weight,\n timestamp,\n uint64(difficulty),\n ips,\n seed,\n )","def setUp(self):\n self.my_model1 = BaseModel()\n self.my_model1.name = \"hello\"\n self.my_model1.number = 9\n self.my_model2 = BaseModel()\n self.my_model2.name = \"goodbye\"\n self.my_model2.number = 19\n self.mock_stdin = create_autospec(sys.stdin)\n self.mock_stdout = create_autospec(sys.stdout)","def test_client_create(self, mock_input, mock_pass):\n # Patch username and password.\n mock_input.return_value = \"user\"\n mock_pass.return_value = \"pass\"\n\n # Instantiate Agave object making reference to local mock server.\n local_uri = \"http://localhost:{port}/\".format(port=self.mock_server_port)\n ag = Agave(api_server=local_uri)\n\n # Create client.\n ag.clients_create(\"client-name\", \"some description\")\n\n assert ag.api_key == \"some api key\"\n assert ag.api_secret == \"some secret\"","def test_block_bad_signature(self):\n pass","def test_001(self):\n user_input = [\"0\",\"0\",\"1\"]\n with patch(\"builtins.input\", side_effect=user_input) as input_call:\n with patch(\"sys.stdout\", new=StringIO()) as output:\n import attempt\n self.assertEqual(output.getvalue().strip(),\"You cannot take this course, sorry!\")","def seed(cls, block: Expr) -> Expr:\n return cls(BlockField.block_seed, block)","def _initBlock(o,block):\n o.block = block.clone().shift(*o.board.startPosition)","def __init__(self, raw_input: Dict):\n self.name = raw_input.get(\"name\")\n self.description = raw_input.get(\"description\")\n self.type: TypeDefer = TypeDefer(raw_input.get(\"type\")) if raw_input.get(\"type\") is not None else None\n self.default_value = raw_input.get(\"defaultValue\")","def generate_inputs(fixture_localhost, fixture_sandbox, fixture_code, generate_remote_data):\n\n def _generate_inputs(parameters=None, settings=None):\n from aiida_quantumespresso.utils.resources import get_default_options\n\n if parameters is None:\n parameters = {'INPUTPP': {}}\n\n return AttributeDict({\n 'code':\n fixture_code('quantumespresso.open_grid'),\n 'parent_folder':\n generate_remote_data(fixture_localhost, fixture_sandbox.abspath, 'quantumespresso.open_grid'),\n 'parameters':\n orm.Dict(dict=parameters),\n 'settings':\n orm.Dict(dict=settings),\n 'metadata': {\n 'options': get_default_options()\n }\n })\n\n return _generate_inputs","def test_000(self):\n user_input = [\"0\",\"0\",\"0\"]\n with patch(\"builtins.input\", side_effect=user_input) as input_call:\n with patch(\"sys.stdout\", new=StringIO()) as output:\n import attempt\n self.assertEqual(output.getvalue().strip(),\"You cannot take this course, sorry!\")","def test_fork_simple(self):\n bvh = self.BlockValidationHandler()\n new_block = self.btm.generate_block(previous_block=self.btm.chain_head,\n add_to_store=True)\n\n bv = self.create_block_validator(new_block, bvh.on_block_validated)\n bv.run()\n\n self.assertTrue(bvh.has_result())\n self.assertTrue(new_block.status == BlockStatus.Valid)\n self.assertTrue(bvh.result[\"commit_new_block\"])","def test_mock_input():\n mock_message = mock.Mock()\n mock_words = mock.Mock()\n with pytest.raises(TypeError):\n message_checker(mock_message, mock_words)","def test_add_new_furniture(self):\n input_vars = ['4', 'Rug', '1', 'y', 'Berber', 's']\n inventory = {}\n with patch('builtins.input', side_effect=input_vars):\n main.add_new_item(inventory)\n self.assertEqual(inventory['4'],\n {\n 'product_code': '4',\n 'description': 'Rug',\n 'market_price': 24,\n 'rental_price': '1',\n 'material': 'Berber',\n 'size': 's'\n })","def setUp(self):\n self.source_id = '12345'\n self.checksum = 'asdfqwert1=='\n self.stream = io.BytesIO(b'fakecontent')","def setUp(self):\n self.source_id = '12345'\n self.checksum = 'asdfqwert1=='\n self.stream = io.BytesIO(b'fakecontent')","def setUp(self):\n self.source_id = '12345'\n self.checksum = 'asdfqwert1=='\n self.stream = io.BytesIO(b'fakecontent')","def setUp(self):\n self.source_id = '12345'\n self.checksum = 'asdfqwert1=='\n self.stream = io.BytesIO(b'fakecontent')","def _expected_inputs():","def get_a_block(self, usage_id=None):\r\n scope_ids = Mock()\r\n if usage_id is None:\r\n usage_id = \"_auto%d\" % len(self.all_blocks)\r\n scope_ids.usage_id = usage_id\r\n block = self.system.construct_xblock_from_class(\r\n self.TestableInheritingXBlock,\r\n field_data=self.field_data,\r\n scope_ids=scope_ids,\r\n )\r\n self.all_blocks[usage_id] = block\r\n return block","def setUp(self):\n self.user = {\n INPUT: \"12345\",\n }","def test_111(self):\n user_input = [\"1\",\"1\",\"1\"]\n with patch(\"builtins.input\", side_effect=user_input) as input_call:\n with patch(\"sys.stdout\", new=StringIO()) as output:\n import attempt\n self.assertEqual(output.getvalue().strip(),\"You cannot take this course, sorry!\")","def create_example(self, content, set_type):\n return InputExample(content=content, processor=self)","def test_stdin_input(self, api_client, ip_addresses, mock_response, expected):\n runner = CliRunner()\n\n api_client.quick.return_value = mock_response\n\n result = runner.invoke(\n subcommand.quick, [\"-f\", \"json\"], input=\"\\n\".join(ip_addresses)\n )\n assert result.exit_code == 0\n assert result.output.strip(\"\\n\") == expected\n api_client.quick.assert_called_with(ip_addresses=ip_addresses)","def _generate_input_file(self):\n if self.input_static:\n return\n\n if self._input_generator_name is None:\n logger.error(\"A testcase has neither a generator nor a static input\")\n self.input_generation_log = \"Generation failed. No generator specified.\"\n self.input_generation_successful = False\n elif self._input_generator is None:\n self.input_generation_log = \"Generation failed. Generator {} not found\".format(\n self._input_generator_name,\n )\n self.input_generation_successful = False\n else:\n generation_command = get_execution_command(self._input_generator.source_language, \"generator\")\n generation_command.extend(shlex.split(self._input_generation_parameters))\n stdout_redirect = \"output.txt\"\n\n try:\n generator_compiled = self._input_generator.compiled_file\n except:\n self.input_generation_log = \"Generation failed. Generator didn't compile. Log: {}\".format(\n self._input_generator.last_compile_log\n )\n self.save()\n return\n\n action = ActionDescription(\n commands=[generation_command],\n executables=[(\"generator\", generator_compiled)],\n stdout_redirect=stdout_redirect,\n output_files=[stdout_redirect],\n time_limit=settings.FAILSAFE_TIME_LIMIT,\n memory_limit=settings.FAILSAFE_MEMORY_LIMIT\n )\n success, execution_success, outputs, sandbox_datas = execute_with_input(action)\n if not success:\n logger.error(\"Generating input for testcase {} failed.\\n Sandbox data:\\n{}\".format(\n str(self),\n str(sandbox_datas[0]))\n )\n self.input_generation_log = \\\n \"System failed to generate the input. \" \\\n \"Check the logs for more details. \" \\\n \"This issue must be resolved by a system administrator\"\n self.input_generation_successful = False\n elif not execution_success:\n self.input_generation_log = \"Generation failed. {}.\".format(\n str(sandbox_datas[0])\n )\n self.input_generation_successful = False\n else:\n self._input_generated_file = outputs[stdout_redirect]\n self.input_generation_log = \"Generation successful.\"\n self.input_generation_successful = True\n self.save()","def __init__(self):\n self.inputs = {}","def test_block_extra_batch(self):\n pass","def createInitializedBlock(self, name: unicode, start: ghidra.program.model.address.Address, is_: java.io.InputStream, length: long, monitor: ghidra.util.task.TaskMonitor, overlay: bool) -> ghidra.program.model.mem.MemoryBlock:\n ...","def test_prompt_ask_var_numbers_valid(self):\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\n result = self.prompt._prompt({}, {\n 'say': 'test',\n 'ask': '12345'\n })\n\n self.assertEquals(result['ansible_facts']['12345'], 'mocked input')","def test_prompt_ask_var_simple_valid(self):\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\n result = self.prompt._prompt({}, {\n 'say': 'test',\n 'ask': 'varname'\n })\n\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')","def create_dummy_args(self):\n if not self.is_built:\n raise RuntimeError(\"A plan needs to be built before input shapes can be known.\")\n\n def traverse_nested_types(arg, leaf_function):\n if isinstance(arg, list):\n return [traverse_nested_types(obj, leaf_function) for obj in arg]\n elif isinstance(arg, tuple):\n return tuple(traverse_nested_types(obj, leaf_function) for obj in arg)\n elif isinstance(arg, dict):\n return {k: traverse_nested_types(v, leaf_function) for k, v in arg.items()}\n else:\n return leaf_function(arg)\n\n input_placeholders = (ph for ph in self.role.input_placeholders())\n\n def create_dummy(input_type, input_placeholder):\n if issubclass(input_type, FrameworkTensor):\n return input_type(\n PlaceHolder.create_placeholders([input_placeholder.expected_shape])[0]\n )\n else:\n return input_type()\n\n return traverse_nested_types(\n self.input_types.nested_input_types,\n lambda input_type: create_dummy(input_type, input_placeholders.__next__()),\n )","def test_truncated_input(self):\n\n def data_reader():\n for _ in range(4):\n yield b\"0123\"\n raise EOFError\n\n self.assertRaises(\n EOFError,\n self.storage.object_create_ext,\n self.account,\n self.container,\n obj_name=\"truncated-input\",\n data=data_reader(),\n )","def test_01(self):\n assert 'True' == Api.requestBlock('test-01')","def test_inputs():\n # Get data from the input file and unpacking it to three variable\n get_data = read_input()\n restructuring_info = get_data[0]\n machine_info = get_data[1]\n length = get_data[2]\n # start, end to slice the generator\n start, end = 0, 0\n # Loop through lenght of restructuring\n # Get x (restructuring_info) and y (machine_info)\n # Use x, y as a parameter for get_max_money function\n for i in range(length):\n x = next(restructuring_info)\n y = []\n # Check if there a machine\n # clone the machine_info generator to slice it\n # the cliced generator represent the machine informations\n # that related to restructuring_info\n if int(x[0]):\n end += int(x[0])\n machine_info, m_backup = itertools.tee(machine_info)\n y = itertools.islice(m_backup, start, end)\n start = end\n\n yield ('Case ' +str(i+1) + \": \" + str(get_max_money(x, y)))","def _build_impl_impl(self, input):","def run(self, input):\n return {}","def test_101(self):\n user_input = [\"1\",\"0\",\"1\"]\n with patch(\"builtins.input\", side_effect=user_input) as input_call:\n with patch(\"sys.stdout\", new=StringIO()) as output:\n import attempt\n self.assertEqual(output.getvalue().strip(),\"You cannot take this course, sorry!\")","def test_make_form():","def test_feed_block_creation(self):\n content_type = 'text'\n content = 'content'\n block = FeedItemDescriptionBlock(content_type, content)\n assert isinstance(block, FeedItemDescriptionBlock)\n assert block.type == content_type\n assert block.content == content","def __create_input(self, timestep):\n self.litter = {}\n if timestep == 0:\n self.initial = {}\n if self.initial_mode!='zero':\n self._define_components(self.initial_def, self.initial)\n if self.md.litter_mode == 'constant yearly':\n self._define_components(self.md.constant_litter, self.litter)\n else:\n timeind = self._map_timestep2timeind(timestep)\n if self.md.litter_mode=='monthly':\n infdata = self.md.monthly_litter\n elif self.md.litter_mode=='yearly':\n infdata = self.md.yearly_litter\n self._define_components(infdata, self.litter, tsind=timeind)\n self._fill_input()","def test_mp3_controller(file_input, filepath, monkeypatch):\n user_input = StringIO(file_input)\n test = VideoSynth()\n controller = Mp3Controller(test)\n monkeypatch.setattr('sys.stdin', user_input)\n controller.create_file_path()\n assert test.file_path() == filepath","def input(self):\r\n pass","def create_inputs(self):\n return {}","def generate_input(title, input_widget):\n\n return html.Div([\n # Titre de l'input\n html.Li([\n html.H6(title)\n ]),\n\n # Input\n input_widget\n ])","def test_main_gc_1(test):\n answers = (i for i in (test, 'b', 'q'))\n with mock.patch.object(builtins, 'input', lambda _: next(answers)):\n g_c.main()","def test_prompt_ask_say_missing_valid(self):\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\n result = self.prompt._prompt({}, {\n 'ask': 'varname'\n })\n\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')","def test_new_block_return_type(self):\n block = self.blockchain.new_block(self.proof, self.previous_hash)\n self.assertIsInstance(block, dict)","def get_input(self):\n pass","def test_011(self):\n user_input = [\"0\",\"1\",\"1\"]\n with patch(\"builtins.input\", side_effect=user_input) as input_call:\n with patch(\"sys.stdout\", new=StringIO()) as output:\n import attempt\n self.assertEqual(output.getvalue().strip(),\"You cannot take this course, sorry!\")","def test_010(self):\n user_input = [\"0\",\"1\",\"0\"]\n with patch(\"builtins.input\", side_effect=user_input) as input_call:\n with patch(\"sys.stdout\", new=StringIO()) as output:\n import attempt\n self.assertEqual(output.getvalue().strip(),\"You cannot take this course, sorry!\")","def createBlock(self, block: ghidra.program.model.mem.MemoryBlock, name: unicode, start: ghidra.program.model.address.Address, length: long) -> ghidra.program.model.mem.MemoryBlock:\n ...","def _make_block(self, model):\n # TODO Make base class\n assert model is not None, 'Top level model must be initialized first'\n self.model = model\n # If block is already present, remove it\n if self.model.component(self.name) is not None:\n self.model.del_component(self.name)\n self.model.add_component(self.name, Block())\n self.block = self.model.__getattribute__(self.name)\n\n self.logger.info(\n 'Optimization block initialized for {}'.format(self.name))","def create_genesis_block(\n self, input_constants: Dict, challenge_hash=bytes([0] * 32), seed: bytes = b\"\"\n ) -> FullBlock:\n test_constants: Dict[str, Any] = constants.copy()\n for key, value in input_constants.items():\n test_constants[key] = value\n\n return self._create_block(\n test_constants,\n challenge_hash,\n uint32(0),\n bytes([0] * 32),\n uint64(0),\n uint64(0),\n uint64(int(time.time())),\n uint64(test_constants[\"DIFFICULTY_STARTING\"]),\n uint64(test_constants[\"VDF_IPS_STARTING\"]),\n seed,\n )","async def async_step_init(self, user_input=None):\n if user_input is not None:\n return self.async_create_entry(title=\"\", data=user_input)\n\n options_schema = vol.Schema(\n {\n vol.Optional(\n CONF_UNIT_BARO,\n default=self.config_entry.options.get(\n CONF_UNIT_BARO, CONF_UNIT_SYSTEM_METRIC,\n ),\n ): vol.In(UNIT_OPTS),\n vol.Optional(\n CONF_UNIT_WIND,\n default=self.config_entry.options.get(\n CONF_UNIT_WIND, CONF_UNIT_SYSTEM_IMPERIAL,\n ),\n ): vol.In(WIND_OPTS),\n vol.Optional(\n CONF_UNIT_RAIN,\n default=self.config_entry.options.get(\n CONF_UNIT_RAIN, CONF_UNIT_SYSTEM_IMPERIAL,\n ),\n ): vol.In(UNIT_OPTS),\n vol.Optional(\n CONF_UNIT_LIGHTNING,\n default=self.config_entry.options.get(\n CONF_UNIT_LIGHTNING, CONF_UNIT_SYSTEM_IMPERIAL,\n ),\n ): vol.In(UNIT_OPTS),\n vol.Optional(\n CONF_UNIT_WINDCHILL,\n default=self.config_entry.options.get(\n CONF_UNIT_WINDCHILL, W_TYPE_HYBRID,\n ),\n ): vol.In(WINDCHILL_OPTS),\n }\n )\n return self.async_show_form(step_id=\"init\", data_schema=options_schema)","def CreateInput(self, name=None, type=None, data=None):\n\n\n inp = self._input_registry.Create(name, type, data)\n\n self._inputs.append(inp)\n\n return inp","def gen_new_block(self):\n block = BasicBlock()\n self.blocks.append(block)\n return block","def block(self) -> IMockPin:\n return self[\"block\"]","def input(self):","def create_engine(self, input):\n return","def ConfigureIO():\n\n def Input():\n try:\n return input()\n except Error as e:\n raise Error(INVALID_LINE_ERROR + str(e))\n\n Output = ActuallyOutput\n return Input, Output","def test_main_gc_2(test):\n answers = (i for i in (test, '1 1 1 1', 'q'))\n with mock.patch.object(builtins, 'input', lambda _: next(answers)):\n g_c.main()","def create_default_input(self):\n input_creator = InputCreator(self.times, self.inputs)\n self.input_file = input_creator.default_creation().getvalue()\n\n return self.input_file","def test_no_vault_secrets(mock_load, localhost_client, gen_input_config):\n mock_load.return_value = gen_input_config(vault_secrets={})\n\n localhost_client.load(\"in.json\")\n\n mock_load.assert_called_with(\"in.json\")","def test_custom_local_input_file() -> None:\n with tempfile.TemporaryDirectory() as tmpdirname:\n file_location = os.path.join(tmpdirname, \"foo.txt\")\n with open(file_location, \"wb\") as write_file:\n write_file.write(b\"foo\")\n\n # Confirm that the file initially exists\n assert os.path.exists(file_location)\n\n # Instantiate the input file\n absolute_file_location = os.path.abspath(file_location)\n input_file = PyArrowFileIO().new_input(location=f\"{absolute_file_location}\")\n\n # Test opening and reading the file\n f = input_file.open()\n data = f.read()\n assert data == b\"foo\"\n assert len(input_file) == 3","def initialize(self, inputs, base_block, n_repeats, *args, **kwargs):\n for repeat in range(n_repeats):\n if args:\n for i, item in enumerate(args):\n # Make block\n if isinstance(item, dict):\n block_constructor = item.pop('base_block', None) or base_block\n block_args = {'inputs': inputs, **dict(Config(kwargs) + Config(item))}\n block = block_constructor(**block_args)\n elif isinstance(item, nn.Module):\n block = item\n else:\n raise ValueError(f'Positional arguments of Block must be either dicts or nn.Modules, '\n f'got {type(item)} instead!')\n\n inputs = self.initialize_block(inputs, block, f'repeat{repeat}-args{i}')\n\n else:\n # Make block\n block = base_block(inputs=inputs, **kwargs)\n inputs = self.initialize_block(inputs, block, f'repeat{repeat}')","async def async_process_input(self, inp: inputs.Input) -> None:\n if isinstance(inp, inputs.ModNameComment):\n command = inp.command\n block_id = inp.block_id\n text = inp.text\n\n if command == \"K\":\n self._comment[block_id] = f\"{text:12s}\"\n await self.cancel(block_id)\n if None not in self._comment:\n self.comment_known.set()\n await self.cancel()"],"string":"[\n \"def mockRawInput(mock):\\n original_raw_input = __builtin__.raw_input\\n __builtin__.raw_input = lambda _: mock\\n yield\\n __builtin__.raw_input = original_raw_input\",\n \"def get_input_mock(inputs=None): # Use this mock if a contest requires interactive input.\\n stdin_mock = MagicMock()\\n stdin_mock.side_effect = inputs # You can emulate standard input lines by using this list.\\n return stdin_mock\",\n \"def fixture_output_block():\\n return Mock()\",\n \"def make_an_xblock(cls, **kw):\\n course_id = SlashSeparatedCourseKey('foo', 'bar', 'baz')\\n runtime = Mock(course_id=course_id)\\n scope_ids = Mock()\\n field_data = DictFieldData(kw)\\n xblock = AdaptiveNumericInput(runtime, field_data, scope_ids)\\n xblock.xmodule_runtime = runtime\\n return xblock\",\n \"def fake_input(inputs):\\n it = iter(inputs)\\n def mock_input(prompt=''):\\n try:\\n return next(it)\\n except StopIteration as e:\\n raise EOFError('No more inputs given') from e\\n\\n return patch('builtins.input', mock_input)\",\n \"def test_raw_input_ex(input_output):\\n with mock.patch.object(builtins, 'input', lambda _: input_output):\\n assert GC.raw_input_ex() == input_output\",\n \"def parse_input_mocked_metadata(monkeypatch):\\n\\n def _parse_input(text, cwd=None):\\n \\\"\\\"\\\"The parser fixture accepts a blackbird string to parse\\\"\\\"\\\"\\n text = \\\"name mockname\\\\nversion 1.0\\\\n\\\" + text\\n lexer = blackbirdLexer(antlr4.InputStream(text))\\n stream = antlr4.CommonTokenStream(lexer)\\n parser = blackbirdParser(stream)\\n\\n tree = parser.start()\\n\\n bb = BlackbirdListener(cwd=cwd)\\n walker = antlr4.ParseTreeWalker()\\n walker.walk(bb, tree)\\n\\n return bb.program\\n\\n return _parse_input\",\n \"def mock_inputs(inputs):\\n def inner(test_func):\\n @wraps(test_func)\\n def wrapped(*args):\\n replier = Replier(inputs)\\n old_input = createsuperuser.input\\n createsuperuser.input = replier\\n createtenant.raw_input = replier\\n\\n old_getpass = createsuperuser.getpass\\n createsuperuser.getpass = GetPass(replier)\\n\\n try:\\n test_func(*args)\\n finally:\\n createsuperuser.input = old_input\\n createtenant.raw_input = raw_input\\n createsuperuser.getpass = old_getpass\\n return wrapped\\n return inner\",\n \"def make_block(self, in_size, out_size, **kwargs):\\n raise NotImplementedError(\\\"Abstract\\\")\",\n \"async def test_is_block_momentary_input(mock_block_device, monkeypatch) -> None:\\n monkeypatch.setattr(mock_block_device.blocks[DEVICE_BLOCK_ID], \\\"type\\\", \\\"relay\\\")\\n\\n monkeypatch.setitem(mock_block_device.settings, \\\"mode\\\", \\\"roller\\\")\\n monkeypatch.setitem(\\n mock_block_device.settings, \\\"rollers\\\", [{\\\"button_type\\\": \\\"detached\\\"}]\\n )\\n assert (\\n is_block_momentary_input(\\n mock_block_device.settings,\\n mock_block_device.blocks[DEVICE_BLOCK_ID],\\n )\\n is False\\n )\\n assert (\\n is_block_momentary_input(\\n mock_block_device.settings, mock_block_device.blocks[DEVICE_BLOCK_ID], True\\n )\\n is True\\n )\\n\\n monkeypatch.setitem(mock_block_device.settings, \\\"mode\\\", \\\"relay\\\")\\n monkeypatch.setitem(mock_block_device.settings[\\\"device\\\"], \\\"type\\\", \\\"SHSW-L\\\")\\n assert (\\n is_block_momentary_input(\\n mock_block_device.settings, mock_block_device.blocks[DEVICE_BLOCK_ID], True\\n )\\n is False\\n )\\n\\n monkeypatch.delitem(mock_block_device.settings, \\\"relays\\\")\\n monkeypatch.delitem(mock_block_device.settings, \\\"rollers\\\")\\n assert (\\n is_block_momentary_input(\\n mock_block_device.settings,\\n mock_block_device.blocks[DEVICE_BLOCK_ID],\\n )\\n is False\\n )\\n\\n monkeypatch.setitem(mock_block_device.settings[\\\"device\\\"], \\\"type\\\", \\\"SHBTN-2\\\")\\n\\n assert (\\n is_block_momentary_input(\\n mock_block_device.settings,\\n mock_block_device.blocks[DEVICE_BLOCK_ID],\\n )\\n is True\\n )\",\n \"def part1_test_input():\\n return \\\"\\\"\\\"\\\"\\\"\\\"\",\n \"def test(self, parent, block):\\r\\n pass\",\n \"def test_prompt_setInput_default_valid(self):\\n self.prompt.setInput()\\n\\n self.assertEquals(\\n self.prompt._instr,\\n '/dev/tty'\\n )\\n\\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\\n result = self.prompt._prompt({}, {\\n 'say': 'test',\\n 'ask': 'varname'\\n })\\n\\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')\",\n \"def __init__(self, meta_model, input_spec):\\r\\n\\r\\n # Check if the input specifications are correct\\r\\n RM.check_if_type(input_spec, list, 'The input specifications')\\r\\n for i in range(len(input_spec)):\\r\\n RM.check_if_type(input_spec[i], str, 'Input specification %x' % i)\\r\\n RM.check_if_poss_input_spec(input_spec[i], i)\\r\\n\\r\\n InputDecorator.__init__(self, meta_model)\\r\\n\\r\\n self.input_spec = input_spec\",\n \"def create_input_element(self, **kwargs):\\r\\n return None\",\n \"def mock_workflow():\\n\\n workflow = DockerBuildWorkflow(\\\"mock:default_built\\\", source=SOURCE)\\n workflow.source = StubSource()\\n builder = StubInsideBuilder().for_workflow(workflow)\\n builder.set_df_path('/mock-path')\\n base_image_name = ImageName.parse(\\\"mock:tag\\\")\\n builder.parent_images[ImageName.parse(\\\"mock:base\\\")] = base_image_name\\n builder.base_image = base_image_name\\n builder.tasker = flexmock()\\n workflow.builder = flexmock(builder)\\n\\n return workflow\",\n \"def open_input(name=None):\\n return Input(name)\",\n \"def dummy_input(request, tmpdir_factory):\\n # Init variables\\n\\n input_path = tmpdir_factory.mktemp(\\\"input_data\\\").join(\\\"datasink_test_s3.txt\\\")\\n\\n # Create input file\\n input_path.write_binary(b\\\"ABCD1234\\\")\\n\\n # Return path\\n return str(input_path)\",\n \"def part2_test_input():\\n return \\\"\\\"\\\"\\\"\\\"\\\"\",\n \"def sample_input(self, loader, is_test=False):\\n pass\",\n \"def test_exit_on_input_signal_error(input_block, kwargs):\\n input_block.side_effect = Exception()\\n with pytest.raises(SystemExit) as exc_info:\\n create_flow(**kwargs)\\n assert exc_info.value.code == 1\",\n \"def test_prompt_setInput_stringio_valid(self):\\n instr = StringIO.StringIO()\\n self.prompt.setInput(instr)\\n\\n self.assertEquals(instr, self.prompt._instr)\\n self.assertEquals(instr.getvalue(), \\\"\\\")\\n\\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\\n result = self.prompt._prompt({}, {\\n 'say': 'test',\\n 'ask': 'varname'\\n })\\n\\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')\",\n \"def test0_init(self):\\n print(\\\"\\\\nTest 0: Initialization\\\")\\n builder = StaticBuilder()\\n in1_name = builder.addInput(10)\\n in1 = builder.input_nodes[in1_name]\\n \\n print('Node keys in builder:', list(builder.input_nodes.keys()))\\n self.assertEqual(in1.label, 0, \\\"The label has not been assigned correctly\\\")\\n self.assertEqual(builder.num_nodes, 1, \\\"The number of nodes has not been \\\"\\n \\\"assigned correctly\\\")\\n self.assertEqual(in1.num_declared_outputs, 0, \\\"The number of outputs of \\\"\\n \\\"the InputNode has not been assigned correctly\\\")\\n self.assertEqual(in1.num_declared_inputs, 0, \\\"The number of outputs of \\\"\\n \\\"the InputNode has not been assigned correctly\\\")\",\n \"def MockArbitraryBuffer( filetype ):\\n\\n # Arbitrary, but valid, single buffer open.\\n current_buffer = VimBuffer( os.path.realpath( 'TEST_BUFFER' ),\\n filetype = filetype )\\n\\n with MockVimBuffers( [ current_buffer ], [ current_buffer ] ):\\n yield\",\n \"def test_default_creation_2():\\n actual = os.path.join('.', 'test_files', 'rc_test_default.input')\\n times = list(range(0, 30, 5))\\n params = {\\\"names\\\": ['V'],\\n \\\"values\\\": [\\n [1],\\n [0],\\n [-1],\\n [0],\\n [1]\\n ]\\n }\\n input_creator = InputCreator(None, times, params)\\n f_out = input_creator.default_creation_2()\\n with open(actual) as f_actual:\\n actual_content = f_actual.read()\\n\\n content = f_out.getvalue()\\n\\n assert_equal(content, actual_content)\",\n \"def createMemoryBlock(self, name: unicode, start: ghidra.program.model.address.Address, input: java.io.InputStream, length: long, overlay: bool) -> ghidra.program.model.mem.MemoryBlock:\\n ...\",\n \"def test_dummy():\\n dummyblock = DummyBlockNode(\\n name=\\\"None\\\",\\n parameters=(),\\n ancestor=None,\\n dirty=False,\\n filepath=\\\"/some/random/path\\\"\\n )\\n dummydirective = DummyDirectiveNode(\\n name=\\\"Name\\\",\\n ancestor=None,\\n filepath=\\\"/another/path\\\"\\n )\\n dummycomment = DummyCommentNode(\\n comment=\\\"Comment\\\",\\n ancestor=dummyblock,\\n filepath=\\\"/some/file\\\"\\n )\",\n \"def test_execute_job_with_inline_input_values(self):\\n cwl = {\\n \\\"cwlVersion\\\": \\\"v1.0\\\",\\n \\\"class\\\": \\\"CommandLineTool\\\",\\n \\\"baseCommand\\\": [\\\"python3\\\", \\\"script.py\\\"],\\n \\\"inputs\\\": {\\n \\\"stringInput\\\": \\\"string\\\",\\n \\\"integerInput\\\": \\\"int\\\",\\n \\\"doubleInput\\\": \\\"float\\\",\\n \\\"stringArrayInput\\\": {\\\"type\\\": {\\\"type\\\": \\\"array\\\", \\\"items\\\": \\\"string\\\"}},\\n \\\"integerArrayInput\\\": {\\\"type\\\": {\\\"type\\\": \\\"array\\\", \\\"items\\\": \\\"int\\\"}},\\n \\\"floatArrayInput\\\": {\\\"type\\\": {\\\"type\\\": \\\"array\\\", \\\"items\\\": \\\"float\\\"}},\\n \\\"measureStringInput\\\": \\\"string\\\",\\n \\\"measureIntegerInput\\\": \\\"int\\\",\\n \\\"measureFloatInput\\\": \\\"float\\\",\\n \\\"measureFileInput\\\": \\\"File\\\"\\n },\\n \\\"requirements\\\": {\\n CWL_REQUIREMENT_APP_DOCKER: {\\n \\\"dockerPull\\\": \\\"python:3.7-alpine\\\"\\n },\\n CWL_REQUIREMENT_INIT_WORKDIR: {\\n \\\"listing\\\": [\\n {\\n \\\"entryname\\\": \\\"script.py\\\",\\n \\\"entry\\\": cleandoc(\\\"\\\"\\\"\\n import json\\n import os\\n import ast\\n input = $(inputs)\\n try:\\n for key, value in input.items():\\n if isinstance(value, dict):\\n path_ = value.get(\\\"path\\\")\\n if path_ and os.path.exists(path_):\\n with open (path_, \\\"r\\\") as file_:\\n file_data = file_.read()\\n input[key] = ast.literal_eval(file_data.upper())\\n json.dump(input, open(\\\"./tmp.txt\\\", \\\"w\\\"))\\n except Exception as exc:\\n print(exc)\\n raise\\n \\\"\\\"\\\")\\n }\\n ]\\n }\\n },\\n \\\"outputs\\\": [{\\\"id\\\": \\\"output_test\\\", \\\"type\\\": \\\"File\\\", \\\"outputBinding\\\": {\\\"glob\\\": \\\"tmp.txt\\\"}}],\\n }\\n body = {\\n \\\"processDescription\\\": {\\n \\\"process\\\": {\\n \\\"id\\\": self._testMethodName,\\n \\\"title\\\": \\\"some title\\\",\\n \\\"abstract\\\": \\\"this is a test\\\",\\n },\\n },\\n \\\"deploymentProfileName\\\": \\\"http://www.opengis.net/profiles/eoc/wpsApplication\\\",\\n \\\"executionUnit\\\": [{\\\"unit\\\": cwl}],\\n }\\n try:\\n desc, _ = self.deploy_process(body, describe_schema=\\\"OLD\\\")\\n except colander.Invalid:\\n self.fail(\\\"Test\\\")\\n\\n assert desc[\\\"process\\\"] is not None\\n\\n with contextlib.ExitStack() as stack_exec:\\n for mock_exec in mocked_execute_process():\\n stack_exec.enter_context(mock_exec)\\n tmp_file = stack_exec.enter_context(tempfile.NamedTemporaryFile(mode=\\\"w\\\", suffix=\\\".json\\\")) # noqa\\n tmp_file.write(json.dumps({\\\"value\\\": {\\\"ref\\\": 1, \\\"measurement\\\": 10.3, \\\"uom\\\": \\\"m\\\"}}))\\n tmp_file.seek(0)\\n\\n exec_body = {\\n \\\"mode\\\": EXECUTE_MODE_ASYNC,\\n \\\"response\\\": EXECUTE_RESPONSE_DOCUMENT,\\n \\\"inputs\\\": {\\n \\\"stringInput\\\": \\\"string_test\\\",\\n \\\"integerInput\\\": 10,\\n \\\"doubleInput\\\": 3.14159,\\n \\\"stringArrayInput\\\": [\\\"1\\\", \\\"2\\\", \\\"3\\\", \\\"4\\\", \\\"5\\\", \\\"6\\\"],\\n \\\"integerArrayInput\\\": [1, 2, 3, 4, 5, 6],\\n \\\"floatArrayInput\\\": [1.45, 2.65, 3.5322, 4.86, 5.57, 6.02],\\n \\\"measureStringInput\\\": {\\n \\\"value\\\": \\\"this is a test\\\"\\n },\\n \\\"measureIntegerInput\\\": {\\n \\\"value\\\": 45\\n },\\n \\\"measureFloatInput\\\": {\\n \\\"value\\\": 10.2\\n },\\n \\\"measureFileInput\\\": {\\n \\\"href\\\": \\\"file://{}\\\".format(tmp_file.name)\\n }\\n },\\n \\\"outputs\\\": [\\n {\\\"id\\\": \\\"output_test\\\", \\\"type\\\": \\\"File\\\"},\\n ]\\n }\\n\\n proc_url = \\\"/processes/{}/jobs\\\".format(self._testMethodName)\\n resp = mocked_sub_requests(self.app, \\\"post_json\\\", proc_url, timeout=5,\\n data=exec_body, headers=self.json_headers, only_local=True)\\n assert resp.status_code in [200, 201], \\\"Failed with: [{}]\\\\nReason:\\\\n{}\\\".format(resp.status_code, resp.json)\\n status_url = resp.json.get(\\\"location\\\")\\n\\n results = self.monitor_job(status_url)\\n\\n job_output_path = results.get(\\\"output_test\\\")[\\\"href\\\"].split(self.settings[\\\"weaver.wps_output_path\\\"])[-1]\\n tmp_file = \\\"{}/{}\\\".format(self.settings[\\\"weaver.wps_output_dir\\\"], job_output_path)\\n\\n try:\\n with open(tmp_file, \\\"r\\\") as f:\\n processed_values = json.load(f)\\n except FileNotFoundError:\\n self.fail(\\\"Output file [{}] was not found where it was expected to resume test\\\".format(tmp_file))\\n except Exception as exception:\\n self.fail(\\\"An error occurred during the reading of the file: {}\\\".format(exception))\\n assert processed_values[\\\"stringInput\\\"] == \\\"string_test\\\"\\n assert processed_values[\\\"integerInput\\\"] == 10\\n assert processed_values[\\\"doubleInput\\\"] == 3.14159\\n assert processed_values[\\\"stringArrayInput\\\"] == [\\\"1\\\", \\\"2\\\", \\\"3\\\", \\\"4\\\", \\\"5\\\", \\\"6\\\"]\\n assert processed_values[\\\"integerArrayInput\\\"] == [1, 2, 3, 4, 5, 6]\\n assert processed_values[\\\"floatArrayInput\\\"] == [1.45, 2.65, 3.5322, 4.86, 5.57, 6.02]\\n assert processed_values[\\\"measureStringInput\\\"] == \\\"this is a test\\\"\\n assert processed_values[\\\"measureIntegerInput\\\"] == 45\\n assert processed_values[\\\"measureFloatInput\\\"] == 10.2\\n assert processed_values[\\\"measureFileInput\\\"] == {\\\"VALUE\\\": {\\\"REF\\\": 1, \\\"MEASUREMENT\\\": 10.3, \\\"UOM\\\": \\\"M\\\"}}\",\n \"async def test_get_block_input_triggers(mock_block_device, monkeypatch) -> None:\\n monkeypatch.setattr(\\n mock_block_device.blocks[DEVICE_BLOCK_ID],\\n \\\"sensor_ids\\\",\\n {\\\"inputEvent\\\": \\\"S\\\", \\\"inputEventCnt\\\": 0},\\n )\\n monkeypatch.setitem(\\n mock_block_device.settings, \\\"rollers\\\", [{\\\"button_type\\\": \\\"detached\\\"}]\\n )\\n assert set(\\n get_block_input_triggers(\\n mock_block_device, mock_block_device.blocks[DEVICE_BLOCK_ID]\\n )\\n ) == {(\\\"long\\\", \\\"button\\\"), (\\\"single\\\", \\\"button\\\")}\\n\\n monkeypatch.setitem(mock_block_device.settings[\\\"device\\\"], \\\"type\\\", \\\"SHBTN-1\\\")\\n assert set(\\n get_block_input_triggers(\\n mock_block_device, mock_block_device.blocks[DEVICE_BLOCK_ID]\\n )\\n ) == {\\n (\\\"long\\\", \\\"button\\\"),\\n (\\\"double\\\", \\\"button\\\"),\\n (\\\"single\\\", \\\"button\\\"),\\n (\\\"triple\\\", \\\"button\\\"),\\n }\\n\\n monkeypatch.setitem(mock_block_device.settings[\\\"device\\\"], \\\"type\\\", \\\"SHIX3-1\\\")\\n assert set(\\n get_block_input_triggers(\\n mock_block_device, mock_block_device.blocks[DEVICE_BLOCK_ID]\\n )\\n ) == {\\n (\\\"long_single\\\", \\\"button\\\"),\\n (\\\"single_long\\\", \\\"button\\\"),\\n (\\\"triple\\\", \\\"button\\\"),\\n (\\\"long\\\", \\\"button\\\"),\\n (\\\"single\\\", \\\"button\\\"),\\n (\\\"double\\\", \\\"button\\\"),\\n }\",\n \"def dummy_code_block() -> CodeBlock:\\n return make_dummy_code_block()\",\n \"def create_initialised_input(self):\\n input_creator = InputCreator(self.times, self.inputs,\\n params=self.params, outputs=self.outputs)\\n f_out = input_creator.initialised_creation(self.burn_in)\\n\\n if self.debug:\\n print(f_out.getvalue(), file=sys.stderr)\\n f_out.seek(0)\\n\\n self.input_file = f_out.getvalue()\\n pprint.pprint(self.input_file)\\n return self.input_file\",\n \"def test_add_new_electric(self):\\n input_vars = ['5', 'Shaver', '1', 'n', 'y', 'Norelco', '110']\\n inventory = {}\\n with patch('builtins.input', side_effect=input_vars):\\n main.add_new_item(inventory)\\n self.assertEqual(inventory['5'],\\n {\\n 'product_code': '5',\\n 'description': 'Shaver',\\n 'market_price': 24,\\n 'rental_price': '1',\\n 'brand': 'Norelco',\\n 'voltage': '110'\\n })\",\n \"def simulate_block():\\n return '''\\n```sh\\n# In build directory\\n./simulate\\n```'''\",\n \"def mock_camera_fetch_input():\\n def fetch_input(self):\\n return np.random.randint(\\n low=0,\\n high=255,\\n size=(256, 256, 3),\\n dtype=np.uint8\\n )\\n\\n CameraDataProvider.fetch_input = fetch_input\\n CameraDataProvider.prepare = lambda self: None\\n CameraDataProvider.detach_from_source = lambda self: None\",\n \"def createStandardInput(self):\\n\\t\\traise NotImplementedError(\\\"\\\")\",\n \"def create_next_block(\\n self,\\n input_constants: Dict,\\n prev_block: FullBlock,\\n timestamp: uint64,\\n difficulty: uint64,\\n ips: uint64,\\n seed: bytes = b\\\"\\\",\\n ) -> FullBlock:\\n test_constants: Dict[str, Any] = constants.copy()\\n for key, value in input_constants.items():\\n test_constants[key] = value\\n\\n assert prev_block.header_block.challenge\\n\\n return self._create_block(\\n test_constants,\\n prev_block.header_block.challenge.get_hash(),\\n uint32(prev_block.height + 1),\\n prev_block.header_hash,\\n prev_block.header_block.challenge.total_iters,\\n prev_block.weight,\\n timestamp,\\n uint64(difficulty),\\n ips,\\n seed,\\n )\",\n \"def setUp(self):\\n self.my_model1 = BaseModel()\\n self.my_model1.name = \\\"hello\\\"\\n self.my_model1.number = 9\\n self.my_model2 = BaseModel()\\n self.my_model2.name = \\\"goodbye\\\"\\n self.my_model2.number = 19\\n self.mock_stdin = create_autospec(sys.stdin)\\n self.mock_stdout = create_autospec(sys.stdout)\",\n \"def test_client_create(self, mock_input, mock_pass):\\n # Patch username and password.\\n mock_input.return_value = \\\"user\\\"\\n mock_pass.return_value = \\\"pass\\\"\\n\\n # Instantiate Agave object making reference to local mock server.\\n local_uri = \\\"http://localhost:{port}/\\\".format(port=self.mock_server_port)\\n ag = Agave(api_server=local_uri)\\n\\n # Create client.\\n ag.clients_create(\\\"client-name\\\", \\\"some description\\\")\\n\\n assert ag.api_key == \\\"some api key\\\"\\n assert ag.api_secret == \\\"some secret\\\"\",\n \"def test_block_bad_signature(self):\\n pass\",\n \"def test_001(self):\\n user_input = [\\\"0\\\",\\\"0\\\",\\\"1\\\"]\\n with patch(\\\"builtins.input\\\", side_effect=user_input) as input_call:\\n with patch(\\\"sys.stdout\\\", new=StringIO()) as output:\\n import attempt\\n self.assertEqual(output.getvalue().strip(),\\\"You cannot take this course, sorry!\\\")\",\n \"def seed(cls, block: Expr) -> Expr:\\n return cls(BlockField.block_seed, block)\",\n \"def _initBlock(o,block):\\n o.block = block.clone().shift(*o.board.startPosition)\",\n \"def __init__(self, raw_input: Dict):\\n self.name = raw_input.get(\\\"name\\\")\\n self.description = raw_input.get(\\\"description\\\")\\n self.type: TypeDefer = TypeDefer(raw_input.get(\\\"type\\\")) if raw_input.get(\\\"type\\\") is not None else None\\n self.default_value = raw_input.get(\\\"defaultValue\\\")\",\n \"def generate_inputs(fixture_localhost, fixture_sandbox, fixture_code, generate_remote_data):\\n\\n def _generate_inputs(parameters=None, settings=None):\\n from aiida_quantumespresso.utils.resources import get_default_options\\n\\n if parameters is None:\\n parameters = {'INPUTPP': {}}\\n\\n return AttributeDict({\\n 'code':\\n fixture_code('quantumespresso.open_grid'),\\n 'parent_folder':\\n generate_remote_data(fixture_localhost, fixture_sandbox.abspath, 'quantumespresso.open_grid'),\\n 'parameters':\\n orm.Dict(dict=parameters),\\n 'settings':\\n orm.Dict(dict=settings),\\n 'metadata': {\\n 'options': get_default_options()\\n }\\n })\\n\\n return _generate_inputs\",\n \"def test_000(self):\\n user_input = [\\\"0\\\",\\\"0\\\",\\\"0\\\"]\\n with patch(\\\"builtins.input\\\", side_effect=user_input) as input_call:\\n with patch(\\\"sys.stdout\\\", new=StringIO()) as output:\\n import attempt\\n self.assertEqual(output.getvalue().strip(),\\\"You cannot take this course, sorry!\\\")\",\n \"def test_fork_simple(self):\\n bvh = self.BlockValidationHandler()\\n new_block = self.btm.generate_block(previous_block=self.btm.chain_head,\\n add_to_store=True)\\n\\n bv = self.create_block_validator(new_block, bvh.on_block_validated)\\n bv.run()\\n\\n self.assertTrue(bvh.has_result())\\n self.assertTrue(new_block.status == BlockStatus.Valid)\\n self.assertTrue(bvh.result[\\\"commit_new_block\\\"])\",\n \"def test_mock_input():\\n mock_message = mock.Mock()\\n mock_words = mock.Mock()\\n with pytest.raises(TypeError):\\n message_checker(mock_message, mock_words)\",\n \"def test_add_new_furniture(self):\\n input_vars = ['4', 'Rug', '1', 'y', 'Berber', 's']\\n inventory = {}\\n with patch('builtins.input', side_effect=input_vars):\\n main.add_new_item(inventory)\\n self.assertEqual(inventory['4'],\\n {\\n 'product_code': '4',\\n 'description': 'Rug',\\n 'market_price': 24,\\n 'rental_price': '1',\\n 'material': 'Berber',\\n 'size': 's'\\n })\",\n \"def setUp(self):\\n self.source_id = '12345'\\n self.checksum = 'asdfqwert1=='\\n self.stream = io.BytesIO(b'fakecontent')\",\n \"def setUp(self):\\n self.source_id = '12345'\\n self.checksum = 'asdfqwert1=='\\n self.stream = io.BytesIO(b'fakecontent')\",\n \"def setUp(self):\\n self.source_id = '12345'\\n self.checksum = 'asdfqwert1=='\\n self.stream = io.BytesIO(b'fakecontent')\",\n \"def setUp(self):\\n self.source_id = '12345'\\n self.checksum = 'asdfqwert1=='\\n self.stream = io.BytesIO(b'fakecontent')\",\n \"def _expected_inputs():\",\n \"def get_a_block(self, usage_id=None):\\r\\n scope_ids = Mock()\\r\\n if usage_id is None:\\r\\n usage_id = \\\"_auto%d\\\" % len(self.all_blocks)\\r\\n scope_ids.usage_id = usage_id\\r\\n block = self.system.construct_xblock_from_class(\\r\\n self.TestableInheritingXBlock,\\r\\n field_data=self.field_data,\\r\\n scope_ids=scope_ids,\\r\\n )\\r\\n self.all_blocks[usage_id] = block\\r\\n return block\",\n \"def setUp(self):\\n self.user = {\\n INPUT: \\\"12345\\\",\\n }\",\n \"def test_111(self):\\n user_input = [\\\"1\\\",\\\"1\\\",\\\"1\\\"]\\n with patch(\\\"builtins.input\\\", side_effect=user_input) as input_call:\\n with patch(\\\"sys.stdout\\\", new=StringIO()) as output:\\n import attempt\\n self.assertEqual(output.getvalue().strip(),\\\"You cannot take this course, sorry!\\\")\",\n \"def create_example(self, content, set_type):\\n return InputExample(content=content, processor=self)\",\n \"def test_stdin_input(self, api_client, ip_addresses, mock_response, expected):\\n runner = CliRunner()\\n\\n api_client.quick.return_value = mock_response\\n\\n result = runner.invoke(\\n subcommand.quick, [\\\"-f\\\", \\\"json\\\"], input=\\\"\\\\n\\\".join(ip_addresses)\\n )\\n assert result.exit_code == 0\\n assert result.output.strip(\\\"\\\\n\\\") == expected\\n api_client.quick.assert_called_with(ip_addresses=ip_addresses)\",\n \"def _generate_input_file(self):\\n if self.input_static:\\n return\\n\\n if self._input_generator_name is None:\\n logger.error(\\\"A testcase has neither a generator nor a static input\\\")\\n self.input_generation_log = \\\"Generation failed. No generator specified.\\\"\\n self.input_generation_successful = False\\n elif self._input_generator is None:\\n self.input_generation_log = \\\"Generation failed. Generator {} not found\\\".format(\\n self._input_generator_name,\\n )\\n self.input_generation_successful = False\\n else:\\n generation_command = get_execution_command(self._input_generator.source_language, \\\"generator\\\")\\n generation_command.extend(shlex.split(self._input_generation_parameters))\\n stdout_redirect = \\\"output.txt\\\"\\n\\n try:\\n generator_compiled = self._input_generator.compiled_file\\n except:\\n self.input_generation_log = \\\"Generation failed. Generator didn't compile. Log: {}\\\".format(\\n self._input_generator.last_compile_log\\n )\\n self.save()\\n return\\n\\n action = ActionDescription(\\n commands=[generation_command],\\n executables=[(\\\"generator\\\", generator_compiled)],\\n stdout_redirect=stdout_redirect,\\n output_files=[stdout_redirect],\\n time_limit=settings.FAILSAFE_TIME_LIMIT,\\n memory_limit=settings.FAILSAFE_MEMORY_LIMIT\\n )\\n success, execution_success, outputs, sandbox_datas = execute_with_input(action)\\n if not success:\\n logger.error(\\\"Generating input for testcase {} failed.\\\\n Sandbox data:\\\\n{}\\\".format(\\n str(self),\\n str(sandbox_datas[0]))\\n )\\n self.input_generation_log = \\\\\\n \\\"System failed to generate the input. \\\" \\\\\\n \\\"Check the logs for more details. \\\" \\\\\\n \\\"This issue must be resolved by a system administrator\\\"\\n self.input_generation_successful = False\\n elif not execution_success:\\n self.input_generation_log = \\\"Generation failed. {}.\\\".format(\\n str(sandbox_datas[0])\\n )\\n self.input_generation_successful = False\\n else:\\n self._input_generated_file = outputs[stdout_redirect]\\n self.input_generation_log = \\\"Generation successful.\\\"\\n self.input_generation_successful = True\\n self.save()\",\n \"def __init__(self):\\n self.inputs = {}\",\n \"def test_block_extra_batch(self):\\n pass\",\n \"def createInitializedBlock(self, name: unicode, start: ghidra.program.model.address.Address, is_: java.io.InputStream, length: long, monitor: ghidra.util.task.TaskMonitor, overlay: bool) -> ghidra.program.model.mem.MemoryBlock:\\n ...\",\n \"def test_prompt_ask_var_numbers_valid(self):\\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\\n result = self.prompt._prompt({}, {\\n 'say': 'test',\\n 'ask': '12345'\\n })\\n\\n self.assertEquals(result['ansible_facts']['12345'], 'mocked input')\",\n \"def test_prompt_ask_var_simple_valid(self):\\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\\n result = self.prompt._prompt({}, {\\n 'say': 'test',\\n 'ask': 'varname'\\n })\\n\\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')\",\n \"def create_dummy_args(self):\\n if not self.is_built:\\n raise RuntimeError(\\\"A plan needs to be built before input shapes can be known.\\\")\\n\\n def traverse_nested_types(arg, leaf_function):\\n if isinstance(arg, list):\\n return [traverse_nested_types(obj, leaf_function) for obj in arg]\\n elif isinstance(arg, tuple):\\n return tuple(traverse_nested_types(obj, leaf_function) for obj in arg)\\n elif isinstance(arg, dict):\\n return {k: traverse_nested_types(v, leaf_function) for k, v in arg.items()}\\n else:\\n return leaf_function(arg)\\n\\n input_placeholders = (ph for ph in self.role.input_placeholders())\\n\\n def create_dummy(input_type, input_placeholder):\\n if issubclass(input_type, FrameworkTensor):\\n return input_type(\\n PlaceHolder.create_placeholders([input_placeholder.expected_shape])[0]\\n )\\n else:\\n return input_type()\\n\\n return traverse_nested_types(\\n self.input_types.nested_input_types,\\n lambda input_type: create_dummy(input_type, input_placeholders.__next__()),\\n )\",\n \"def test_truncated_input(self):\\n\\n def data_reader():\\n for _ in range(4):\\n yield b\\\"0123\\\"\\n raise EOFError\\n\\n self.assertRaises(\\n EOFError,\\n self.storage.object_create_ext,\\n self.account,\\n self.container,\\n obj_name=\\\"truncated-input\\\",\\n data=data_reader(),\\n )\",\n \"def test_01(self):\\n assert 'True' == Api.requestBlock('test-01')\",\n \"def test_inputs():\\n # Get data from the input file and unpacking it to three variable\\n get_data = read_input()\\n restructuring_info = get_data[0]\\n machine_info = get_data[1]\\n length = get_data[2]\\n # start, end to slice the generator\\n start, end = 0, 0\\n # Loop through lenght of restructuring\\n # Get x (restructuring_info) and y (machine_info)\\n # Use x, y as a parameter for get_max_money function\\n for i in range(length):\\n x = next(restructuring_info)\\n y = []\\n # Check if there a machine\\n # clone the machine_info generator to slice it\\n # the cliced generator represent the machine informations\\n # that related to restructuring_info\\n if int(x[0]):\\n end += int(x[0])\\n machine_info, m_backup = itertools.tee(machine_info)\\n y = itertools.islice(m_backup, start, end)\\n start = end\\n\\n yield ('Case ' +str(i+1) + \\\": \\\" + str(get_max_money(x, y)))\",\n \"def _build_impl_impl(self, input):\",\n \"def run(self, input):\\n return {}\",\n \"def test_101(self):\\n user_input = [\\\"1\\\",\\\"0\\\",\\\"1\\\"]\\n with patch(\\\"builtins.input\\\", side_effect=user_input) as input_call:\\n with patch(\\\"sys.stdout\\\", new=StringIO()) as output:\\n import attempt\\n self.assertEqual(output.getvalue().strip(),\\\"You cannot take this course, sorry!\\\")\",\n \"def test_make_form():\",\n \"def test_feed_block_creation(self):\\n content_type = 'text'\\n content = 'content'\\n block = FeedItemDescriptionBlock(content_type, content)\\n assert isinstance(block, FeedItemDescriptionBlock)\\n assert block.type == content_type\\n assert block.content == content\",\n \"def __create_input(self, timestep):\\n self.litter = {}\\n if timestep == 0:\\n self.initial = {}\\n if self.initial_mode!='zero':\\n self._define_components(self.initial_def, self.initial)\\n if self.md.litter_mode == 'constant yearly':\\n self._define_components(self.md.constant_litter, self.litter)\\n else:\\n timeind = self._map_timestep2timeind(timestep)\\n if self.md.litter_mode=='monthly':\\n infdata = self.md.monthly_litter\\n elif self.md.litter_mode=='yearly':\\n infdata = self.md.yearly_litter\\n self._define_components(infdata, self.litter, tsind=timeind)\\n self._fill_input()\",\n \"def test_mp3_controller(file_input, filepath, monkeypatch):\\n user_input = StringIO(file_input)\\n test = VideoSynth()\\n controller = Mp3Controller(test)\\n monkeypatch.setattr('sys.stdin', user_input)\\n controller.create_file_path()\\n assert test.file_path() == filepath\",\n \"def input(self):\\r\\n pass\",\n \"def create_inputs(self):\\n return {}\",\n \"def generate_input(title, input_widget):\\n\\n return html.Div([\\n # Titre de l'input\\n html.Li([\\n html.H6(title)\\n ]),\\n\\n # Input\\n input_widget\\n ])\",\n \"def test_main_gc_1(test):\\n answers = (i for i in (test, 'b', 'q'))\\n with mock.patch.object(builtins, 'input', lambda _: next(answers)):\\n g_c.main()\",\n \"def test_prompt_ask_say_missing_valid(self):\\n with mock.patch('__builtin__.raw_input', return_value='mocked input') as mockinput:\\n result = self.prompt._prompt({}, {\\n 'ask': 'varname'\\n })\\n\\n self.assertEquals(result['ansible_facts']['varname'], 'mocked input')\",\n \"def test_new_block_return_type(self):\\n block = self.blockchain.new_block(self.proof, self.previous_hash)\\n self.assertIsInstance(block, dict)\",\n \"def get_input(self):\\n pass\",\n \"def test_011(self):\\n user_input = [\\\"0\\\",\\\"1\\\",\\\"1\\\"]\\n with patch(\\\"builtins.input\\\", side_effect=user_input) as input_call:\\n with patch(\\\"sys.stdout\\\", new=StringIO()) as output:\\n import attempt\\n self.assertEqual(output.getvalue().strip(),\\\"You cannot take this course, sorry!\\\")\",\n \"def test_010(self):\\n user_input = [\\\"0\\\",\\\"1\\\",\\\"0\\\"]\\n with patch(\\\"builtins.input\\\", side_effect=user_input) as input_call:\\n with patch(\\\"sys.stdout\\\", new=StringIO()) as output:\\n import attempt\\n self.assertEqual(output.getvalue().strip(),\\\"You cannot take this course, sorry!\\\")\",\n \"def createBlock(self, block: ghidra.program.model.mem.MemoryBlock, name: unicode, start: ghidra.program.model.address.Address, length: long) -> ghidra.program.model.mem.MemoryBlock:\\n ...\",\n \"def _make_block(self, model):\\n # TODO Make base class\\n assert model is not None, 'Top level model must be initialized first'\\n self.model = model\\n # If block is already present, remove it\\n if self.model.component(self.name) is not None:\\n self.model.del_component(self.name)\\n self.model.add_component(self.name, Block())\\n self.block = self.model.__getattribute__(self.name)\\n\\n self.logger.info(\\n 'Optimization block initialized for {}'.format(self.name))\",\n \"def create_genesis_block(\\n self, input_constants: Dict, challenge_hash=bytes([0] * 32), seed: bytes = b\\\"\\\"\\n ) -> FullBlock:\\n test_constants: Dict[str, Any] = constants.copy()\\n for key, value in input_constants.items():\\n test_constants[key] = value\\n\\n return self._create_block(\\n test_constants,\\n challenge_hash,\\n uint32(0),\\n bytes([0] * 32),\\n uint64(0),\\n uint64(0),\\n uint64(int(time.time())),\\n uint64(test_constants[\\\"DIFFICULTY_STARTING\\\"]),\\n uint64(test_constants[\\\"VDF_IPS_STARTING\\\"]),\\n seed,\\n )\",\n \"async def async_step_init(self, user_input=None):\\n if user_input is not None:\\n return self.async_create_entry(title=\\\"\\\", data=user_input)\\n\\n options_schema = vol.Schema(\\n {\\n vol.Optional(\\n CONF_UNIT_BARO,\\n default=self.config_entry.options.get(\\n CONF_UNIT_BARO, CONF_UNIT_SYSTEM_METRIC,\\n ),\\n ): vol.In(UNIT_OPTS),\\n vol.Optional(\\n CONF_UNIT_WIND,\\n default=self.config_entry.options.get(\\n CONF_UNIT_WIND, CONF_UNIT_SYSTEM_IMPERIAL,\\n ),\\n ): vol.In(WIND_OPTS),\\n vol.Optional(\\n CONF_UNIT_RAIN,\\n default=self.config_entry.options.get(\\n CONF_UNIT_RAIN, CONF_UNIT_SYSTEM_IMPERIAL,\\n ),\\n ): vol.In(UNIT_OPTS),\\n vol.Optional(\\n CONF_UNIT_LIGHTNING,\\n default=self.config_entry.options.get(\\n CONF_UNIT_LIGHTNING, CONF_UNIT_SYSTEM_IMPERIAL,\\n ),\\n ): vol.In(UNIT_OPTS),\\n vol.Optional(\\n CONF_UNIT_WINDCHILL,\\n default=self.config_entry.options.get(\\n CONF_UNIT_WINDCHILL, W_TYPE_HYBRID,\\n ),\\n ): vol.In(WINDCHILL_OPTS),\\n }\\n )\\n return self.async_show_form(step_id=\\\"init\\\", data_schema=options_schema)\",\n \"def CreateInput(self, name=None, type=None, data=None):\\n\\n\\n inp = self._input_registry.Create(name, type, data)\\n\\n self._inputs.append(inp)\\n\\n return inp\",\n \"def gen_new_block(self):\\n block = BasicBlock()\\n self.blocks.append(block)\\n return block\",\n \"def block(self) -> IMockPin:\\n return self[\\\"block\\\"]\",\n \"def input(self):\",\n \"def create_engine(self, input):\\n return\",\n \"def ConfigureIO():\\n\\n def Input():\\n try:\\n return input()\\n except Error as e:\\n raise Error(INVALID_LINE_ERROR + str(e))\\n\\n Output = ActuallyOutput\\n return Input, Output\",\n \"def test_main_gc_2(test):\\n answers = (i for i in (test, '1 1 1 1', 'q'))\\n with mock.patch.object(builtins, 'input', lambda _: next(answers)):\\n g_c.main()\",\n \"def create_default_input(self):\\n input_creator = InputCreator(self.times, self.inputs)\\n self.input_file = input_creator.default_creation().getvalue()\\n\\n return self.input_file\",\n \"def test_no_vault_secrets(mock_load, localhost_client, gen_input_config):\\n mock_load.return_value = gen_input_config(vault_secrets={})\\n\\n localhost_client.load(\\\"in.json\\\")\\n\\n mock_load.assert_called_with(\\\"in.json\\\")\",\n \"def test_custom_local_input_file() -> None:\\n with tempfile.TemporaryDirectory() as tmpdirname:\\n file_location = os.path.join(tmpdirname, \\\"foo.txt\\\")\\n with open(file_location, \\\"wb\\\") as write_file:\\n write_file.write(b\\\"foo\\\")\\n\\n # Confirm that the file initially exists\\n assert os.path.exists(file_location)\\n\\n # Instantiate the input file\\n absolute_file_location = os.path.abspath(file_location)\\n input_file = PyArrowFileIO().new_input(location=f\\\"{absolute_file_location}\\\")\\n\\n # Test opening and reading the file\\n f = input_file.open()\\n data = f.read()\\n assert data == b\\\"foo\\\"\\n assert len(input_file) == 3\",\n \"def initialize(self, inputs, base_block, n_repeats, *args, **kwargs):\\n for repeat in range(n_repeats):\\n if args:\\n for i, item in enumerate(args):\\n # Make block\\n if isinstance(item, dict):\\n block_constructor = item.pop('base_block', None) or base_block\\n block_args = {'inputs': inputs, **dict(Config(kwargs) + Config(item))}\\n block = block_constructor(**block_args)\\n elif isinstance(item, nn.Module):\\n block = item\\n else:\\n raise ValueError(f'Positional arguments of Block must be either dicts or nn.Modules, '\\n f'got {type(item)} instead!')\\n\\n inputs = self.initialize_block(inputs, block, f'repeat{repeat}-args{i}')\\n\\n else:\\n # Make block\\n block = base_block(inputs=inputs, **kwargs)\\n inputs = self.initialize_block(inputs, block, f'repeat{repeat}')\",\n \"async def async_process_input(self, inp: inputs.Input) -> None:\\n if isinstance(inp, inputs.ModNameComment):\\n command = inp.command\\n block_id = inp.block_id\\n text = inp.text\\n\\n if command == \\\"K\\\":\\n self._comment[block_id] = f\\\"{text:12s}\\\"\\n await self.cancel(block_id)\\n if None not in self._comment:\\n self.comment_known.set()\\n await self.cancel()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6843587","0.66973007","0.6653255","0.63940287","0.6144296","0.6105641","0.5916343","0.58348626","0.57676345","0.56919837","0.55923426","0.55832005","0.55725527","0.5560723","0.5554768","0.55407476","0.5519871","0.5497402","0.54970086","0.5474238","0.5459816","0.54584813","0.5456826","0.5443481","0.5430159","0.54167366","0.54028976","0.53781635","0.53760946","0.53734905","0.5356117","0.5350661","0.5339983","0.5312176","0.5254384","0.5244666","0.5243147","0.52391094","0.5238466","0.5225161","0.52192456","0.52154356","0.5214678","0.5210685","0.52059495","0.51967466","0.5196451","0.5195986","0.51898676","0.51898676","0.51898676","0.51898676","0.518529","0.5182342","0.51775247","0.5169422","0.5168687","0.5138714","0.51376736","0.513601","0.51324767","0.51297814","0.5127734","0.5127496","0.51263124","0.51186764","0.51176804","0.5117519","0.5113529","0.5102884","0.50928736","0.5091395","0.5090217","0.5088697","0.507032","0.5068432","0.5063748","0.5057104","0.5055933","0.5052422","0.50509906","0.5047814","0.50451124","0.5044799","0.5041755","0.5030502","0.5029018","0.5025764","0.5019918","0.5019031","0.50187594","0.50162137","0.500863","0.5004392","0.50041384","0.5002705","0.5001584","0.4997343","0.49965638","0.49959275"],"string":"[\n \"0.6843587\",\n \"0.66973007\",\n \"0.6653255\",\n \"0.63940287\",\n \"0.6144296\",\n \"0.6105641\",\n \"0.5916343\",\n \"0.58348626\",\n \"0.57676345\",\n \"0.56919837\",\n \"0.55923426\",\n \"0.55832005\",\n \"0.55725527\",\n \"0.5560723\",\n \"0.5554768\",\n \"0.55407476\",\n \"0.5519871\",\n \"0.5497402\",\n \"0.54970086\",\n \"0.5474238\",\n \"0.5459816\",\n \"0.54584813\",\n \"0.5456826\",\n \"0.5443481\",\n \"0.5430159\",\n \"0.54167366\",\n \"0.54028976\",\n \"0.53781635\",\n \"0.53760946\",\n \"0.53734905\",\n \"0.5356117\",\n \"0.5350661\",\n \"0.5339983\",\n \"0.5312176\",\n \"0.5254384\",\n \"0.5244666\",\n \"0.5243147\",\n \"0.52391094\",\n \"0.5238466\",\n \"0.5225161\",\n \"0.52192456\",\n \"0.52154356\",\n \"0.5214678\",\n \"0.5210685\",\n \"0.52059495\",\n \"0.51967466\",\n \"0.5196451\",\n \"0.5195986\",\n \"0.51898676\",\n \"0.51898676\",\n \"0.51898676\",\n \"0.51898676\",\n \"0.518529\",\n \"0.5182342\",\n \"0.51775247\",\n \"0.5169422\",\n \"0.5168687\",\n \"0.5138714\",\n \"0.51376736\",\n \"0.513601\",\n \"0.51324767\",\n \"0.51297814\",\n \"0.5127734\",\n \"0.5127496\",\n \"0.51263124\",\n \"0.51186764\",\n \"0.51176804\",\n \"0.5117519\",\n \"0.5113529\",\n \"0.5102884\",\n \"0.50928736\",\n \"0.5091395\",\n \"0.5090217\",\n \"0.5088697\",\n \"0.507032\",\n \"0.5068432\",\n \"0.5063748\",\n \"0.5057104\",\n \"0.5055933\",\n \"0.5052422\",\n \"0.50509906\",\n \"0.5047814\",\n \"0.50451124\",\n \"0.5044799\",\n \"0.5041755\",\n \"0.5030502\",\n \"0.5029018\",\n \"0.5025764\",\n \"0.5019918\",\n \"0.5019031\",\n \"0.50187594\",\n \"0.50162137\",\n \"0.500863\",\n \"0.5004392\",\n \"0.50041384\",\n \"0.5002705\",\n \"0.5001584\",\n \"0.4997343\",\n \"0.49965638\",\n \"0.49959275\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8625998"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13096,"cells":{"query":{"kind":"string","value":"Create mock output block."},"document":{"kind":"string","value":"def fixture_output_block():\n return Mock()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def fixture_input_block():\n return Mock()","def test_03_out(self, mock_stdout):\n msg = udocker.Msg(udocker.Msg.MSG)\n msg.out(\"111\", \"222\", \"333\", 444, ('555'))\n self.assertEqual(\"111 222 333 444 555\\n\", mock_stdout.getvalue())\n sys.stdout = STDOUT\n sys.stderr = STDERR","def test_block_default_output(self):\n\n @output('out1', default=True)\n @output('out2')\n class MyBlock(Block):\n pass\n\n blk = MyBlock()\n self.configure_block(blk, {})\n sig1, sig2, sig3 = (\n Signal({'sig': 1}),\n Signal({'sig': 2}),\n Signal({'sig': 3}),\n )\n blk.notify_signals([sig1], 'out1')\n self.assert_last_signal_notified(sig1, 'out1')\n blk.notify_signals([sig2], 'out2')\n self.assert_last_signal_notified(sig2, 'out2')\n # Notify the last signal without any output ID, make sure the actual\n # default terminal of the block is used\n blk.notify_signals([sig3])\n self.assert_last_signal_notified(sig3, 'out1')","def setUp(self):\n self._output = io.StringIO()","def _generate_output(self):\n raise NotImplementedError()","def __init__(self, output_mediator_object):\n super(TestOutputModule, self).__init__(output_mediator_object)\n self.events = []\n self.macb_groups = []","def _populate_output(self):\n pass","def setUp(self):\n\t\tself.output = self.switchstdout()","def mock_output(self, command, _rc, output, _err):\n\n self.mocks[command] = (_rc, output, _err)","def simulate_block():\n return '''\n```sh\n# In build directory\n./simulate\n```'''","def test_export_custom(self): # pylint: disable=no-self-use\n mock_record_str = Mock(str)\n\n def formatter(record): # pylint: disable=unused-argument\n return mock_record_str\n\n mock_stdout = Mock()\n exporter = ConsoleLogExporter(out=mock_stdout, formatter=formatter)\n log_data = LogData(\n log_record=LogRecord(),\n instrumentation_scope=InstrumentationScope(\n \"first_name\", \"first_version\"\n ),\n )\n exporter.export([log_data])\n mock_stdout.write.assert_called_once_with(mock_record_str)","def test_create(self):\n _help = \"[Usage: create <class name>]\\n\"\n with patch('sys.stdout', new=StringIO()) as f:\n HBNBCommand().onecmd(\"help create\")\n self.assertEqual(f.getvalue(), _help)","def test_dump(\n mock_hvac_client_read, mock_dump, localhost_client, gen_input_config, gen_processed_config, gen_vault_response_kv1\n):\n mock_hvac_client_read.return_value = gen_vault_response_kv1()\n\n localhost_client.dump(gen_input_config(), \"out.json\")\n\n mock_hvac_client_read.assert_called_with(gen_input_config()[\"vault_secrets\"][\"acme.user\"])\n mock_dump.assert_called_with(gen_processed_config(), \"out.json\")","def create_outputs(block):\n return [nbbase.NotebookNode(output)\n for output in json.loads(block['content'])]","def test(self, parent, block):\r\n pass","def test_default_output(self):\n env = pike.Environment()\n output = pike.Graph('output')\n output.sink = pike.noop()\n with patch.object(output, 'run') as run:\n run.return_value = []\n env.set_default_output(output)\n with pike.Graph('g') as graph:\n pike.glob('.', '*')\n env.add(graph)\n env.run_all()\n run.assert_called_with([])","def test_exit_on_output_cb_error(output_block, kwargs):\n output_block.side_effect = Exception()\n with pytest.raises(SystemExit) as exc_info:\n create_flow(**kwargs)\n assert exc_info.value.code == 1","def test_create_stream_handler(self, mock_handler: MagicMock):\n\n instance = mock_handler.return_value\n instance.setFormatter = MagicMock()\n instance.setLevel = MagicMock()\n\n handler = create_stream_handler(self.level, self.format)\n\n mock_handler.assert_called_with(stdout)\n instance.setFormatter.assert_called_with(self.format)\n instance.setLevel.assert_called_with(self.level)\n\n self.assertIsNotNone(handler)","def __init__(self):\n super(MockOutputModule, self).__init__()\n self.hostname = None\n self.port = None","def setUp(self):\n super(BlockBookingsReportTests, self).setUp()\n self.user1 = baker.make_recipe('booking.user')\n self.user2 = baker.make_recipe('booking.user')\n\n self.event_type = baker.make_recipe('booking.event_type_PC')\n\n self.user1_active_block = baker.make_recipe(\n 'booking.block_5', user=self.user1,\n start_date=timezone.now() - timedelta(10),\n block_type__event_type=self.event_type,\n paid=True\n )\n self.user2_active_block = baker.make_recipe(\n 'booking.block_5', user=self.user2,\n start_date=timezone.now() - timedelta(10),\n block_type__event_type=self.event_type, paid=True\n )\n\n user1_bookings_on_block = baker.make_recipe(\n 'booking.booking',\n user=self.user1,\n event__event_type=self.event_type,\n block=self.user1_active_block,\n date_booked=timezone.now() - timedelta(8),\n _quantity=2\n )\n self.user1_booking_not_on_block = baker.make_recipe(\n 'booking.booking',\n user=self.user1,\n event__event_type=self.event_type,\n date_booked=timezone.now() - timedelta(8)\n )\n user1_booking_old = baker.make_recipe(\n 'booking.booking',\n user=self.user1,\n event__event_type=self.event_type,\n date_booked=timezone.now() - timedelta(12)\n )\n user1_booking_free = baker.make_recipe(\n 'booking.booking',\n user=self.user1,\n event__event_type=self.event_type,\n free_class=True,\n date_booked=timezone.now() - timedelta(8)\n )\n\n # redirect stdout so we can test it\n self.output = StringIO()\n self.saved_stdout = sys.stdout\n sys.stdout = self.output","def write_output(self):","def create_output(self, messages):","def testNewOutputModule(self):\n manager.OutputManager.RegisterOutput(TestOutput)\n\n output_module = manager.OutputManager.NewOutputModule('test_output')\n self.assertIsInstance(output_module, TestOutput)\n\n with self.assertRaises(ValueError):\n manager.OutputManager.NewOutputModule(1)\n\n with self.assertRaises(KeyError):\n manager.OutputManager.NewOutputModule('bogus')\n\n manager.OutputManager.DeregisterOutput(TestOutput)","def generateStandardMock(monkeypatch, return_value_output, return_value_error, return_code, type=\"gpt\"):\n mock_popen = mock.MagicMock()\n mock_popen.communicate.return_value = (return_value_output, return_value_error)\n mock_popen.returncode = return_code\n def popen_constructor(*args, **kargs):\n return mock_popen\n def mock_table_type(*args, **kargs):\n return type\n monkeypatch.setattr(\"subprocess.Popen\", popen_constructor)\n if type != None:\n monkeypatch.setattr(\"weresync.device.DeviceManager.get_partition_table_type\", mock_table_type)","def GetTestWrapper(self):\n return ''","def test_updated_display1(self):\n capturedOutput = io.StringIO()\n sys.stdout = capturedOutput\n r1 = Rectangle(2, 3, 2, 2)\n r1.display()\n sys.stdout = sys.__stdout__\n desired = '\\n\\n ##\\n ##\\n ##\\n'\n self.assertEqual(capturedOutput.getvalue(), desired)","def setUp(self):\n self.actualstdout = sys.stdout\n sys.stdout = StringIO.StringIO()","def test_generateconfig(self):\n args = mock.Mock()\n args.debug = None\n args.generateconfig = True\n args.config = None\n expected_text = ('Sample configuration file written to sample_config.json\\n'\n \"Replicate the site JSON for each site.\\n\"\n \" Valid values for use_https and local are 'True' and 'False'\\n\"\n \" One site must have local set to 'True'\\n\"\n 'Replicate the export JSON for each exported contract.\\n')\n with mock.patch('sys.stdout', new=StringIO()) as fake_out:\n execute_tool(args)\n self.assertEqual(fake_out.getvalue(), expected_text)","def test_format_start_new_output(self):\n # Setup params and mock result of parking lot execution\n start_new_cmd = \"create_parking_lot\"\n result = 5\n\n # Verify formatting is correct\n success, output = self.controller.format_start_new_output(result)\n self.assertTrue(success)\n self.assertEqual(output, \"Created a parking lot with {} slots\".format(result))","def test_html_output(self):\n pass","def test_filter(self, logger: Logger, mocker: MockerFixture) -> None:\n task = OctaveTask()\n task.session_id = \"123\"\n handler = OutputHandler(task)\n logger.addHandler(handler)\n\n send_func = mocker.patch(\"matl_online.tasks.OutputHandler.send\")\n\n logger.warning(\"warning\")\n logger.error(\"error\")\n logger.debug(\"debug\")\n\n assert len(handler.contents) == 0\n send_func.assert_not_called()","def writer_wrapper_2(coroutine):\n yield from coroutine","def output_verilog_testbench(file, simulation_trace=None, block=None):\n\n block = working_block(block)\n inputs = block.wirevector_subset(Input)\n outputs = block.wirevector_subset(Output)\n\n # Output header\n print('module tb();', file=file)\n\n # Declare all block inputs as reg\n print(' reg clk;', file=file)\n for w in inputs:\n print(' reg {:s} {:s};'.format(_verilog_vector_decl(w), w.name), file=file)\n\n # Declare all block outputs as wires\n for w in outputs:\n print(' wire {:s} {:s};'.format(_verilog_vector_decl(w), w.name), file=file)\n print('', file=file)\n\n # Instantiate logic block\n io_list = [w.name for w in block.wirevector_subset((Input, Output))]\n io_list.append('clk')\n io_list_str = ['.{0:s}({0:s})'.format(w) for w in io_list]\n print(' toplevel block({:s});\\n'.format(', '.join(io_list_str)), file=file)\n\n # Generate clock signal\n print(' always', file=file)\n print(' #0.5 clk = ~clk;\\n', file=file)\n\n # Move through all steps of trace, writing out input assignments per cycle\n print(' initial begin', file=file)\n print(' $dumpfile (\"waveform.vcd\");', file=file)\n print(' $dumpvars;\\n', file=file)\n print(' clk = 0;', file=file)\n\n for i in range(len(simulation_trace)):\n for w in inputs:\n print(' {:s} = {:s}{:d};'.format(\n w.name,\n \"{:d}'d\".format(len(w)),\n simulation_trace.trace[w][i]), file=file)\n print('\\n #2', file=file)\n\n # Footer\n print(' $finish;', file=file)\n print(' end', file=file)\n print('endmodule', file=file)","def test_addOutput(self):\n print(\"\\nTest 2: Adding OutputNode\")\n builder = StaticBuilder()\n builder.addInput(10, name=\"In\")\n builder.addInner(3, name=\"Det\")\n o_name = builder.addOutput(name=\"Out\")\n \n o1 = builder.nodes[o_name]\n print(\"\\nNode keys in builder:\", list(builder.nodes.keys()))\n print(\"This node's key:\", o_name)\n self.assertEqual(o1.label, 2, \"The label has not been assigned correctly\")\n self.assertEqual(builder.num_nodes, 3, \"The number of nodes has not been \"\n \"assigned correctly\")\n self.assertEqual(o1.num_declared_outputs, 0, \"The number of outputs of the \"\n \"OutputNode has not been assigned correctly\")\n self.assertEqual(o1.num_declared_inputs, 0, \"The number of inputs of the \"\n \"OutputNode has not been assigned correctly\")","def test_display_method2(self):\n capturedOutput = io.StringIO()\n sys.stdout = capturedOutput\n r2 = Rectangle(2, 2)\n r2.display()\n sys.stdout = sys.__stdout__\n desired = '##\\n##\\n'\n self.assertEqual(capturedOutput.getvalue(), desired)","def test_display__method2(self):\n Rectangle.reset_objects()\n s2 = Square(2, 2)\n f = io.StringIO()\n with contextlib.redirect_stdout(f):\n s2.display()\n self.assertEqual(f.getvalue(), \" ##\\n ##\\n\")","def run_output(mocker):\n return mocker.patch('d.subprocess.check_output')","def test_display__method(self):\n Rectangle.reset_objects()\n s1 = Square(5)\n f = io.StringIO()\n with contextlib.redirect_stdout(f):\n s1.display()\n self.assertEqual(f.getvalue(), \"#####\\n#####\\n#####\\n#####\\n#####\\n\")","def mock_result_stream():\n response_file_path = os.path.join(import_module(__name__).__path__[0], \n \"splunk_job_result_stream_sample.xml\")\n with open(response_file_path, 'r') as response_file:\n response = StringIO(response_file.read())\n alsoProvides(response, ISplunkResultsStream)\n return response","def __init__(self, output_mediator):\n event_formatting_helper = shared_json.JSONEventFormattingHelper(\n output_mediator)\n super(JSONLineOutputModule, self).__init__(\n output_mediator, event_formatting_helper)","def test_updated_display3(self):\n capturedOutput = io.StringIO()\n sys.stdout = capturedOutput\n r3 = Rectangle(3, 2, 0, 1)\n r3.display()\n sys.stdout = sys.__stdout__\n desired = '\\n###\\n###\\n'\n self.assertEqual(capturedOutput.getvalue(), desired)","def _CreateOutputMediator(self, config=None, storage_object=None):\n formatter_mediator = formatters_mediator.FormatterMediator()\n return mediator.OutputMediator(\n formatter_mediator, storage_object, config=config)","def write_output_inline(self, index, content):\n self.expected_output_mask.add(index)\n ref = self.block_store.ref_from_string(content, self.task_descriptor['expected_outputs'][index])\n self.task_record.publish_ref(ref)\n return ref","def test_updated_display2(self):\n capturedOutput = io.StringIO()\n sys.stdout = capturedOutput\n r2 = Rectangle(3, 2, 1, 0)\n r2.display()\n sys.stdout = sys.__stdout__\n desired = ' ###\\n ###\\n'\n self.assertEqual(capturedOutput.getvalue(), desired)","def setUp(self):\n self.output = StringIO.StringIO()\n self.formatter = json_out.Json(None, self.output)\n self.event_object = JsonTestEvent()","def testNoOutput(self):\n output_mediator = self._CreateOutputMediator()\n output_writer = cli_test_lib.TestOutputWriter()\n output_module = null.NullOutputModule(output_mediator)\n\n output_module.WriteHeader()\n\n event, event_data, event_data_stream = (\n containers_test_lib.CreateEventFromValues(self._TEST_EVENTS[0]))\n output_module.WriteEventBody(\n event, event_data, event_data_stream, None)\n\n output_module.WriteFooter()\n\n output = output_writer.ReadOutput()\n self.assertEqual('', output)","def test_wrapper_output(self):\r\n tmpdir = None\r\n try:\r\n tmpdir = tempfile.mkdtemp()\r\n result = mib2pysnmp('conpot/tests/data/VOGON-POEM-MIB.mib')\r\n\r\n with open(os.path.join(tmpdir, 'VOGON-POEM-MIB' + '.py'), 'w') as output_file:\r\n output_file.write(result)\r\n\r\n cmd_responder = command_responder.CommandResponder('', 0, [tmpdir])\r\n cmd_responder.snmpEngine.msgAndPduDsp.mibInstrumController.mibBuilder.loadModules('VOGON-POEM-MIB')\r\n result = cmd_responder._get_mibSymbol('VOGON-POEM-MIB', 'poemNumber')\r\n\r\n self.assertIsNotNone(result, 'The expected MIB (VOGON-POEM-MIB) could not be loaded.')\r\n finally:\r\n shutil.rmtree(tmpdir)","def test_generate_secret_file(self, mock_context, mock_create_aws, mock_file_open, mock_json, mock_dump):\n context = ef_password.EFPWContext()\n context.env, context.service = self.env, self.service\n context.secret_file = self.secret_file\n context.match = 'password'\n mock_context.return_value = context\n mock_create_aws.return_value = {\"kms\": self.mock_kms}\n mock_json.return_value = {\"params\": {\"test\": {\"password\": \"mock_secret1\"}}}\n ef_password.main()\n self.mock_kms.decrypt.assert_not_called()\n self.mock_kms.encrypt.assert_called_once_with(\n KeyId='alias/{}-{}'.format(self.env, self.service),\n Plaintext=\"mock_secret1\".encode()\n )\n mock_file_open.assert_called_with(self.secret_file, 'w')\n handle = mock_file_open()\n mock_dump.assert_called_once_with({'params': {'test': {'password': '{{aws:kms:decrypt,Y2lwaGVyX2Jsb2I=}}'}}},\n handle, indent=2, separators=(',', ': '))\n handle.write.assert_called_with('\\n')","def test_updated_display4(self):\n capturedOutput = io.StringIO()\n sys.stdout = capturedOutput\n r4 = Rectangle(3, 2, 0, 0)\n r4.display()\n sys.stdout = sys.__stdout__\n desired = '###\\n###\\n'\n self.assertEqual(capturedOutput.getvalue(), desired)","def test_display__method3(self):\n Rectangle.reset_objects()\n s3 = Square(3, 1, 3)\n f = io.StringIO()\n with contextlib.redirect_stdout(f):\n s3.display()\n self.assertEqual(f.getvalue(), \"\\n\\n\\n ###\\n ###\\n ###\\n\")","def handle_output(self, workunit, label, s):\r\n pass","def handle_output(self, workunit, label, s):\r\n pass","def test_get_node_outputs(self):\n pass","def test_container_stops_normally(self, m_sys, m_docker_client):\n\n # attach(..., stream=True) returns a generator.\n def container_output_gen():\n yield (\"Some output\\n\")\n yield (\"from the container.\")\n\n m_docker_client.attach.return_value = container_output_gen()\n m_stdout = Mock(spec=sys.stdout)\n m_sys.stdout = m_stdout\n m_container = Mock()\n _attach_and_stream(m_container)\n\n m_docker_client.attach.assert_called_once_with(m_container,\n stream=True)\n self.assertFalse(m_container.called)\n m_stdout.write.assert_has_calls([call(\"Some output\\n\"),\n call(\"from the container.\")])\n m_docker_client.stop.assert_called_once_with(m_container)","def test_display_method1(self):\n capturedOutput = io.StringIO()\n sys.stdout = capturedOutput\n r1 = Rectangle(4, 6)\n r1.display()\n sys.stdout = sys.__stdout__\n desired = '####\\n####\\n####\\n####\\n####\\n####\\n'\n self.assertEqual(capturedOutput.getvalue(), desired)","def test_stub_example():\n clean_outs()\n\n # Cyclus simulation input for null sink testing\n sim_input = \"./input/stub_example.xml\"\n holdsrtn = [1] # needed because nose does not send() to test generator\n outfile = which_outfile()\n cmd = [\"cyclus\", \"-o\", outfile, \"--input-file\", sim_input]\n yield check_cmd, cmd, os.getcwd(), holdsrtn\n rtn = holdsrtn[0]\n if rtn != 0:\n return # don't execute further commands\n\n legal_paths = [\"/AgentEntry\", \"/Info\"]\n illegal_paths = [\"/Transactions\"] # this must contain tables to test\n # Check if these tables exist\n yield assert_true, tables_exist(outfile, legal_paths)\n if not tables_exist(outfile, legal_paths):\n outfile.close()\n clean_outs()\n return # don't execute further commands\n\n # Get specific data\n if outfile == h5out:\n output = tables.open_file(h5out, mode = \"r\")\n agent_entry = output.get_node(\"/AgentEntry\")[:]\n info = output.get_node(\"/Info\")[:]\n output.close()\n else:\n conn = sqlite3.connect(sqliteout)\n conn.row_factory = sqlite3.Row\n cur = conn.cursor()\n exc = cur.execute\n agent_entry = exc('SELECT * FROM AgentEntry').fetchall()\n info = exc('SELECT * FROM Info').fetchall()\n conn.close()\n \n # Sink's deployment\n agent_ids = to_ary(agent_entry, \"AgentId\")\n spec = to_ary(agent_entry, \"Spec\")\n\n sink_id = find_ids(\"stubs:StubFacility:StubFacility\", spec, agent_ids)\n # Test if one SimpleSink is deployed\n yield assert_equal, len(sink_id), 1\n\n # No resource exchange is expected\n yield assert_false, tables_exist(outfile, illegal_paths)\n\n clean_outs()","def test_policer_handoff_output(self):\n self.policer_handoff_test(Dir.TX)","def test_output_interception(self):\n expected_output = 'testing, 1, 2, 3 ..'\n actual_output = capture(['echo', expected_output])\n assert actual_output.strip() == expected_output.strip()","def mockpipe_fmt(request, testdir):\n mp = testdir.makefile(\"\", pipeline=MOCK_PIPELINE_FMT)\n return mp","def make_block(self, in_size, out_size, **kwargs):\n raise NotImplementedError(\"Abstract\")","def _create_output_test(test_src, tested_function, options=None):\n def do_test_expected(self):\n \"\"\"\n Execute a test by calling a tested_function on test_src data.\n \"\"\"\n self.maxDiff = None\n\n # We currently don't throw any exceptions in Writer, so this\n # this is always false\n if 'error' in test_src:\n self.assertRaises(test_src['error'], yamlish.dumps,\n test_src['in'], options)\n else:\n logging.debug(\"out:\\n%s\", textwrap.dedent(test_src['out']))\n want = yaml.load(textwrap.dedent(test_src['out']))\n logging.debug(\"want:\\n%s\", want)\n with tempfile.NamedTemporaryFile() as test_file:\n tested_function(test_src['in'], test_file)\n test_file.seek(0)\n got_str = test_file.read()\n logging.debug(\"got_str = %s\", got_str)\n got = yaml.load(got_str)\n self.assertEqual(got, want, \"Result matches\")\n\n return do_test_expected","def test_output_vs_expectations(self):\n inventory = Inventory()\n inventory.add_host('superhost', hostvars={'ansible_connection':'local'})\n inventory.add_host('superhost2', hostvars={'ansible_connection':'local'})\n inventory.add_group('awesome')\n inventory.add_group('awesome2')\n inventory.groups['awesome'].add_host(inventory.hosts['superhost'])\n inventory.groups['awesome'].add_host(inventory.hosts['superhost2'])\n output = inventory.write_output_json()\n assert len(output['_meta']['hostvars']) == 2\n output.pop('_meta')\n assert len(output) == 4 #awesome, awesome2, all, ungrouped","def out_test(self, func, arg, expect):\n std_out = StringIO()\n sys.stdout = std_out\n func(arg)\n output = std_out.getvalue()\n self.assertEqual(output, expect + '\\n')\n return output","def test_as_output(self):\n self.assertEqual(render('{% output_as 1 %}-{{ out }}'), '1-')\n self.assertEqual(render('{% output_as 1 as out %}-{{ out }}'),\n 'yes_as-1')","def output(self):\r\n self.logic ( )\r\n return self.output","def test_sysout_capturing(self):\n #self.C.begin()\n self.L.begin()\n output(\"a message\",\"INFO\")\n #self.C.finalize(\"what result\")\n self.L.end()\n eq_(\"GREAP INFO a message\", self.msg)\n eq_(\"GREAP INFO a message\", \"message\")","def to_basic_block(self):\n return _TestA_swig.cleanslate_sptr_to_basic_block(self)","def test_converter_area(self):\n \n input_values = [4,0,1,'20']\n\n output = []\n expected_result = \"Result: 20 Square meter(m^2) equals to 215.29 Square foot(ft^2)\"\n\n def mock_input(s):\n output.append(s)\n return input_values.pop(0)\n\n mp2.input = mock_input\n mp2.print = lambda s:output.append(s)\n mp2.main()\n self.assertEqual(output[-1],expected_result)","def test_output(self):\n new_route = self.route.output(\"test data\", transform=\"transformed\")\n assert new_route != self.route\n assert new_route.route[\"output\"] == \"test data\"\n assert new_route.route[\"transform\"] == \"transformed\"","def testgen(self):\n self.parse()\n self.generate()","def ninja_simulate_block():\n return '''\n```sh\n# In build directory\nninja && ./simulate\n```'''","def render_to_template_mock(*_args):","def test_get_task_output(self):\n pass","def test_get_request_output(self):\n pass","def test_output_one_client(self):\n self.test_case = 'one_client'\n self._run_test_case()","def test_EOF(self):\n _help = 'EOF method to exit cmd program\\n'\n with patch('sys.stdout', new=StringIO()) as f:\n HBNBCommand().onecmd(\"help EOF\")\n self.assertEqual(f.getvalue(), _help)","def test_create():\n\n with tempfile.TemporaryDirectory() as td:\n fp = os.path.join(td, 'outputs.h5')\n\n with Outputs(fp, 'w') as f:\n f.meta = meta\n f.time_index = time_index\n\n with h5py.File(fp, 'r') as f:\n test_meta = pd.DataFrame(f['meta'][...])\n test_ti = f['time_index'][...]\n assert test_meta.shape == (100, 2)\n assert len(test_ti) == 8760\n\n assert f.attrs['package'] == 'reV'\n assert f.attrs['version'] == __version__","def test_invalid_output(self):\n b1 = Block()\n self.configure_block(b1, {})\n b1.notify_signals([Signal()], \"invalid_output\")\n self.assert_num_signals_notified(1, b1, \"invalid_output\")","def test_debug_output(self):\n assert output(self.msg) is not None","def test_x2y2_print(self):\n from io import StringIO\n import io\n import contextlib\n r1 = Square(2, 3, 2, 2)\n temp_stdout = io.StringIO()\n with contextlib.redirect_stdout(temp_stdout):\n r1.display()\n output = temp_stdout.getvalue()\n self.assertEqual(output, '\\n\\n ##\\n ##\\n')","def end_rendering(self, output):\n if self.wrapper_to_generate:\n output = self.div(output, id=self.id, class_='nagare-generated nagare-async-view')\n\n return output","def testShowHistory(self):\n self.maxDiff = None\n de_object = de.DockerExplorerTool()\n de_object._explorer = self.explorer_object\n # We pick one of the container IDs.\n container_id = container.GetAllContainersIDs(self.docker_directory_path)[0]\n with unittest.mock.patch('sys.stdout', new=StringIO()) as fake_output:\n de_object.docker_directory = self.docker_directory_path\n de_object.ShowHistory(container_id)\n expected_string = \"\"\"{\n \"sha256:8ac48589692a53a9b8c2d1ceaa6b402665aa7fe667ba51ccc03002300856d8c7\": {\n \"created_at\": \"2018-04-05T10:41:28.876407+00:00\", \n \"container_cmd\": \"/bin/sh -c #(nop) CMD [\\\\\"sh\\\\\"]\", \n \"size\": 0\n }\n}\n\n\"\"\"\n\n self.assertEqual(expected_string, fake_output.getvalue())","def test_make_writer(self):\n log_func = Mock()\n msg = \"dummy-message\"\n expected = \"-- {}\".format(msg)\n writer = log_lib.make_writer(log_func)\n writer(msg)\n log_func.assert_called_once_with(expected)","def test_format_park_output(self):\n # Setup params and mock result for successfully parking a car\n park_cmd = \"park\"\n success_result, fail_result = 3, -1\n\n # Mock success resp and verify formatting is correct\n success, output = self.controller.format_park_output(success_result)\n self.assertTrue(success)\n self.assertEqual(output, \"Allocated slot number: {}\".format(success_result))\n\n # Mock fail resp and verify formatting is correct\n success, output = self.controller.format_park_output(fail_result)\n self.assertFalse(success)\n self.assertEqual(output, \"Sorry, parking lot is full\")","def _create_block(\n self,\n test_constants: Dict,\n challenge_hash: bytes32,\n height: uint32,\n prev_header_hash: bytes32,\n prev_iters: uint64,\n prev_weight: uint64,\n timestamp: uint64,\n difficulty: uint64,\n ips: uint64,\n seed: bytes,\n ) -> FullBlock:\n prover = None\n plot_pk = None\n plot_sk = None\n qualities: List[bytes] = []\n for pn in range(num_plots):\n # Allow passing in seed, to create reorgs and different chains\n seeded_pn = (pn + 17 * int.from_bytes(seed, \"big\")) % num_plots\n filename = self.filenames[seeded_pn]\n plot_pk = plot_pks[seeded_pn]\n plot_sk = plot_sks[seeded_pn]\n prover = DiskProver(os.path.join(self.plot_dir, filename))\n qualities = prover.get_qualities_for_challenge(challenge_hash)\n if len(qualities) > 0:\n break\n\n assert prover\n assert plot_pk\n assert plot_sk\n if len(qualities) == 0:\n raise NoProofsOfSpaceFound(\"No proofs for this challenge\")\n\n proof_xs: bytes = prover.get_full_proof(challenge_hash, 0)\n proof_of_space: ProofOfSpace = ProofOfSpace(\n challenge_hash, pool_pk, plot_pk, k, [uint8(b) for b in proof_xs]\n )\n number_iters: uint64 = pot_iterations.calculate_iterations(\n proof_of_space, difficulty, ips, test_constants[\"MIN_BLOCK_TIME\"]\n )\n\n disc: int = create_discriminant(\n challenge_hash, test_constants[\"DISCRIMINANT_SIZE_BITS\"]\n )\n start_x: ClassGroup = ClassGroup.from_ab_discriminant(2, 1, disc)\n y_cl, proof_bytes = create_proof_of_time_nwesolowski(\n disc, start_x, number_iters, disc, n_wesolowski\n )\n\n output = ClassgroupElement(y_cl[0], y_cl[1])\n\n proof_of_time = ProofOfTime(\n challenge_hash,\n number_iters,\n output,\n n_wesolowski,\n [uint8(b) for b in proof_bytes],\n )\n\n coinbase: CoinbaseInfo = CoinbaseInfo(\n height,\n block_rewards.calculate_block_reward(uint32(height)),\n coinbase_target,\n )\n coinbase_sig: PrependSignature = pool_sk.sign_prepend(bytes(coinbase))\n fees_target: FeesTarget = FeesTarget(fee_target, uint64(0))\n solutions_generator: bytes32 = sha256(seed).digest()\n cost = uint64(0)\n body: Body = Body(\n coinbase, coinbase_sig, fees_target, None, solutions_generator, cost\n )\n\n header_data: HeaderData = HeaderData(\n prev_header_hash,\n timestamp,\n bytes([0] * 32),\n proof_of_space.get_hash(),\n body.get_hash(),\n bytes([0] * 32),\n )\n\n header_hash_sig: PrependSignature = plot_sk.sign_prepend(header_data.get_hash())\n\n header: Header = Header(header_data, header_hash_sig)\n\n challenge = Challenge(\n challenge_hash,\n proof_of_space.get_hash(),\n proof_of_time.get_hash(),\n height,\n uint64(prev_weight + difficulty),\n uint64(prev_iters + number_iters),\n )\n header_block = HeaderBlock(proof_of_space, proof_of_time, challenge, header)\n\n full_block: FullBlock = FullBlock(header_block, body)\n\n return full_block","def test_gethtml(self):\r\n mock_module = CHModuleFactory.create()\r\n\r\n def fake_get_display_items():\r\n \"\"\"\r\n A mock of get_display_items\r\n \"\"\"\r\n return [FakeChild()]\r\n mock_module.get_display_items = fake_get_display_items\r\n out_html = mock_module.render('student_view').content\r\n self.assertTrue('This is supposed to be test html.' in out_html)\r\n self.assertTrue('i4x://this/is/a/fake/id' in out_html)","def bos_fixture():\n block_config = {\n \"Clock\": {\"start_time\": 0,\n \"end_time\": 10,\n \"num_steps\": 100},\n \"PhysicsModules\": {\n \"BlockOnSpring\": {\n \"mass\": 1,\n \"spring_constant\": 1,\n \"pusher\": \"Leapfrog\",\n \"x0\": [0, 1, 0],\n }\n },\n \"Tools\": {\n \"Leapfrog\": {},\n \"ForwardEuler\": {},\n \"BackwardEuler\": {}\n },\n \"Diagnostics\": {\n # default values come first\n \"directory\": \"test_output/\",\n \"output_type\": \"csv\",\n \"clock\": {\"filename\": \"time.csv\"},\n \"BlockDiagnostic\": [\n {'component': 'momentum', 'filename': 'block_p.csv'},\n {'component': 'position', 'filename': 'block_x.csv'}\n ]\n }\n }\n\n return block_config","def test_custom_local_output_file() -> None:\n with tempfile.TemporaryDirectory() as tmpdirname:\n file_location = os.path.join(tmpdirname, \"foo.txt\")\n\n # Instantiate the output file\n absolute_file_location = os.path.abspath(file_location)\n output_file = PyArrowFileIO().new_output(location=f\"{absolute_file_location}\")\n\n # Create the output file and write to it\n f = output_file.create()\n f.write(b\"foo\")\n\n # Confirm that bytes were written\n with open(file_location, \"rb\") as f:\n assert f.read() == b\"foo\"\n\n assert len(output_file) == 3","def dummy_code_block() -> CodeBlock:\n return make_dummy_code_block()","def with_output(self, output, output_format):\n\t\tself.variables['output'] = output\n\t\tself.variables['output_format'] = output_format\n\t\treturn self","def captured_output(stream_name):\n import StringIO\n orig_stdout = getattr(sys, stream_name)\n setattr(sys, stream_name, StringIO.StringIO())\n yield getattr(sys, stream_name)\n setattr(sys, stream_name, orig_stdout)","def test_format_leave_output(self):\n # Setup params and mock result for car successfully leave parking lot\n leave_cmd = \"leave\"\n slot_id = 1\n\n # Mock success resp and verify\n success, output = self.controller.format_leave_output(slot_id)\n self.assertTrue(success)\n self.assertEqual(output, \"Slot number {} is free\".format(slot_id))","def testProcess(self, mock_get_write_results):\n self.mock_grr_api.Hunt.return_value.Get.return_value = \\\n mock_grr_hosts.MOCK_HUNT\n self.grr_hunt_downloader.Process()\n mock_get_write_results.assert_called_with(mock_grr_hosts.MOCK_HUNT,\n '/tmp/test')","def writeOutput(self, output):","def test_dumps(\n mock_hvac_client_read, mock_dumps, localhost_client, gen_input_config, gen_processed_config, gen_vault_response_kv1\n):\n mock_hvac_client_read.return_value = gen_vault_response_kv1(pwd_key=\"password\")\n\n input_config = gen_input_config()\n input_config[\"vault_secrets\"][\"acme.pwd\"] = \"secret/acme/server/user.password\"\n\n localhost_client.dumps(input_config)\n\n mock_hvac_client_read.assert_called_with(gen_input_config()[\"vault_secrets\"][\"acme.user\"])\n mock_dumps.assert_called_with(gen_processed_config())","def side_effect_create_mock_tool(tool_path):\n\n def _side_effect(*args, **kwargs):\n tool_path.parent.mkdir(parents=True)\n with tool_path.open(\"w\") as f:\n f.write(\"I am a complete tool\")\n return \"new-downloaded-file\"\n\n return _side_effect","def test_help(self):\n _help = \"*** No help on hello\\n\"\n with patch('sys.stdout', new=StringIO()) as f:\n HBNBCommand().onecmd(\"help hello\")\n self.assertEqual(f.getvalue(), _help)","def test_main_output(self, capsys):\n args = self.args.copy()\n args[\"out_file\"] = \"text.txt\"\n UI.main(**args)\n captured = capsys.readouterr().out\n assert \"Results written to text.txt\" in captured","def expect_output(self, file, parse_json=False):\n contents = self._data_file(file)\n patcher = mock.patch('sys.stdout', new_callable=StringIO)\n output = patcher.start()\n yield\n patcher.stop()\n if parse_json:\n self.assertEqual(json.loads(output.getvalue()),\n json.loads(contents))\n else:\n self.assertEqual(output.getvalue().split('\\n'), contents.split('\\n'))","def parsed_output(output_elements):\n parsed_output = {}\n for stanza, stanza_value in output_elements.items():\n fake_section = MagicMock()\n fake_section.options = {}\n fake_section.name = stanza\n parsed_output.update({stanza: fake_section})\n for option, value in stanza_value.items():\n fake_setting = MagicMock()\n fake_setting.name = option\n fake_setting.value = value\n parsed_output[stanza].options.update({option: fake_setting})\n return parsed_output"],"string":"[\n \"def fixture_input_block():\\n return Mock()\",\n \"def test_03_out(self, mock_stdout):\\n msg = udocker.Msg(udocker.Msg.MSG)\\n msg.out(\\\"111\\\", \\\"222\\\", \\\"333\\\", 444, ('555'))\\n self.assertEqual(\\\"111 222 333 444 555\\\\n\\\", mock_stdout.getvalue())\\n sys.stdout = STDOUT\\n sys.stderr = STDERR\",\n \"def test_block_default_output(self):\\n\\n @output('out1', default=True)\\n @output('out2')\\n class MyBlock(Block):\\n pass\\n\\n blk = MyBlock()\\n self.configure_block(blk, {})\\n sig1, sig2, sig3 = (\\n Signal({'sig': 1}),\\n Signal({'sig': 2}),\\n Signal({'sig': 3}),\\n )\\n blk.notify_signals([sig1], 'out1')\\n self.assert_last_signal_notified(sig1, 'out1')\\n blk.notify_signals([sig2], 'out2')\\n self.assert_last_signal_notified(sig2, 'out2')\\n # Notify the last signal without any output ID, make sure the actual\\n # default terminal of the block is used\\n blk.notify_signals([sig3])\\n self.assert_last_signal_notified(sig3, 'out1')\",\n \"def setUp(self):\\n self._output = io.StringIO()\",\n \"def _generate_output(self):\\n raise NotImplementedError()\",\n \"def __init__(self, output_mediator_object):\\n super(TestOutputModule, self).__init__(output_mediator_object)\\n self.events = []\\n self.macb_groups = []\",\n \"def _populate_output(self):\\n pass\",\n \"def setUp(self):\\n\\t\\tself.output = self.switchstdout()\",\n \"def mock_output(self, command, _rc, output, _err):\\n\\n self.mocks[command] = (_rc, output, _err)\",\n \"def simulate_block():\\n return '''\\n```sh\\n# In build directory\\n./simulate\\n```'''\",\n \"def test_export_custom(self): # pylint: disable=no-self-use\\n mock_record_str = Mock(str)\\n\\n def formatter(record): # pylint: disable=unused-argument\\n return mock_record_str\\n\\n mock_stdout = Mock()\\n exporter = ConsoleLogExporter(out=mock_stdout, formatter=formatter)\\n log_data = LogData(\\n log_record=LogRecord(),\\n instrumentation_scope=InstrumentationScope(\\n \\\"first_name\\\", \\\"first_version\\\"\\n ),\\n )\\n exporter.export([log_data])\\n mock_stdout.write.assert_called_once_with(mock_record_str)\",\n \"def test_create(self):\\n _help = \\\"[Usage: create <class name>]\\\\n\\\"\\n with patch('sys.stdout', new=StringIO()) as f:\\n HBNBCommand().onecmd(\\\"help create\\\")\\n self.assertEqual(f.getvalue(), _help)\",\n \"def test_dump(\\n mock_hvac_client_read, mock_dump, localhost_client, gen_input_config, gen_processed_config, gen_vault_response_kv1\\n):\\n mock_hvac_client_read.return_value = gen_vault_response_kv1()\\n\\n localhost_client.dump(gen_input_config(), \\\"out.json\\\")\\n\\n mock_hvac_client_read.assert_called_with(gen_input_config()[\\\"vault_secrets\\\"][\\\"acme.user\\\"])\\n mock_dump.assert_called_with(gen_processed_config(), \\\"out.json\\\")\",\n \"def create_outputs(block):\\n return [nbbase.NotebookNode(output)\\n for output in json.loads(block['content'])]\",\n \"def test(self, parent, block):\\r\\n pass\",\n \"def test_default_output(self):\\n env = pike.Environment()\\n output = pike.Graph('output')\\n output.sink = pike.noop()\\n with patch.object(output, 'run') as run:\\n run.return_value = []\\n env.set_default_output(output)\\n with pike.Graph('g') as graph:\\n pike.glob('.', '*')\\n env.add(graph)\\n env.run_all()\\n run.assert_called_with([])\",\n \"def test_exit_on_output_cb_error(output_block, kwargs):\\n output_block.side_effect = Exception()\\n with pytest.raises(SystemExit) as exc_info:\\n create_flow(**kwargs)\\n assert exc_info.value.code == 1\",\n \"def test_create_stream_handler(self, mock_handler: MagicMock):\\n\\n instance = mock_handler.return_value\\n instance.setFormatter = MagicMock()\\n instance.setLevel = MagicMock()\\n\\n handler = create_stream_handler(self.level, self.format)\\n\\n mock_handler.assert_called_with(stdout)\\n instance.setFormatter.assert_called_with(self.format)\\n instance.setLevel.assert_called_with(self.level)\\n\\n self.assertIsNotNone(handler)\",\n \"def __init__(self):\\n super(MockOutputModule, self).__init__()\\n self.hostname = None\\n self.port = None\",\n \"def setUp(self):\\n super(BlockBookingsReportTests, self).setUp()\\n self.user1 = baker.make_recipe('booking.user')\\n self.user2 = baker.make_recipe('booking.user')\\n\\n self.event_type = baker.make_recipe('booking.event_type_PC')\\n\\n self.user1_active_block = baker.make_recipe(\\n 'booking.block_5', user=self.user1,\\n start_date=timezone.now() - timedelta(10),\\n block_type__event_type=self.event_type,\\n paid=True\\n )\\n self.user2_active_block = baker.make_recipe(\\n 'booking.block_5', user=self.user2,\\n start_date=timezone.now() - timedelta(10),\\n block_type__event_type=self.event_type, paid=True\\n )\\n\\n user1_bookings_on_block = baker.make_recipe(\\n 'booking.booking',\\n user=self.user1,\\n event__event_type=self.event_type,\\n block=self.user1_active_block,\\n date_booked=timezone.now() - timedelta(8),\\n _quantity=2\\n )\\n self.user1_booking_not_on_block = baker.make_recipe(\\n 'booking.booking',\\n user=self.user1,\\n event__event_type=self.event_type,\\n date_booked=timezone.now() - timedelta(8)\\n )\\n user1_booking_old = baker.make_recipe(\\n 'booking.booking',\\n user=self.user1,\\n event__event_type=self.event_type,\\n date_booked=timezone.now() - timedelta(12)\\n )\\n user1_booking_free = baker.make_recipe(\\n 'booking.booking',\\n user=self.user1,\\n event__event_type=self.event_type,\\n free_class=True,\\n date_booked=timezone.now() - timedelta(8)\\n )\\n\\n # redirect stdout so we can test it\\n self.output = StringIO()\\n self.saved_stdout = sys.stdout\\n sys.stdout = self.output\",\n \"def write_output(self):\",\n \"def create_output(self, messages):\",\n \"def testNewOutputModule(self):\\n manager.OutputManager.RegisterOutput(TestOutput)\\n\\n output_module = manager.OutputManager.NewOutputModule('test_output')\\n self.assertIsInstance(output_module, TestOutput)\\n\\n with self.assertRaises(ValueError):\\n manager.OutputManager.NewOutputModule(1)\\n\\n with self.assertRaises(KeyError):\\n manager.OutputManager.NewOutputModule('bogus')\\n\\n manager.OutputManager.DeregisterOutput(TestOutput)\",\n \"def generateStandardMock(monkeypatch, return_value_output, return_value_error, return_code, type=\\\"gpt\\\"):\\n mock_popen = mock.MagicMock()\\n mock_popen.communicate.return_value = (return_value_output, return_value_error)\\n mock_popen.returncode = return_code\\n def popen_constructor(*args, **kargs):\\n return mock_popen\\n def mock_table_type(*args, **kargs):\\n return type\\n monkeypatch.setattr(\\\"subprocess.Popen\\\", popen_constructor)\\n if type != None:\\n monkeypatch.setattr(\\\"weresync.device.DeviceManager.get_partition_table_type\\\", mock_table_type)\",\n \"def GetTestWrapper(self):\\n return ''\",\n \"def test_updated_display1(self):\\n capturedOutput = io.StringIO()\\n sys.stdout = capturedOutput\\n r1 = Rectangle(2, 3, 2, 2)\\n r1.display()\\n sys.stdout = sys.__stdout__\\n desired = '\\\\n\\\\n ##\\\\n ##\\\\n ##\\\\n'\\n self.assertEqual(capturedOutput.getvalue(), desired)\",\n \"def setUp(self):\\n self.actualstdout = sys.stdout\\n sys.stdout = StringIO.StringIO()\",\n \"def test_generateconfig(self):\\n args = mock.Mock()\\n args.debug = None\\n args.generateconfig = True\\n args.config = None\\n expected_text = ('Sample configuration file written to sample_config.json\\\\n'\\n \\\"Replicate the site JSON for each site.\\\\n\\\"\\n \\\" Valid values for use_https and local are 'True' and 'False'\\\\n\\\"\\n \\\" One site must have local set to 'True'\\\\n\\\"\\n 'Replicate the export JSON for each exported contract.\\\\n')\\n with mock.patch('sys.stdout', new=StringIO()) as fake_out:\\n execute_tool(args)\\n self.assertEqual(fake_out.getvalue(), expected_text)\",\n \"def test_format_start_new_output(self):\\n # Setup params and mock result of parking lot execution\\n start_new_cmd = \\\"create_parking_lot\\\"\\n result = 5\\n\\n # Verify formatting is correct\\n success, output = self.controller.format_start_new_output(result)\\n self.assertTrue(success)\\n self.assertEqual(output, \\\"Created a parking lot with {} slots\\\".format(result))\",\n \"def test_html_output(self):\\n pass\",\n \"def test_filter(self, logger: Logger, mocker: MockerFixture) -> None:\\n task = OctaveTask()\\n task.session_id = \\\"123\\\"\\n handler = OutputHandler(task)\\n logger.addHandler(handler)\\n\\n send_func = mocker.patch(\\\"matl_online.tasks.OutputHandler.send\\\")\\n\\n logger.warning(\\\"warning\\\")\\n logger.error(\\\"error\\\")\\n logger.debug(\\\"debug\\\")\\n\\n assert len(handler.contents) == 0\\n send_func.assert_not_called()\",\n \"def writer_wrapper_2(coroutine):\\n yield from coroutine\",\n \"def output_verilog_testbench(file, simulation_trace=None, block=None):\\n\\n block = working_block(block)\\n inputs = block.wirevector_subset(Input)\\n outputs = block.wirevector_subset(Output)\\n\\n # Output header\\n print('module tb();', file=file)\\n\\n # Declare all block inputs as reg\\n print(' reg clk;', file=file)\\n for w in inputs:\\n print(' reg {:s} {:s};'.format(_verilog_vector_decl(w), w.name), file=file)\\n\\n # Declare all block outputs as wires\\n for w in outputs:\\n print(' wire {:s} {:s};'.format(_verilog_vector_decl(w), w.name), file=file)\\n print('', file=file)\\n\\n # Instantiate logic block\\n io_list = [w.name for w in block.wirevector_subset((Input, Output))]\\n io_list.append('clk')\\n io_list_str = ['.{0:s}({0:s})'.format(w) for w in io_list]\\n print(' toplevel block({:s});\\\\n'.format(', '.join(io_list_str)), file=file)\\n\\n # Generate clock signal\\n print(' always', file=file)\\n print(' #0.5 clk = ~clk;\\\\n', file=file)\\n\\n # Move through all steps of trace, writing out input assignments per cycle\\n print(' initial begin', file=file)\\n print(' $dumpfile (\\\"waveform.vcd\\\");', file=file)\\n print(' $dumpvars;\\\\n', file=file)\\n print(' clk = 0;', file=file)\\n\\n for i in range(len(simulation_trace)):\\n for w in inputs:\\n print(' {:s} = {:s}{:d};'.format(\\n w.name,\\n \\\"{:d}'d\\\".format(len(w)),\\n simulation_trace.trace[w][i]), file=file)\\n print('\\\\n #2', file=file)\\n\\n # Footer\\n print(' $finish;', file=file)\\n print(' end', file=file)\\n print('endmodule', file=file)\",\n \"def test_addOutput(self):\\n print(\\\"\\\\nTest 2: Adding OutputNode\\\")\\n builder = StaticBuilder()\\n builder.addInput(10, name=\\\"In\\\")\\n builder.addInner(3, name=\\\"Det\\\")\\n o_name = builder.addOutput(name=\\\"Out\\\")\\n \\n o1 = builder.nodes[o_name]\\n print(\\\"\\\\nNode keys in builder:\\\", list(builder.nodes.keys()))\\n print(\\\"This node's key:\\\", o_name)\\n self.assertEqual(o1.label, 2, \\\"The label has not been assigned correctly\\\")\\n self.assertEqual(builder.num_nodes, 3, \\\"The number of nodes has not been \\\"\\n \\\"assigned correctly\\\")\\n self.assertEqual(o1.num_declared_outputs, 0, \\\"The number of outputs of the \\\"\\n \\\"OutputNode has not been assigned correctly\\\")\\n self.assertEqual(o1.num_declared_inputs, 0, \\\"The number of inputs of the \\\"\\n \\\"OutputNode has not been assigned correctly\\\")\",\n \"def test_display_method2(self):\\n capturedOutput = io.StringIO()\\n sys.stdout = capturedOutput\\n r2 = Rectangle(2, 2)\\n r2.display()\\n sys.stdout = sys.__stdout__\\n desired = '##\\\\n##\\\\n'\\n self.assertEqual(capturedOutput.getvalue(), desired)\",\n \"def test_display__method2(self):\\n Rectangle.reset_objects()\\n s2 = Square(2, 2)\\n f = io.StringIO()\\n with contextlib.redirect_stdout(f):\\n s2.display()\\n self.assertEqual(f.getvalue(), \\\" ##\\\\n ##\\\\n\\\")\",\n \"def run_output(mocker):\\n return mocker.patch('d.subprocess.check_output')\",\n \"def test_display__method(self):\\n Rectangle.reset_objects()\\n s1 = Square(5)\\n f = io.StringIO()\\n with contextlib.redirect_stdout(f):\\n s1.display()\\n self.assertEqual(f.getvalue(), \\\"#####\\\\n#####\\\\n#####\\\\n#####\\\\n#####\\\\n\\\")\",\n \"def mock_result_stream():\\n response_file_path = os.path.join(import_module(__name__).__path__[0], \\n \\\"splunk_job_result_stream_sample.xml\\\")\\n with open(response_file_path, 'r') as response_file:\\n response = StringIO(response_file.read())\\n alsoProvides(response, ISplunkResultsStream)\\n return response\",\n \"def __init__(self, output_mediator):\\n event_formatting_helper = shared_json.JSONEventFormattingHelper(\\n output_mediator)\\n super(JSONLineOutputModule, self).__init__(\\n output_mediator, event_formatting_helper)\",\n \"def test_updated_display3(self):\\n capturedOutput = io.StringIO()\\n sys.stdout = capturedOutput\\n r3 = Rectangle(3, 2, 0, 1)\\n r3.display()\\n sys.stdout = sys.__stdout__\\n desired = '\\\\n###\\\\n###\\\\n'\\n self.assertEqual(capturedOutput.getvalue(), desired)\",\n \"def _CreateOutputMediator(self, config=None, storage_object=None):\\n formatter_mediator = formatters_mediator.FormatterMediator()\\n return mediator.OutputMediator(\\n formatter_mediator, storage_object, config=config)\",\n \"def write_output_inline(self, index, content):\\n self.expected_output_mask.add(index)\\n ref = self.block_store.ref_from_string(content, self.task_descriptor['expected_outputs'][index])\\n self.task_record.publish_ref(ref)\\n return ref\",\n \"def test_updated_display2(self):\\n capturedOutput = io.StringIO()\\n sys.stdout = capturedOutput\\n r2 = Rectangle(3, 2, 1, 0)\\n r2.display()\\n sys.stdout = sys.__stdout__\\n desired = ' ###\\\\n ###\\\\n'\\n self.assertEqual(capturedOutput.getvalue(), desired)\",\n \"def setUp(self):\\n self.output = StringIO.StringIO()\\n self.formatter = json_out.Json(None, self.output)\\n self.event_object = JsonTestEvent()\",\n \"def testNoOutput(self):\\n output_mediator = self._CreateOutputMediator()\\n output_writer = cli_test_lib.TestOutputWriter()\\n output_module = null.NullOutputModule(output_mediator)\\n\\n output_module.WriteHeader()\\n\\n event, event_data, event_data_stream = (\\n containers_test_lib.CreateEventFromValues(self._TEST_EVENTS[0]))\\n output_module.WriteEventBody(\\n event, event_data, event_data_stream, None)\\n\\n output_module.WriteFooter()\\n\\n output = output_writer.ReadOutput()\\n self.assertEqual('', output)\",\n \"def test_wrapper_output(self):\\r\\n tmpdir = None\\r\\n try:\\r\\n tmpdir = tempfile.mkdtemp()\\r\\n result = mib2pysnmp('conpot/tests/data/VOGON-POEM-MIB.mib')\\r\\n\\r\\n with open(os.path.join(tmpdir, 'VOGON-POEM-MIB' + '.py'), 'w') as output_file:\\r\\n output_file.write(result)\\r\\n\\r\\n cmd_responder = command_responder.CommandResponder('', 0, [tmpdir])\\r\\n cmd_responder.snmpEngine.msgAndPduDsp.mibInstrumController.mibBuilder.loadModules('VOGON-POEM-MIB')\\r\\n result = cmd_responder._get_mibSymbol('VOGON-POEM-MIB', 'poemNumber')\\r\\n\\r\\n self.assertIsNotNone(result, 'The expected MIB (VOGON-POEM-MIB) could not be loaded.')\\r\\n finally:\\r\\n shutil.rmtree(tmpdir)\",\n \"def test_generate_secret_file(self, mock_context, mock_create_aws, mock_file_open, mock_json, mock_dump):\\n context = ef_password.EFPWContext()\\n context.env, context.service = self.env, self.service\\n context.secret_file = self.secret_file\\n context.match = 'password'\\n mock_context.return_value = context\\n mock_create_aws.return_value = {\\\"kms\\\": self.mock_kms}\\n mock_json.return_value = {\\\"params\\\": {\\\"test\\\": {\\\"password\\\": \\\"mock_secret1\\\"}}}\\n ef_password.main()\\n self.mock_kms.decrypt.assert_not_called()\\n self.mock_kms.encrypt.assert_called_once_with(\\n KeyId='alias/{}-{}'.format(self.env, self.service),\\n Plaintext=\\\"mock_secret1\\\".encode()\\n )\\n mock_file_open.assert_called_with(self.secret_file, 'w')\\n handle = mock_file_open()\\n mock_dump.assert_called_once_with({'params': {'test': {'password': '{{aws:kms:decrypt,Y2lwaGVyX2Jsb2I=}}'}}},\\n handle, indent=2, separators=(',', ': '))\\n handle.write.assert_called_with('\\\\n')\",\n \"def test_updated_display4(self):\\n capturedOutput = io.StringIO()\\n sys.stdout = capturedOutput\\n r4 = Rectangle(3, 2, 0, 0)\\n r4.display()\\n sys.stdout = sys.__stdout__\\n desired = '###\\\\n###\\\\n'\\n self.assertEqual(capturedOutput.getvalue(), desired)\",\n \"def test_display__method3(self):\\n Rectangle.reset_objects()\\n s3 = Square(3, 1, 3)\\n f = io.StringIO()\\n with contextlib.redirect_stdout(f):\\n s3.display()\\n self.assertEqual(f.getvalue(), \\\"\\\\n\\\\n\\\\n ###\\\\n ###\\\\n ###\\\\n\\\")\",\n \"def handle_output(self, workunit, label, s):\\r\\n pass\",\n \"def handle_output(self, workunit, label, s):\\r\\n pass\",\n \"def test_get_node_outputs(self):\\n pass\",\n \"def test_container_stops_normally(self, m_sys, m_docker_client):\\n\\n # attach(..., stream=True) returns a generator.\\n def container_output_gen():\\n yield (\\\"Some output\\\\n\\\")\\n yield (\\\"from the container.\\\")\\n\\n m_docker_client.attach.return_value = container_output_gen()\\n m_stdout = Mock(spec=sys.stdout)\\n m_sys.stdout = m_stdout\\n m_container = Mock()\\n _attach_and_stream(m_container)\\n\\n m_docker_client.attach.assert_called_once_with(m_container,\\n stream=True)\\n self.assertFalse(m_container.called)\\n m_stdout.write.assert_has_calls([call(\\\"Some output\\\\n\\\"),\\n call(\\\"from the container.\\\")])\\n m_docker_client.stop.assert_called_once_with(m_container)\",\n \"def test_display_method1(self):\\n capturedOutput = io.StringIO()\\n sys.stdout = capturedOutput\\n r1 = Rectangle(4, 6)\\n r1.display()\\n sys.stdout = sys.__stdout__\\n desired = '####\\\\n####\\\\n####\\\\n####\\\\n####\\\\n####\\\\n'\\n self.assertEqual(capturedOutput.getvalue(), desired)\",\n \"def test_stub_example():\\n clean_outs()\\n\\n # Cyclus simulation input for null sink testing\\n sim_input = \\\"./input/stub_example.xml\\\"\\n holdsrtn = [1] # needed because nose does not send() to test generator\\n outfile = which_outfile()\\n cmd = [\\\"cyclus\\\", \\\"-o\\\", outfile, \\\"--input-file\\\", sim_input]\\n yield check_cmd, cmd, os.getcwd(), holdsrtn\\n rtn = holdsrtn[0]\\n if rtn != 0:\\n return # don't execute further commands\\n\\n legal_paths = [\\\"/AgentEntry\\\", \\\"/Info\\\"]\\n illegal_paths = [\\\"/Transactions\\\"] # this must contain tables to test\\n # Check if these tables exist\\n yield assert_true, tables_exist(outfile, legal_paths)\\n if not tables_exist(outfile, legal_paths):\\n outfile.close()\\n clean_outs()\\n return # don't execute further commands\\n\\n # Get specific data\\n if outfile == h5out:\\n output = tables.open_file(h5out, mode = \\\"r\\\")\\n agent_entry = output.get_node(\\\"/AgentEntry\\\")[:]\\n info = output.get_node(\\\"/Info\\\")[:]\\n output.close()\\n else:\\n conn = sqlite3.connect(sqliteout)\\n conn.row_factory = sqlite3.Row\\n cur = conn.cursor()\\n exc = cur.execute\\n agent_entry = exc('SELECT * FROM AgentEntry').fetchall()\\n info = exc('SELECT * FROM Info').fetchall()\\n conn.close()\\n \\n # Sink's deployment\\n agent_ids = to_ary(agent_entry, \\\"AgentId\\\")\\n spec = to_ary(agent_entry, \\\"Spec\\\")\\n\\n sink_id = find_ids(\\\"stubs:StubFacility:StubFacility\\\", spec, agent_ids)\\n # Test if one SimpleSink is deployed\\n yield assert_equal, len(sink_id), 1\\n\\n # No resource exchange is expected\\n yield assert_false, tables_exist(outfile, illegal_paths)\\n\\n clean_outs()\",\n \"def test_policer_handoff_output(self):\\n self.policer_handoff_test(Dir.TX)\",\n \"def test_output_interception(self):\\n expected_output = 'testing, 1, 2, 3 ..'\\n actual_output = capture(['echo', expected_output])\\n assert actual_output.strip() == expected_output.strip()\",\n \"def mockpipe_fmt(request, testdir):\\n mp = testdir.makefile(\\\"\\\", pipeline=MOCK_PIPELINE_FMT)\\n return mp\",\n \"def make_block(self, in_size, out_size, **kwargs):\\n raise NotImplementedError(\\\"Abstract\\\")\",\n \"def _create_output_test(test_src, tested_function, options=None):\\n def do_test_expected(self):\\n \\\"\\\"\\\"\\n Execute a test by calling a tested_function on test_src data.\\n \\\"\\\"\\\"\\n self.maxDiff = None\\n\\n # We currently don't throw any exceptions in Writer, so this\\n # this is always false\\n if 'error' in test_src:\\n self.assertRaises(test_src['error'], yamlish.dumps,\\n test_src['in'], options)\\n else:\\n logging.debug(\\\"out:\\\\n%s\\\", textwrap.dedent(test_src['out']))\\n want = yaml.load(textwrap.dedent(test_src['out']))\\n logging.debug(\\\"want:\\\\n%s\\\", want)\\n with tempfile.NamedTemporaryFile() as test_file:\\n tested_function(test_src['in'], test_file)\\n test_file.seek(0)\\n got_str = test_file.read()\\n logging.debug(\\\"got_str = %s\\\", got_str)\\n got = yaml.load(got_str)\\n self.assertEqual(got, want, \\\"Result matches\\\")\\n\\n return do_test_expected\",\n \"def test_output_vs_expectations(self):\\n inventory = Inventory()\\n inventory.add_host('superhost', hostvars={'ansible_connection':'local'})\\n inventory.add_host('superhost2', hostvars={'ansible_connection':'local'})\\n inventory.add_group('awesome')\\n inventory.add_group('awesome2')\\n inventory.groups['awesome'].add_host(inventory.hosts['superhost'])\\n inventory.groups['awesome'].add_host(inventory.hosts['superhost2'])\\n output = inventory.write_output_json()\\n assert len(output['_meta']['hostvars']) == 2\\n output.pop('_meta')\\n assert len(output) == 4 #awesome, awesome2, all, ungrouped\",\n \"def out_test(self, func, arg, expect):\\n std_out = StringIO()\\n sys.stdout = std_out\\n func(arg)\\n output = std_out.getvalue()\\n self.assertEqual(output, expect + '\\\\n')\\n return output\",\n \"def test_as_output(self):\\n self.assertEqual(render('{% output_as 1 %}-{{ out }}'), '1-')\\n self.assertEqual(render('{% output_as 1 as out %}-{{ out }}'),\\n 'yes_as-1')\",\n \"def output(self):\\r\\n self.logic ( )\\r\\n return self.output\",\n \"def test_sysout_capturing(self):\\n #self.C.begin()\\n self.L.begin()\\n output(\\\"a message\\\",\\\"INFO\\\")\\n #self.C.finalize(\\\"what result\\\")\\n self.L.end()\\n eq_(\\\"GREAP INFO a message\\\", self.msg)\\n eq_(\\\"GREAP INFO a message\\\", \\\"message\\\")\",\n \"def to_basic_block(self):\\n return _TestA_swig.cleanslate_sptr_to_basic_block(self)\",\n \"def test_converter_area(self):\\n \\n input_values = [4,0,1,'20']\\n\\n output = []\\n expected_result = \\\"Result: 20 Square meter(m^2) equals to 215.29 Square foot(ft^2)\\\"\\n\\n def mock_input(s):\\n output.append(s)\\n return input_values.pop(0)\\n\\n mp2.input = mock_input\\n mp2.print = lambda s:output.append(s)\\n mp2.main()\\n self.assertEqual(output[-1],expected_result)\",\n \"def test_output(self):\\n new_route = self.route.output(\\\"test data\\\", transform=\\\"transformed\\\")\\n assert new_route != self.route\\n assert new_route.route[\\\"output\\\"] == \\\"test data\\\"\\n assert new_route.route[\\\"transform\\\"] == \\\"transformed\\\"\",\n \"def testgen(self):\\n self.parse()\\n self.generate()\",\n \"def ninja_simulate_block():\\n return '''\\n```sh\\n# In build directory\\nninja && ./simulate\\n```'''\",\n \"def render_to_template_mock(*_args):\",\n \"def test_get_task_output(self):\\n pass\",\n \"def test_get_request_output(self):\\n pass\",\n \"def test_output_one_client(self):\\n self.test_case = 'one_client'\\n self._run_test_case()\",\n \"def test_EOF(self):\\n _help = 'EOF method to exit cmd program\\\\n'\\n with patch('sys.stdout', new=StringIO()) as f:\\n HBNBCommand().onecmd(\\\"help EOF\\\")\\n self.assertEqual(f.getvalue(), _help)\",\n \"def test_create():\\n\\n with tempfile.TemporaryDirectory() as td:\\n fp = os.path.join(td, 'outputs.h5')\\n\\n with Outputs(fp, 'w') as f:\\n f.meta = meta\\n f.time_index = time_index\\n\\n with h5py.File(fp, 'r') as f:\\n test_meta = pd.DataFrame(f['meta'][...])\\n test_ti = f['time_index'][...]\\n assert test_meta.shape == (100, 2)\\n assert len(test_ti) == 8760\\n\\n assert f.attrs['package'] == 'reV'\\n assert f.attrs['version'] == __version__\",\n \"def test_invalid_output(self):\\n b1 = Block()\\n self.configure_block(b1, {})\\n b1.notify_signals([Signal()], \\\"invalid_output\\\")\\n self.assert_num_signals_notified(1, b1, \\\"invalid_output\\\")\",\n \"def test_debug_output(self):\\n assert output(self.msg) is not None\",\n \"def test_x2y2_print(self):\\n from io import StringIO\\n import io\\n import contextlib\\n r1 = Square(2, 3, 2, 2)\\n temp_stdout = io.StringIO()\\n with contextlib.redirect_stdout(temp_stdout):\\n r1.display()\\n output = temp_stdout.getvalue()\\n self.assertEqual(output, '\\\\n\\\\n ##\\\\n ##\\\\n')\",\n \"def end_rendering(self, output):\\n if self.wrapper_to_generate:\\n output = self.div(output, id=self.id, class_='nagare-generated nagare-async-view')\\n\\n return output\",\n \"def testShowHistory(self):\\n self.maxDiff = None\\n de_object = de.DockerExplorerTool()\\n de_object._explorer = self.explorer_object\\n # We pick one of the container IDs.\\n container_id = container.GetAllContainersIDs(self.docker_directory_path)[0]\\n with unittest.mock.patch('sys.stdout', new=StringIO()) as fake_output:\\n de_object.docker_directory = self.docker_directory_path\\n de_object.ShowHistory(container_id)\\n expected_string = \\\"\\\"\\\"{\\n \\\"sha256:8ac48589692a53a9b8c2d1ceaa6b402665aa7fe667ba51ccc03002300856d8c7\\\": {\\n \\\"created_at\\\": \\\"2018-04-05T10:41:28.876407+00:00\\\", \\n \\\"container_cmd\\\": \\\"/bin/sh -c #(nop) CMD [\\\\\\\\\\\"sh\\\\\\\\\\\"]\\\", \\n \\\"size\\\": 0\\n }\\n}\\n\\n\\\"\\\"\\\"\\n\\n self.assertEqual(expected_string, fake_output.getvalue())\",\n \"def test_make_writer(self):\\n log_func = Mock()\\n msg = \\\"dummy-message\\\"\\n expected = \\\"-- {}\\\".format(msg)\\n writer = log_lib.make_writer(log_func)\\n writer(msg)\\n log_func.assert_called_once_with(expected)\",\n \"def test_format_park_output(self):\\n # Setup params and mock result for successfully parking a car\\n park_cmd = \\\"park\\\"\\n success_result, fail_result = 3, -1\\n\\n # Mock success resp and verify formatting is correct\\n success, output = self.controller.format_park_output(success_result)\\n self.assertTrue(success)\\n self.assertEqual(output, \\\"Allocated slot number: {}\\\".format(success_result))\\n\\n # Mock fail resp and verify formatting is correct\\n success, output = self.controller.format_park_output(fail_result)\\n self.assertFalse(success)\\n self.assertEqual(output, \\\"Sorry, parking lot is full\\\")\",\n \"def _create_block(\\n self,\\n test_constants: Dict,\\n challenge_hash: bytes32,\\n height: uint32,\\n prev_header_hash: bytes32,\\n prev_iters: uint64,\\n prev_weight: uint64,\\n timestamp: uint64,\\n difficulty: uint64,\\n ips: uint64,\\n seed: bytes,\\n ) -> FullBlock:\\n prover = None\\n plot_pk = None\\n plot_sk = None\\n qualities: List[bytes] = []\\n for pn in range(num_plots):\\n # Allow passing in seed, to create reorgs and different chains\\n seeded_pn = (pn + 17 * int.from_bytes(seed, \\\"big\\\")) % num_plots\\n filename = self.filenames[seeded_pn]\\n plot_pk = plot_pks[seeded_pn]\\n plot_sk = plot_sks[seeded_pn]\\n prover = DiskProver(os.path.join(self.plot_dir, filename))\\n qualities = prover.get_qualities_for_challenge(challenge_hash)\\n if len(qualities) > 0:\\n break\\n\\n assert prover\\n assert plot_pk\\n assert plot_sk\\n if len(qualities) == 0:\\n raise NoProofsOfSpaceFound(\\\"No proofs for this challenge\\\")\\n\\n proof_xs: bytes = prover.get_full_proof(challenge_hash, 0)\\n proof_of_space: ProofOfSpace = ProofOfSpace(\\n challenge_hash, pool_pk, plot_pk, k, [uint8(b) for b in proof_xs]\\n )\\n number_iters: uint64 = pot_iterations.calculate_iterations(\\n proof_of_space, difficulty, ips, test_constants[\\\"MIN_BLOCK_TIME\\\"]\\n )\\n\\n disc: int = create_discriminant(\\n challenge_hash, test_constants[\\\"DISCRIMINANT_SIZE_BITS\\\"]\\n )\\n start_x: ClassGroup = ClassGroup.from_ab_discriminant(2, 1, disc)\\n y_cl, proof_bytes = create_proof_of_time_nwesolowski(\\n disc, start_x, number_iters, disc, n_wesolowski\\n )\\n\\n output = ClassgroupElement(y_cl[0], y_cl[1])\\n\\n proof_of_time = ProofOfTime(\\n challenge_hash,\\n number_iters,\\n output,\\n n_wesolowski,\\n [uint8(b) for b in proof_bytes],\\n )\\n\\n coinbase: CoinbaseInfo = CoinbaseInfo(\\n height,\\n block_rewards.calculate_block_reward(uint32(height)),\\n coinbase_target,\\n )\\n coinbase_sig: PrependSignature = pool_sk.sign_prepend(bytes(coinbase))\\n fees_target: FeesTarget = FeesTarget(fee_target, uint64(0))\\n solutions_generator: bytes32 = sha256(seed).digest()\\n cost = uint64(0)\\n body: Body = Body(\\n coinbase, coinbase_sig, fees_target, None, solutions_generator, cost\\n )\\n\\n header_data: HeaderData = HeaderData(\\n prev_header_hash,\\n timestamp,\\n bytes([0] * 32),\\n proof_of_space.get_hash(),\\n body.get_hash(),\\n bytes([0] * 32),\\n )\\n\\n header_hash_sig: PrependSignature = plot_sk.sign_prepend(header_data.get_hash())\\n\\n header: Header = Header(header_data, header_hash_sig)\\n\\n challenge = Challenge(\\n challenge_hash,\\n proof_of_space.get_hash(),\\n proof_of_time.get_hash(),\\n height,\\n uint64(prev_weight + difficulty),\\n uint64(prev_iters + number_iters),\\n )\\n header_block = HeaderBlock(proof_of_space, proof_of_time, challenge, header)\\n\\n full_block: FullBlock = FullBlock(header_block, body)\\n\\n return full_block\",\n \"def test_gethtml(self):\\r\\n mock_module = CHModuleFactory.create()\\r\\n\\r\\n def fake_get_display_items():\\r\\n \\\"\\\"\\\"\\r\\n A mock of get_display_items\\r\\n \\\"\\\"\\\"\\r\\n return [FakeChild()]\\r\\n mock_module.get_display_items = fake_get_display_items\\r\\n out_html = mock_module.render('student_view').content\\r\\n self.assertTrue('This is supposed to be test html.' in out_html)\\r\\n self.assertTrue('i4x://this/is/a/fake/id' in out_html)\",\n \"def bos_fixture():\\n block_config = {\\n \\\"Clock\\\": {\\\"start_time\\\": 0,\\n \\\"end_time\\\": 10,\\n \\\"num_steps\\\": 100},\\n \\\"PhysicsModules\\\": {\\n \\\"BlockOnSpring\\\": {\\n \\\"mass\\\": 1,\\n \\\"spring_constant\\\": 1,\\n \\\"pusher\\\": \\\"Leapfrog\\\",\\n \\\"x0\\\": [0, 1, 0],\\n }\\n },\\n \\\"Tools\\\": {\\n \\\"Leapfrog\\\": {},\\n \\\"ForwardEuler\\\": {},\\n \\\"BackwardEuler\\\": {}\\n },\\n \\\"Diagnostics\\\": {\\n # default values come first\\n \\\"directory\\\": \\\"test_output/\\\",\\n \\\"output_type\\\": \\\"csv\\\",\\n \\\"clock\\\": {\\\"filename\\\": \\\"time.csv\\\"},\\n \\\"BlockDiagnostic\\\": [\\n {'component': 'momentum', 'filename': 'block_p.csv'},\\n {'component': 'position', 'filename': 'block_x.csv'}\\n ]\\n }\\n }\\n\\n return block_config\",\n \"def test_custom_local_output_file() -> None:\\n with tempfile.TemporaryDirectory() as tmpdirname:\\n file_location = os.path.join(tmpdirname, \\\"foo.txt\\\")\\n\\n # Instantiate the output file\\n absolute_file_location = os.path.abspath(file_location)\\n output_file = PyArrowFileIO().new_output(location=f\\\"{absolute_file_location}\\\")\\n\\n # Create the output file and write to it\\n f = output_file.create()\\n f.write(b\\\"foo\\\")\\n\\n # Confirm that bytes were written\\n with open(file_location, \\\"rb\\\") as f:\\n assert f.read() == b\\\"foo\\\"\\n\\n assert len(output_file) == 3\",\n \"def dummy_code_block() -> CodeBlock:\\n return make_dummy_code_block()\",\n \"def with_output(self, output, output_format):\\n\\t\\tself.variables['output'] = output\\n\\t\\tself.variables['output_format'] = output_format\\n\\t\\treturn self\",\n \"def captured_output(stream_name):\\n import StringIO\\n orig_stdout = getattr(sys, stream_name)\\n setattr(sys, stream_name, StringIO.StringIO())\\n yield getattr(sys, stream_name)\\n setattr(sys, stream_name, orig_stdout)\",\n \"def test_format_leave_output(self):\\n # Setup params and mock result for car successfully leave parking lot\\n leave_cmd = \\\"leave\\\"\\n slot_id = 1\\n\\n # Mock success resp and verify\\n success, output = self.controller.format_leave_output(slot_id)\\n self.assertTrue(success)\\n self.assertEqual(output, \\\"Slot number {} is free\\\".format(slot_id))\",\n \"def testProcess(self, mock_get_write_results):\\n self.mock_grr_api.Hunt.return_value.Get.return_value = \\\\\\n mock_grr_hosts.MOCK_HUNT\\n self.grr_hunt_downloader.Process()\\n mock_get_write_results.assert_called_with(mock_grr_hosts.MOCK_HUNT,\\n '/tmp/test')\",\n \"def writeOutput(self, output):\",\n \"def test_dumps(\\n mock_hvac_client_read, mock_dumps, localhost_client, gen_input_config, gen_processed_config, gen_vault_response_kv1\\n):\\n mock_hvac_client_read.return_value = gen_vault_response_kv1(pwd_key=\\\"password\\\")\\n\\n input_config = gen_input_config()\\n input_config[\\\"vault_secrets\\\"][\\\"acme.pwd\\\"] = \\\"secret/acme/server/user.password\\\"\\n\\n localhost_client.dumps(input_config)\\n\\n mock_hvac_client_read.assert_called_with(gen_input_config()[\\\"vault_secrets\\\"][\\\"acme.user\\\"])\\n mock_dumps.assert_called_with(gen_processed_config())\",\n \"def side_effect_create_mock_tool(tool_path):\\n\\n def _side_effect(*args, **kwargs):\\n tool_path.parent.mkdir(parents=True)\\n with tool_path.open(\\\"w\\\") as f:\\n f.write(\\\"I am a complete tool\\\")\\n return \\\"new-downloaded-file\\\"\\n\\n return _side_effect\",\n \"def test_help(self):\\n _help = \\\"*** No help on hello\\\\n\\\"\\n with patch('sys.stdout', new=StringIO()) as f:\\n HBNBCommand().onecmd(\\\"help hello\\\")\\n self.assertEqual(f.getvalue(), _help)\",\n \"def test_main_output(self, capsys):\\n args = self.args.copy()\\n args[\\\"out_file\\\"] = \\\"text.txt\\\"\\n UI.main(**args)\\n captured = capsys.readouterr().out\\n assert \\\"Results written to text.txt\\\" in captured\",\n \"def expect_output(self, file, parse_json=False):\\n contents = self._data_file(file)\\n patcher = mock.patch('sys.stdout', new_callable=StringIO)\\n output = patcher.start()\\n yield\\n patcher.stop()\\n if parse_json:\\n self.assertEqual(json.loads(output.getvalue()),\\n json.loads(contents))\\n else:\\n self.assertEqual(output.getvalue().split('\\\\n'), contents.split('\\\\n'))\",\n \"def parsed_output(output_elements):\\n parsed_output = {}\\n for stanza, stanza_value in output_elements.items():\\n fake_section = MagicMock()\\n fake_section.options = {}\\n fake_section.name = stanza\\n parsed_output.update({stanza: fake_section})\\n for option, value in stanza_value.items():\\n fake_setting = MagicMock()\\n fake_setting.name = option\\n fake_setting.value = value\\n parsed_output[stanza].options.update({option: fake_setting})\\n return parsed_output\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.64789915","0.6219317","0.6141315","0.61250573","0.5885682","0.58214647","0.5781268","0.5775005","0.5772843","0.57672167","0.57131493","0.5694267","0.5624239","0.56047845","0.5593248","0.55418766","0.5537944","0.5513371","0.5504529","0.5503281","0.54982126","0.54970914","0.5494901","0.54899496","0.54666483","0.5453526","0.54494965","0.5445999","0.54419893","0.5434951","0.54306424","0.54300404","0.54299957","0.5425663","0.54213053","0.5421275","0.54181314","0.5417634","0.5405306","0.54035515","0.5395903","0.53895","0.53882766","0.5385427","0.5363847","0.53628016","0.53551","0.53467697","0.53427595","0.53414494","0.5337091","0.5337091","0.53367394","0.5335126","0.533359","0.5333117","0.5329796","0.5303878","0.5303741","0.52950025","0.52918833","0.52886784","0.528502","0.52832615","0.5277914","0.52758896","0.5270391","0.5267612","0.5254842","0.52494186","0.5248075","0.5238838","0.52334344","0.5224854","0.52129465","0.52116984","0.52089393","0.52068365","0.5202925","0.51995003","0.51888776","0.518652","0.51836383","0.51832026","0.51726925","0.51684994","0.5164746","0.51564944","0.5155857","0.51357263","0.5123833","0.51203245","0.5119547","0.5117735","0.5116399","0.5115759","0.51095784","0.51093805","0.51088566","0.5108485"],"string":"[\n \"0.64789915\",\n \"0.6219317\",\n \"0.6141315\",\n \"0.61250573\",\n \"0.5885682\",\n \"0.58214647\",\n \"0.5781268\",\n \"0.5775005\",\n \"0.5772843\",\n \"0.57672167\",\n \"0.57131493\",\n \"0.5694267\",\n \"0.5624239\",\n \"0.56047845\",\n \"0.5593248\",\n \"0.55418766\",\n \"0.5537944\",\n \"0.5513371\",\n \"0.5504529\",\n \"0.5503281\",\n \"0.54982126\",\n \"0.54970914\",\n \"0.5494901\",\n \"0.54899496\",\n \"0.54666483\",\n \"0.5453526\",\n \"0.54494965\",\n \"0.5445999\",\n \"0.54419893\",\n \"0.5434951\",\n \"0.54306424\",\n \"0.54300404\",\n \"0.54299957\",\n \"0.5425663\",\n \"0.54213053\",\n \"0.5421275\",\n \"0.54181314\",\n \"0.5417634\",\n \"0.5405306\",\n \"0.54035515\",\n \"0.5395903\",\n \"0.53895\",\n \"0.53882766\",\n \"0.5385427\",\n \"0.5363847\",\n \"0.53628016\",\n \"0.53551\",\n \"0.53467697\",\n \"0.53427595\",\n \"0.53414494\",\n \"0.5337091\",\n \"0.5337091\",\n \"0.53367394\",\n \"0.5335126\",\n \"0.533359\",\n \"0.5333117\",\n \"0.5329796\",\n \"0.5303878\",\n \"0.5303741\",\n \"0.52950025\",\n \"0.52918833\",\n \"0.52886784\",\n \"0.528502\",\n \"0.52832615\",\n \"0.5277914\",\n \"0.52758896\",\n \"0.5270391\",\n \"0.5267612\",\n \"0.5254842\",\n \"0.52494186\",\n \"0.5248075\",\n \"0.5238838\",\n \"0.52334344\",\n \"0.5224854\",\n \"0.52129465\",\n \"0.52116984\",\n \"0.52089393\",\n \"0.52068365\",\n \"0.5202925\",\n \"0.51995003\",\n \"0.51888776\",\n \"0.518652\",\n \"0.51836383\",\n \"0.51832026\",\n \"0.51726925\",\n \"0.51684994\",\n \"0.5164746\",\n \"0.51564944\",\n \"0.5155857\",\n \"0.51357263\",\n \"0.5123833\",\n \"0.51203245\",\n \"0.5119547\",\n \"0.5117735\",\n \"0.5116399\",\n \"0.5115759\",\n \"0.51095784\",\n \"0.51093805\",\n \"0.51088566\",\n \"0.5108485\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.85911703"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":13097,"cells":{"query":{"kind":"string","value":"Signal objects are connected as expected."},"document":{"kind":"string","value":"def test_signals_connected(input_block, output_block, kwargs):\n input_signal = input_block()\n output_cb = output_block()\n\n with patch('rabbithole.cli.Batcher') as batcher_cls:\n create_flow(**kwargs)\n\n input_signal.connect.assert_called_once_with(\n batcher_cls().message_received_cb,\n weak=False,\n )\n batcher_signal = batcher_cls().batch_ready\n batcher_signal.connect.assert_called_once_with(\n output_cb,\n weak=False,\n )"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __enter__(self):\n if self.models:\n for m in self.models:\n self._connect(m)\n else:\n self._connect()\n return super(SignalChecker, self).__enter__()","def connected(self):\n pass","def connected(self):\n pass","def connected(self):\n _abstract()","def connected(self):\n _abstract()","def connect_all_signals():\n rohypnol.connect()","def signal(self):\n pass","def signal(self) -> list:\n raise NotImplementedError(\"You must implement signal\")","def caculate_signals(self):\n\t\traise NotImplementedError(\"Should implement calculate_signals()\")","def connect_slots(self):\n\n self.set_elf_sig.connect(self.set_elf)\n self.run_target_sig.connect(self.run_target)\n self.continue_target_sig.connect(self.continue_target)\n self.set_breakpoint_sig.connect(self.set_breakpoint)\n self.set_app_mode_sig.connect(self.set_app_mode)\n self.write_hex_value_sig.connect(self.write_word_to_address)","def signal_oi(self):\n pass","def _onconnect(self):\n\n pass","def _connect_signals(self):\r\n\r\n\t\t# Connecting socket signals\r\n\t\tself.__tcpSocket.error.connect(self.__display_error)\r\n\t\tself.__tcpSocket.readyRead.connect(self.__read_message)\r\n\r\n\t\t# Connecting the socket when requested\r\n\t\tself._window.set_connection_infos.connect(lambda x: self.connect_to_server(*x))\r\n\r\n\t\t# Connecting the bar names request\r\n\t\tself._window.get_bar_names.connect(lambda: self.encode_message(action=\"LA\"))\r\n\r\n\t\t# Setting the bar name when requested\r\n\t\tself._window.set_bar_name.connect(self.__set_name)\r\n\r\n\t\t# Connecting the preferences\r\n\t\tself._window.ask_preferences.connect(\r\n\t\t\tlambda: self.fill_preferences.emit((self.__tcpSocket.peerAddress().toString(), self.__tcpSocket.peerPort()),\r\n\t\t\t\t\t\t\t\t\t\t\t self.__name))\r\n\r\n\t\t# Connecting the send message signal\r\n\t\tself._window.send_message.connect(lambda x: self.encode_message(action=\"ME\", message=x))\r\n\r\n\t\t# Connecting for the connection dialog\r\n\t\tself._window.request_connection_infos.connect(\r\n\t\t\tlambda: self.open_connection_dialog.emit([[self.__tcpSocket.peerAddress().toString(),\r\n\t\t\t\t\t\t\t\t\t\t\t\t\t self.__tcpSocket.state() == QAbstractSocket.ConnectedState]]))","def signal(self, args):\n pass","def connect(self, event):\n self.out_graph = False","def test_allows_signal_notify(self):\n b1 = Block()\n b2 = Block()\n self.configure_block(b1, {})\n self.configure_block(b2, {})\n\n b1.notify_signals([Signal(), Signal()])\n b2.notify_signals([Signal()])\n\n # Assert that 3 total signals were captured\n self.assert_num_signals_notified(3)\n\n # Assert that we captured the right number of signals per block too\n self.assert_num_signals_notified(2, b1)\n self.assert_num_signals_notified(1, b2)","def __init__(self, computed=None, antenna=None):\n super(ConnectionStatus.Signal, self).__init__(computed=computed,\n antenna=antenna)","def signalSetup(self):\n self.ui.b_info.clicked.connect(self.showInfo)\n self.ui.b_save.clicked.connect(self.openSave)\n self.ui.b_vid.clicked.connect(self.openVideo)\n self.ui.b_run.clicked.connect(self.startRun)\n self.ui.b_colour.clicked.connect(self.pickColour)\n self.ui.b_ground_truth.clicked.connect(self.openGroundTruth)\n\n self.ui.t_fps.textChanged.connect(self.changeFps)\n self.ui.t_low.editingFinished.connect(self.changeLow)\n self.ui.t_high.editingFinished.connect(self.changeHigh)\n self.ui.c_error_plot.stateChanged.connect(self.checkFiles)\n self.ui.c_speed_plot.stateChanged.connect(self.checkFiles)\n self.ui.c_crash_plot.stateChanged.connect(self.checkFiles)\n self.ui.combo_superpixel.currentIndexChanged.connect(\n self.changeSuperPixelMethod\n )\n self.ui.c_optimize.stateChanged.connect(self.checkFiles)\n self.ui.c_draw.stateChanged.connect(self.checkFiles)\n self.ui.c_velocity.stateChanged.connect(self.checkFiles)\n self.ui.c_object_detection.stateChanged.connect(self.checkFiles)","def connect(self):","def connect(self):","def get_signals(self):\n raise NotImplementedError('Agent is an abstract base class')","def outConnectEvent(self):\r\n pass","def register_signals(self):\n for _, callback in self.signal_callbacks:\n Signal.subscribe(self, callback)","def connect_signals_and_slots(self):\n # Orthogonality\n self.orthogonality_m.sliderReleased.connect(self.calc_integral)\n self.psi_psi.clicked.connect(self.calc_integral)\n self.psi_phi.clicked.connect(self.calc_integral)\n self.phi_phi.clicked.connect(self.calc_integral)\n\n # Fourier series\n self.function_selector.currentIndexChanged.connect(self.select_function)\n self.number_of_terms.sliderReleased.connect(self.change_terms)\n self.save.clicked.connect(self.save_file)\n self.fs_checkbox.stateChanged.connect(self.select_function)\n\n #Parseval's Theorem\n self.number_of_terms_pi.sliderReleased.connect(self.approximate_pi)\n self.parseval_save.clicked.connect(self.save_file)","def signalsConnections(self):\n # self.yearChanged.connect()\n self.bot_next.clicked.connect(self.changeDisplayedMonth)\n self.bot_prev.clicked.connect(self.changeDisplayedMonth)\n self.currentPageChanged.connect(self.changeDisplayedMonthCombo)\n self.currentPageChanged.connect(self.setComplexLabels)\n self.currentPageChanged.connect(self.removeSelection)\n self.currentPageChanged.connect(self.updateIconsAndBooked)\n self.listaGiorniDellAnnoChanged.connect(self.setComplexLabels)\n self.listaGiorniDellAnnoChanged.connect(self.updateIconsAndBooked)\n self.combo_mesi.currentIndexChanged.connect(self.setComplexLabels)\n self.combo_mesi.currentIndexChanged.connect(self.removeSelection)\n self.table.cellClicked.connect(self.clickedCell)\n self.datesIndicatorsChanged.connect(self.updateIconsAndBooked)","def ready(self):\n import main.signals # noqa","def connect(self, gate) :\n self.notifyList.append(gate)","def connected(self, p, q):\n pass","def generate_signals(self):\n\n raise NotImplementedError('''\n Must implement generate_signals. Call help() for details.\n ''')","def connect(self) -> None:","def test_signal(self):\n mediator = Mediator()\n mediator.connect(\"set_dog_sound\", self.dog.set_sound)\n mediator.connect(\"set_cat_sound\", self.cat.set_sound)\n mediator.signal(\"set_dog_sound\", \"woof\")\n mediator.signal(\"set_cat_sound\", \"meow\")\n\n self.assertEquals(\"woof\", self.dog.sound)\n self.assertEquals(\"meow\", self.cat.sound)","def connect_actions(self):\n self.single_acq.clicked.connect(lambda: self.cam.single_acquisition())\n self.single_acq.clicked.connect(lambda: self.status.setText(\"Single\"))\n self.start_acq.clicked.connect(lambda: self.cam.start_acquisition())\n self.start_acq.clicked.connect(lambda: self.status.setText(\"Started\"))\n self.stop_acq.clicked.connect(lambda: self.cam.stop_acquisition())\n self.stop_acq.clicked.connect(lambda: self.status.setText(\"Stopped\"))\n self.stop_acq.clicked.connect(lambda: self.fps.hide())\n # connect after finding params so we don't send accidental update\n self.exposure.valueChanged.connect(self.exposure_cb)\n self.mark.clicked.connect(self.mark_cb)\n self.unmark.clicked.connect(self.unmark_cb)\n\n proxy = pg.SignalProxy(self.g_layout.scene().sigMouseMoved,\n rateLimit=20, slot=self.cursor_cb)\n self.g_layout.scene().sigMouseMoved.connect(self.cursor_cb)\n self.g_layout.scene().sigMouseClicked.connect(self.clicked_cb)","def signals_notified(self, block, signals, output_id=DEFAULT_TERMINAL):\n self._signals_notified = True\n super().signals_notified(block, signals, output_id)","def connect(self):\n pass","def enableSignalDebugging(self, **kwargs: Any) -> None:\n\n def f(*args):\n return None\n connectCall: Callable = kwargs.get('connectCall', f)\n disconnectCall: Callable = kwargs.get('disconnectCall', f)\n emitCall: Callable = kwargs.get('emitCall', f)\n\n def printIt(msg: str) -> Callable:\n\n def call(*args: Any) -> None:\n print(msg, args)\n\n return call\n\n # Monkey-patch.\n\n QtCore.QObject.connect = self._wrapConnect(connectCall)\n QtCore.QObject.disconnect = self._wrapDisconnect(disconnectCall)\n\n def new_emit(self, *args: Any) -> None: # type:ignore\n emitCall(self, *args)\n self._oldEmit(self, *args)\n\n QtCore.QObject.emit = new_emit","def connect(self):\n pass","def connect(self):\n pass","def connect(self):\n pass","def connect(self):\n pass","def connect(self):\n pass","def connect(self):\n pass","def connect(self):\n pass","def connect(self):\n pass","def make_connections(self):\n self.run_button.clicked.connect(self.on_run_clicked)\n self.step_button.clicked.connect(self.on_step_clicked)\n self.stop_button.clicked.connect(self.on_stop_clicked)\n self.reset_button.clicked.connect(self.on_reset_clicked)\n \n self.toggle_running_button_state.connect(self.run_button.setEnabled)\n self.toggle_running_button_state.connect(self.step_button.setEnabled)\n self.toggle_running_button_state.connect(self.stop_button.setEnabled)\n self.toggle_running_button_state.connect(self.reset_button.setEnabled)\n \n self.algorithm_finished.connect(self.run_button.setEnabled)\n self.algorithm_finished.connect(self.step_button.setEnabled)","def onConnect(self, *args):\n UAV_Logger.log(\"connect signal recieved\")\n self.socketIO.emit('CORE_SL_SLOTS_SET', Request(self.getModuleName()).newData({\"slots\":self.slots}).toDictionary())","def setup_signals(self):\n\n # Hook the play/pause buttons\n self.ui.actionContinue_Live_Updates.triggered.connect(self.on_live)\n self.ui.actionPause_Live_Updates.triggered.connect(self.on_pause)\n self.ui.actionSave.triggered.connect(self.on_save)\n\n # Custom graph buttons\n self.action_graph_reset.triggered.connect(self.reset_graph)\n self.action_graph_full_extent.triggered.connect(self.full_extent)\n\n # Custom tools generated in visualize that are not actions\n self.zoom_tool.wrap_sig.clicked.connect(self.process_zoom)\n self.select_tool.wrap_sig.clicked.connect(self.process_select)","def connect(self):\n\t\tpass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\n pass","def calculate_signals(self):\n raise NotImplementedError(\"Should implement calculate_signals()\")","def emit (self, signal):\n for room in self.transmissionarea :\n for listener in room.listeners:\n listener.signalReceived(signal)","def notifyObservers(self):","def signalReceived (self, signal): \n raise NotImplementedError(\"Lack of signalReceived method\")","def _on_connect(self, component: \"Model\") -> None:\n if self.circuit != component.circuit:\n # make sure to merge the smaller circuit into the larger\n if len(component.circuit) > len(self.circuit):\n component.circuit._merge(self.circuit)\n else:\n self.circuit._merge(component.circuit)","def connect(self, receiver, sender=ANY, weak=True, retval=False):\n\t\trv = super(Signal, self).connect(receiver, sender, weak)\n\t\tif retval and rv:\n\t\t\tsid = ANY_ID if sender is ANY else self.hashable_id(self.get_sender_id(sender))\n\t\t\tself._pipes[self.hashable_id(receiver)].add(sid)\n\t\treturn rv","def __init__(self):\n # noinspection PyUnresolvedReferences\n self._generic_signal.connect(self._generic_slot)\n self._call_counters = {}","def _connectSignals(self):\r\n self.imperial_button.clicked.connect(self._units_chosen)\r\n self.metric_button.clicked.connect(self._units_chosen)\r\n self.age_field.valueChanged.connect(self._age_changed)\r\n self.height_field.valueChanged.connect(self._height_changed)\r\n self.weight_field.valueChanged.connect(self._weight_changed)\r\n self.bodyFat_field.valueChanged.connect(self._bodyFat_changed)\r\n self.gender_combobox.currentIndexChanged.connect(self._gender_changed)\r\n self.calculate_button.clicked.connect(self._calculate_feedback)","def test_allows_signal_handler_override(self):\n self._signals_notified = False\n b1 = Block()\n self.configure_block(b1, {})\n\n self.assertFalse(self._signals_notified)\n b1.notify_signals([Signal()])\n self.assertTrue(self._signals_notified)","def isSignal(self, p_int): # real signature unknown; restored from __doc__\n return False","def makeConnections(self):\n\t\tself.connect(self.addTextureToOcc_btn, QtCore.SIGNAL(\"clicked()\"), self.addTextureToOcc)\n\t\tself.connect(self.removeTextureToOcc_btn, QtCore.SIGNAL(\"clicked()\"), self.removeTextureToOcc)\n\t\tself.connect(self.addIrisToOcc_btn, QtCore.SIGNAL(\"clicked()\"), self.addIrisToOcc)\n\t\tself.connect(self.removeIrisToOcc_btn, QtCore.SIGNAL(\"clicked()\"), self.removeIrisToOcc)\n\t\tself.connect(self.addHideOcc_btn, QtCore.SIGNAL(\"clicked()\"), self.addHideForOcc)\n\t\tself.connect(self.removeHideOcc_btn, QtCore.SIGNAL(\"clicked()\"), self.removeHideForOcc)","def connect(self):\n for signal, models in six.iteritems(self._registry):\n for model, keys in six.iteritems(models):\n # Local function the current signal is going to be\n # connected to.\n # Defining it dynamically allows us to pass in the current\n # set of keys for the given model, but we have to store\n # a strong reference to it to avoid garbage collection.\n def delete_cache(signal, sender=model, keys=keys):\n cache.delete_many(list(keys))\n signal.connect(delete_cache, sender=model, weak=False, dispatch_uid=signal)","def connect(self, *args, **kwargs):","def ready(self):\n\n from . import signals # noqa","def connect(self) -> None:\n ...","def set_connected(self):\n self.connected = True","def connect(self):\n raise NotImplementedError","def connect(self):\n raise NotImplementedError","def signals(self):\n if self._current_inputs is None:\n raise RuntimeError(\n 'Internal Error: The current inputs have not been properly '\n 'generated. First call features_and_labels, then call signals.')\n signals = self._current_inputs['signals']\n self._current_inputs = None\n return signals","def _notifyConnect(self, function, **kwargs):\n self._sig_connect.subscribe(function, **kwargs)","def test_connection(self):\n gen = self.create(GeneralizationItem)\n c1 = self.create(ClassItem, UML.Class)\n c2 = self.create(ClassItem, UML.Class)\n\n self.connect(gen, gen.tail, c1)\n assert self.get_connected(gen.tail) is c1\n\n self.connect(gen, gen.head, c2)\n assert gen.subject is not None\n assert gen.subject.general is c2.subject\n assert gen.subject.specific is c1.subject","def checksignals(self):\n if self.space.check_signal_action is not None:\n self.space.check_signal_action.perform(self, None)","def register(self):\n REGISTERED_SIGNALS.setdefault(self.path, []).append(self)","def setup(self):\n\t\tif self.hasSignalModule and not self.signalsRegistered:\n\t\t\t# Jython does not support all signals, so we only use\n\t\t\t# the available ones\n\t\t\tsignals = ['SIGINT', 'SIGHUP', 'SIGABRT', 'SIGQUIT', 'SIGTERM']\n\t\t\timport signal\n\t\t\tfor sig in signals:\n\t\t\t\ttry:\n\t\t\t\t\tsignal.signal(getattr(signal, sig), self._shutdown)\n\t\t\t\t\tself.signalsRegistered.append(sig)\n\t\t\t\texcept Exception as e:\n\t\t\t\t\tLogger.Err(\"[!] monitoring.Signals._registerSignals:%s %s\\n\" % (sig, e))","def connected(self) -> bool:\n raise NotImplementedError","def Connected(self) -> bool:","def Connected(self) -> bool:","def send_connection_state(self, conn=None):\n self.connection_state_signal.emit(conn)","def test_connect(self):\n mediator = Mediator()\n mediator.connect(\"set_dog_sound\", self.dog.set_sound)\n self.assertEquals([self.dog.set_sound], mediator.signals[\"set_dog_sound\"])\n\n mediator.connect(\"set_cat_sound\", self.cat.set_sound)\n self.assertEquals([self.cat.set_sound], mediator.signals[\"set_cat_sound\"])","def _create_connections(self):\n # Level Size\n self._level_size_x_spinbox.valueChanged.connect(self._set_x_size)\n self._level_size_y_spinbox.valueChanged.connect(self._set_y_size)\n self._level_size_z_spinbox.valueChanged.connect(self._set_z_size)\n\n # Minimum Length\n self._minimum_length_checkbox.toggled.connect(self._checked_minimum)\n self._minimum_length_spinbox.valueChanged.connect(self._set_minimum)\n\n # Maximum Length\n self._maximum_length_checkbox.toggled.connect(self._checked_maximum)\n self._maximum_length_spinbox.valueChanged.connect(self._set_maximum)\n\n # Seed\n self._seed_checkbox.toggled.connect(self._checked_seed)\n self._seed_le.textEdited.connect(self._set_seed)\n \n # Block Size\n self._block_size_x_spinbox.valueChanged.connect(self._set_x_block_size)\n self._block_size_y_spinbox.valueChanged.connect(self._set_y_block_size)\n self._block_size_z_spinbox.valueChanged.connect(self._set_z_block_size)\n\n # Group Name\n self._group_name_le.textEdited.connect(self._set_group_name)\n\n # Object Blocks\n for blk_type in VALID_BLOCK_TYPES:\n self._object_blocks[blk_type][\"pth_le\"].textEdited.connect(self._object_block_pth(blk_type))\n self._object_blocks[blk_type][\"weight_spinbox\"].valueChanged.connect(self._object_block_weight(blk_type))\n\n # Buttons\n self._cancel_btn.clicked.connect(self._cancel)\n self._generate_btn.clicked.connect(self._generate)","def connect(self):\n return 1","def test_get_signal(self):\n\n self.signal_getter.set_signal_source(MockSignalSource())\n self.assertEqual(self.signal_getter.get_signal(), [0])\n self.assertEqual(self.signal_getter.get_signal(), [1])\n self.assertEqual(self.signal_getter.get_signal(), [2])","def __connected(self):\n self.connected()\n if self.__callbacks.get(\"connected\"):\n cb = self.__callbacks[\"connected\"]()\n if cb is not None:\n cb()","def _connect_signals(self):\n\n # File menu\n self.openConfigAction.triggered.connect(self.inputDataModule.on_open_config_clicked)\n self.saveConfigAction.triggered.connect(self.inputDataModule.on_save_config_clicked)\n self.openStatsAction.triggered.connect(self.on_open_stats_file_triggered)\n self.openSpectrogramsAction.triggered.connect(self.on_open_spectrograms_file)\n\n # View menu\n # self.showPlotScreen.triggered.connect(self.view_mod_stats_screening)\n\n # Process menu\n self.processScreeningAction.triggered.connect(self.process_screening)\n self.runIntegrationAction.triggered.connect(self.process_ts_integration)\n self.calcSeascatterAction.triggered.connect(self.calc_seascatter)\n self.calcTFAction.triggered.connect(self.calc_transfer_functions)\n self.calcFatigueAction.triggered.connect(self.calc_fatigue)\n\n # Plot settings menu\n # self.add2HIcon.triggered.connect(self.add_2h_icon)\n self.loggerPlotSettingsAction.triggered.connect(self.on_logger_plot_settings_triggered)\n self.spectPlotSettingsAction.triggered.connect(self.on_spect_plot_settings_triggered)\n\n # Export menu\n self.exportScatterDiagAction.triggered.connect(self.on_export_scatter_diagram_triggered)\n\n # Azure menu\n self.azureSettingsAction.triggered.connect(self.on_azure_account_settings_triggered)\n\n # Filter settings menu\n self.filterSettingsAction.triggered.connect(self.on_filter_settings_triggered)\n\n # Help menu\n self.helpAction.triggered.connect(self.show_help)\n self.aboutAction.triggered.connect(self.show_about)\n\n # Toolbar dashboard buttons\n self.projConfigButton.clicked.connect(self.view_proj_config_mod)\n self.rawDataButton.clicked.connect(self.view_mod_raw_data)\n self.dataQualityButton.clicked.connect(self.view_mod_data_quality)\n self.statsScreeningButton.clicked.connect(self.view_mod_stats_screening)\n self.spectralScreeningButton.clicked.connect(self.view_mod_spectral_screening)\n self.histogramsButton.clicked.connect(self.view_mod_histograms)\n self.seascatterButton.clicked.connect(self.view_mod_seascatter)\n self.transFuncsButton.clicked.connect(self.view_mod_transfer_functions)\n self.fatigueButton.clicked.connect(self.view_mod_fatigue)","def enable_callbacks(self):\n\n onObjectUpdate_received = self.message_handler.register('ObjectUpdate')\n onObjectUpdate_received.subscribe(self.onObjectUpdate)\n\n onObjectUpdateCached_received = self.message_handler.register('ObjectUpdateCached')\n onObjectUpdateCached_received.subscribe(self.onObjectUpdateCached)\n\n onObjectUpdateCompressed_received = self.message_handler.register('ObjectUpdateCompressed')\n onObjectUpdateCompressed_received.subscribe(self.onObjectUpdateCompressed)\n\n onImprovedTerseObjectUpdate_received = self.message_handler.register('ImprovedTerseObjectUpdate')\n onImprovedTerseObjectUpdate_received.subscribe(self.onImprovedTerseObjectUpdate)\n \n onObjectProperties_received = self.message_handler.register('ObjectProperties')\n onObjectProperties_received.subscribe(self.onObjectProperties)\n\n onKillObject_received = self.message_handler.register('KillObject')\n onKillObject_received.subscribe(self.onKillObject)\n\n # uncomment these to view packets sent back to simulator\n # onObjectName_sent = self.message_handler.register('ObjectName')\n # onObjectName_sent.subscribe(self.helpers.log_packet, self)\n\n # onDeRezObject_sent = self.message_handler.register('DeRezObject')\n # onDeRezObject_sent.subscribe(self.helpers.log_packet, self)","def empty_signal(self, *args, **kwargs):\n pass","def __init__(self, connected=True):\n self._connected = connected"],"string":"[\n \"def __enter__(self):\\n if self.models:\\n for m in self.models:\\n self._connect(m)\\n else:\\n self._connect()\\n return super(SignalChecker, self).__enter__()\",\n \"def connected(self):\\n pass\",\n \"def connected(self):\\n pass\",\n \"def connected(self):\\n _abstract()\",\n \"def connected(self):\\n _abstract()\",\n \"def connect_all_signals():\\n rohypnol.connect()\",\n \"def signal(self):\\n pass\",\n \"def signal(self) -> list:\\n raise NotImplementedError(\\\"You must implement signal\\\")\",\n \"def caculate_signals(self):\\n\\t\\traise NotImplementedError(\\\"Should implement calculate_signals()\\\")\",\n \"def connect_slots(self):\\n\\n self.set_elf_sig.connect(self.set_elf)\\n self.run_target_sig.connect(self.run_target)\\n self.continue_target_sig.connect(self.continue_target)\\n self.set_breakpoint_sig.connect(self.set_breakpoint)\\n self.set_app_mode_sig.connect(self.set_app_mode)\\n self.write_hex_value_sig.connect(self.write_word_to_address)\",\n \"def signal_oi(self):\\n pass\",\n \"def _onconnect(self):\\n\\n pass\",\n \"def _connect_signals(self):\\r\\n\\r\\n\\t\\t# Connecting socket signals\\r\\n\\t\\tself.__tcpSocket.error.connect(self.__display_error)\\r\\n\\t\\tself.__tcpSocket.readyRead.connect(self.__read_message)\\r\\n\\r\\n\\t\\t# Connecting the socket when requested\\r\\n\\t\\tself._window.set_connection_infos.connect(lambda x: self.connect_to_server(*x))\\r\\n\\r\\n\\t\\t# Connecting the bar names request\\r\\n\\t\\tself._window.get_bar_names.connect(lambda: self.encode_message(action=\\\"LA\\\"))\\r\\n\\r\\n\\t\\t# Setting the bar name when requested\\r\\n\\t\\tself._window.set_bar_name.connect(self.__set_name)\\r\\n\\r\\n\\t\\t# Connecting the preferences\\r\\n\\t\\tself._window.ask_preferences.connect(\\r\\n\\t\\t\\tlambda: self.fill_preferences.emit((self.__tcpSocket.peerAddress().toString(), self.__tcpSocket.peerPort()),\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t self.__name))\\r\\n\\r\\n\\t\\t# Connecting the send message signal\\r\\n\\t\\tself._window.send_message.connect(lambda x: self.encode_message(action=\\\"ME\\\", message=x))\\r\\n\\r\\n\\t\\t# Connecting for the connection dialog\\r\\n\\t\\tself._window.request_connection_infos.connect(\\r\\n\\t\\t\\tlambda: self.open_connection_dialog.emit([[self.__tcpSocket.peerAddress().toString(),\\r\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t self.__tcpSocket.state() == QAbstractSocket.ConnectedState]]))\",\n \"def signal(self, args):\\n pass\",\n \"def connect(self, event):\\n self.out_graph = False\",\n \"def test_allows_signal_notify(self):\\n b1 = Block()\\n b2 = Block()\\n self.configure_block(b1, {})\\n self.configure_block(b2, {})\\n\\n b1.notify_signals([Signal(), Signal()])\\n b2.notify_signals([Signal()])\\n\\n # Assert that 3 total signals were captured\\n self.assert_num_signals_notified(3)\\n\\n # Assert that we captured the right number of signals per block too\\n self.assert_num_signals_notified(2, b1)\\n self.assert_num_signals_notified(1, b2)\",\n \"def __init__(self, computed=None, antenna=None):\\n super(ConnectionStatus.Signal, self).__init__(computed=computed,\\n antenna=antenna)\",\n \"def signalSetup(self):\\n self.ui.b_info.clicked.connect(self.showInfo)\\n self.ui.b_save.clicked.connect(self.openSave)\\n self.ui.b_vid.clicked.connect(self.openVideo)\\n self.ui.b_run.clicked.connect(self.startRun)\\n self.ui.b_colour.clicked.connect(self.pickColour)\\n self.ui.b_ground_truth.clicked.connect(self.openGroundTruth)\\n\\n self.ui.t_fps.textChanged.connect(self.changeFps)\\n self.ui.t_low.editingFinished.connect(self.changeLow)\\n self.ui.t_high.editingFinished.connect(self.changeHigh)\\n self.ui.c_error_plot.stateChanged.connect(self.checkFiles)\\n self.ui.c_speed_plot.stateChanged.connect(self.checkFiles)\\n self.ui.c_crash_plot.stateChanged.connect(self.checkFiles)\\n self.ui.combo_superpixel.currentIndexChanged.connect(\\n self.changeSuperPixelMethod\\n )\\n self.ui.c_optimize.stateChanged.connect(self.checkFiles)\\n self.ui.c_draw.stateChanged.connect(self.checkFiles)\\n self.ui.c_velocity.stateChanged.connect(self.checkFiles)\\n self.ui.c_object_detection.stateChanged.connect(self.checkFiles)\",\n \"def connect(self):\",\n \"def connect(self):\",\n \"def get_signals(self):\\n raise NotImplementedError('Agent is an abstract base class')\",\n \"def outConnectEvent(self):\\r\\n pass\",\n \"def register_signals(self):\\n for _, callback in self.signal_callbacks:\\n Signal.subscribe(self, callback)\",\n \"def connect_signals_and_slots(self):\\n # Orthogonality\\n self.orthogonality_m.sliderReleased.connect(self.calc_integral)\\n self.psi_psi.clicked.connect(self.calc_integral)\\n self.psi_phi.clicked.connect(self.calc_integral)\\n self.phi_phi.clicked.connect(self.calc_integral)\\n\\n # Fourier series\\n self.function_selector.currentIndexChanged.connect(self.select_function)\\n self.number_of_terms.sliderReleased.connect(self.change_terms)\\n self.save.clicked.connect(self.save_file)\\n self.fs_checkbox.stateChanged.connect(self.select_function)\\n\\n #Parseval's Theorem\\n self.number_of_terms_pi.sliderReleased.connect(self.approximate_pi)\\n self.parseval_save.clicked.connect(self.save_file)\",\n \"def signalsConnections(self):\\n # self.yearChanged.connect()\\n self.bot_next.clicked.connect(self.changeDisplayedMonth)\\n self.bot_prev.clicked.connect(self.changeDisplayedMonth)\\n self.currentPageChanged.connect(self.changeDisplayedMonthCombo)\\n self.currentPageChanged.connect(self.setComplexLabels)\\n self.currentPageChanged.connect(self.removeSelection)\\n self.currentPageChanged.connect(self.updateIconsAndBooked)\\n self.listaGiorniDellAnnoChanged.connect(self.setComplexLabels)\\n self.listaGiorniDellAnnoChanged.connect(self.updateIconsAndBooked)\\n self.combo_mesi.currentIndexChanged.connect(self.setComplexLabels)\\n self.combo_mesi.currentIndexChanged.connect(self.removeSelection)\\n self.table.cellClicked.connect(self.clickedCell)\\n self.datesIndicatorsChanged.connect(self.updateIconsAndBooked)\",\n \"def ready(self):\\n import main.signals # noqa\",\n \"def connect(self, gate) :\\n self.notifyList.append(gate)\",\n \"def connected(self, p, q):\\n pass\",\n \"def generate_signals(self):\\n\\n raise NotImplementedError('''\\n Must implement generate_signals. Call help() for details.\\n ''')\",\n \"def connect(self) -> None:\",\n \"def test_signal(self):\\n mediator = Mediator()\\n mediator.connect(\\\"set_dog_sound\\\", self.dog.set_sound)\\n mediator.connect(\\\"set_cat_sound\\\", self.cat.set_sound)\\n mediator.signal(\\\"set_dog_sound\\\", \\\"woof\\\")\\n mediator.signal(\\\"set_cat_sound\\\", \\\"meow\\\")\\n\\n self.assertEquals(\\\"woof\\\", self.dog.sound)\\n self.assertEquals(\\\"meow\\\", self.cat.sound)\",\n \"def connect_actions(self):\\n self.single_acq.clicked.connect(lambda: self.cam.single_acquisition())\\n self.single_acq.clicked.connect(lambda: self.status.setText(\\\"Single\\\"))\\n self.start_acq.clicked.connect(lambda: self.cam.start_acquisition())\\n self.start_acq.clicked.connect(lambda: self.status.setText(\\\"Started\\\"))\\n self.stop_acq.clicked.connect(lambda: self.cam.stop_acquisition())\\n self.stop_acq.clicked.connect(lambda: self.status.setText(\\\"Stopped\\\"))\\n self.stop_acq.clicked.connect(lambda: self.fps.hide())\\n # connect after finding params so we don't send accidental update\\n self.exposure.valueChanged.connect(self.exposure_cb)\\n self.mark.clicked.connect(self.mark_cb)\\n self.unmark.clicked.connect(self.unmark_cb)\\n\\n proxy = pg.SignalProxy(self.g_layout.scene().sigMouseMoved,\\n rateLimit=20, slot=self.cursor_cb)\\n self.g_layout.scene().sigMouseMoved.connect(self.cursor_cb)\\n self.g_layout.scene().sigMouseClicked.connect(self.clicked_cb)\",\n \"def signals_notified(self, block, signals, output_id=DEFAULT_TERMINAL):\\n self._signals_notified = True\\n super().signals_notified(block, signals, output_id)\",\n \"def connect(self):\\n pass\",\n \"def enableSignalDebugging(self, **kwargs: Any) -> None:\\n\\n def f(*args):\\n return None\\n connectCall: Callable = kwargs.get('connectCall', f)\\n disconnectCall: Callable = kwargs.get('disconnectCall', f)\\n emitCall: Callable = kwargs.get('emitCall', f)\\n\\n def printIt(msg: str) -> Callable:\\n\\n def call(*args: Any) -> None:\\n print(msg, args)\\n\\n return call\\n\\n # Monkey-patch.\\n\\n QtCore.QObject.connect = self._wrapConnect(connectCall)\\n QtCore.QObject.disconnect = self._wrapDisconnect(disconnectCall)\\n\\n def new_emit(self, *args: Any) -> None: # type:ignore\\n emitCall(self, *args)\\n self._oldEmit(self, *args)\\n\\n QtCore.QObject.emit = new_emit\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def connect(self):\\n pass\",\n \"def make_connections(self):\\n self.run_button.clicked.connect(self.on_run_clicked)\\n self.step_button.clicked.connect(self.on_step_clicked)\\n self.stop_button.clicked.connect(self.on_stop_clicked)\\n self.reset_button.clicked.connect(self.on_reset_clicked)\\n \\n self.toggle_running_button_state.connect(self.run_button.setEnabled)\\n self.toggle_running_button_state.connect(self.step_button.setEnabled)\\n self.toggle_running_button_state.connect(self.stop_button.setEnabled)\\n self.toggle_running_button_state.connect(self.reset_button.setEnabled)\\n \\n self.algorithm_finished.connect(self.run_button.setEnabled)\\n self.algorithm_finished.connect(self.step_button.setEnabled)\",\n \"def onConnect(self, *args):\\n UAV_Logger.log(\\\"connect signal recieved\\\")\\n self.socketIO.emit('CORE_SL_SLOTS_SET', Request(self.getModuleName()).newData({\\\"slots\\\":self.slots}).toDictionary())\",\n \"def setup_signals(self):\\n\\n # Hook the play/pause buttons\\n self.ui.actionContinue_Live_Updates.triggered.connect(self.on_live)\\n self.ui.actionPause_Live_Updates.triggered.connect(self.on_pause)\\n self.ui.actionSave.triggered.connect(self.on_save)\\n\\n # Custom graph buttons\\n self.action_graph_reset.triggered.connect(self.reset_graph)\\n self.action_graph_full_extent.triggered.connect(self.full_extent)\\n\\n # Custom tools generated in visualize that are not actions\\n self.zoom_tool.wrap_sig.clicked.connect(self.process_zoom)\\n self.select_tool.wrap_sig.clicked.connect(self.process_select)\",\n \"def connect(self):\\n\\t\\tpass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def connect_data(self, detailed_signal, handler, *data, **kwargs): # reliably restored by inspect\\n pass\",\n \"def calculate_signals(self):\\n raise NotImplementedError(\\\"Should implement calculate_signals()\\\")\",\n \"def emit (self, signal):\\n for room in self.transmissionarea :\\n for listener in room.listeners:\\n listener.signalReceived(signal)\",\n \"def notifyObservers(self):\",\n \"def signalReceived (self, signal): \\n raise NotImplementedError(\\\"Lack of signalReceived method\\\")\",\n \"def _on_connect(self, component: \\\"Model\\\") -> None:\\n if self.circuit != component.circuit:\\n # make sure to merge the smaller circuit into the larger\\n if len(component.circuit) > len(self.circuit):\\n component.circuit._merge(self.circuit)\\n else:\\n self.circuit._merge(component.circuit)\",\n \"def connect(self, receiver, sender=ANY, weak=True, retval=False):\\n\\t\\trv = super(Signal, self).connect(receiver, sender, weak)\\n\\t\\tif retval and rv:\\n\\t\\t\\tsid = ANY_ID if sender is ANY else self.hashable_id(self.get_sender_id(sender))\\n\\t\\t\\tself._pipes[self.hashable_id(receiver)].add(sid)\\n\\t\\treturn rv\",\n \"def __init__(self):\\n # noinspection PyUnresolvedReferences\\n self._generic_signal.connect(self._generic_slot)\\n self._call_counters = {}\",\n \"def _connectSignals(self):\\r\\n self.imperial_button.clicked.connect(self._units_chosen)\\r\\n self.metric_button.clicked.connect(self._units_chosen)\\r\\n self.age_field.valueChanged.connect(self._age_changed)\\r\\n self.height_field.valueChanged.connect(self._height_changed)\\r\\n self.weight_field.valueChanged.connect(self._weight_changed)\\r\\n self.bodyFat_field.valueChanged.connect(self._bodyFat_changed)\\r\\n self.gender_combobox.currentIndexChanged.connect(self._gender_changed)\\r\\n self.calculate_button.clicked.connect(self._calculate_feedback)\",\n \"def test_allows_signal_handler_override(self):\\n self._signals_notified = False\\n b1 = Block()\\n self.configure_block(b1, {})\\n\\n self.assertFalse(self._signals_notified)\\n b1.notify_signals([Signal()])\\n self.assertTrue(self._signals_notified)\",\n \"def isSignal(self, p_int): # real signature unknown; restored from __doc__\\n return False\",\n \"def makeConnections(self):\\n\\t\\tself.connect(self.addTextureToOcc_btn, QtCore.SIGNAL(\\\"clicked()\\\"), self.addTextureToOcc)\\n\\t\\tself.connect(self.removeTextureToOcc_btn, QtCore.SIGNAL(\\\"clicked()\\\"), self.removeTextureToOcc)\\n\\t\\tself.connect(self.addIrisToOcc_btn, QtCore.SIGNAL(\\\"clicked()\\\"), self.addIrisToOcc)\\n\\t\\tself.connect(self.removeIrisToOcc_btn, QtCore.SIGNAL(\\\"clicked()\\\"), self.removeIrisToOcc)\\n\\t\\tself.connect(self.addHideOcc_btn, QtCore.SIGNAL(\\\"clicked()\\\"), self.addHideForOcc)\\n\\t\\tself.connect(self.removeHideOcc_btn, QtCore.SIGNAL(\\\"clicked()\\\"), self.removeHideForOcc)\",\n \"def connect(self):\\n for signal, models in six.iteritems(self._registry):\\n for model, keys in six.iteritems(models):\\n # Local function the current signal is going to be\\n # connected to.\\n # Defining it dynamically allows us to pass in the current\\n # set of keys for the given model, but we have to store\\n # a strong reference to it to avoid garbage collection.\\n def delete_cache(signal, sender=model, keys=keys):\\n cache.delete_many(list(keys))\\n signal.connect(delete_cache, sender=model, weak=False, dispatch_uid=signal)\",\n \"def connect(self, *args, **kwargs):\",\n \"def ready(self):\\n\\n from . import signals # noqa\",\n \"def connect(self) -> None:\\n ...\",\n \"def set_connected(self):\\n self.connected = True\",\n \"def connect(self):\\n raise NotImplementedError\",\n \"def connect(self):\\n raise NotImplementedError\",\n \"def signals(self):\\n if self._current_inputs is None:\\n raise RuntimeError(\\n 'Internal Error: The current inputs have not been properly '\\n 'generated. First call features_and_labels, then call signals.')\\n signals = self._current_inputs['signals']\\n self._current_inputs = None\\n return signals\",\n \"def _notifyConnect(self, function, **kwargs):\\n self._sig_connect.subscribe(function, **kwargs)\",\n \"def test_connection(self):\\n gen = self.create(GeneralizationItem)\\n c1 = self.create(ClassItem, UML.Class)\\n c2 = self.create(ClassItem, UML.Class)\\n\\n self.connect(gen, gen.tail, c1)\\n assert self.get_connected(gen.tail) is c1\\n\\n self.connect(gen, gen.head, c2)\\n assert gen.subject is not None\\n assert gen.subject.general is c2.subject\\n assert gen.subject.specific is c1.subject\",\n \"def checksignals(self):\\n if self.space.check_signal_action is not None:\\n self.space.check_signal_action.perform(self, None)\",\n \"def register(self):\\n REGISTERED_SIGNALS.setdefault(self.path, []).append(self)\",\n \"def setup(self):\\n\\t\\tif self.hasSignalModule and not self.signalsRegistered:\\n\\t\\t\\t# Jython does not support all signals, so we only use\\n\\t\\t\\t# the available ones\\n\\t\\t\\tsignals = ['SIGINT', 'SIGHUP', 'SIGABRT', 'SIGQUIT', 'SIGTERM']\\n\\t\\t\\timport signal\\n\\t\\t\\tfor sig in signals:\\n\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\tsignal.signal(getattr(signal, sig), self._shutdown)\\n\\t\\t\\t\\t\\tself.signalsRegistered.append(sig)\\n\\t\\t\\t\\texcept Exception as e:\\n\\t\\t\\t\\t\\tLogger.Err(\\\"[!] monitoring.Signals._registerSignals:%s %s\\\\n\\\" % (sig, e))\",\n \"def connected(self) -> bool:\\n raise NotImplementedError\",\n \"def Connected(self) -> bool:\",\n \"def Connected(self) -> bool:\",\n \"def send_connection_state(self, conn=None):\\n self.connection_state_signal.emit(conn)\",\n \"def test_connect(self):\\n mediator = Mediator()\\n mediator.connect(\\\"set_dog_sound\\\", self.dog.set_sound)\\n self.assertEquals([self.dog.set_sound], mediator.signals[\\\"set_dog_sound\\\"])\\n\\n mediator.connect(\\\"set_cat_sound\\\", self.cat.set_sound)\\n self.assertEquals([self.cat.set_sound], mediator.signals[\\\"set_cat_sound\\\"])\",\n \"def _create_connections(self):\\n # Level Size\\n self._level_size_x_spinbox.valueChanged.connect(self._set_x_size)\\n self._level_size_y_spinbox.valueChanged.connect(self._set_y_size)\\n self._level_size_z_spinbox.valueChanged.connect(self._set_z_size)\\n\\n # Minimum Length\\n self._minimum_length_checkbox.toggled.connect(self._checked_minimum)\\n self._minimum_length_spinbox.valueChanged.connect(self._set_minimum)\\n\\n # Maximum Length\\n self._maximum_length_checkbox.toggled.connect(self._checked_maximum)\\n self._maximum_length_spinbox.valueChanged.connect(self._set_maximum)\\n\\n # Seed\\n self._seed_checkbox.toggled.connect(self._checked_seed)\\n self._seed_le.textEdited.connect(self._set_seed)\\n \\n # Block Size\\n self._block_size_x_spinbox.valueChanged.connect(self._set_x_block_size)\\n self._block_size_y_spinbox.valueChanged.connect(self._set_y_block_size)\\n self._block_size_z_spinbox.valueChanged.connect(self._set_z_block_size)\\n\\n # Group Name\\n self._group_name_le.textEdited.connect(self._set_group_name)\\n\\n # Object Blocks\\n for blk_type in VALID_BLOCK_TYPES:\\n self._object_blocks[blk_type][\\\"pth_le\\\"].textEdited.connect(self._object_block_pth(blk_type))\\n self._object_blocks[blk_type][\\\"weight_spinbox\\\"].valueChanged.connect(self._object_block_weight(blk_type))\\n\\n # Buttons\\n self._cancel_btn.clicked.connect(self._cancel)\\n self._generate_btn.clicked.connect(self._generate)\",\n \"def connect(self):\\n return 1\",\n \"def test_get_signal(self):\\n\\n self.signal_getter.set_signal_source(MockSignalSource())\\n self.assertEqual(self.signal_getter.get_signal(), [0])\\n self.assertEqual(self.signal_getter.get_signal(), [1])\\n self.assertEqual(self.signal_getter.get_signal(), [2])\",\n \"def __connected(self):\\n self.connected()\\n if self.__callbacks.get(\\\"connected\\\"):\\n cb = self.__callbacks[\\\"connected\\\"]()\\n if cb is not None:\\n cb()\",\n \"def _connect_signals(self):\\n\\n # File menu\\n self.openConfigAction.triggered.connect(self.inputDataModule.on_open_config_clicked)\\n self.saveConfigAction.triggered.connect(self.inputDataModule.on_save_config_clicked)\\n self.openStatsAction.triggered.connect(self.on_open_stats_file_triggered)\\n self.openSpectrogramsAction.triggered.connect(self.on_open_spectrograms_file)\\n\\n # View menu\\n # self.showPlotScreen.triggered.connect(self.view_mod_stats_screening)\\n\\n # Process menu\\n self.processScreeningAction.triggered.connect(self.process_screening)\\n self.runIntegrationAction.triggered.connect(self.process_ts_integration)\\n self.calcSeascatterAction.triggered.connect(self.calc_seascatter)\\n self.calcTFAction.triggered.connect(self.calc_transfer_functions)\\n self.calcFatigueAction.triggered.connect(self.calc_fatigue)\\n\\n # Plot settings menu\\n # self.add2HIcon.triggered.connect(self.add_2h_icon)\\n self.loggerPlotSettingsAction.triggered.connect(self.on_logger_plot_settings_triggered)\\n self.spectPlotSettingsAction.triggered.connect(self.on_spect_plot_settings_triggered)\\n\\n # Export menu\\n self.exportScatterDiagAction.triggered.connect(self.on_export_scatter_diagram_triggered)\\n\\n # Azure menu\\n self.azureSettingsAction.triggered.connect(self.on_azure_account_settings_triggered)\\n\\n # Filter settings menu\\n self.filterSettingsAction.triggered.connect(self.on_filter_settings_triggered)\\n\\n # Help menu\\n self.helpAction.triggered.connect(self.show_help)\\n self.aboutAction.triggered.connect(self.show_about)\\n\\n # Toolbar dashboard buttons\\n self.projConfigButton.clicked.connect(self.view_proj_config_mod)\\n self.rawDataButton.clicked.connect(self.view_mod_raw_data)\\n self.dataQualityButton.clicked.connect(self.view_mod_data_quality)\\n self.statsScreeningButton.clicked.connect(self.view_mod_stats_screening)\\n self.spectralScreeningButton.clicked.connect(self.view_mod_spectral_screening)\\n self.histogramsButton.clicked.connect(self.view_mod_histograms)\\n self.seascatterButton.clicked.connect(self.view_mod_seascatter)\\n self.transFuncsButton.clicked.connect(self.view_mod_transfer_functions)\\n self.fatigueButton.clicked.connect(self.view_mod_fatigue)\",\n \"def enable_callbacks(self):\\n\\n onObjectUpdate_received = self.message_handler.register('ObjectUpdate')\\n onObjectUpdate_received.subscribe(self.onObjectUpdate)\\n\\n onObjectUpdateCached_received = self.message_handler.register('ObjectUpdateCached')\\n onObjectUpdateCached_received.subscribe(self.onObjectUpdateCached)\\n\\n onObjectUpdateCompressed_received = self.message_handler.register('ObjectUpdateCompressed')\\n onObjectUpdateCompressed_received.subscribe(self.onObjectUpdateCompressed)\\n\\n onImprovedTerseObjectUpdate_received = self.message_handler.register('ImprovedTerseObjectUpdate')\\n onImprovedTerseObjectUpdate_received.subscribe(self.onImprovedTerseObjectUpdate)\\n \\n onObjectProperties_received = self.message_handler.register('ObjectProperties')\\n onObjectProperties_received.subscribe(self.onObjectProperties)\\n\\n onKillObject_received = self.message_handler.register('KillObject')\\n onKillObject_received.subscribe(self.onKillObject)\\n\\n # uncomment these to view packets sent back to simulator\\n # onObjectName_sent = self.message_handler.register('ObjectName')\\n # onObjectName_sent.subscribe(self.helpers.log_packet, self)\\n\\n # onDeRezObject_sent = self.message_handler.register('DeRezObject')\\n # onDeRezObject_sent.subscribe(self.helpers.log_packet, self)\",\n \"def empty_signal(self, *args, **kwargs):\\n pass\",\n \"def __init__(self, connected=True):\\n self._connected = connected\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68499154","0.68350697","0.68350697","0.68059605","0.68059605","0.66427344","0.660732","0.6563658","0.64170116","0.63776684","0.63700235","0.634242","0.6340475","0.6244015","0.6181083","0.6158528","0.61514074","0.61073714","0.61058384","0.61058384","0.6036816","0.603572","0.60286546","0.6006002","0.60038084","0.5983616","0.5937282","0.59168774","0.58930343","0.58856696","0.5876272","0.5873898","0.5872325","0.58666795","0.5842597","0.58239424","0.58239424","0.58239424","0.58239424","0.58239424","0.58239424","0.58239424","0.58239424","0.58020425","0.57926685","0.57791394","0.57676464","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57652277","0.57543427","0.5754058","0.5751098","0.5742234","0.5738409","0.5731877","0.57276237","0.57274264","0.5714909","0.5709014","0.5690365","0.5684259","0.56765723","0.5675369","0.567327","0.5672332","0.5665568","0.5665568","0.5662785","0.56515527","0.5646576","0.56411576","0.5640453","0.56270295","0.56165224","0.56139976","0.56139976","0.56103307","0.5609851","0.56092954","0.560416","0.56028426","0.5597763","0.55939853","0.5591203","0.55795705","0.5569821"],"string":"[\n \"0.68499154\",\n \"0.68350697\",\n \"0.68350697\",\n \"0.68059605\",\n \"0.68059605\",\n \"0.66427344\",\n \"0.660732\",\n \"0.6563658\",\n \"0.64170116\",\n \"0.63776684\",\n \"0.63700235\",\n \"0.634242\",\n \"0.6340475\",\n \"0.6244015\",\n \"0.6181083\",\n \"0.6158528\",\n \"0.61514074\",\n \"0.61073714\",\n \"0.61058384\",\n \"0.61058384\",\n \"0.6036816\",\n \"0.603572\",\n \"0.60286546\",\n \"0.6006002\",\n \"0.60038084\",\n \"0.5983616\",\n \"0.5937282\",\n \"0.59168774\",\n \"0.58930343\",\n \"0.58856696\",\n \"0.5876272\",\n \"0.5873898\",\n \"0.5872325\",\n \"0.58666795\",\n \"0.5842597\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58239424\",\n \"0.58020425\",\n \"0.57926685\",\n \"0.57791394\",\n \"0.57676464\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57652277\",\n \"0.57543427\",\n \"0.5754058\",\n \"0.5751098\",\n \"0.5742234\",\n \"0.5738409\",\n \"0.5731877\",\n \"0.57276237\",\n \"0.57274264\",\n \"0.5714909\",\n \"0.5709014\",\n \"0.5690365\",\n \"0.5684259\",\n \"0.56765723\",\n \"0.5675369\",\n \"0.567327\",\n \"0.5672332\",\n \"0.5665568\",\n \"0.5665568\",\n \"0.5662785\",\n \"0.56515527\",\n \"0.5646576\",\n \"0.56411576\",\n \"0.5640453\",\n \"0.56270295\",\n \"0.56165224\",\n \"0.56139976\",\n \"0.56139976\",\n \"0.56103307\",\n \"0.5609851\",\n \"0.56092954\",\n \"0.560416\",\n \"0.56028426\",\n \"0.5597763\",\n \"0.55939853\",\n \"0.5591203\",\n \"0.55795705\",\n \"0.5569821\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":13098,"cells":{"query":{"kind":"string","value":"Exit on error trying to get the input signal."},"document":{"kind":"string","value":"def test_exit_on_input_signal_error(input_block, kwargs):\n input_block.side_effect = Exception()\n with pytest.raises(SystemExit) as exc_info:\n create_flow(**kwargs)\n assert exc_info.value.code == 1"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def call_error():\r\n print(\"Error in input format.\")\r\n sys.exit()","def signal_handler(sig, frame):\n raise ExitException()","def handle_sigterm(signum, frame):\n raise TermException","def signal_handler(signum, frame):\n sys.exit(0)","def _signal_handler(signum, frame):\n res_mgr()\n sys.exit(0)","def handler(signum, frame):\n print(\"Signal handler called with signal %i\" % signum)\n sys.exit(-1)","def signal_handler(sig, frame):\n sys.exit(0)","def signal_handler(self, signal_number, frame):\n sys.exit(0)","def signal_handler(signal, frame):\n sys.exit(0)","def signal_handler(signal, frame):\n sys.exit(0)","def signal_handler(signal, frame):\n sys.exit(0)","def error_handler(num, err):\n print(\"Error in input {}\".format(num))\n err = err.decode()\n raise Exception(err)","def handle_sigint(signum, frame):\n print(\"\\nInterrupted by SIGINT\\n\")\n sys.exit()","def signal_handler(self, signum):\n raise Exception(\"Caught signal {0}\".format(signum))","def test_getsignal(self):\n from signal import getsignal, signal, SIGINT, SIG_DFL, SIG_IGN\n\n def handler(*a):\n pass\n\n try:\n assert getsignal(SIGINT) == SIG_DFL\n signal(SIGINT, SIG_DFL)\n assert getsignal(SIGINT) == SIG_DFL\n signal(SIGINT, SIG_IGN)\n assert getsignal(SIGINT) == SIG_IGN\n signal(SIGINT, handler)\n assert getsignal(SIGINT) is handler\n finally:\n signal(SIGINT, SIG_DFL)","def handle_err(self):\n pass","def safe_input():\n try:\n input(\"Please enter something: \")\n except EOFError:\n return None\n except KeyboardInterrupt:\n return None","def _sigterm_handler(signum: int, _frame: FrameType) -> None:\n sys.exit('from sigterm handler')","def error_received(self, exc):\n print('Error received:', exc)","def error(self, message):\n self.exit(2, f\"Input error: {message}\\n\")","def signal_oi(self):\n pass","def test_invalid_signal(self):\n mediator = Mediator()\n\n try:\n mediator.signal(\"foo\")\n except:\n raise AssertionError()","def _handle_term_signal(self, sig: int, frame: FrameType) -> None:\n del sig, frame # Unused.\n raise SystemExit()","def test_signal_interruption(self):\n process = Popen(\n [STRATIS_CLI, \"pool\", \"create\",\n p_n(), DISKS[0]],\n stdout=PIPE,\n stderr=PIPE,\n close_fds=True,\n env=os.environ)\n time.sleep(0.05)\n process.send_signal(2)\n result = process.communicate()\n stdout_text = \"\"\n stderr_text = \"\"\n if result[0]:\n stdout_text = bytes(result[0]).decode(\"utf-8\")\n if result[1]:\n stderr_text = bytes(result[1]).decode(\"utf-8\")\n\n self.assertTrue(\"Traceback\" not in stdout_text)\n self.assertTrue(\"Traceback\" not in stderr_text)\n self.assertNotEqual(process.returncode, 0)","def _handle_interrupts(signal_number, current_stack_frame):\n print(\" Interrupted!\\n\", file=sys.stderr)\n _display_help()\n sys.exit(1) # no match","def abort() -> NoReturn:\n raise AbortSignal","def handler(signum, frame):\n m.signal()","def SIGINT_handler(signal, frame):\n exit(2)","def error():\n return None","def test_get_input_signal(network_with_devices):\n network = network_with_devices\n devices = network.devices\n names = devices.names\n\n [SW1_ID, SW2_ID, OR1_ID, I1, I2] = names.lookup([\"Sw1\", \"Sw2\", \"Or1\", \"I1\",\n \"I2\"])\n # Inputs are unconnected, get_input_signal should return None\n assert network.get_input_signal(OR1_ID, I1) is None\n assert network.get_input_signal(OR1_ID, I2) is None\n\n # Make connections\n network.make_connection(SW1_ID, None, OR1_ID, I1)\n network.make_connection(SW2_ID, None, OR1_ID, I2)\n\n # Set Sw2 output to HIGH\n switch2 = devices.get_device(SW2_ID)\n switch2.outputs[None] = devices.HIGH\n\n assert network.get_input_signal(OR1_ID, I1) == devices.LOW\n assert network.get_input_signal(OR1_ID, I2) == devices.HIGH","def get_input(self):\n if self.input_asked:\n return self.retrieved_input\n else:\n raise PInputInputNotEnteredExeception()","def signal_handler(*unused_argvs):\n sys.stderr.write(\"\\nCtrl^C caught, bailing...\\n\")\n sys.exit(0)","def sigterm(signum, frame):\n loop.stop()","def clean_input(prompt):\n try:\n return input(prompt)\n # There is a general handling of KeyboardInterrupt in main() but\n # here it leads to a cleaner exit as the option to quit is returned.\n except KeyboardInterrupt:\n return 'Quit'","def error(err):\n print(\"ERROR: \" + err)\n avrprog.end()\n while True:\n pass","def catch_keyboard_interrupt() -> Callable:\n return signal.signal(signal.SIGINT, keyboard_interrupt_handler)","def sig_exit_gracefully(cursignal, frame):\n print(\"Exiting in a Graceful way sig=\", cursignal, frame)\n traceback.print_exc(file=sys.stdout)\n #for c in mac_targets.values():\n # try:\n # c.set_var(0)\n # except Exception, x:\n # print \"Exception:\", x\n sys.stdout.flush()\n sys.stderr.flush()\n sys.exit(0)","def signal_kernel(self, signum: int):","def __get_correct_input(self):\n\t\twhile True:\n\t\t\ttemp = input(f'Next Temperature: (or {self.__QUIT_COMMAND} to quit)? ')\n\t\t\ttry:\n\t\t\t\treturn int(temp)\n\t\t\texcept ValueError:\n\t\t\t\tprint('The input is not valid')","def signal(self):\n pass","def _sigterm_handler(signum, stackframe):\n if signum == signal.SIGTERM:\n raise SigTermException","def _handle_interrupts(signal_number, current_stack_frame):\n print(\" Interrupted!\\n\", file=sys.stderr)\n _display_help()\n sys.exit(0)","def mic_input():\n try:\n r = sr.Recognizer()\n with sr.Microphone() as source:\n print('Say something...')\n r.pause_threshold = 1\n r.adjust_for_ambient_noise(source, duration=1)\n audio = r.listen(source)\n try:\n command = r.recognize_google(audio).lower()\n print('You said: ' + command + '\\n')\n except sr.UnknownValueError:\n print('....')\n command = self.mic_input()\n return command\n except Exception as e:\n print(e)\n return False","def raxmlInputErrorHandling(self):\n try:\n # input alignment for raxml\n self.raxmlOperations.inputFilename = self.checkEntryPopulated(self.inputFileEntry, errorTitle='Missing Alignment', errorMessage='Please select an alignment.')\n self.raxmlOperations.windowSize = self.checkEntryInRange(self.windowSizeEntry, min=0, inclusive=False, errorTitle='Invalid Window Size', errorMessage='Window size needs to be a positive integer.')\n self.raxmlOperations.windowOffset = self.checkEntryInRange(self.windowOffsetEntry, min=0, inclusive=False, errorTitle='Invalid Window Offset', errorMessage='Window offset needs to be a positive integer.')\n self.raxmlOperations.outGroup = self.outgroupComboBox.currentText()\n self.raxmlOperations.model = self.modelComboBox.currentText()\n self.raxmlOperations.isCustomRaxmlCommand = self.checkBoxCustomRaxml.isChecked()\n self.raxmlOperations.bootstrap = self.checkboxBootstrap.isChecked()\n self.raxmlOperations.rooted = self.checkboxRooted.isChecked()\n self.rooted = self.checkboxRooted.isChecked()\n\n # if user is generating Top Topologies or scatter plot or donut plor or circle graph run error handling on top topologies entry\n if self.checkboxAllTrees.isChecked() or self.checkboxScatterPlot.isChecked() or self.checkboxDonutPlot.isChecked():\n self.checkEntryPopulated(self.numberOfTopTopologiesEntry, errorTitle='Number of Top Topologies Field is Blank', errorMessage='Please enter a number of top topologies.')\n self.topTopologies = self.checkEntryInRange(self.numberOfTopTopologiesEntry, min=0, max=16, inclusive=False, errorTitle='Invalid Number of Top Topologies', errorMessage='Please enter an integer between 0 and 15.')\n\n # bootstrap error handling\n self.raxmlOperations.numBootstraps = 0\n if self.checkboxBootstrap.isChecked():\n self.confidenceLevel = self.checkEntryInRange(self.confidenceLevelEntry, min=0, max=100, errorTitle='Invalid Confidence Level', errorMessage='Please enter an integer between 0 and 100.')\n self.raxmlOperations.numBootstraps = self.checkEntryInRange(self.numberOfBootstrapsEntry, min=2, errorTitle='Invalid Number of Bootstraps', errorMessage='Please enter an integer greater than 1.')\n\n # if using custom rax -- make sure that the user doesn't use the -s or -n flags\n if self.checkBoxCustomRaxml.isChecked():\n self.raxmlOperations.customRaxmlCommand = self.checkEntryPopulated(self.customRaxmlCommandEntry, errorTitle='No RAxML Command', errorMessage='Please enter a custom raxml command or uncheck the box.')\n if re.search('([\\-][n])|([\\-][s])', self.customRaxmlCommandEntry.text()):\n raise ValueError, ('Invalid RAxML Command', 'Please do not specify the -s or -n flags.', 'the -s and -n flags will be handled internally based on the alignment you input.')\n\n # species tree error handling\n if self.speciesTreeEntry.text() != \"\" and self.newickFileEntry.text() != \"\":\n raise ValueError, ('Multiple Species Trees', 'You have both selected a species tree file and entered a species tree. Please only do one.', 'Both the \"Species Tree File and \"Enter Species Tree\" fields are populated. Please only use one.')\n\n # if the user selects either statistic plot -- open the inputted newick and read it into memory as a string on a single line\n if self.checkboxRobinsonFoulds.isChecked() or self.checkboxPGTST.isChecked():\n if self.newickFileEntry.text() != \"\":\n self.newickFileName = self.checkEntryPopulated(self.newickFileEntry, errorTitle='Missing Species Tree', errorMessage='Please select a species tree.', errorDescription='Please select a species tree.')\n with open(self.newickFileEntry.text(), 'r') as f:\n self.speciesTree = f.read().replace('\\n', '')\n else:\n self.speciesTree = self.checkEntryPopulated(self.speciesTreeEntry, errorTitle='Missing Species Tree', errorMessage='Please select a species tree.', errorDescription='Please select a species tree.')\n\n\n except ValueError, (ErrorTitle, ErrorMessage, ErrorDescription):\n self.message(str(ErrorTitle), str(ErrorMessage), str(ErrorDescription))\n return False\n\n return True","def checkInterrupt():\n if wasInterrupted():\n raise KeyboardInterrupt()","def _syringeErrorHandler(self):\n try:\n yield\n except SyringeError, e:\n if e.err_code == 7:\n last_cmd = self.last_cmd\n try:\n self.init()\n except SyringeError, e:\n if e.err_code == 7:\n pass\n else:\n raise e\n self.waitReady()\n self.sendRcv(last_cmd)\n else:\n self.resetChain()\n raise e\n except Exception, e:\n self.resetChain()\n raise e","def test_validate_input_rejection(self):\n with nose.assert_raises(exceptions.RejectionError):\n self.dtm1.validate_input('000011')","def test_read_one_signal_failure(self):\n cwd = os.path.dirname(os.path.abspath(__file__))\n dir1 = os.path.join(cwd, 'test_files/')\n dir2 = '/home/tomas/here-be-dragons/'\n signal1 = read_signal(dir1, 'here-be-dragons')\n signal2 = read_signal(dir2, 'test3')\n self.assertIsNone(signal1)\n self.assertIsNone(signal2)","def get_input(label):\n result = input(label)\n sounds.play_input_beep()\n return result","def interrupt_handler(signum, frame): #pylint: disable=W0613\n cleanup()\n sys.exit(-2) # Terminate process here as catching the signal\n # removes the close process behaviour of Ctrl-C","def all_exception_handler(handler_input, exception):\n # type: (HandlerInput, Exception) -> None\n print(\"Encountered following exception: {}\".format(exception))\n\n speech = \"Sorry, there was some problem. Please try again!!\"\n handler_input.response_builder.speak(speech).ask(speech)\n\n return handler_input.response_builder.response","def unhandled(self):\n return True","def chk_stdin(self):\t# check keyboard input\n\t\tdr, dw, de = select([sys.stdin], [], [], 0)\n\t\treturn dr","def sigint_handler(*args):\n sys.stderr.write('\\r')\n QtGui.QApplication.quit()","def test_ignore_return(self):\n from signal import signal, SIGINT, SIG_DFL, SIG_IGN\n\n try:\n for handler in SIG_DFL, SIG_IGN, lambda *a: None:\n signal(SIGINT, SIG_IGN)\n assert signal(SIGINT, handler) == SIG_IGN\n finally:\n signal(SIGINT, SIG_DFL)","def exit_on_error(self) -> None:\n if self.errors:\n sys.exit(1)","def handle_sigint(self, signum, frame):\n self.finish()\n self.original_handler(signum, frame)","def signal_handler(sig_num, frame):\n global exit_flag\n logger.warn('Signal Recieved: {}'.format(str(sig_num)))\n if sig_num:\n exit_flag = True","def cont():\n\n try:\n input = raw_input()\n except Exception:\n pass","def __exit_condition(data_logger):\n try:\n while True:\n raw_input(\"\") # FIXME: is raw_input the right approach\n if CLOSE:\n raise KeyboardInterrupt()\n\n except (KeyboardInterrupt, EOFError):\n sys.stdin.close()\n data_logger.stop()","def signal_kernel(self, signum):\n pass","def die_screaming(instr):\n LOG.error(instr)\n sys.exit(1)","def die_screaming(instr):\n LOG.error(instr)\n sys.exit(1)","def handler(signum, frame):\n logging.warning(\"Got a {} signal. Doing nothing\".format(signum))","def _exit_gracefully(self, signum, frame):\n self.log.info(\"Exiting gracefully upon receiving signal %s\", signum)\n self.log.debug(\"Current Stacktrace is: %s\", \"\\n\".join(map(str, inspect.stack())))\n self.terminate()\n self.end()\n self.log.debug(\"Finished terminating DAG processors.\")\n sys.exit(os.EX_OK)","def _signal_handler(signalnum: int, _: Any) -> None:\n logger.info('Received signal: {0}', signal.Signals(signalnum).name)\n # safely close video stream & writer\n stream.stop()\n writer.close()\n sys.exit(0)","def signal_handler(signal, frame):\n print()\n endProgram(0)","def interrupted(self):\n pass","def inConnectionLost(self):\n self.logger('stdin closed by process %d' % self._pid)","def input_(text=''):\n while True:\n try:\n thing = input(text)\n if thing == '':\n raise ValueError\n else:\n return thing\n except (EOFError, KeyboardInterrupt, ValueError):\n print()","def handle_expt(self):\r\n self._perform_on_error_handling()","def _signal_handler(*args):\n self._user_exit = True","def signal_handler(signal_number, stack_frame):\n if signal_number in [signal.SIGTERM, signal.SIGINT]:\n terminate_surveillance()","def keyboard_interrupt_handler(interrupt_signal, frame):\n print(\"Scanning finished\")\n print(\"KeyboardInterrupt ID: {} {} has been caught.\".format(interrupt_signal, frame))\n exit(1)","def keyboard_interrupt_handler(interrupt_signal, frame):\n print(\"Scanning finished\")\n print(\"KeyboardInterrupt ID: {} {} has been caught.\".format(interrupt_signal, frame))\n exit(1)","def ask_numbers(question, error):\n while True:\n value = 0\n try:\n value = int(input(question))\n except ValueError:\n print(error)\n except UnboundLocalError:\n print(error)\n except Exception:\n print(error)\n if value <= 0:\n print(\"Syötä positiivinen luku, joka on suurempi kuin 0\\n->\")\n else:\n break\n return value","def test_default_return(self):\n from signal import signal, SIGINT, SIG_DFL, SIG_IGN\n\n try:\n for handler in SIG_DFL, SIG_IGN, lambda *a: None:\n signal(SIGINT, SIG_DFL)\n assert signal(SIGINT, handler) == SIG_DFL\n finally:\n signal(SIGINT, SIG_DFL)","def _sigint(self, signal, frame):\n self.disconnect = True\n if self.cardinal:\n self.cardinal.quit('Received SIGINT.')","def do_input_events(self):\r\n for event in EventStream.allNext(self.streams):\r\n if self.handler.event(event) and self.unhandledHandler:\r\n self.unhandledHandler(event)","def sighandler(signum, frame):\n global _terminate\n global _interruptcnt\n print >> FileKeyUtils.WMSlog, 'sighandler> ', signum\n ++_interruptcnt \n if signum in(signal.SIGABRT, signal.SIGINT, signal.SIGTERM):\n print >> FileKeyUtils.WMSlog, 'sighandler> terminate pid: ', os.getpid(), signum\n _terminate = True\n elif signum in(signal.SIGHUP, signal.SIGTSTP):\n print >> FileKeyUtils.WMSlog, 'sighandler> suspend/stop/pause pid: ', os.getpid(), signum\n signal.pause()\n else:\n print >> FileKeyUtils.WMSlog, 'sighandler> resume/continue pid: ', os.getpid(), signum\n _terminate = False","def haltExec(self, input_pin=0):\n if not 0 <= input_pin < 2:\n raise(ValueError('`input_pin` [{0}] must be between 0 and 2'\n ''.format(input_sig)))\n cmd_string = 'H{0}'.format(input_sig)\n return self.sendRcv(cmd_string)","def ERR(self):","def test_init(self):\n nt.assert_raises(Exception, CisInterface.CisInput, 'error')","def handle_exception(e):\n print(e)\n return error()","def signal_handler(signum, frame):\n monitor.stop()\n sys.exit(0)","def gracefulexit(signalnumber, frame):\n\t\n\tsys.exit(0) # resources will be closed on their corresponding finally blocks","def src_error(state):\n return _lib.src_error(state) if state else None","def _cmd_exit(self):\n raise EOFError()","def _termination_handler(self, signum, frame):\n print '[i] Shutting down...'\n self.sensor.close()\n sys.exit(1)","def _readsignal(self, signame):\n try:\n signal = self.tree.getNode(signame)\n except AttributeError:\n signal = self.tree.get(signame)\n return signal","def signal_handler(signal, frame): \n import signal\n import sys\n from time import localtime, strftime\n time = strftime(\"%H:%M:%S\", localtime())\n sel = raw_input('\\n\\n%s: Paused. Press return to resume, or type exit to quit: \\n' % time)\n if sel.startswith('e') or sel.startswith('E'):\n sys.exit(0)\n else:\n time = strftime(\"%H:%M:%S\", localtime())\n print '%s: Interrogation resumed.\\n' % time","def caught_signal(\n self, signals: int, max_signals: int, executor: \"TaskGraphExecutor\"\n ) -> None:","def interrupt_handler(signum, frame):\n if DOCKER_MONITOR:\n util.log.warning(\"Signal %d received - Tearing down monitoring\"\n % (signum))\n DOCKER_MONITOR.tear_down_all()\n sys.exit(0)","def error(self):\n pass","def sigHandler(sig, frame):\n # pylint: disable=unused-argument\n shutdown()\n sys.exit(0)","def test_signal_no_pid(self):\n code, out, err = self.t.runError(\"--pid 0\")\n self.assertIn(\"A non-zero PID must be specified.\", out)","def main():\n os.write(2,bytes(process_infos(sys.argv[0])+\"\\n\",'utf-8'))\n # Some signals of interest. Extend the list at will...\n signal.signal(signal.SIGALRM,sigtrace_handler)\n signal.signal(signal.SIGUSR1,sigtrace_handler)\n signal.signal(signal.SIGUSR2,sigtrace_handler)\n signal.signal(signal.SIGINT,sigtrace_handler)\n signal.signal(signal.SIGTERM,sigtrace_handler)\n signal.signal(signal.SIGCONT,sigtrace_handler)\n signal.signal(signal.SIGTSTP,sigtrace_handler)\n signal.signal(signal.SIGTTOU,sigtrace_handler)\n signal.signal(signal.SIGTTIN,sigtrace_handler)\n signal.signal(signal.SIGHUP,sigtrace_handler)\n\n\n while True:\n # Receiving a signal while in select will raise an exception\n try:\n # Wait for new input for at most one second\n rrdy,wrdy,erdy = select.select([sys.stdin],[],[],1.0)\n if len(rrdy) > 0:\n # select returns with stdin ready (before one second)\n buf = os.read(0,1024)\n os.write(1, bytes(sys.argv[0]+\":\",'utf-8')+buf)\n else:\n # select return with nothing to read on stdin\n os.write(1,bytes(sys.argv[0]+\"\\n\",\"utf-8\"))\n except InterruptedError:\n # select interrupted by signal: simply ignore and proceed\n pass","def __call__(self, *args):\n if not args:\n return self._get_value()\n else:\n raise RuntimeError('Can only set signal values of InputSignal objects, '\n 'which signal %r is not.' % self._name)","def error_handler(self):\n if self.ctx.exit_code is not None:\n return self.ctx.exit_code","def sig_handler(sig, frame):\n if sig == signal.SIGINT:\n stop_ros()\n print(\"Shutting down...\")\n sys.exit(0)"],"string":"[\n \"def call_error():\\r\\n print(\\\"Error in input format.\\\")\\r\\n sys.exit()\",\n \"def signal_handler(sig, frame):\\n raise ExitException()\",\n \"def handle_sigterm(signum, frame):\\n raise TermException\",\n \"def signal_handler(signum, frame):\\n sys.exit(0)\",\n \"def _signal_handler(signum, frame):\\n res_mgr()\\n sys.exit(0)\",\n \"def handler(signum, frame):\\n print(\\\"Signal handler called with signal %i\\\" % signum)\\n sys.exit(-1)\",\n \"def signal_handler(sig, frame):\\n sys.exit(0)\",\n \"def signal_handler(self, signal_number, frame):\\n sys.exit(0)\",\n \"def signal_handler(signal, frame):\\n sys.exit(0)\",\n \"def signal_handler(signal, frame):\\n sys.exit(0)\",\n \"def signal_handler(signal, frame):\\n sys.exit(0)\",\n \"def error_handler(num, err):\\n print(\\\"Error in input {}\\\".format(num))\\n err = err.decode()\\n raise Exception(err)\",\n \"def handle_sigint(signum, frame):\\n print(\\\"\\\\nInterrupted by SIGINT\\\\n\\\")\\n sys.exit()\",\n \"def signal_handler(self, signum):\\n raise Exception(\\\"Caught signal {0}\\\".format(signum))\",\n \"def test_getsignal(self):\\n from signal import getsignal, signal, SIGINT, SIG_DFL, SIG_IGN\\n\\n def handler(*a):\\n pass\\n\\n try:\\n assert getsignal(SIGINT) == SIG_DFL\\n signal(SIGINT, SIG_DFL)\\n assert getsignal(SIGINT) == SIG_DFL\\n signal(SIGINT, SIG_IGN)\\n assert getsignal(SIGINT) == SIG_IGN\\n signal(SIGINT, handler)\\n assert getsignal(SIGINT) is handler\\n finally:\\n signal(SIGINT, SIG_DFL)\",\n \"def handle_err(self):\\n pass\",\n \"def safe_input():\\n try:\\n input(\\\"Please enter something: \\\")\\n except EOFError:\\n return None\\n except KeyboardInterrupt:\\n return None\",\n \"def _sigterm_handler(signum: int, _frame: FrameType) -> None:\\n sys.exit('from sigterm handler')\",\n \"def error_received(self, exc):\\n print('Error received:', exc)\",\n \"def error(self, message):\\n self.exit(2, f\\\"Input error: {message}\\\\n\\\")\",\n \"def signal_oi(self):\\n pass\",\n \"def test_invalid_signal(self):\\n mediator = Mediator()\\n\\n try:\\n mediator.signal(\\\"foo\\\")\\n except:\\n raise AssertionError()\",\n \"def _handle_term_signal(self, sig: int, frame: FrameType) -> None:\\n del sig, frame # Unused.\\n raise SystemExit()\",\n \"def test_signal_interruption(self):\\n process = Popen(\\n [STRATIS_CLI, \\\"pool\\\", \\\"create\\\",\\n p_n(), DISKS[0]],\\n stdout=PIPE,\\n stderr=PIPE,\\n close_fds=True,\\n env=os.environ)\\n time.sleep(0.05)\\n process.send_signal(2)\\n result = process.communicate()\\n stdout_text = \\\"\\\"\\n stderr_text = \\\"\\\"\\n if result[0]:\\n stdout_text = bytes(result[0]).decode(\\\"utf-8\\\")\\n if result[1]:\\n stderr_text = bytes(result[1]).decode(\\\"utf-8\\\")\\n\\n self.assertTrue(\\\"Traceback\\\" not in stdout_text)\\n self.assertTrue(\\\"Traceback\\\" not in stderr_text)\\n self.assertNotEqual(process.returncode, 0)\",\n \"def _handle_interrupts(signal_number, current_stack_frame):\\n print(\\\" Interrupted!\\\\n\\\", file=sys.stderr)\\n _display_help()\\n sys.exit(1) # no match\",\n \"def abort() -> NoReturn:\\n raise AbortSignal\",\n \"def handler(signum, frame):\\n m.signal()\",\n \"def SIGINT_handler(signal, frame):\\n exit(2)\",\n \"def error():\\n return None\",\n \"def test_get_input_signal(network_with_devices):\\n network = network_with_devices\\n devices = network.devices\\n names = devices.names\\n\\n [SW1_ID, SW2_ID, OR1_ID, I1, I2] = names.lookup([\\\"Sw1\\\", \\\"Sw2\\\", \\\"Or1\\\", \\\"I1\\\",\\n \\\"I2\\\"])\\n # Inputs are unconnected, get_input_signal should return None\\n assert network.get_input_signal(OR1_ID, I1) is None\\n assert network.get_input_signal(OR1_ID, I2) is None\\n\\n # Make connections\\n network.make_connection(SW1_ID, None, OR1_ID, I1)\\n network.make_connection(SW2_ID, None, OR1_ID, I2)\\n\\n # Set Sw2 output to HIGH\\n switch2 = devices.get_device(SW2_ID)\\n switch2.outputs[None] = devices.HIGH\\n\\n assert network.get_input_signal(OR1_ID, I1) == devices.LOW\\n assert network.get_input_signal(OR1_ID, I2) == devices.HIGH\",\n \"def get_input(self):\\n if self.input_asked:\\n return self.retrieved_input\\n else:\\n raise PInputInputNotEnteredExeception()\",\n \"def signal_handler(*unused_argvs):\\n sys.stderr.write(\\\"\\\\nCtrl^C caught, bailing...\\\\n\\\")\\n sys.exit(0)\",\n \"def sigterm(signum, frame):\\n loop.stop()\",\n \"def clean_input(prompt):\\n try:\\n return input(prompt)\\n # There is a general handling of KeyboardInterrupt in main() but\\n # here it leads to a cleaner exit as the option to quit is returned.\\n except KeyboardInterrupt:\\n return 'Quit'\",\n \"def error(err):\\n print(\\\"ERROR: \\\" + err)\\n avrprog.end()\\n while True:\\n pass\",\n \"def catch_keyboard_interrupt() -> Callable:\\n return signal.signal(signal.SIGINT, keyboard_interrupt_handler)\",\n \"def sig_exit_gracefully(cursignal, frame):\\n print(\\\"Exiting in a Graceful way sig=\\\", cursignal, frame)\\n traceback.print_exc(file=sys.stdout)\\n #for c in mac_targets.values():\\n # try:\\n # c.set_var(0)\\n # except Exception, x:\\n # print \\\"Exception:\\\", x\\n sys.stdout.flush()\\n sys.stderr.flush()\\n sys.exit(0)\",\n \"def signal_kernel(self, signum: int):\",\n \"def __get_correct_input(self):\\n\\t\\twhile True:\\n\\t\\t\\ttemp = input(f'Next Temperature: (or {self.__QUIT_COMMAND} to quit)? ')\\n\\t\\t\\ttry:\\n\\t\\t\\t\\treturn int(temp)\\n\\t\\t\\texcept ValueError:\\n\\t\\t\\t\\tprint('The input is not valid')\",\n \"def signal(self):\\n pass\",\n \"def _sigterm_handler(signum, stackframe):\\n if signum == signal.SIGTERM:\\n raise SigTermException\",\n \"def _handle_interrupts(signal_number, current_stack_frame):\\n print(\\\" Interrupted!\\\\n\\\", file=sys.stderr)\\n _display_help()\\n sys.exit(0)\",\n \"def mic_input():\\n try:\\n r = sr.Recognizer()\\n with sr.Microphone() as source:\\n print('Say something...')\\n r.pause_threshold = 1\\n r.adjust_for_ambient_noise(source, duration=1)\\n audio = r.listen(source)\\n try:\\n command = r.recognize_google(audio).lower()\\n print('You said: ' + command + '\\\\n')\\n except sr.UnknownValueError:\\n print('....')\\n command = self.mic_input()\\n return command\\n except Exception as e:\\n print(e)\\n return False\",\n \"def raxmlInputErrorHandling(self):\\n try:\\n # input alignment for raxml\\n self.raxmlOperations.inputFilename = self.checkEntryPopulated(self.inputFileEntry, errorTitle='Missing Alignment', errorMessage='Please select an alignment.')\\n self.raxmlOperations.windowSize = self.checkEntryInRange(self.windowSizeEntry, min=0, inclusive=False, errorTitle='Invalid Window Size', errorMessage='Window size needs to be a positive integer.')\\n self.raxmlOperations.windowOffset = self.checkEntryInRange(self.windowOffsetEntry, min=0, inclusive=False, errorTitle='Invalid Window Offset', errorMessage='Window offset needs to be a positive integer.')\\n self.raxmlOperations.outGroup = self.outgroupComboBox.currentText()\\n self.raxmlOperations.model = self.modelComboBox.currentText()\\n self.raxmlOperations.isCustomRaxmlCommand = self.checkBoxCustomRaxml.isChecked()\\n self.raxmlOperations.bootstrap = self.checkboxBootstrap.isChecked()\\n self.raxmlOperations.rooted = self.checkboxRooted.isChecked()\\n self.rooted = self.checkboxRooted.isChecked()\\n\\n # if user is generating Top Topologies or scatter plot or donut plor or circle graph run error handling on top topologies entry\\n if self.checkboxAllTrees.isChecked() or self.checkboxScatterPlot.isChecked() or self.checkboxDonutPlot.isChecked():\\n self.checkEntryPopulated(self.numberOfTopTopologiesEntry, errorTitle='Number of Top Topologies Field is Blank', errorMessage='Please enter a number of top topologies.')\\n self.topTopologies = self.checkEntryInRange(self.numberOfTopTopologiesEntry, min=0, max=16, inclusive=False, errorTitle='Invalid Number of Top Topologies', errorMessage='Please enter an integer between 0 and 15.')\\n\\n # bootstrap error handling\\n self.raxmlOperations.numBootstraps = 0\\n if self.checkboxBootstrap.isChecked():\\n self.confidenceLevel = self.checkEntryInRange(self.confidenceLevelEntry, min=0, max=100, errorTitle='Invalid Confidence Level', errorMessage='Please enter an integer between 0 and 100.')\\n self.raxmlOperations.numBootstraps = self.checkEntryInRange(self.numberOfBootstrapsEntry, min=2, errorTitle='Invalid Number of Bootstraps', errorMessage='Please enter an integer greater than 1.')\\n\\n # if using custom rax -- make sure that the user doesn't use the -s or -n flags\\n if self.checkBoxCustomRaxml.isChecked():\\n self.raxmlOperations.customRaxmlCommand = self.checkEntryPopulated(self.customRaxmlCommandEntry, errorTitle='No RAxML Command', errorMessage='Please enter a custom raxml command or uncheck the box.')\\n if re.search('([\\\\-][n])|([\\\\-][s])', self.customRaxmlCommandEntry.text()):\\n raise ValueError, ('Invalid RAxML Command', 'Please do not specify the -s or -n flags.', 'the -s and -n flags will be handled internally based on the alignment you input.')\\n\\n # species tree error handling\\n if self.speciesTreeEntry.text() != \\\"\\\" and self.newickFileEntry.text() != \\\"\\\":\\n raise ValueError, ('Multiple Species Trees', 'You have both selected a species tree file and entered a species tree. Please only do one.', 'Both the \\\"Species Tree File and \\\"Enter Species Tree\\\" fields are populated. Please only use one.')\\n\\n # if the user selects either statistic plot -- open the inputted newick and read it into memory as a string on a single line\\n if self.checkboxRobinsonFoulds.isChecked() or self.checkboxPGTST.isChecked():\\n if self.newickFileEntry.text() != \\\"\\\":\\n self.newickFileName = self.checkEntryPopulated(self.newickFileEntry, errorTitle='Missing Species Tree', errorMessage='Please select a species tree.', errorDescription='Please select a species tree.')\\n with open(self.newickFileEntry.text(), 'r') as f:\\n self.speciesTree = f.read().replace('\\\\n', '')\\n else:\\n self.speciesTree = self.checkEntryPopulated(self.speciesTreeEntry, errorTitle='Missing Species Tree', errorMessage='Please select a species tree.', errorDescription='Please select a species tree.')\\n\\n\\n except ValueError, (ErrorTitle, ErrorMessage, ErrorDescription):\\n self.message(str(ErrorTitle), str(ErrorMessage), str(ErrorDescription))\\n return False\\n\\n return True\",\n \"def checkInterrupt():\\n if wasInterrupted():\\n raise KeyboardInterrupt()\",\n \"def _syringeErrorHandler(self):\\n try:\\n yield\\n except SyringeError, e:\\n if e.err_code == 7:\\n last_cmd = self.last_cmd\\n try:\\n self.init()\\n except SyringeError, e:\\n if e.err_code == 7:\\n pass\\n else:\\n raise e\\n self.waitReady()\\n self.sendRcv(last_cmd)\\n else:\\n self.resetChain()\\n raise e\\n except Exception, e:\\n self.resetChain()\\n raise e\",\n \"def test_validate_input_rejection(self):\\n with nose.assert_raises(exceptions.RejectionError):\\n self.dtm1.validate_input('000011')\",\n \"def test_read_one_signal_failure(self):\\n cwd = os.path.dirname(os.path.abspath(__file__))\\n dir1 = os.path.join(cwd, 'test_files/')\\n dir2 = '/home/tomas/here-be-dragons/'\\n signal1 = read_signal(dir1, 'here-be-dragons')\\n signal2 = read_signal(dir2, 'test3')\\n self.assertIsNone(signal1)\\n self.assertIsNone(signal2)\",\n \"def get_input(label):\\n result = input(label)\\n sounds.play_input_beep()\\n return result\",\n \"def interrupt_handler(signum, frame): #pylint: disable=W0613\\n cleanup()\\n sys.exit(-2) # Terminate process here as catching the signal\\n # removes the close process behaviour of Ctrl-C\",\n \"def all_exception_handler(handler_input, exception):\\n # type: (HandlerInput, Exception) -> None\\n print(\\\"Encountered following exception: {}\\\".format(exception))\\n\\n speech = \\\"Sorry, there was some problem. Please try again!!\\\"\\n handler_input.response_builder.speak(speech).ask(speech)\\n\\n return handler_input.response_builder.response\",\n \"def unhandled(self):\\n return True\",\n \"def chk_stdin(self):\\t# check keyboard input\\n\\t\\tdr, dw, de = select([sys.stdin], [], [], 0)\\n\\t\\treturn dr\",\n \"def sigint_handler(*args):\\n sys.stderr.write('\\\\r')\\n QtGui.QApplication.quit()\",\n \"def test_ignore_return(self):\\n from signal import signal, SIGINT, SIG_DFL, SIG_IGN\\n\\n try:\\n for handler in SIG_DFL, SIG_IGN, lambda *a: None:\\n signal(SIGINT, SIG_IGN)\\n assert signal(SIGINT, handler) == SIG_IGN\\n finally:\\n signal(SIGINT, SIG_DFL)\",\n \"def exit_on_error(self) -> None:\\n if self.errors:\\n sys.exit(1)\",\n \"def handle_sigint(self, signum, frame):\\n self.finish()\\n self.original_handler(signum, frame)\",\n \"def signal_handler(sig_num, frame):\\n global exit_flag\\n logger.warn('Signal Recieved: {}'.format(str(sig_num)))\\n if sig_num:\\n exit_flag = True\",\n \"def cont():\\n\\n try:\\n input = raw_input()\\n except Exception:\\n pass\",\n \"def __exit_condition(data_logger):\\n try:\\n while True:\\n raw_input(\\\"\\\") # FIXME: is raw_input the right approach\\n if CLOSE:\\n raise KeyboardInterrupt()\\n\\n except (KeyboardInterrupt, EOFError):\\n sys.stdin.close()\\n data_logger.stop()\",\n \"def signal_kernel(self, signum):\\n pass\",\n \"def die_screaming(instr):\\n LOG.error(instr)\\n sys.exit(1)\",\n \"def die_screaming(instr):\\n LOG.error(instr)\\n sys.exit(1)\",\n \"def handler(signum, frame):\\n logging.warning(\\\"Got a {} signal. Doing nothing\\\".format(signum))\",\n \"def _exit_gracefully(self, signum, frame):\\n self.log.info(\\\"Exiting gracefully upon receiving signal %s\\\", signum)\\n self.log.debug(\\\"Current Stacktrace is: %s\\\", \\\"\\\\n\\\".join(map(str, inspect.stack())))\\n self.terminate()\\n self.end()\\n self.log.debug(\\\"Finished terminating DAG processors.\\\")\\n sys.exit(os.EX_OK)\",\n \"def _signal_handler(signalnum: int, _: Any) -> None:\\n logger.info('Received signal: {0}', signal.Signals(signalnum).name)\\n # safely close video stream & writer\\n stream.stop()\\n writer.close()\\n sys.exit(0)\",\n \"def signal_handler(signal, frame):\\n print()\\n endProgram(0)\",\n \"def interrupted(self):\\n pass\",\n \"def inConnectionLost(self):\\n self.logger('stdin closed by process %d' % self._pid)\",\n \"def input_(text=''):\\n while True:\\n try:\\n thing = input(text)\\n if thing == '':\\n raise ValueError\\n else:\\n return thing\\n except (EOFError, KeyboardInterrupt, ValueError):\\n print()\",\n \"def handle_expt(self):\\r\\n self._perform_on_error_handling()\",\n \"def _signal_handler(*args):\\n self._user_exit = True\",\n \"def signal_handler(signal_number, stack_frame):\\n if signal_number in [signal.SIGTERM, signal.SIGINT]:\\n terminate_surveillance()\",\n \"def keyboard_interrupt_handler(interrupt_signal, frame):\\n print(\\\"Scanning finished\\\")\\n print(\\\"KeyboardInterrupt ID: {} {} has been caught.\\\".format(interrupt_signal, frame))\\n exit(1)\",\n \"def keyboard_interrupt_handler(interrupt_signal, frame):\\n print(\\\"Scanning finished\\\")\\n print(\\\"KeyboardInterrupt ID: {} {} has been caught.\\\".format(interrupt_signal, frame))\\n exit(1)\",\n \"def ask_numbers(question, error):\\n while True:\\n value = 0\\n try:\\n value = int(input(question))\\n except ValueError:\\n print(error)\\n except UnboundLocalError:\\n print(error)\\n except Exception:\\n print(error)\\n if value <= 0:\\n print(\\\"Syötä positiivinen luku, joka on suurempi kuin 0\\\\n->\\\")\\n else:\\n break\\n return value\",\n \"def test_default_return(self):\\n from signal import signal, SIGINT, SIG_DFL, SIG_IGN\\n\\n try:\\n for handler in SIG_DFL, SIG_IGN, lambda *a: None:\\n signal(SIGINT, SIG_DFL)\\n assert signal(SIGINT, handler) == SIG_DFL\\n finally:\\n signal(SIGINT, SIG_DFL)\",\n \"def _sigint(self, signal, frame):\\n self.disconnect = True\\n if self.cardinal:\\n self.cardinal.quit('Received SIGINT.')\",\n \"def do_input_events(self):\\r\\n for event in EventStream.allNext(self.streams):\\r\\n if self.handler.event(event) and self.unhandledHandler:\\r\\n self.unhandledHandler(event)\",\n \"def sighandler(signum, frame):\\n global _terminate\\n global _interruptcnt\\n print >> FileKeyUtils.WMSlog, 'sighandler> ', signum\\n ++_interruptcnt \\n if signum in(signal.SIGABRT, signal.SIGINT, signal.SIGTERM):\\n print >> FileKeyUtils.WMSlog, 'sighandler> terminate pid: ', os.getpid(), signum\\n _terminate = True\\n elif signum in(signal.SIGHUP, signal.SIGTSTP):\\n print >> FileKeyUtils.WMSlog, 'sighandler> suspend/stop/pause pid: ', os.getpid(), signum\\n signal.pause()\\n else:\\n print >> FileKeyUtils.WMSlog, 'sighandler> resume/continue pid: ', os.getpid(), signum\\n _terminate = False\",\n \"def haltExec(self, input_pin=0):\\n if not 0 <= input_pin < 2:\\n raise(ValueError('`input_pin` [{0}] must be between 0 and 2'\\n ''.format(input_sig)))\\n cmd_string = 'H{0}'.format(input_sig)\\n return self.sendRcv(cmd_string)\",\n \"def ERR(self):\",\n \"def test_init(self):\\n nt.assert_raises(Exception, CisInterface.CisInput, 'error')\",\n \"def handle_exception(e):\\n print(e)\\n return error()\",\n \"def signal_handler(signum, frame):\\n monitor.stop()\\n sys.exit(0)\",\n \"def gracefulexit(signalnumber, frame):\\n\\t\\n\\tsys.exit(0) # resources will be closed on their corresponding finally blocks\",\n \"def src_error(state):\\n return _lib.src_error(state) if state else None\",\n \"def _cmd_exit(self):\\n raise EOFError()\",\n \"def _termination_handler(self, signum, frame):\\n print '[i] Shutting down...'\\n self.sensor.close()\\n sys.exit(1)\",\n \"def _readsignal(self, signame):\\n try:\\n signal = self.tree.getNode(signame)\\n except AttributeError:\\n signal = self.tree.get(signame)\\n return signal\",\n \"def signal_handler(signal, frame): \\n import signal\\n import sys\\n from time import localtime, strftime\\n time = strftime(\\\"%H:%M:%S\\\", localtime())\\n sel = raw_input('\\\\n\\\\n%s: Paused. Press return to resume, or type exit to quit: \\\\n' % time)\\n if sel.startswith('e') or sel.startswith('E'):\\n sys.exit(0)\\n else:\\n time = strftime(\\\"%H:%M:%S\\\", localtime())\\n print '%s: Interrogation resumed.\\\\n' % time\",\n \"def caught_signal(\\n self, signals: int, max_signals: int, executor: \\\"TaskGraphExecutor\\\"\\n ) -> None:\",\n \"def interrupt_handler(signum, frame):\\n if DOCKER_MONITOR:\\n util.log.warning(\\\"Signal %d received - Tearing down monitoring\\\"\\n % (signum))\\n DOCKER_MONITOR.tear_down_all()\\n sys.exit(0)\",\n \"def error(self):\\n pass\",\n \"def sigHandler(sig, frame):\\n # pylint: disable=unused-argument\\n shutdown()\\n sys.exit(0)\",\n \"def test_signal_no_pid(self):\\n code, out, err = self.t.runError(\\\"--pid 0\\\")\\n self.assertIn(\\\"A non-zero PID must be specified.\\\", out)\",\n \"def main():\\n os.write(2,bytes(process_infos(sys.argv[0])+\\\"\\\\n\\\",'utf-8'))\\n # Some signals of interest. Extend the list at will...\\n signal.signal(signal.SIGALRM,sigtrace_handler)\\n signal.signal(signal.SIGUSR1,sigtrace_handler)\\n signal.signal(signal.SIGUSR2,sigtrace_handler)\\n signal.signal(signal.SIGINT,sigtrace_handler)\\n signal.signal(signal.SIGTERM,sigtrace_handler)\\n signal.signal(signal.SIGCONT,sigtrace_handler)\\n signal.signal(signal.SIGTSTP,sigtrace_handler)\\n signal.signal(signal.SIGTTOU,sigtrace_handler)\\n signal.signal(signal.SIGTTIN,sigtrace_handler)\\n signal.signal(signal.SIGHUP,sigtrace_handler)\\n\\n\\n while True:\\n # Receiving a signal while in select will raise an exception\\n try:\\n # Wait for new input for at most one second\\n rrdy,wrdy,erdy = select.select([sys.stdin],[],[],1.0)\\n if len(rrdy) > 0:\\n # select returns with stdin ready (before one second)\\n buf = os.read(0,1024)\\n os.write(1, bytes(sys.argv[0]+\\\":\\\",'utf-8')+buf)\\n else:\\n # select return with nothing to read on stdin\\n os.write(1,bytes(sys.argv[0]+\\\"\\\\n\\\",\\\"utf-8\\\"))\\n except InterruptedError:\\n # select interrupted by signal: simply ignore and proceed\\n pass\",\n \"def __call__(self, *args):\\n if not args:\\n return self._get_value()\\n else:\\n raise RuntimeError('Can only set signal values of InputSignal objects, '\\n 'which signal %r is not.' % self._name)\",\n \"def error_handler(self):\\n if self.ctx.exit_code is not None:\\n return self.ctx.exit_code\",\n \"def sig_handler(sig, frame):\\n if sig == signal.SIGINT:\\n stop_ros()\\n print(\\\"Shutting down...\\\")\\n sys.exit(0)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6209089","0.6186397","0.61726344","0.6003437","0.59561807","0.5893812","0.5862972","0.57583606","0.57415015","0.57415015","0.57415015","0.5725218","0.57188","0.5668054","0.566546","0.56114185","0.5606983","0.5574848","0.5552682","0.5544291","0.5509935","0.5498945","0.54941124","0.54848766","0.54484683","0.5443166","0.5411852","0.54023296","0.539988","0.5383669","0.5354423","0.53409415","0.5334076","0.5317581","0.53165174","0.5315287","0.5306428","0.53051233","0.5298437","0.5297666","0.52802813","0.527984","0.52782893","0.5271709","0.5260182","0.524795","0.52305406","0.5225208","0.5209465","0.520275","0.5198082","0.5197873","0.5186485","0.5176791","0.51730424","0.5162815","0.516096","0.51603305","0.51586145","0.5151993","0.5149533","0.5148651","0.5148651","0.5137058","0.51329803","0.51284593","0.51217586","0.5113117","0.51086456","0.51072055","0.5103164","0.50971967","0.5094761","0.5092605","0.5092605","0.50900793","0.5087676","0.50818604","0.5080865","0.5079431","0.5074431","0.5069858","0.50536394","0.50486565","0.5046454","0.5044631","0.503662","0.5035936","0.5033795","0.50205237","0.5019374","0.5019297","0.50174326","0.50153244","0.50057757","0.5003071","0.49974957","0.49966908","0.49948016","0.49946553"],"string":"[\n \"0.6209089\",\n \"0.6186397\",\n \"0.61726344\",\n \"0.6003437\",\n \"0.59561807\",\n \"0.5893812\",\n \"0.5862972\",\n \"0.57583606\",\n \"0.57415015\",\n \"0.57415015\",\n \"0.57415015\",\n \"0.5725218\",\n \"0.57188\",\n \"0.5668054\",\n \"0.566546\",\n \"0.56114185\",\n \"0.5606983\",\n \"0.5574848\",\n \"0.5552682\",\n \"0.5544291\",\n \"0.5509935\",\n \"0.5498945\",\n \"0.54941124\",\n \"0.54848766\",\n \"0.54484683\",\n \"0.5443166\",\n \"0.5411852\",\n \"0.54023296\",\n \"0.539988\",\n \"0.5383669\",\n \"0.5354423\",\n \"0.53409415\",\n \"0.5334076\",\n \"0.5317581\",\n \"0.53165174\",\n \"0.5315287\",\n \"0.5306428\",\n \"0.53051233\",\n \"0.5298437\",\n \"0.5297666\",\n \"0.52802813\",\n \"0.527984\",\n \"0.52782893\",\n \"0.5271709\",\n \"0.5260182\",\n \"0.524795\",\n \"0.52305406\",\n \"0.5225208\",\n \"0.5209465\",\n \"0.520275\",\n \"0.5198082\",\n \"0.5197873\",\n \"0.5186485\",\n \"0.5176791\",\n \"0.51730424\",\n \"0.5162815\",\n \"0.516096\",\n \"0.51603305\",\n \"0.51586145\",\n \"0.5151993\",\n \"0.5149533\",\n \"0.5148651\",\n \"0.5148651\",\n \"0.5137058\",\n \"0.51329803\",\n \"0.51284593\",\n \"0.51217586\",\n \"0.5113117\",\n \"0.51086456\",\n \"0.51072055\",\n \"0.5103164\",\n \"0.50971967\",\n \"0.5094761\",\n \"0.5092605\",\n \"0.5092605\",\n \"0.50900793\",\n \"0.5087676\",\n \"0.50818604\",\n \"0.5080865\",\n \"0.5079431\",\n \"0.5074431\",\n \"0.5069858\",\n \"0.50536394\",\n \"0.50486565\",\n \"0.5046454\",\n \"0.5044631\",\n \"0.503662\",\n \"0.5035936\",\n \"0.5033795\",\n \"0.50205237\",\n \"0.5019374\",\n \"0.5019297\",\n \"0.50174326\",\n \"0.50153244\",\n \"0.50057757\",\n \"0.5003071\",\n \"0.49974957\",\n \"0.49966908\",\n \"0.49948016\",\n \"0.49946553\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5870097"},"document_rank":{"kind":"string","value":"6"}}},{"rowIdx":13099,"cells":{"query":{"kind":"string","value":"Exit on error trying to get the output callback."},"document":{"kind":"string","value":"def test_exit_on_output_cb_error(output_block, kwargs):\n output_block.side_effect = Exception()\n with pytest.raises(SystemExit) as exc_info:\n create_flow(**kwargs)\n assert exc_info.value.code == 1"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def finalize_error():\n print('')\n exit(-1)","def call_error():\r\n print(\"Error in input format.\")\r\n sys.exit()","def error_handler(self):\n if self.ctx.exit_code is not None:\n return self.ctx.exit_code","def failure_callback(self):\n error_filename = self.run_dir / \"eplusout.err\"\n if error_filename.exists():\n with open(error_filename, \"r\") as stderr:\n stderr_r = stderr.read()\n self.exception = EnergyPlusProcessError(\n cmd=self.cmd, stderr=stderr_r, idf=self.idf\n )\n self.cleanup_callback()","def _on_exit(cls, error=None):\n # type: (Exception) -> None\n pass","def exit_on_error(self) -> None:\n if self.errors:\n sys.exit(1)","def _cmd_exit(self):\n raise EOFError()","def _err(self, *args):\n logger.error(*args)\n exit(1)","def ConsoleExit(self, errorcode=200):\n pass","def main() -> None:\n try:\n run()\n except errors.BaseError as e:\n sys.stderr.write(f'{str(e)}\\n')\n sys.exit(e.code)","def handle_err(self):\n pass","def process_tool_output(self, proc, log_fn, name):\n output, error = proc.communicate()\n if proc.returncode != 0:\n fd = open(log_fn, \"a+\")\n fd.write(\"Error: %s returned the following output:\"\n \"\\n%s\" % (name, error))\n fd.close()\n raise Exception(\"%s returned the following output:\"\n \"\\n%s\" % (name, error))\n else:\n fd = open(log_fn, \"a+\")\n fd.write(\"%s output: %s %s\" % (name, output, error))\n # printing stdout and stderr though bowtie2 currently will always\n # output to stderr instead of stdout even if no error occurred\n fd.close()","def ErrorExit(msg):\r\n print >>sys.stderr, msg\r\n sys.exit(1)","def error_exit(error):\n if isinstance(error, (DataError, MetadataError)):\n error = \"{0}: {1} (key: {2})\".format(\n error.__class__.__name__, str(error), error.key)\n elif isinstance(error, Exception):\n error = \"{0}: {1}\".format(\n error.__class__.__name__, str(error))\n sys.stderr.write(\"ERROR: \" + error + \"\\n\")\n sys.exit(1)","def check_output(args, **kwargs):\n kwargs.setdefault('stdin', DEVNULL)\n if 'stdout' in kwargs:\n raise ValueError('stdout argument not allowed, it would be overridden.')\n return check_call_out(args, stdout=PIPE, **kwargs)[0]","def error(message):\n print message\n sys.exit(2)","def ErrorExit(msg):\n print >>sys.stderr, msg\n sys.exit(1)","def failsafe(return_arg_num_on_failure):\n def deco(func):\n def safe(*args):\n try:\n return func(*args)\n except:\n import traceback, sys \n sys.stderr.write(\"ERROR: Exception during callback \")\n try:\n sys.stderr.write(\"%s\\n\" % (map(str, args)))\n except:\n pass\n traceback.print_exc()\n return args[return_arg_num_on_failure]\n return safe\n return deco","def report_callback_exception(self, *args):\n err = traceback.format_exception(*args)\n self._logger.error(\"Exception: %s\", err)\n print(\"\".join(err))\n import os\n os._exit(1)","def bail_out(exit_code=ErrorCode.NO_ERROR):\n sys.exit(exit_code.value)","def errorExit(msg):\n msgString = (\"Error: \" + msg + \"\\n\")\n sys.stderr.write(msgString)\n sys.exit()","def error_handler(num, err):\n print(\"Error in input {}\".format(num))\n err = err.decode()\n raise Exception(err)","def OnError(self, error):\r\n\t\tLogErr(error)\r\n#\t\tself.Shutdown()\r\n\t\tself.onError()","def errReceived(self, data):\n log.msg(\"Error output from process: \" + data,\n isError=True)","def stop_err(msg):\n sys.stderr.write('%s\\n' % msg)\n sys.exit(-1)","def fail_on_output(self, **kwargs):\n return kwargs.get('value')","def shell_error(msg, exitcode=1):\n print(msg, file=sys.stderr)\n exit(exitcode)","def error(msg):\n print(msg, file=sys.stderr)\n sys.exit()","def bail( msg ):\n # Terminate, with helpful error message:\n print(\"ERROR: \" + msg + \"... exiting.\", file=sys.stderr)\n exit(1)","def err(string, exitval):\n\tprint >> sys.stderr, string.rstrip()\n\tsys.exit(exitval)","def error():\n return None","def _error(self, *args, **kwargs):\n print(\"[{}]\".format(self.type), *args, file=sys.stderr, **kwargs)\n sys.exit(1)","def output_on_fail(process, outputs):\n status = _maybe_use_running_output(process, outputs)\n if status is not None:\n return status\n\n def reader(handle, input_queue):\n \"\"\"Thread which reads handle, until EOF.\"\"\"\n input_queue.put(handle.read())\n\n with thread_output(target=reader, args=(outputs[0], )) as stdout_queue:\n with thread_output(target=reader,\n args=(outputs[1], )) as stderr_queue:\n stdout = stdout_queue.get()\n stderr = stderr_queue.get()\n\n status = process.wait()\n\n if status != 0:\n IndentedLogger.message(\"\\n\")\n IndentedLogger.message(stdout.decode(\"utf-8\"))\n IndentedLogger.message(stderr.decode(\"utf-8\"))\n\n return status","def check_call_out(args, **kwargs):\n out, returncode = communicate(args, **kwargs)\n if returncode:\n raise CalledProcessError(\n returncode, args, kwargs.get('cwd'), out[0], out[1])\n return out","def exit_with_error(error_msg):\n print error_msg\n sys.exit(1)","def _error_and_die(errorMessage):\n\n print(errorMessage, file=sys.stderr)\n sys.exit(1)","def __exit__(self, error_class, error_inst, error_tb):\n print ('Returning from exit ...')\n if error_class in (KeyError, IndexError):\n print (\"Got them thar errors\")\n return True # True means that the exception is not to be raised","def bail(self, msg):\n self.logger.error(\"Can't handle follower result: {}\".format(msg))\n self.call('ctrl', 'stop_full')\n sys.exit(1)","def errReceived(self, data):\n\n if self._fired:\n return\n self._stderr.append(data)\n if data.find('\\n') == -1:\n return\n # This expects tcpdump to output an line like\n # tcpdump: listening on eth1, link-type EN10MB (Ethernet), capture size 96 bytes\n # as first output on stderr ...\n stderr = \"\".join(self._stderr)\n self._fired = True\n if re.search(\"listening on.*link-type\", stderr):\n self._deferred.callback((True, None, stderr))\n else:\n self._deferred.callback((False, None, stderr))","def print_std_error(self):\n print(self.std_error)\n sys.exit()","def error(code, message):\n sys.stderr.write(message)\n sys.exit(code)","def _exit(message):\n\tprint('ERROR: ' + message, file=sys.stderr)\n\tsys.exit(1)","def check_error(err):\n if err != None:\n logging.error(err)\n sys.exit(-1)","def main_log_error() -> None:\n\n try:\n main()\n except Exception:\n error(\"Unhandled exception: {}\".format(traceback.format_exc()))\n raise","def screen_exit(self, error=0):\n sys.exit(error)","def stop_err(msg, error_level=1):\n sys.stderr.write(\"%s\\n\" % msg)\n sys.exit(error_level)","def cb(future):\n try:\n future.result()\n except:\n chat.reply('Script had an error.')\n # FIXME: send to log, not stdout\n traceback.print_exc(file=sys.stdout)","def check_error_output(self, output):\n\n # Display info message\n log.info(\"check_error_output\")\n\n # Check if output has some data\n if output:\n\n # Yes\n\n # Display info message\n log.info(\"check_error_output: output has some data\")\n\n # Check all elements in the list of output\n for element in self._send_command_error_in_returned_output:\n\n # Display info message\n log.info(f\"check_error_output: element: {element}\")\n\n # Display info message\n log.info(f\"check_error_output: output[0]: {output[0]}\")\n\n # Check if the output starts with a string with an error message (like \"% Invalid input detected at '^' marker.\")\n\n # Error message?\n if output.startswith(element):\n\n # Yes\n\n # Raise an exception\n raise Exception(output)","def error_exit():\n print(\"Invalid arguments!\")\n print(\"Type -h to get help.\")\n exit(0)","def errConnectionLost(self):\n self.logger('stderr closed by process %d' % self._pid)","def check_output(self, args):\n if isinstance(args, str):\n args = [args]\n try:\n return check_output(args)\n\n except IOError as e:\n raise ScriptError(e)\n\n except OSError as e:\n raise ScriptError(e)\n\n except CalledProcessError as e:\n raise ScriptError(e)","def error(error_no):\n print('--] Encountered unrecoverable ERROR [%s] ... leaving' % error_no)\n write_termination_message(error_no)\n sys.exit(0)","def _ErrorExit(message):\n print >>sys.stderr, message\n sys.exit(1)","def handle_errors(self, output):\n\n if \"Error: Could not find specified account(s).\" in output:\n return []\n\n logger.error(\"LastPass Error: %s\", output)\n raise LastPassError(output)","def test_handles_no_output(self):\n self.assertRaises(ValueError, self.pybird.get_peer_status, \"no output\")","def _run_callback_on_entry(\n self, callback: Callable[[LogEntry], None], entry: LogEntry\n ) -> None:\n try:\n callback(entry)\n except Exception:\n # Only print the first callback error to avoid insanity.\n if not self._printed_callback_error:\n import traceback\n\n traceback.print_exc(file=self._echofile)\n self._printed_callback_error = True","def __my_exit__(self, arg=0):\n self.services.error('Called sys.exit() from component code')\n raise Exception('Called sys.exit() from component code')","def main_wrapper() -> Optional[\n int\n]: # noqa: D401 (First line should be in imperative mood)\n try:\n return main()\n except KeyboardInterrupt:\n logger.info('Exiting on KeyboardInterrupt')\n return None\n except SystemExit as e:\n if e.args[0] == 'from sigterm handler':\n logger.info('Exiting on SIGTERM')\n else:\n logger.info('Exiting on SystemExit')\n return None","def __exit__(self, exc_type, exc_value, traceback):\n if self.returncode is None and self.proc.poll() is None:\n self.proc.terminate()","def captureOutput(callable, args=(), kwargs={}):\n\trealOut, realErr = sys.stdout, sys.stderr\n\tsys.stdout, sys.stderr = StringIO(), StringIO()\n\ttry:\n\t\tretVal = 2 # in case the callable sys.exits\n\t\ttry:\n\t\t\tretVal = callable(*args, **kwargs)\n\t\texcept SystemExit:\n\t\t\t# don't terminate just because someone thinks it's a good idea\n\t\t\tpass\n\tfinally:\n\t\toutCont, errCont = sys.stdout.getvalue(), sys.stderr.getvalue()\n\t\tsys.stdout, sys.stderr = realOut, realErr\n\treturn retVal, outCont, errCont","def _write_err_msg_and_quit(self, msg):\n sys.stderr.write(msg)\n sys.exit(1)","def error(msg):\n print 'ERROR: %s' % msg\n sys.exit(1)","def error_exit(text):\n logging.error(text)\n exit(1)","def run(self):\n sys.exit(-1)","def check_output_wrapper(*args, **kwargs):\n\n logger.debug('Executing %s, %s', args, kwargs)\n try:\n return check_output(*args, **kwargs)\n except CalledProcessError as msg:\n logger.warning('Error %s,%s,%s from command.', msg.returncode, msg.output, msg.stderr)\n logger.debug('Output: %s', msg.output)\n sys.exit(ERROR_EXECUTING_COMMAND);","def die_screaming(instr):\n LOG.error(instr)\n sys.exit(1)","def die_screaming(instr):\n LOG.error(instr)\n sys.exit(1)","def __exit(self, *args):\n sys.exit(0)","def on_error(self, callback):\n self.error_callback = callback","def geterror(self):\n c = [self.nsdchat, '-s', self.connection_string, '-c', 'geterror']\n process = subprocess.Popen(\n c, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n try:\n out, err = process.communicate()\n except subprocess.TimeoutExpired:\n process.kill()\n raise\n if (process.returncode != 0):\n Connection.logger.error(\"nsdchat exited with errorcode \"\n \"{rc}.\".format(rc=process.returncode))\n else:\n return out.decode('utf-8')","def called_process_error2exit_decorator(func):\n @functools.wraps(func)\n def func_wrapper(*args, **kwargs):\n try:\n func(*args, **kwargs)\n except subprocess.CalledProcessError as e:\n print(\"{err}:\\n{msg}\".format(err=str(e), msg=e.output))\n sys.exit(1)\n return func_wrapper","def on_failure(self):\n pass","def on_end(self, returncode):\n self.stdout.close()\n self.stderr.close()","def error(self):\n if self.p_err.poll():\n return self.p_err.recv()","def _handle_error(self, errno, msg):\n if self.error_callback != None:\n #Call the error callback but expect failure.\n try:\n self.error_callback(errno, msg, self.rpcclient)\n except Exception as ex:\n self.log.failure(\"Error in error handler for '{cmd!r}'.\",cmd=self.command)\n else:\n #If no handler is set, all we do is log.\n self.log.error(\"Notice: no on_error defined for '{cmd!r}, command result: {msg!r}\",cmd=self.command,msg=msg)","def output_error(text):\n if conf.eval_output:\n info_dict = {'type':'error', 'text' : text}\n output_result_eval(info_dict)\n else:\n output_result('[ERROR] ' + text)","def _handler_direct_access_exit(self, *args, **kwargs):","def do_get_error(self):\n if self._last_exception is None:\n print('no errors')\n else:\n traceback.print_exception(*self._last_exception)","def error_exit(cls, error_code):\n cls.exit_program(error_code)","def error(err):\n print(\"ERROR: \" + err)\n avrprog.end()\n while True:\n pass","def epilog(out):\n pass","def _on_error(self, error):\n print(error + \" for \" + self.session_name)","def error(text, exitcode=1):\n\n print(\"pkgmogrify: {0}\".format(text), file=sys.stderr)\n if exitcode != None:\n sys.exit(exitcode)","def exit_error(message: Optional[str] = None) -> NoReturn:\n\n\tif (message != None):\n\t\tprint(message)\n\tsys.exit(EXIT_FAILURE)","def outConnectionLost(self):\n self.logger('stdout closed by process %d' % self._pid)","def mute_stderr(callback, *args):\n nullwrite = NullWriter()\n oldstderr = sys.stderr\n sys.stderr = nullwrite # stderr deaktivieren\n result = callback(*args)\n sys.stderr = oldstderr # stderr aktivieren\n return result","def error_out(self) -> bool:\n return self._action == 'error'","def __cli_connection_error(self, output):\n ret = True\n regex = None\n regex = re.search( r'Using Thrift port ' + re.escape(self.thrift_port) + r'\\n', output, re.M|re.I)\n if regex:\n regex = re.search( r'Could not connect to thrift client on port ' + self.thrift_port + r'\\n', output, re.M|re.I)\n if(regex):\n self.logger.error(\"CLI Error: %s\", regex.group())\n else:\n regex = re.search( r'Obtaining JSON from switch\\.\\.\\.\\nDone', output, re.M|re.I)\n if(regex): ret = False\n else:\n regex = re.search( r'No Thrift port specified, using CLI default\\n', output, re.M|re.I)\n if regex:\n regex = re.search( r'Could not connect to thrift client on port 9090\\n', output, re.M|re.I)\n if(regex):\n self.logger.error(\"CLI Error: %s\", regex.group())\n else:\n regex = re.search( r'Obtaining JSON from switch\\.\\.\\.\\nDone', output, re.M|re.I)\n if(regex): ret = False\n else:\n self.logger.error(\"__cli_connection_error: Unknown Error\")\n return ret","def cmd_error_check(self, cmd_out):\n for err in self.err_strings:\n if re.search('\\\\b%s\\\\b' % (err), cmd_out, re.I):\n _log.info(cmd_out)\n _log.info(\n \"Cmd execution failed! with this Return Error: \\n%s\" % (\n cmd_out))\n return 0","def _handle_failure(self, proc, test_case):\n if proc.returncode != 0:\n print('ERROR: Test execution failed: {}'.format(test_case.get_name()))\n stdout, stderr = proc.communicate()\n raise TestCaseFailure('Test case {} failed. stdout: {}, stderr: {}, '\n 'return code: {}.'.format(test_case.get_name(),\n stdout, stderr,\n proc.returncode))","def error(s):\n sys.stderr.write(\"%s: %s\\n\" % (NAME, s))\n sys.exit(1)","def redirect(self, cmd, outfp, errfp, *args, **kwargs):\n if cmd == ['docker', 'run', 'confluent'] and outfp == 1 and errfp == 2:\n return\n raise ValueError(self, cmd, outfp, errfp, args, kwargs)","def err_handler(gui):\n\n try:\n yield\n except (errs.PortError,\n errs.IpError,\n errs.SelectionError,\n errs.ZBrushServerError) as err:\n print err.msg\n gui(err.msg)\n except Exception as err:\n print err\n gui(err)\n finally:\n pass","def handle_exception(e):\n print(e)\n return error()","def broken_pipe_handler(func: Callable[[List[str]], int], arguments: List[str]) -> int:\n try:\n returncode = func(arguments)\n sys.stdout.flush()\n except BrokenPipeError:\n devnull = os.open(os.devnull, os.O_WRONLY)\n os.dup2(devnull, sys.stdout.fileno())\n # Convention is 128 + whatever the return code would otherwise be\n returncode = 128 + 1\n return returncode","def check_output(self, cmd, nonzero_e = tc.error_e):\n _exitcode, stdoutf, _stderrf = self.run(cmd, nonzero_e = nonzero_e)\n return stdoutf.read()","def error_and_die(self, msg, *args, **kwargs):\n self.error(msg, *args, **kwargs)\n sys.stderr.write(\"exiting...\\n\")\n os._exit(2)","def stop_output(out):\n if out is not None:\n out.stop()\n pass","def on_error(data):\n print('Market Data Error', data)","def processError(sMsg, sOutput):\n if sOutput == \"\":\n errorMsg(sMsg)\n else:\n errorMsg(sMsg + \":\\n \" + ' '.join(sOutput.splitlines(True)))"],"string":"[\n \"def finalize_error():\\n print('')\\n exit(-1)\",\n \"def call_error():\\r\\n print(\\\"Error in input format.\\\")\\r\\n sys.exit()\",\n \"def error_handler(self):\\n if self.ctx.exit_code is not None:\\n return self.ctx.exit_code\",\n \"def failure_callback(self):\\n error_filename = self.run_dir / \\\"eplusout.err\\\"\\n if error_filename.exists():\\n with open(error_filename, \\\"r\\\") as stderr:\\n stderr_r = stderr.read()\\n self.exception = EnergyPlusProcessError(\\n cmd=self.cmd, stderr=stderr_r, idf=self.idf\\n )\\n self.cleanup_callback()\",\n \"def _on_exit(cls, error=None):\\n # type: (Exception) -> None\\n pass\",\n \"def exit_on_error(self) -> None:\\n if self.errors:\\n sys.exit(1)\",\n \"def _cmd_exit(self):\\n raise EOFError()\",\n \"def _err(self, *args):\\n logger.error(*args)\\n exit(1)\",\n \"def ConsoleExit(self, errorcode=200):\\n pass\",\n \"def main() -> None:\\n try:\\n run()\\n except errors.BaseError as e:\\n sys.stderr.write(f'{str(e)}\\\\n')\\n sys.exit(e.code)\",\n \"def handle_err(self):\\n pass\",\n \"def process_tool_output(self, proc, log_fn, name):\\n output, error = proc.communicate()\\n if proc.returncode != 0:\\n fd = open(log_fn, \\\"a+\\\")\\n fd.write(\\\"Error: %s returned the following output:\\\"\\n \\\"\\\\n%s\\\" % (name, error))\\n fd.close()\\n raise Exception(\\\"%s returned the following output:\\\"\\n \\\"\\\\n%s\\\" % (name, error))\\n else:\\n fd = open(log_fn, \\\"a+\\\")\\n fd.write(\\\"%s output: %s %s\\\" % (name, output, error))\\n # printing stdout and stderr though bowtie2 currently will always\\n # output to stderr instead of stdout even if no error occurred\\n fd.close()\",\n \"def ErrorExit(msg):\\r\\n print >>sys.stderr, msg\\r\\n sys.exit(1)\",\n \"def error_exit(error):\\n if isinstance(error, (DataError, MetadataError)):\\n error = \\\"{0}: {1} (key: {2})\\\".format(\\n error.__class__.__name__, str(error), error.key)\\n elif isinstance(error, Exception):\\n error = \\\"{0}: {1}\\\".format(\\n error.__class__.__name__, str(error))\\n sys.stderr.write(\\\"ERROR: \\\" + error + \\\"\\\\n\\\")\\n sys.exit(1)\",\n \"def check_output(args, **kwargs):\\n kwargs.setdefault('stdin', DEVNULL)\\n if 'stdout' in kwargs:\\n raise ValueError('stdout argument not allowed, it would be overridden.')\\n return check_call_out(args, stdout=PIPE, **kwargs)[0]\",\n \"def error(message):\\n print message\\n sys.exit(2)\",\n \"def ErrorExit(msg):\\n print >>sys.stderr, msg\\n sys.exit(1)\",\n \"def failsafe(return_arg_num_on_failure):\\n def deco(func):\\n def safe(*args):\\n try:\\n return func(*args)\\n except:\\n import traceback, sys \\n sys.stderr.write(\\\"ERROR: Exception during callback \\\")\\n try:\\n sys.stderr.write(\\\"%s\\\\n\\\" % (map(str, args)))\\n except:\\n pass\\n traceback.print_exc()\\n return args[return_arg_num_on_failure]\\n return safe\\n return deco\",\n \"def report_callback_exception(self, *args):\\n err = traceback.format_exception(*args)\\n self._logger.error(\\\"Exception: %s\\\", err)\\n print(\\\"\\\".join(err))\\n import os\\n os._exit(1)\",\n \"def bail_out(exit_code=ErrorCode.NO_ERROR):\\n sys.exit(exit_code.value)\",\n \"def errorExit(msg):\\n msgString = (\\\"Error: \\\" + msg + \\\"\\\\n\\\")\\n sys.stderr.write(msgString)\\n sys.exit()\",\n \"def error_handler(num, err):\\n print(\\\"Error in input {}\\\".format(num))\\n err = err.decode()\\n raise Exception(err)\",\n \"def OnError(self, error):\\r\\n\\t\\tLogErr(error)\\r\\n#\\t\\tself.Shutdown()\\r\\n\\t\\tself.onError()\",\n \"def errReceived(self, data):\\n log.msg(\\\"Error output from process: \\\" + data,\\n isError=True)\",\n \"def stop_err(msg):\\n sys.stderr.write('%s\\\\n' % msg)\\n sys.exit(-1)\",\n \"def fail_on_output(self, **kwargs):\\n return kwargs.get('value')\",\n \"def shell_error(msg, exitcode=1):\\n print(msg, file=sys.stderr)\\n exit(exitcode)\",\n \"def error(msg):\\n print(msg, file=sys.stderr)\\n sys.exit()\",\n \"def bail( msg ):\\n # Terminate, with helpful error message:\\n print(\\\"ERROR: \\\" + msg + \\\"... exiting.\\\", file=sys.stderr)\\n exit(1)\",\n \"def err(string, exitval):\\n\\tprint >> sys.stderr, string.rstrip()\\n\\tsys.exit(exitval)\",\n \"def error():\\n return None\",\n \"def _error(self, *args, **kwargs):\\n print(\\\"[{}]\\\".format(self.type), *args, file=sys.stderr, **kwargs)\\n sys.exit(1)\",\n \"def output_on_fail(process, outputs):\\n status = _maybe_use_running_output(process, outputs)\\n if status is not None:\\n return status\\n\\n def reader(handle, input_queue):\\n \\\"\\\"\\\"Thread which reads handle, until EOF.\\\"\\\"\\\"\\n input_queue.put(handle.read())\\n\\n with thread_output(target=reader, args=(outputs[0], )) as stdout_queue:\\n with thread_output(target=reader,\\n args=(outputs[1], )) as stderr_queue:\\n stdout = stdout_queue.get()\\n stderr = stderr_queue.get()\\n\\n status = process.wait()\\n\\n if status != 0:\\n IndentedLogger.message(\\\"\\\\n\\\")\\n IndentedLogger.message(stdout.decode(\\\"utf-8\\\"))\\n IndentedLogger.message(stderr.decode(\\\"utf-8\\\"))\\n\\n return status\",\n \"def check_call_out(args, **kwargs):\\n out, returncode = communicate(args, **kwargs)\\n if returncode:\\n raise CalledProcessError(\\n returncode, args, kwargs.get('cwd'), out[0], out[1])\\n return out\",\n \"def exit_with_error(error_msg):\\n print error_msg\\n sys.exit(1)\",\n \"def _error_and_die(errorMessage):\\n\\n print(errorMessage, file=sys.stderr)\\n sys.exit(1)\",\n \"def __exit__(self, error_class, error_inst, error_tb):\\n print ('Returning from exit ...')\\n if error_class in (KeyError, IndexError):\\n print (\\\"Got them thar errors\\\")\\n return True # True means that the exception is not to be raised\",\n \"def bail(self, msg):\\n self.logger.error(\\\"Can't handle follower result: {}\\\".format(msg))\\n self.call('ctrl', 'stop_full')\\n sys.exit(1)\",\n \"def errReceived(self, data):\\n\\n if self._fired:\\n return\\n self._stderr.append(data)\\n if data.find('\\\\n') == -1:\\n return\\n # This expects tcpdump to output an line like\\n # tcpdump: listening on eth1, link-type EN10MB (Ethernet), capture size 96 bytes\\n # as first output on stderr ...\\n stderr = \\\"\\\".join(self._stderr)\\n self._fired = True\\n if re.search(\\\"listening on.*link-type\\\", stderr):\\n self._deferred.callback((True, None, stderr))\\n else:\\n self._deferred.callback((False, None, stderr))\",\n \"def print_std_error(self):\\n print(self.std_error)\\n sys.exit()\",\n \"def error(code, message):\\n sys.stderr.write(message)\\n sys.exit(code)\",\n \"def _exit(message):\\n\\tprint('ERROR: ' + message, file=sys.stderr)\\n\\tsys.exit(1)\",\n \"def check_error(err):\\n if err != None:\\n logging.error(err)\\n sys.exit(-1)\",\n \"def main_log_error() -> None:\\n\\n try:\\n main()\\n except Exception:\\n error(\\\"Unhandled exception: {}\\\".format(traceback.format_exc()))\\n raise\",\n \"def screen_exit(self, error=0):\\n sys.exit(error)\",\n \"def stop_err(msg, error_level=1):\\n sys.stderr.write(\\\"%s\\\\n\\\" % msg)\\n sys.exit(error_level)\",\n \"def cb(future):\\n try:\\n future.result()\\n except:\\n chat.reply('Script had an error.')\\n # FIXME: send to log, not stdout\\n traceback.print_exc(file=sys.stdout)\",\n \"def check_error_output(self, output):\\n\\n # Display info message\\n log.info(\\\"check_error_output\\\")\\n\\n # Check if output has some data\\n if output:\\n\\n # Yes\\n\\n # Display info message\\n log.info(\\\"check_error_output: output has some data\\\")\\n\\n # Check all elements in the list of output\\n for element in self._send_command_error_in_returned_output:\\n\\n # Display info message\\n log.info(f\\\"check_error_output: element: {element}\\\")\\n\\n # Display info message\\n log.info(f\\\"check_error_output: output[0]: {output[0]}\\\")\\n\\n # Check if the output starts with a string with an error message (like \\\"% Invalid input detected at '^' marker.\\\")\\n\\n # Error message?\\n if output.startswith(element):\\n\\n # Yes\\n\\n # Raise an exception\\n raise Exception(output)\",\n \"def error_exit():\\n print(\\\"Invalid arguments!\\\")\\n print(\\\"Type -h to get help.\\\")\\n exit(0)\",\n \"def errConnectionLost(self):\\n self.logger('stderr closed by process %d' % self._pid)\",\n \"def check_output(self, args):\\n if isinstance(args, str):\\n args = [args]\\n try:\\n return check_output(args)\\n\\n except IOError as e:\\n raise ScriptError(e)\\n\\n except OSError as e:\\n raise ScriptError(e)\\n\\n except CalledProcessError as e:\\n raise ScriptError(e)\",\n \"def error(error_no):\\n print('--] Encountered unrecoverable ERROR [%s] ... leaving' % error_no)\\n write_termination_message(error_no)\\n sys.exit(0)\",\n \"def _ErrorExit(message):\\n print >>sys.stderr, message\\n sys.exit(1)\",\n \"def handle_errors(self, output):\\n\\n if \\\"Error: Could not find specified account(s).\\\" in output:\\n return []\\n\\n logger.error(\\\"LastPass Error: %s\\\", output)\\n raise LastPassError(output)\",\n \"def test_handles_no_output(self):\\n self.assertRaises(ValueError, self.pybird.get_peer_status, \\\"no output\\\")\",\n \"def _run_callback_on_entry(\\n self, callback: Callable[[LogEntry], None], entry: LogEntry\\n ) -> None:\\n try:\\n callback(entry)\\n except Exception:\\n # Only print the first callback error to avoid insanity.\\n if not self._printed_callback_error:\\n import traceback\\n\\n traceback.print_exc(file=self._echofile)\\n self._printed_callback_error = True\",\n \"def __my_exit__(self, arg=0):\\n self.services.error('Called sys.exit() from component code')\\n raise Exception('Called sys.exit() from component code')\",\n \"def main_wrapper() -> Optional[\\n int\\n]: # noqa: D401 (First line should be in imperative mood)\\n try:\\n return main()\\n except KeyboardInterrupt:\\n logger.info('Exiting on KeyboardInterrupt')\\n return None\\n except SystemExit as e:\\n if e.args[0] == 'from sigterm handler':\\n logger.info('Exiting on SIGTERM')\\n else:\\n logger.info('Exiting on SystemExit')\\n return None\",\n \"def __exit__(self, exc_type, exc_value, traceback):\\n if self.returncode is None and self.proc.poll() is None:\\n self.proc.terminate()\",\n \"def captureOutput(callable, args=(), kwargs={}):\\n\\trealOut, realErr = sys.stdout, sys.stderr\\n\\tsys.stdout, sys.stderr = StringIO(), StringIO()\\n\\ttry:\\n\\t\\tretVal = 2 # in case the callable sys.exits\\n\\t\\ttry:\\n\\t\\t\\tretVal = callable(*args, **kwargs)\\n\\t\\texcept SystemExit:\\n\\t\\t\\t# don't terminate just because someone thinks it's a good idea\\n\\t\\t\\tpass\\n\\tfinally:\\n\\t\\toutCont, errCont = sys.stdout.getvalue(), sys.stderr.getvalue()\\n\\t\\tsys.stdout, sys.stderr = realOut, realErr\\n\\treturn retVal, outCont, errCont\",\n \"def _write_err_msg_and_quit(self, msg):\\n sys.stderr.write(msg)\\n sys.exit(1)\",\n \"def error(msg):\\n print 'ERROR: %s' % msg\\n sys.exit(1)\",\n \"def error_exit(text):\\n logging.error(text)\\n exit(1)\",\n \"def run(self):\\n sys.exit(-1)\",\n \"def check_output_wrapper(*args, **kwargs):\\n\\n logger.debug('Executing %s, %s', args, kwargs)\\n try:\\n return check_output(*args, **kwargs)\\n except CalledProcessError as msg:\\n logger.warning('Error %s,%s,%s from command.', msg.returncode, msg.output, msg.stderr)\\n logger.debug('Output: %s', msg.output)\\n sys.exit(ERROR_EXECUTING_COMMAND);\",\n \"def die_screaming(instr):\\n LOG.error(instr)\\n sys.exit(1)\",\n \"def die_screaming(instr):\\n LOG.error(instr)\\n sys.exit(1)\",\n \"def __exit(self, *args):\\n sys.exit(0)\",\n \"def on_error(self, callback):\\n self.error_callback = callback\",\n \"def geterror(self):\\n c = [self.nsdchat, '-s', self.connection_string, '-c', 'geterror']\\n process = subprocess.Popen(\\n c, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n try:\\n out, err = process.communicate()\\n except subprocess.TimeoutExpired:\\n process.kill()\\n raise\\n if (process.returncode != 0):\\n Connection.logger.error(\\\"nsdchat exited with errorcode \\\"\\n \\\"{rc}.\\\".format(rc=process.returncode))\\n else:\\n return out.decode('utf-8')\",\n \"def called_process_error2exit_decorator(func):\\n @functools.wraps(func)\\n def func_wrapper(*args, **kwargs):\\n try:\\n func(*args, **kwargs)\\n except subprocess.CalledProcessError as e:\\n print(\\\"{err}:\\\\n{msg}\\\".format(err=str(e), msg=e.output))\\n sys.exit(1)\\n return func_wrapper\",\n \"def on_failure(self):\\n pass\",\n \"def on_end(self, returncode):\\n self.stdout.close()\\n self.stderr.close()\",\n \"def error(self):\\n if self.p_err.poll():\\n return self.p_err.recv()\",\n \"def _handle_error(self, errno, msg):\\n if self.error_callback != None:\\n #Call the error callback but expect failure.\\n try:\\n self.error_callback(errno, msg, self.rpcclient)\\n except Exception as ex:\\n self.log.failure(\\\"Error in error handler for '{cmd!r}'.\\\",cmd=self.command)\\n else:\\n #If no handler is set, all we do is log.\\n self.log.error(\\\"Notice: no on_error defined for '{cmd!r}, command result: {msg!r}\\\",cmd=self.command,msg=msg)\",\n \"def output_error(text):\\n if conf.eval_output:\\n info_dict = {'type':'error', 'text' : text}\\n output_result_eval(info_dict)\\n else:\\n output_result('[ERROR] ' + text)\",\n \"def _handler_direct_access_exit(self, *args, **kwargs):\",\n \"def do_get_error(self):\\n if self._last_exception is None:\\n print('no errors')\\n else:\\n traceback.print_exception(*self._last_exception)\",\n \"def error_exit(cls, error_code):\\n cls.exit_program(error_code)\",\n \"def error(err):\\n print(\\\"ERROR: \\\" + err)\\n avrprog.end()\\n while True:\\n pass\",\n \"def epilog(out):\\n pass\",\n \"def _on_error(self, error):\\n print(error + \\\" for \\\" + self.session_name)\",\n \"def error(text, exitcode=1):\\n\\n print(\\\"pkgmogrify: {0}\\\".format(text), file=sys.stderr)\\n if exitcode != None:\\n sys.exit(exitcode)\",\n \"def exit_error(message: Optional[str] = None) -> NoReturn:\\n\\n\\tif (message != None):\\n\\t\\tprint(message)\\n\\tsys.exit(EXIT_FAILURE)\",\n \"def outConnectionLost(self):\\n self.logger('stdout closed by process %d' % self._pid)\",\n \"def mute_stderr(callback, *args):\\n nullwrite = NullWriter()\\n oldstderr = sys.stderr\\n sys.stderr = nullwrite # stderr deaktivieren\\n result = callback(*args)\\n sys.stderr = oldstderr # stderr aktivieren\\n return result\",\n \"def error_out(self) -> bool:\\n return self._action == 'error'\",\n \"def __cli_connection_error(self, output):\\n ret = True\\n regex = None\\n regex = re.search( r'Using Thrift port ' + re.escape(self.thrift_port) + r'\\\\n', output, re.M|re.I)\\n if regex:\\n regex = re.search( r'Could not connect to thrift client on port ' + self.thrift_port + r'\\\\n', output, re.M|re.I)\\n if(regex):\\n self.logger.error(\\\"CLI Error: %s\\\", regex.group())\\n else:\\n regex = re.search( r'Obtaining JSON from switch\\\\.\\\\.\\\\.\\\\nDone', output, re.M|re.I)\\n if(regex): ret = False\\n else:\\n regex = re.search( r'No Thrift port specified, using CLI default\\\\n', output, re.M|re.I)\\n if regex:\\n regex = re.search( r'Could not connect to thrift client on port 9090\\\\n', output, re.M|re.I)\\n if(regex):\\n self.logger.error(\\\"CLI Error: %s\\\", regex.group())\\n else:\\n regex = re.search( r'Obtaining JSON from switch\\\\.\\\\.\\\\.\\\\nDone', output, re.M|re.I)\\n if(regex): ret = False\\n else:\\n self.logger.error(\\\"__cli_connection_error: Unknown Error\\\")\\n return ret\",\n \"def cmd_error_check(self, cmd_out):\\n for err in self.err_strings:\\n if re.search('\\\\\\\\b%s\\\\\\\\b' % (err), cmd_out, re.I):\\n _log.info(cmd_out)\\n _log.info(\\n \\\"Cmd execution failed! with this Return Error: \\\\n%s\\\" % (\\n cmd_out))\\n return 0\",\n \"def _handle_failure(self, proc, test_case):\\n if proc.returncode != 0:\\n print('ERROR: Test execution failed: {}'.format(test_case.get_name()))\\n stdout, stderr = proc.communicate()\\n raise TestCaseFailure('Test case {} failed. stdout: {}, stderr: {}, '\\n 'return code: {}.'.format(test_case.get_name(),\\n stdout, stderr,\\n proc.returncode))\",\n \"def error(s):\\n sys.stderr.write(\\\"%s: %s\\\\n\\\" % (NAME, s))\\n sys.exit(1)\",\n \"def redirect(self, cmd, outfp, errfp, *args, **kwargs):\\n if cmd == ['docker', 'run', 'confluent'] and outfp == 1 and errfp == 2:\\n return\\n raise ValueError(self, cmd, outfp, errfp, args, kwargs)\",\n \"def err_handler(gui):\\n\\n try:\\n yield\\n except (errs.PortError,\\n errs.IpError,\\n errs.SelectionError,\\n errs.ZBrushServerError) as err:\\n print err.msg\\n gui(err.msg)\\n except Exception as err:\\n print err\\n gui(err)\\n finally:\\n pass\",\n \"def handle_exception(e):\\n print(e)\\n return error()\",\n \"def broken_pipe_handler(func: Callable[[List[str]], int], arguments: List[str]) -> int:\\n try:\\n returncode = func(arguments)\\n sys.stdout.flush()\\n except BrokenPipeError:\\n devnull = os.open(os.devnull, os.O_WRONLY)\\n os.dup2(devnull, sys.stdout.fileno())\\n # Convention is 128 + whatever the return code would otherwise be\\n returncode = 128 + 1\\n return returncode\",\n \"def check_output(self, cmd, nonzero_e = tc.error_e):\\n _exitcode, stdoutf, _stderrf = self.run(cmd, nonzero_e = nonzero_e)\\n return stdoutf.read()\",\n \"def error_and_die(self, msg, *args, **kwargs):\\n self.error(msg, *args, **kwargs)\\n sys.stderr.write(\\\"exiting...\\\\n\\\")\\n os._exit(2)\",\n \"def stop_output(out):\\n if out is not None:\\n out.stop()\\n pass\",\n \"def on_error(data):\\n print('Market Data Error', data)\",\n \"def processError(sMsg, sOutput):\\n if sOutput == \\\"\\\":\\n errorMsg(sMsg)\\n else:\\n errorMsg(sMsg + \\\":\\\\n \\\" + ' '.join(sOutput.splitlines(True)))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.66235447","0.6495243","0.6490984","0.64486736","0.628487","0.6235582","0.6078088","0.6077453","0.60774106","0.6030557","0.6004493","0.5937128","0.5927308","0.5906779","0.58894056","0.5872576","0.5862885","0.58574635","0.58571845","0.58409643","0.58380216","0.583373","0.58270705","0.5806193","0.5804208","0.5785311","0.5775035","0.5774366","0.5771194","0.57652843","0.57593954","0.57530826","0.5744759","0.5744628","0.5742637","0.5735356","0.5728433","0.5716632","0.5712304","0.57106113","0.5710118","0.57075316","0.5699229","0.56926626","0.5691378","0.5690647","0.5690639","0.5683898","0.56798905","0.5671534","0.5668013","0.56670153","0.56620723","0.5658075","0.5654656","0.56461227","0.5642995","0.5631923","0.56300914","0.56258225","0.56162924","0.56073976","0.5601581","0.5592406","0.5591848","0.55914116","0.55914116","0.55908513","0.5585899","0.55711013","0.556817","0.55651283","0.55638313","0.55596864","0.5554076","0.55471987","0.55438536","0.5541029","0.5524971","0.55246955","0.5523966","0.5522565","0.55200166","0.5519906","0.55184805","0.5510272","0.5505696","0.5494658","0.54937136","0.54924136","0.54839206","0.54780686","0.54749477","0.5474592","0.5462323","0.5457861","0.5448241","0.54454017","0.5443937","0.54379725"],"string":"[\n \"0.66235447\",\n \"0.6495243\",\n \"0.6490984\",\n \"0.64486736\",\n \"0.628487\",\n \"0.6235582\",\n \"0.6078088\",\n \"0.6077453\",\n \"0.60774106\",\n \"0.6030557\",\n \"0.6004493\",\n \"0.5937128\",\n \"0.5927308\",\n \"0.5906779\",\n \"0.58894056\",\n \"0.5872576\",\n \"0.5862885\",\n \"0.58574635\",\n \"0.58571845\",\n \"0.58409643\",\n \"0.58380216\",\n \"0.583373\",\n \"0.58270705\",\n \"0.5806193\",\n \"0.5804208\",\n \"0.5785311\",\n \"0.5775035\",\n \"0.5774366\",\n \"0.5771194\",\n \"0.57652843\",\n \"0.57593954\",\n \"0.57530826\",\n \"0.5744759\",\n \"0.5744628\",\n \"0.5742637\",\n \"0.5735356\",\n \"0.5728433\",\n \"0.5716632\",\n \"0.5712304\",\n \"0.57106113\",\n \"0.5710118\",\n \"0.57075316\",\n \"0.5699229\",\n \"0.56926626\",\n \"0.5691378\",\n \"0.5690647\",\n \"0.5690639\",\n \"0.5683898\",\n \"0.56798905\",\n \"0.5671534\",\n \"0.5668013\",\n \"0.56670153\",\n \"0.56620723\",\n \"0.5658075\",\n \"0.5654656\",\n \"0.56461227\",\n \"0.5642995\",\n \"0.5631923\",\n \"0.56300914\",\n \"0.56258225\",\n \"0.56162924\",\n \"0.56073976\",\n \"0.5601581\",\n \"0.5592406\",\n \"0.5591848\",\n \"0.55914116\",\n \"0.55914116\",\n \"0.55908513\",\n \"0.5585899\",\n \"0.55711013\",\n \"0.556817\",\n \"0.55651283\",\n \"0.55638313\",\n \"0.55596864\",\n \"0.5554076\",\n \"0.55471987\",\n \"0.55438536\",\n \"0.5541029\",\n \"0.5524971\",\n \"0.55246955\",\n \"0.5523966\",\n \"0.5522565\",\n \"0.55200166\",\n \"0.5519906\",\n \"0.55184805\",\n \"0.5510272\",\n \"0.5505696\",\n \"0.5494658\",\n \"0.54937136\",\n \"0.54924136\",\n \"0.54839206\",\n \"0.54780686\",\n \"0.54749477\",\n \"0.5474592\",\n \"0.5462323\",\n \"0.5457861\",\n \"0.5448241\",\n \"0.54454017\",\n \"0.5443937\",\n \"0.54379725\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6417455"},"document_rank":{"kind":"string","value":"4"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":130,"numItemsPerPage":100,"numTotalItems":95772,"offset":13000,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NjAxNTIwNiwianRpIjoiNGE3MmEzODUtNmRiMy00NmE4LTkxM2EtZmRkZmRkOWYyOWU5Iiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODYwMTg4MDYsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.w9TRLs4_bq5fzHJjDH7BhyZ4K3bGmAW4bk8sNrYbGf-9SXb8DQyiDnC2oJ0r7IQue79lJO1myAkGgNH84We3Bw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Function to create a dataframe of all the upstream catchments from specific locations. Input should be the output from ArcGIS script (2 columns of catchments and sites). | def catch_net(catch_sites_csv, catch_sites_col=['GRIDCODE', 'SITE']):
## Read in data
catch_sites_names=['catch', 'site']
catch_sites = read_csv(catch_sites_csv)[catch_sites_col]
catch_sites.columns = catch_sites_names
## Reorganize and select intial catchments
catch_sites1 = catch_sites[catch... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def agg_catch(catch_del_shp, catch_sites_csv, catch_sites_col=['GRIDCODE', 'SITE'], catch_col='GRIDCODE'):\n\n ## Catchment areas shp\n catch = read_file(catch_del_shp)[[catch_col, 'geometry']]\n\n ## dissolve the polygon\n catch3 = catch.dissolve(catch_col)\n\n ## Determine upstream catchments\n ... | [
"0.6559877",
"0.5908647",
"0.55847895",
"0.5509037",
"0.53329223",
"0.52562225",
"0.5231378",
"0.5186255",
"0.5075003",
"0.50579935",
"0.5006199",
"0.49805748",
"0.49723944",
"0.4970214",
"0.4946404",
"0.49155456",
"0.49110398",
"0.4893645",
"0.48922464",
"0.4881623",
"0.4866... | 0.52581215 | 5 |
Function to take the output of the ArcGIS catchment delineation polygon shapefile and cathcment sites csv and return a shapefile with appropriately delineated polygons. | def agg_catch(catch_del_shp, catch_sites_csv, catch_sites_col=['GRIDCODE', 'SITE'], catch_col='GRIDCODE'):
## Catchment areas shp
catch = read_file(catch_del_shp)[[catch_col, 'geometry']]
## dissolve the polygon
catch3 = catch.dissolve(catch_col)
## Determine upstream catchments
catch_df, sin... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def combine_catchments(catchmentfile, flowfile, elevationfile, comid, \n output = None, overwrite = False, verbose = True):\n\n t0 = time.time()\n numpy.seterr(all = 'raise')\n\n if output is None: output = os.getcwd() + r'\\combined'\n\n if os.path.isfile(output + '.shp') and not... | [
"0.5526519",
"0.55115604",
"0.5385016",
"0.53638154",
"0.5314633",
"0.53080976",
"0.5173656",
"0.50681376",
"0.50139534",
"0.49680954",
"0.495339",
"0.49488038",
"0.49403173",
"0.49082854",
"0.49027666",
"0.48932567",
"0.48877347",
"0.4870424",
"0.48680896",
"0.48623064",
"0.... | 0.5947495 | 0 |
Catchment delineation using the REC streams and catchments. sites_shp Points shapfile of the sites along the streams.\n sites_col The column name of the site numbers in the sites_shp.\n catch_output The output polygon shapefile path of the catchment delineation. | def rec_catch_del(sites_shp, sites_col='site', catch_output=None):
### Parameters
server = 'SQL2012PROD05'
db = 'GIS'
streams_table = 'MFE_NZTM_REC'
streams_cols = ['NZREACH', 'NZFNODE', 'NZTNODE']
catch_table = 'MFE_NZTM_RECWATERSHEDCANTERBURY'
catch_cols = ['NZREACH']
### Modificatio... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def agg_catch(catch_del_shp, catch_sites_csv, catch_sites_col=['GRIDCODE', 'SITE'], catch_col='GRIDCODE'):\n\n ## Catchment areas shp\n catch = read_file(catch_del_shp)[[catch_col, 'geometry']]\n\n ## dissolve the polygon\n catch3 = catch.dissolve(catch_col)\n\n ## Determine upstream catchments\n ... | [
"0.62439525",
"0.57997125",
"0.48219526",
"0.46345586",
"0.4631852",
"0.46315864",
"0.4526034",
"0.45056954",
"0.44907907",
"0.44516155",
"0.44467697",
"0.44328094",
"0.44328094",
"0.43942088",
"0.43738577",
"0.43644437",
"0.43510073",
"0.42912412",
"0.428687",
"0.4282901",
"... | 0.776218 | 0 |
Return prob(chisq >= chi, with df degrees of freedom). df must be even. | def chi2P(chi, df):
assert df & 1 == 0
# If chi is very large, exp(-m) will underflow to 0.
m = chi / 2.0
sum = term = exp(-m)
for i in range(1, df//2):
term *= m / i
sum += term
# With small chi and large df, accumulated
# roundoff error, plus error in
# the platform exp... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def achisqprob(chisq,df):\r\n BIG = 200.0\r\n def ex(x):\r\n BIG = 200.0\r\n exponents = N.where(N.less(x,-BIG),-BIG,x)\r\n return N.exp(exponents)\r\n\r\n if type(chisq) == N.ndarray:\r\n arrayflag = 1\r\n else:\r\n arrayflag = 0\r\n chisq = N.array([chisq])\r... | [
"0.74559987",
"0.724271",
"0.69441646",
"0.6661619",
"0.6657019",
"0.60960495",
"0.6026556",
"0.59603435",
"0.5947283",
"0.5885562",
"0.5863677",
"0.5858906",
"0.5848407",
"0.58128613",
"0.581115",
"0.580568",
"0.57811344",
"0.57709396",
"0.572794",
"0.5714124",
"0.56916016",... | 0.7435911 | 1 |
Read a C1.CSV file using csv.DictReader | def loadC1(filename):
data = []
with open(filename) as f_obj:
reader = csv.DictReader(f_obj, delimiter=';')
for line in reader:
dTetta = float(line['dTetta'])
Q = float(line['Q'])
U = float(line['U'])
V = float(line['V'])
item = itemC1(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def csv_dict_reader(file_obj):\n #import re\n #file = open(file_obj)\n\n # reader = csv.DictReader(file_obj)\n # for line in reader:\n # print(line[\"Name\"])",
"def csv_dict_reader(file_path):\r\n with open(file_path, 'r') as file_obj:\r\n\r\n reader = csv.DictReader(file_obj, delim... | [
"0.76946783",
"0.7543261",
"0.7435131",
"0.69613403",
"0.6928663",
"0.6915481",
"0.68936694",
"0.6893386",
"0.6850034",
"0.68068963",
"0.67897266",
"0.6773187",
"0.67644227",
"0.6734396",
"0.672309",
"0.67230624",
"0.6668023",
"0.6667102",
"0.66442615",
"0.66364485",
"0.66364... | 0.0 | -1 |
Read a C2.CSV file using csv.DictReader | def loadC2(filename):
data = []
with open(filename) as f_obj:
reader = csv.DictReader(f_obj, delimiter=';')
for line in reader:
# dGamma, Q, U, V
dGamma = float(line['dGamma'])
Q = float(line['Q'])
U = float(line['U'])
V = float(line['V... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def csv_dict_reader(file_obj):\n #import re\n #file = open(file_obj)\n\n # reader = csv.DictReader(file_obj)\n # for line in reader:\n # print(line[\"Name\"])",
"def CSVReader(self, input_file):\n f = open(input_file, 'r')\n reader = csv.reader(f)\n headers = reader.next()\n reader... | [
"0.7612505",
"0.7385898",
"0.7355741",
"0.7106169",
"0.69446945",
"0.6906966",
"0.68946433",
"0.68873245",
"0.687486",
"0.6859886",
"0.6836637",
"0.6813016",
"0.67940485",
"0.6778344",
"0.67435807",
"0.67227536",
"0.67118466",
"0.66973794",
"0.6679642",
"0.66714406",
"0.66629... | 0.0 | -1 |
Read a C3.CSV file using csv.DictReader | def loadC3(filename):
data = []
with open(filename) as f_obj:
reader = csv.DictReader(f_obj, delimiter=';')
for line in reader:
# dGamma, Alfa, Beta
dGamma = float(line['dGamma'])
Alfa = float(line['Alfa'])
Beta = float(line['Beta'])
it... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def csv_dict_reader(file_obj):\n #import re\n #file = open(file_obj)\n\n # reader = csv.DictReader(file_obj)\n # for line in reader:\n # print(line[\"Name\"])",
"def csv_dict_reader(file_path):\r\n with open(file_path, 'r') as file_obj:\r\n\r\n reader = csv.DictReader(file_obj, delim... | [
"0.7582805",
"0.74330664",
"0.73564386",
"0.6933669",
"0.691283",
"0.6908902",
"0.6887531",
"0.68846565",
"0.686481",
"0.68575877",
"0.6850132",
"0.6821035",
"0.6745821",
"0.6673853",
"0.66631335",
"0.6646696",
"0.66155756",
"0.66056746",
"0.6605367",
"0.6605286",
"0.6596739"... | 0.5735032 | 92 |
Read a MaterialRefraction.CSV file using csv.DictReader | def loadMaterial(filename):
data = []
with open(filename, encoding="utf-8") as f_obj:
reader = csv.DictReader(f_obj, delimiter=';')
for line in reader:
name = line['MaterialName']
re_min = float(line['ReValueMin'])
re_max = float(line['ReValueMax'])
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def csv_dict_reader(file_obj):\n #import re\n #file = open(file_obj)\n\n # reader = csv.DictReader(file_obj)\n # for line in reader:\n # print(line[\"Name\"])",
"def csv_dict_reader(file_path):\r\n with open(file_path, 'r') as file_obj:\r\n\r\n reader = csv.DictReader(file_obj, delim... | [
"0.7296654",
"0.72312284",
"0.6741361",
"0.6668469",
"0.6529582",
"0.6523582",
"0.64916676",
"0.62862843",
"0.6276672",
"0.62392443",
"0.62238324",
"0.6223094",
"0.6220048",
"0.6196683",
"0.6186961",
"0.6156472",
"0.6146962",
"0.6143966",
"0.6129653",
"0.61118865",
"0.6110114... | 0.5697329 | 59 |
Read a samples file for plane type calculation | def loadSamples(filename):
data = []
with open(filename, encoding="utf-8") as f_obj:
reader = csv.DictReader(f_obj, delimiter=';')
for line in reader:
Tetta = float(line['dTetta'])
Lambda = float(line['Lambda'])
item = TSample(Tetta, Lambda)
data.a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _read_from_file(self, filename):\n ff = fits.open(filename)\n # Load the normalized intensity\n self.norm_int = ff[0].data\n # Load the other parameters\n self.lam = ff[1].data['lam']\n self.lam_unit = ff[1].columns['lam'].unit\n self.theta = ff[2].data['theta']... | [
"0.63230526",
"0.62693244",
"0.62324",
"0.62110573",
"0.6139132",
"0.613021",
"0.6109676",
"0.6094271",
"0.6090338",
"0.60887986",
"0.60725564",
"0.60611904",
"0.60423905",
"0.6030552",
"0.5997111",
"0.5997111",
"0.59914887",
"0.59912354",
"0.59882784",
"0.5980029",
"0.596220... | 0.6207575 | 4 |
safe to call on floats and arrays get_shape(1) > None, get_shape(ones(2)) > (2,) | def get_shape(x):
return None if jnp.isscalar(x) else x.shape | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _check_shape(placeholder_shape, data_shape):\n\n return True",
"def validate_common(ndarray, name):\n\tvalidate_ndarray(ndarray,(np.float, np.int), (2,) , name)",
"def _is_scalar(shape):\n return F.shape_mul(shape) == 1",
"def _is_scalar_from_shape(shape):\n return _logical_equal(_ndims_from_shape... | [
"0.72709566",
"0.67900205",
"0.67742664",
"0.67406166",
"0.6730081",
"0.6688898",
"0.664606",
"0.6638844",
"0.66229963",
"0.65788215",
"0.6564183",
"0.65422463",
"0.6526019",
"0.65226525",
"0.65096045",
"0.64582187",
"0.6442337",
"0.64415085",
"0.6415565",
"0.63730866",
"0.63... | 0.586161 | 76 |
assume x is scalar if shape is None | def reshape(x, shape):
return float(x) if shape is None else jnp.reshape(x, shape) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_scalar(x):\n return x.ndim == 0",
"def is_scalar(x: Any) -> bool:\r\n return np.isscalar(x) or (isinstance(x, np.ndarray) and x.ndim == 0)",
"def _is_scalar(shape):\n return F.shape_mul(shape) == 1",
"def standardize_single_array(x):\n if x is None:\n return None\n if tensor_util... | [
"0.75711805",
"0.69461375",
"0.69240475",
"0.6782489",
"0.6748175",
"0.66977507",
"0.66780156",
"0.6534423",
"0.64858645",
"0.640593",
"0.64018637",
"0.629402",
"0.62908137",
"0.62318295",
"0.6230541",
"0.61999226",
"0.6194809",
"0.61947954",
"0.6124859",
"0.60925704",
"0.606... | 0.6028252 | 24 |
floats (indicated by None) have 1 element | def num_elements(shape):
return 1 if shape is None else int(np.prod(shape)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def empty_float():\n x = float()\n return x",
"def get_none1(self):\n pass",
"def _preprocess_float(values: Sequence) -> Tuple[Union[float, NullValue]]:\n\n processed = [float(x)\n if isinstance(x, numbers.Number)\n else x\n for x ... | [
"0.6339963",
"0.6163803",
"0.5955822",
"0.59350157",
"0.5902223",
"0.58178884",
"0.5803332",
"0.5800464",
"0.57801056",
"0.56740105",
"0.56332743",
"0.5626155",
"0.56216",
"0.560248",
"0.5596908",
"0.5581029",
"0.5577356",
"0.5514214",
"0.5481083",
"0.5474649",
"0.5474362",
... | 0.0 | -1 |
Make a pair of functions flatten(tree) > x, unflatten(x) > tree | def flatten_and_unflatten(input_tree) -> Tuple[Callable, Callable]:
tree_structure = tree_util.tree_structure(input_tree)
leaf_shapes = [get_shape(leaf) for leaf in tree_util.tree_leaves(input_tree)]
def flatten(tree):
leaves = tree_util.tree_leaves(tree)
flattened_leaves = [reshape(leaf,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def flatten():",
"def flatten(node: ir.Node) -> ir.Node:\n\n def visitor(node: ir.Node, args=None) -> ir.Node:\n if isinstance(node, ir.BinaryOp):\n\n # Flatten singleton BinaryOp\n if len(node.operand) == 1:\n return flatten(node.operand[0])\n\n # Flatten BinaryOp with reduction operat... | [
"0.7424356",
"0.7009518",
"0.673188",
"0.6717321",
"0.6695242",
"0.6640111",
"0.66385573",
"0.6636192",
"0.6581992",
"0.6532039",
"0.6504157",
"0.65039814",
"0.6488403",
"0.6451589",
"0.643888",
"0.6405306",
"0.6398433",
"0.63705224",
"0.6344484",
"0.62895566",
"0.6286946",
... | 0.7750934 | 0 |
load all training data into a dictionary stored in order of X, u, L, W, k | def load_all():
training_data = dict()
for i in range(7):
training_data[i+1] = load_data(i+1)
return training_data | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_training_data(self):\n self._save_training_data()",
"def training_data(self):\n if self._training_data is None:\n self._load_training_data()\n if self._swapped_training_data is None:\n self._swapped_training_data = {}\n for key, value in self._train... | [
"0.72685313",
"0.6999833",
"0.6843773",
"0.6823378",
"0.6724388",
"0.6672758",
"0.6670386",
"0.6663503",
"0.6590046",
"0.65890056",
"0.6577699",
"0.6511327",
"0.6481927",
"0.6450511",
"0.64183396",
"0.6417053",
"0.6415652",
"0.6405644",
"0.63804287",
"0.6376085",
"0.6344903",... | 0.8075104 | 0 |
compile the training set corresponding to experiments listed in ind_list | def make_training_set(ind_list, training_data):
exp = training_data[ind_list[0]]
X_train = exp[0]
u_train = exp[1]
for i in ind_list[1:]:
exp = training_data[i]
X_train = np.append(X_train, exp[0], axis=0)
u_train = np.append(u_train, exp[1], axis=0)
return X_train... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def train(self, input_vects):\n \n #Training iterations\n for iter_no in range(self._n_iterations):\n #Train with each vector one by one\n if iter_no % 20 == 0:\n print(iter_no)\n for input_vect in input_vects:\n self._sess.run(self._trai... | [
"0.5979961",
"0.58931327",
"0.5842986",
"0.5816581",
"0.5816086",
"0.5768412",
"0.575343",
"0.5698102",
"0.5657766",
"0.5611364",
"0.55773675",
"0.5553645",
"0.5535842",
"0.55307597",
"0.5524448",
"0.5512024",
"0.5494072",
"0.5475803",
"0.54679567",
"0.5410617",
"0.5362356",
... | 0.64535296 | 0 |
Verteld of de tree leeg is of niet | def isEmpty(self):
if self.size == 0:
return True
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tree():\n nobv.visual_tree()",
"def drawtree(self):\r\n\r\n Phylo.draw(self.tree)",
"def visit(self):\n self.tree = self.recursive_visit(self.tree)\n # assert self.current_line == self.tree.absolute_bounding_box.bottom_right.line",
"def visualise_binary_tree(self):\n tree_e... | [
"0.742669",
"0.6817363",
"0.6572952",
"0.6495102",
"0.644491",
"0.64102066",
"0.6300795",
"0.6276956",
"0.6271785",
"0.6242756",
"0.61643314",
"0.614813",
"0.6090898",
"0.60891956",
"0.60890216",
"0.608826",
"0.6072502",
"0.60488236",
"0.60438526",
"0.6036604",
"0.60356086",
... | 0.0 | -1 |
Voegt item toe aan tree | def insert(self, key, content, root=None):
if root is None:
root = self.root
if self.size == 0:
self.root = Node(content, key)
self.allNodes.append(self.root)
self.size += 1
return
elif key >= root.key:
if root.right is N... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __setitem__(self, i: int, o: 'Tree') -> None:\n ...",
"def add(self, item):\r\n self.root = self.recurse_add(self.root, item)",
"def add(tree, item):\n # This is a non recursive add method. A recursive method would be cleaner.\n if tree.root == None: # ... Empty tree ...\n tree.... | [
"0.6387445",
"0.63075423",
"0.62571263",
"0.62491727",
"0.6172571",
"0.6109202",
"0.60886395",
"0.60559595",
"0.6052861",
"0.60287714",
"0.6014096",
"0.59769017",
"0.59751266",
"0.59655714",
"0.59653354",
"0.595593",
"0.5940784",
"0.5928278",
"0.58982855",
"0.5893961",
"0.589... | 0.0 | -1 |
Verwijdert item uit tree | def delete(self, key):
root = self.find(key, True)
if root is False:
return False
parent = root.parent
# root deleten
if self.root == root:
found = False
current = root
if root.left is not None:
current = root.lef... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_item(self):\n\n\t\tdb.session.delete(self)\n\t\tdb.session.commit()",
"def delete(self):\n self.parent.delete_node(self)",
"def __delitem__(self, key):\n if self._size > 1:\n node_to_delete = self._getItemHelper(key, self._root)\n if node_to_delete:\n ... | [
"0.65211713",
"0.64184713",
"0.6387559",
"0.63569087",
"0.634312",
"0.6334422",
"0.63276106",
"0.63249993",
"0.62840253",
"0.6268403",
"0.62670267",
"0.6182453",
"0.6156681",
"0.6122682",
"0.61049175",
"0.6080987",
"0.60439867",
"0.6016591",
"0.60058963",
"0.6005304",
"0.5999... | 0.57628065 | 40 |
Zoekt in de tree naar het item dat bij het gegeven key hoort | def find(self, key, forDel=False):
found = False
root = self.root
while not found:
if key > root.key:
if root.right is None:
print("Key not found")
return False
root = root.right
elif key < root.key:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __getitem__(self, item):\n if self.child_keys is None:\n self.child_keys = sorted(self.children.keys(), key=str.lower)\n return self.children[self.child_keys[item]]",
"def __getitem__(self, item: int) -> int:\n return self.root[item].key",
"def _insert(self, key: int) -> Tre... | [
"0.6803085",
"0.65903795",
"0.6250117",
"0.61360836",
"0.6082913",
"0.6021574",
"0.5987229",
"0.5981191",
"0.5947651",
"0.5926669",
"0.5909166",
"0.5901913",
"0.5853368",
"0.584072",
"0.579246",
"0.5786548",
"0.57726324",
"0.5757052",
"0.5740202",
"0.572945",
"0.5721693",
"... | 0.5882669 | 12 |
zet tree om naar dot en png | def print(self):
dot = "digraph G {\nrankdir = UD\n"
for i in range(len(self.allNodes)):
if self.allNodes[i].left is not None:
dot += str(self.allNodes[i].key) + " -> " + str(self.allNodes[i].left.key) + "\n"
if self.allNodes[i].right is not None:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def drawtree(self):\r\n\r\n Phylo.draw(self.tree)",
"def _repr_png_(self):\n return self.tree._repr_png_()",
"def tree():\n nobv.visual_tree()",
"def debug_dot (tree, fn):\n\n if __debug__ and DEBUG_DOT:\n dot = tree.to_dot ()\n debug (\"writing dot: %s\", fn)\n with ... | [
"0.7049467",
"0.6888196",
"0.6836354",
"0.67927814",
"0.6758332",
"0.66430676",
"0.6581356",
"0.65705216",
"0.6519011",
"0.6504541",
"0.6384689",
"0.6383924",
"0.6375139",
"0.6375139",
"0.63687086",
"0.63460416",
"0.63119423",
"0.62603015",
"0.6194407",
"0.61821556",
"0.61777... | 0.6703262 | 5 |
Trains the network using back propagation, use the logistic activation function and the square loss, along with bias inputs | def fit(self, X, y, alpha, t):
m = X.shape[0] # number of examples
n = X.shape[1] # number of features
normalized_X = normalize(X) # normalize X for accuracy
K = len(np.unique(y)) # number of units in the output layer = number of classes
if K == 2... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def backprop(self, x, y):\n \n #Building an empty networks filled with empty 0 \n updated_bias = []\n for b in self.biases:\n updated_bias.append(np.zeros(b.shape)) \n \n updated_weight = []\n for w in self.weights:\n updated_weight.appe... | [
"0.70576835",
"0.6613435",
"0.6567604",
"0.6545431",
"0.65237206",
"0.65193415",
"0.64829934",
"0.6418162",
"0.64143413",
"0.64051306",
"0.6401433",
"0.6364397",
"0.6361401",
"0.6345978",
"0.6330163",
"0.63294196",
"0.6279485",
"0.6272271",
"0.6270294",
"0.6262799",
"0.625279... | 0.0 | -1 |
Returns the class probabilities for a (q, n)shaped numpy array T of test examples. Assume T has the same columns as X used in training. Return value should be an (q, k)shaped numpy array, P, in which k is the number of distinct classes in y during training P[i, j] is the model's probability of example i belonging to cl... | def predict(self, T):
# a is a list of size (h+2), each element is the array of the activation values for each layer
a = [None] * (self.h+2)
# z is a list of size (h+2), each element is the array of the input values for each layer
# z[0] should be None and never be accessed
z = [... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def estimatePosterior(trainX, trainC, testX):\n P = [] # Classification computed by the algorithm\n (p, q, r) = estimateProbabilities(trainX, trainC)\n n = len(testX)\n c = 2 # Number of classes\n for i in range(n):\n P.append([])\n for j in range(c):\n res = bayes(j, testX[... | [
"0.65724635",
"0.6323323",
"0.6309152",
"0.62347585",
"0.61794364",
"0.6172974",
"0.61581737",
"0.61085993",
"0.60545534",
"0.60510653",
"0.60303223",
"0.6023098",
"0.598686",
"0.5980664",
"0.5979464",
"0.5968876",
"0.5946437",
"0.593831",
"0.591688",
"0.5899787",
"0.58854496... | 0.56429154 | 42 |
Prints the current weights from the input layer to the output layer | def print(self):
for l in range(self.h+1):
print("Weight matrix between layer " + str(l) + " and layer " + str(l+1))
print(self.W[l]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def print_weights(self, round=False):\n\n print \"[\",\n for l in range(1, self.num_layers()):\n for n in range(self.get_layer(l).num_nodes):\n weights = self.get_node_with_layer(l, n).weights\n for w in range(len(weights)):\n if round:\n ... | [
"0.6859355",
"0.68313724",
"0.66972566",
"0.6644771",
"0.64783883",
"0.6384424",
"0.63238245",
"0.6312617",
"0.62208253",
"0.6220219",
"0.62092155",
"0.61812043",
"0.61801636",
"0.6177608",
"0.6095806",
"0.60859853",
"0.6069307",
"0.6046852",
"0.5931208",
"0.5914785",
"0.5906... | 0.68034106 | 2 |
The derivative of the sigmoid function | def g_prime(z):
return np.multiply(g(z), 1-g(z)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sigmoid_derivative(x):\n return x * (1-x)",
"def derivative_sigmoid(x):\n return x * (1 - x)",
"def derivative_sigmoid(x):\n return x * (1 - x)",
"def sigmoid_derivative(x):\n return x * (1.0 - x)",
"def sigmoid_derivative(x):\n\n return sigmoid(x) * (1 - sigmoid(x))",
"def sigmoid_der... | [
"0.8931355",
"0.88970494",
"0.88970494",
"0.88566244",
"0.8723297",
"0.8572503",
"0.83397293",
"0.82558525",
"0.81656826",
"0.7952699",
"0.7922646",
"0.7874329",
"0.7820545",
"0.77842283",
"0.77320105",
"0.7693423",
"0.7673917",
"0.767192",
"0.764811",
"0.760601",
"0.7604099"... | 0.0 | -1 |
Returns a plugin instance. | def getInstance(config):
return Plugin(config) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def plugin_instance(self):\n return self.__plugin_instance",
"def create_plugin(self, **kwargs):\n return self.plugin_class(**kwargs)",
"def getPlugin(self, *args):\n return _libsbml.SBase_getPlugin(self, *args)",
"def new(self, plugin, *args, **kwargs):\n if plugin in self.module... | [
"0.84703135",
"0.7754983",
"0.73671436",
"0.70479256",
"0.7027809",
"0.6509363",
"0.6499314",
"0.6483052",
"0.63523436",
"0.6320262",
"0.6309016",
"0.6308648",
"0.62907016",
"0.6254284",
"0.6235442",
"0.62242097",
"0.62042576",
"0.61898714",
"0.61353517",
"0.61204034",
"0.611... | 0.82682073 | 2 |
Prepare for target . | def process(self, node, format):
if format.endswith("latex"):
result = self.LaTeX_ProcessMath(node)
else:
result = self.XHTML_ProcessMath(node)
#end if
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prepare_gen(self, targets):\r\n pass",
"def prepare(self):",
"def _prepare(self):",
"def _prepare(self):",
"def actionPrepare():\n \n #Do preparation that is common for all platforms. Pass true if ortc is one of targets\n result = Preparation.setUp('ortc' in Settings.targets)\n if result != NO_E... | [
"0.7460234",
"0.69315946",
"0.66796947",
"0.66796947",
"0.66599566",
"0.6525683",
"0.6525683",
"0.6525683",
"0.64102614",
"0.6305251",
"0.6096762",
"0.6053131",
"0.6021104",
"0.5947197",
"0.594579",
"0.594579",
"0.5922696",
"0.5914593",
"0.5904647",
"0.58516353",
"0.58514154"... | 0.0 | -1 |
If target format is XHTML, generate GIFs from formulae. | def flush(self):
# generate bitmaps of formulae
if self.out.tell() > 0:
self.out.write("\\end{document}\n")
self.__LaTeX2Dvi2Gif()
self.out.close()
self.out = io.StringIO()
#end if
#reset counter
self.counter = 1
self.node... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_gif(frames, reward, path, number=None, evaluation=False):\n for i, frame in enumerate(frames):\n frames[i] = resize(frame, (420, 320, 3),\n order=0, preserve_range=True).astype(np.uint8)\n if evaluation:\n path += '/atari-step-{}-reward-{}.gif'.format(numb... | [
"0.58204705",
"0.57823205",
"0.57576567",
"0.5614984",
"0.5570564",
"0.5538513",
"0.55213165",
"0.5484985",
"0.5448945",
"0.5419624",
"0.53846264",
"0.5338472",
"0.53065234",
"0.5276483",
"0.5274553",
"0.5256931",
"0.52548414",
"0.5248981",
"0.52419114",
"0.5239205",
"0.52383... | 0.0 | -1 |
Call LaTeX and ImageMagick to produce a GIF. | def XHTML_ProcessMath(self, node):
if self.out.tell() == 0:
self.out.write("""\
\\documentclass[12pt]{scrartcl}\\usepackage{courier}
\\usepackage{courier}
\\usepackage{helvet}
\\usepackage{mathpazo}
\\usepackage{amsmath}
\\usepackage[active,displaymath,textmath]{preview}
\\frenchspacing{}
\\usepack... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def gif(self, delay=20, savefile=None, iterations=0, show_path=False,\n use_ffmpeg=False):\n from sage.misc.sage_ostools import have_program\n have_convert = have_program('convert')\n have_ffmpeg = self._have_ffmpeg()\n if use_ffmpeg or not have_convert:\n if have_... | [
"0.6888435",
"0.6775817",
"0.6772993",
"0.66560054",
"0.6630138",
"0.6614447",
"0.6607935",
"0.6585795",
"0.6558889",
"0.64578474",
"0.6438855",
"0.6422275",
"0.6338262",
"0.6297525",
"0.61565846",
"0.60966945",
"0.60572386",
"0.605021",
"0.60144264",
"0.59625584",
"0.5935778... | 0.0 | -1 |
Write formulae to LaTeX file, compile and extract images. | def __LaTeX2Dvi2Gif(self):
# open a temporary file for TeX output
tmpfp, tmpname = tempfile.mkstemp(suffix=".tex", dir=self.tmp_dir)
try:
with os.fdopen(tmpfp, "w", encoding="utf-8") as texfile:
texfile.write(self.out.getvalue())
except IOError:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_insertImages(self):\r\n parent = Element('div')\r\n base = FilePath(self.mktemp())\r\n base.makedirs()\r\n\r\n macros = Element('span')\r\n macros.setAttribute('class', 'latexmacros')\r\n text = Text()\r\n text.data = 'foo'\r\n macros.appendChild(tex... | [
"0.62115526",
"0.6149558",
"0.6059989",
"0.6026761",
"0.6008063",
"0.59548503",
"0.59547037",
"0.59331125",
"0.58783996",
"0.58253497",
"0.5790371",
"0.5730374",
"0.568745",
"0.5668162",
"0.56146497",
"0.5612511",
"0.5592571",
"0.5578856",
"0.5540914",
"0.5473427",
"0.5442843... | 0.51824105 | 36 |
Lowers a list of TealBlocks into a list of TealComponents. | def flattenBlocks(blocks: List[TealBlock]) -> List[TealComponent]:
codeblocks = []
references: DefaultDict[int, int] = defaultdict(int)
indexToLabel = lambda index: "l{}".format(index)
for i, block in enumerate(blocks):
code = list(block.ops)
codeblocks.append(code)
if block.is... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def block(self, block: tuple) -> list:\n b = []\n for j in range(3):\n index = block * 3 + j * 9 + 18 * (block // 3)\n for val in self.grid[index:index+3]:\n b.append(val)\n return b",
"def get_blocks(self) -> list:\n self.clingo = ClingoBridge() ... | [
"0.57208264",
"0.56381387",
"0.5355571",
"0.5295688",
"0.5244981",
"0.52368444",
"0.5234634",
"0.51819783",
"0.5135695",
"0.50644815",
"0.5015755",
"0.4994735",
"0.49924207",
"0.4943743",
"0.49335623",
"0.49311888",
"0.49311888",
"0.4920625",
"0.4920625",
"0.4903881",
"0.4891... | 0.68299204 | 0 |
If the object_id is found in the db for the last 5 minutes, it retrieves this job's information and skips processing. If the object_id cannot be found in the db for the last 5 minutes, it saves it and sends it to a queue to be processed. | def process(object_id: str) -> Job:
jobs = db.Jobs().get_by_object_id(object_id)
job_processed_in_last_five_minutes = list(
filter(
lambda x: (
datetime.datetime.utcnow() - x.timestamp < datetime.timedelta(minutes=5)
),
jobs,
)
)
if job... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def on_tick(self):\n if ((len(self._queue) >= self.config.batchsize) or\n (time.time() - self._last_get > self.config.batchtime and self._queue)):\n self._get()",
"def run(self):\n assert self.queue is not None, \"Must specify queue or override run()\"\n\n while not sel... | [
"0.55987585",
"0.54896456",
"0.54685956",
"0.54629576",
"0.54253185",
"0.54224366",
"0.53269327",
"0.52808934",
"0.52751964",
"0.527179",
"0.52460194",
"0.5220358",
"0.52187735",
"0.52122515",
"0.5173813",
"0.51726663",
"0.51726663",
"0.5172634",
"0.51683325",
"0.51590395",
"... | 0.7468584 | 0 |
It retrieves the job's information that finds in the db or None if the job was not found. | def retrieve(received_job_id: str) -> Union[Job, None]:
# todo: add error handling
found_job = db.Jobs().get_by_id(received_job_id)
if not found_job:
return
return found_job | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getJob(self, name=None):\n if name == None: \n name = self.jobstable.get_selectedRecordNames()[0]\n if name == None:\n return None, name\n jobid = self.DB.meta.peatsa_jobs[name]\n try:\n job = PEATSA.WebApp.Data.Job(jo... | [
"0.76924163",
"0.7398963",
"0.73788226",
"0.7289772",
"0.7167101",
"0.71370995",
"0.7100012",
"0.70188844",
"0.695432",
"0.6841215",
"0.6807646",
"0.6797778",
"0.67940956",
"0.6781903",
"0.6744986",
"0.67234474",
"0.6719189",
"0.6660137",
"0.66556096",
"0.66002905",
"0.657437... | 0.72142863 | 4 |
It retrieves the job from the job_id received in the 'body' parameter. Looks for it in the db and updates its status to 'done'. If no job was found, it returns None. | def finish(ch, method, properties, body) -> Union[Job, None]:
del ch, method, properties
# todo: add error handling
found_job = db.Jobs().get_by_id(body)
if not found_job:
return
found_job.status = "done"
return db.Jobs().update(found_job) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def retrieve(received_job_id: str) -> Union[Job, None]:\n # todo: add error handling\n found_job = db.Jobs().get_by_id(received_job_id)\n if not found_job:\n return\n return found_job",
"def get_a_job(job_id):\n job = JobModel.get_one_job(job_id)\n if not job:\n return custom_resp... | [
"0.73908395",
"0.67515594",
"0.6725238",
"0.6640862",
"0.6567949",
"0.6564976",
"0.65523577",
"0.6539249",
"0.645343",
"0.6404884",
"0.6329182",
"0.63278353",
"0.6320748",
"0.6312006",
"0.6310086",
"0.62760997",
"0.6257062",
"0.62490344",
"0.6210643",
"0.6202674",
"0.6179973"... | 0.67114484 | 3 |
Persists the model to the disk. Returns | def save(self):
try:
joblib.dump(self._clf, self._modelFile)
except:
return False
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def persist(self) -> None:\n if self.model is None:\n logger.debug(\n \"Method `persist(...)` was called without a trained model present. \"\n \"Nothing to persist then!\"\n )\n return\n\n with self._model_storage.write_to(self._resource)... | [
"0.75183755",
"0.7461746",
"0.7306015",
"0.72938365",
"0.72782624",
"0.7239542",
"0.72115964",
"0.7096571",
"0.7087327",
"0.7077688",
"0.7059958",
"0.7047942",
"0.7047942",
"0.7047942",
"0.70443946",
"0.7019755",
"0.7019061",
"0.7017741",
"0.7017741",
"0.7017741",
"0.7009537"... | 0.0 | -1 |
Restores the model from the disk. Returns | def load(self):
try:
clf = joblib.load(self._modelFile)
except:
return False
self._clf = clf
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def restore_model(self, path):\n # if cuda is not available load everything to cpu\n if not self.use_cuda:\n state = torch.load(path, map_location=lambda storage, loc: storage)\n else:\n state = torch.load(path)\n self.net.load_state_dict(state['state_dict'])\n ... | [
"0.73742014",
"0.73594147",
"0.7124561",
"0.7120268",
"0.70914626",
"0.70485914",
"0.7038069",
"0.70330733",
"0.6970493",
"0.69665897",
"0.6962411",
"0.6935343",
"0.6898966",
"0.68929976",
"0.6836925",
"0.66743976",
"0.66743976",
"0.667007",
"0.6655594",
"0.663932",
"0.663613... | 0.0 | -1 |
Detects the immersion level based on the given features. | def detect(self, features):
pass # TODO | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def detect(self, detect_img):\n features = self.classifier.detectMultiScale(detect_img,1.3,5)\n self.features = features\n self.features_detected = True",
"def get_basic_feature(image, featurelist=['entropy']):\n features = {'min': image.min(), 'max': image.max(), 'variance': 0, 'mean': 0... | [
"0.56744266",
"0.5453125",
"0.54530686",
"0.5328636",
"0.53202724",
"0.5282828",
"0.5223401",
"0.5216018",
"0.5200532",
"0.51810616",
"0.5085944",
"0.50755256",
"0.50647336",
"0.50630873",
"0.50608903",
"0.5057752",
"0.5049103",
"0.5029467",
"0.5027702",
"0.49991143",
"0.4995... | 0.6558402 | 0 |
Reads the data used for training or crossvalidating the model. | def readData(self, annotationPath):
##################################
# Read the data
##################################
print('Reading the data...')
scaler = MinMaxScaler(feature_range=(0, 1))
subjects = [1, 2, 6, 7, 14, 15, 17, 18, 20, 21, 23, 25, 26, 30, 31, 34,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_training_data(self):\n self._save_training_data()",
"def model_data():\n x_train, y_train, x_val, y_val, x_test, y_test = read_data(\"src/tests/dataclassificationmodel/ferPlus_processed.pbz2\", False)\n return x_train, y_train, x_val, y_val, x_test, y_test",
"def read_model(self):\n ... | [
"0.7283673",
"0.71832824",
"0.7180556",
"0.7124762",
"0.6943364",
"0.6842195",
"0.682788",
"0.6827234",
"0.68214357",
"0.6777717",
"0.67765874",
"0.66363525",
"0.6634755",
"0.6543852",
"0.65244555",
"0.65077186",
"0.6503315",
"0.6501531",
"0.64838386",
"0.63968337",
"0.638111... | 0.0 | -1 |
Performs a crossvalidation on the EmotionsDetector model. | def crossValidate(self, args):
##################################
# Read the training data
##################################
if not os.path.isdir(args.annotationPath):
print('annotation path does not exist: {}' \
.format(args.annotationPath))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cross_validation(exp_name):\n click.echo(\"Mode: Cross-validation.\")\n # defaults = get_defaults()\n\n # fitted_model_filename = add_extension(fitted_model_filename)\n\n # derive final path for fitted model as base output path for fitted models + model filename\n # fitted_model_path = os.path.j... | [
"0.6481566",
"0.6469234",
"0.6464313",
"0.63635683",
"0.62649405",
"0.60989666",
"0.5989488",
"0.59890103",
"0.5985422",
"0.59439325",
"0.58854234",
"0.58310795",
"0.57946634",
"0.57931525",
"0.5780316",
"0.5777693",
"0.5720764",
"0.56935006",
"0.56931883",
"0.5672364",
"0.56... | 0.64009774 | 3 |
Trains the EmotionsDetector model. | def train(self, args):
##################################
# Read the training data
##################################
if not os.path.isdir(args.annotationPath):
print('annotation path does not exist: {}' \
.format(args.annotationPath))
ret... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def train(self):\n # self.recognizer.train()\n self.detector.train()\n self.shared_conv.train()",
"def run(self) -> None:\n self.model = self.trainer.train_model(self.model, self.data)",
"def train(self):\n pass",
"def train(self):\n pass",
"def train(self):\n ... | [
"0.5869736",
"0.5637332",
"0.5600479",
"0.5600479",
"0.5600479",
"0.5600479",
"0.5600479",
"0.5562379",
"0.55589205",
"0.5527747",
"0.55013394",
"0.5439256",
"0.5433788",
"0.5421395",
"0.5412488",
"0.5401844",
"0.5383513",
"0.538006",
"0.5360298",
"0.5336405",
"0.5336392",
... | 0.5195484 | 36 |
Optimizes the EmotionsDetector model, trying to find the SVM parameters that would yield better results. | def optimize(self, args):
############################
# Get the data
############################
# Read the CSV file ignoring the header and the first column (which
# contains the file name of the image used for extracting the data in
# a row)
try:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def svm():",
"def optimize(self):\n self.vbe_step()\n self.compute_responsibilities()\n self.compute_sufficient_stats()\n self.vbmstep()",
"def svm_clf_training(max_features, data):\r\n X_train, y_train, X_test, y_test = data\r\n clf = Pipeline([('feature_selection', SelectKBe... | [
"0.6111361",
"0.5912575",
"0.5642402",
"0.5623126",
"0.5623126",
"0.5623126",
"0.55785716",
"0.5568076",
"0.5529505",
"0.55088013",
"0.54948574",
"0.5481435",
"0.5458506",
"0.5439299",
"0.5435268",
"0.54325897",
"0.5422759",
"0.5416318",
"0.5403779",
"0.5397329",
"0.53708524"... | 0.6573799 | 0 |
Compile and install the fake library used for testing | def fake(ctx, clean=False):
work_dir = join(PROJ_ROOT, "func", "dynlink")
build_dir = join(PROJ_ROOT, "build", "libfake")
clean_dir(build_dir, clean)
build_cmd = [
"cmake",
"-GNinja",
"-DFAASM_BUILD_SHARED=ON",
"-DFAASM_BUILD_TYPE=wasm",
"-DCMAKE_TOOLCHAIN_FILE=... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_project_with_dependencies(self):\n self.make_project()\n # 'test_library.zip' is not currently compiled for diorite.\n self.project.app_platforms = \"aplite,basalt,chalk\"\n self.project.save()\n tempdir = tempfile.mkdtemp()\n try:\n # Extract a premade... | [
"0.6840887",
"0.62958485",
"0.61345935",
"0.60900086",
"0.60620475",
"0.60337037",
"0.6018115",
"0.60040337",
"0.60032463",
"0.59797657",
"0.5962672",
"0.5853615",
"0.5829548",
"0.5787476",
"0.5776545",
"0.5772395",
"0.577139",
"0.5742527",
"0.5735555",
"0.5723381",
"0.572238... | 0.6825305 | 1 |
Get job status from the job queue provider. | def wait_for_job(self, value):
logger.info('Waiting for job %s' % self.job_name)
if self.provider_options.dry_run == True:
logger.info('Dry run: continuing')
else:
logger.info('Checking job status...')
provider = provider_base.get_provider(self.provider_options)
while True:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __get_job_status_from_queue__(self):\n\n return (lambda job: (int(job[-1]['JobStatus']),\n job[-1]))(self.schedd.query(\"ClusterId =?= {0}\".format(self.id)))",
"def get_status(self):\n\t\treturn call_sdk_function('PrlJob_GetStatus', self.handle)",
"def get_job_status(self):\n if self.worker... | [
"0.7685984",
"0.7638158",
"0.7302522",
"0.7206052",
"0.717944",
"0.71723753",
"0.7002564",
"0.6996343",
"0.69698",
"0.69682205",
"0.69247717",
"0.69158053",
"0.68639976",
"0.6845352",
"0.68310195",
"0.67442805",
"0.6669167",
"0.66362804",
"0.6592583",
"0.6538537",
"0.6525278"... | 0.5733461 | 97 |
Create branches in the DAG. | def create_branches(branches, pcoll, provider_options):
logger.info('Branch count: %i' % len(branches))
pcoll_tuple = ()
for branch in branches:
logger.info('Adding branch')
output = create_graph(branch, pcoll, provider_options)
pcoll_tuple = pcoll_tuple + (output,)
logger.info('Transform: MergeB... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_branch(self):\n os.chdir(str(self.repository_path))\n sh.git.checkout('master')\n sh.git.checkout('-b', self.branch)\n logger.debug('Branch {} created', self.branch)",
"def main(github_token, branch_name, repository, sha):\n create_branch(github_token, branch_name, repos... | [
"0.71373373",
"0.6745019",
"0.6531341",
"0.64341766",
"0.62213826",
"0.6209696",
"0.6113299",
"0.60638833",
"0.6030111",
"0.60283864",
"0.60153705",
"0.59939706",
"0.59934443",
"0.5881487",
"0.5877085",
"0.5869261",
"0.5821324",
"0.58131206",
"0.579358",
"0.5737575",
"0.56994... | 0.6769689 | 1 |
Recursively construct the Beam graph. | def create_graph(graph_item, pcoll, provider_options):
output = None
if isinstance(graph_item, basestring):
logger.info('Adding job %s' % graph_item)
job_name = graph_item
logger.info("Transform: WaitForJob")
output = pcoll | job_name >> WaitForJob(provider_options, job_name)
elif isinstance(g... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _build_graph(self):\n pass",
"def build_graph(self):\n pass",
"def _construct_graph(self):\n raise NotImplementedError",
"def build_graph(self):\n raise NotImplementedError",
"def build_graph(self):\n self.import_tree(ZOO_PATH, self.import_zoo, self.verify_zoos)\n ... | [
"0.7039644",
"0.68590266",
"0.67472506",
"0.6589838",
"0.65440136",
"0.6482974",
"0.6370373",
"0.6276264",
"0.6258234",
"0.6218308",
"0.6155739",
"0.5972295",
"0.59721893",
"0.59721893",
"0.5941389",
"0.5937874",
"0.58516246",
"0.58126825",
"0.5786413",
"0.57589984",
"0.57532... | 0.55035263 | 41 |
Call dview with an array of commandline flags. This is the recommended way to use dview as a Python library. | def call(argv):
known_args, beam_options = parse_args(argv)
yaml_string = known_args.dag.decode('string_escape')
dag = yaml.load(yaml_string)
pipeline_options = PipelineOptions(beam_options)
pipeline_options.view_as(SetupOptions).save_main_session = True
p = beam.Pipeline(options=pipeline_options)
pcol... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cli(args): # noqa; pylint: disable=unused-argument",
"def do_view_data(self, *args):\n with suppress(SystemExit):\n if str(*args).split(' ')[0] == '':\n command = self.cli.view_parser.parse_args(*args)\n else:\n command = self.cli.view_parser.parse_... | [
"0.6036357",
"0.6024427",
"0.60039175",
"0.5983105",
"0.59002405",
"0.57954013",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
"0.5790334",
... | 0.0 | -1 |
Represent the topics features of original features | def topic(df, num_topics=5):
# X, y = df[df.columns[:-1]], df[df.columns[-1]]
lda = LatentDirichletAllocation(n_topics=num_topics,
max_iter=5,
learning_method='online',
learning_offset=50.,
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def display_topics2(model, feature_names, n_top_words=25):\n word_dict = {};\n for topic_idx, topic in enumerate(model.components_):\n word_dict[\"Topic%d\" % (topic_idx)] = [feature_names[i]\n for i in topic.argsort()[:-n_top_words - 1:-1]]\n return pd.DataFrame(word_dict).T... | [
"0.652589",
"0.63945407",
"0.62877035",
"0.62470025",
"0.6179667",
"0.6089571",
"0.6085861",
"0.6072998",
"0.60302705",
"0.60291487",
"0.6021849",
"0.6014187",
"0.59974027",
"0.5994276",
"0.59592044",
"0.5955263",
"0.59346074",
"0.5914524",
"0.5907316",
"0.58988845",
"0.58709... | 0.56479675 | 66 |
given pymongo databaseand a regex object (or string) for geo_id return (pubmed_id, geo_id) | def getPubmedIds(db, geo_id, limit=0):
pm_tups = []
for ds in db.datasets.find({ '$or' : [{'reference_series':geo_id} , {"geo_id" :geo_id }]}).limit(limit):
if 'pubmed_id' in ds:
pm_tups.append((ds['pubmed_id'], ds['geo_id']))
pm_tups.append((ds['pubmed_id'], ds['reference_series... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def geonameid_from_location(text):\n if 'HASCORE_SERVER' in app.config:\n url = urljoin(app.config['HASCORE_SERVER'], '/1/geo/parse_locations')\n response = requests.get(url, params={'q': text}).json()\n geonameids = [field['geoname']['geonameid'] for field in response['result'] if 'geoname... | [
"0.55480814",
"0.53312546",
"0.53300273",
"0.5205659",
"0.511528",
"0.5103334",
"0.50721294",
"0.50375956",
"0.50349665",
"0.49944767",
"0.4975143",
"0.49461344",
"0.49347347",
"0.49083653",
"0.48941147",
"0.48785365",
"0.48737317",
"0.48682904",
"0.4865054",
"0.48643872",
"0... | 0.6269434 | 0 |
given a pubmed id, return a list of words from the given fields | def getWords(pubmed_id, fields=["MeshHeading" , "AbstractText", "ArticleTitle"]):
def findText(anode):
if anode.nodeType == anode.TEXT_NODE:
return anode.data
elif anode.hasChildNodes():
return ' '.join(map(findText, anode.childNodes))
else:
return ''
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def words(self, fields, normalizer_class):\n return sorted(set(itertools.chain.from_iterable(\n bib.raw_data(fields, normalizer_class)\n for bib in self.documents\n )))",
"def get_words(data):\n return data[\"words\"]",
"def get_page_words(parsed_hocr_page, pageid):\n... | [
"0.6270164",
"0.62465376",
"0.62347436",
"0.6110164",
"0.5964306",
"0.58644086",
"0.5819131",
"0.58036935",
"0.5776748",
"0.57580763",
"0.57580763",
"0.5744212",
"0.57393175",
"0.56931",
"0.5689465",
"0.5641902",
"0.5632844",
"0.5622878",
"0.5604147",
"0.5599055",
"0.55986273... | 0.78243196 | 0 |
given mongo db, geo_id and a list of words insert into word2geo collection | def insertWords(db, geo_id, words):
def f( word):
return {'geo_id' : geo_id, 'word': word}
try:
db.word2geo.insert(map( f, words))
except:
print "error in " + geo_id
print map( f, words) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def _insert_words(self, dict_words: List[DictWordModel]) -> NoReturn:\n docs = [word.dict() for word in dict_words]\n is_inserted = await self._db_client.try_insert_many(self._db_name, self._db_collection_name, docs)\n if not is_inserted:\n raise DBError('Failed to save many w... | [
"0.671187",
"0.66561407",
"0.64611846",
"0.6321505",
"0.61196697",
"0.60452765",
"0.6039269",
"0.6009112",
"0.5792243",
"0.5741951",
"0.57339126",
"0.57302725",
"0.56968504",
"0.5630612",
"0.55702686",
"0.55599356",
"0.55106515",
"0.55084234",
"0.5503626",
"0.5496883",
"0.546... | 0.8156848 | 0 |
Build a dictionary recording the min and max indices (indicating the position in a list) of documents for each review; | def build_indices(review_ids):
review_indices = {}
# Load qrel_abs_train txt file
clef_data = pd.read_csv(config.TRAIN_QREL_LOCATION, sep="\s+", names=['review_id', 'q0', 'pmid', 'included'])
# Get index of documents for each review
for review_id in review_ids:
index = clef_data.index[clef_data['review... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def generate_dict(self):\n dict = defaultdict(list)\n for i in range(self.no_of_docs-1):\n doc_txt = self.doc_to_df(i)\n #assign key to index in dictionary and its locations as tuples(docid,line,wordpos) as the values\n for j in range(len(doc_txt)):\n f... | [
"0.6648486",
"0.6142995",
"0.5936477",
"0.5701389",
"0.56871146",
"0.5630566",
"0.5610905",
"0.5560928",
"0.55124485",
"0.54871017",
"0.54758066",
"0.546961",
"0.54175454",
"0.5414213",
"0.53981483",
"0.5375703",
"0.5374007",
"0.5359983",
"0.53506577",
"0.53481126",
"0.534723... | 0.70010144 | 0 |
This function split one dataset into the training set and the test set with different standardization; | def run_train_test_split():
# Load all documents
conn = sq.connect(config.DB_FILE)
documents = pd.read_sql_query('select pubmed_id, review_id, included, title, abstract from article ', conn)
# Identify unique review IDs
review_ids = documents['review_id'].unique()
# Set seed for random sampling
np.rando... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __split_dataset(self):\n self.train, self.valid, _, _ = train_test_split(self.data, self.data, test_size=0.2)\n self.valid, self.test, _, _ = train_test_split(self.valid, self.valid, test_size=0.5)",
"def split_data_into_train_and_test(raw_training_data):\n train_set, test_set = train_test_s... | [
"0.7990251",
"0.7974505",
"0.7581833",
"0.7565025",
"0.7559627",
"0.7552167",
"0.75416225",
"0.75179213",
"0.74247026",
"0.7367997",
"0.73663753",
"0.7344645",
"0.730346",
"0.7287729",
"0.7281219",
"0.72798365",
"0.72691244",
"0.7258459",
"0.7252591",
"0.7251626",
"0.71612626... | 0.6987368 | 50 |
Redirect index to students page | def index() -> str:
return redirect('/students') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def index():\n return redirect(url_for('second_page'))",
"def home_page():\n return redirect('/users')",
"def idx(_request):\n return HttpResponseRedirect('/home')",
"def second_page():\n return redirect(url_for('index'))",
"def index_file():\n return redirect(\"/\")",
"def index(reque... | [
"0.6889249",
"0.685594",
"0.68496305",
"0.6730005",
"0.6604118",
"0.651976",
"0.6506114",
"0.6469121",
"0.6458482",
"0.64317304",
"0.640421",
"0.6387237",
"0.63767403",
"0.6375142",
"0.6348239",
"0.6342875",
"0.6328945",
"0.6312688",
"0.630708",
"0.63059723",
"0.6292399",
"... | 0.8471828 | 0 |
Query for Students Grades | def student_summary() -> str:
db_path: str = "810_startup.db"
try:
db: sqlite3.Connection = sqlite3.connect(db_path)
except sqlite3.OperationalError:
return f'Error: Unable to open database at path {db_path}'
else:
query: str = "select students.Name, students.CWID, grades.Course... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_grade_by_student(first_name):\n\n QUERY = \"\"\"\n SELECT g.project_title, g.grade \n FROM Students AS s JOIN Grades AS g \n ON s.github = g.student_github\n WHERE s.first_name = ?\n \"\"\"\n\n db_cursor.execute(QUERY, (first_name,))\n row = db_cursor.fetchall()\n ... | [
"0.7164799",
"0.69506854",
"0.68604916",
"0.68100643",
"0.6796675",
"0.666562",
"0.6567092",
"0.65628946",
"0.6529846",
"0.6339504",
"0.6262113",
"0.6254564",
"0.6247507",
"0.62131083",
"0.62120914",
"0.6165898",
"0.616138",
"0.61275333",
"0.6107583",
"0.60531247",
"0.6040625... | 0.0 | -1 |
Gets a card chosen at random | def get_random_card() -> "Card":
last = Card.objects.count() - 1
index = random.randint(0, last)
return Card.objects.all()[index] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_card(self):\n\n card = random.randint(1,13)\n return card",
"def card_output():\n cards = [11, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 10]\n return random.choice(cards)",
"def deal_card():\r\n cards = [11, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 10]\r\n return (random.choice(c... | [
"0.82879335",
"0.7804626",
"0.7780696",
"0.776896",
"0.7735164",
"0.7631362",
"0.7494053",
"0.7380841",
"0.7303759",
"0.725385",
"0.7194026",
"0.7147254",
"0.70656097",
"0.69215983",
"0.6893707",
"0.686891",
"0.6754502",
"0.6732325",
"0.67218757",
"0.66885597",
"0.6679748",
... | 0.7639505 | 5 |
Returns the total number of cards that given user owns of this card | def get_user_ownership_count(
self, user: get_user_model(), prefetched: bool = False
) -> int:
if prefetched:
return sum(
ownership.count
for card_printing in self.printings.all()
for localisation in card_printing.localisations.all()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_user_ownership_count(\n self, user: get_user_model(), prefetched: bool = False\n ) -> int:\n if prefetched:\n return sum(\n ownership.count\n for localisation in self.localisations.all()\n for ownership in localisation.ownerships.all(... | [
"0.7715831",
"0.69351727",
"0.67096174",
"0.6708182",
"0.6541524",
"0.64215946",
"0.63916093",
"0.6306432",
"0.6229252",
"0.6144589",
"0.6107996",
"0.6098523",
"0.60861856",
"0.6067441",
"0.6061621",
"0.60230386",
"0.60217756",
"0.6010899",
"0.6005462",
"0.5943102",
"0.589071... | 0.7711362 | 1 |
Returns whether or not this is an oversized card | def is_wide(self) -> bool:
return self.layout == "planar" | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def cardDiscardable(self, card):\n if self.cardDead(card):\n return True\n\n cardAttr = \"\"\n if Suit.toString(card.getSuit()) == \"white\":\n cardAttr = \"w\"\n elif Suit.toString(card.getSuit()) == \"blue\":\n cardAttr = \"b\"\n elif Suit.toStr... | [
"0.6903517",
"0.6678937",
"0.66666347",
"0.6406128",
"0.6370988",
"0.6358832",
"0.63576776",
"0.61906356",
"0.60390383",
"0.6031032",
"0.6008816",
"0.60084003",
"0.5983178",
"0.5980432",
"0.59701866",
"0.5922477",
"0.589019",
"0.58800906",
"0.58325684",
"0.5811311",
"0.580227... | 0.0 | -1 |
Gets whether this card has another card on the back | def is_double_faced(self) -> bool:
return self.layout in ("transform", "meld", "modal_dfc") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def can_go_back(self):\n return self._pointer >= 1",
"def still_in_hand(self):\n return len(self.hand.cards)!=0",
"def __gt__(self, other: Card) -> bool:\n return not self.__le__(other)",
"def hasBlackjack(self):\n return len(self.cards) == 2 and self.getPoints() == 21",
"def is_car... | [
"0.66254383",
"0.65699077",
"0.63486546",
"0.6297219",
"0.61691415",
"0.60999364",
"0.60874003",
"0.6041563",
"0.5999124",
"0.5998032",
"0.59420705",
"0.59275377",
"0.5925401",
"0.5924849",
"0.5910813",
"0.58968544",
"0.589199",
"0.58911973",
"0.58838475",
"0.5872889",
"0.585... | 0.0 | -1 |
Gets whether this card has another half (flip, split, transform etc) | def has_other_half(self) -> bool:
return self.layout in (
"flip",
"split",
"transform",
"meld",
"aftermath",
"adventure",
"modal_dfc",
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def can_split(self) -> bool:\n if len(self.cards) == 2 and self.cards[0].value == self.cards[1].value:\n return True\n else:\n return False",
"def is_pair(hand):\n\tis_a_pair = False\n\ti = 0\n\twhile i < 13:\n\t\tif hand[i] == 2:\n\t\t\tis_a_pair = True\n\t\ti += 1 \n\thigh_c... | [
"0.6733933",
"0.618208",
"0.61451954",
"0.61021394",
"0.60967654",
"0.6092608",
"0.60442275",
"0.60439914",
"0.6035215",
"0.59942883",
"0.5980618",
"0.5967132",
"0.5947805",
"0.58967525",
"0.5893755",
"0.5892925",
"0.5842676",
"0.5830995",
"0.5810103",
"0.5801732",
"0.5799426... | 0.7691357 | 0 |
Returns whether or not this is a land card | def is_land(self, only_land: bool = False) -> bool:
generator = (
any(_type.name == "Land" for _type in face.types.all())
for face in self.faces.all()
)
if only_land:
return all(generator)
return any(generator) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_facing_north(): #py:is_facing_north\n return RUR._is_facing_north_()",
"def has_cards(self):\n return self.hand.len() > 0",
"def is_facing_north(self): #py:UR.is_facing_north\n return RUR._UR.is_facing_north_(self.body)",
"def is_red_car(self):\n return self.identifier == 18"... | [
"0.6574346",
"0.6381043",
"0.6235261",
"0.6200675",
"0.6090455",
"0.60712475",
"0.6066724",
"0.60589635",
"0.594777",
"0.5855346",
"0.57903135",
"0.56646883",
"0.5646702",
"0.56021655",
"0.55966115",
"0.5596539",
"0.5566923",
"0.5530669",
"0.5515748",
"0.5515474",
"0.5508919"... | 0.6243277 | 2 |
Gets the keyrune code that should be used for this printing In 99% of all cases, this will return the same value as printing.set.keyrune_code But for Guild Kit printings, the guild symbol should be used instead | def get_set_keyrune_code(self) -> str:
if self.set.code in ("GK1", "GK2") and len(self.face_printings.all()) == 1:
first_face = self.face_printings.all()[0]
if first_face.watermark:
return first_face.watermark
return self.set.keyrune_code.lower() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_code_to_printings_key(printing):\n return (\n printing.set_integer or 0,\n str(printing.set_variant),\n printing.multiverseid or 0,\n printing.card_name,\n )",
"def getCode1Letter(self):\n dataDict = self.__dict__\n # NB must be done by direct access\n result = ... | [
"0.5882872",
"0.5875788",
"0.57938766",
"0.5729844",
"0.57142025",
"0.5691378",
"0.5621861",
"0.5621861",
"0.55469465",
"0.5541225",
"0.55250955",
"0.55160975",
"0.55054325",
"0.5503266",
"0.54999036",
"0.54993963",
"0.549464",
"0.5456612",
"0.5454372",
"0.5450911",
"0.539756... | 0.7367078 | 0 |
Returns the total number of cards that given user owns of this printing | def get_user_ownership_count(
self, user: get_user_model(), prefetched: bool = False
) -> int:
if prefetched:
return sum(
ownership.count
for localisation in self.localisations.all()
for ownership in localisation.ownerships.all()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_user_ownership_count(\n self, user: get_user_model(), prefetched: bool = False\n ) -> int:\n if prefetched:\n return sum(\n ownership.count\n for card_printing in self.printings.all()\n for localisation in card_printing.localisations.... | [
"0.7798705",
"0.6641717",
"0.6554687",
"0.65397143",
"0.65318733",
"0.62367505",
"0.62067574",
"0.6073335",
"0.59826356",
"0.5970287",
"0.59580576",
"0.5957845",
"0.5957355",
"0.5945392",
"0.5938073",
"0.5932106",
"0.5879058",
"0.57467246",
"0.5720436",
"0.56724894",
"0.56695... | 0.7298613 | 1 |
Applies a change of the number of cards a user owns (can add or subtract cards) | def apply_user_change(self, change_count: int, user: get_user_model()) -> bool:
if user is None or change_count == 0:
return False
try:
existing_card = UserOwnedCard.objects.get(
card_localisation=self, owner=user
)
if change_count < 0 and... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def calculate_cards(cards):\n if 11 in cards and sum(cards) > 21:\n cards.remove(11)\n cards.append(1)\n print('Changing 11 --> 1')\n print(f'Your hand is now {cards} and your total is {sum(cards)}')\n elif sum(cards) > 21:\n print('Sorry. Looks like you busted!')\n ... | [
"0.6545522",
"0.63200855",
"0.6267624",
"0.61299944",
"0.60999966",
"0.5987832",
"0.59660965",
"0.5964261",
"0.5903642",
"0.58689475",
"0.5830519",
"0.58236086",
"0.58002126",
"0.5779088",
"0.5747298",
"0.5740831",
"0.57314503",
"0.57169497",
"0.57010615",
"0.56986016",
"0.56... | 0.71913886 | 0 |
Gets most fitting image path for this localisation (the first face if there are multiple | def get_image_path(self) -> Optional[str]:
try:
return self.localised_faces.all()[0].get_image_path()
except IndexError:
logging.exception("Failed to find an image for %s", self)
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_best_face(self, image):\n\t\ttry:\n\t\t\treturn max(self.get_faces(image),\n\t\t\t key = (lambda f: f[1]))\n\t\texcept ValueError:\n\t\t\treturn None",
"def getFirst(self):\n if self.use_dic:\n data = sorted(self.dic.keys())[0]\n activity = sorted(self.dic[data].key... | [
"0.61643314",
"0.60766",
"0.602109",
"0.5965046",
"0.592761",
"0.57702565",
"0.57653356",
"0.57164794",
"0.57031834",
"0.55963093",
"0.546135",
"0.5455214",
"0.5410387",
"0.5387471",
"0.5364005",
"0.53553",
"0.53441226",
"0.5299835",
"0.529249",
"0.5285781",
"0.52561975",
"... | 0.71636146 | 0 |
Gets the path of the image for this localisation | def get_image_path(self) -> Optional[str]:
if not self.image or not self.image.file_path:
return None
return self.image.file_path | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def imagePath(self):\n return self.path",
"def imagePath(self):\n if self.use_dic:\n if self.imlist:\n paths = []\n for img in self.allimgs:\n paths.append(join(self.home, 'data'+str(self.data), self.activity, self.imsize, str(img)+'.jpg')... | [
"0.77722317",
"0.7762283",
"0.75915486",
"0.7475588",
"0.72751784",
"0.72202283",
"0.7217706",
"0.71703494",
"0.7101081",
"0.7060908",
"0.70575166",
"0.7046028",
"0.70416915",
"0.6934585",
"0.6831975",
"0.68238866",
"0.6806959",
"0.68018746",
"0.68018746",
"0.68018746",
"0.68... | 0.6939893 | 13 |
Parses the date and meal for a menu, both from CLI and function calls. This method will only return a nonNone value if that's what the user specified, since more information then available at this point is necessary to make an automatic decision (namely, the menu date), in which case it returns None so that whichever f... | def _parse_args(input_date, input_meal):
parser = ArgumentParser()
parser.add_argument('-d', '--date', type=str)
parser.add_argument('-m', '--meal', type=str)
args = parser.parse_args()
# Allows getting the args from either CLI or as the function parameters
query_date = args.date or input_date
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parseMenu(self):\n soup = BeautifulSoup(self.sourceText,\n markupMassage = Parser.SOURCE_FIXES,\n convertEntities = BeautifulStoneSoup.HTML_ENTITIES)\n\n keyTranslations = {'prato principal': 'principal',\n 'salada': 'salada',\n ... | [
"0.63029546",
"0.62325466",
"0.6204037",
"0.5833007",
"0.57940876",
"0.5668976",
"0.5628858",
"0.55757457",
"0.5570373",
"0.5545508",
"0.5543758",
"0.55230284",
"0.5504087",
"0.5475572",
"0.5453246",
"0.5448193",
"0.54172593",
"0.5367389",
"0.5333646",
"0.53286713",
"0.531885... | 0.6623508 | 0 |
Fetches the menu, menu date and available dates for a date and returns them as a string. | def run(input_date=None, input_meal=None):
query_date, query_meal = _parse_args(input_date, input_meal)
# Get the data and instantiate the required classes
html = scrapper.fetch_data(query_date)
meal_date = scrapper.get_meal_date(html)
available_dates = scrapper.get_available_dates(html)
meals =... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_menu() -> str:\n date = datetime.date.today()\n urls = generate_urls(date)\n menu_json = fetch_menu(urls)\n menu = extract_menu(menu_json, date)\n\n return menu",
"def extract_menu(menu_json: dict, date: datetime.date) -> str:\n\n inner_menu = menu_json[-1]\n acf = inner_menu.get(\"a... | [
"0.6648928",
"0.6201048",
"0.6086085",
"0.5976661",
"0.58711296",
"0.5790145",
"0.57648087",
"0.5746348",
"0.5727172",
"0.5688281",
"0.5654021",
"0.5632435",
"0.56074226",
"0.5510806",
"0.54997593",
"0.5482736",
"0.5477754",
"0.5470137",
"0.5470137",
"0.5449332",
"0.54168594"... | 0.5486585 | 15 |
Fetches the menu, menu date and available dates for a date and prints them to the stdout. | def run_and_print(dt=None):
write_plain(run(dt)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def search_by_date(self):\n # Using set comprehension to eliminate duplicates,\n # but converting to list for sorting\n dates = list({entry.date for entry in self.entries})\n dates.sort()\n print(\"*** Lookup by Date ***\\n\")\n print(\"Select a date the view all entries... | [
"0.63600284",
"0.6308452",
"0.6301404",
"0.6149177",
"0.5963567",
"0.5958459",
"0.5943125",
"0.58782434",
"0.5859757",
"0.5806425",
"0.5799375",
"0.57832366",
"0.5746213",
"0.5720881",
"0.56968534",
"0.5650051",
"0.56274515",
"0.56261396",
"0.55827737",
"0.5580598",
"0.548507... | 0.0 | -1 |
p is for print if length is 0 print the p tuple otherwise iterate. | def permute(p,l,length):
assert length >= 0
if length == 0:
print p
return
for i in range(0,length):
n = p + (l[i],)
permute(n,l[0:i]+l[i+1:],length-1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rec_print(p):\n if len(p) == 0:\n return\n t = p.pop(0)\n print t\n rec_print(p)",
"def print_PQ(q):\n for item in q:\n print(str(item), end=' ')\n print()",
"def trace(self,p):\n n = self\n c=0 \n while n!=None :\n print (n)\n n... | [
"0.7379953",
"0.6051226",
"0.5867241",
"0.58340585",
"0.5805494",
"0.57953507",
"0.5735741",
"0.5687979",
"0.5644167",
"0.5516746",
"0.5510768",
"0.5509927",
"0.55093926",
"0.5386433",
"0.535035",
"0.5301946",
"0.525214",
"0.5249476",
"0.5226239",
"0.52225846",
"0.51804423",
... | 0.0 | -1 |
Builds a network from config file | def build_network(config):
network_cfg = config['network']
network_name = network_cfg['name']
network_params = list(inspect.signature(eval(network_name).__init__).parameters)[1:]
args = [f'{param}={network_cfg[param]}' for param in network_params if network_cfg.get(param)]
try:
model = e... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _build_network(self):\n pass",
"def create_net(args):\n\n # Load config file for this experiment\n xinfo = yaml.load(open(args.exp)) # experiment info\n\n # copy config to run directory\n assert osp.isdir(args.cache_dir), 'Working directory not found: ' + args.cache_dir\n # output confi... | [
"0.71432847",
"0.6280527",
"0.6222136",
"0.62148905",
"0.62123084",
"0.6184715",
"0.61805207",
"0.60832465",
"0.60693824",
"0.6053631",
"0.6041396",
"0.6024714",
"0.6021795",
"0.6015814",
"0.5989596",
"0.597385",
"0.596626",
"0.583157",
"0.58275205",
"0.5820853",
"0.5814393",... | 0.7545299 | 0 |
For the given installer conditions, verify the dependencies for every single one of the conditions that are in some way referenced in specs or source. | def test_verify_all_dependencies(self):
for condition in self.all_references():
result = self.verify_dependencies(condition)
if result:
self.ill_defined[condition] = result
else:
self.well_defined.add(condition)
return self.ill_defin... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_verify_dependencies(self, cond_id, conditions):\n\n if not cond_id in conditions.get_keys():\n return 1\n else:\n result = self.verify_dependencies(cond_id)\n return result",
"def check_all(self, exe_paths=False):\n self.status_msg = \"\"\n for de... | [
"0.68579435",
"0.6556382",
"0.6347779",
"0.63326347",
"0.62767583",
"0.62427205",
"0.61748946",
"0.6174221",
"0.6137063",
"0.60748786",
"0.6053641",
"0.5956393",
"0.588417",
"0.5882532",
"0.58643204",
"0.5854203",
"0.5835256",
"0.58289266",
"0.5825942",
"0.57865596",
"0.57855... | 0.6852399 | 1 |
Verifies that the given condition id is defined, and that its' dependencies and their transitive dependencies are all defined and valid. | def test_verify_dependencies(self, cond_id, conditions):
if not cond_id in conditions.get_keys():
return 1
else:
result = self.verify_dependencies(cond_id)
return result | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _verify_dependencies(self, cond_id, undefined_paths, current_path):\n\n # Exception for izpack conditions:\n if cond_id in self.conditions.properties[WHITE_LIST]:\n return True\n\n # Short-circuit on well-defined conditions:\n if cond_id in self.well_defined:\n ... | [
"0.7233518",
"0.71392715",
"0.60746115",
"0.5732978",
"0.5654439",
"0.5454553",
"0.5448558",
"0.5441111",
"0.52943414",
"0.52780235",
"0.5251414",
"0.5139405",
"0.51285505",
"0.51267743",
"0.51252174",
"0.5048138",
"0.50332785",
"0.5028958",
"0.49913806",
"0.4958716",
"0.4956... | 0.78313273 | 0 |
Performs a depthfirst search of a condition's dependencies in order to verify that all dependencies and transitive dependencies are defined and valid. | def verify_dependencies(self, cond_id):
undefined_paths = set()
self._verify_dependencies(cond_id, undefined_paths, tuple())
return undefined_paths | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_verify_dependencies(self, cond_id, conditions):\n\n if not cond_id in conditions.get_keys():\n return 1\n else:\n result = self.verify_dependencies(cond_id)\n return result",
"def _verify_dependencies(self, cond_id, undefined_paths, current_path):\n\n # ... | [
"0.6695402",
"0.6293103",
"0.60720724",
"0.60228133",
"0.5990557",
"0.5964589",
"0.59326696",
"0.5578468",
"0.5578364",
"0.53697",
"0.5355786",
"0.53459734",
"0.53228617",
"0.53076524",
"0.5307568",
"0.5283302",
"0.5280135",
"0.527394",
"0.5268686",
"0.5262103",
"0.52600974",... | 0.5844651 | 7 |
Given the soup for a condition, test that its dependencies are validly defined. | def _verify_dependencies(self, cond_id, undefined_paths, current_path):
# Exception for izpack conditions:
if cond_id in self.conditions.properties[WHITE_LIST]:
return True
# Short-circuit on well-defined conditions:
if cond_id in self.well_defined:
return True
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def testConditionChecking(self):\n\n state = State.from_problem(self.prob)\n \n drive = self.dom.get_action(\"drive\")\n with drive.instantiate([\"agent\", \"tru1\", \"apt1\"], self.prob):\n self.assert_(state.is_satisfied(drive.precondition))\n\n with drive.instantiat... | [
"0.6394948",
"0.6064821",
"0.6038692",
"0.60127705",
"0.5969924",
"0.5887158",
"0.5801091",
"0.5776576",
"0.57205003",
"0.56385154",
"0.5614725",
"0.56072754",
"0.5539833",
"0.5475634",
"0.54365665",
"0.54158586",
"0.54152584",
"0.53983265",
"0.5347427",
"0.5322336",
"0.53194... | 0.63148606 | 1 |
Tests if a 'variable' type condition is correctly defined. | def test_variable(self, condition, undefined_paths, current_path):
var = str(condition.find('name').text)
if not var in self.variables.get_keys() and self.fail_on_undefined_vars:
current_path += ((var, 'undefined variable'),)
undefined_paths.add(current_path)
return F... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _validate_variable(self, variable):\n if variable is not None:\n # test type\n if not self.validate_type(variable):\n return False\n\n return True",
"def isvar(var):\n return _coconut_tail_call(isinstance, var, (Const, Var))",
"def _check_variable_defin... | [
"0.71227634",
"0.6907246",
"0.6733456",
"0.65082616",
"0.64736354",
"0.645199",
"0.64293915",
"0.63758117",
"0.6359905",
"0.63548344",
"0.63531965",
"0.63153076",
"0.6288625",
"0.62509894",
"0.62427473",
"0.62259036",
"0.6190489",
"0.6148015",
"0.6144128",
"0.6127952",
"0.612... | 0.71669835 | 0 |
Tests if an 'exists' type condition is welldefined. | def test_exists(self, condition, undefined_paths, current_path):
var = str(condition.find('variable').text)
if not var in self.variables.get_keys() and self.fail_on_undefined_vars:
current_path += ((var, 'undefined variable'),)
undefined_paths.add(current_path)
return... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exist(x):\n return x is not None",
"def exists(self):\n return True",
"def exists(self):\n return True",
"def definition_exists(name: str) -> bool:\n try:\n return bool(lookup_definition(name))\n except:\n return False",
"def exists(self):\n return self.obj i... | [
"0.6585829",
"0.6297913",
"0.6297913",
"0.6214394",
"0.6142705",
"0.60860187",
"0.604842",
"0.59506786",
"0.5899629",
"0.58844423",
"0.5882149",
"0.58796376",
"0.5875572",
"0.58542025",
"0.5844161",
"0.5812089",
"0.5798914",
"0.5771523",
"0.57615334",
"0.57554024",
"0.5733867... | 0.62473893 | 3 |
Tests if a 'java' type condition is welldefined. ie, if the class that the java var is a field of exists. my.package.MyClass myStaticField true | def test_java(self, condition, undefined_paths, current_path):
cond_id = str(condition.get('id'))
try:
cid = str(condition.find('class').text)
except AttributeError:
current_path += ((cond_id, 'ill-defined java condition'),)
undefined_paths.add(current_path)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_field_type(field_class):\n if field_class == 'TextField':\n field_type = 'Text field'\n elif field_class == 'NumericField':\n field_type = 'Numeric field'\n elif field_class == 'DateField':\n field_type = 'Date field'\n elif field_class == 'DateTimeField':\n field_... | [
"0.5906985",
"0.5887892",
"0.5847857",
"0.58403444",
"0.58391064",
"0.58101076",
"0.57811445",
"0.5773369",
"0.5730297",
"0.567376",
"0.56302613",
"0.55703485",
"0.55521667",
"0.5544753",
"0.5519627",
"0.5511953",
"0.54748327",
"0.54581445",
"0.5455314",
"0.5455117",
"0.54478... | 0.5669835 | 10 |
Unzips a list of tuples, x. | def unzip(self, x):
if (len(x)>0):
return list(zip(*x))
else:
return x, list() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def unzip(pairs):\n return tuple(zip(*pairs))",
"def unzip(zipped):\n return zip(*zipped)",
"def unzip(seq):\n return zip(*seq)",
"def unzip(seq: Iterable) -> tuple:\n seq = iter(seq)\n # check how many iterators we need\n try:\n first = tuple(next(seq))\n except StopIteration:\n ... | [
"0.75591034",
"0.6889838",
"0.68766",
"0.6743751",
"0.6709593",
"0.6456803",
"0.63671273",
"0.62731713",
"0.6267873",
"0.6260321",
"0.6234096",
"0.6152076",
"0.60384727",
"0.60337454",
"0.5970998",
"0.5970998",
"0.5949191",
"0.5846596",
"0.5812543",
"0.5775136",
"0.57129973",... | 0.79986495 | 0 |
returns teh version of the passed object | def get_revision_of_object(obj):
return getattr(obj, get_version_fieldname(obj)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_object ( self, object ):\n return object",
"def get(self, obj):",
"def obj(self) -> object:\n pass",
"def object(self):",
"def __invert__(self):\n return self.obj",
"def get(self, obj):\n raise NotImplementedError",
"def serialize(self, obj):\n return obj",
... | [
"0.70676875",
"0.7010541",
"0.6859093",
"0.68377954",
"0.6828108",
"0.66855097",
"0.662894",
"0.6485851",
"0.63837457",
"0.6309126",
"0.6275122",
"0.62676996",
"0.62326336",
"0.6201213",
"0.61918557",
"0.6187754",
"0.61847454",
"0.6175625",
"0.61751205",
"0.61347693",
"0.6134... | 0.63562226 | 9 |
returns True if `obj` is changed or deleted on the database | def is_changed(obj):
revision_field = get_version_fieldname(obj)
version = get_revision_of_object(obj)
return not obj.__class__.objects.filter(**{obj._meta.pk.name: obj.pk,
revision_field: version}).exists() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_live(self, obj):\n most_appropriate_object = get_appropriate_object_from_model(self.model)\n if most_appropriate_object == obj:\n return True\n return False",
"def has_change_permission(self, request, obj=None):\n if obj is not None:\n return False\n ... | [
"0.6930333",
"0.6525286",
"0.64501333",
"0.64336836",
"0.6431397",
"0.64131296",
"0.64131296",
"0.6349598",
"0.63452303",
"0.63142246",
"0.63139683",
"0.6300048",
"0.62984204",
"0.62824523",
"0.6207841",
"0.616058",
"0.61573696",
"0.6101484",
"0.60884404",
"0.60836864",
"0.60... | 0.80351144 | 0 |
try go load from the database one object with specific version | def get_version(model_instance, version):
version_field = get_version_fieldname(model_instance)
kwargs = {'pk': model_instance.pk, version_field: version}
return model_instance.__class__.objects.get(**kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_version(cls, unpickler, version):\n model = unpickler.load()\n if version == 0:\n feature = model._state['features']\n model._state['output_column_name'] = 'extracted.' + feature\n return model",
"def _load_version():\n version = session.get('version')\n\n ... | [
"0.61055326",
"0.60126936",
"0.59640944",
"0.58599895",
"0.5854756",
"0.58120066",
"0.5810105",
"0.5798865",
"0.5735602",
"0.57199824",
"0.57042235",
"0.56773525",
"0.56663936",
"0.55917364",
"0.55864733",
"0.55482763",
"0.552244",
"0.55130196",
"0.54902387",
"0.54607445",
"0... | 0.5590578 | 14 |
A loop to test movement showing in the terminal | def test_movement(self):
running = True
self.refresh_tile_maps()
self.data = self.board.data
self.board_objects = self.board.board_objects
self.weapons = self.board.weapons
self.rooms = self.board.rooms
self.players = self.board.players
self.player_cards... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def main_loop(self):\n center_point = self.mot.center_point\n\n screen_width = center_point[0] * 2\n screen_height = center_point[1] * 2\n\n time.sleep(1)\n pretty_progress_bar(\n 3,\n )\n\n # while int(time.time()) - start <= 10:\n while not self.... | [
"0.67542243",
"0.6601597",
"0.6516112",
"0.6261025",
"0.62314874",
"0.62044203",
"0.61881465",
"0.6146819",
"0.61307657",
"0.60168695",
"0.5986854",
"0.5973035",
"0.5970921",
"0.59660184",
"0.5957132",
"0.59444493",
"0.5920678",
"0.59130436",
"0.5904488",
"0.59033316",
"0.590... | 0.5588828 | 64 |
Initialize relation as a set of nodes and edges. Edges are added onebyone as to assure the integrity of a structure. root_graphs is a subgraph of universe that does not have "dead ends" | def __init__(self, nodes: Set[Node], edges: Set[Edge]):
super().__init__()
self.nodes = nodes
for edge in edges:
self.add_edge(edge)
self.leaves = {node for node in self.nodes if self.degree_out(node) == 0}
root_nodes = self.nodes - self.leaves
root_edges = {e... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialize_graph(compound_relations, relation_types):\n graph = nx.DiGraph()\n for compound, targets in compound_relations.items():\n for target, relation in targets.items():\n if relation in relation_types:\n graph.add_edge(compound, target)\n return graph",
"def po... | [
"0.6473229",
"0.61222476",
"0.6110643",
"0.6073983",
"0.5881061",
"0.5881061",
"0.57006747",
"0.5691904",
"0.5682234",
"0.5674344",
"0.5652",
"0.5635029",
"0.5594031",
"0.55848473",
"0.557185",
"0.55271906",
"0.5522342",
"0.5512572",
"0.54549974",
"0.54519945",
"0.54198855",
... | 0.58929604 | 4 |
Redefine the root graph for universe. It omits edges whose labels are in omit_edge_labels and also does not store references for nodes they point at. This is used mostly to get rid of uniquely identifying nodes. | def re_root(self, omit_edge_label: List[str]):
self.leaves = {node for node in self.nodes
if any([edge.label in omit_edge_label for edge in self.edges_to(node)])}
root_nodes = self.nodes - self.leaves
root_edges = {edge for edge in self.edges if edge.node_to in root_nodes ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def reset_graph(self):\n self.nodes = {}\n self.add_node(self.initial_state)\n self.add_node(self.final_state)",
"def reset_graph(self):\n raise NotImplementedError",
"def reset_graph(self):\n self.graph = OrderedDict()",
"def _restoreGraph(self):\n\n # self.tempG = ... | [
"0.66198105",
"0.6407392",
"0.61415255",
"0.61093223",
"0.6048665",
"0.60347766",
"0.60298306",
"0.5988843",
"0.5949874",
"0.5943684",
"0.5910985",
"0.5874265",
"0.58275336",
"0.57994217",
"0.5747671",
"0.57045126",
"0.57044613",
"0.565234",
"0.56324726",
"0.5624728",
"0.5622... | 0.7510522 | 0 |
Create a mask, that is a graphlike structure which can be thought of as a subgraph of universe. It holds only the references for known nodes and edges. This method create subgraph induced by its nodes. | def get_random_full_mask(self, size: int, breadth_first_preference: float = 0.5, from_root: bool = True) -> Mask:
if from_root:
g = self.root_graph
else:
g = self
nodes = set(random.sample(g.nodes, 1))
while len(nodes) < size:
to_extend = {edge.node_to... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def subgraph_mask(self, size):\n init_matrix = np.random.randn(size,size)\n Tcs = csgraph.minimum_spanning_tree(init_matrix)\n mask_matrix = Tcs.toarray()\n return mask_matrix",
"def __init__(self, nodes: Set[Node], edges: Set[Edge]):\n super().__init__()\n self.nodes = ... | [
"0.69909257",
"0.6730791",
"0.6133464",
"0.60049623",
"0.5896379",
"0.5863855",
"0.5832731",
"0.57625717",
"0.5693712",
"0.5613123",
"0.55460924",
"0.553991",
"0.5532406",
"0.54798096",
"0.53914773",
"0.53446835",
"0.53339267",
"0.5312013",
"0.5276624",
"0.52759224",
"0.52489... | 0.5328217 | 17 |
return a cursor to a query | def query_to_cur(dbh, qry, args):
if args.debug:
print(datetime.datetime.strftime(datetime.datetime.now(), "%D %H:%m:%S"), qry, file=sys.stderr)
t0 = time.time()
cur = dbh.cursor()
cur.execute(qry)
print("query took", time.time() - t0, "seconds")
return cur | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_cursor(self):\r\n cursor = self.connection.cursor()\r\n return cursor",
"def cursor():\n dbh = handle()\n return dbh.cursor()",
"def get_cursor(self, *args, **kwargs):",
"def _cursor(self):\n cursor = self.conn.cursor()\n\n return cursor",
"def cursor(self):\n ... | [
"0.77592504",
"0.7748701",
"0.7519825",
"0.7482258",
"0.7413113",
"0.7369768",
"0.7340349",
"0.731754",
"0.731754",
"0.7271211",
"0.7255303",
"0.7223003",
"0.71825427",
"0.7179095",
"0.7167863",
"0.71537787",
"0.70854706",
"0.7069509",
"0.7030988",
"0.7016853",
"0.69801897",
... | 0.6644475 | 35 |
print data returned from a query in nice aligned columns | def printPrettyFromCursor(cur, args):
rows = []
#get column headers -- not very ergonomic
# exit if function does nto return things
if not cur.description:
return
if args.header:
rows.append([item[0] for item in cur.description])
rows = rows + cur.fetchall()
zipped = zip(*ro... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def format_bash(self,query_results):\n data=query_results.data\n \n name=\"ddb\"\n\n print (\"{0}_row_length={1}\".format(name,len(data)))\n print (\"{0}_column_length={1}\".format(name,len(query_results.columns)))\n print (\"\")\n\n column_index=0\n for colu... | [
"0.7219429",
"0.7074841",
"0.6891936",
"0.6827231",
"0.6793333",
"0.67474353",
"0.67346114",
"0.67292243",
"0.6686646",
"0.6618329",
"0.65630335",
"0.65622455",
"0.65239674",
"0.65194356",
"0.6492314",
"0.6478941",
"0.64734554",
"0.64621496",
"0.6452394",
"0.6452233",
"0.6450... | 0.6469105 | 17 |
output the query results as a CSV | def printCSVFromCursor(cur, args):
import csv
if not cur.description:
return #nothing to print.
writer = csv.writer(sys.stdout, delimiter=args.delimiter, quotechar='|',
lineterminator='\n', quoting=csv.QUOTE_MINIMAL)
if args.header:
hdr = [col[0] for col in cur.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_query_csv(self):\n\n self.query_df.to_csv(self.query_output_file)",
"def process_results(result, title=\"\", doWrite=True, query=\"\"):\n\n\tif not result or not result.returns_rows:\n\t\tprint \"-> 0 records returned\"\n\t\tprint result\n\t\treturn\n\n\tdoPrint = True\n\n\t# get column names\n... | [
"0.7392405",
"0.70663726",
"0.7028599",
"0.69381297",
"0.690984",
"0.6848239",
"0.679453",
"0.67345744",
"0.6721",
"0.667645",
"0.6661048",
"0.6578225",
"0.6552651",
"0.65504265",
"0.6536412",
"0.6536164",
"0.6484346",
"0.6483709",
"0.64407593",
"0.6437607",
"0.64326495",
"... | 0.0 | -1 |
Send the query to the database and render the results as requested | def query(args):
dbh = despydb.DesDbi(args.service, args.section)
if args.query not in "-+":
do1Query(dbh, args.query, args)
elif args.query == "-":
line = sys.stdin.readline()
while line:
line = line.strip()
if not line or line.startswith("#"):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def execute_query(self):\n try:\n # get query and templates\n query = self.request.data.get(\"query\", None)\n templates = self.request.data.get(\"templates\", \"[]\")\n registries = self.get_registries()\n order_by_field = self.request.data.get(\"order... | [
"0.6671056",
"0.6531192",
"0.64979106",
"0.63335913",
"0.6329612",
"0.6328952",
"0.6239457",
"0.6226256",
"0.6211864",
"0.6154065",
"0.61292285",
"0.611252",
"0.60824287",
"0.6070119",
"0.60307413",
"0.6025734",
"0.5974545",
"0.5968892",
"0.59402233",
"0.5872386",
"0.5866393"... | 0.0 | -1 |
Parse command line arguments and pass them to the query engine | def main():
parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('--service', default=os.path.join(os.getenv("HOME"), ".desservices.ini"))
parser.add_argument('--section', '-s', default='db-desoper',
help='sec... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parse_arguments(args):",
"def arg_parse():\n p = ap.ArgumentParser()\n p.add_argument('column_name',\n type=str,\n help='column_name to search')\n p.add_argument('operation',\n choices=['gt', 'lt', 'eq'])\n p.add_argument('limit',\n ... | [
"0.7214492",
"0.67600626",
"0.6744214",
"0.6540915",
"0.65117174",
"0.64484125",
"0.6437705",
"0.63874245",
"0.63734406",
"0.63580865",
"0.63525504",
"0.63441116",
"0.6306649",
"0.62947834",
"0.6288351",
"0.6278856",
"0.6265019",
"0.6261954",
"0.6249996",
"0.6239955",
"0.6234... | 0.6177763 | 30 |
Initializes the VNIStatsTableEntrySchema object attributes. | def __init__(self, py_dict=None):
super(VNIStatsTableEntrySchema, self).__init__()
self.update_arp = None
self.query_arp = None
if py_dict is not None:
self.get_object_from_py_dict(py_dict) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def InitStats(ss):\n\n ss.SumSSE = 0\n ss.SumAvgSSE = 0\n ss.SumCosDiff = 0\n ss.SumErr = 0\n ss.FirstZero = -1\n ss.NZero = 0\n\n ss.TrlErr = 0\n ss.TrlSSE = 0\n ss.TrlAvgSSE = 0\n ss.EpcSSE = 0\n ss.EpcAvgSSE = 0\n ss.EpcPctErr =... | [
"0.6132577",
"0.61266005",
"0.582939",
"0.56516737",
"0.56412935",
"0.5606859",
"0.5601135",
"0.55859405",
"0.5571048",
"0.555038",
"0.5544171",
"0.54862404",
"0.54842335",
"0.54761785",
"0.5465003",
"0.5443442",
"0.5419218",
"0.5413731",
"0.54091996",
"0.539648",
"0.5395933"... | 0.70146513 | 0 |
Search through a table and return the first [row, column] pair who's value is None. | def find_unassigned_table_cell(table):
for row in range(len(table)):
for column in range(len(table[row])):
if table[row][column] is None:
return row, column
return row, column | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _get_first_element(cls, d):\n\n t = np.where(d[:, 2] > 0)[0]\n if len(t):\n return d[t[0], 0], d[t[0], 1], t[0]\n return None, None, None",
"def firstEmptyCell(board):\r\n for i in range(9):\r\n for j in range(9):\r\n if board[i][j] == 0:\r\n ... | [
"0.64960337",
"0.634782",
"0.633694",
"0.6331864",
"0.6245917",
"0.6233299",
"0.60606706",
"0.60600805",
"0.5962007",
"0.5913134",
"0.5856047",
"0.5801559",
"0.57643837",
"0.57631135",
"0.5742628",
"0.5713552",
"0.56185967",
"0.5603105",
"0.559049",
"0.55511755",
"0.54848987"... | 0.7773614 | 0 |
Creates a parser and parses arguments. View help for valid flags and inputs. Make sure that subjects are aligned on the same line for all text files. For instance, if a subject's path to epi data is found on line 10 of the file containing paths to epi data, the subject's anatomical, output directory, and, optionally, s... | def parse_args(args):
parser = argparse.ArgumentParser(
description="""Generates and runs an afni_proc.py script to preprocess resting state fMRI data""",
formatter_class=argparse.RawDescriptionHelpFormatter)
# Optional Flags
parser.add_argument("-t", "--trs_remove", action="store", defaul... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parser():\n \n \n parser = ap.ArgumentParser(description='Parsing some file names in various forms')\n group = parser.add_mutually_exclusive_group()\n group.add_argument('-f','--filepaths',dest='filepaths',metavar='PATH1,PATH2,...',type=str,\n help='Input a string or list ... | [
"0.6712574",
"0.6688427",
"0.66874635",
"0.66772443",
"0.66594255",
"0.6603691",
"0.6600838",
"0.6586496",
"0.6582369",
"0.6565811",
"0.65460694",
"0.65405774",
"0.65191436",
"0.6493583",
"0.6438784",
"0.64371055",
"0.6433585",
"0.6426523",
"0.6417857",
"0.6408057",
"0.640757... | 0.0 | -1 |
Trigger the recompute of the taxes if the pricelist is changed on the invoice. | def _compute_tax_id(self):
for inv in self:
for line in inv.invoice_line_ids:
line.tax_ids = line._get_computed_taxes()
inv._recompute_dynamic_lines(recompute_all_taxes=True, recompute_tax_base_amount=True) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _compute_taxed_lst_price2(self):\n company_id = self._context.get(\n 'company_id', self.env.user.company_id.id)\n for product in self:\n product.taxed_lst_price = product.taxes_id.filtered(\n lambda x: x.company_id.id == company_id).compute_all(\n ... | [
"0.653335",
"0.6431408",
"0.6352757",
"0.6336871",
"0.6145967",
"0.59902364",
"0.5716785",
"0.56393623",
"0.56122774",
"0.55956626",
"0.5582768",
"0.553678",
"0.5504171",
"0.54466707",
"0.5415386",
"0.5409386",
"0.5396369",
"0.53878236",
"0.53794277",
"0.5378179",
"0.5345203"... | 0.59978676 | 5 |
Delete old files from FS, nullify path value in DB | def remove_files(max_age_sec):
with session_transaction() as session:
nb_deleted = File.remove_old_files(max_age_sec, session)
log.debug("Max_age_sec: %s Nb_deleted: %s", max_age_sec, nb_deleted)
return nb_deleted | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_path():\n #TODO delete path from database\n pass",
"def clear_outdated_files():\n for f in os.listdir(MEDIA_ROOT):\n file_path = os.path.join(MEDIA_ROOT, f)\n if os.path.isfile(file_path) and os.stat(file_path).st_mtime < time.time() - STORE_PDF_DAYS * 86400:\n os.rem... | [
"0.71850747",
"0.6885767",
"0.6821727",
"0.68192995",
"0.6756899",
"0.6753063",
"0.67357886",
"0.6704431",
"0.6660613",
"0.65907323",
"0.6541612",
"0.6512646",
"0.6490424",
"0.64857215",
"0.64697266",
"0.6452348",
"0.64341843",
"0.64337134",
"0.6421972",
"0.64179254",
"0.6413... | 0.0 | -1 |
Delete old files from FS, nullify path value in DB | def remove_files_size(max_size):
with session_transaction() as session:
nb_deleted = File.remove_files_max_size(max_size, session)
log.debug("Max_size: %s Nb_deleted: %s", max_size, nb_deleted)
return nb_deleted | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def delete_path():\n #TODO delete path from database\n pass",
"def clear_outdated_files():\n for f in os.listdir(MEDIA_ROOT):\n file_path = os.path.join(MEDIA_ROOT, f)\n if os.path.isfile(file_path) and os.stat(file_path).st_mtime < time.time() - STORE_PDF_DAYS * 86400:\n os.rem... | [
"0.7185494",
"0.68854076",
"0.682105",
"0.6820686",
"0.6756345",
"0.6754087",
"0.67368037",
"0.67044604",
"0.6659871",
"0.65905446",
"0.654088",
"0.6512677",
"0.64891416",
"0.6486032",
"0.646998",
"0.64524764",
"0.64349043",
"0.6433434",
"0.64230174",
"0.64174724",
"0.6413873... | 0.0 | -1 |
Create mock input block. | def fixture_input_block():
return Mock() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mockRawInput(mock):\n original_raw_input = __builtin__.raw_input\n __builtin__.raw_input = lambda _: mock\n yield\n __builtin__.raw_input = original_raw_input",
"def get_input_mock(inputs=None): # Use this mock if a contest requires interactive input.\n stdin_mock = MagicMock()\n s... | [
"0.6843587",
"0.66973007",
"0.6653255",
"0.63940287",
"0.6144296",
"0.6105641",
"0.5916343",
"0.58348626",
"0.57676345",
"0.56919837",
"0.55923426",
"0.55832005",
"0.55725527",
"0.5560723",
"0.5554768",
"0.55407476",
"0.5519871",
"0.5497402",
"0.54970086",
"0.5474238",
"0.545... | 0.8625998 | 0 |
Create mock output block. | def fixture_output_block():
return Mock() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fixture_input_block():\n return Mock()",
"def test_03_out(self, mock_stdout):\n msg = udocker.Msg(udocker.Msg.MSG)\n msg.out(\"111\", \"222\", \"333\", 444, ('555'))\n self.assertEqual(\"111 222 333 444 555\\n\", mock_stdout.getvalue())\n sys.stdout = STDOUT\n sys.stderr... | [
"0.64789915",
"0.6219317",
"0.6141315",
"0.61250573",
"0.5885682",
"0.58214647",
"0.5781268",
"0.5775005",
"0.5772843",
"0.57672167",
"0.57131493",
"0.5694267",
"0.5624239",
"0.56047845",
"0.5593248",
"0.55418766",
"0.5537944",
"0.5513371",
"0.5504529",
"0.5503281",
"0.549821... | 0.85911703 | 0 |
Signal objects are connected as expected. | def test_signals_connected(input_block, output_block, kwargs):
input_signal = input_block()
output_cb = output_block()
with patch('rabbithole.cli.Batcher') as batcher_cls:
create_flow(**kwargs)
input_signal.connect.assert_called_once_with(
batcher_cls().message_received_cb,
wea... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __enter__(self):\n if self.models:\n for m in self.models:\n self._connect(m)\n else:\n self._connect()\n return super(SignalChecker, self).__enter__()",
"def connected(self):\n pass",
"def connected(self):\n pass",
"def connected(se... | [
"0.68499154",
"0.68350697",
"0.68350697",
"0.68059605",
"0.68059605",
"0.66427344",
"0.660732",
"0.6563658",
"0.64170116",
"0.63776684",
"0.63700235",
"0.634242",
"0.6340475",
"0.6244015",
"0.6181083",
"0.6158528",
"0.61514074",
"0.61073714",
"0.61058384",
"0.61058384",
"0.60... | 0.0 | -1 |
Exit on error trying to get the input signal. | def test_exit_on_input_signal_error(input_block, kwargs):
input_block.side_effect = Exception()
with pytest.raises(SystemExit) as exc_info:
create_flow(**kwargs)
assert exc_info.value.code == 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def call_error():\r\n print(\"Error in input format.\")\r\n sys.exit()",
"def signal_handler(sig, frame):\n raise ExitException()",
"def handle_sigterm(signum, frame):\n raise TermException",
"def signal_handler(signum, frame):\n sys.exit(0)",
"def _signal_handler(signum, frame):\n re... | [
"0.6209089",
"0.6186397",
"0.61726344",
"0.6003437",
"0.59561807",
"0.5893812",
"0.5862972",
"0.57583606",
"0.57415015",
"0.57415015",
"0.57415015",
"0.5725218",
"0.57188",
"0.5668054",
"0.566546",
"0.56114185",
"0.5606983",
"0.5574848",
"0.5552682",
"0.5544291",
"0.5509935",... | 0.5870097 | 6 |
Exit on error trying to get the output callback. | def test_exit_on_output_cb_error(output_block, kwargs):
output_block.side_effect = Exception()
with pytest.raises(SystemExit) as exc_info:
create_flow(**kwargs)
assert exc_info.value.code == 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def finalize_error():\n print('')\n exit(-1)",
"def call_error():\r\n print(\"Error in input format.\")\r\n sys.exit()",
"def error_handler(self):\n if self.ctx.exit_code is not None:\n return self.ctx.exit_code",
"def failure_callback(self):\n error_filename = self.run_d... | [
"0.66235447",
"0.6495243",
"0.6490984",
"0.64486736",
"0.628487",
"0.6235582",
"0.6078088",
"0.6077453",
"0.60774106",
"0.6030557",
"0.6004493",
"0.5937128",
"0.5927308",
"0.5906779",
"0.58894056",
"0.5872576",
"0.5862885",
"0.58574635",
"0.58571845",
"0.58409643",
"0.5838021... | 0.6417455 | 4 |
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