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def reset_worker_optimizations(): global trace_task_ret trace_task_ret = _trace_task_ret try: delattr(BaseTask, u'_stackprotected') except AttributeError: pass try: BaseTask.__call__ = _patched.pop(u'BaseTask.__call__') except KeyError: pass from celery.worker import request as request_module request_module.trace_task_ret = _trace_task_ret
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reset previously configured optimizations .
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def nopackage(pkg_name): if is_installed(pkg_name): uninstall(pkg_name)
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require an rpm package to be uninstalled .
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false
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def fetch_requirements(requirements_file_path): links = [] reqs = [] for req in parse_requirements(requirements_file_path, session=False): if req.link: links.append(str(req.link)) reqs.append(str(req.req)) return (reqs, links)
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return a list of requirements and links by parsing the provided requirements file .
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false
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def concatenate3(arrays): arrays = concrete(arrays) ndim = ndimlist(arrays) if (not ndim): return arrays if (not arrays): return np.empty(0) chunks = chunks_from_arrays(arrays) shape = tuple(map(sum, chunks)) def dtype(x): try: return x.dtype except AttributeError: return type(x) result = np.empty(shape=shape, dtype=dtype(deepfirst(arrays))) for (idx, arr) in zip(slices_from_chunks(chunks), core.flatten(arrays)): if hasattr(arr, 'ndim'): while (arr.ndim < ndim): arr = arr[None, ...] result[idx] = arr return result
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recursive np .
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def find_file(path, saltenv='base', **kwargs): if ('env' in kwargs): salt.utils.warn_until('Oxygen', "Parameter 'env' has been detected in the argument list. This parameter is no longer used and has been replaced by 'saltenv' as of Salt 2016.11.0. This warning will be removed in Salt Oxygen.") kwargs.pop('env') path = os.path.normpath(path) fnd = {'path': '', 'rel': ''} if os.path.isabs(path): return fnd if (saltenv not in __opts__['file_roots']): return fnd def _add_file_stat(fnd): '\n Stat the file and, assuming no errors were found, convert the stat\n result to a list of values and add to the return dict.\n\n Converting the stat result to a list, the elements of the list\n correspond to the following stat_result params:\n\n 0 => st_mode=33188\n 1 => st_ino=10227377\n 2 => st_dev=65026\n 3 => st_nlink=1\n 4 => st_uid=1000\n 5 => st_gid=1000\n 6 => st_size=1056233\n 7 => st_atime=1468284229\n 8 => st_mtime=1456338235\n 9 => st_ctime=1456338235\n ' try: fnd['stat'] = list(os.stat(fnd['path'])) except Exception: pass return fnd if ('index' in kwargs): try: root = __opts__['file_roots'][saltenv][int(kwargs['index'])] except IndexError: return fnd except ValueError: return fnd full = os.path.join(root, path) if (os.path.isfile(full) and (not salt.fileserver.is_file_ignored(__opts__, full))): fnd['path'] = full fnd['rel'] = path return _add_file_stat(fnd) return fnd for root in __opts__['file_roots'][saltenv]: full = os.path.join(root, path) if (os.path.isfile(full) and (not salt.fileserver.is_file_ignored(__opts__, full))): fnd['path'] = full fnd['rel'] = path return _add_file_stat(fnd) return fnd
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recursively find matching file from the current working path .
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def start_version(module, version): rpc = start_version_async(module, version) rpc.get_result()
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start all instances for the given version of the module .
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def _is_national_number_suffix_of_other(numobj1, numobj2): nn1 = str(numobj1.national_number) nn2 = str(numobj2.national_number) return (nn1.endswith(nn2) or nn2.endswith(nn1))
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returns true when one national number is the suffix of the other or both are the same .
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def rotation_angles(m): x = np.arctan2(m[(2, 1)], m[(2, 2)]) c2 = np.sqrt(((m[(0, 0)] ** 2) + (m[(1, 0)] ** 2))) y = np.arctan2((- m[(2, 0)]), c2) s1 = np.sin(x) c1 = np.cos(x) z = np.arctan2(((s1 * m[(0, 2)]) - (c1 * m[(0, 1)])), ((c1 * m[(1, 1)]) - (s1 * m[(1, 2)]))) return (x, y, z)
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find rotation angles from a transformation matrix .
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def _jobs(): response = salt.utils.http.query('{0}/scheduler/jobs'.format(_base_url()), decode_type='json', decode=True) jobs = {} for job in response['dict']: jobs[job.pop('name')] = job return jobs
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return the currently configured jobs .
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true
17,664
def get_next_url_for_login_page(request): redirect_to = request.GET.get('next', None) if (redirect_to and (not http.is_safe_url(redirect_to))): log.error(u'Unsafe redirect parameter detected: %(redirect_to)r', {'redirect_to': redirect_to}) redirect_to = None if (not redirect_to): try: redirect_to = reverse('dashboard') except NoReverseMatch: redirect_to = reverse('home') if any(((param in request.GET) for param in POST_AUTH_PARAMS)): params = [(param, request.GET[param]) for param in POST_AUTH_PARAMS if (param in request.GET)] params.append(('next', redirect_to)) redirect_to = '{}?{}'.format(reverse('finish_auth'), urllib.urlencode(params)) return redirect_to
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determine the url to redirect to following login/registration/third_party_auth the user is currently on a login or registration page .
train
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def cycle_list(k, n): k = (k % n) return (list(range(k, n)) + list(range(k)))
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returns the elements of the list range(n) shifted to the left by k (so the list starts with k ) .
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def jssafe(text=u''): if (text.__class__ != unicode): text = _force_unicode(text) return _Unsafe(text.translate(_js_escapes))
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prevents text from breaking outside of string literals in js .
train
false
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def action_event_start(context, values): return IMPL.action_event_start(context, values)
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start an event on an instance action .
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def check_regexs(filename, matchers): extras = [] for expressions in matchers: (expression, extramatchers) = expressions match1 = expression.search(filename) if match1: for m in extramatchers: match2 = m.findall(filename, match1.end()) if match2: for match in match2: if ((type(match) == type(())) and (len(match) > 1)): extras.append(match[1]) else: extras.append(match) break return (match1, extras) return (None, None)
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regular expression match for a list of regexes returns the matchobject if a match is made this version checks for an additional match .
train
false
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def prefix_indexes(config): if hasattr(config, 'slaveinput'): prefix = 'test_{[slaveid]}'.format(config.slaveinput) else: prefix = 'test' for (key, index) in settings.ES_INDEXES.items(): if (not index.startswith(prefix)): settings.ES_INDEXES[key] = '{prefix}_amo_{index}'.format(prefix=prefix, index=index) settings.CACHE_PREFIX = 'amo:{0}:'.format(prefix) settings.KEY_PREFIX = settings.CACHE_PREFIX
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prefix all es index names and cache keys with test_ and .
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@docfiller def whosmat(file_name, appendmat=True, **kwargs): ML = mat_reader_factory(file_name, **kwargs) variables = ML.list_variables() if isinstance(file_name, string_types): ML.mat_stream.close() return variables
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list variables inside a matlab file .
train
false
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def get_code2lang_map(lang_code=None, force=False): global CODE2LANG_MAP if (force or (not CODE2LANG_MAP)): lmap = softload_json(settings.LANG_LOOKUP_FILEPATH, logger=logging.debug) CODE2LANG_MAP = {} for (lc, entry) in lmap.iteritems(): CODE2LANG_MAP[lcode_to_ietf(lc)] = entry return (CODE2LANG_MAP.get(lcode_to_ietf(lang_code)) if lang_code else CODE2LANG_MAP)
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given a language code .
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def getNewRepository(): return ExportRepository()
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get new repository .
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def flattenString(request, root): io = StringIO() d = flatten(request, root, io.write) d.addCallback((lambda _: io.getvalue())) return d
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collate a string representation of c{root} into a single string .
train
false
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def adjusted_mutual_info_score(labels_true, labels_pred): (labels_true, labels_pred) = check_clusterings(labels_true, labels_pred) n_samples = labels_true.shape[0] classes = np.unique(labels_true) clusters = np.unique(labels_pred) if ((classes.shape[0] == clusters.shape[0] == 1) or (classes.shape[0] == clusters.shape[0] == 0)): return 1.0 contingency = contingency_matrix(labels_true, labels_pred, sparse=True) contingency = contingency.astype(np.float64) mi = mutual_info_score(labels_true, labels_pred, contingency=contingency) emi = expected_mutual_information(contingency, n_samples) (h_true, h_pred) = (entropy(labels_true), entropy(labels_pred)) ami = ((mi - emi) / (max(h_true, h_pred) - emi)) return ami
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adjusted mutual information between two clusterings .
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false
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def replace_nonprintables(string): new_string = '' modified = 0 for c in string: o = ord(c) if (o <= 31): new_string += ('^' + chr((ord('@') + o))) modified += 1 elif (o == 127): new_string += '^?' modified += 1 else: new_string += c if (modified and (S3.Config.Config().urlencoding_mode != 'fixbucket')): warning(('%d non-printable characters replaced in: %s' % (modified, new_string))) return new_string
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replace_nonprintables replaces all non-printable characters ch in string where ord <= 26 with ^@ .
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def handle_sigint(signal, frame): for thread in threading.enumerate(): if thread.isAlive(): thread._Thread__stop() sys.exit(0)
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attempt to kill all child threads and exit .
train
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def strategy_connected_sequential_dfs(G, colors): return strategy_connected_sequential(G, colors, 'dfs')
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returns an iterable over nodes in g in the order given by a depth-first traversal .
train
false
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def mod_run_check_cmd(cmd, filename, **check_cmd_opts): log.debug('running our check_cmd') _cmd = '{0} {1}'.format(cmd, filename) cret = __salt__['cmd.run_all'](_cmd, **check_cmd_opts) if (cret['retcode'] != 0): ret = {'comment': 'check_cmd execution failed', 'skip_watch': True, 'result': False} if cret.get('stdout'): ret['comment'] += ('\n' + cret['stdout']) if cret.get('stderr'): ret['comment'] += ('\n' + cret['stderr']) return ret return True
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execute the check_cmd logic .
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def pre_upgrade(name): if (name not in _tracker['pre_upgrade']): return False return _tracker['pre_upgrade'][name]
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check if a package is about to be upgraded (in plugin_unloaded()) .
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def send_commit(): return s3db.req_send_commit()
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send a shipment containing all items in a commitment .
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def sql_destroy_indexes(app, style, connection): output = [] for model in models.get_models(app, include_auto_created=True): output.extend(connection.creation.sql_destroy_indexes_for_model(model, style)) return output
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returns a list of the drop index sql statements for all models in the given app .
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@real_memoize def is_freebsd(): return sys.platform.startswith('freebsd')
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simple function to return if host is freebsd or not .
train
false
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def to_dict_of_dicts(G, nodelist=None, edge_data=None): dod = {} if (nodelist is None): if (edge_data is None): for (u, nbrdict) in G.adjacency(): dod[u] = nbrdict.copy() else: for (u, nbrdict) in G.adjacency(): dod[u] = dod.fromkeys(nbrdict, edge_data) elif (edge_data is None): for u in nodelist: dod[u] = {} for (v, data) in ((v, data) for (v, data) in G[u].items() if (v in nodelist)): dod[u][v] = data else: for u in nodelist: dod[u] = {} for v in (v for v in G[u] if (v in nodelist)): dod[u][v] = edge_data return dod
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return adjacency representation of graph as a dictionary of dictionaries .
train
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def group_connections(connections): grouped_conns = defaultdict(list) if isinstance(connections, QuerySet): languages = connections.values_list('contact__language', flat=True) for language in languages.distinct(): lang_conns = connections.filter(contact__language=language) grouped_conns[language].extend(lang_conns) else: for connection in connections: language = connection.contact.language grouped_conns[language].append(connection) for (lang, conns) in grouped_conns.items(): (yield (lang, conns))
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return a list of pairs .
train
false
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def unique_window(iterable, window, key=None): seen = collections.deque(maxlen=window) seen_add = seen.append if (key is None): for element in iterable: if (element not in seen): (yield element) seen_add(element) else: for element in iterable: k = key(element) if (k not in seen): (yield element) seen_add(k)
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unique_everseen -> iterator get unique elements .
train
false
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@should_dump_processes def start_process_dump(): dump_data_every_thread(dump_processes, DELAY_MINUTES, SAVE_PROCESS_PTR)
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if the environment variable w3af_processes is set to 1 .
train
false
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def _stream_encoding(stream, default='utf-8'): encoding = config['terminal_encoding'].get() if encoding: return encoding if (not hasattr(stream, 'encoding')): return default return (stream.encoding or default)
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a helper for _in_encoding and _out_encoding: get the streams preferred encoding .
train
false
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def bw_usage_get_by_uuids(context, uuids, start_period): return IMPL.bw_usage_get_by_uuids(context, uuids, start_period)
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return bw usages for instance(s) in a given audit period .
train
false
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def block_device_mapping_update(context, bdm_id, values, legacy=True): return IMPL.block_device_mapping_update(context, bdm_id, values, legacy)
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update an entry of block device mapping .
train
false
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@check_login_required @check_local_site_access def download_orig_file(*args, **kwargs): return _download_diff_file(False, *args, **kwargs)
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downloads an original file from a diff .
train
false
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def scalar_potential(field, frame): if (not is_conservative(field)): raise ValueError('Field is not conservative') if (field == Vector(0)): return S(0) _check_frame(frame) field = express(field, frame, variables=True) dimensions = [x for x in frame] temp_function = integrate(field.dot(dimensions[0]), frame[0]) for (i, dim) in enumerate(dimensions[1:]): partial_diff = diff(temp_function, frame[(i + 1)]) partial_diff = (field.dot(dim) - partial_diff) temp_function += integrate(partial_diff, frame[(i + 1)]) return temp_function
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returns the scalar potential function of a field in a given coordinate system .
train
false
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def gaussian_nll(x, mean, ln_var): assert isinstance(x, variable.Variable) assert isinstance(mean, variable.Variable) assert isinstance(ln_var, variable.Variable) D = x.size x_prec = exponential.exp((- ln_var)) x_diff = (x - mean) x_power = (((x_diff * x_diff) * x_prec) * (-0.5)) return (((sum.sum(ln_var) + (D * math.log((2 * math.pi)))) / 2) - sum.sum(x_power))
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computes the negative log-likelihood of a gaussian distribution .
train
false
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def set_current_comp(info, comp): comp_now = get_current_comp(info) for (k, chan) in enumerate(info['chs']): if (chan['kind'] == FIFF.FIFFV_MEG_CH): rem = (chan['coil_type'] - (comp_now << 16)) chan['coil_type'] = int((rem + (comp << 16)))
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set the current compensation in effect in the data .
train
false
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def save_to_db(item, msg='Saved to db', print_error=True): try: logging.info(msg) db.session.add(item) logging.info('added to session') db.session.commit() return True except Exception as e: if print_error: print e traceback.print_exc() logging.error(('DB Exception! %s' % e)) db.session.rollback() return False
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convenience function to wrap a proper db save .
train
false
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def nice_size(size, include_bytes=False): niced = False nice_string = ('%s bytes' % size) try: nsize = Decimal(size) for x in ['bytes', 'KB', 'MB', 'GB']: if (nsize.compare(Decimal('1024.0')) == Decimal('-1')): nice_string = ('%3.1f %s' % (nsize, x)) niced = True break nsize /= Decimal('1024.0') if (not niced): nice_string = ('%3.1f %s' % (nsize, 'TB')) niced = True if (include_bytes and (x != 'bytes')): nice_string = ('%s (%s bytes)' % (nice_string, size)) except: pass return nice_string
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returns a readably formatted string with the size .
train
false
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def is_position_inf(pos1, pos2): return (pos1 < pos2)
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return true is pos1 < pos2 .
train
false
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def load_tile_features(lock, host, port, path_fmt, tiles, features): while True: try: tile = tiles.pop() except IndexError: break conn = HTTPConnection(host, port) head = {'Accept-Encoding': 'gzip'} path = (path_fmt % tile) conn.request('GET', path, headers=head) resp = conn.getresponse() file = StringIO(resp.read()) if (resp.getheader('Content-Encoding') == 'gzip'): file = GzipFile(fileobj=file, mode='r') with lock: mime_type = resp.getheader('Content-Type') if (mime_type in ('text/json', 'application/json')): file_features = geojson.decode(file) elif (mime_type == 'application/octet-stream+mvt'): file_features = mvt.decode(file) else: logging.error(('Unknown MIME-Type "%s" from %s:%d%s' % (mime_type, host, port, path))) return logging.debug(('%d features in %s:%d%s' % (len(file_features), host, port, path))) features.extend(file_features)
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load data from tiles to features .
train
false
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def dmp_rr_lcm(f, g, u, K): (fc, f) = dmp_ground_primitive(f, u, K) (gc, g) = dmp_ground_primitive(g, u, K) c = K.lcm(fc, gc) h = dmp_quo(dmp_mul(f, g, u, K), dmp_gcd(f, g, u, K), u, K) return dmp_mul_ground(h, c, u, K)
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computes polynomial lcm over a ring in k[x] .
train
false
17,716
def makeopts_contains(value): return var_contains('MAKEOPTS', value)
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verify if makeopts variable contains a value in make .
train
false
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def text_filter(regex_base, value): regex = (regex_base % {u're_cap': u'[a-zA-Z0-9\\.\\,:;/_ \\(\\)\\-\\!\\?"]+', u're_img': u'[a-zA-Z0-9\\.:/_\\-\\% ]+'}) images = re.findall(regex, value) for i in images: image = i[1] if image.startswith(settings.MEDIA_URL): image = image[len(settings.MEDIA_URL):] im = get_thumbnail(image, str(sorl_settings.THUMBNAIL_FILTER_WIDTH)) value = value.replace(i[1], im.url) return value
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helper method to regex replace images with captions in different markups .
train
false
17,718
def text_blocks_to_pandas(reader, block_lists, header, head, kwargs, collection=True, enforce=False): dtypes = head.dtypes.to_dict() columns = list(head.columns) delayed_pandas_read_text = delayed(pandas_read_text) dfs = [] for blocks in block_lists: if (not blocks): continue df = delayed_pandas_read_text(reader, blocks[0], header, kwargs, dtypes, columns, write_header=False, enforce=enforce) dfs.append(df) for b in blocks[1:]: dfs.append(delayed_pandas_read_text(reader, b, header, kwargs, dtypes, columns, enforce=enforce)) if collection: head = clear_known_categories(head) return from_delayed(dfs, head) else: return dfs
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convert blocks of bytes to a dask .
train
false
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def database(dburl=None, **params): dbn = params.pop('dbn') if (dbn in _databases): return _databases[dbn](**params) else: raise UnknownDB, dbn
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database setup .
train
false
17,720
@login_required @require_POST @xframe_options_sameorigin def upload_async(request, media_type='image'): try: if (media_type == 'image'): file_info = upload_image(request) else: msg = _(u'Unrecognized media type.') return HttpResponseBadRequest(json.dumps({'status': 'error', 'message': msg})) except FileTooLargeError as e: return HttpResponseBadRequest(json.dumps({'status': 'error', 'message': e.args[0]})) if (isinstance(file_info, dict) and ('thumbnail_url' in file_info)): schedule_rebuild_kb() return HttpResponse(json.dumps({'status': 'success', 'file': file_info})) message = _(u'Could not upload your image.') return HttpResponseBadRequest(json.dumps({'status': 'error', 'message': unicode(message), 'errors': file_info}))
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upload images or videos from request .
train
false
17,722
def set_enabled_units(units): context = _UnitContext(equivalencies=get_current_unit_registry().equivalencies) get_current_unit_registry().set_enabled_units(units) return context
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sets the units enabled in the unit registry .
train
false
17,725
def circmean(samples, high=(2 * pi), low=0, axis=None): (samples, ang) = _circfuncs_common(samples, high, low) S = sin(ang).sum(axis=axis) C = cos(ang).sum(axis=axis) res = arctan2(S, C) mask = (res < 0) if (mask.ndim > 0): res[mask] += (2 * pi) elif mask: res += (2 * pi) return ((((res * (high - low)) / 2.0) / pi) + low)
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computes the circular mean angle of an array of circular data .
train
false
17,726
def delete_thumbnails(relative_source_path, root=None, basedir=None, subdir=None, prefix=None): thumbs = thumbnails_for_file(relative_source_path, root, basedir, subdir, prefix) return _delete_using_thumbs_list(thumbs)
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delete all thumbnails for a source image .
train
true
17,727
def map_dict_keys(dict_, key_map): mapped = {} for (key, value) in dict_.iteritems(): mapped_key = (key_map[key] if (key in key_map) else key) mapped[mapped_key] = value return mapped
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return a dict in which the dictionaries keys are mapped to new keys .
train
false
17,729
def generate_names(): adjectives = ['Exquisite', 'Delicious', 'Elegant', 'Swanky', 'Spicy', 'Food Truck', 'Artisanal', 'Tasty'] nouns = ['Sandwich', 'Pizza', 'Curry', 'Pierogi', 'Sushi', 'Salad', 'Stew', 'Pasta', 'Barbeque', 'Bacon', 'Pancake', 'Waffle', 'Chocolate', 'Gyro', 'Cookie', 'Burrito', 'Pie'] return [' '.join(parts) for parts in product(adjectives, nouns)]
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generate a list of random adjective + noun strings .
train
false
17,730
def linkify(text, nofollow=True, target=None, filter_url=identity, filter_text=identity, skip_pre=False, parse_email=False, tokenizer=HTMLSanitizer): text = force_unicode(text) if (not text): return u'' parser = html5lib.HTMLParser(tokenizer=tokenizer) forest = parser.parseFragment(text) if nofollow: rel = u'rel="nofollow"' else: rel = u'' def replace_nodes(tree, new_frag, node): new_tree = parser.parseFragment(new_frag) for n in new_tree.childNodes: tree.insertBefore(n, node) tree.removeChild(node) def strip_wrapping_parentheses(fragment): 'Strips wrapping parentheses.\n\n Returns a tuple of the following format::\n\n (string stripped from wrapping parentheses,\n count of stripped opening parentheses,\n count of stripped closing parentheses)\n ' opening_parentheses = closing_parentheses = 0 for char in fragment: if (char == '('): opening_parentheses += 1 else: break if opening_parentheses: newer_frag = '' fragment = fragment[opening_parentheses:] reverse_fragment = fragment[::(-1)] skip = False for char in reverse_fragment: if ((char == ')') and (closing_parentheses < opening_parentheses) and (not skip)): closing_parentheses += 1 continue elif (char != ')'): skip = True newer_frag += char fragment = newer_frag[::(-1)] return (fragment, opening_parentheses, closing_parentheses) def linkify_nodes(tree, parse_text=True): for node in tree.childNodes: if ((node.type == NODE_TEXT) and parse_text): new_frag = node.toxml() if parse_email: new_frag = re.sub(email_re, email_repl, new_frag) if (new_frag != node.toxml()): replace_nodes(tree, new_frag, node) linkify_nodes(tree) continue new_frag = re.sub(url_re, link_repl, new_frag) replace_nodes(tree, new_frag, node) elif (node.name == 'a'): if ('href' in node.attributes): if nofollow: node.attributes['rel'] = 'nofollow' if (target is not None): node.attributes['target'] = target href = node.attributes['href'] node.attributes['href'] = filter_url(href) elif (skip_pre and (node.name == 'pre')): linkify_nodes(node, False) else: linkify_nodes(node) def email_repl(match): repl = u'<a href="mailto:%(mail)s">%(mail)s</a>' return (repl % {'mail': match.group(0).replace('"', '&quot;')}) def link_repl(match): url = match.group(0) open_brackets = close_brackets = 0 if url.startswith('('): (url, open_brackets, close_brackets) = strip_wrapping_parentheses(url) end = u'' m = re.search(punct_re, url) if m: end = m.group(0) url = url[0:m.start()] if re.search(proto_re, url): href = url else: href = u''.join([u'http://', url]) repl = u'%s<a href="%s" %s>%s</a>%s%s' attribs = [rel] if (target is not None): attribs.append(('target="%s"' % target)) return (repl % (('(' * open_brackets), filter_url(href), ' '.join(attribs), filter_text(url), end, (')' * close_brackets))) linkify_nodes(forest) return _render(forest)
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adds the documentation site root to doc paths .
train
false
17,731
def accept_key(pki_dir, pub, id_): for key_dir in ('minions', 'minions_pre', 'minions_rejected'): key_path = os.path.join(pki_dir, key_dir) if (not os.path.exists(key_path)): os.makedirs(key_path) key = os.path.join(pki_dir, 'minions', id_) with salt.utils.fopen(key, 'w+') as fp_: fp_.write(pub) oldkey = os.path.join(pki_dir, 'minions_pre', id_) if os.path.isfile(oldkey): with salt.utils.fopen(oldkey) as fp_: if (fp_.read() == pub): os.remove(oldkey)
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if the master config was available then we will have a pki_dir key in the opts directory .
train
true
17,732
def worker_edit(worker, lbn, settings, profile='default'): settings['cmd'] = 'update' settings['mime'] = 'prop' settings['w'] = lbn settings['sw'] = worker return (_do_http(settings, profile)['worker.result.type'] == 'OK')
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edit the worker settings note: URL data parameters for the standard update action cli examples: .
train
true
17,733
def write_request_load_scenario(reactor, cluster, request_rate=10, sample_size=DEFAULT_SAMPLE_SIZE, timeout=45, tolerance_percentage=0.2): return RequestLoadScenario(reactor, WriteRequest(reactor, cluster.get_control_service(reactor)), request_rate=request_rate, sample_size=sample_size, timeout=timeout, tolerance_percentage=tolerance_percentage)
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factory that will initialise and return a scenario that places load on the cluster by performing write requests at a specified rate .
train
false
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def check_key_path_and_mode(provider, key_path): if (not os.path.exists(key_path)): log.error("The key file '{0}' used in the '{1}' provider configuration does not exist.\n".format(key_path, provider)) return False key_mode = str(oct(stat.S_IMODE(os.stat(key_path).st_mode))) if (key_mode not in ('0400', '0600')): log.error("The key file '{0}' used in the '{1}' provider configuration needs to be set to mode 0400 or 0600.\n".format(key_path, provider)) return False return True
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checks that the key_path exists and the key_mode is either 0400 or 0600 .
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def math_to_image(s, filename_or_obj, prop=None, dpi=None, format=None): from matplotlib import figure from matplotlib.backends import backend_agg if (prop is None): prop = FontProperties() parser = MathTextParser(u'path') (width, height, depth, _, _) = parser.parse(s, dpi=72, prop=prop) fig = figure.Figure(figsize=((width / 72.0), (height / 72.0))) fig.text(0, (depth / height), s, fontproperties=prop) backend_agg.FigureCanvasAgg(fig) fig.savefig(filename_or_obj, dpi=dpi, format=format) return depth
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given a math expression .
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def assert_array_index_eq(left, right): assert_eq(left, (pd.Index(right) if isinstance(right, np.ndarray) else right))
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left and right are equal .
train
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@default_selem def erosion(image, selem=None, out=None, shift_x=False, shift_y=False): selem = np.array(selem) selem = _shift_selem(selem, shift_x, shift_y) if (out is None): out = np.empty_like(image) ndi.grey_erosion(image, footprint=selem, output=out) return out
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return greyscale morphological erosion of an image .
train
false
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def job_get_by_id(job_id): try: job = Job.objects.get(pk=job_id) return job except Job.DoesNotExist: return None
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return a job based on its id .
train
false
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def read_uint16(fid): return _unpack_simple(fid, '>u2', np.uint16)
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read unsigned 16bit integer from bti file .
train
false
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def on_create(connection): def on_connect(session): session.on_join(on_join) session.join(u'public') connection.on_connect(on_connect)
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this is the main entry into user code .
train
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def iterate_base4(d): return product(xrange(4), repeat=d)
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iterates over a base 4 number with d digits .
train
false
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def sync_ldap_groups(connection, failed_users=None): groups = Group.objects.filter(group__in=LdapGroup.objects.all()) for group in groups: _import_ldap_groups(connection, group.name, failed_users=failed_users) return groups
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syncs ldap group memberships .
train
false
17,748
def volume_create(**kwargs): return create_volume(kwargs, 'function')
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create a volume from the values dictionary .
train
false
17,749
def logistic(x, A, u, d, v, y0): y = ((A / (1 + np.exp(((((4 * u) / A) * (d - x)) + 2)))) + y0) return y
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logistic growth model proposed in zwietering et al .
train
false
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def grep(pattern, items, squash=True): isdict = (type(items) is dict) if (pattern in __grep_cache): regex = __grep_cache[pattern] else: regex = __grep_cache[pattern] = re.compile(pattern) matched = [] matchdict = {} for item in items: match = regex.match(item) if (not match): continue groups = match.groups() if (not groups): subitems = match.group(0) elif (len(groups) == 1): subitems = groups[0] else: subitems = list(groups) if isdict: matchdict[item] = items[item] else: matched.append(subitems) if isdict: return matchdict elif (squash and (len(matched) == 1)): return matched[0] else: return matched
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search for ports using a regular expression .
train
false
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@inspect_command(alias=u'dump_revoked') def revoked(state, **kwargs): return list(worker_state.revoked)
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list of revoked task-ids .
train
false
17,753
def upcast_char(*args): t = _upcast_memo.get(args) if (t is not None): return t t = upcast(*map(np.dtype, args)) _upcast_memo[args] = t return t
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same as upcast but taking dtype .
train
false
17,755
def _load_and_process_metadata(captions_file, image_dir): with tf.gfile.FastGFile(captions_file, 'r') as f: caption_data = json.load(f) id_to_filename = [(x['id'], x['file_name']) for x in caption_data['images']] id_to_captions = {} for annotation in caption_data['annotations']: image_id = annotation['image_id'] caption = annotation['caption'] id_to_captions.setdefault(image_id, []) id_to_captions[image_id].append(caption) assert (len(id_to_filename) == len(id_to_captions)) assert (set([x[0] for x in id_to_filename]) == set(id_to_captions.keys())) print(('Loaded caption metadata for %d images from %s' % (len(id_to_filename), captions_file))) print('Proccessing captions.') image_metadata = [] num_captions = 0 for (image_id, base_filename) in id_to_filename: filename = os.path.join(image_dir, base_filename) captions = [_process_caption(c) for c in id_to_captions[image_id]] image_metadata.append(ImageMetadata(image_id, filename, captions)) num_captions += len(captions) print(('Finished processing %d captions for %d images in %s' % (num_captions, len(id_to_filename), captions_file))) return image_metadata
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loads image metadata from a json file and processes the captions .
train
false
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def cluster_quorum(**kwargs): return ceph_cfg.cluster_quorum(**kwargs)
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get the clusters quorum status cli example: .
train
false
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def regexp_extract(pattern, method=re.match, group=1): def regexp_extract_lambda(value): if (not value): return None matches = method(pattern, value) if (not matches): return None return matches.group(group) return regexp_extract_lambda
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return first group in the value matching the pattern using re .
train
false
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def _ParseInputSpec(input_spec): pattern = re.compile('(\\d+),(\\d+),(\\d+),(\\d+)') m = pattern.match(input_spec) if (m is None): raise ValueError(('Failed to parse input spec:' + input_spec)) batch_size = int(m.group(1)) y_size = (int(m.group(2)) if (int(m.group(2)) > 0) else None) x_size = (int(m.group(3)) if (int(m.group(3)) > 0) else None) depth = int(m.group(4)) if (depth not in [1, 3]): raise ValueError('Depth must be 1 or 3, had:', depth) return vgsl_input.ImageShape(batch_size, y_size, x_size, depth)
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parses input_spec and returns the numbers obtained therefrom .
train
false
17,760
def send_request(url, method='GET', headers=None, param_get=None, data=None): final_hostname = urlsplit(url).netloc dbgprint('FinalRequestUrl', url, 'FinalHostname', final_hostname) if ((final_hostname not in allowed_domains_set) and (not developer_temporary_disable_ssrf_prevention)): raise ConnectionAbortedError('Trying to access an OUT-OF-ZONE domain(SSRF Layer 2):', final_hostname) if (not data): data = None prepped_req = requests.Request(method, url, headers=headers, params=param_get, data=data).prepare() if enable_connection_keep_alive: _session = connection_pool.get_session(final_hostname) else: _session = requests.Session() parse.time['req_start_time'] = time() r = _session.send(prepped_req, proxies=requests_proxies, allow_redirects=False, stream=enable_stream_content_transfer, verify=(not developer_do_not_verify_ssl)) parse.time['req_time_header'] = (time() - parse.time['req_start_time']) dbgprint('RequestTime:', parse.time['req_time_header'], v=4) if (verbose_level >= 3): dbgprint(r.request.method, 'FinalSentToRemoteRequestUrl:', r.url, '\nRem Resp Stat: ', r.status_code) dbgprint('RemoteRequestHeaders: ', r.request.headers) if data: dbgprint('RemoteRequestRawData: ', r.request.body) dbgprint('RemoteResponseHeaders: ', r.headers) return r
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sends a request to notes api with appropriate parameters and headers .
train
false
17,761
def force_header_for_response(response, header, value): force_headers = {} if hasattr(response, 'force_headers'): force_headers = response.force_headers force_headers[header] = value response.force_headers = force_headers
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forces the given header for the given response using the header_control middleware .
train
false
17,762
def getComplexByDictionaryListValue(value, valueComplex): if (value.__class__ == complex): return value if (value.__class__ == dict): return getComplexByDictionary(value, valueComplex) if (value.__class__ == list): return getComplexByFloatList(value, valueComplex) floatFromValue = euclidean.getFloatFromValue(value) if (floatFromValue == None): return valueComplex return complex(floatFromValue, floatFromValue)
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get complex by dictionary .
train
false
17,763
def _GetKeyKind(key): return key.path().element_list()[(-1)].type()
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return the kind of the given key .
train
false
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def set_stubs(test): test.stub_out('nova.virt.vmwareapi.network_util.get_network_with_the_name', fake.fake_get_network) test.stub_out('nova.virt.vmwareapi.images.upload_image_stream_optimized', fake.fake_upload_image) test.stub_out('nova.virt.vmwareapi.images.fetch_image', fake.fake_fetch_image) test.stub_out('nova.virt.vmwareapi.driver.VMwareAPISession.vim', fake_vim_prop) test.stub_out('nova.virt.vmwareapi.driver.VMwareAPISession._is_vim_object', fake_is_vim_object) if CONF.use_neutron: test.stub_out('nova.network.neutronv2.api.API.update_instance_vnic_index', (lambda *args, **kwargs: None))
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set the stubs .
train
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def _write_mri_config(fname, subject_from, subject_to, scale): scale = np.asarray(scale) if (np.isscalar(scale) or (scale.shape == ())): n_params = 1 else: n_params = 3 config = configparser.RawConfigParser() config.add_section('MRI Scaling') config.set('MRI Scaling', 'subject_from', subject_from) config.set('MRI Scaling', 'subject_to', subject_to) config.set('MRI Scaling', 'n_params', str(n_params)) if (n_params == 1): config.set('MRI Scaling', 'scale', str(scale)) else: config.set('MRI Scaling', 'scale', ' '.join([str(s) for s in scale])) config.set('MRI Scaling', 'version', '1') with open(fname, 'w') as fid: config.write(fid)
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write the cfg file describing a scaled mri subject .
train
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@needs('pavelib.prereqs.install_prereqs', 'pavelib.utils.test.utils.clean_reports_dir') @cmdopts([('failed', 'f', 'Run only failed tests'), ('fail-fast', 'x', 'Run only failed tests'), make_option('-c', '--cov-args', default='', help='adds as args to coverage for the test run'), make_option('--verbose', action='store_const', const=2, dest='verbosity'), make_option('-q', '--quiet', action='store_const', const=0, dest='verbosity'), make_option('-v', '--verbosity', action='count', dest='verbosity', default=1), make_option('--disable-migrations', action='store_true', dest='disable_migrations', help="Create tables directly from apps' models. Can also be used by exporting DISABLE_MIGRATIONS=1."), ('cov_args=', None, 'deprecated in favor of cov-args'), make_option('-e', '--extra_args', default='', help='deprecated, pass extra options directly in the paver commandline'), ('fail_fast', None, 'deprecated in favor of fail-fast')]) @PassthroughTask @timed def test_python(options, passthrough_options): python_suite = suites.PythonTestSuite('Python Tests', passthrough_options=passthrough_options, **options.test_python) python_suite.run()
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run all python tests .
train
false
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def test_write_noformat_arbitrary(): _identifiers.update(_IDENTIFIERS_ORIGINAL) with pytest.raises(io_registry.IORegistryError) as exc: TestData().write(object()) assert str(exc.value).startswith(u'Format could not be identified.')
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test that all identifier functions can accept arbitrary input .
train
false
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def extras_msg(extras): if (len(extras) == 1): verb = 'was' else: verb = 'were' return (', '.join((repr(extra) for extra in extras)), verb)
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create an error message for extra items or properties .
train
true
17,771
def urepr(value): if isinstance(value, list): return (('[' + ', '.join(map(urepr, value))) + ']') if isinstance(value, unicode): return (('u"' + value.encode('utf-8').replace('"', '\\"').replace('\\', '\\\\')) + '"') return repr(value)
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like repr() .
train
false
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def _ListIndexesResponsePbToGetResponse(response, include_schema): return GetResponse(results=[_NewIndexFromPb(index, include_schema) for index in response.index_metadata_list()])
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returns a getresponse constructed from get_indexes response pb .
train
false
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@csrf_exempt def default_render_failure(request, message, status=403, template_name='extauth_failure.html', exception=None): log.debug(('In openid_failure ' + message)) data = render_to_string(template_name, dict(message=message, exception=exception)) return HttpResponse(data, status=status)
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render an error page to the user .
train
false
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def append_features(value): return append_var('FEATURES', value)
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add to or create a new features in the make .
train
false
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def set_dataset_root(path): global _dataset_root _dataset_root = path
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sets the root directory to download and cache datasets .
train
false
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def decrypt_keyfile(): print('Running in Travis during merge, decrypting stored key file.') encrypted_key = os.getenv(ENCRYPTED_KEY_ENV) encrypted_iv = os.getenv(ENCRYPTED_INIT_VECTOR_ENV) out_file = os.getenv(CREDENTIALS) subprocess.call(['openssl', 'aes-256-cbc', '-K', encrypted_key, '-iv', encrypted_iv, '-in', ENCRYPTED_KEYFILE, '-out', out_file, '-d'])
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decrypt a keyfile .
train
false
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def naf(n): while n: z = ((2 - (n % 4)) if (n & 1) else 0) n = ((n - z) // 2) (yield z)
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naf -> int generator returns a generator for the non-adjacent form of a number .
train
false
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def _get_connection(): global COUCHBASE_CONN if (COUCHBASE_CONN is None): opts = _get_options() if opts['password']: COUCHBASE_CONN = couchbase.Couchbase.connect(host=opts['host'], port=opts['port'], bucket=opts['bucket'], password=opts['password']) else: COUCHBASE_CONN = couchbase.Couchbase.connect(host=opts['host'], port=opts['port'], bucket=opts['bucket']) return COUCHBASE_CONN
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global function to access the couchbase connection .
train
true
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def _compute_host(host, instance): if host: return host if (not instance): raise exception.NovaException(_('No compute host specified')) if (not instance.host): raise exception.NovaException((_('Unable to find host for Instance %s') % instance.uuid)) return instance.host
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get the destination host for a message .
train
false
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def Win32Input(prompt=None): return eval(input(prompt))
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provide input() for gui apps .
train
false
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def utf8_keys(dictionary): return dict([(key.encode('utf8'), val) for (key, val) in dictionary.items()])
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convert dictionary keys to utf8-encoded strings for mapnik .
train
false
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def filter_users_by_email(email): from .models import EmailAddress User = get_user_model() mails = EmailAddress.objects.filter(email__iexact=email) users = [e.user for e in mails.prefetch_related('user')] if app_settings.USER_MODEL_EMAIL_FIELD: q_dict = {(app_settings.USER_MODEL_EMAIL_FIELD + '__iexact'): email} users += list(User.objects.filter(**q_dict)) return list(set(users))
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return list of users by email address typically one .
train
true
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def _param_from_config(key, data): param = {} if isinstance(data, dict): for (k, v) in six.iteritems(data): param.update(_param_from_config('{0}.{1}'.format(key, k), v)) elif (isinstance(data, list) or isinstance(data, tuple)): for (idx, conf_item) in enumerate(data): prefix = '{0}.{1}'.format(key, idx) param.update(_param_from_config(prefix, conf_item)) elif isinstance(data, bool): param.update({key: str(data).lower()}) else: param.update({key: data}) return param
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return ec2 api parameters based on the given config data .
train
true
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def test_singleton(): AreEqual((frozenset([]) is frozenset([])), True) x = frozenset([1, 2, 3]) AreEqual((x is frozenset(x)), True)
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verify that an empty frozenset is a singleton .
train
false
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def getFirstChildElementByTagName(self, tagName): for child in self.childNodes: if isinstance(child, Element): if (child.tagName == tagName): return child return None
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return the first element of type tagname if found .
train
true