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def isRat(x): return isinstance(x, Rat)
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test wheter an object is an instance of the rat class .
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false
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@register.function @jinja2.contextfunction def hub_breadcrumbs(context, addon=None, items=None, add_default=False): crumbs = [(reverse('ecosystem.landing'), _('Developers'))] title = _('My Submissions') link = reverse('mkt.developers.apps') if addon: if ((not addon) and (not items)): crumbs.append((None, title)) else: crumbs.append((link, title)) if items: url = addon.get_dev_url() else: url = None crumbs.append((url, addon.name)) if items: crumbs.extend(items) if (len(crumbs) == 1): crumbs = [] return mkt_breadcrumbs(context, items=crumbs)
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wrapper function for breadcrumbs .
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def readWriteDeleteHypertextHelp(documentDirectoryPath, hypertextFileIndex, hypertextFiles, transferredFileNames): fileName = os.path.basename(hypertextFiles[hypertextFileIndex]) print ('readWriteDeleteHypertextHelp ' + fileName) filePath = os.path.join(documentDirectoryPath, fileName) fileText = archive.getFileText(fileName) fileText = getWrappedHypertext(fileText, hypertextFileIndex, hypertextFiles) if (fileText.find('This page is in the table of contents.') > (-1)): fileText = fileText.replace('This page is in the table of contents.', '') transferredFileNames.append(fileName) archive.writeFileText(filePath, fileText) os.remove(fileName)
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read the pydoc hypertext help documents .
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false
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def _a_encode_none(value, mapping): return ['0n']
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none --> [0 .
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def get_cxxflags(): return get_var('CXXFLAGS')
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get the value of cxxflags variable in the make .
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def getPointsFromLoop(loop, radius, thresholdRatio=0.9): radius = abs(radius) points = [] for pointIndex in xrange(len(loop)): pointBegin = loop[pointIndex] pointEnd = loop[((pointIndex + 1) % len(loop))] points.append(pointBegin) addPointsFromSegment(pointBegin, pointEnd, points, radius, thresholdRatio) return points
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get the points from every point on a loop and between points .
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def extract_variables(log_format): if (log_format == 'combined'): log_format = LOG_FORMAT_COMBINED for match in re.findall(REGEX_LOG_FORMAT_VARIABLE, log_format): (yield match)
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extract all variables from a log format string .
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def handleEventException(source, event, args, kw, exc_info): try: c = source t = event if hasattr(c, '__class__'): c = c.__class__.__name__ if isinstance(t, Event): t = t.__class__.__name__ elif issubclass(t, Event): t = t.__name__ except: pass import sys sys.stderr.write(('Exception while handling %s!%s...\n' % (c, t))) import traceback traceback.print_exception(*exc_info)
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called when an exception is raised by an event handler when the event was raised by raiseeventnoerrors() .
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def _do_mb_query(entity, id, includes=[], params={}): if (not isinstance(includes, list)): includes = [includes] _check_includes(entity, includes) auth_required = _get_auth_type(entity, id, includes) args = dict(params) if (len(includes) > 0): inc = ' '.join(includes) args['inc'] = inc path = ('%s/%s' % (entity, id)) return _mb_request(path, 'GET', auth_required, args=args)
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make a single get call to the musicbrainz xml api .
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false
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def new_create_tag(name=u'', ref=u'', sign=False, settings=None, parent=None): opts = TagOptions(name, ref, sign) view = CreateTag(opts, settings=settings, parent=parent) return view
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entry point for external callers .
train
false
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def prints(*args, **kwargs): file = kwargs.get('file', sys.stdout) sep = kwargs.get('sep', ' ') end = kwargs.get('end', '\n') enc = preferred_encoding safe_encode = kwargs.get('safe_encode', False) if ('CALIBRE_WORKER' in os.environ): enc = 'utf-8' for (i, arg) in enumerate(args): if isinstance(arg, unicode): try: arg = arg.encode(enc) except UnicodeEncodeError: try: arg = arg.encode('utf-8') except: if (not safe_encode): raise arg = repr(arg) if (not isinstance(arg, str)): try: arg = str(arg) except ValueError: arg = unicode(arg) if isinstance(arg, unicode): try: arg = arg.encode(enc) except UnicodeEncodeError: try: arg = arg.encode('utf-8') except: if (not safe_encode): raise arg = repr(arg) try: file.write(arg) except: import repr as reprlib file.write(reprlib.repr(arg)) if (i != (len(args) - 1)): file.write(bytes(sep)) file.write(bytes(end))
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print unicode arguments safely by encoding them to preferred_encoding has the same signature as the print function from python 3 .
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false
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def print_title(text): print_col('==================== {} ===================='.format(text), 'yellow')
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print a title .
train
false
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def channel_data_files(dest=None): channel_data_filename = 'channel_data.json' if dest: if (not channel_data_path): sourcedir = os.path.dirname(path) sourcefile = ((os.path.basename(path) + '.json') if os.path.exists((os.path.basename(path) + '.json')) else channel_data_filename) else: sourcedir = channel_data_path sourcefile = channel_data_filename shutil.copy(os.path.join(sourcedir, sourcefile), os.path.join(dest, channel_data_filename)) shutil.rmtree(os.path.join(dest, 'images'), ignore_errors=True) shutil.copytree(os.path.join(sourcedir, 'images'), os.path.join(dest, 'images'))
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copies all remaining files to appropriate channel data directory .
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def session_view(request): request.session['tobacconist'] = 'hovercraft' t = Template('This is a view that modifies the session.', name='Session Modifying View Template') c = Context() return HttpResponse(t.render(c))
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a view that modifies the session .
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def get_job_output(job_id): return job_models.JobModel.get_by_id(job_id).output
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returns the output of a job .
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def nearlyEqual(lst1, lst2, tolerance=0.001): return all(((abs((i - j)) <= tolerance) for (i, j) in zip(lst1, lst2)))
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tell whether the itemwise differences of the two lists is never bigger than tolerance .
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def get_latest_versions(versions, num=1): versions = group_versions(versions) return [versions[index][0] for index in range(num)]
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return a list of the most recent versions for each major .
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def are_content_experiments_enabled(course): return (('split_test' in ADVANCED_COMPONENT_TYPES) and ('split_test' in course.advanced_modules))
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returns true if content experiments have been enabled for the course .
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def beta_from_features(dataset, **kwargs): return beta_from_design(dataset.X, **kwargs)
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returns the marginal precision of the features in a dataset .
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def basic_clean_up_f(f): deletion_list = [l.strip() for l in f] remove_all(deletion_list) return True
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removes list of files in f f: file containing list of filepaths example f: f1 .
train
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def generate_open_shard_key(): open_shards = get_open_shards() shard_id = random.choice(open_shards) key = (shard_id << 48) return key
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return the key that can be passed into session_scope() for an open shard .
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def GetCurrentTimestamp(): return (_TEST_TIME if (_TEST_TIME is not None) else time.time())
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if _test_time has been set .
train
false
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@command('fileset', optional=['filename']) def fileset_command(options, input_filename=None): with open_input_file(input_filename) as input_file: descriptor_content = input_file.read() dest_dir = os.path.expanduser(options.dest_dir) if ((not os.path.isdir(dest_dir)) and os.path.exists(dest_dir)): fatal_error(("Destination '%s' is not a directory" % dest_dir)) file_set = protobuf.decode_message(descriptor.FileSet, descriptor_content) for file_descriptor in file_set.files: generate_file_descriptor(dest_dir, file_descriptor=file_descriptor, force_overwrite=options.force)
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generate source directory structure from fileset .
train
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def random_urlsafe_str(): return base64.urlsafe_b64encode(uuid.uuid4().bytes)[:(-2)].decode('utf-8')
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generate a random url-safe string .
train
false
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def test_Trapezoid1D(): model = models.Trapezoid1D(amplitude=4.2, x_0=2.0, width=1.0, slope=3) xx = np.linspace(0, 4, 8) yy = model(xx) yy_ref = [0.0, 1.41428571, 3.12857143, 4.2, 4.2, 3.12857143, 1.41428571, 0.0] assert_allclose(yy, yy_ref, rtol=0, atol=1e-06)
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regression test for URL .
train
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def handle_shared_float32(tf): if tf: theano.compile.shared_constructor(float32_shared_constructor) else: theano.compile.shared_constructor(float32_shared_constructor, True) assert (float32_shared_constructor not in theano.compile.shared.constructors)
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set the default shared type for float32 tensor to cudandarraytype .
train
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def _acquire_subtask_lock(task_id): key = 'subtask-{}'.format(task_id) succeeded = cache.add(key, 'true', SUBTASK_LOCK_EXPIRE) if (not succeeded): TASK_LOG.warning("task_id '%s': already locked. Contains value '%s'", task_id, cache.get(key)) return succeeded
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mark the specified task_id as being in progress .
train
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def http_log_req(method, uri, args, kwargs): if (not pyrax.get_http_debug()): return string_parts = [('curl -i -X %s' % method)] for element in args: string_parts.append(('%s' % element)) for element in kwargs['headers']: header = ("-H '%s: %s'" % (element, kwargs['headers'][element])) string_parts.append(header) string_parts.append(uri) log = logging.getLogger('pyrax') log.debug(('\nREQ: %s\n' % ' '.join(string_parts))) if ('body' in kwargs): pyrax._logger.debug(('REQ BODY: %s\n' % kwargs['body'])) if ('data' in kwargs): pyrax._logger.debug(('REQ DATA: %s\n' % kwargs['data']))
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when pyrax .
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def dmp_zz_wang_test_points(f, T, ct, A, u, K): if (not dmp_eval_tail(dmp_LC(f, K), A, (u - 1), K)): raise EvaluationFailed('no luck') g = dmp_eval_tail(f, A, u, K) if (not dup_sqf_p(g, K)): raise EvaluationFailed('no luck') (c, h) = dup_primitive(g, K) if K.is_negative(dup_LC(h, K)): (c, h) = ((- c), dup_neg(h, K)) v = (u - 1) E = [dmp_eval_tail(t, A, v, K) for (t, _) in T] D = dmp_zz_wang_non_divisors(E, c, ct, K) if (D is not None): return (c, h, E) else: raise EvaluationFailed('no luck')
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wang/eez: test evaluation points for suitability .
train
false
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def filter_formatdate(val, format): encoding = locale.getpreferredencoding() if (not isinstance(val, (datetime, date, time))): return val return native_str_to_text(val.strftime(text_to_native_str(format, encoding=encoding)), encoding=encoding)
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returns a string representation of a datetime object according to format string .
train
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def get_monitor_doc(var): doc = None if (var.__doc__ is not var.__class__.__doc__): doc = var.__doc__ return doc
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returns the __doc__ field of var or none .
train
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@public def xring(symbols, domain, order=lex): _ring = PolyRing(symbols, domain, order) return (_ring, _ring.gens)
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construct a polynomial ring returning (ring .
train
false
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def _get_branch_opts(branch, local_branch, all_local_branches, desired_upstream, git_ver=None): if ((branch is not None) and (branch not in all_local_branches)): return None if (git_ver is None): git_ver = _LooseVersion(__salt__['git.version'](versioninfo=False)) ret = [] if (git_ver >= _LooseVersion('1.8.0')): ret.extend(['--set-upstream-to', desired_upstream]) else: ret.append('--set-upstream') ret.append((local_branch if (branch is None) else branch)) ret.append(desired_upstream) return ret
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dry helper to build list of opts for git .
train
true
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@pytest.fixture(scope=u'session') def celery_session_worker(request, celery_session_app, celery_includes, celery_worker_pool, celery_worker_parameters): if (not NO_WORKER): for module in celery_includes: celery_session_app.loader.import_task_module(module) with worker.start_worker(celery_session_app, pool=celery_worker_pool, **celery_worker_parameters) as w: (yield w)
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session fixture: start worker that lives throughout test suite .
train
false
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@register.inclusion_tag(u'includes/editable_loader.html', takes_context=True) def editable_loader(context): user = context[u'request'].user template_vars = {u'has_site_permission': has_site_permission(user), u'request': context[u'request']} if (settings.INLINE_EDITING_ENABLED and template_vars[u'has_site_permission']): t = get_template(u'includes/editable_toolbar.html') template_vars[u'REDIRECT_FIELD_NAME'] = REDIRECT_FIELD_NAME template_vars[u'editable_obj'] = context.get(u'editable_obj', context.get(u'page', None)) template_vars[u'accounts_logout_url'] = context.get(u'accounts_logout_url', None) template_vars[u'toolbar'] = t.render(Context(template_vars)) template_vars[u'richtext_media'] = RichTextField().formfield().widget.media return template_vars
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set up the required js/css for the in-line editing toolbar and controls .
train
false
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def CorrelatedGenerator(rho): x = random.gauss(0, 1) (yield x) sigma = math.sqrt((1 - (rho ** 2))) while True: x = random.gauss((x * rho), sigma) (yield x)
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generates standard normal variates with serial correlation .
train
false
13,573
def replace_patterns(x, replace): for (from_, to) in iteritems(replace): x = x.replace(str(from_), str(to)) return x
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replace replace in string x .
train
false
13,574
def expm_frechet_block_enlarge(A, E): n = A.shape[0] M = np.vstack([np.hstack([A, E]), np.hstack([np.zeros_like(A), A])]) expm_M = scipy.linalg.expm(M) return (expm_M[:n, :n], expm_M[:n, n:])
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this is a helper function .
train
false
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def test_solve_fixed_trajectory(): (t0, k0) = (0, np.array([5.0])) results = _compute_fixed_length_solns(model, t0, k0) for (integrator, numeric_solution) in results.items(): ti = numeric_solution[:, 0] analytic_solution = solow_analytic_solution(ti, k0, *valid_params) np.testing.assert_allclose(numeric_solution, analytic_solution)
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testing computation of fixed length solution trajectory .
train
false
13,576
def parse_ansi(string, strip_ansi=False, parser=ANSI_PARSER, xterm256=False, mxp=False): return parser.parse_ansi(string, strip_ansi=strip_ansi, xterm256=xterm256, mxp=mxp)
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parses a string .
train
false
13,579
def validate_badge_image(image): if (image.width != image.height): raise ValidationError(_(u'The badge image must be square.')) if (not (image.size < (250 * 1024))): raise ValidationError(_(u'The badge image file size must be less than 250KB.'))
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validates that a particular image is small enough to be a badge and square .
train
false
13,580
def max_score(scores): lst = sorted_score(scores) max_score = lst[0][1] return [(i[0], i[1]) for i in lst if (i[1] == max_score)]
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the max scroe and the persons name .
train
false
13,581
def p_jump_statement_1(t): pass
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jump_statement : goto id semi .
train
false
13,582
def _crawl(expr, func, *args, **kwargs): val = func(expr, *args, **kwargs) if (val is not None): return val new_args = (_crawl(arg, func, *args, **kwargs) for arg in expr.args) return expr.func(*new_args)
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crawl the expression tree .
train
false
13,584
def get_lang_dict(fortype, name=None): from frappe.translate import get_dict return get_dict(fortype, name)
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returns all languages in dict format .
train
false
13,586
def test_label_problems_at_runtime(): @_preprocess_data(label_namer='z') def func(*args, **kwargs): pass with pytest.warns(RuntimeWarning): func(None, x='a', y='b') def real_func(x, y): pass @_preprocess_data(label_namer='x') def func(*args, **kwargs): real_func(**kwargs) with pytest.raises(TypeError): func(None, x='a', y='b')
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tests for behaviour which would actually be nice to get rid of .
train
false
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def course_ids_between(start_word, end_word): valid_courses = [] for course in modulestore().get_courses(): course_id = course.id.to_deprecated_string() if (start_word.lower() <= course_id.lower() <= end_word.lower()): valid_courses.append(course.id) return valid_courses
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returns a list of all valid course_ids that fall alphabetically between start_word and end_word .
train
false
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def formatnumber(n): parts = list(str(n)) for i in range((len(parts) - 3), 0, (-3)): parts.insert(i, ',') return ''.join(parts)
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format a number with beautiful commas .
train
false
13,589
def corpus2dense(corpus, num_terms, num_docs=None, dtype=np.float32): if (num_docs is not None): (docno, result) = ((-1), np.empty((num_terms, num_docs), dtype=dtype)) for (docno, doc) in enumerate(corpus): result[:, docno] = sparse2full(doc, num_terms) assert ((docno + 1) == num_docs) else: result = np.column_stack((sparse2full(doc, num_terms) for doc in corpus)) return result.astype(dtype)
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convert corpus into a dense np array .
train
false
13,590
def make_global_ns(name): if is_private(name): raise ValueError(('cannot turn [%s] into a global name' % name)) if (not is_global(name)): name = (SEP + name) if (name[(-1)] != SEP): name = (name + SEP) return name
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convert name to a global name with a trailing namespace separator .
train
false
13,591
def get_targets(): logs = NodeLog.find((((((((((Q('action', 'eq', 'registration_initiated') | Q('action', 'eq', 'registration_approved')) | Q('action', 'eq', 'registration_cancelled')) | Q('action', 'eq', 'retraction_initiated')) | Q('action', 'eq', 'retraction_approved')) | Q('action', 'eq', 'retraction_cancelled')) | Q('action', 'eq', 'embargo_initiated')) | Q('action', 'eq', 'embargo_approved')) | Q('action', 'eq', 'embargo_completed')) | Q('action', 'eq', 'embargo_cancelled'))) return logs
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get addongithubnodesettings records with authorization and a non-null webhook .
train
false
13,592
def _massage_stats(request, stats): path = stats['path'] normalized = request.fs.normpath(path) return {'path': normalized, 'name': stats['name'], 'stats': stats.to_json_dict(), 'mtime': (datetime.fromtimestamp(stats['mtime']).strftime('%B %d, %Y %I:%M %p') if stats['mtime'] else ''), 'humansize': filesizeformat(stats['size']), 'type': filetype(stats['mode']), 'rwx': rwx(stats['mode'], stats['aclBit']), 'mode': stringformat(stats['mode'], 'o'), 'url': reverse('filebrowser.views.view', kwargs=dict(path=normalized)), 'is_sentry_managed': request.fs.is_sentry_managed(path)}
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massage a stats record as returned by the filesystem implementation into the format that the views would like it in .
train
false
13,593
def zero_remove(data, mask): new_mask = mask.copy() new_mask[(data == 0)] = 0 return new_mask
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modify inputted mask to also mask out zero values .
train
false
13,594
def get_file_from_request(ext=None, folder=None, name='file'): if (ext is None): ext = [] print ('get_file_from_request() INVOKED. We have: request.files = %r' % request.files) if (name not in request.files): raise NotFoundError('File not found') uploaded_file = request.files[name] if (uploaded_file.filename == ''): raise NotFoundError('File not found') if (not _allowed_file(uploaded_file.filename, ext)): raise NotFoundError('Invalid file type') if (not folder): folder = app.config['UPLOAD_FOLDER'] else: with app.app_context(): folder = (app.config['BASE_DIR'] + folder) filename = secure_filename(uploaded_file.filename) uploaded_file.save(os.path.join(folder, filename)) return os.path.join(folder, filename)
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get file from a request .
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false
13,595
def unixTime(): return systime.time()
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return the current time in seconds with high precision (unix version .
train
false
13,596
def testing_warn(msg, stacklevel=3): filename = 'sqlalchemy.testing.warnings' lineno = 1 if isinstance(msg, util.string_types): warnings.warn_explicit(msg, sa_exc.SAWarning, filename, lineno) else: warnings.warn_explicit(msg, filename, lineno)
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replaces sqlalchemy .
train
false
13,597
def toChunk(data): return (('%x\r\n' % len(data)), data, '\r\n')
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convert string to a chunk .
train
false
13,598
def gravatar(email, default_avatar_url=settings.DEFAULT_AVATAR_URL, size=175, rating='pg'): url = GRAVATAR_URL.format(emaildigest=md5(email).hexdigest()) url = urlparams(url, d=utils.absolutify(default_avatar_url), s=size, r=rating) return url
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hacked from djangosnippets .
train
false
13,600
def getFeedRateMinute(feedRateMinute, splitLine): indexOfF = getIndexOfStartingWithSecond('F', splitLine) if (indexOfF > 0): return getDoubleAfterFirstLetter(splitLine[indexOfF]) return feedRateMinute
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get the feed rate per minute if the split line has a feed rate .
train
false
13,601
def humanitarian_id(): channel = settings.get_auth_humanitarian_id() if (not channel): redirect(URL(f='user', args=request.args, vars=get_vars)) from s3oauth import HumanitarianIDAccount auth.settings.login_form = HumanitarianIDAccount(channel) form = auth() return {'form': form}
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login using humanitarian .
train
false
13,602
def runs(seq, op=gt): cycles = [] seq = iter(seq) try: run = [next(seq)] except StopIteration: return [] while True: try: ei = next(seq) except StopIteration: break if op(ei, run[(-1)]): run.append(ei) continue else: cycles.append(run) run = [ei] if run: cycles.append(run) return cycles
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group the sequence into lists in which successive elements all compare the same with the comparison operator .
train
false
13,603
@login_required @ensure_csrf_cookie @require_http_methods(('GET', 'POST', 'PUT', 'DELETE')) def course_team_handler(request, course_key_string=None, email=None): course_key = (CourseKey.from_string(course_key_string) if course_key_string else None) if ('application/json' in request.META.get('HTTP_ACCEPT', 'application/json')): return _course_team_user(request, course_key, email) elif (request.method == 'GET'): return _manage_users(request, course_key) else: return HttpResponseNotFound()
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the restful handler for course team users .
train
false
13,604
def Enum(*args, **kwargs): def getLabel(cls, val): ' Get a string label for the current value of the enum ' return cls.__labels[val] def validate(cls, val): ' Returns True if val is a valid value for the enumeration ' return (val in cls.__values) def getValues(cls): ' Returns a list of all the possible values for this enum ' return list(cls.__values) def getLabels(cls): ' Returns a list of all possible labels for this enum ' return list(cls.__labels.values()) def getValue(cls, label): ' Returns value given a label ' return cls.__labels[label] for arg in (list(args) + kwargs.keys()): if (type(arg) is not str): raise TypeError('Enum arg {0} must be a string'.format(arg)) if (not __isidentifier(arg)): raise ValueError("Invalid enum value '{0}'. '{0}' is not a valid identifier".format(arg)) kwargs.update(zip(args, args)) newType = type('Enum', (object,), kwargs) newType.__labels = dict(((v, k) for (k, v) in kwargs.iteritems())) newType.__values = set(newType.__labels.keys()) newType.getLabel = functools.partial(getLabel, newType) newType.validate = functools.partial(validate, newType) newType.getValues = functools.partial(getValues, newType) newType.getLabels = functools.partial(getLabels, newType) newType.getValue = functools.partial(getValue, newType) return newType
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enum is an adapter to another field: it will just change its display attribute .
train
true
13,605
def neutron_public_url(catalog): for i in catalog['access']['serviceCatalog']: if (i['type'] == 'network'): for endpoint in i['endpoints']: return endpoint['publicURL']
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get neutron publicurl .
train
false
13,608
def blast_genome(seqs, blast_db, e_value, max_hits, word_size, working_dir, blast_mat_root, extra_params=[], DEBUG=True): params = {'-M': 'BLOSUM62', '-a': '1', '-e': e_value, '-b': max_hits, '-W': word_size, '-v': max_hits, '-m': '9', '-p': 'blastn'} params.update(extra_params) output = blast_seqs(seqs, Blastall, blast_db=blast_db, params=params, WorkingDir=working_dir, add_seq_names=False, blast_mat_root=blast_mat_root) raw_output = [x for x in output['StdOut']] return raw_output
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blast sequences against all genes in a genome seqs -- input sequences as strings blast_db -- path to blast database e_value -- e_value max_hits -- maximum sequences detected by blast to show word_size -- word size for initial blast screen .
train
false
13,609
def test_random_sample_size(): a = db.from_sequence(range(1000), npartitions=5) assert (10 < len(list(a.random_sample(0.1, 42))) < 300)
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number of randomly sampled elements are in the expected range .
train
false
13,610
@testing.requires_testing_data def test_plot_source_spectrogram(): sample_src = read_source_spaces(op.join(subjects_dir, 'sample', 'bem', 'sample-oct-6-src.fif')) vertices = [s['vertno'] for s in sample_src] n_times = 5 n_verts = sum((len(v) for v in vertices)) stc_data = np.ones((n_verts, n_times)) stc = SourceEstimate(stc_data, vertices, 1, 1) plot_source_spectrogram([stc, stc], [[1, 2], [3, 4]]) assert_raises(ValueError, plot_source_spectrogram, [], []) assert_raises(ValueError, plot_source_spectrogram, [stc, stc], [[1, 2], [3, 4]], tmin=0) assert_raises(ValueError, plot_source_spectrogram, [stc, stc], [[1, 2], [3, 4]], tmax=7)
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test plotting of source spectrogram .
train
false
13,613
def CohenEffectSize(group1, group2): diff = (group1.mean() - group2.mean()) (n1, n2) = (len(group1), len(group2)) var1 = group1.var() var2 = group2.var() pooled_var = (((n1 * var1) + (n2 * var2)) / (n1 + n2)) d = (diff / math.sqrt(pooled_var)) return d
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compute cohens d .
train
false
13,614
def dedent_lines(lines): return textwrap.dedent('\n'.join(lines)).split('\n')
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deindent a list of lines maximally .
train
false
13,615
def getDisplayToolButtonsRepository(directoryPath, importantFileNames, names, repository): displayToolButtons = [] for name in names: displayToolButton = DisplayToolButton().getFromPath((name in importantFileNames), name, os.path.join(directoryPath, name), repository) displayToolButtons.append(displayToolButton) return displayToolButtons
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get the display tool buttons .
train
false
13,617
def IsPacificDST(now): pst = time.gmtime(now) year = pst[0] assert (year >= 2007) begin = calendar.timegm((year, 3, 8, 2, 0, 0, 0, 0, 0)) while (time.gmtime(begin).tm_wday != SUNDAY): begin += DAY end = calendar.timegm((year, 11, 1, 2, 0, 0, 0, 0, 0)) while (time.gmtime(end).tm_wday != SUNDAY): end += DAY return (begin <= now < end)
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helper for pacifictime to decide whether now is pacific dst .
train
false
13,619
def getAppExt(loops=0): bb = '!\xff\x0b' bb += 'NETSCAPE2.0' bb += '\x03\x01' if (loops == 0): loops = ((2 ** 16) - 1) bb += intToBin(loops) bb += '\x00' return bb
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application extention .
train
false
13,620
def test_run_tb(): with TemporaryDirectory() as td: path = pjoin(td, 'foo.py') with open(path, 'w') as f: f.write('\n'.join(['def foo():', ' return bar()', 'def bar():', " raise RuntimeError('hello!')", 'foo()'])) with capture_output() as io: _ip.magic('run {}'.format(path)) out = io.stdout nt.assert_not_in('execfile', out) nt.assert_in('RuntimeError', out) nt.assert_equal(out.count('---->'), 3)
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test traceback offset in %run .
train
false
13,621
def _lg_undirected(G, selfloops=False, create_using=None): if (create_using is None): L = G.__class__() else: L = create_using get_edges = _edge_func(G) sorted_node = _node_func(G) shift = (0 if selfloops else 1) edges = set([]) for u in G: nodes = [sorted_node(*x) for x in get_edges(u)] if (len(nodes) == 1): L.add_node(nodes[0]) for (i, a) in enumerate(nodes): edges.update([_sorted_edge(a, b) for b in nodes[(i + shift):]]) L.add_edges_from(edges) return L
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return the line graph l of the graph g .
train
false
13,622
def is_internal_attribute(obj, attr): if isinstance(obj, types.FunctionType): if (attr in UNSAFE_FUNCTION_ATTRIBUTES): return True elif isinstance(obj, types.MethodType): if ((attr in UNSAFE_FUNCTION_ATTRIBUTES) or (attr in UNSAFE_METHOD_ATTRIBUTES)): return True elif isinstance(obj, type): if (attr == 'mro'): return True elif isinstance(obj, (types.CodeType, types.TracebackType, types.FrameType)): return True elif isinstance(obj, types.GeneratorType): if (attr in UNSAFE_GENERATOR_ATTRIBUTES): return True elif (hasattr(types, 'CoroutineType') and isinstance(obj, types.CoroutineType)): if (attr in UNSAFE_COROUTINE_ATTRIBUTES): return True elif (hasattr(types, 'AsyncGeneratorType') and isinstance(obj, types.AsyncGeneratorType)): if (attr in UNSAFE_ASYNC_GENERATOR_ATTRIBUTES): return True return attr.startswith('__')
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test if the attribute given is an internal python attribute .
train
true
13,623
def glob(tgt, minion_id=None): if (minion_id is not None): if (not isinstance(minion_id, string_types)): minion_id = str(minion_id) else: minion_id = __grains__['id'] matcher = salt.minion.Matcher({'id': minion_id}, __salt__) try: return matcher.glob_match(tgt) except Exception as exc: log.exception(exc) return False
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iterates all filesystem paths that get matched by the glob pattern .
train
false
13,624
def _all_bookmarks(repo): return repo.bookmarks()[0]
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returns all bookmarks for the specified repo .
train
false
13,625
def getSpherical(azimuthDegrees, elevationDegrees, radius=1.0): return getSphericalByRadians(math.radians(azimuthDegrees), math.radians(elevationDegrees), radius)
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get the spherical vector3 unit by degrees .
train
false
13,626
def funcname(func): if isinstance(func, functools.partial): return funcname(func.func) if isinstance(func, methodcaller): return func.method module_name = (getattr(func, '__module__', None) or '') type_name = (getattr(type(func), '__name__', None) or '') if (('toolz' in module_name) and ('curry' == type_name)): return func.func_name if (('multipledispatch' in module_name) and ('Dispatcher' == type_name)): return func.name try: name = func.__name__ if (name == '<lambda>'): return 'lambda' return name except: return str(func)
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get the name of a function .
train
false
13,628
def uniconvert(s, enc): if (not isinstance(s, unicode)): try: s = bin2unicode(s, enc) except UnicodeError: raise UnicodeError(('bad filename: ' + s)) return s.encode(enc)
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convert s to a string containing a unicode sequence encoded using encoding "enc" .
train
false
13,629
def _step4(state): C = (state.C == 0).astype(np.int) covered_C = (C * state.row_uncovered[:, np.newaxis]) covered_C *= astype(state.col_uncovered, dtype=np.int, copy=False) n = state.C.shape[0] m = state.C.shape[1] while True: (row, col) = np.unravel_index(np.argmax(covered_C), (n, m)) if (covered_C[(row, col)] == 0): return _step6 else: state.marked[(row, col)] = 2 star_col = np.argmax((state.marked[row] == 1)) if (not (state.marked[(row, star_col)] == 1)): state.Z0_r = row state.Z0_c = col return _step5 else: col = star_col state.row_uncovered[row] = False state.col_uncovered[col] = True covered_C[:, col] = (C[:, col] * astype(state.row_uncovered, dtype=np.int, copy=False)) covered_C[row] = 0
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find a noncovered zero and prime it .
train
false
13,630
def lowercase_keys(mapping): items = mapping.items() for (key, value) in items: del mapping[key] mapping[key.lower()] = value
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converts the values of the keys in mapping to lowercase .
train
false
13,631
def test_import_vispy(): modnames = loaded_vispy_modules('vispy', 2) assert_equal(modnames, set(_min_modules))
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importing vispy should only pull in other vispy .
train
false
13,632
def query_all_issues(after): page = count(1) data = [] while True: page_data = query_issues(next(page), after) if (not page_data): break data.extend(page_data) return data
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hits the github api for all closed issues after the given date .
train
true
13,633
def switch_desc_to_dict(desc): r = {} for k in ['mfr_desc', 'hw_desc', 'sw_desc', 'serial_num', 'dp_desc']: r[k] = getattr(desc, k) return r
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takes ofp_desc_stats response .
train
false
13,634
def copy_query_dict(query_dict, attr_list): res = QueryDict('', mutable=True) for attr in attr_list: if query_dict.has_key(attr): res[attr] = query_dict.get(attr) return res
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copy_query_dict -> querydict object copy the specified attributes to a new querydict .
train
false
13,635
def getBackOfLoops(loops): negativeFloat = (-999999999.7534235) back = negativeFloat for loop in loops: for point in loop: back = max(back, point.imag) if (back == negativeFloat): print 'This should never happen, there are no loops for getBackOfLoops in euclidean' return back
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get the back of the loops .
train
false
13,636
def set_backend_policy(name, port, policies=None, region=None, key=None, keyid=None, profile=None): conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) if (not exists(name, region, key, keyid, profile)): return True if (policies is None): policies = [] try: conn.set_lb_policies_of_backend_server(name, port, policies) log.info('Set policies {0} on ELB {1} backend server {2}'.format(policies, name, port)) except boto.exception.BotoServerError as e: log.debug(e) log.info('Failed to set policy {0} on ELB {1} backend server {2}: {3}'.format(policies, name, port, e.message)) return False return True
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set the policies of an elb backend server .
train
true
13,637
def averageOnTimePerTimestep(vectors, numSamples=None): if (vectors.ndim == 1): vectors.shape = ((-1), 1) numTimeSteps = len(vectors) numElements = len(vectors[0]) if (numSamples is not None): import pdb pdb.set_trace() countOn = numpy.random.randint(0, numElements, numSamples) vectors = vectors[:, countOn] durations = numpy.zeros(vectors.shape, dtype='int32') for col in xrange(vectors.shape[1]): _fillInOnTimes(vectors[:, col], durations[:, col]) sums = vectors.sum(axis=1) sums.clip(min=1, max=numpy.inf, out=sums) avgDurations = (durations.sum(axis=1, dtype='float64') / sums) avgOnTime = (avgDurations.sum() / (avgDurations > 0).sum()) freqCounts = _accumulateFrequencyCounts(avgDurations) return (avgOnTime, freqCounts)
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computes the average on-time of the outputs that are on at each time step .
train
true
13,638
def uniform_linear_layout(points): indices = numpy.argsort(points) space = numpy.asarray(linspace(len(points))) indices = invert_permutation_indices(indices) points = space[indices] return points.tolist()
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layout the points in a uniform linear space while preserving the existing sorting order .
train
false
13,639
def _KNV0(B, ker_pole, transfer_matrix, j, poles): transfer_matrix_not_j = np.delete(transfer_matrix, j, axis=1) (Q, R) = s_qr(transfer_matrix_not_j, mode='full') mat_ker_pj = np.dot(ker_pole[j], ker_pole[j].T) yj = np.dot(mat_ker_pj, Q[:, (-1)]) if (not np.allclose(yj, 0)): xj = (yj / np.linalg.norm(yj)) transfer_matrix[:, j] = xj
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algorithm "knv0" kautsky et al .
train
false
13,643
def get_qualitycheck_list(path_obj): result = [] checks = get_qualitychecks() for (check, cat) in checks.items(): result.append({'code': check, 'is_critical': (cat == Category.CRITICAL), 'title': (u'%s' % check_names.get(check, check)), 'url': path_obj.get_translate_url(check=check)}) def alphabetical_critical_first(item): critical_first = (0 if item['is_critical'] else 1) return (critical_first, item['title'].lower()) result = sorted(result, key=alphabetical_critical_first) return result
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returns list of checks sorted in alphabetical order but having critical checks first .
train
false
13,645
def apply_filters(records, filters): operators = {COMPARISON.LT: operator.lt, COMPARISON.MAX: operator.le, COMPARISON.EQ: operator.eq, COMPARISON.NOT: operator.ne, COMPARISON.MIN: operator.ge, COMPARISON.GT: operator.gt, COMPARISON.IN: operator.contains, COMPARISON.EXCLUDE: (lambda x, y: (not operator.contains(x, y))), COMPARISON.LIKE: (lambda x, y: re.search(y, x, re.IGNORECASE))} for record in records: matches = True for f in filters: right = f.value if (f.field == DEFAULT_ID_FIELD): if isinstance(right, int): right = str(right) left = record subfields = f.field.split('.') for subfield in subfields: if (not isinstance(left, dict)): break left = left.get(subfield) if (f.operator in (COMPARISON.IN, COMPARISON.EXCLUDE)): (right, left) = (left, right) elif (left is None): right_is_number = (isinstance(right, (int, float)) and (right not in (True, False))) if right_is_number: matches = False continue else: left = '' matches = (matches and operators[f.operator](left, right)) if matches: (yield record)
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use this method to apply an iterable of filters to a stream .
train
false
13,646
def nathanathan(function, yays=[], nays=[]): yay_set = set() nay_set = set() for yay in yays: if (yay in yay_set): print (yay + ' tried to vote more than once.') else: yay_set.add(yay) for nay in nays: if (nay in nay_set): print (nay + ' tried to vote more than once.') else: nay_set.add(nay) for yay_nay_vote in yay_set.intersection(nay_set): print (yay_nay_vote + ' voted yay and nay.') valid_names = nathanathan.__globals__.keys() for vote in yay_set.union(nay_set): if (vote not in valid_names): print (vote + ' is not a valid voter') if (vote in yay_set): yay_set.remove(vote) if (vote in nay_set): nay_set.remove(vote) if (len(yay_set) >= len(nay_set)): function()
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this is a function for voting on whether functions should run .
train
false
13,647
def label_indivs(valuation, lexicon=False): domain = valuation.domain pairs = [(e, e) for e in domain] if lexicon: lex = make_lex(domain) with open(u'chat_pnames.cfg', u'w') as outfile: outfile.writelines(lex) valuation.update(pairs) return valuation
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assign individual constants to the individuals in the domain of a valuation .
train
false
13,649
def sub_func_doit(eq, func, new): reps = {} repu = {} for d in eq.atoms(Derivative): u = Dummy('u') repu[u] = d.subs(func, new).doit() reps[d] = u return eq.subs(reps).subs(func, new).subs(repu)
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when replacing the func with something else .
train
false
13,650
def tee(content, file): fd = open(file, 'a') fd.write((content + '\n')) fd.close() print content
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write content to standard output and file .
train
false
13,652
def wrap_old_error_serializer(old_fn): def new_fn(req, resp, exception): (media_type, body) = old_fn(req, exception) if (body is not None): resp.body = body resp.content_type = media_type return new_fn
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wraps an old-style error serializer to add body/content_type setting .
train
false
13,653
@ensure_csrf_cookie @cache_if_anonymous() def courses(request): enable_mktg_site = configuration_helpers.get_value('ENABLE_MKTG_SITE', settings.FEATURES.get('ENABLE_MKTG_SITE', False)) if enable_mktg_site: return redirect(marketing_link('COURSES'), permanent=True) if (not settings.FEATURES.get('COURSES_ARE_BROWSABLE')): raise Http404 return courseware.views.views.courses(request)
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render the "find courses" page .
train
false
13,654
def standard_node(hostname): return ProcessNode.using_ssh(hostname, 22, 'root', SSH_PRIVATE_KEY_PATH)
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create the default production inode for the given hostname .
train
false