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def compile_multiple(sources, options): sources = [os.path.abspath(source) for source in sources] processed = set() results = CompilationResultSet() timestamps = options.timestamps verbose = options.verbose context = None cwd = os.getcwd() for source in sources: if (source not in processed): if (context is None): context = options.create_context() output_filename = get_output_filename(source, cwd, options) out_of_date = context.c_file_out_of_date(source, output_filename) if ((not timestamps) or out_of_date): if verbose: sys.stderr.write(('Compiling %s\n' % source)) result = run_pipeline(source, options, context=context) results.add(source, result) context = None processed.add(source) return results
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compile_multiple compiles the given sequence of pyrex implementation files and returns a compilationresultset .
train
false
16,712
def permutation_matrix(orig_vec, per_vec): if (not isinstance(orig_vec, (list, tuple))): orig_vec = flatten(orig_vec) if (not isinstance(per_vec, (list, tuple))): per_vec = flatten(per_vec) if (set(orig_vec) != set(per_vec)): raise ValueError(('orig_vec and per_vec must be the same length, ' + 'and contain the same symbols.')) ind_list = [orig_vec.index(i) for i in per_vec] p_matrix = zeros(len(orig_vec)) for (i, j) in enumerate(ind_list): p_matrix[(i, j)] = 1 return p_matrix
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compute the permutation matrix to change order of orig_vec into order of per_vec .
train
false
16,713
def linear_fit_slope(ps): avex = ave([x for (x, y) in ps]) avey = ave([y for (x, y) in ps]) sxy = sum([((x - avex) * (y - avey)) for (x, y) in ps]) sxx = sum([((x - avex) ** 2) for (x, y) in ps]) if (sxx == 0): return None return (sxy / sxx)
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single-independent-variable linear regression -- least squares method .
train
false
16,715
def modify_hosts(host_filter_data, update_data): rpc_utils.check_modify_host(update_data) hosts = models.Host.query_objects(host_filter_data) for host in hosts: host.update_object(update_data)
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modify multiple hosts .
train
false
16,716
def environ(env_key): return os.environ.get(env_key, '')
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return the requested environment variable .
train
false
16,718
def read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None): con = _engine_builder(con) if (not _is_sqlalchemy_connectable(con)): raise NotImplementedError('read_sql_table only supported for SQLAlchemy connectable.') import sqlalchemy from sqlalchemy.schema import MetaData meta = MetaData(con, schema=schema) try: meta.reflect(only=[table_name], views=True) except sqlalchemy.exc.InvalidRequestError: raise ValueError(('Table %s not found' % table_name)) pandas_sql = SQLDatabase(con, meta=meta) table = pandas_sql.read_table(table_name, index_col=index_col, coerce_float=coerce_float, parse_dates=parse_dates, columns=columns, chunksize=chunksize) if (table is not None): return table else: raise ValueError(('Table %s not found' % table_name), con)
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read sql database table into a dataframe .
train
true
16,720
def sliding_window(n, seq): it = iter(seq) d = collections.deque(itertools.islice(it, n), n) if (len(d) != n): raise StopIteration() d_append = d.append for item in it: (yield tuple(d)) d_append(item) (yield tuple(d))
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a sequence of overlapping subsequences .
train
false
16,721
@contextmanager def _noop_context_manager(obj): (yield obj)
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context manager that has the same api as closing but does nothing .
train
false
16,723
def test_human_readable(): f = formatters.human_readable assert (f(1) == '1') assert (f(1.0) == '1') assert (f(10) == '10') assert (f(12.5) == '12.5') assert (f(1000) == '1k') assert (f(5000) == '5k') assert (f(100000) == '100k') assert (f(1253) == '1.253k') assert (f(1250) == '1.25k') assert (f(0.1) == '100m') assert (f(0.01) == '10m') assert (f(0.001) == '1m') assert (f(0.002) == '2m') assert (f(0.0025) == '2.5m') assert (f(0.0001) == u('100\xc2\xb5')) assert (f(0.000123) == u('123\xc2\xb5')) assert (f(1e-05) == u('10\xc2\xb5')) assert (f(1e-06) == u('1\xc2\xb5')) assert (f(1e-07) == u('100n')) assert (f(1e-10) == u('100p')) assert (f(0) == '0') assert (f(0.0) == '0') assert (f((-1337)) == '-1.337k') assert (f((-4.2e-08)) == '-42n')
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test human readable option .
train
false
16,724
def refget(objs, level=1): for _ in xrange(level): refs = gc.get_referrers(*objs) try: refs.remove(objs) except ValueError: pass objs = refs return refs
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get the referrers to the sequence of objects passed in .
train
false
16,725
def median_grouped(data, interval=1): data = sorted(data) n = len(data) if (n == 0): raise StatisticsError('no median for empty data') elif (n == 1): return data[0] x = data[(n // 2)] for obj in (x, interval): if isinstance(obj, (str, bytes)): raise TypeError(('expected number but got %r' % obj)) try: L = (x - (interval / 2)) except TypeError: L = (float(x) - (float(interval) / 2)) l1 = _find_lteq(data, x) l2 = _find_rteq(data, l1, x) cf = l1 f = ((l2 - l1) + 1) return (L + ((interval * ((n / 2) - cf)) / f))
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calculates the grouped mean of the num most recent values .
train
false
16,726
def _format_optdict(optdict, script=False, ignore=None): opts = [] for (opt, value) in optdict.iteritems(): if ((not ignore) or (opt not in ignore)): opts.append(('-%s' % opt)) if (value is not None): opts.append(_format_optvalue(value, script)) return _flatten(opts)
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formats optdict to a tuple to pass it to tk .
train
false
16,727
@register_canonicalize('local_setsubtensor_of_allocs') @register_stabilize('local_setsubtensor_of_allocs') @gof.local_optimizer([IncSubtensor]) def local_setsubtensor_of_constants(node): if (isinstance(node.op, IncSubtensor) and node.op.set_instead_of_inc): x = node.inputs[0] y = node.inputs[1] try: replace_x = get_scalar_constant_value(x, elemwise=False) except NotScalarConstantError: return try: replace_y = get_scalar_constant_value(y, elemwise=False) except NotScalarConstantError: return if (replace_x == replace_y): return [x] else: return False
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setsubtensor -> x when x is constant or alloc .
train
false
16,729
def estimate_optimal_with_K_and_M(num_kmers, mem_cap): n_tables = (math.log(2) * (mem_cap / float(num_kmers))) int_n_tables = int(n_tables) if (int_n_tables == 0): int_n_tables = 1 ht_size = int((mem_cap / int_n_tables)) mem_cap = (ht_size * int_n_tables) fp_rate = ((1 - math.exp(((- num_kmers) / float(ht_size)))) ** int_n_tables) res = namedtuple(u'result', [u'num_htables', u'htable_size', u'mem_use', u'fp_rate']) return res(int_n_tables, ht_size, mem_cap, fp_rate)
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estimate optimal countgraph args .
train
false
16,730
def test_bounds_check(): w = wcs.WCS(naxis=2) w.wcs.ctype = [u'RA---CAR', u'DEC--CAR'] w.wcs.cdelt = [10, 10] w.wcs.crval = [(-90), 90] w.wcs.crpix = [1, 1] w.wcs.bounds_check(False, False) (ra, dec) = w.wcs_pix2world(300, 0, 0) assert_allclose(ra, (-180)) assert_allclose(dec, (-30))
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test for #4957 .
train
false
16,731
def ssl_required(view_func): @wraps(view_func) def _checkssl(request, *args, **kwargs): if (settings.SESSION_COOKIE_SECURE and (not request.is_secure())): url_str = request.build_absolute_uri() url_str = url_str.replace('http://', 'https://') return http.HttpResponseRedirect(url_str) return view_func(request, *args, **kwargs) return _checkssl
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a view decorator that enforces https .
train
false
16,732
def _delete_orphans(course_usage_key, user_id, commit=False): store = modulestore() items = store.get_orphans(course_usage_key) branch = course_usage_key.branch if commit: with store.bulk_operations(course_usage_key): for itemloc in items: revision = ModuleStoreEnum.RevisionOption.all if (branch == ModuleStoreEnum.BranchName.published): revision = ModuleStoreEnum.RevisionOption.published_only store.delete_item(itemloc, user_id, revision=revision) return [unicode(item) for item in items]
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helper function to delete orphans for a given course .
train
false
16,733
def thin_path(cachedir): return os.path.join(cachedir, 'thin', 'thin.tgz')
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return the path to the thin tarball .
train
false
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def import_vul_ui(): date = request.utcnow post_vars = request.post_vars location_id = post_vars.location update_super = s3db.update_super ss_table = s3db.stats_source source_id = ss_table.insert(name='Vulnerability indicators submitted through UI') vdoc_table = s3db.vulnerability_document id = vdoc_table.insert(document_type='indicator', date=date, location_id=location_id, source_id=source_id) update_super(vdoc_table, dict(id=id)) itable = s3db.vulnerability_indicator rows = db((itable.deleted == False)).select(itable.posn, itable.parameter_id, orderby=itable.posn) vd_table = db.vulnerability_data for row in rows: id = vd_table.insert(parameter_id=row.parameter_id, location_id=location_id, value=post_vars[str(row.posn)], date=date, source_id=source_id) update_super(vd_table, dict(id=id))
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controller to add a new set of vulnerability indicators which have been input direct into the gui .
train
false
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def get_kdb_reader(signature): if (signature[0] != BASE_SIGNATURE): raise IOError('Unknown base signature.') if (signature[1] not in _kdb_readers): raise IOError('Unknown sub signature.') return _kdb_readers[signature[1]]
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retrieve the class used to process a keepass file by signature .
train
false
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def plugin_report(): plugin_report = [] all_plugins = CMSPlugin.objects.order_by(u'plugin_type') plugin_types = list(set(all_plugins.values_list(u'plugin_type', flat=True))) plugin_types.sort() for plugin_type in plugin_types: plugin = {} plugin[u'type'] = plugin_type try: plugins = CMSPlugin.objects.filter(plugin_type=plugin_type) plugin[u'instances'] = plugins plugin[u'model'] = plugin_pool.get_plugin(name=plugin_type).model unsaved_instances = [p for p in plugins if (not p.get_plugin_instance()[0])] plugin[u'unsaved_instances'] = unsaved_instances except KeyError: plugin[u'model'] = None plugin[u'instances'] = plugins plugin[u'unsaved_instances'] = [] plugin_report.append(plugin) return plugin_report
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returns a report of existing plugins structure of report: type: cmsplugin class .
train
false
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def make_sign_blob_call(rpc, bytes_to_sign): if (not isinstance(bytes_to_sign, str)): raise TypeError(('bytes_to_sign must be str: %s' % bytes_to_sign)) request = app_identity_service_pb.SignForAppRequest() request.set_bytes_to_sign(bytes_to_sign) response = app_identity_service_pb.SignForAppResponse() def signing_for_app_result(rpc): 'Check success, handle exceptions, and return converted RPC result.\n\n This method waits for the RPC if it has not yet finished, and calls the\n post-call hooks on the first invocation.\n\n Args:\n rpc: A UserRPC object.\n\n Returns:\n A tuple that contains signing key name and signature.\n ' assert (rpc.service == _APP_IDENTITY_SERVICE_NAME), repr(rpc.service) assert (rpc.method == _SIGN_FOR_APP_METHOD_NAME), repr(rpc.method) try: rpc.check_success() except apiproxy_errors.ApplicationError as err: raise _to_app_identity_error(err) return (response.key_name(), response.signature_bytes()) rpc.make_call(_SIGN_FOR_APP_METHOD_NAME, request, response, signing_for_app_result)
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executes the rpc call to sign a blob .
train
false
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def decimate_surface(points, triangles, n_triangles): reduction = (1 - (float(n_triangles) / len(triangles))) return _decimate_surface(points, triangles, reduction)
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decimate surface data .
train
false
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def p_file_input(p): if isinstance(p[(len(p) - 1)], basestring): if (len(p) == 3): p[0] = p[1] else: p[0] = [] elif (len(p) == 3): p[0] = (p[1] + p[2]) else: p[0] = p[1]
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file_input : file_input newline | file_input stmt | newline | stmt .
train
false
16,740
def get_pip_path(): try: from virtualenv import path_locations (home_dir, lib_dir, inc_dir, bin_dir) = path_locations(sys.prefix) return os.path.join(bin_dir, u'pip') except ImportError: pass return u'pip'
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try to figure out an explicit path to the pip executable script .
train
false
16,742
def get_data_filename(filename): return pkg_resources.resource_filename('certbot_nginx.tests', os.path.join('testdata', 'etc_nginx', filename))
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gets the filename of a test data file .
train
false
16,743
def adjusted_rand_score(labels_true, labels_pred): (labels_true, labels_pred) = check_clusterings(labels_true, labels_pred) n_samples = labels_true.shape[0] n_classes = np.unique(labels_true).shape[0] n_clusters = np.unique(labels_pred).shape[0] if ((n_classes == n_clusters == 1) or (n_classes == n_clusters == 0) or (n_classes == n_clusters == n_samples)): return 1.0 contingency = contingency_matrix(labels_true, labels_pred, sparse=True) sum_comb_c = sum((comb2(n_c) for n_c in np.ravel(contingency.sum(axis=1)))) sum_comb_k = sum((comb2(n_k) for n_k in np.ravel(contingency.sum(axis=0)))) sum_comb = sum((comb2(n_ij) for n_ij in contingency.data)) prod_comb = ((sum_comb_c * sum_comb_k) / comb(n_samples, 2)) mean_comb = ((sum_comb_k + sum_comb_c) / 2.0) return ((sum_comb - prod_comb) / (mean_comb - prod_comb))
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rand index adjusted for chance .
train
false
16,744
def _easy_install(argv, python_cmd, use_sudo): command = ('python -c " from pkg_resources import load_entry_point; ez = load_entry_point(\'setuptools\', \'console_scripts\', \'easy_install\'); ez(argv=%(argv)r) ' % locals()) if use_sudo: run_as_root(command) else: run(command)
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install packages using easy_install we dont know if the easy_install command in the path will be the right one .
train
true
16,745
@login_required def project_notifications(request, project_slug): project = get_object_or_404(Project.objects.for_admin_user(request.user), slug=project_slug) email_form = EmailHookForm(data=(request.POST or None), project=project) webhook_form = WebHookForm(data=(request.POST or None), project=project) if (request.method == 'POST'): if email_form.is_valid(): email_form.save() if webhook_form.is_valid(): webhook_form.save() project_dashboard = reverse('projects_notifications', args=[project.slug]) return HttpResponseRedirect(project_dashboard) emails = project.emailhook_notifications.all() urls = project.webhook_notifications.all() return render_to_response('projects/project_notifications.html', {'email_form': email_form, 'webhook_form': webhook_form, 'project': project, 'emails': emails, 'urls': urls}, context_instance=RequestContext(request))
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project notification view and form view .
train
false
16,747
def theme_url(): return get_bootstrap_setting(u'theme_url')
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return the full url to the theme css file .
train
false
16,748
def font_is_installed(font): return [fam for fam in QFontDatabase().families() if (to_text_string(fam) == font)]
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check if font is installed .
train
false
16,749
def customer(request): msg = u"The request object does not contain a customer. Edit your MIDDLEWARE_CLASSES setting to insert 'shop.middlerware.CustomerMiddleware'." assert hasattr(request, u'customer'), msg context = {u'customer': request.customer, u'site_header': app_settings.APP_LABEL.capitalize()} if request.user.is_staff: try: context.update(customer=CustomerModel.objects.get(pk=request.session[u'emulate_user_id'])) except (CustomerModel.DoesNotExist, KeyError, AttributeError): pass return context
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add the customer to the requestcontext .
train
false
16,750
def package_tree(pkgroot): path = os.path.dirname(__file__) subdirs = [os.path.relpath(i[0], path).replace(os.path.sep, '.') for i in os.walk(os.path.join(path, pkgroot)) if ('__init__.py' in i[2])] return sorted(subdirs)
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get the submodule list .
train
false
16,753
def tex_coord(x, y, n=4): m = (1.0 / n) dx = (x * m) dy = (y * m) return (dx, dy, (dx + m), dy, (dx + m), (dy + m), dx, (dy + m))
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return the bounding vertices of the texture square .
train
false
16,754
def modify_tags(gce, module, node, tags, state='present'): zone = node.extra['zone'].name existing_tags = node.extra['tags'] tags = [x.lower() for x in tags] tags_changed = [] if (state == 'absent'): tags_changed = _intersect_items(existing_tags, tags) if (not tags_changed): return (False, None) node_tags = _get_changed_items(existing_tags, tags) else: tags_changed = _get_changed_items(tags, existing_tags) if (not tags_changed): return (False, None) node_tags = _union_items(existing_tags, tags) try: gce.ex_set_node_tags(node, node_tags) return (True, tags_changed) except (GoogleBaseError, InvalidRequestError) as e: module.fail_json(msg=str(e), changed=False)
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modify tags on an instance .
train
false
16,755
def cpu(): max_primes = [500, 1000, 2500, 5000] test_command = 'sysbench --test=cpu --cpu-max-prime={0} run' result = None ret_val = {} for primes in max_primes: key = 'Prime numbers limit: {0}'.format(primes) run_command = test_command.format(primes) result = __salt__['cmd.run'](run_command) ret_val[key] = _parser(result) return ret_val
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tests for the cpu performance of minions .
train
true
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def reparam(string_, dictionary): dictionary = dictionary.copy() result = [] for (live, chunk) in _interpolate(string_): if live: v = eval(chunk, dictionary) result.append(sqlquote(v)) else: result.append(chunk) return SQLQuery.join(result, '')
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takes a string and a dictionary and interpolates the string using values from the dictionary .
train
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def generate_timeout_series(timeout): iteration = 0 while True: iteration += 1 (yield ((iteration * timeout) + iteration))
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generate a series of times that exceeds the given timeout .
train
false
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def get_liked(user_or_id, model): obj_type = apps.get_model('contenttypes', 'ContentType').objects.get_for_model(model) conditions = ('likes_like.content_type_id = %s', ('%s.id = likes_like.object_id' % model._meta.db_table), 'likes_like.user_id = %s') if isinstance(user_or_id, get_user_model()): user_id = user_or_id.id else: user_id = user_or_id return model.objects.extra(where=conditions, tables=('likes_like',), params=(obj_type.id, user_id))
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get the objects liked by an user .
train
false
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def getFilePaths(fileInDirectory=''): directoryName = os.getcwd() if (fileInDirectory != ''): directoryName = os.path.dirname(fileInDirectory) return getFilePathsByDirectory(directoryName)
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get the file paths in the directory of the file in directory .
train
false
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def rotate_juggle(lst, dist): n = len(lst) for i in xrange(gcd(dist, n)): t = lst[i] j = i while 1: k = ((j + dist) % n) if (k == i): break lst[j] = lst[k] j = k lst[j] = t
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an iterative juggle method .
train
false
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def format_date_time(request, value, format='shortdatetime'): if (not isinstance(value, datetime.datetime)): if isinstance(value, datetime.date): value = datetime.datetime.combine(value, datetime.datetime.min.time()) else: raise ValueError default_tz = timezone(settings.TIME_ZONE) tzvalue = default_tz.localize(value) user = request.user try: if (user.is_authenticated() and user.timezone): user_tz = timezone(user.timezone) tzvalue = user_tz.normalize(tzvalue.astimezone(user_tz)) except AttributeError: pass locale = _babel_locale(_get_request_locale(request)) try: formatted = format_date_value(value, tzvalue, locale, format) except KeyError: formatted = format_date_value(value, tzvalue, _babel_locale(settings.LANGUAGE_CODE), format) return (formatted, tzvalue)
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returns date/time formatted using babels locale settings .
train
false
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def strlist_minus(a, b): temp = cidict() for elt in b: temp[elt] = elt result = [elt for elt in a if (not temp.has_key(elt))] return result
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return list of all items in a which are not in b .
train
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def check_param_val(param): val = param.value if (val is None): raise ValueError('Problem has missing parameter value.') else: return val
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wrapper on accessing a parameter .
train
false
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def catch_integrity_errors(session): def decorated(func): 'Returns a decorated version of ``func``, as described in the\n wrapper defined within.\n\n ' @wraps(func) def wrapped(*args, **kw): 'Executes ``func(*args, **kw)`` but catches any exception\n that warrants a database rollback.\n\n ' try: return func(*args, **kw) except SQLAlchemyError as exception: session.rollback() status = (409 if is_conflict(exception) else 400) detail = str(exception) title = un_camel_case(exception.__class__.__name__) return error_response(status, cause=exception, detail=detail, title=title) return wrapped return decorated
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returns a decorator that catches database integrity errors .
train
false
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def _get_request_obj(csr): text = _text_or_file(csr) text = get_pem_entry(text, pem_type='CERTIFICATE REQUEST') return M2Crypto.X509.load_request_string(text)
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returns a csr object based on pem text .
train
true
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def _isnotsuite(test): try: iter(test) except TypeError: return True return False
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a crude way to tell apart testcases and suites with duck-typing .
train
false
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def _scipy_sparse_matrix_to_zero(e): if (not np): raise ImportError edense = e.todense() test = np.zeros_like(edense) if np.allclose(edense, test): return 0.0 else: return e
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convert a scipy .
train
false
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def set_autostart(vm_, state='on'): dom = _get_domain(vm_) if (state == 'on'): return (dom.setAutostart(1) == 0) elif (state == 'off'): return (dom.setAutostart(0) == 0) else: return False
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set the autostart flag on a vm so that the vm will start with the host system on reboot .
train
false
16,773
def egyptian_fraction(r, algorithm='Greedy'): if (r <= 0): raise ValueError('Value must be positive') (prefix, rem) = egypt_harmonic(r) if (rem == 0): return prefix (x, y) = rem.as_numer_denom() if (algorithm == 'Greedy'): return (prefix + egypt_greedy(x, y)) elif (algorithm == 'Graham Jewett'): return (prefix + egypt_graham_jewett(x, y)) elif (algorithm == 'Takenouchi'): return (prefix + egypt_takenouchi(x, y)) elif (algorithm == 'Golomb'): return (prefix + egypt_golomb(x, y)) else: raise ValueError('Entered invalid algorithm')
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return the list of denominators of an egyptian fraction expansion [1]_ of the said rational r .
train
false
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def make_and_verify_selection(server_root, temp_dir): (copied_files, copied_dirs) = copy_config(server_root, temp_dir) print(textwrap.fill('A secure copy of the files that have been selected for submission has been created under {0}. All comments have been removed and the files are only accessible by the current user. A list of the files that have been included is shown below. Please make sure that this selection does not contain private keys, passwords, or any other sensitive information.'.format(temp_dir))) print('\nFiles:') for copied_file in copied_files: print(copied_file) print('Directories (including all contained files):') for copied_dir in copied_dirs: print(copied_dir) sys.stdout.write('\nIs it safe to submit these files? ') while True: ans = raw_input('(Y)es/(N)o: ').lower() if ans.startswith('y'): return elif ans.startswith('n'): sys.exit('Your files were not submitted')
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copies server_root to temp_dir and verifies selection with the user .
train
false
16,776
def memoizemethod_noargs(method): cache = weakref.WeakKeyDictionary() @wraps(method) def new_method(self, *args, **kwargs): if (self not in cache): cache[self] = method(self, *args, **kwargs) return cache[self] return new_method
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decorator to cache the result of a method using a weak reference to its object .
train
false
16,777
def validate_rpc_host(ip): if ((not is_valid_ipv4(ip)) and (not is_valid_ipv6(ip))): raise ApplicationException(desc=('Invalid RPC ip address: %s' % ip)) return ip
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validates the given ip for use as rpc server address .
train
true
16,778
def normalize_languages(opf_languages, mi_languages): def parse(x): try: return parse_lang_code(x) except ValueError: return None opf_languages = filter(None, map(parse, opf_languages)) cc_map = {c.langcode: c.countrycode for c in opf_languages} mi_languages = filter(None, map(parse, mi_languages)) def norm(x): lc = x.langcode cc = (x.countrycode or cc_map.get(lc, None)) lc = (lang_as_iso639_1(lc) or lc) if cc: lc += (u'-' + cc) return lc return list(map(norm, mi_languages))
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preserve original country codes and use 2-letter lang codes where possible .
train
false
16,779
def GetIndexesAsync(**kwargs): extra_hook = kwargs.pop('extra_hook', None) config = _GetConfigFromKwargs(kwargs) def local_extra_hook(result): if extra_hook: return extra_hook(result) return result return _GetConnection().async_get_indexes(config, local_extra_hook)
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asynchronously retrieves the application indexes and their states .
train
false
16,780
def extract_events_from_keen(client, event_collection, start_date=None, end_date=None): timeframe = VERY_LONG_TIMEFRAME if (start_date and end_date): logger.info('Gathering events from the {} collection between {} and {}'.format(event_collection, start_date, end_date)) timeframe = {'start': start_date.isoformat(), 'end': end_date.isoformat()} else: logger.info('Gathering events from the {} collection using timeframe {}'.format(event_collection, VERY_LONG_TIMEFRAME)) return client.extraction(event_collection, timeframe=timeframe)
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get analytics from keen to use as a starting point for smoothing or transferring .
train
false
16,781
def not_(clause): return operators.inv(_literal_as_binds(clause))
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same as not a .
train
false
16,784
def security_group_rule_create(context, values): return IMPL.security_group_rule_create(context, values)
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create a new security group .
train
false
16,785
def generate_java_binary(target, source, env): target_name = str(target[0]) onejar_path = str(source[0]) return _generate_java_binary(target_name, onejar_path, '', '')
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build function to generate wrapper shell script for java binary .
train
false
16,786
@pytest.mark.parametrize((u'model_class', u'mode'), list(itertools.product(test_models_1D, modes))) def test_pixel_sum_1D(model_class, mode): if ((model_class == Box1D) and (mode == u'center')): pytest.skip(u'Non integrating mode. Skip integral test.') parameters = models_1D[model_class] model = create_model(model_class, parameters) values = discretize_model(model, models_1D[model_class][u'x_lim'], mode=mode) assert_allclose(values.sum(), models_1D[model_class][u'integral'], atol=0.0001)
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test if the sum of all pixels corresponds nearly to the integral .
train
false
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def get_repository_by_name_and_owner(app, name, owner): repository_query = get_repository_query(app) if is_tool_shed_client(app): return repository_query.filter(and_((app.install_model.ToolShedRepository.table.c.name == name), (app.install_model.ToolShedRepository.table.c.owner == owner))).first() user = common_util.get_user_by_username(app, owner) if user: return repository_query.filter(and_((app.model.Repository.table.c.name == name), (app.model.Repository.table.c.user_id == user.id))).first() return None
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get a repository from the database via name and owner .
train
false
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def get_aware_datetime(dt_string, tz=None): if (not dt_string): return None try: return make_aware(parse_datetime(dt_string), tz=tz) except ValueError: raise ArgumentTypeError(('The provided datetime/date string is not valid: "%s"' % dt_string))
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return an aware datetime parsed from a datetime or date string .
train
false
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def handle_missing_index_file(app, tool_path, sample_files, repository_tools_tups, sample_files_copied): for (index, repository_tools_tup) in enumerate(repository_tools_tups): (tup_path, guid, repository_tool) = repository_tools_tup params_with_missing_index_file = repository_tool.params_with_missing_index_file for param in params_with_missing_index_file: options = param.options missing_file_name = basic_util.strip_path(options.missing_index_file) if (missing_file_name not in sample_files_copied): for sample_file in sample_files: sample_file_name = basic_util.strip_path(sample_file) if (sample_file_name == ('%s.sample' % missing_file_name)): copy_sample_file(app, sample_file) if (options.tool_data_table and options.tool_data_table.missing_index_file): options.tool_data_table.handle_found_index_file(options.missing_index_file) sample_files_copied.append(options.missing_index_file) break repository_tool = app.toolbox.load_tool(os.path.join(tool_path, tup_path), guid=guid, use_cached=False) repository_tools_tups[index] = (tup_path, guid, repository_tool) return (repository_tools_tups, sample_files_copied)
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inspect each tool to see if it has any input parameters that are dynamically generated select lists that depend on a .
train
false
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def get_response_object(url, method='GET', headers=None): parsed_url = urlparse.urlparse(url) parsed_qs = parse_qs(parsed_url.query) secure = (parsed_url.scheme == 'https') headers = (headers or {}) method = method.upper() con = Connection(secure=secure, host=parsed_url.netloc) response = con.request(action=parsed_url.path, params=parsed_qs, headers=headers, method=method) return response
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utility function which uses libclouds connection class to issue an http request .
train
false
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def _get_encrypted_user_slug(): cname = False data = [(c.user._id36 if c.user_is_loggedin else ''), get_srpath(), (c.lang or ''), cname] return encrypt('|'.join((_force_utf8(s) for s in data)))
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return an encrypted string containing context info .
train
false
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@pytest.mark.usefixtures(u'clean_system') @pytest.mark.parametrize(u'input_params, expected_context', context_data()) def test_generate_context(input_params, expected_context): assert (generate.generate_context(**input_params) == expected_context)
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test the generated context for several input parameters against the according expected context .
train
false
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def endpointForTesting(fireImmediately=False): @implementer(IStreamClientEndpoint) class ClientTestEndpoint(object, ): def connect(self, factory): result = Deferred() info.passedFactories.append(factory) @result.addCallback def createProtocol(ignored): protocol = factory.buildProtocol(None) info.constructedProtocols.append(protocol) transport = StringTransport() protocol.makeConnection(transport) return protocol info.connectQueue.append(result) if fireImmediately: result.callback(None) return result info = ConnectInformation() return (info, ClientTestEndpoint())
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make a sample endpoint for testing .
train
false
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def momentcondunbound(distfn, params, mom2, quantile=None): (shape, loc, scale) = params mom2diff = (np.array(distfn.stats(shape, loc, scale)) - mom2) if (not (quantile is None)): (pq, xq) = quantile cdfdiff = (distfn.cdf(xq, shape, loc, scale) - pq) return np.concatenate([mom2diff, cdfdiff[:1]]) return mom2diff
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moment conditions for estimating distribution parameters using method of moments .
train
false
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def isInIOThread(): return (ioThread == getThreadID())
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are we in the thread responsable for i/o requests ? .
train
false
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def allowed_gai_family(): family = socket.AF_INET if HAS_IPV6: family = socket.AF_UNSPEC return family
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this function is designed to work in the context of getaddrinfo .
train
false
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def get_default_price_list(party): if party.default_price_list: return party.default_price_list if (party.doctype == u'Customer'): price_list = frappe.db.get_value(u'Customer Group', party.customer_group, u'default_price_list') if price_list: return price_list return None
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return default price list for party .
train
false
16,801
def serialize_user(user, node=None, admin=False, full=False, is_profile=False): fullname = user.display_full_name(node=node) ret = {'id': str(user._primary_key), 'registered': user.is_registered, 'surname': user.family_name, 'fullname': fullname, 'shortname': (fullname if (len(fullname) < 50) else ((fullname[:23] + '...') + fullname[(-23):])), 'gravatar_url': gravatar(user, use_ssl=True, size=settings.PROFILE_IMAGE_MEDIUM), 'active': user.is_active} if (node is not None): if admin: flags = {'visible': False, 'permission': 'read'} else: flags = {'visible': node.contributor_set.filter(user=user, visible=True).exists(), 'permission': reduce_permissions(node.get_permissions(user))} ret.update(flags) if user.is_registered: ret.update({'url': user.url, 'absolute_url': user.absolute_url, 'display_absolute_url': user.display_absolute_url, 'date_registered': user.date_registered.strftime('%Y-%m-%d')}) if full: if is_profile: ret['emails'] = ([{'address': each, 'primary': (each.strip().lower() == user.username.strip().lower()), 'confirmed': True} for each in user.emails] + [{'address': each, 'primary': (each.strip().lower() == user.username.strip().lower()), 'confirmed': False} for each in user.unconfirmed_emails]) if user.is_merged: merger = user.merged_by merged_by = {'id': str(merger._primary_key), 'url': merger.url, 'absolute_url': merger.absolute_url} else: merged_by = None ret.update({'number_projects': get_projects(user).count(), 'number_public_projects': get_public_projects(user).count(), 'activity_points': user.get_activity_points(), 'gravatar_url': gravatar(user, use_ssl=True, size=settings.PROFILE_IMAGE_LARGE), 'is_merged': user.is_merged, 'merged_by': merged_by}) return ret
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returns a milestones-friendly representation of a user object .
train
false
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def trim_trailing_lines(lines): lines = list(lines) while (lines and (not lines[(-1)])): lines.pop((-1)) return lines
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trim trailing blank lines .
train
false
16,804
def lint_general(tool_source, lint_ctx): version = tool_source.parse_version() if (not version): lint_ctx.error(ERROR_VERSION_MSG) else: lint_ctx.valid((VALID_VERSION_MSG % version)) name = tool_source.parse_name() if (not name): lint_ctx.error(ERROR_NAME_MSG) else: lint_ctx.valid((VALID_NAME_MSG % name)) tool_id = tool_source.parse_id() if (not tool_id): lint_ctx.error(ERROR_ID_MSG) else: lint_ctx.valid((VALID_ID_MSG % tool_id)) if re.search('\\s', tool_id): lint_ctx.warn('Tool id contains a space - this is discouraged.')
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check tool version .
train
false
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def strip_entities(value): return re.sub('&(?:\\w+|#\\d);', '', value)
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returns the given html with all entities stripped .
train
false
16,806
def collect_registered_bears_dirs(entrypoint): collected_dirs = [] for ep in pkg_resources.iter_entry_points(entrypoint): registered_package = None try: registered_package = ep.load() except pkg_resources.DistributionNotFound: continue collected_dirs.append(os.path.abspath(os.path.dirname(registered_package.__file__))) return collected_dirs
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searches setuptools for the entrypoint and returns the bear directories given by the module .
train
false
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def read_uint32(fid): return _unpack_simple(fid, '>u4', np.uint32)
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read unsigned 32bit integer from bti file .
train
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def create_target_index(lang): create_index() return STORAGE.create_index(TargetSchema(), ('target-%s' % lang))
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creates traget string index for given language .
train
false
16,810
def get_ndata(ofile): data = [next(ofile)] loc = 1 if (data[0].strip()[0] == '{'): raise ValueError('This looks like a sparse ARFF: not supported yet') for i in ofile: loc += 1 return loc
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read the whole file to get number of data attributes .
train
false
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def _validate_customization_args_and_values(item_name, item_type, customization_args, ca_specs_to_validate_against): ca_spec_names = [ca_spec.name for ca_spec in ca_specs_to_validate_against] if (not isinstance(customization_args, dict)): raise utils.ValidationError(('Expected customization args to be a dict, received %s' % customization_args)) customization_args = _get_full_customization_args(customization_args, ca_specs_to_validate_against) extra_args = [] for arg_name in customization_args.keys(): if (not isinstance(arg_name, basestring)): raise utils.ValidationError(('Invalid customization arg name: %s' % arg_name)) if (arg_name not in ca_spec_names): extra_args.append(arg_name) logging.warning(('%s %s does not support customization arg %s.' % (item_name.capitalize(), item_type, arg_name))) for extra_arg in extra_args: del customization_args[extra_arg] for ca_spec in ca_specs_to_validate_against: try: customization_args[ca_spec.name]['value'] = schema_utils.normalize_against_schema(customization_args[ca_spec.name]['value'], ca_spec.schema) except Exception: pass
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validates the given customization_args dict against the specs set out in ca_specs_to_validate_against .
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def exec_prompt_glib(bus, prompt): from gi.repository import GLib loop = GLib.MainLoop() result = [] def callback(dismissed, unlocked): result.append(dismissed) result.append(unlocked) loop.quit() exec_prompt(bus, prompt, callback) loop.run() return (result[0], result[1])
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like :func:exec_prompt .
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def markdown_column_params(): (yield (tables.Move, None, 'effect')) (yield (tables.Move, None, 'short_effect')) for cls in tables.mapped_classes: for translation_cls in cls.translation_classes: for column in translation_cls.__table__.c: if (column.info.get('string_getter') == markdown.MarkdownString): (yield (cls, translation_cls, column.name))
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check all markdown values scans the database schema for markdown columns .
train
false
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@docstring.dedent_interpd def complex_spectrum(x, Fs=None, window=None, pad_to=None, sides=None): return _single_spectrum_helper(x=x, Fs=Fs, window=window, pad_to=pad_to, sides=sides, mode=u'complex')
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compute the complex-valued frequency spectrum of *x* .
train
false
16,816
@pytest.mark.skipif((not PY3), reason='Only necessary on Python3') def test_not_ascii(): try: preferred_encoding = locale.getpreferredencoding() fs_enc = codecs.lookup(preferred_encoding).name except Exception: fs_enc = 'ascii' assert (fs_enc != 'ascii')
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make sure that the systems preferred encoding is not ascii .
train
false
16,817
@pytest.mark.parametrize('url_text', ['http://abc123.com/this/awesome/url.html', 'https://supersecret.gov/nsa/files.txt', None]) def test_set_hover_url(url_widget, url_text): url_widget.set_hover_url(url_text) if (url_text is not None): assert (url_widget.text() == url_text) assert (url_widget._urltype == url.UrlType.hover) else: assert (url_widget.text() == '') assert (url_widget._urltype == url.UrlType.normal)
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test text when hovering over a link .
train
false
16,818
def assert_has_line(output, line): match = re.search(('^%s$' % re.escape(line)), output, flags=re.MULTILINE) assert (match is not None), ("No line of output file was '%s' (output was '%s') " % (line, output))
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asserts the specified output contains the line specified the argument line .
train
false
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def test_patched_no_errwindow(capfd, monkeypatch): monkeypatch.setattr('qutebrowser.misc.checkpyver.sys.argv', [sys.argv[0], '--no-err-windows']) monkeypatch.setattr('qutebrowser.misc.checkpyver.sys.hexversion', 50331648) monkeypatch.setattr('qutebrowser.misc.checkpyver.sys.exit', (lambda status: None)) checkpyver.check_python_version() (stdout, stderr) = capfd.readouterr() assert (not stdout) assert re.match(TEXT, stderr), stderr
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test with a patched sys .
train
false
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def sample(prediction): p = np.zeros(shape=[1, vocabulary_size], dtype=np.float) p[(0, sample_distribution(prediction[0]))] = 1.0 return p
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sample an index from a probability array .
train
false
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def delete_all_thumbnails(path, recursive=True): total = 0 for thumbs in all_thumbnails(path, recursive=recursive).values(): total += _delete_using_thumbs_list(thumbs) return total
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delete all files within a path which match the thumbnails pattern .
train
true
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def _ofport_retry(fn): @six.wraps(fn) def wrapped(*args, **kwargs): self = args[0] new_fn = tenacity.retry(reraise=True, retry=tenacity.retry_if_result(_ofport_result_pending), wait=tenacity.wait_exponential(multiplier=0.01, max=1), stop=tenacity.stop_after_delay(self.vsctl_timeout))(fn) return new_fn(*args, **kwargs) return wrapped
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decorator for retrying when ovs has yet to assign an ofport .
train
false
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def init(mpstate): return SerialModule(mpstate)
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initialize all standard dirs .
train
false
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def handdrawn(): table = s3db.vulnerability_document s3.filter = ((s3db.doc_image.doc_id == table.doc_id) & (table.document_type == 'map')) return s3_rest_controller('doc', 'image')
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rest controller for hand-drawn maps .
train
false
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def mult_matrix((a1, b1, c1, d1, e1, f1), (a0, b0, c0, d0, e0, f0)): return (((a0 * a1) + (c0 * b1)), ((b0 * a1) + (d0 * b1)), ((a0 * c1) + (c0 * d1)), ((b0 * c1) + (d0 * d1)), (((a0 * e1) + (c0 * f1)) + e0), (((b0 * e1) + (d0 * f1)) + f0))
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returns the multiplication of two matrices .
train
true
16,827
def test_optimization_minimizes_kl_divergence(): random_state = check_random_state(0) (X, _) = make_blobs(n_features=3, random_state=random_state) kl_divergences = [] for n_iter in [200, 250, 300]: tsne = TSNE(n_components=2, perplexity=10, learning_rate=100.0, n_iter=n_iter, random_state=0) tsne.fit_transform(X) kl_divergences.append(tsne.kl_divergence_) assert_less_equal(kl_divergences[1], kl_divergences[0]) assert_less_equal(kl_divergences[2], kl_divergences[1])
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t-sne should give a lower kl divergence with more iterations .
train
false
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def check_conv_gradinputs_shape(image_shape, kernel_shape, output_shape, border_mode, subsample, filter_dilation=None): image_shape = tuple(image_shape) kernel_shape = tuple(kernel_shape) output_shape = tuple(output_shape) if ((len(image_shape) != len(kernel_shape)) or (len(image_shape) != len(output_shape))): return False if ((len(image_shape) - 2) != len(subsample)): return False if ((filter_dilation is not None) and ((len(image_shape) - 2) != len(filter_dilation))): return False computed_output_shape = get_conv_output_shape(image_shape, kernel_shape, border_mode, subsample, filter_dilation) def check_dim(given, computed): if ((given is None) or (computed is None)): return True try: given = get_scalar_constant_value(given) computed = get_scalar_constant_value(computed) return (int(given) == int(computed)) except NotScalarConstantError: return True return all((check_dim(given, computed) for (given, computed) in zip(output_shape, computed_output_shape)))
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this function checks if the given image shapes are consistent .
train
false
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def _filter_sample_ids_from_category_state_coverage(metadata_map, sample_ids, coverage_category, subject_category, consider_state_fn, min_num_states=None, required_states=None): subjects = defaultdict(list) for samp_id in sample_ids: subject = metadata_map.getCategoryValue(samp_id, subject_category) subjects[subject].append(samp_id) samp_ids_to_keep = [] num_subjects_kept = 0 states_kept = [] for (subject, samp_ids) in subjects.items(): subject_covered_states = set(metadata_map.getCategoryValues(samp_ids, coverage_category)) keep_subject = True if (min_num_states is not None): if (sum([consider_state_fn(s) for s in subject_covered_states]) < min_num_states): keep_subject = False if (keep_subject and (required_states is not None)): if (len((subject_covered_states & required_states)) != len(required_states)): keep_subject = False if keep_subject: samp_ids_to_keep.extend(samp_ids) states_kept.extend(subject_covered_states) num_subjects_kept += 1 return (set(samp_ids_to_keep), num_subjects_kept, set(states_kept))
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helper function to perform filtering based on category state coverage .
train
false
16,830
def test_feature_max_length_on_scenario_outline(): feature = Feature.from_string(FEATURE6) assert_equals(feature.max_length, 79)
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the max length of a feature considering when the table of some of the scenario oulines is longer than the remaining things .
train
false
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def percentError(out, true): arrout = array(out).flatten() wrong = where((arrout != array(true).flatten()))[0].size return ((100.0 * float(wrong)) / float(arrout.size))
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return percentage of mismatch between out and target values .
train
false
16,833
def get_service_protocols(service): cmd = '--permanent --service={0} --get-protocols'.format(service) return __firewall_cmd(cmd).split()
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list protocols of a service .
train
false
16,835
def tunnel_request_data(host, port, proxy_auth_header=None): host_value = ((to_bytes(host, encoding='ascii') + ':') + to_bytes(str(port))) tunnel_req = (('CONNECT ' + host_value) + ' HTTP/1.1\r\n') tunnel_req += (('Host: ' + host_value) + '\r\n') if proxy_auth_header: tunnel_req += (('Proxy-Authorization: ' + proxy_auth_header) + '\r\n') tunnel_req += '\r\n' return tunnel_req
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return binary content of a connect request .
train
false