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def sizeof(object): return sys.getsizeof(object)
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return the size of an object when packed .
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def gradient1(f, v): return tt.flatten(tt.grad(f, v, disconnected_inputs='warn'))
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flat gradient of f wrt v .
train
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def showerror(title=None, message=None, **options): return _show(title, message, ERROR, OK, **options)
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show an error message .
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def _run_wsgi_app(*args): global _run_wsgi_app from werkzeug.test import run_wsgi_app as _run_wsgi_app return _run_wsgi_app(*args)
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this function replaces itself to ensure that the test module is not imported unless required .
train
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def load_ancestors(pages): pages_by_id = dict(((page.pk, page) for page in pages)) pages_list = list(pages) missing = list(pages) while missing: page = missing.pop() page.ancestors_descending = [] page._cached_descendants = [] if (page.parent_id and (page.parent_id not in pages_by_id)): pages_list.append(page.parent) pages_by_id[page.parent_id] = page.parent missing.append(page.parent) pages_list.sort(key=(lambda page: page.path)) for page in pages_list: if page.parent_id: parent = pages_by_id[page.parent_id] page.ancestors_descending = (parent.ancestors_descending + [parent]) for ancestor in page.ancestors_descending: ancestor._cached_descendants.append(page) else: page.ancestors_descending = [] page.ancestors_ascending = list(reversed(page.ancestors_descending)) return pages_list
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loads the ancestors .
train
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@then(u'the command output should contain "{text}"') def step_command_output_should_contain_text(context, text): expected_text = text if (('{__WORKDIR__}' in expected_text) or ('{__CWD__}' in expected_text)): expected_text = textutil.template_substitute(text, __WORKDIR__=posixpath_normpath(context.workdir), __CWD__=posixpath_normpath(os.getcwd())) actual_output = context.command_result.output with on_assert_failed_print_details(actual_output, expected_text): textutil.assert_normtext_should_contain(actual_output, expected_text)
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example: then the command output should contain "text" .
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def NoCallback(*args, **kwargs): pass
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used where the conclusion of an asynchronous operation can be ignored .
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def _add_step(emr_connection, step, jobflow_name, **jobflow_kw): running = get_live_clusters(emr_connection) for cluster in running: if (cluster.name == jobflow_name): jobflowid = cluster.id emr_connection.add_jobflow_steps(jobflowid, step) print ('Added %s to jobflow %s' % (step.name, jobflowid)) break else: base = TrafficBase(emr_connection, jobflow_name, steps=[step], **jobflow_kw) base.run() jobflowid = base.jobflowid print ('Added %s to new jobflow %s' % (step.name, jobflowid)) return jobflowid
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add step to a running jobflow .
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def dup_zz_mignotte_bound(f, K): a = dup_max_norm(f, K) b = abs(dup_LC(f, K)) n = dup_degree(f) return (((K.sqrt(K((n + 1))) * (2 ** n)) * a) * b)
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mignotte bound for univariate polynomials in k[x] .
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def decompogen(f, symbol): f = sympify(f) result = [] if isinstance(f, (Function, Pow)): if (f.args[0] == symbol): return [f] result += ([f.subs(f.args[0], symbol)] + decompogen(f.args[0], symbol)) return result fp = Poly(f) gens = list(filter((lambda x: (symbol in x.free_symbols)), fp.gens)) if ((len(gens) == 1) and (gens[0] != symbol)): f1 = f.subs(gens[0], symbol) f2 = gens[0] result += ([f1] + decompogen(f2, symbol)) return result try: result += decompose(f) return result except ValueError: return [f]
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computes general functional decomposition of f .
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def configure_follower(follower_ident): from sqlalchemy.testing import provision provision.FOLLOWER_IDENT = follower_ident
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configure required state for a follower .
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def find_git(): if (not utils.is_win32()): return None git_bindir = os.path.expanduser(os.path.join(u'~', u'.config', u'git-cola', u'git-bindir')) if core.exists(git_bindir): custom_path = core.read(git_bindir).strip() if (custom_path and core.exists(custom_path)): return custom_path pf = os.environ.get(u'ProgramFiles', u'C:\\Program Files') pf32 = os.environ.get(u'ProgramFiles(x86)', u'C:\\Program Files (x86)') for p in [pf32, pf, u'C:\\']: candidate = os.path.join(p, u'Git\\bin') if os.path.isdir(candidate): return candidate return None
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return the path of git .
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def update_configuration(lineagename, archive_dir, target, cli_config): config_filename = renewal_filename_for_lineagename(cli_config, lineagename) temp_filename = (config_filename + '.new') if os.path.exists(temp_filename): os.unlink(temp_filename) values = relevant_values(vars(cli_config.namespace)) write_renewal_config(config_filename, temp_filename, archive_dir, target, values) os.rename(temp_filename, config_filename) return configobj.ConfigObj(config_filename)
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modifies lineagenames config to contain the specified values .
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def get_vmdk_name_from_ovf(xmlstr): ovf = etree.fromstring(encodeutils.safe_encode(xmlstr)) nsovf = ('{%s}' % ovf.nsmap['ovf']) disk = ovf.find(('./%sDiskSection/%sDisk' % (nsovf, nsovf))) file_id = disk.get(('%sfileRef' % nsovf)) file = ovf.find(('./%sReferences/%sFile[@%sid="%s"]' % (nsovf, nsovf, nsovf, file_id))) vmdk_name = file.get(('%shref' % nsovf)) return vmdk_name
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parse the ova descriptor to extract the vmdk name .
train
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def test_probable_prime(candidate, randfunc=None): if (randfunc is None): randfunc = Random.new().read if (not isinstance(candidate, Integer)): candidate = Integer(candidate) try: map(candidate.fail_if_divisible_by, _sieve_base) except ValueError: return False mr_ranges = ((220, 30), (280, 20), (390, 15), (512, 10), (620, 7), (740, 6), (890, 5), (1200, 4), (1700, 3), (3700, 2)) bit_size = candidate.size_in_bits() try: mr_iterations = list(filter((lambda x: (bit_size < x[0])), mr_ranges))[0][1] except IndexError: mr_iterations = 1 if (miller_rabin_test(candidate, mr_iterations, randfunc=randfunc) == COMPOSITE): return COMPOSITE if (lucas_test(candidate) == COMPOSITE): return COMPOSITE return PROBABLY_PRIME
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test if a number is prime .
train
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def decode_morse(msg, sep='|', mapping=None): mapping = (mapping or morse_char) word_sep = (2 * sep) characterstring = [] words = msg.strip(word_sep).split(word_sep) for word in words: letters = word.split(sep) chars = [mapping[c] for c in letters] word = ''.join(chars) characterstring.append(word) rv = ' '.join(characterstring) return rv
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decodes a morse code with letters separated by sep and words by word_sep into plaintext .
train
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def read_sql_query(sql, con, index_col=None, coerce_float=True, params=None, parse_dates=None, chunksize=None): pandas_sql = pandasSQL_builder(con) return pandas_sql.read_query(sql, index_col=index_col, params=params, coerce_float=coerce_float, parse_dates=parse_dates, chunksize=chunksize)
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read sql query into a dataframe .
train
true
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def to_key_val_list(value): if (value is None): return None if isinstance(value, (str, bytes, bool, int)): raise ValueError('cannot encode objects that are not 2-tuples') if isinstance(value, collections.Mapping): value = value.items() return list(value)
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take an object and test to see if it can be represented as a dictionary .
train
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@pytest.fixture(params=[0, 1, (-1)]) def pickle_protocol(request): return request.param
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fixture to run all the tests for protocols 0 and 1 .
train
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def search_dict_list(l, key, value): for i in l: if (i.get(key) == value): return i
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search a list of dict * return dict with specific value & key .
train
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def is_builtin_object(node): return (node and (node.root().name == BUILTINS_NAME))
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returns true if the given node is an object from the __builtin__ module .
train
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def l1_min_c(X, y, loss='squared_hinge', fit_intercept=True, intercept_scaling=1.0): if (loss not in ('squared_hinge', 'log')): raise ValueError('loss type not in ("squared_hinge", "log", "l2")') X = check_array(X, accept_sparse='csc') check_consistent_length(X, y) Y = LabelBinarizer(neg_label=(-1)).fit_transform(y).T den = np.max(np.abs(safe_sparse_dot(Y, X))) if fit_intercept: bias = (intercept_scaling * np.ones((np.size(y), 1))) den = max(den, abs(np.dot(Y, bias)).max()) if (den == 0.0): raise ValueError('Ill-posed l1_min_c calculation: l1 will always select zero coefficients for this data') if (loss == 'squared_hinge'): return (0.5 / den) else: return (2.0 / den)
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return the lowest bound for c such that for c in the model is guaranteed not to be empty .
train
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def kit(): if (len(request.args) == 2): s3db.configure('budget_kit', update_next=URL(f='kit_item', args=request.args[1])) return s3_rest_controller(rheader=s3db.budget_rheader, main='code')
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rest controller for kits .
train
false
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def get_dir_pkg(d): parent = os.path.dirname(os.path.realpath(d)) while ((not os.path.exists(os.path.join(d, MANIFEST_FILE))) and (not os.path.exists(os.path.join(d, PACKAGE_FILE))) and (parent != d)): d = parent parent = os.path.dirname(d) if (os.path.exists(os.path.join(d, MANIFEST_FILE)) or os.path.exists(os.path.join(d, PACKAGE_FILE))): pkg = os.path.basename(os.path.abspath(d)) return (d, pkg) return (None, None)
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get the package that the directory is contained within .
train
false
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@jingo.register.filter def locale_html(translatedfield): if (not translatedfield): return '' site_locale = translation.to_locale(translation.get_language()) locale = translation.to_locale(translatedfield.locale) if (locale == site_locale): return '' else: rtl_locales = map(translation.to_locale, settings.RTL_LANGUAGES) textdir = ('rtl' if (locale in rtl_locales) else 'ltr') return jinja2.Markup((' lang="%s" dir="%s"' % (jinja2.escape(translatedfield.locale), textdir)))
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html attributes for languages different than the site language .
train
false
29,464
def findtests(testdir=None, stdtests=STDTESTS, nottests=NOTTESTS): testdir = findtestdir(testdir) names = os.listdir(testdir) tests = [] others = (set(stdtests) | nottests) for name in names: (modname, ext) = os.path.splitext(name) if ((modname[:5] == 'test_') and (ext == '.py') and (modname not in others)): tests.append(modname) return (stdtests + sorted(tests))
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return a list of all applicable test modules .
train
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def abspath_listdir(path): path = abspath(path) return [join(path, filename) for filename in listdir(path)]
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lists paths content using absolute paths .
train
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def pipe_wait(popens): popens = copy.copy(popens) results = ([0] * len(popens)) while popens: last = popens.pop((-1)) results[len(popens)] = last.wait() return results
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given an array of popen objects returned by the pipe method .
train
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def _ScoreRequested(params): return (params.has_scorer_spec() and params.scorer_spec().has_scorer())
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returns true if match scoring requested .
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def get_quarter_names(width='wide', context='format', locale=LC_TIME): return Locale.parse(locale).quarters[context][width]
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return the quarter names used by the locale for the specified format .
train
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def send_args_to_spyder(args): port = CONF.get('main', 'open_files_port') for _x in range(200): try: for arg in args: client = socket.socket(socket.AF_INET, socket.SOCK_STREAM, socket.IPPROTO_TCP) client.connect(('127.0.0.1', port)) if is_unicode(arg): arg = arg.encode('utf-8') client.send(osp.abspath(arg)) client.close() except socket.error: time.sleep(0.25) continue break
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simple socket client used to send the args passed to the spyder executable to an already running instance .
train
true
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def split_slug(slug): slug_split = slug.split('/') length = len(slug_split) root = None seo_root = '' bad_seo_roots = ['Web'] if (length > 1): root = slug_split[0] if (root in bad_seo_roots): if (length > 2): seo_root = ((root + '/') + slug_split[1]) else: seo_root = root specific = slug_split.pop() parent = '/'.join(slug_split) return {'specific': specific, 'parent': parent, 'full': slug, 'parent_split': slug_split, 'length': length, 'root': root, 'seo_root': seo_root}
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utility function to do basic slug splitting .
train
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def _collapse_addresses_internal(addresses): to_merge = list(addresses) subnets = {} while to_merge: net = to_merge.pop() supernet = net.supernet() existing = subnets.get(supernet) if (existing is None): subnets[supernet] = net elif (existing != net): del subnets[supernet] to_merge.append(supernet) last = None for net in sorted(subnets.values()): if (last is not None): if (last.broadcast_address >= net.broadcast_address): continue (yield net) last = net
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loops through the addresses .
train
true
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def demographic(): return s3_rest_controller('stats', 'demographic')
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rest controller .
train
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def copystat(src, dst): st = os.stat(src) mode = stat.S_IMODE(st.st_mode) if hasattr(os, 'utime'): os.utime(dst, (st.st_atime, st.st_mtime)) if hasattr(os, 'chmod'): os.chmod(dst, mode) if (hasattr(os, 'chflags') and hasattr(st, 'st_flags')): os.chflags(dst, st.st_flags)
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copy all stat info from src to dst .
train
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def doc_wraps(func): def _(func2): if (func.__doc__ is not None): func2.__doc__ = func.__doc__.replace('>>>', '>>').replace('...', '..') return func2 return _
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copy docstring from one function to another .
train
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def test_http_invalid_response_header(): mocked_socket = mock.MagicMock() mocked_socket.sendall = mock.MagicMock() mocked_request = mock.MagicMock() response = Response(mocked_request, mocked_socket, None) with pytest.raises(InvalidHeader): response.start_response('200 OK', [('foo', 'essai\r\n')]) response = Response(mocked_request, mocked_socket, None) with pytest.raises(InvalidHeaderName): response.start_response('200 OK', [('foo\r\n', 'essai')])
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tests whether http response headers are contains control chars .
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def bootstrap2(value, distr, args=(), nobs=200, nrep=100): count = 0 for irep in range(nrep): rvs = distr.rvs(args, **{'size': nobs}) params = distr.fit_vec(rvs) cdfvals = np.sort(distr.cdf(rvs, params)) stat = asquare(cdfvals, axis=0) count += (stat >= value) return ((count * 1.0) / nrep)
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monte carlo p-values for gof currently hardcoded for a^2 only non vectorized .
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def _get_local_rev_and_branch(target, user, password): log.info('Checking local revision for {0}'.format(target)) try: local_rev = __salt__['git.revision'](target, user=user, password=password, ignore_retcode=True) except CommandExecutionError: log.info('No local revision for {0}'.format(target)) local_rev = None log.info('Checking local branch for {0}'.format(target)) try: local_branch = __salt__['git.current_branch'](target, user=user, password=password, ignore_retcode=True) except CommandExecutionError: log.info('No local branch for {0}'.format(target)) local_branch = None return (local_rev, local_branch)
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return the local revision for before/after comparisons .
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def get_sosfiltfilt(): try: from scipy.signal import sosfiltfilt except ImportError: sosfiltfilt = _sosfiltfilt return sosfiltfilt
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helper to get sosfiltfilt from scipy .
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def ihilbert(x): return (- hilbert(x))
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return inverse hilbert transform of a periodic sequence x .
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@register(u'clear-screen') def clear_screen(event): event.cli.renderer.clear()
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clear the screen and redraw everything at the top of the screen .
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def Semaphore(*args, **kwargs): return _Semaphore(*args, **kwargs)
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a factory function that returns a new semaphore .
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def output_json(data, code, headers=None): settings = current_app.config.get('RESTFUL_JSON', {}) if current_app.debug: settings.setdefault('indent', 4) settings.setdefault('sort_keys', True) dumped = (dumps(data, **settings) + '\n') resp = make_response(dumped, code) resp.headers.extend((headers or {})) return resp
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makes a flask response with a json encoded body .
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def smart_split(text): text = force_unicode(text) for bit in smart_split_re.finditer(text): (yield bit.group(0))
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generator that splits a string by spaces .
train
false
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def paths_from_indexes(model, indexes, item_type=TreeWidgetItem.TYPE, item_filter=None): items = [model.itemFromIndex(i) for i in indexes] return paths_from_items(items, item_type=item_type, item_filter=item_filter)
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return paths from a list of qstandarditemmodel indexes .
train
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def kerp_zeros(nt): if ((not isscalar(nt)) or (floor(nt) != nt) or (nt <= 0)): raise ValueError('nt must be positive integer scalar.') return specfun.klvnzo(nt, 7)
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compute nt zeros of the kelvin function ker(x) .
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def buildMixedNestedNetwork(): N = RecurrentNetwork('outer') a = LinearLayer(1, name='a') b = LinearLayer(2, name='b') c = buildNetwork(2, 3, 1) c.name = 'inner' N.addInputModule(a) N.addModule(c) N.addOutputModule(b) N.addConnection(FullConnection(a, b)) N.addConnection(FullConnection(b, c)) N.addRecurrentConnection(FullConnection(c, c)) N.sortModules() return N
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build a nested network with the inner one being a ffn and the outer one being recurrent .
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def get_checkers_for(lang=u'python'): global NOTIFICATIONS_CHECKERS return NOTIFICATIONS_CHECKERS.get(lang, [])
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get a registered checker for some language .
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def linear_interpolate(p, x, y): return LinearInterpolate()(p, x, y)
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elementwise linear-interpolation function .
train
false
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def _get_subgraph(codons, G): subgraph = {} for i in codons: subgraph[i] = {} for j in codons: if (i != j): subgraph[i][j] = G[i][j] return subgraph
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get the subgraph that contains all codons in list .
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def _prefix(subject): if email().prefix: return '{} {}'.format(email().prefix, subject) else: return subject
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if the config has a special prefix for emails then this function adds this prefix .
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def store_outcome_parameters(request_params, user, lti_consumer): result_id = request_params.get('lis_result_sourcedid', None) if result_id: result_service = request_params.get('lis_outcome_service_url', None) if (not result_service): log.warn('Outcome Service: lis_outcome_service_url parameter missing from scored assignment; we will be unable to return a score. Request parameters: %s', request_params) return usage_key = request_params['usage_key'] course_key = request_params['course_key'] (outcomes, __) = OutcomeService.objects.get_or_create(lis_outcome_service_url=result_service, lti_consumer=lti_consumer) GradedAssignment.objects.get_or_create(lis_result_sourcedid=result_id, course_key=course_key, usage_key=usage_key, user=user, outcome_service=outcomes)
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determine whether a set of lti launch parameters contains information about an expected score .
train
false
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def is_global(name): return (name and (name[0] == SEP))
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test if name is a global graph resource name .
train
false
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def _split_left_right(name): parts = name.split(None, 1) (lhs, rhs) = [parts[0], (parts[1] if (len(parts) > 1) else u'')] return (lhs, rhs)
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split record name at the first whitespace and return both parts .
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def tokenMap(func, *args): def pa(s, l, t): return [func(tokn, *args) for tokn in t] try: func_name = getattr(func, '__name__', getattr(func, '__class__').__name__) except Exception: func_name = str(func) pa.__name__ = func_name return pa
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helper to define a parse action by mapping a function to all elements of a parseresults list .
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def getFilesWithFileTypesWithoutWordsRecursively(fileTypes, words=[], fileInDirectory=''): filesWithFileTypesRecursively = [] for filePath in getFilePathsRecursively(fileInDirectory): for fileType in fileTypes: if isFileWithFileTypeWithoutWords(fileType, filePath, words): filesWithFileTypesRecursively.append(filePath) filesWithFileTypesRecursively.sort() return filesWithFileTypesRecursively
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get files recursively which have a given file type .
train
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def test_line_endings(): tempdir = _TempDir() with open(op.join(tempdir, 'foo'), 'wb') as fid: fid.write('bad\r\ngood\n'.encode('ascii')) _assert_line_endings(tempdir) with open(op.join(tempdir, 'bad.py'), 'wb') as fid: fid.write('\x97') assert_raises(AssertionError, _assert_line_endings, tempdir) with open(op.join(tempdir, 'bad.py'), 'wb') as fid: fid.write('bad\r\ngood\n'.encode('ascii')) assert_raises(AssertionError, _assert_line_endings, tempdir) _assert_line_endings(_get_root_dir())
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test line endings of mne-python .
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def parse_contributions_calendar(contributions_calendar): for line in contributions_calendar.splitlines(): for day in line.split(): if ('data-count=' in day): commit = day.split('=')[1] commit = commit.strip('"') (yield int(commit))
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yield daily counts extracted from the contributions svg .
train
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def replay(): g['pause'] = False printNicely(green('Stream is running back now'))
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a simple context manager for using the httreplay library .
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def filter_docker_plays(plays, repo_path): items = set() for play in plays: dockerfile = pathlib2.Path(DOCKER_PATH_ROOT, play, 'Dockerfile') if dockerfile.exists(): items.add(play) else: LOGGER.warning(("covered playbook '%s' does not have Dockerfile." % play)) return items
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filters out docker plays that do not have a dockerfile .
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def db_check(name, table=None, **connection_args): ret = [] if (table is None): tables = db_tables(name, **connection_args) for table in tables: log.info("Checking table '{0}' in db '{1}'..".format(name, table)) ret.append(__check_table(name, table, **connection_args)) else: log.info("Checking table '{0}' in db '{1}'..".format(name, table)) ret = __check_table(name, table, **connection_args) return ret
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repairs the full database or just a given table cli example: .
train
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def setup_test(): warnings.simplefilter('default') from scipy import signal, ndimage, special, optimize, linalg from scipy.io import loadmat from skimage import viewer np.random.seed(0) warnings.simplefilter('error')
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direct invoke test .
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def ffi_callback(signature, name, **kwargs): def wrapper(func): if lib.Cryptography_STATIC_CALLBACKS: ffi.def_extern(name=name, **kwargs)(func) callback = getattr(lib, name) else: callback = ffi.callback(signature, **kwargs)(func) return callback return wrapper
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callback dispatcher the ffi_callback() dispatcher keeps callbacks compatible between dynamic and static callbacks .
train
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def get_property(obj, name, old_name, default=None): if hasattr(obj, old_name): warnings.warn(('Property %s is obsolete, please use %s instead' % (old_name, name)), stacklevel=2) return getattr(obj, old_name) return getattr(obj, name, default)
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check if old property name exists and if it does - show warning message and return value .
train
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def raise_if_reindex_in_progress(site): already_reindexing = Reindexing.objects._is_reindexing(site) if (already_reindexing and ('FORCE_INDEXING' not in os.environ)): raise CommandError('Indexation already occurring. Add a FORCE_INDEXING variable in the environ to force it')
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checks if the database indexation flag is on for the given site .
train
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def do_indent(s, width=4, indentfirst=False): indention = (u' ' * width) rv = (u'\n' + indention).join(s.splitlines()) if indentfirst: rv = (indention + rv) return rv
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return a copy of the passed string .
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def manage_changed(wrapped): def changed(session, *arg, **kw): session.accessed = int(time.time()) session.changed() return wrapped(session, *arg, **kw) changed.__doc__ = wrapped.__doc__ return changed
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decorator which causes a cookie to be set when a setter method is called .
train
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def whitespace_before_parameters(logical_line, tokens): (prev_type, prev_text, __, prev_end, __) = tokens[0] for index in range(1, len(tokens)): (token_type, text, start, end, __) = tokens[index] if ((token_type == tokenize.OP) and (text in '([') and (start != prev_end) and ((prev_type == tokenize.NAME) or (prev_text in '}])')) and ((index < 2) or (tokens[(index - 2)][1] != 'class')) and (not keyword.iskeyword(prev_text))): (yield (prev_end, ("E211 whitespace before '%s'" % text))) prev_type = token_type prev_text = text prev_end = end
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avoid extraneous whitespace in the following situations: - immediately before the open parenthesis that starts the argument list of a function call .
train
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def safe_mask(X, mask): mask = np.asarray(mask) if np.issubdtype(mask.dtype, np.int): return mask if hasattr(X, 'toarray'): ind = np.arange(mask.shape[0]) mask = ind[mask] return mask
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return a mask which is safe to use on x .
train
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def mail_admins(subject, message, fail_silently=False, connection=None, html_message=None): if (not settings.ADMINS): return mail = EmailMultiAlternatives(('%s%s' % (settings.EMAIL_SUBJECT_PREFIX, subject)), message, settings.SERVER_EMAIL, [a[1] for a in settings.ADMINS], connection=connection) if html_message: mail.attach_alternative(html_message, 'text/html') mail.send(fail_silently=fail_silently)
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sends a message to the admins .
train
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def _gen_random_array(n): randArray = [random.random() for i in range(n)] total = sum(randArray) normalizedRandArray = [(x / total) for x in randArray] return normalizedRandArray
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return an array of n random numbers .
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def _format_syslog_config(cmd_ret): ret_dict = {'success': (cmd_ret['retcode'] == 0)} if (cmd_ret['retcode'] != 0): ret_dict['message'] = cmd_ret['stdout'] else: for line in cmd_ret['stdout'].splitlines(): line = line.strip() cfgvars = line.split(': ') key = cfgvars[0].strip() value = cfgvars[1].strip() ret_dict[key] = value return ret_dict
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helper function to format the stdout from the get_syslog_config function .
train
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def group_snapshot_creating_from_src(): return IMPL.group_snapshot_creating_from_src()
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get a filter to check if a grp snapshot is being created from a grp .
train
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def reconnect(hass): hass.services.call(DOMAIN, SERVICE_RECONNECT, {})
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reconnects before running .
train
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def _sort_possible_cpu_topologies(possible, wanttopology): scores = collections.defaultdict(list) for topology in possible: score = _score_cpu_topology(topology, wanttopology) scores[score].append(topology) desired = [] desired.extend(scores[3]) desired.extend(scores[2]) desired.extend(scores[1]) desired.extend(scores[0]) return desired
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sort the topologies in order of preference .
train
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def _get_picks(raw): return [0, 1, 2, 6, 7, 8, 306, 340, 341, 342]
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get picks .
train
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def clean_symbols(text): result = text if isinstance(result, str): result = normalize(u'NFKD', result) result = re.sub(u'[ \\(\\)\\-_\\[\\]\\.]+', u' ', result).lower() result = re.sub(u'[^a-zA-Z0-9 ]', u'', result) return result
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replaces common symbols with spaces .
train
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def traverse_post_order(start_node, get_children, filter_func=None): class _Node(object, ): '\n Wrapper node class to keep an active children iterator.\n An active iterator is needed in order to determine when all\n children are visited and so the node itself should be visited.\n ' def __init__(self, node, get_children): self.node = node self.children = iter(get_children(node)) filter_func = (filter_func or (lambda __: True)) stack = deque([_Node(start_node, get_children)]) visited = set() while stack: current = stack[(-1)] if ((current.node in visited) or (not filter_func(current.node))): stack.pop() continue try: next_child = current.children.next() except StopIteration: (yield current.node) visited.add(current.node) stack.pop() else: stack.append(_Node(next_child, get_children))
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generator for yielding nodes of a tree in a post-order sort .
train
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def gather(reference, indices): return tf.gather(reference, indices)
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gathers variables from different gpus on a specified device .
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def test_inverse_deriv(): np.random.seed(24235) for link in Links: for k in range(10): z = (- np.log(np.random.uniform())) d = link.inverse_deriv(z) f = (1 / link.deriv(link.inverse(z))) assert_allclose(d, f, rtol=1e-08, atol=1e-10, err_msg=str(link))
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logic check that inverse_deriv equals 1/link .
train
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def register_unpack_format(name, extensions, function, extra_args=None, description=''): if (extra_args is None): extra_args = [] _check_unpack_options(extensions, function, extra_args) _UNPACK_FORMATS[name] = (extensions, function, extra_args, description)
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registers an unpack format .
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def _unlock_cache(w_lock): if (not os.path.exists(w_lock)): return try: if os.path.isdir(w_lock): os.rmdir(w_lock) elif os.path.isfile(w_lock): os.unlink(w_lock) except (OSError, IOError) as exc: log.trace('Error removing lockfile {0}: {1}'.format(w_lock, exc))
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unlock a fs file/dir based lock .
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@verbose def twitterclass_demo(): tw = Twitter() print('Track from the public stream\n') tw.tweets(keywords='love, hate', limit=10) print(SPACER) print('Search past Tweets\n') tw = Twitter() tw.tweets(keywords='love, hate', stream=False, limit=10) print(SPACER) print(('Follow two accounts in the public stream' + ' -- be prepared to wait a few minutes\n')) tw = Twitter() tw.tweets(follow=['759251', '6017542'], stream=True, limit=5)
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use the simplified :class:twitter class to write some tweets to a file .
train
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def Area(data=None, x=None, y=None, **kws): kws['x'] = x kws['y'] = y return create_and_build(AreaBuilder, data, **kws)
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create an area chart using :class:areabuilder <bokeh .
train
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def readline_generator(f): line = f.readline() while line: (yield line) line = f.readline()
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as advised in doc/library/configparser .
train
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def column_has_value(data, fieldname): has_value = False for row in data: value = row.get(fieldname) if value: if isinstance(value, basestring): if strip_html(value).strip(): has_value = True break else: has_value = True break return has_value
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check if at least one cell in column has non-zero and non-blank value .
train
false
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def test_save(config_stub, fake_save_manager, monkeypatch, qapp): monkeypatch.setattr(lineparser, 'LineParser', LineparserSaveStub) jar = cookies.CookieJar() jar._lineparser.data = [COOKIE1, COOKIE2, SESSION_COOKIE, EXPIRED_COOKIE] jar.parse_cookies() jar.save() saved_cookies = [cookie.data() for cookie in jar._lineparser.saved] assert (saved_cookies == [COOKIE1, COOKIE2])
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test %save .
train
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def _inherited_panel(panel, base_panels_from_pillar, ret): base_panels = [] for base_panel_from_pillar in base_panels_from_pillar: base_panel = __salt__['pillar.get'](base_panel_from_pillar) if base_panel: base_panels.append(base_panel) elif (base_panel_from_pillar != _DEFAULT_PANEL_PILLAR): ret.setdefault('warnings', []) warning_message = 'Cannot find panel pillar "{0}".'.format(base_panel_from_pillar) if (warning_message not in ret['warnings']): ret['warnings'].append(warning_message) base_panels.append(panel) result_panel = {} for panel in base_panels: result_panel.update(panel) return result_panel
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return a panel with properties from parents .
train
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def load_linker_sequences(linker_fname): global linkerlengths if (not os.path.getsize(linker_fname)): raise RuntimeError((("File empty? '" + linker_fname) + "'")) fh = open(linker_fname, 'r') linkerseqs = read_fasta(fh) if (len(linkerseqs) == 0): raise RuntimeError((linker_fname + ': no sequence found?')) for i in linkerseqs: if (i.name in linkerlengths): raise RuntimeError((((linker_fname + ": sequence '") + i.name) + "' present multiple times. Aborting.")) linkerlengths[i.name] = len(i.sequence) fh.close()
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loads all linker sequences into memory .
train
false
29,556
def stop_version_async(module=None, version=None): def _ResultHook(rpc): mapped_errors = [modules_service_pb.ModulesServiceError.INVALID_VERSION, modules_service_pb.ModulesServiceError.TRANSIENT_ERROR] expected_errors = {modules_service_pb.ModulesServiceError.UNEXPECTED_STATE: ('The specified module: %s, version: %s is already stopped.' % (module, version))} _CheckAsyncResult(rpc, mapped_errors, expected_errors) request = modules_service_pb.StopModuleRequest() if module: request.set_module(module) if version: request.set_version(version) response = modules_service_pb.StopModuleResponse() return _MakeAsyncCall('StopModule', request, response, _ResultHook)
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returns a userrpc to stop all instances for the given module version .
train
false
29,557
def contextualize_text(text, context): if (not text): return text for key in sorted(context, (lambda x, y: cmp(len(y), len(x)))): if (('$' + key) in text): try: s = str(context[key]) except UnicodeEncodeError: s = context[key].encode('utf8', errors='ignore') text = text.replace(('$' + key), s) return text
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takes a string with variables .
train
false
29,558
def LoadSingleCron(cron_info, open_fn=None): builder = yaml_object.ObjectBuilder(CronInfoExternal) handler = yaml_builder.BuilderHandler(builder) listener = yaml_listener.EventListener(handler) listener.Parse(cron_info) cron_info = handler.GetResults() if (len(cron_info) < 1): raise MalformedCronfigurationFile('Empty cron configuration.') if (len(cron_info) > 1): raise MalformedCronfigurationFile('Multiple cron sections in configuration.') return cron_info[0]
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load a cron .
train
false
29,559
def _platform(*args): platform = '-'.join((x.strip() for x in filter(len, args))) platform = platform.replace(' ', '_') platform = platform.replace('/', '-') platform = platform.replace('\\', '-') platform = platform.replace(':', '-') platform = platform.replace(';', '-') platform = platform.replace('"', '-') platform = platform.replace('(', '-') platform = platform.replace(')', '-') platform = platform.replace('unknown', '') while 1: cleaned = platform.replace('--', '-') if (cleaned == platform): break platform = cleaned while (platform[(-1)] == '-'): platform = platform[:(-1)] return platform
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helper to format the platform string in a filename compatible format e .
train
false
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def BoundedSemaphore(value=1): from multiprocessing.synchronize import BoundedSemaphore return BoundedSemaphore(value)
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a factory function that returns a new bounded semaphore .
train
false
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def _has_init(directory): mod_or_pack = join(directory, '__init__') for ext in (PY_SOURCE_EXTS + ('pyc', 'pyo')): if exists(((mod_or_pack + '.') + ext)): return ((mod_or_pack + '.') + ext) return None
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if the given directory has a valid __init__ file .
train
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def create_slices(start, stop, step=None, length=1): if (step is None): step = length slices = [slice(t, (t + length), 1) for t in range(start, ((stop - length) + 1), step)] return slices
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generate slices of time indexes .
train
false
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def inverse_fisher_z_transform(z): return (((e ** (2 * z)) - 1.0) / ((e ** (2 * z)) + 1.0))
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calculate the inverse of the fisher z transform on a z value .
train
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def AddErrors(counts1, counts2): return ErrorCounts((counts1.fn + counts2.fn), (counts1.fp + counts2.fp), (counts1.truth_count + counts2.truth_count), (counts1.test_count + counts2.test_count))
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adds the counts and returns a new sum tuple .
train
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def setup_formatters(): _registry.register_formats(_BUILTIN_FORMATS)
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register all built-in formatters .
train
false