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def get_repository_for_hook(repository_id, hosting_service_id, local_site_name, hooks_uuid=None): q = (Q(pk=repository_id) & Q(hosting_account__service_name=hosting_service_id)) if hooks_uuid: q &= Q(hooks_uuid=hooks_uuid) if local_site_name: q &= Q(local_site__name=local_site_name) else: q &= Q(local_site__isnull=True) return get_object_or_404(Repository, q)
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returns a repository for the given hook parameters .
train
false
38,737
def quota_update_resource(context, old_res, new_res): return IMPL.quota_update_resource(context, old_res, new_res)
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update resource of quotas .
train
false
38,738
def quote_identifier(identifier, for_grants=False): if for_grants: return (('`' + identifier.replace('`', '``').replace('_', '\\_').replace('%', '\\%%')) + '`') else: return (('`' + identifier.replace('`', '``').replace('%', '%%')) + '`')
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return an identifier name escaped for mysql this means surrounded by "" character and escaping this character inside .
train
false
38,740
def HashFile(f): if (type(f) is list): f = f[0] try: return hashlib.sha256(open(f, 'rb').read()).hexdigest() except: return 'UNKNOWN'
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returns sha-256 hash of a given file .
train
false
38,742
def attach_bumper_transcript(item, filename, lang='en'): item.video_bumper['transcripts'][lang] = filename
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attach bumper transcript .
train
false
38,743
def metadef_object_get_all(context, namespace_name, session=None): session = (session or get_session()) return metadef_object_api.get_all(context, namespace_name, session)
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get a metadata-schema object or raise if it does not exist .
train
false
38,744
def _verify_revision_is_published(location): assert (location.revision == MongoRevisionKey.published)
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asserts that the revision set on the given location is mongorevisionkey .
train
false
38,745
def do_list_extensions(cs, _args): extensions = cs.list_extensions.show_all() fields = ['Name', 'Summary', 'Alias', 'Updated'] utils.print_list(extensions, fields)
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list all the os-api extensions that are available .
train
false
38,746
def bellman_ford(G, source, weight='weight'): _warnings.warn('Function bellman_ford() is deprecated, use function bellman_ford_predecessor_and_distance() instead.', DeprecationWarning) return bellman_ford_predecessor_and_distance(G, source, weight=weight)
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deprecated: has been replaced by function bellman_ford_predecessor_and_distance() .
train
false
38,748
def system_specific_scripts(system=None): if is_windows(system): return ['.bat', '.vbs'] elif is_osx(system): return ['.command', '.sh'] else: return ['.sh']
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all scripting types for that platform .
train
false
38,749
def test_update_contact(contacts_provider, contact_sync, db): contacts_provider.supply_contact('Old Name', 'old@email.address') contact_sync.provider = contacts_provider contact_sync.sync() results = db.session.query(Contact).all() email_addresses = [r.email_address for r in results] assert ('old@email.address' in email_addresses) contacts_provider.__init__() contacts_provider.supply_contact('New Name', 'new@email.address') contact_sync.sync() db.session.commit() results = db.session.query(Contact).all() names = [r.name for r in results] assert ('New Name' in names) email_addresses = [r.email_address for r in results] assert ('new@email.address' in email_addresses)
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test that subsequent contact updates get stored .
train
false
38,750
def CleanList(list, folder, files): for path in sorted(list.keys()): (fld, name) = os.path.split(path) if (fld == folder): present = False for name in files: if (os.path.join(folder, name) == path): present = True break if (not present): del list[path]
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remove elements of "list" not found in "files" .
train
false
38,751
def run_simulation(session, users): for (n, user) in enumerate(users): if (((n % 100) == 0) and (n != 0)): print 'Simulated data for {} users'.format(n) simulate_user_history(session, user) print 'COMPLETE: Simulated data for {} users'.format(len(users))
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simulates app activity for all users .
train
false
38,752
def get_platform_info_dict(): platform_dict = {} (sysname, nodename, release, version, machine) = os.uname() platform_dict['os'] = sysname.lower() platform_dict['architecture'] = machine.lower() return platform_dict
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return a dict with information about the current platform .
train
false
38,753
def get_all_types_by_group(context, group_id): vol_types = db.volume_type_get_all_by_group(context, group_id) return vol_types
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get all volume_types in a group .
train
false
38,754
def test_unit_summary_prefixes(): from .. import astrophys for summary in utils._iter_unit_summary(astrophys.__dict__): (unit, _, _, _, prefixes) = summary if (unit.name == u'lyr'): assert prefixes elif (unit.name == u'pc'): assert prefixes elif (unit.name == u'barn'): assert prefixes elif (unit.name == u'cycle'): assert (not prefixes) elif (unit.name == u'vox'): assert prefixes
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test for a few units that the unit summary table correctly reports whether or not that unit supports prefixes .
train
false
38,756
def _FixPaths(paths): return [_FixPath(i) for i in paths]
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fix each of the paths of the list .
train
false
38,759
def blankline_separated_blocks(text): block = [] for line in text.splitlines(True): block.append(line) line = line.strip() if ((not line) or (line.startswith('===') and (not line.strip('=')))): (yield ''.join(block)) block = [] if block: (yield ''.join(block))
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a bunch of === characters is also considered a blank line .
train
false
38,760
def frequencies(seq): d = collections.defaultdict(int) for item in seq: d[item] += 1 return dict(d)
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find number of occurrences of each value in seq .
train
false
38,761
def sort_results(results): results.sort(key=(lambda x: unicode_sorter(force_text(x))))
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performs in-place sort of filterchain results .
train
false
38,762
def get_feedback_message_references(user_id): model = feedback_models.UnsentFeedbackEmailModel.get(user_id, strict=False) if (model is None): return [] return [feedback_domain.FeedbackMessageReference(reference['exploration_id'], reference['thread_id'], reference['message_id']) for reference in model.feedback_message_references]
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fetches all feedbackmessagereference objects written by the given user。 args: user_id: str .
train
false
38,763
def compute_node_get_all_by_pagination(context, limit=None, marker=None): return IMPL.compute_node_get_all_by_pagination(context, limit=limit, marker=marker)
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get compute nodes by pagination .
train
false
38,764
def _split_conditional(string): bracks_open = 0 args = [] carg = '' escaped = False for (idx, char) in enumerate(string): if (char == '('): if (not escaped): bracks_open += 1 elif (char == ')'): if (not escaped): bracks_open -= 1 elif ((char == ':') and (not bracks_open) and (not escaped)): args.append(carg) carg = '' escaped = False continue carg += char if (char == '\\'): escaped = (not escaped) else: escaped = False args.append(carg) return args
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split the given conditional string into its arguments .
train
false
38,766
@contextlib.contextmanager def ignored(*exceptions): try: (yield) except exceptions: pass
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context manager that ignores all of the specified exceptions .
train
false
38,769
def publish_programmatically(source_class, source, source_path, destination_class, destination, destination_path, reader, reader_name, parser, parser_name, writer, writer_name, settings, settings_spec, settings_overrides, config_section, enable_exit_status): pub = Publisher(reader, parser, writer, settings=settings, source_class=source_class, destination_class=destination_class) pub.set_components(reader_name, parser_name, writer_name) pub.process_programmatic_settings(settings_spec, settings_overrides, config_section) pub.set_source(source, source_path) pub.set_destination(destination, destination_path) output = pub.publish(enable_exit_status=enable_exit_status) return (output, pub)
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set up & run a publisher for custom programmatic use .
train
false
38,770
def preorder_traversal(task): for item in task: if istask(item): for i in preorder_traversal(item): (yield i) elif isinstance(item, list): (yield list) for i in preorder_traversal(item): (yield i) else: (yield item)
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a generator to preorder-traverse a task .
train
false
38,771
def _find_baremetal_node(cs, node): return utils.find_resource(cs.baremetal, node)
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get a node by id .
train
false
38,772
def activity_detail_list(context, data_dict): model = context['model'] activity_id = _get_or_bust(data_dict, 'id') activity_detail_objects = model.ActivityDetail.by_activity_id(activity_id) return model_dictize.activity_detail_list_dictize(activity_detail_objects, context)
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return an activitys list of activity detail items .
train
false
38,774
def group_by_node(notifications): emails = NotificationsDict() for notification in notifications: emails.add_message(notification['node_lineage'], notification['message']) return emails
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take list of notifications and group by node .
train
false
38,777
def p_struct_or_union_specifier_3(t): pass
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struct_or_union_specifier : struct_or_union id .
train
false
38,778
def add_users(caller, role, *users): _check_caller_authority(caller, role) role.add_users(*users)
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the caller requests adding the given users to the role .
train
false
38,779
def p_postfix_expression_4(t): pass
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postfix_expression : postfix_expression lparen rparen .
train
false
38,780
def dmp_clear_denoms(f, u, K0, K1=None, convert=False): if (not u): return dup_clear_denoms(f, K0, K1, convert=convert) if (K1 is None): if K0.has_assoc_Ring: K1 = K0.get_ring() else: K1 = K0 common = _rec_clear_denoms(f, u, K0, K1) if (not K1.is_one(common)): f = dmp_mul_ground(f, common, u, K0) if (not convert): return (common, f) else: return (common, dmp_convert(f, u, K0, K1))
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clear denominators .
train
false
38,781
def getNumberOfIntersectionsToLeft(loop, point): if (point == None): return 0 numberOfIntersectionsToLeft = 0 for pointIndex in xrange(len(loop)): firstPointComplex = loop[pointIndex] secondPointComplex = loop[((pointIndex + 1) % len(loop))] xIntersection = getXIntersectionIfExists(firstPointComplex, secondPointComplex, point.imag) if (xIntersection != None): if (xIntersection < point.real): numberOfIntersectionsToLeft += 1 return numberOfIntersectionsToLeft
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get the number of intersections through the loop for the line going left .
train
false
38,783
@pytest.mark.skipif('not HAS_BEAUTIFUL_SOUP') def test_htmlinputter(): f = 't/html.html' with open(f) as fd: table = fd.read() inputter = html.HTMLInputter() inputter.html = {} expected = ['<tr><th>Column 1</th><th>Column 2</th><th>Column 3</th></tr>', '<tr><td>1</td><td>a</td><td>1.05</td></tr>', '<tr><td>2</td><td>b</td><td>2.75</td></tr>', '<tr><td>3</td><td>c</td><td>-1.25</td></tr>'] assert ([str(x) for x in inputter.get_lines(table)] == expected) inputter.html = {'table_id': 4} with pytest.raises(core.InconsistentTableError): inputter.get_lines(table) inputter.html['table_id'] = 'second' expected = ['<tr><th>Column A</th><th>Column B</th><th>Column C</th></tr>', '<tr><td>4</td><td>d</td><td>10.5</td></tr>', '<tr><td>5</td><td>e</td><td>27.5</td></tr>', '<tr><td>6</td><td>f</td><td>-12.5</td></tr>'] assert ([str(x) for x in inputter.get_lines(table)] == expected) inputter.html['table_id'] = 3 expected = ['<tr><th>C1</th><th>C2</th><th>C3</th></tr>', '<tr><td>7</td><td>g</td><td>105.0</td></tr>', '<tr><td>8</td><td>h</td><td>275.0</td></tr>', '<tr><td>9</td><td>i</td><td>-125.0</td></tr>'] assert ([str(x) for x in inputter.get_lines(table)] == expected)
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test to ensure that htmlinputter correctly converts input into a list of soupstrings representing table elements .
train
false
38,784
def validate_hatch(s): if (not isinstance(s, six.string_types)): raise ValueError(u'Hatch pattern must be a string') unknown = (set(s) - {u'\\', u'/', u'|', u'-', u'+', u'*', u'.', u'x', u'o', u'O'}) if unknown: raise ValueError((u'Unknown hatch symbol(s): %s' % list(unknown))) return s
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validate a hatch pattern .
train
false
38,785
def rational_independent(terms, x): if (not terms): return [] ind = terms[0:1] for t in terms[1:]: n = t.as_independent(x)[1] for (i, term) in enumerate(ind): d = term.as_independent(x)[1] q = (n / d).cancel() if q.is_rational_function(x): ind[i] += t break else: ind.append(t) return ind
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returns a list of all the rationally independent terms .
train
false
38,786
def getNumberOfIntersectionsToLeftOfLoops(loops, point): totalNumberOfIntersectionsToLeft = 0 for loop in loops: totalNumberOfIntersectionsToLeft += getNumberOfIntersectionsToLeft(loop, point) return totalNumberOfIntersectionsToLeft
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get the number of intersections through the loop for the line starting from the left point and going left .
train
false
38,787
def whiten_ar(x, ar_coefs): rho = ar_coefs x = np.array(x, np.float64) if (x.ndim == 2): rho = rho[:, None] for i in range(self.order): _x[(i + 1):] = (_x[(i + 1):] - (rho[i] * x[0:(- (i + 1))])) return _x[self.order:]
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whiten a series of columns according to an ar(p) covariance structure .
train
false
38,789
def pat_matrix(m, dx, dy, dz): dxdy = ((- dx) * dy) dydz = ((- dy) * dz) dzdx = ((- dz) * dx) dxdx = (dx ** 2) dydy = (dy ** 2) dzdz = (dz ** 2) mat = (((dydy + dzdz), dxdy, dzdx), (dxdy, (dxdx + dzdz), dydz), (dzdx, dydz, (dydy + dxdx))) return (m * Matrix(mat))
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returns the parallel axis theorem matrix to translate the inertia matrix a distance of for a body of mass m .
train
false
38,791
def trim_gentoo_mirrors(value): return trim_var('GENTOO_MIRRORS', value)
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remove a value from gentoo_mirrors variable in the make .
train
false
38,793
def get_visible_pages(request, pages, site=None): pages = get_visible_page_objects(request, pages, site) return [page.pk for page in pages]
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returns the ids of all visible pages .
train
false
38,796
def test_hsl_to_rgb_part_17(): assert (hsl_to_rgb(240, 100, 0) == (0, 0, 0)) assert (hsl_to_rgb(240, 100, 10) == (0, 0, 51)) assert (hsl_to_rgb(240, 100, 20) == (0, 0, 102)) assert (hsl_to_rgb(240, 100, 30) == (0, 0, 153)) assert (hsl_to_rgb(240, 100, 40) == (0, 0, 204)) assert (hsl_to_rgb(240, 100, 50) == (0, 0, 255)) assert (hsl_to_rgb(240, 100, 60) == (51, 51, 255)) assert (hsl_to_rgb(240, 100, 70) == (102, 102, 255)) assert (hsl_to_rgb(240, 100, 80) == (153, 153, 255)) assert (hsl_to_rgb(240, 100, 90) == (204, 204, 255)) assert (hsl_to_rgb(240, 100, 100) == (255, 255, 255))
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test hsl to rgb color function .
train
false
38,797
def program_exists(program): proc = Popen(['which', program], stdout=PIPE, stderr=PIPE) txt = proc.communicate() if ((txt[0].strip() == '') and (txt[1].strip() == '')): return False if ((txt[0].strip() != '') and (txt[1].strip() == '')): return True return (not ((txt[1].strip() == '') or (txt[1].find(('no %s in' % program)) != (-1))))
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uses which to check if a program is installed .
train
false
38,798
def _get_zone(gcdns, zone_name, zone_id): if (zone_id is not None): try: return gcdns.get_zone(zone_id) except ZoneDoesNotExistError: return None available_zones = gcdns.iterate_zones() found_zone = None for zone in available_zones: if (zone.domain == zone_name): found_zone = zone break return found_zone
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gets the zone object for a given domain name .
train
false
38,799
def get_urls(): try: (__, __, port) = get_pid() urls = [] for addr in get_ip_addresses(): urls.append('http://{}:{}/'.format(addr, port)) return (STATUS_RUNNING, urls) except NotRunning as e: return (e.status_code, [])
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fetch a list of urls :returns: status_code .
train
false
38,800
def ip_host(value, options=None, version=None): ipaddr_filter_out = _filter_ipaddr(value, options=options, version=version) if (not ipaddr_filter_out): return return [ipaddress.ip_interface(ip_a) for ip_a in ipaddr_filter_out]
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returns the interfaces ip address .
train
false
38,801
def fill_paragraphs(s, width, sep=u'\n'): return sep.join((fill(p, width) for p in s.split(sep)))
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fill paragraphs with newlines .
train
false
38,802
def _natsort_key_case_insensitive(item): item = str(item).lower() try: chunks = re.split('(\\d+(?:\\.\\d+)?)', item) except TypeError: chunks = re.split('(\\d+(?:\\.\\d+)?)', item[0]) for ii in range(len(chunks)): if (chunks[ii] and (chunks[ii][0] in '0123456789')): if ('.' in chunks[ii]): numtype = float else: numtype = int chunks[ii] = (0, numtype(chunks[ii])) else: chunks[ii] = (1, chunks[ii]) return (chunks, item)
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provides normalized version of item for sorting with digits .
train
false
38,803
def skeletonize(image): image = image.astype(np.uint8) if (image.ndim != 2): raise ValueError('Skeletonize requires a 2D array') if (not np.all(np.in1d(image.flat, (0, 1)))): raise ValueError('Image contains values other than 0 and 1') return _fast_skeletonize(image)
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return the skeleton of a binary image .
train
false
38,805
def elemwise_mul(a, b): return (a * b)
[ "def", "elemwise_mul", "(", "a", ",", "b", ")", ":", "return", "(", "a", "*", "b", ")" ]
a: a theano matrix b: a theano matrix returns the elementwise product of a and b .
train
false
38,806
def find_or_create_node(branch, key): for node in branch: if (not isinstance(node, dict)): continue if (key in node): return node[key] new_branch = [] node = {key: new_branch} branch.append(node) return new_branch
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given a list .
train
false
38,809
def test_import_error_reporting(): def _import_error_test(): try: import_buffer_to_ast('(import "sys")', '') except HyTypeError: return 'Error reported' assert (_import_error_test() == 'Error reported') assert (_import_error_test() is not None)
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make sure that reports errors correctly .
train
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def get_entry_ids(entry): ids = {} for lazy in [False, True]: if entry.get(u'trakt_movie_id', eval_lazy=lazy): ids[u'trakt'] = entry[u'trakt_movie_id'] elif entry.get(u'trakt_show_id', eval_lazy=lazy): ids[u'trakt'] = entry[u'trakt_show_id'] elif entry.get(u'trakt_episode_id', eval_lazy=lazy): ids[u'trakt'] = entry[u'trakt_episode_id'] if entry.get(u'tmdb_id', eval_lazy=lazy): ids[u'tmdb'] = entry[u'tmdb_id'] if entry.get(u'tvdb_id', eval_lazy=lazy): ids[u'tvdb'] = entry[u'tvdb_id'] if entry.get(u'imdb_id', eval_lazy=lazy): ids[u'imdb'] = entry[u'imdb_id'] if entry.get(u'tvrage_id', eval_lazy=lazy): ids[u'tvrage'] = entry[u'tvrage_id'] if ids: break return ids
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creates a trakt ids dict from id fields on an entry .
train
false
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def _parse_life_span_string(life_span_string): try: life_span = int(life_span_string) except: life_span = _convert_life_span_string(life_span_string) if (life_span <= 0): raise Exception('Life span must be greater than 0') return life_span
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parses a life span string .
train
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def import_book(stream): (format, stream) = detect(stream) try: databook = Databook() format.import_book(databook, stream) return databook except AttributeError: return None
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return dataset of given stream .
train
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def min_dist(coord, surface): d = (surface - coord) d2 = numpy.sum((d * d), 1) return numpy.sqrt(min(d2))
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return minimum distance between coord and surface .
train
false
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def ec2_snap_id_to_uuid(ec2_id): ctxt = context.get_admin_context() int_id = ec2_id_to_id(ec2_id) return get_snapshot_uuid_from_int_id(ctxt, int_id)
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get the corresponding uuid for the given ec2-id .
train
false
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def _get_bbox_regression_labels(bbox_target_data, num_classes): clss = bbox_target_data[:, 0] bbox_targets = np.zeros((clss.size, (4 * num_classes)), dtype=np.float32) bbox_inside_weights = np.zeros(bbox_targets.shape, dtype=np.float32) inds = np.where((clss > 0))[0] for ind in inds: cls = clss[ind] start = (4 * cls) end = (start + 4) bbox_targets[ind, start:end] = bbox_target_data[ind, 1:] bbox_inside_weights[ind, start:end] = cfg.TRAIN.BBOX_INSIDE_WEIGHTS return (bbox_targets, bbox_inside_weights)
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bounding-box regression targets are stored in a compact form in the roidb .
train
false
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def volume_absent(name, driver=None): ret = {'name': name, 'changes': {}, 'result': False, 'comment': ''} volume = _find_volume(name) if (not volume): ret['result'] = True ret['comment'] = "Volume '{0}' already absent".format(name) return ret try: ret['changes']['removed'] = __salt__['dockerng.remove_volume'](name) ret['result'] = True except Exception as exc: ret['comment'] = "Failed to remove volume '{0}': {1}".format(name, exc) return ret
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check that a block volume exists .
train
true
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def unlock_keychain(keychain, password): cmd = 'security unlock-keychain -p {0} {1}'.format(password, keychain) __salt__['cmd.run'](cmd)
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unlock the given keychain with the password keychain the keychain to unlock password the password to use to unlock the keychain .
train
false
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def create_vm(session, instance, vm_folder, config_spec, res_pool_ref): LOG.debug('Creating VM on the ESX host', instance=instance) vm_create_task = session._call_method(session.vim, 'CreateVM_Task', vm_folder, config=config_spec, pool=res_pool_ref) try: task_info = session._wait_for_task(vm_create_task) except vexc.VMwareDriverException: with excutils.save_and_reraise_exception(): if (config_spec.guestId not in constants.VALID_OS_TYPES): LOG.warning(_LW("vmware_ostype from image is not recognised: '%(ostype)s'. An invalid os type may be one cause of this instance creation failure"), {'ostype': config_spec.guestId}) LOG.debug('Created VM on the ESX host', instance=instance) return task_info.result
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create vm on esx host .
train
false
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def _unpack_actions(b, length, offset=0): if ((len(b) - offset) < length): raise UnderrunError actions = [] end = (length + offset) while (offset < end): (t, l) = struct.unpack_from('!HH', b, offset) if ((len(b) - offset) < l): raise UnderrunError a = _action_type_to_class.get(t) if (a is None): a = ofp_action_generic() else: a = a() a.unpack(b[offset:(offset + l)]) assert (len(a) == l) actions.append(a) offset += l return (offset, actions)
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parses actions from a buffer b is a buffer offset .
train
false
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def load_sprite_image(img_path, rows_cols, n_sprites=None): (rows, cols) = rows_cols if (n_sprites is None): n_sprites = (rows * cols) img = caffe_load_image(img_path, color=True, as_uint=True) assert ((img.shape[0] % rows) == 0), ('sprite image has shape %s which is not divisible by rows_cols %' % (img.shape, rows_cols)) assert ((img.shape[1] % cols) == 0), ('sprite image has shape %s which is not divisible by rows_cols %' % (img.shape, rows_cols)) sprite_height = (img.shape[0] / rows) sprite_width = (img.shape[1] / cols) sprite_channels = img.shape[2] ret = np.zeros((n_sprites, sprite_height, sprite_width, sprite_channels), dtype=img.dtype) for idx in xrange(n_sprites): ii = (idx / cols) jj = (idx % cols) ret[idx] = img[(ii * sprite_height):((ii + 1) * sprite_height), (jj * sprite_width):((jj + 1) * sprite_width), :] return ret
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load a 2d sprite image where = rows_cols .
train
false
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def _ListUnion(list_1, list_2): if (not (isinstance(list_1, list) and isinstance(list_2, list))): raise TypeError('Arguments must be lists.') union = [] for x in (list_1 + list_2): if (x not in union): union.append(x) return union
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returns the union of two lists .
train
false
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def check_doubled_words(physical_line, filename): msg = "N343: Doubled word '%(word)s' typo found" match = re.search(doubled_words_re, physical_line) if match: return (0, (msg % {'word': match.group(1)}))
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check for the common doubled-word typos n343 .
train
false
38,832
def _comp_sort_keys(c): return (int(c['coeff_type']), int(c['scanno']))
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sort the compensation data .
train
false
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def depends(**dependencies): def decorator(func): @wraps(func) def wrapper(*a, **explicit): deps = dict([(k, get_dependency_for(k, v)) for (k, v) in dependencies.iteritems() if (k not in explicit)]) return func(*a, **union(deps, explicit)) return wrapper return decorator
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return a decorator that specifies the field dependencies of a "compute" method .
train
false
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def filter_comments(tree): def traverse(tree): 'Generator dropping comment nodes' for entry in tree: spaceless = [e for e in entry if (not nginxparser.spacey(e))] if spaceless: key = spaceless[0] values = (spaceless[1] if (len(spaceless) > 1) else None) else: key = values = '' if isinstance(key, list): new = copy.deepcopy(entry) new[1] = filter_comments(values) (yield new) elif ((key != '#') and spaceless): (yield spaceless) return list(traverse(tree))
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filter comment nodes from parsed configurations .
train
false
38,840
def get_default_stylesheet_location(): import os css_file = os.path.join(os.path.dirname(__file__), 'default.css') if (not os.path.exists(css_file)): raise Exception(('Default CSS file could not be found at %s' % css_file)) return css_file
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get_default_stylesheet_location() => file path returns the path of the default cascading style sheet file that is installed with the rest of the silvercity package .
train
false
38,844
def make_basic(app, global_conf, realm, authfunc, **kw): from paste.util.import_string import eval_import import types authfunc = eval_import(authfunc) assert isinstance(authfunc, types.FunctionType), 'authfunc must resolve to a function' return AuthBasicHandler(app, realm, authfunc)
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grant access via basic authentication config looks like this:: [filter:grant] use = egg:paste#auth_basic realm=myrealm authfunc=somepackage .
train
false
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def h5_deconv_data(filename): ret = list() with h5py.File(filename, 'r') as f: if ('deconv' not in list(f.keys())): return None act_data = f['deconv/max_act'] img_data = f['deconv/img'] for layer in list(act_data.keys()): layer_data = list() for fm in range(act_data[layer]['vis'].shape[0]): (batch_ind, img_ind) = act_data[layer]['batch_img'][fm] img_store = img_data['batch_{}'.format(batch_ind)] img_cache_ofs = img_store.attrs[str(img_ind)] plot_img = convert_rgb_to_bokehrgba(img_store['HWC_uint8'][:, :, :, img_cache_ofs]) plot_deconv = convert_rgb_to_bokehrgba(act_data[layer]['vis'][fm]) layer_data.append((fm, plot_deconv, plot_img)) ret.append((layer, layer_data)) return ret
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read deconv visualization data from hdf5 file .
train
false
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def _log_record_from_hadoop(record): if (not _is_counter_log4j_record(record)): level = getattr(logging, (record.get('level') or ''), None) _log_line_from_hadoop(record['message'], level=level)
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log log4j record parsed from hadoop stderr .
train
false
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@json_view @non_atomic_requests def ajax_search(request): search_obj = BaseAjaxSearch(request) search_obj.types = amo.ADDON_SEARCH_TYPES return search_obj.items
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this is currently used only to return add-ons for populating a new collection .
train
false
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def _linear_jac(t, y, a): return a
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jacobian of a * y is a .
train
false
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def get_oauth_url(scope, redirect_uri, extra_params=None): scope = parse_scope(scope) query_dict = QueryDict('', True) query_dict['scope'] = ','.join(scope) query_dict['client_id'] = facebook_settings.FACEBOOK_APP_ID query_dict['redirect_uri'] = redirect_uri oauth_url = 'https://www.facebook.com/dialog/oauth?' oauth_url += query_dict.urlencode() return oauth_url
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returns the oauth url for the given scope and redirect_uri .
train
false
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def _filterout_legal(lines): return [line for line in lines[5:] if ((not ('This experiment was created using PsychoPy2 Experiment Builder (' in line)) and (not (('trialList=data.importConditions(' in line) and (".xlsx'))" in line))))]
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ignore first 5 lines: header info .
train
false
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def get_training_roidb(imdb): if cfg.TRAIN.USE_FLIPPED: print 'Appending horizontally-flipped training examples...' imdb.append_flipped_images() print 'done' print 'Preparing training data...' rdl_roidb.prepare_roidb(imdb) print 'done' return imdb.roidb
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returns a roidb for use in training .
train
false
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def construct_parser(magic_func): kwds = getattr(magic_func, 'argcmd_kwds', {}) if ('description' not in kwds): kwds['description'] = getattr(magic_func, '__doc__', None) arg_name = real_name(magic_func) parser = MagicArgumentParser(arg_name, **kwds) group = None for deco in magic_func.decorators[::(-1)]: result = deco.add_to_parser(parser, group) if (result is not None): group = result magic_func.__doc__ = parser.format_help() return parser
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construct an argument parser using the function decorations .
train
true
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def repeat_first_axis(array, count): return as_strided(array, ((count,) + array.shape), ((0,) + array.strides))
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restride array to repeat count times along the first axis .
train
true
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def build_request_type(direction, type, recipient): return ((recipient | type) | direction)
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build a bmrequesttype field for control requests .
train
false
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def identity(x): return x
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identity function .
train
false
38,858
def name_lookup(qualified_name): if ('.' not in qualified_name): qualified_name = ('__builtin__.' + qualified_name) (module_name, class_name) = qualified_name.rsplit('.', 1) module = __import__(module_name, fromlist=[class_name]) return getattr(module, class_name)
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return the object referenced by a qualified name .
train
false
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def Compilable(filename): for res in (filename.endswith(e) for e in COMPILABLE_EXTENSIONS): if res: return True return False
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return true if the file is compilable .
train
false
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def bufsize_validator(kwargs): invalid = [] in_ob = kwargs.get('in', None) out_ob = kwargs.get('out', None) in_buf = kwargs.get('in_bufsize', None) out_buf = kwargs.get('out_bufsize', None) in_no_buf = (ob_is_tty(in_ob) or ob_is_pipe(in_ob)) out_no_buf = (ob_is_tty(out_ob) or ob_is_pipe(out_ob)) err = "Can't specify an {target} bufsize if the {target} target is a pipe or TTY" if (in_no_buf and (in_buf is not None)): invalid.append((('in', 'in_bufsize'), err.format(target='in'))) if (out_no_buf and (out_buf is not None)): invalid.append((('out', 'out_bufsize'), err.format(target='out'))) return invalid
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a validator to prevent a user from saying that they want custom buffering when theyre using an in/out object that will be os .
train
true
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def to_table(data, bins=None): data = np.asarray(data) (n_rows, n_cols) = data.shape if (bins is None): (cat_uni, cat_int) = np.unique(data.ravel(), return_inverse=True) n_cat = len(cat_uni) data_ = cat_int.reshape(data.shape) bins_ = (np.arange((n_cat + 1)) - 0.5) elif np.isscalar(bins): bins_ = (np.arange((bins + 1)) - 0.5) data_ = data else: bins_ = bins data_ = data tt = np.histogramdd(data_, ((bins_,) * n_cols)) return (tt[0], bins_)
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convert raw data with shape to brings data into correct format for cohens_kappa parameters data : array_like .
train
false
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def postBuildStatic(static): pass
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called after building a static file .
train
false
38,864
def _get_user_agent(): product_tokens = [] version = sdk_update_checker.GetVersionObject() if (version is None): release = 'unknown' else: release = version['release'] product_tokens.append(('%s/%s' % (SDK_PRODUCT, release))) product_tokens.append(appengine_rpc.GetPlatformToken()) python_version = '.'.join((str(i) for i in sys.version_info)) product_tokens.append(('Python/%s' % python_version)) return ' '.join(product_tokens)
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returns the value of the user-agent header to use for update requests .
train
false
38,865
def delete_datasource(datasourceid, orgname=None, profile='grafana'): if isinstance(profile, string_types): profile = __salt__['config.option'](profile) response = requests.delete('{0}/api/datasources/{1}'.format(profile['grafana_url'], datasourceid), auth=_get_auth(profile), headers=_get_headers(profile), timeout=profile.get('grafana_timeout', 3)) if (response.status_code >= 400): response.raise_for_status() return response.json()
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delete a datasource .
train
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@with_setup(reset) def test_invalid_call(): assert_raises(TypeError, register) assert_raises(TypeError, register, 'one-argument-only')
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test calling register with an invalid syntax .
train
false
38,868
@register.filter() def startswith(value, arg): return str(value).startswith(arg)
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test whether a string starts with the given argument .
train
false
38,870
def is_bogus_ip(ip): return (ip.startswith('0.') or ip.startswith('127.'))
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checks if the given ip address is bogus .
train
false
38,871
@cronjobs.register def enqueue_lag_monitor_task(): measure_queue_lag.delay(datetime.now())
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fires a task that measures the queue lag .
train
false
38,872
def servicegroup_server_up(sg_name, s_name, s_port, **connection_args): server = _servicegroup_get_server(sg_name, s_name, s_port, **connection_args) return ((server is not None) and (server.get_svrstate() == 'UP'))
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check if a server:port combination is in state up in a servicegroup cli example: .
train
true
38,873
def _build_align_cmdline(cmdline, pair, output_filename, kbyte=None, force_type=None, quiet=False): cmdline = cmdline[:] if (kbyte is None): try: cmdline.extend(('-kbyte', os.environ['WISE_KBYTE'])) except KeyError: pass else: cmdline.extend(('-kbyte', str(kbyte))) if (not os.isatty(sys.stderr.fileno())): cmdline.append('-quiet') cmdline.extend(pair) cmdline.extend(('>', output_filename)) if quiet: cmdline.extend(('2>', '/dev/null')) cmdline_str = ' '.join(cmdline) return cmdline_str
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helper function to build a command line string .
train
false
38,874
@requires_segment_info def jobnum(pl, segment_info, show_zero=False): jobnum = segment_info[u'args'].jobnum if ((jobnum is None) or ((not show_zero) and (jobnum == 0))): return None else: return str(jobnum)
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return the number of jobs .
train
false
38,878
def timed(registry, xml_parent, data): scmtrig = XML.SubElement(xml_parent, 'hudson.triggers.TimerTrigger') XML.SubElement(scmtrig, 'spec').text = data
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yaml: timed trigger builds at certain times .
train
false
38,879
def get_default_dest_dir(): t_downloaddir = u'TriblerDownloads' if os.path.isdir(t_downloaddir): return os.path.abspath(t_downloaddir) downloads_dir = os.path.join(get_home_dir(), u'Downloads') if os.path.isdir(downloads_dir): return os.path.join(downloads_dir, t_downloaddir) else: return os.path.join(get_home_dir(), t_downloaddir)
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returns the default dir to save content to .
train
false
38,881
def xl_rowcol_to_cell(row, col, row_abs=False, col_abs=False): row += 1 row_abs = ('$' if row_abs else '') col_str = xl_col_to_name(col, col_abs) return ((col_str + row_abs) + str(row))
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convert a zero indexed row and column cell reference to a a1 style string .
train
false
38,882
def _replaceIf(condition, alternative): def decorator(func): if (condition is True): call = alternative elif (condition is False): call = func else: raise ValueError('condition argument to _replaceIf requires a bool, not {}'.format(repr(condition))) @wraps(func) def wrapped(*args, **kwargs): return call(*args, **kwargs) return wrapped return decorator
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if c{condition} .
train
false