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MolSSI-BSE/basis_set_exchange
basis_set_exchange/cli/bse_handlers.py
https://github.com/MolSSI-BSE/basis_set_exchange/blob/e79110aaeb65f392ed5032420322dee3336948f7/basis_set_exchange/cli/bse_handlers.py#L40-L49
def _bse_cli_list_ref_formats(args): '''Handles the list-ref-formats subcommand''' all_refformats = api.get_reference_formats() if args.no_description: liststr = all_refformats.keys() else: liststr = format_columns(all_refformats.items()) return '\n'.join(liststr)
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Handles the list-ref-formats subcommand
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python
train
OSSOS/MOP
src/ossos/core/ossos/astrom.py
https://github.com/OSSOS/MOP/blob/94f91d32ad5ec081d5a1ebd67604a838003465af/src/ossos/core/ossos/astrom.py#L345-L373
def _write_observation_headers(self, observations): """ See src/pipematt/step1matt-c """ for observation in observations: header = observation.header def get_header_vals(header_list): header_vals = [] for key in header_list: val = header[key] if key == MJD_OBS_CENTER: header_vals.append(val) elif key == DETECTOR: header_vals.append(val.ljust(20)) else: header_vals.append(float(val)) return tuple(header_vals) self._write_line("## MOPversion") self._write_line("# %s" % header[MOPVERSION]) self._write_line("## MJD-OBS-CENTER EXPTIME THRES FWHM MAXCOUNT CRVAL1 CRVAL2 EXPNUM") self._write_line("# %s%8.2f%6.2f%6.2f%9.1f%11.5f%11.5f%9d" % get_header_vals( [MJD_OBS_CENTER, EXPTIME, THRES, FWHM, MAXCOUNT, CRVAL1, CRVAL2, EXPNUM])) self._write_line("## SCALE CHIP CRPIX1 CRPIX2 NAX1 NAX2 DETECTOR PHADU RDNOIS") self._write_line("# %6.3f%4d%10.2f%10.2f%6d%6d %s%5.2f %5.2f" % get_header_vals( [SCALE, CHIP, CRPIX1, CRPIX2, NAX1, NAX2, DETECTOR, PHADU, RDNOIS]))
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See src/pipematt/step1matt-c
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python
train
mottosso/be
be/vendor/requests/sessions.py
https://github.com/mottosso/be/blob/0f3d4f3597c71223f616d78c6d9b2c8dffcd8a71/be/vendor/requests/sessions.py#L42-L72
def merge_setting(request_setting, session_setting, dict_class=OrderedDict): """ Determines appropriate setting for a given request, taking into account the explicit setting on that request, and the setting in the session. If a setting is a dictionary, they will be merged together using `dict_class` """ if session_setting is None: return request_setting if request_setting is None: return session_setting # Bypass if not a dictionary (e.g. verify) if not ( isinstance(session_setting, Mapping) and isinstance(request_setting, Mapping) ): return request_setting merged_setting = dict_class(to_key_val_list(session_setting)) merged_setting.update(to_key_val_list(request_setting)) # Remove keys that are set to None. for (k, v) in request_setting.items(): if v is None: del merged_setting[k] merged_setting = dict((k, v) for (k, v) in merged_setting.items() if v is not None) return merged_setting
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Determines appropriate setting for a given request, taking into account the explicit setting on that request, and the setting in the session. If a setting is a dictionary, they will be merged together using `dict_class`
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python
train
eventable/vobject
docs/build/lib/vobject/icalendar.py
https://github.com/eventable/vobject/blob/498555a553155ea9b26aace93332ae79365ecb31/docs/build/lib/vobject/icalendar.py#L802-L822
def transformToNative(obj): """ Turn obj.value into a list of dates, datetimes, or (datetime, timedelta) tuples. """ if obj.isNative: return obj obj.isNative = True if obj.value == '': obj.value = [] return obj tzinfo = getTzid(getattr(obj, 'tzid_param', None)) valueParam = getattr(obj, 'value_param', "DATE-TIME").upper() valTexts = obj.value.split(",") if valueParam == "DATE": obj.value = [stringToDate(x) for x in valTexts] elif valueParam == "DATE-TIME": obj.value = [stringToDateTime(x, tzinfo) for x in valTexts] elif valueParam == "PERIOD": obj.value = [stringToPeriod(x, tzinfo) for x in valTexts] return obj
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Turn obj.value into a list of dates, datetimes, or (datetime, timedelta) tuples.
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python
train
datosgobar/pydatajson
pydatajson/indicators.py
https://github.com/datosgobar/pydatajson/blob/3141082ffbaa295e2deaf6ffbbc5a59f5859960e/pydatajson/indicators.py#L509-L562
def _count_fields_recursive(dataset, fields): """Cuenta la información de campos optativos/recomendados/requeridos desde 'fields', y cuenta la ocurrencia de los mismos en 'dataset'. Args: dataset (dict): diccionario con claves a ser verificadas. fields (dict): diccionario con los campos a verificar en dataset como claves, y 'optativo', 'recomendado', o 'requerido' como valores. Puede tener objetios anidados pero no arrays. Returns: dict: diccionario con las claves 'recomendado', 'optativo', 'requerido', 'recomendado_total', 'optativo_total', 'requerido_total', con la cantidad como valores. """ key_count = { 'recomendado': 0, 'optativo': 0, 'requerido': 0, 'total_optativo': 0, 'total_recomendado': 0, 'total_requerido': 0 } for k, v in fields.items(): # Si la clave es un diccionario se implementa recursivamente el # mismo algoritmo if isinstance(v, dict): # dataset[k] puede ser o un dict o una lista, ej 'dataset' es # list, 'publisher' no. Si no es lista, lo metemos en una. # Si no es ninguno de los dos, dataset[k] es inválido # y se pasa un diccionario vacío para poder comparar elements = dataset.get(k) if not isinstance(elements, (list, dict)): elements = [{}] if isinstance(elements, dict): elements = [dataset[k].copy()] for element in elements: # Llamada recursiva y suma del resultado al nuestro result = _count_fields_recursive(element, v) for key in result: key_count[key] += result[key] # Es un elemento normal (no iterable), se verifica si está en # dataset o no. Se suma 1 siempre al total de su tipo else: # total_requerido, total_recomendado, o total_optativo key_count['total_' + v] += 1 if k in dataset: key_count[v] += 1 return key_count
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python
train
GoogleCloudPlatform/appengine-mapreduce
python/src/mapreduce/output_writers.py
https://github.com/GoogleCloudPlatform/appengine-mapreduce/blob/2045eb3605b6ecb40c83d11dd5442a89fe5c5dd6/python/src/mapreduce/output_writers.py#L504-L509
def _get_tmp_account_id(cls, writer_spec): """Returns the account id to use with tmp bucket.""" # pick tmp id iff tmp bucket is set explicitly if cls.TMP_BUCKET_NAME_PARAM in writer_spec: return writer_spec.get(cls._TMP_ACCOUNT_ID_PARAM, None) return cls._get_account_id(writer_spec)
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Returns the account id to use with tmp bucket.
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python
train
greenelab/django-genes
genes/api.py
https://github.com/greenelab/django-genes/blob/298939adcb115031acfc11cfcef60ea0b596fae5/genes/api.py#L202-L214
def post_list(self, request, **kwargs): """ (Copied from implementation in https://github.com/greenelab/adage-server/blob/master/adage/analyze/api.py) Handle an incoming POST as a GET to work around URI length limitations """ # The convert_post_to_VERB() technique is borrowed from # resources.py in tastypie source. This helps us to convert the POST # to a GET in the proper way internally. request.method = 'GET' # override the incoming POST dispatch_request = convert_post_to_VERB(request, 'GET') return self.dispatch('list', dispatch_request, **kwargs)
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(Copied from implementation in https://github.com/greenelab/adage-server/blob/master/adage/analyze/api.py) Handle an incoming POST as a GET to work around URI length limitations
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python
train
aarongarrett/inspyred
inspyred/swarm/topologies.py
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/swarm/topologies.py#L69-L101
def ring_topology(random, population, args): """Returns the neighbors using a ring topology. This function sets all particles in a specified sized neighborhood as neighbors for a given particle. This is known as a ring topology. The resulting list of lists of neighbors is returned. .. Arguments: random -- the random number generator object population -- the population of particles args -- a dictionary of keyword arguments Optional keyword arguments in args: - *neighborhood_size* -- the width of the neighborhood around a particle which determines the size of the neighborhood (default 3) """ neighborhood_size = args.setdefault('neighborhood_size', 3) half_hood = neighborhood_size // 2 neighbor_index_start = [] for index in range(len(population)): if index < half_hood: neighbor_index_start.append(len(population) - half_hood + index) else: neighbor_index_start.append(index - half_hood) neighbors = [] for start in neighbor_index_start: n = [] for i in range(0, neighborhood_size): n.append(population[(start + i) % len(population)]) yield n
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Returns the neighbors using a ring topology. This function sets all particles in a specified sized neighborhood as neighbors for a given particle. This is known as a ring topology. The resulting list of lists of neighbors is returned. .. Arguments: random -- the random number generator object population -- the population of particles args -- a dictionary of keyword arguments Optional keyword arguments in args: - *neighborhood_size* -- the width of the neighborhood around a particle which determines the size of the neighborhood (default 3)
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python
train
mar10/wsgidav
wsgidav/server/server_cli.py
https://github.com/mar10/wsgidav/blob/cec0d84222fc24bea01be1cea91729001963f172/wsgidav/server/server_cli.py#L715-L730
def _run_wsgiref(app, config, mode): """Run WsgiDAV using wsgiref.simple_server, on Python 2.5+.""" # http://www.python.org/doc/2.5.2/lib/module-wsgiref.html from wsgiref.simple_server import make_server, software_version version = "WsgiDAV/{} {}".format(__version__, software_version) _logger.info("Running {}...".format(version)) _logger.warning( "WARNING: This single threaded server (wsgiref) is not meant for production." ) httpd = make_server(config["host"], config["port"], app) try: httpd.serve_forever() except KeyboardInterrupt: _logger.warning("Caught Ctrl-C, shutting down...") return
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Run WsgiDAV using wsgiref.simple_server, on Python 2.5+.
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python
valid
hazelcast/hazelcast-python-client
hazelcast/proxy/queue.py
https://github.com/hazelcast/hazelcast-python-client/blob/3f6639443c23d6d036aa343f8e094f052250d2c1/hazelcast/proxy/queue.py#L199-L208
def put(self, item): """ Adds the specified element into this queue. If there is no space, it waits until necessary space becomes available. :param item: (object), the specified item. """ check_not_none(item, "Value can't be None") element_data = self._to_data(item) return self._encode_invoke(queue_put_codec, value=element_data)
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Adds the specified element into this queue. If there is no space, it waits until necessary space becomes available. :param item: (object), the specified item.
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python
train
ddorn/GUI
GUI/vracabulous.py
https://github.com/ddorn/GUI/blob/e1fcb5286d24e0995f280d5180222e51895c368c/GUI/vracabulous.py#L251-L265
def update_on_event(self, e): """Process a single event.""" if e.type == QUIT: self.running = False elif e.type == KEYDOWN: if e.key == K_ESCAPE: self.running = False elif e.key == K_F4 and e.mod & KMOD_ALT: # Alt+F4 --> quits self.running = False elif e.type == VIDEORESIZE: self.SCREEN_SIZE = e.size self.screen = self.new_screen()
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Process a single event.
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python
train
quodlibet/mutagen
mutagen/apev2.py
https://github.com/quodlibet/mutagen/blob/e393df5971ba41ba5a50de9c2c9e7e5484d82c4e/mutagen/apev2.py#L427-L485
def save(self, filething=None): """Save changes to a file. If no filename is given, the one most recently loaded is used. Tags are always written at the end of the file, and include a header and a footer. """ fileobj = filething.fileobj data = _APEv2Data(fileobj) if data.is_at_start: delete_bytes(fileobj, data.end - data.start, data.start) elif data.start is not None: fileobj.seek(data.start) # Delete an ID3v1 tag if present, too. fileobj.truncate() fileobj.seek(0, 2) tags = [] for key, value in self.items(): # Packed format for an item: # 4B: Value length # 4B: Value type # Key name # 1B: Null # Key value value_data = value._write() if not isinstance(key, bytes): key = key.encode("utf-8") tag_data = bytearray() tag_data += struct.pack("<2I", len(value_data), value.kind << 1) tag_data += key + b"\0" + value_data tags.append(bytes(tag_data)) # "APE tags items should be sorted ascending by size... This is # not a MUST, but STRONGLY recommended. Actually the items should # be sorted by importance/byte, but this is not feasible." tags.sort(key=lambda tag: (len(tag), tag)) num_tags = len(tags) tags = b"".join(tags) header = bytearray(b"APETAGEX") # version, tag size, item count, flags header += struct.pack("<4I", 2000, len(tags) + 32, num_tags, HAS_HEADER | IS_HEADER) header += b"\0" * 8 fileobj.write(header) fileobj.write(tags) footer = bytearray(b"APETAGEX") footer += struct.pack("<4I", 2000, len(tags) + 32, num_tags, HAS_HEADER) footer += b"\0" * 8 fileobj.write(footer)
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Save changes to a file. If no filename is given, the one most recently loaded is used. Tags are always written at the end of the file, and include a header and a footer.
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python
train
cs50/check50
check50/api.py
https://github.com/cs50/check50/blob/42c1f0c36baa6a24f69742d74551a9ea7a5ceb33/check50/api.py#L67-L86
def hash(file): """ Hashes file using SHA-256. :param file: name of file to be hashed :type file: str :rtype: str :raises check50.Failure: if ``file`` does not exist """ exists(file) log(_("hashing {}...").format(file)) # https://stackoverflow.com/a/22058673 with open(file, "rb") as f: sha256 = hashlib.sha256() for block in iter(lambda: f.read(65536), b""): sha256.update(block) return sha256.hexdigest()
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Hashes file using SHA-256. :param file: name of file to be hashed :type file: str :rtype: str :raises check50.Failure: if ``file`` does not exist
[ "Hashes", "file", "using", "SHA", "-", "256", "." ]
python
train
fossasia/knittingpattern
knittingpattern/Loader.py
https://github.com/fossasia/knittingpattern/blob/8e608896b0ab82fea1ca9fbfa2b4ee023d8c8027/knittingpattern/Loader.py#L198-L211
def url(self, url, encoding="UTF-8"): """load and process the content behind a url :return: the processed result of the :paramref:`url's <url>` content :param str url: the url to retrieve the content from :param str encoding: the encoding of the retrieved content. The default encoding is UTF-8. """ import urllib.request with urllib.request.urlopen(url) as file: webpage_content = file.read() webpage_content = webpage_content.decode(encoding) return self.string(webpage_content)
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load and process the content behind a url :return: the processed result of the :paramref:`url's <url>` content :param str url: the url to retrieve the content from :param str encoding: the encoding of the retrieved content. The default encoding is UTF-8.
[ "load", "and", "process", "the", "content", "behind", "a", "url" ]
python
valid
jonathf/chaospy
chaospy/distributions/sampler/generator.py
https://github.com/jonathf/chaospy/blob/25ecfa7bf5608dc10c0b31d142ded0e3755f5d74/chaospy/distributions/sampler/generator.py#L76-L139
def generate_samples(order, domain=1, rule="R", antithetic=None): """ Sample generator. Args: order (int): Sample order. Determines the number of samples to create. domain (Dist, int, numpy.ndarray): Defines the space where the samples are generated. If integer is provided, the space ``[0, 1]^domain`` will be used. If array-like object is provided, a hypercube it defines will be used. If distribution, the domain it spans will be used. rule (str): rule for generating samples. The various rules are listed in :mod:`chaospy.distributions.sampler.generator`. antithetic (tuple): Sequence of boolean values. Represents the axes to mirror using antithetic variable. """ logger = logging.getLogger(__name__) logger.debug("generating random samples using rule %s", rule) rule = rule.upper() if isinstance(domain, int): dim = domain trans = lambda x_data: x_data elif isinstance(domain, (tuple, list, numpy.ndarray)): domain = numpy.asfarray(domain) if len(domain.shape) < 2: dim = 1 else: dim = len(domain[0]) trans = lambda x_data: ((domain[1]-domain[0])*x_data.T + domain[0]).T else: dist = domain dim = len(dist) trans = dist.inv if antithetic is not None: from .antithetic import create_antithetic_variates antithetic = numpy.array(antithetic, dtype=bool).flatten() if antithetic.size == 1 and dim > 1: antithetic = numpy.repeat(antithetic, dim) size = numpy.sum(1*numpy.array(antithetic)) order_saved = order order = int(numpy.log(order - dim)) order = order if order > 1 else 1 while order**dim < order_saved: order += 1 trans_ = trans trans = lambda x_data: trans_( create_antithetic_variates(x_data, antithetic)[:, :order_saved]) assert rule in SAMPLERS, "rule not recognised" sampler = SAMPLERS[rule] x_data = trans(sampler(order=order, dim=dim)) logger.debug("order: %d, dim: %d -> shape: %s", order, dim, x_data.shape) return x_data
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Sample generator. Args: order (int): Sample order. Determines the number of samples to create. domain (Dist, int, numpy.ndarray): Defines the space where the samples are generated. If integer is provided, the space ``[0, 1]^domain`` will be used. If array-like object is provided, a hypercube it defines will be used. If distribution, the domain it spans will be used. rule (str): rule for generating samples. The various rules are listed in :mod:`chaospy.distributions.sampler.generator`. antithetic (tuple): Sequence of boolean values. Represents the axes to mirror using antithetic variable.
[ "Sample", "generator", "." ]
python
train
google/tangent
tangent/transformers.py
https://github.com/google/tangent/blob/6533e83af09de7345d1b438512679992f080dcc9/tangent/transformers.py#L81-L96
def append(self, node): """Append a statement to the current statement. Note that multiple calls to append will result in the last statement to be appended to end up at the bottom. Args: node: The statement to append. Raises: ValueError: If the given node is not a statement. """ if not isinstance(node, grammar.STATEMENTS): raise ValueError self.to_append[-1].append(node)
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Append a statement to the current statement. Note that multiple calls to append will result in the last statement to be appended to end up at the bottom. Args: node: The statement to append. Raises: ValueError: If the given node is not a statement.
[ "Append", "a", "statement", "to", "the", "current", "statement", "." ]
python
train
MagicStack/asyncpg
asyncpg/prepared_stmt.py
https://github.com/MagicStack/asyncpg/blob/92c2d81256a1efd8cab12c0118d74ccd1c18131b/asyncpg/prepared_stmt.py#L95-L108
def cursor(self, *args, prefetch=None, timeout=None) -> cursor.CursorFactory: """Return a *cursor factory* for the prepared statement. :param args: Query arguments. :param int prefetch: The number of rows the *cursor iterator* will prefetch (defaults to ``50``.) :param float timeout: Optional timeout in seconds. :return: A :class:`~cursor.CursorFactory` object. """ return cursor.CursorFactory(self._connection, self._query, self._state, args, prefetch, timeout)
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Return a *cursor factory* for the prepared statement. :param args: Query arguments. :param int prefetch: The number of rows the *cursor iterator* will prefetch (defaults to ``50``.) :param float timeout: Optional timeout in seconds. :return: A :class:`~cursor.CursorFactory` object.
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python
train
wonambi-python/wonambi
wonambi/attr/anat.py
https://github.com/wonambi-python/wonambi/blob/1d8e3d7e53df8017c199f703bcab582914676e76/wonambi/attr/anat.py#L295-L318
def read_label(self, hemi, parc_type='aparc'): """Read the labels (annotations) for each hemisphere. Parameters ---------- hemi : str 'lh' or 'rh' parc_type : str 'aparc', 'aparc.a2009s', 'BA', 'BA.thresh', or 'aparc.DKTatlas40' 'aparc.DKTatlas40' is only for recent freesurfer versions Returns ------- numpy.ndarray value at each vertex, indicating the label numpy.ndarray RGB + alpha colors for each label list of str names of the labels """ parc_file = self.dir / 'label' / (hemi + '.' + parc_type + '.annot') vert_val, region_color, region_name = read_annot(parc_file) region_name = [x.decode('utf-8') for x in region_name] return vert_val, region_color, region_name
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Read the labels (annotations) for each hemisphere. Parameters ---------- hemi : str 'lh' or 'rh' parc_type : str 'aparc', 'aparc.a2009s', 'BA', 'BA.thresh', or 'aparc.DKTatlas40' 'aparc.DKTatlas40' is only for recent freesurfer versions Returns ------- numpy.ndarray value at each vertex, indicating the label numpy.ndarray RGB + alpha colors for each label list of str names of the labels
[ "Read", "the", "labels", "(", "annotations", ")", "for", "each", "hemisphere", "." ]
python
train
CenturyLinkCloud/clc-python-sdk
src/clc/APIv2/time_utils.py
https://github.com/CenturyLinkCloud/clc-python-sdk/blob/f4dba40c627cb08dd4b7d0d277e8d67578010b05/src/clc/APIv2/time_utils.py#L16-L24
def SecondsToZuluTS(secs=None): """Returns Zulu TS from unix time seconds. If secs is not provided will convert the current time. """ if not secs: secs = int(time.time()) return(datetime.utcfromtimestamp(secs).strftime("%Y-%m-%dT%H:%M:%SZ"))
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Returns Zulu TS from unix time seconds. If secs is not provided will convert the current time.
[ "Returns", "Zulu", "TS", "from", "unix", "time", "seconds", "." ]
python
train
pecan/pecan
pecan/secure.py
https://github.com/pecan/pecan/blob/833d0653fa0e6bbfb52545b091c30182105f4a82/pecan/secure.py#L205-L217
def handle_security(controller, im_self=None): """ Checks the security of a controller. """ if controller._pecan.get('secured', False): check_permissions = controller._pecan['check_permissions'] if isinstance(check_permissions, six.string_types): check_permissions = getattr( im_self or six.get_method_self(controller), check_permissions ) if not check_permissions(): raise exc.HTTPUnauthorized
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Checks the security of a controller.
[ "Checks", "the", "security", "of", "a", "controller", "." ]
python
train
fedora-python/pyp2rpm
pyp2rpm/archive.py
https://github.com/fedora-python/pyp2rpm/blob/853eb3d226689a5ccdcdb9358b1a3394fafbd2b5/pyp2rpm/archive.py#L183-L188
def extract_all(self, directory=".", members=None): """Extract all member from the archive to the specified working directory. """ if self.handle: self.handle.extractall(path=directory, members=members)
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Extract all member from the archive to the specified working directory.
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python
train
StackStorm/pybind
pybind/slxos/v17r_2_00/cluster/__init__.py
https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/slxos/v17r_2_00/cluster/__init__.py#L317-L338
def _set_designated_forwarder_hold_time(self, v, load=False): """ Setter method for designated_forwarder_hold_time, mapped from YANG variable /cluster/designated_forwarder_hold_time (uint16) If this variable is read-only (config: false) in the source YANG file, then _set_designated_forwarder_hold_time is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_designated_forwarder_hold_time() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), restriction_dict={'range': [u'1..60']}), is_leaf=True, yang_name="designated-forwarder-hold-time", rest_name="designated-forwarder-hold-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Time in seconds to wait before electing a designated forwarder (Range:<1-60>, default:3)', u'cli-suppress-show-conf-path': None, u'cli-suppress-show-match': None}}, namespace='urn:brocade.com:mgmt:brocade-mct', defining_module='brocade-mct', yang_type='uint16', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """designated_forwarder_hold_time must be of a type compatible with uint16""", 'defined-type': "uint16", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=RestrictedClassType(base_type=int, restriction_dict={'range': ['0..65535']},int_size=16), restriction_dict={'range': [u'1..60']}), is_leaf=True, yang_name="designated-forwarder-hold-time", rest_name="designated-forwarder-hold-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Time in seconds to wait before electing a designated forwarder (Range:<1-60>, default:3)', u'cli-suppress-show-conf-path': None, u'cli-suppress-show-match': None}}, namespace='urn:brocade.com:mgmt:brocade-mct', defining_module='brocade-mct', yang_type='uint16', is_config=True)""", }) self.__designated_forwarder_hold_time = t if hasattr(self, '_set'): self._set()
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Setter method for designated_forwarder_hold_time, mapped from YANG variable /cluster/designated_forwarder_hold_time (uint16) If this variable is read-only (config: false) in the source YANG file, then _set_designated_forwarder_hold_time is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_designated_forwarder_hold_time() directly.
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python
train
bitesofcode/projexui
projexui/widgets/xviewwidget/xviewprofile.py
https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xviewwidget/xviewprofile.py#L442-L490
def fromXml( xprofile ): """ Restores the profile information from XML. :param xprofile | <xml.etree.ElementTree.Element> :return <XViewProfile> """ # determine the proper version if xprofile.tag != 'profile': return XViewProfile() version = int(xprofile.get('version', '1')) # load the legacy information - just layout data if version == 1: prof = XViewProfile() prof.setXmlElement(xprofile) return prof # load latest information prof = XViewProfile() prof.setName(xprofile.get('name', '')) prof.setVersion(float(xprofile.get('profile_version', '1.0'))) ico = xprofile.get('icon') if ico is not None: prof.setIcon(os.path.expandvars(ico)) else: ico = xprofile.find('icon') if ico is not None: prof.setIcon(projexui.generatePixmap(ico.text)) # restore data xdata = xprofile.find('data') if ( xdata is not None ): prof._customData = DataSet.fromXml(xdata) # load description xdesc = xprofile.find('desc') if ( xdesc is not None ): prof.setDescription(xdesc.text) # load layout xlayout = xprofile.find('layout') if ( xlayout is not None ): prof.setXmlElement(xlayout) return prof
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Restores the profile information from XML. :param xprofile | <xml.etree.ElementTree.Element> :return <XViewProfile>
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python
train
bcbio/bcbio-nextgen
bcbio/variation/vcfanno.py
https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/variation/vcfanno.py#L150-L154
def annotate_gemini(data, retriever=None): """Annotate with population calls if have data installed. """ r = dd.get_variation_resources(data) return all([r.get(k) and objectstore.file_exists_or_remote(r[k]) for k in ["exac", "gnomad_exome"]])
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Annotate with population calls if have data installed.
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python
train
jorbas/GADDAG
gaddag/gaddag.py
https://github.com/jorbas/GADDAG/blob/a0ede3def715c586e1f273d96e9fc0d537cd9561/gaddag/gaddag.py#L186-L203
def add_word(self, word): """ Add a word to the GADDAG. Args: word: A word to be added to the GADDAG. """ word = word.lower() if not (word.isascii() and word.isalpha()): raise ValueError("Invalid character in word '{}'".format(word)) word = word.encode(encoding="ascii") result = cgaddag.gdg_add_word(self.gdg, word) if result == 1: raise ValueError("Invalid character in word '{}'".format(word)) elif result == 2: raise MemoryError("Out of memory, GADDAG is in an undefined state")
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Add a word to the GADDAG. Args: word: A word to be added to the GADDAG.
[ "Add", "a", "word", "to", "the", "GADDAG", "." ]
python
train
DEIB-GECO/PyGMQL
gmql/RemoteConnection/RemoteManager.py
https://github.com/DEIB-GECO/PyGMQL/blob/e58b2f9402a86056dcda484a32e3de0bb06ed991/gmql/RemoteConnection/RemoteManager.py#L611-L622
def trace_job(self, jobId): """ Get information about the specified remote job :param jobId: the job identifier :return: a dictionary with the information """ header = self.__check_authentication() status_url = self.address + "/jobs/" + jobId + "/trace" status_resp = requests.get(status_url, headers=header) if status_resp.status_code != 200: raise ValueError("Code {}. {}".format(status_resp.status_code, status_resp.json().get("error"))) return status_resp.json()
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Get information about the specified remote job :param jobId: the job identifier :return: a dictionary with the information
[ "Get", "information", "about", "the", "specified", "remote", "job" ]
python
train
martinpitt/python-dbusmock
dbusmock/templates/logind.py
https://github.com/martinpitt/python-dbusmock/blob/26f65f78bc0ed347233f699a8d6ee0e6880e7eb0/dbusmock/templates/logind.py#L117-L145
def AddSeat(self, seat): '''Convenience method to add a seat. Return the object path of the new seat. ''' seat_path = '/org/freedesktop/login1/seat/' + seat if seat_path in mockobject.objects: raise dbus.exceptions.DBusException('Seat %s already exists' % seat, name=MOCK_IFACE + '.SeatExists') self.AddObject(seat_path, 'org.freedesktop.login1.Seat', { 'Sessions': dbus.Array([], signature='(so)'), 'CanGraphical': False, 'CanMultiSession': True, 'CanTTY': False, 'IdleHint': False, 'ActiveSession': ('', dbus.ObjectPath('/')), 'Id': seat, 'IdleSinceHint': dbus.UInt64(0), 'IdleSinceHintMonotonic': dbus.UInt64(0), }, [ ('ActivateSession', 's', '', ''), ('Terminate', '', '', '') ]) return seat_path
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Convenience method to add a seat. Return the object path of the new seat.
[ "Convenience", "method", "to", "add", "a", "seat", "." ]
python
train
dbarsam/python-vsgen
vsgen/solution.py
https://github.com/dbarsam/python-vsgen/blob/640191bb018a1ff7d7b7a4982e0d3c1a423ba878/vsgen/solution.py#L37-L47
def _import(self, datadict): """ Internal method to import instance variables data from a dictionary :param dict datadict: The dictionary containing variables values. """ self.GUID = datadict.get("GUID", uuid.uuid1()) self.FileName = datadict.get("FileName", "") self.Name = datadict.get("Name", "") self.Projects = datadict.get("Projects", []) self.VSVersion = datadict.get("VSVersion", None)
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Internal method to import instance variables data from a dictionary :param dict datadict: The dictionary containing variables values.
[ "Internal", "method", "to", "import", "instance", "variables", "data", "from", "a", "dictionary" ]
python
train
opendatateam/udata
udata/commands/images.py
https://github.com/opendatateam/udata/blob/f016585af94b0ff6bd73738c700324adc8ba7f8f/udata/commands/images.py#L30-L72
def render(): '''Force (re)rendering stored images''' from udata.core.organization.models import Organization from udata.core.post.models import Post from udata.core.reuse.models import Reuse from udata.core.user.models import User header('Rendering images') count = Counter() total = Counter() organizations = Organization.objects(logo__exists=True) total['orgs'] = organizations.count() log.info('Processing {0} organizations logos'.format(total['orgs'])) for org in organizations: count['orgs'] += render_or_skip(org, 'logo') users = User.objects(avatar__exists=True) total['users'] = users.count() log.info('Processing {0} user avatars'.format(total['users'])) for user in users: count['users'] += render_or_skip(user, 'avatar') posts = Post.objects(image__exists=True) total['posts'] = posts.count() log.info('Processing {0} post images'.format(total['posts'])) for post in posts: count['posts'] += render_or_skip(post, 'image') reuses = Reuse.objects(image__exists=True) total['reuses'] = reuses.count() log.info('Processing {0} reuse images'.format(total['reuses'])) for reuse in reuses: count['reuses'] += render_or_skip(reuse, 'image') log.info('''Summary: Organization logos: {count[orgs]}/{total[orgs]} User avatars: {count[users]}/{total[users]} Post images: {count[posts]}/{total[posts]} Reuse images: {count[reuses]}/{total[reuses]} '''.format(count=count, total=total)) success('Images rendered')
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Force (re)rendering stored images
[ "Force", "(", "re", ")", "rendering", "stored", "images" ]
python
train
AirtestProject/Poco
poco/pocofw.py
https://github.com/AirtestProject/Poco/blob/2c559a586adf3fd11ee81cabc446d4d3f6f2d119/poco/pocofw.py#L162-L199
def freeze(this): """ Snapshot current **hierarchy** and cache it into a new poco instance. This new poco instance is a copy from current poco instance (``self``). The hierarchy of the new poco instance is fixed and immutable. It will be super fast when calling ``dump`` function from frozen poco. See the example below. Examples: :: poco = Poco(...) frozen_poco = poco.freeze() hierarchy_dict = frozen_poco.agent.hierarchy.dump() # will return the already cached hierarchy data Returns: :py:class:`Poco <poco.pocofw.Poco>`: new poco instance copy from current poco instance (``self``) """ class FrozenPoco(Poco): def __init__(self, **kwargs): hierarchy_dict = this.agent.hierarchy.dump() hierarchy = create_immutable_hierarchy(hierarchy_dict) agent_ = PocoAgent(hierarchy, this.agent.input, this.agent.screen) kwargs['action_interval'] = 0.01 kwargs['pre_action_wait_for_appearance'] = 0 super(FrozenPoco, self).__init__(agent_, **kwargs) self.this = this def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): pass def __getattr__(self, item): return getattr(self.this, item) return FrozenPoco()
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Snapshot current **hierarchy** and cache it into a new poco instance. This new poco instance is a copy from current poco instance (``self``). The hierarchy of the new poco instance is fixed and immutable. It will be super fast when calling ``dump`` function from frozen poco. See the example below. Examples: :: poco = Poco(...) frozen_poco = poco.freeze() hierarchy_dict = frozen_poco.agent.hierarchy.dump() # will return the already cached hierarchy data Returns: :py:class:`Poco <poco.pocofw.Poco>`: new poco instance copy from current poco instance (``self``)
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python
train
pypa/setuptools
setuptools/__init__.py
https://github.com/pypa/setuptools/blob/83c667e0b2a98193851c07115d1af65011ed0fb6/setuptools/__init__.py#L203-L212
def _find_all_simple(path): """ Find all files under 'path' """ results = ( os.path.join(base, file) for base, dirs, files in os.walk(path, followlinks=True) for file in files ) return filter(os.path.isfile, results)
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Find all files under 'path'
[ "Find", "all", "files", "under", "path" ]
python
train
chemlab/chemlab
chemlab/graphics/transformations.py
https://github.com/chemlab/chemlab/blob/c8730966316d101e24f39ac3b96b51282aba0abe/chemlab/graphics/transformations.py#L1039-L1087
def superimposition_matrix(v0, v1, scale=False, usesvd=True): """Return matrix to transform given 3D point set into second point set. v0 and v1 are shape (3, \*) or (4, \*) arrays of at least 3 points. The parameters scale and usesvd are explained in the more general affine_matrix_from_points function. The returned matrix is a similarity or Eucledian transformation matrix. This function has a fast C implementation in transformations.c. >>> v0 = numpy.random.rand(3, 10) >>> M = superimposition_matrix(v0, v0) >>> numpy.allclose(M, numpy.identity(4)) True >>> R = random_rotation_matrix(numpy.random.random(3)) >>> v0 = [[1,0,0], [0,1,0], [0,0,1], [1,1,1]] >>> v1 = numpy.dot(R, v0) >>> M = superimposition_matrix(v0, v1) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> v0 = (numpy.random.rand(4, 100) - 0.5) * 20 >>> v0[3] = 1 >>> v1 = numpy.dot(R, v0) >>> M = superimposition_matrix(v0, v1) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> S = scale_matrix(random.random()) >>> T = translation_matrix(numpy.random.random(3)-0.5) >>> M = concatenate_matrices(T, R, S) >>> v1 = numpy.dot(M, v0) >>> v0[:3] += numpy.random.normal(0, 1e-9, 300).reshape(3, -1) >>> M = superimposition_matrix(v0, v1, scale=True) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> M = superimposition_matrix(v0, v1, scale=True, usesvd=False) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> v = numpy.empty((4, 100, 3)) >>> v[:, :, 0] = v0 >>> M = superimposition_matrix(v0, v1, scale=True, usesvd=False) >>> numpy.allclose(v1, numpy.dot(M, v[:, :, 0])) True """ v0 = numpy.array(v0, dtype=numpy.float64, copy=False)[:3] v1 = numpy.array(v1, dtype=numpy.float64, copy=False)[:3] return affine_matrix_from_points(v0, v1, shear=False, scale=scale, usesvd=usesvd)
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Return matrix to transform given 3D point set into second point set. v0 and v1 are shape (3, \*) or (4, \*) arrays of at least 3 points. The parameters scale and usesvd are explained in the more general affine_matrix_from_points function. The returned matrix is a similarity or Eucledian transformation matrix. This function has a fast C implementation in transformations.c. >>> v0 = numpy.random.rand(3, 10) >>> M = superimposition_matrix(v0, v0) >>> numpy.allclose(M, numpy.identity(4)) True >>> R = random_rotation_matrix(numpy.random.random(3)) >>> v0 = [[1,0,0], [0,1,0], [0,0,1], [1,1,1]] >>> v1 = numpy.dot(R, v0) >>> M = superimposition_matrix(v0, v1) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> v0 = (numpy.random.rand(4, 100) - 0.5) * 20 >>> v0[3] = 1 >>> v1 = numpy.dot(R, v0) >>> M = superimposition_matrix(v0, v1) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> S = scale_matrix(random.random()) >>> T = translation_matrix(numpy.random.random(3)-0.5) >>> M = concatenate_matrices(T, R, S) >>> v1 = numpy.dot(M, v0) >>> v0[:3] += numpy.random.normal(0, 1e-9, 300).reshape(3, -1) >>> M = superimposition_matrix(v0, v1, scale=True) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> M = superimposition_matrix(v0, v1, scale=True, usesvd=False) >>> numpy.allclose(v1, numpy.dot(M, v0)) True >>> v = numpy.empty((4, 100, 3)) >>> v[:, :, 0] = v0 >>> M = superimposition_matrix(v0, v1, scale=True, usesvd=False) >>> numpy.allclose(v1, numpy.dot(M, v[:, :, 0])) True
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python
train
common-workflow-language/cwltool
cwltool/executors.py
https://github.com/common-workflow-language/cwltool/blob/cb81b22abc52838823da9945f04d06739ab32fda/cwltool/executors.py#L252-L305
def run_job(self, job, # type: Union[JobBase, WorkflowJob, None] runtime_context # type: RuntimeContext ): # type: (...) -> None """ Execute a single Job in a seperate thread. """ if job is not None: with self.pending_jobs_lock: self.pending_jobs.append(job) with self.pending_jobs_lock: n = 0 while (n+1) <= len(self.pending_jobs): job = self.pending_jobs[n] if isinstance(job, JobBase): if ((job.builder.resources["ram"]) > self.max_ram or (job.builder.resources["cores"]) > self.max_cores): _logger.error( 'Job "%s" cannot be run, requests more resources (%s) ' 'than available on this host (max ram %d, max cores %d', job.name, job.builder.resources, self.allocated_ram, self.allocated_cores, self.max_ram, self.max_cores) self.pending_jobs.remove(job) return if ((self.allocated_ram + job.builder.resources["ram"]) > self.max_ram or (self.allocated_cores + job.builder.resources["cores"]) > self.max_cores): _logger.debug( 'Job "%s" cannot run yet, resources (%s) are not ' 'available (already allocated ram is %d, allocated cores is %d, ' 'max ram %d, max cores %d', job.name, job.builder.resources, self.allocated_ram, self.allocated_cores, self.max_ram, self.max_cores) n += 1 continue thread = threading.Thread(target=self._runner, args=(job, runtime_context)) thread.daemon = True self.threads.add(thread) if isinstance(job, JobBase): self.allocated_ram += job.builder.resources["ram"] self.allocated_cores += job.builder.resources["cores"] thread.start() self.pending_jobs.remove(job)
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Execute a single Job in a seperate thread.
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python
train
TeamHG-Memex/eli5
eli5/transform.py
https://github.com/TeamHG-Memex/eli5/blob/371b402a0676295c05e582a2dd591f7af476b86b/eli5/transform.py#L7-L34
def transform_feature_names(transformer, in_names=None): """Get feature names for transformer output as a function of input names. Used by :func:`explain_weights` when applied to a scikit-learn Pipeline, this ``singledispatch`` should be registered with custom name transformations for each class of transformer. If there is no ``singledispatch`` handler registered for a transformer class, ``transformer.get_feature_names()`` method is called; if there is no such method then feature names are not supported and this function raises an exception. Parameters ---------- transformer : scikit-learn-compatible transformer in_names : list of str, optional Names for features input to transformer.transform(). If not provided, the implementation may generate default feature names if the number of input features is known. Returns ------- feature_names : list of str """ if hasattr(transformer, 'get_feature_names'): return transformer.get_feature_names() raise NotImplementedError('transform_feature_names not available for ' '{}'.format(transformer))
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Get feature names for transformer output as a function of input names. Used by :func:`explain_weights` when applied to a scikit-learn Pipeline, this ``singledispatch`` should be registered with custom name transformations for each class of transformer. If there is no ``singledispatch`` handler registered for a transformer class, ``transformer.get_feature_names()`` method is called; if there is no such method then feature names are not supported and this function raises an exception. Parameters ---------- transformer : scikit-learn-compatible transformer in_names : list of str, optional Names for features input to transformer.transform(). If not provided, the implementation may generate default feature names if the number of input features is known. Returns ------- feature_names : list of str
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python
train
ejeschke/ginga
ginga/rv/Control.py
https://github.com/ejeschke/ginga/blob/a78c893ec6f37a837de851947e9bb4625c597915/ginga/rv/Control.py#L939-L945
def zoom_1_to_1(self): """Zoom the view to a 1 to 1 pixel ratio (100 %%). """ viewer = self.getfocus_viewer() if hasattr(viewer, 'scale_to'): viewer.scale_to(1.0, 1.0) return True
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Zoom the view to a 1 to 1 pixel ratio (100 %%).
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python
train
zengbin93/zb
zb/crawlers/xinshipu.py
https://github.com/zengbin93/zb/blob/ccdb384a0b5801b459933220efcb71972c2b89a7/zb/crawlers/xinshipu.py#L86-L100
def get_all_classify(): """获取全部菜谱分类""" url = "https://www.xinshipu.com/%E8%8F%9C%E8%B0%B1%E5%A4%A7%E5%85%A8.html" response = requests.get(url, headers=get_header()) html = BeautifulSoup(response.text, "lxml") all_a = html.find("div", {'class': "detail-cate-list clearfix mt20"}).find_all('a') classify = dict() for a in all_a: if a.has_attr('rel') and not a.has_attr('class'): class_url = urljoin(HOME_URL, a['href']) classify[a.text] = class_url return classify
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获取全部菜谱分类
[ "获取全部菜谱分类" ]
python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/core/shellapp.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/core/shellapp.py#L231-L244
def init_code(self): """run the pre-flight code, specified via exec_lines""" self._run_startup_files() self._run_exec_lines() self._run_exec_files() self._run_cmd_line_code() self._run_module() # flush output, so itwon't be attached to the first cell sys.stdout.flush() sys.stderr.flush() # Hide variables defined here from %who etc. self.shell.user_ns_hidden.update(self.shell.user_ns)
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run the pre-flight code, specified via exec_lines
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python
test
SHTOOLS/SHTOOLS
pyshtools/shclasses/shwindow.py
https://github.com/SHTOOLS/SHTOOLS/blob/9a115cf83002df2ddec6b7f41aeb6be688e285de/pyshtools/shclasses/shwindow.py#L714-L864
def plot_windows(self, nwin, lmax=None, maxcolumns=3, tick_interval=[60, 45], minor_tick_interval=None, xlabel='Longitude', ylabel='Latitude', axes_labelsize=None, tick_labelsize=None, title_labelsize=None, grid=False, show=True, title=True, ax=None, fname=None): """ Plot the best-concentrated localization windows. Usage ----- x.plot_windows(nwin, [lmax, maxcolumns, tick_interval, minor_tick_interval, xlabel, ylabel, grid, show, title, axes_labelsize, tick_labelsize, title_labelsize, ax, fname]) Parameters ---------- nwin : int The number of localization windows to plot. lmax : int, optional, default = self.lwin The maximum degree to use when plotting the windows, which controls the number of samples in latitude and longitude. maxcolumns : int, optional, default = 3 The maximum number of columns to use when plotting multiple localization windows. tick_interval : list or tuple, optional, default = [60, 45] Intervals to use when plotting the x and y ticks. If set to None, ticks will not be plotted. minor_tick_interval : list or tuple, optional, default = None Intervals to use when plotting the minor x and y ticks. If set to None, minor ticks will not be plotted. xlabel : str, optional, default = 'longitude' Label for the longitude axis. ylabel : str, optional, default = 'latitude' Label for the latitude axis. grid : bool, optional, default = False If True, plot grid lines. show : bool, optional, default = True If True, plot the image to the screen. title : bool, optional, default = True If True, plot a title on top of each subplot providing the taper number and 1 minus the concentration factor. axes_labelsize : int, optional, default = None The font size for the x and y axes labels. tick_labelsize : int, optional, default = None The font size for the x and y tick labels. title_labelsize : int, optional, default = None The font size for the subplot titles. ax : matplotlib axes object, optional, default = None An array of matplotlib axes objects where the plots will appear. fname : str, optional, default = None If present, save the image to the specified file. """ if self.kind == 'cap': if self.nwinrot is not None and self.nwinrot <= nwin: nwin = self.nwinrot ncolumns = min(maxcolumns, nwin) nrows = _np.ceil(nwin / ncolumns).astype(int) figsize = (_mpl.rcParams['figure.figsize'][0], _mpl.rcParams['figure.figsize'][0] * 0.55 * nrows / ncolumns + 0.41) if ax is None: fig, axes = _plt.subplots(nrows, ncolumns, figsize=figsize, sharex='all', sharey='all') else: if hasattr(ax, 'flatten') and ax.size < nwin: raise ValueError('ax.size must be greater or equal to nwin. ' + 'nwin = {:s}'.format(repr(nwin)) + ' and ax.size = {:s}.'.format(repr(ax.size))) axes = ax if tick_interval is None: xticks = [] yticks = [] else: xticks = _np.linspace(0, 360, num=360//tick_interval[0]+1, endpoint=True) yticks = _np.linspace(-90, 90, num=180//tick_interval[1]+1, endpoint=True) if axes_labelsize is None: axes_labelsize = _mpl.rcParams['axes.labelsize'] if tick_labelsize is None: tick_labelsize = _mpl.rcParams['xtick.labelsize'] if title_labelsize is None: title_labelsize = _mpl.rcParams['axes.titlesize'] if minor_tick_interval is None: minor_xticks = [] minor_yticks = [] else: minor_xticks = _np.linspace( 0, 360, num=360//minor_tick_interval[0]+1, endpoint=True) minor_yticks = _np.linspace( -90, 90, num=180//minor_tick_interval[1]+1, endpoint=True) deg = '$^{\circ}$' xticklabels = [str(int(y)) + deg for y in xticks] yticklabels = [str(int(y)) + deg for y in yticks] if ax is None: if nrows > 1: for axtemp in axes[:-1, :].flatten(): for xlabel_i in axtemp.get_xticklabels(): xlabel_i.set_visible(False) axtemp.set_xlabel('', visible=False) for axtemp in axes[:, 1:].flatten(): for ylabel_i in axtemp.get_yticklabels(): ylabel_i.set_visible(False) axtemp.set_ylabel('', visible=False) elif nwin > 1: for axtemp in axes[1:].flatten(): for ylabel_i in axtemp.get_yticklabels(): ylabel_i.set_visible(False) axtemp.set_ylabel('', visible=False) for itaper in range(min(self.nwin, nwin)): evalue = self.eigenvalues[itaper] if min(self.nwin, nwin) == 1 and ax is None: axtemp = axes elif hasattr(axes, 'flatten'): axtemp = axes.flatten()[itaper] else: axtemp = axes[itaper] gridout = _shtools.MakeGridDH(self.to_array(itaper), sampling=2, lmax=lmax, norm=1, csphase=1) axtemp.imshow(gridout, origin='upper', extent=(0., 360., -90., 90.)) axtemp.set(xticks=xticks, yticks=yticks) axtemp.set_xlabel(xlabel, fontsize=axes_labelsize) axtemp.set_ylabel(ylabel, fontsize=axes_labelsize) axtemp.set_xticklabels(xticklabels, fontsize=tick_labelsize) axtemp.set_yticklabels(yticklabels, fontsize=tick_labelsize) axtemp.set_xticks(minor_xticks, minor=True) axtemp.set_yticks(minor_yticks, minor=True) axtemp.grid(grid, which='major') if title is True: axtemp.set_title('#{:d} [loss={:2.2g}]' .format(itaper, 1-evalue), fontsize=title_labelsize) if ax is None: fig.tight_layout(pad=0.5) if show: fig.show() if fname is not None: fig.savefig(fname) return fig, axes
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Plot the best-concentrated localization windows. Usage ----- x.plot_windows(nwin, [lmax, maxcolumns, tick_interval, minor_tick_interval, xlabel, ylabel, grid, show, title, axes_labelsize, tick_labelsize, title_labelsize, ax, fname]) Parameters ---------- nwin : int The number of localization windows to plot. lmax : int, optional, default = self.lwin The maximum degree to use when plotting the windows, which controls the number of samples in latitude and longitude. maxcolumns : int, optional, default = 3 The maximum number of columns to use when plotting multiple localization windows. tick_interval : list or tuple, optional, default = [60, 45] Intervals to use when plotting the x and y ticks. If set to None, ticks will not be plotted. minor_tick_interval : list or tuple, optional, default = None Intervals to use when plotting the minor x and y ticks. If set to None, minor ticks will not be plotted. xlabel : str, optional, default = 'longitude' Label for the longitude axis. ylabel : str, optional, default = 'latitude' Label for the latitude axis. grid : bool, optional, default = False If True, plot grid lines. show : bool, optional, default = True If True, plot the image to the screen. title : bool, optional, default = True If True, plot a title on top of each subplot providing the taper number and 1 minus the concentration factor. axes_labelsize : int, optional, default = None The font size for the x and y axes labels. tick_labelsize : int, optional, default = None The font size for the x and y tick labels. title_labelsize : int, optional, default = None The font size for the subplot titles. ax : matplotlib axes object, optional, default = None An array of matplotlib axes objects where the plots will appear. fname : str, optional, default = None If present, save the image to the specified file.
[ "Plot", "the", "best", "-", "concentrated", "localization", "windows", "." ]
python
train
apache/incubator-mxnet
python/mxnet/image/image.py
https://github.com/apache/incubator-mxnet/blob/1af29e9c060a4c7d60eeaacba32afdb9a7775ba7/python/mxnet/image/image.py#L1290-L1300
def hard_reset(self): """Resets the iterator and ignore roll over data""" if self.seq is not None and self.shuffle: random.shuffle(self.seq) if self.imgrec is not None: self.imgrec.reset() self.cur = 0 self._allow_read = True self._cache_data = None self._cache_label = None self._cache_idx = None
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Resets the iterator and ignore roll over data
[ "Resets", "the", "iterator", "and", "ignore", "roll", "over", "data" ]
python
train
dokterbob/django-multilingual-model
multilingual_model/forms.py
https://github.com/dokterbob/django-multilingual-model/blob/2479b2c3d6f7b697e95aa1e082c8bc8699f1f638/multilingual_model/forms.py#L19-L58
def clean(self): """ Make sure there is at least a translation has been filled in. If a default language has been specified, make sure that it exists amongst translations. """ # First make sure the super's clean method is called upon. super(TranslationFormSet, self).clean() if settings.HIDE_LANGUAGE: return if len(self.forms) > 0: # If a default language has been provided, make sure a translation # is available if settings.DEFAULT_LANGUAGE and not any(self.errors): # Don't bother validating the formset unless each form is # valid on its own. Reference: # http://docs.djangoproject.com/en/dev/topics/forms/formsets/#custom-formset-validation for form in self.forms: language_code = form.cleaned_data.get( 'language_code', None ) if language_code == settings.DEFAULT_LANGUAGE: # All is good, don't bother checking any further return raise forms.ValidationError(_( 'No translation provided for default language \'%s\'.' ) % settings.DEFAULT_LANGUAGE) else: raise forms.ValidationError( _('At least one translation should be provided.') )
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Make sure there is at least a translation has been filled in. If a default language has been specified, make sure that it exists amongst translations.
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python
train
PmagPy/PmagPy
pmagpy/ipmag.py
https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/ipmag.py#L6155-L6301
def azdip_magic(orient_file='orient.txt', samp_file="samples.txt", samp_con="1", Z=1, method_codes='FS-FD', location_name='unknown', append=False, output_dir='.', input_dir='.', data_model=3): """ takes space delimited AzDip file and converts to MagIC formatted tables Parameters __________ orient_file : name of azdip formatted input file samp_file : name of samples.txt formatted output file samp_con : integer of sample orientation convention [1] XXXXY: where XXXX is an arbitrary length site designation and Y is the single character sample designation. e.g., TG001a is the first sample from site TG001. [default] [2] XXXX-YY: YY sample from site XXXX (XXX, YY of arbitary length) [3] XXXX.YY: YY sample from site XXXX (XXX, YY of arbitary length) [4-Z] XXXX[YYY]: YYY is sample designation with Z characters from site XXX [5] site name same as sample [6] site name entered in site_name column in the orient.txt format input file -- NOT CURRENTLY SUPPORTED [7-Z] [XXXX]YYY: XXXX is site designation with Z characters with sample name XXXXYYYY method_codes : colon delimited string with the following as desired FS-FD field sampling done with a drill FS-H field sampling done with hand samples FS-LOC-GPS field location done with GPS FS-LOC-MAP field location done with map SO-POM a Pomeroy orientation device was used SO-ASC an ASC orientation device was used SO-MAG orientation with magnetic compass location_name : location of samples append : boolean. if True, append to the output file output_dir : path to output file directory input_dir : path to input file directory data_model : MagIC data model. INPUT FORMAT Input files must be space delimited: Samp Az Dip Strike Dip Orientation convention: Lab arrow azimuth = mag_azimuth; Lab arrow dip = 90-field_dip e.g. field_dip is degrees from horizontal of drill direction Magnetic declination convention: Az is already corrected in file """ # # initialize variables # data_model = int(data_model) if (data_model != 3) and (samp_file == "samples.txt"): samp_file = "er_samples.txt" if (data_model == 2) and (samp_file == "er_samples.txt"): samp_file = "samples.txt" DEBUG = 0 version_num = pmag.get_version() or_con, corr = "3", "1" # date of sampling, latitude (pos North), longitude (pos East) date, lat, lon = "", "", "" bed_dip, bed_dip_dir = "", "" participantlist = "" sites = [] # list of site names Lats, Lons = [], [] # list of latitudes and longitudes # lists of Sample records and Site records SampRecs, SiteRecs, ImageRecs, imagelist = [], [], [], [] average_bedding = "1", 1, "0" newbaseline, newbeddir, newbeddip = "", "", "" delta_u = "0" sclass, lithology, type = "", "", "" newclass, newlith, newtype = '', '', '' user = "" corr == "3" DecCorr = 0. samp_file = pmag.resolve_file_name(samp_file, output_dir) orient_file = pmag.resolve_file_name(orient_file, input_dir) input_dir = os.path.split(orient_file)[0] output_dir = os.path.split(samp_file)[0] # # if append: try: SampRecs, file_type = pmag.magic_read(samp_file) print("sample data to be appended to: ", samp_file) except: print('problem with existing samp file: ', samp_file, ' will create new') # # read in file to convert # azfile = open(orient_file, 'r') AzDipDat = azfile.readlines() azfile.close() if not AzDipDat: return False, 'No data in orientation file, please try again' azfile.close() SampOut, samplist = [], [] for line in AzDipDat: orec = line.split() if len(orec) > 2: labaz, labdip = pmag.orient(float(orec[1]), float(orec[2]), or_con) bed_dip = float(orec[4]) if bed_dip != 0: bed_dip_dir = float(orec[3]) - \ 90. # assume dip to right of strike else: bed_dip_dir = float(orec[3]) # assume dip to right of strike MagRec = {} MagRec["er_location_name"] = location_name MagRec["er_citation_names"] = "This study" # # parse information common to all orientation methods # MagRec["er_sample_name"] = orec[0] MagRec["sample_bed_dip"] = '%7.1f' % (bed_dip) MagRec["sample_bed_dip_direction"] = '%7.1f' % (bed_dip_dir) MagRec["sample_dip"] = '%7.1f' % (labdip) MagRec["sample_azimuth"] = '%7.1f' % (labaz) methods = method_codes.replace(" ", "").split(":") OR = 0 for method in methods: method_type = method.split("-") if "SO" in method_type: OR = 1 if OR == 0: method_codes = method_codes + ":SO-NO" MagRec["magic_method_codes"] = method_codes # parse out the site name site = pmag.parse_site(orec[0], samp_con, Z) MagRec["er_site_name"] = site MagRec['magic_software_packages'] = version_num SampOut.append(MagRec) if MagRec['er_sample_name'] not in samplist: samplist.append(MagRec['er_sample_name']) for samp in SampRecs: if samp not in samplist: SampOut.append(samp) Samps, keys = pmag.fillkeys(SampOut) if data_model == 2: # write to file pmag.magic_write(samp_file, Samps, "er_samples") else: # translate sample records to MagIC 3 Samps3 = [] for samp in Samps: Samps3.append(map_magic.mapping( samp, map_magic.samp_magic2_2_magic3_map)) # write to file pmag.magic_write(samp_file, Samps3, "samples") print("Data saved in ", samp_file) return True, None
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takes space delimited AzDip file and converts to MagIC formatted tables Parameters __________ orient_file : name of azdip formatted input file samp_file : name of samples.txt formatted output file samp_con : integer of sample orientation convention [1] XXXXY: where XXXX is an arbitrary length site designation and Y is the single character sample designation. e.g., TG001a is the first sample from site TG001. [default] [2] XXXX-YY: YY sample from site XXXX (XXX, YY of arbitary length) [3] XXXX.YY: YY sample from site XXXX (XXX, YY of arbitary length) [4-Z] XXXX[YYY]: YYY is sample designation with Z characters from site XXX [5] site name same as sample [6] site name entered in site_name column in the orient.txt format input file -- NOT CURRENTLY SUPPORTED [7-Z] [XXXX]YYY: XXXX is site designation with Z characters with sample name XXXXYYYY method_codes : colon delimited string with the following as desired FS-FD field sampling done with a drill FS-H field sampling done with hand samples FS-LOC-GPS field location done with GPS FS-LOC-MAP field location done with map SO-POM a Pomeroy orientation device was used SO-ASC an ASC orientation device was used SO-MAG orientation with magnetic compass location_name : location of samples append : boolean. if True, append to the output file output_dir : path to output file directory input_dir : path to input file directory data_model : MagIC data model. INPUT FORMAT Input files must be space delimited: Samp Az Dip Strike Dip Orientation convention: Lab arrow azimuth = mag_azimuth; Lab arrow dip = 90-field_dip e.g. field_dip is degrees from horizontal of drill direction Magnetic declination convention: Az is already corrected in file
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python
train
neovim/pynvim
pynvim/api/buffer.py
https://github.com/neovim/pynvim/blob/5e577188e6d7133f597ad0ce60dc6a4b1314064a/pynvim/api/buffer.py#L86-L90
def append(self, lines, index=-1): """Append a string or list of lines to the buffer.""" if isinstance(lines, (basestring, bytes)): lines = [lines] return self.request('nvim_buf_set_lines', index, index, True, lines)
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Append a string or list of lines to the buffer.
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python
train
blockstack/blockstack-core
blockstack/lib/client.py
https://github.com/blockstack/blockstack-core/blob/1dcfdd39b152d29ce13e736a6a1a0981401a0505/blockstack/lib/client.py#L240-L254
def json_is_exception(resp): """ Is the given response object an exception traceback? Return True if so Return False if not """ if not json_is_error(resp): return False if 'traceback' not in resp.keys() or 'error' not in resp.keys(): return False return True
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Is the given response object an exception traceback? Return True if so Return False if not
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python
train
jupyterhub/nbgitpuller
nbgitpuller/pull.py
https://github.com/jupyterhub/nbgitpuller/blob/30df8d548078c58665ce0ae920308f991122abe3/nbgitpuller/pull.py#L133-L146
def find_upstream_changed(self, kind): """ Return list of files that have been changed upstream belonging to a particular kind of change """ output = subprocess.check_output([ 'git', 'log', '{}..origin/{}'.format(self.branch_name, self.branch_name), '--oneline', '--name-status' ], cwd=self.repo_dir).decode() files = [] for line in output.split('\n'): if line.startswith(kind): files.append(os.path.join(self.repo_dir, line.split('\t', 1)[1])) return files
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Return list of files that have been changed upstream belonging to a particular kind of change
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python
train
wonambi-python/wonambi
wonambi/ioeeg/ktlx.py
https://github.com/wonambi-python/wonambi/blob/1d8e3d7e53df8017c199f703bcab582914676e76/wonambi/ioeeg/ktlx.py#L770-L835
def _read_hdr_file(ktlx_file): """Reads header of one KTLX file. Parameters ---------- ktlx_file : Path name of one of the ktlx files inside the directory (absolute path) Returns ------- dict dict with information about the file Notes ----- p.3: says long, but python-long requires 8 bytes, so we use f.read(4) GUID is correct, BUT little/big endian problems somewhere """ with ktlx_file.open('rb') as f: hdr = {} assert f.tell() == 0 hdr['file_guid'] = hexlify(f.read(16)) hdr['file_schema'], = unpack('<H', f.read(2)) if not hdr['file_schema'] in (1, 3, 7, 8, 9): raise NotImplementedError('Reading header not implemented for ' + 'file_schema ' + str(hdr['file_schema'])) hdr['base_schema'], = unpack('<H', f.read(2)) if not hdr['base_schema'] == 1: # p.3: base_schema 0 is rare, I think raise NotImplementedError('Reading header not implemented for ' + 'base_schema ' + str(hdr['base_schema'])) hdr['creation_time'] = datetime.fromtimestamp(unpack('<i', f.read(4))[0]) hdr['patient_id'], = unpack('<i', f.read(4)) hdr['study_id'], = unpack('<i', f.read(4)) hdr['pat_last_name'] = _make_str(unpack('c' * 80, f.read(80))) hdr['pat_first_name'] = _make_str(unpack('c' * 80, f.read(80))) hdr['pat_middle_name'] = _make_str(unpack('c' * 80, f.read(80))) hdr['patient_id'] = _make_str(unpack('c' * 80, f.read(80))) assert f.tell() == 352 if hdr['file_schema'] >= 7: hdr['sample_freq'], = unpack('<d', f.read(8)) n_chan, = unpack('<i', f.read(4)) hdr['num_channels'] = n_chan hdr['deltabits'], = unpack('<i', f.read(4)) hdr['phys_chan'] = unpack('<' + 'i' * hdr['num_channels'], f.read(hdr['num_channels'] * 4)) f.seek(4464) hdr['headbox_type'] = unpack('<' + 'i' * 4, f.read(16)) hdr['headbox_sn'] = unpack('<' + 'i' * 4, f.read(16)) hdr['headbox_sw_version'] = _make_str(unpack('c' * 40, f.read(40))) hdr['dsp_hw_version'] = _make_str(unpack('c' * 10, f.read(10))) hdr['dsp_sw_version'] = _make_str(unpack('c' * 10, f.read(10))) hdr['discardbits'], = unpack('<i', f.read(4)) if hdr['file_schema'] >= 8: hdr['shorted'] = unpack('<' + 'h' * 1024, f.read(2048))[:n_chan] hdr['frequency_factor'] = unpack('<' + 'h' * 1024, f.read(2048))[:n_chan] return hdr
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Reads header of one KTLX file. Parameters ---------- ktlx_file : Path name of one of the ktlx files inside the directory (absolute path) Returns ------- dict dict with information about the file Notes ----- p.3: says long, but python-long requires 8 bytes, so we use f.read(4) GUID is correct, BUT little/big endian problems somewhere
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python
train
Clinical-Genomics/scout
scout/parse/omim.py
https://github.com/Clinical-Genomics/scout/blob/90a551e2e1653a319e654c2405c2866f93d0ebb9/scout/parse/omim.py#L43-L166
def parse_genemap2(lines): """Parse the omim source file called genemap2.txt Explanation of Phenotype field: Brackets, "[ ]", indicate "nondiseases," mainly genetic variations that lead to apparently abnormal laboratory test values. Braces, "{ }", indicate mutations that contribute to susceptibility to multifactorial disorders (e.g., diabetes, asthma) or to susceptibility to infection (e.g., malaria). A question mark, "?", before the phenotype name indicates that the relationship between the phenotype and gene is provisional. More details about this relationship are provided in the comment field of the map and in the gene and phenotype OMIM entries. The number in parentheses after the name of each disorder indicates the following: (1) the disorder was positioned by mapping of the wildtype gene; (2) the disease phenotype itself was mapped; (3) the molecular basis of the disorder is known; (4) the disorder is a chromosome deletion or duplication syndrome. Args: lines(iterable(str)) Yields: parsed_entry(dict) """ LOG.info("Parsing the omim genemap2") header = [] for i,line in enumerate(lines): line = line.rstrip() if line.startswith('#'): if i < 10: if line.startswith('# Chromosome'): header = line[2:].split('\t') continue if len(line) < 5: continue parsed_entry = parse_omim_line(line, header) parsed_entry['mim_number'] = int(parsed_entry['Mim Number']) parsed_entry['raw'] = line # This is the approved symbol for the entry hgnc_symbol = parsed_entry.get("Approved Symbol") # If no approved symbol could be found choose the first of # the gene symbols gene_symbols = [] if parsed_entry.get('Gene Symbols'): gene_symbols = [symbol.strip() for symbol in parsed_entry['Gene Symbols'].split(',')] parsed_entry['hgnc_symbols'] = gene_symbols if not hgnc_symbol and gene_symbols: hgnc_symbol = gene_symbols[0] parsed_entry['hgnc_symbol'] = hgnc_symbol # Gene inheritance is a construct. It is the union of all inheritance # patterns found in the associated phenotypes gene_inheritance = set() parsed_phenotypes = [] # Information about the related phenotypes # Each related phenotype is separated by ';' for phenotype_info in parsed_entry.get('Phenotypes', '').split(';'): if not phenotype_info: continue phenotype_info = phenotype_info.lstrip() # First symbol in description indicates phenotype status # If no special symbol is used the phenotype is 'established' phenotype_status = OMIM_STATUS_MAP.get(phenotype_info[0], 'established') # Skip phenotype entries that not associated to disease if phenotype_status == 'nondisease': continue phenotype_description = "" # We will try to save the description splitted_info = phenotype_info.split(',') for i, text in enumerate(splitted_info): # Everything before ([1,2,3]) # We check if we are in the part where the mim number exists match = entry_pattern.search(text) if not match: phenotype_description += text else: # If we find the end of the entry mimnr_match = mimnr_pattern.search(phenotype_info) # Then if the entry have a mim number we choose that if mimnr_match: phenotype_mim = int(mimnr_match.group()) else: phenotype_mim = parsed_entry['mim_number'] phenotype_description += text[:-4] break # Find the inheritance inheritance = set() inheritance_text = ','.join(splitted_info[i:]) for term in mim_inheritance_terms: if term in inheritance_text: inheritance.add(TERMS_MAPPER[term]) gene_inheritance.add(TERMS_MAPPER[term]) parsed_phenotypes.append( { 'mim_number':phenotype_mim, 'inheritance': inheritance, 'description': phenotype_description.strip('?\{\}'), 'status': phenotype_status, } ) parsed_entry['phenotypes'] = parsed_phenotypes parsed_entry['inheritance'] = gene_inheritance yield parsed_entry
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Parse the omim source file called genemap2.txt Explanation of Phenotype field: Brackets, "[ ]", indicate "nondiseases," mainly genetic variations that lead to apparently abnormal laboratory test values. Braces, "{ }", indicate mutations that contribute to susceptibility to multifactorial disorders (e.g., diabetes, asthma) or to susceptibility to infection (e.g., malaria). A question mark, "?", before the phenotype name indicates that the relationship between the phenotype and gene is provisional. More details about this relationship are provided in the comment field of the map and in the gene and phenotype OMIM entries. The number in parentheses after the name of each disorder indicates the following: (1) the disorder was positioned by mapping of the wildtype gene; (2) the disease phenotype itself was mapped; (3) the molecular basis of the disorder is known; (4) the disorder is a chromosome deletion or duplication syndrome. Args: lines(iterable(str)) Yields: parsed_entry(dict)
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python
test
pvlib/pvlib-python
pvlib/clearsky.py
https://github.com/pvlib/pvlib-python/blob/2e844a595b820b43d1170269781fa66bd0ccc8a3/pvlib/clearsky.py#L491-L499
def _calc_b(w, aod700): """Calculate the b coefficient.""" b1 = 0.00925*aod700**2 + 0.0148*aod700 - 0.0172 b0 = -0.7565*aod700**2 + 0.5057*aod700 + 0.4557 b = b1 * np.log(w) + b0 return b
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Calculate the b coefficient.
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python
train
mar10/wsgidav
wsgidav/dc/simple_dc.py
https://github.com/mar10/wsgidav/blob/cec0d84222fc24bea01be1cea91729001963f172/wsgidav/dc/simple_dc.py#L109-L117
def require_authentication(self, realm, environ): """Return True if this realm requires authentication (grant anonymous access otherwise).""" realm_entry = self._get_realm_entry(realm) if realm_entry is None: _logger.error( 'Missing configuration simple_dc.user_mapping["{}"] (or "*"): ' "realm is not accessible!".format(realm) ) return realm_entry is not True
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Return True if this realm requires authentication (grant anonymous access otherwise).
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python
valid
CS207-Final-Project-Group-10/cs207-FinalProject
fluxions/fluxion_node.py
https://github.com/CS207-Final-Project-Group-10/cs207-FinalProject/blob/842e9c2d3ca1490cef18c086dfde81856d8d3a82/fluxions/fluxion_node.py#L419-L431
def _forward_mode(self, *args): """Forward mode differentiation for a constant""" # Evaluate inner function self.f X: np.ndarray dX: np.ndarray X, dX = self.f._forward_mode(*args) # Alias the power to p for legibility p: float = self.p # The function value val = X ** p # The derivative diff = p * X ** (p-1) * dX return (val, diff)
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Forward mode differentiation for a constant
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python
train
zeroSteiner/AdvancedHTTPServer
advancedhttpserver.py
https://github.com/zeroSteiner/AdvancedHTTPServer/blob/8c53cf7e1ddbf7ae9f573c82c5fe5f6992db7b5a/advancedhttpserver.py#L1521-L1536
def close(self): """ Close the web socket connection and stop processing results. If the connection is still open, a WebSocket close message will be sent to the peer. """ if not self.connected: return self.connected = False if self.handler.wfile.closed: return if select.select([], [self.handler.wfile], [], 0)[1]: with self.lock: self.handler.wfile.write(b'\x88\x00') self.handler.wfile.flush() self.on_closed()
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Close the web socket connection and stop processing results. If the connection is still open, a WebSocket close message will be sent to the peer.
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python
train
azraq27/neural
neural/general.py
https://github.com/azraq27/neural/blob/fe91bfeecbf73ad99708cf5dca66cb61fcd529f5/neural/general.py#L24-L30
def voxel_loop(self): '''iterator that loops through each voxel and yields the coords and time series as a tuple''' # Prob not the most efficient, but the best I can do for now: for x in xrange(len(self.data)): for y in xrange(len(self.data[x])): for z in xrange(len(self.data[x][y])): yield ((x,y,z),self.data[x][y][z])
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iterator that loops through each voxel and yields the coords and time series as a tuple
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python
train
crs4/hl7apy
hl7apy/__init__.py
https://github.com/crs4/hl7apy/blob/91be488e9274f6ec975519a1d9c17045bc91bf74/hl7apy/__init__.py#L239-L281
def load_reference(name, element_type, version): """ Look for an element of the given type, name and version and return its reference structure :type element_type: ``str`` :param element_type: the element type to look for (e.g. 'Segment') :type name: ``str`` :param name: the element name to look for (e.g. 'MSH') :type version: ``str`` :param version: the version of the library where to search the element (e.g. '2.6') :rtype: ``dict`` :return: a dictionary describing the element structure :raise: ``KeyError`` if the element has not been found The returned dictionary will contain the following keys: +--------------+--------------------------------------------+ |Key |Value | +==============+============================================+ |cls |an :class:`hl7apy.core.Element` subclass | +--------------+--------------------------------------------+ |name |the Element name (e.g. PID) | +--------------+--------------------------------------------+ |ref |a tuple of one of the following format: | | | | | |('leaf', <datatype>, <longName>, <table>) | | |('sequence', (<child>, (<min>, <max>), ...))| +--------------+--------------------------------------------+ >>> load_reference('UNKNOWN', 'Segment', '2.5') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ChildNotFound: No child named UNKNOWN >>> r = load_reference('ADT_A01', 'Message', '2.5') >>> print(r[0]) sequence >>> r = load_reference('MSH_3', 'Field', '2.5') >>> print(r[0]) sequence """ lib = load_library(version) ref = lib.get(name, element_type) return ref
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Look for an element of the given type, name and version and return its reference structure :type element_type: ``str`` :param element_type: the element type to look for (e.g. 'Segment') :type name: ``str`` :param name: the element name to look for (e.g. 'MSH') :type version: ``str`` :param version: the version of the library where to search the element (e.g. '2.6') :rtype: ``dict`` :return: a dictionary describing the element structure :raise: ``KeyError`` if the element has not been found The returned dictionary will contain the following keys: +--------------+--------------------------------------------+ |Key |Value | +==============+============================================+ |cls |an :class:`hl7apy.core.Element` subclass | +--------------+--------------------------------------------+ |name |the Element name (e.g. PID) | +--------------+--------------------------------------------+ |ref |a tuple of one of the following format: | | | | | |('leaf', <datatype>, <longName>, <table>) | | |('sequence', (<child>, (<min>, <max>), ...))| +--------------+--------------------------------------------+ >>> load_reference('UNKNOWN', 'Segment', '2.5') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ChildNotFound: No child named UNKNOWN >>> r = load_reference('ADT_A01', 'Message', '2.5') >>> print(r[0]) sequence >>> r = load_reference('MSH_3', 'Field', '2.5') >>> print(r[0]) sequence
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python
train
ourway/auth
auth/CAS/authorization.py
https://github.com/ourway/auth/blob/f0d9676854dcec494add4fa086a9b2a3e4d8cea5/auth/CAS/authorization.py#L62-L66
def get_role_members(self, role): """get permissions of a user""" targetRoleDb = AuthGroup.objects(creator=self.client, role=role) members = AuthMembership.objects(groups__in=targetRoleDb).only('user') return json.loads(members.to_json())
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get permissions of a user
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python
train
linkedin/luminol
src/luminol/algorithms/anomaly_detector_algorithms/default_detector.py
https://github.com/linkedin/luminol/blob/42e4ab969b774ff98f902d064cb041556017f635/src/luminol/algorithms/anomaly_detector_algorithms/default_detector.py#L35-L49
def _set_scores(self): """ Set anomaly scores using a weighted sum. """ anom_scores_ema = self.exp_avg_detector.run() anom_scores_deri = self.derivative_detector.run() anom_scores = {} for timestamp in anom_scores_ema.timestamps: # Compute a weighted anomaly score. anom_scores[timestamp] = max(anom_scores_ema[timestamp], anom_scores_ema[timestamp] * DEFAULT_DETECTOR_EMA_WEIGHT + anom_scores_deri[timestamp] * (1 - DEFAULT_DETECTOR_EMA_WEIGHT)) # If ema score is significant enough, take the bigger one of the weighted score and deri score. if anom_scores_ema[timestamp] > DEFAULT_DETECTOR_EMA_SIGNIFICANT: anom_scores[timestamp] = max(anom_scores[timestamp], anom_scores_deri[timestamp]) self.anom_scores = TimeSeries(self._denoise_scores(anom_scores))
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Set anomaly scores using a weighted sum.
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python
train
juju/charm-helpers
charmhelpers/contrib/openstack/audits/openstack_security_guide.py
https://github.com/juju/charm-helpers/blob/aa785c40c3b7a8c69dbfbc7921d6b9f30142e171/charmhelpers/contrib/openstack/audits/openstack_security_guide.py#L220-L237
def validate_file_permissions(config): """Verify that permissions on configuration files are secure enough.""" files = config.get('files', {}) for file_name, options in files.items(): for key in options.keys(): if key not in ["owner", "group", "mode"]: raise RuntimeError( "Invalid ownership configuration: {}".format(key)) mode = options.get('mode', config.get('permissions', '600')) optional = options.get('optional', config.get('optional', 'False')) if '*' in file_name: for file in glob.glob(file_name): if file not in files.keys(): if os.path.isfile(file): _validate_file_mode(mode, file, optional) else: if os.path.isfile(file_name): _validate_file_mode(mode, file_name, optional)
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Verify that permissions on configuration files are secure enough.
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python
train
pyviz/holoviews
holoviews/core/dimension.py
https://github.com/pyviz/holoviews/blob/ae0dd2f3de448b0ca5e9065aabd6ef8d84c7e655/holoviews/core/dimension.py#L1206-L1284
def options(self, *args, **kwargs): """Applies simplified option definition returning a new object. Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.: obj.options(cmap='viridis', show_title=False) If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.: obj.options('Image', cmap='viridis', show_title=False) or using: obj.options({'Image': dict(cmap='viridis', show_title=False)}) Identical to the .opts method but returns a clone of the object by default. Args: *args: Sets of options to apply to object Supports a number of formats including lists of Options objects, a type[.group][.label] followed by a set of keyword options to apply and a dictionary indexed by type[.group][.label] specs. backend (optional): Backend to apply options to Defaults to current selected backend clone (bool, optional): Whether to clone object Options can be applied inplace with clone=False **kwargs: Keywords of options Set of options to apply to the object Returns: Returns the cloned object with the options applied """ backend = kwargs.get('backend', None) clone = kwargs.pop('clone', True) if len(args) == 0 and len(kwargs)==0: options = None elif args and isinstance(args[0], basestring): options = {args[0]: kwargs} elif args and isinstance(args[0], list): if kwargs: raise ValueError('Please specify a list of option objects, or kwargs, but not both') options = args[0] elif args and [k for k in kwargs.keys() if k != 'backend']: raise ValueError("Options must be defined in one of two formats. " "Either supply keywords defining the options for " "the current object, e.g. obj.options(cmap='viridis'), " "or explicitly define the type, e.g. " "obj.options({'Image': {'cmap': 'viridis'}}). " "Supplying both formats is not supported.") elif args and all(isinstance(el, dict) for el in args): if len(args) > 1: self.warning('Only a single dictionary can be passed ' 'as a positional argument. Only processing ' 'the first dictionary') options = [Options(spec, **kws) for spec,kws in args[0].items()] elif args: options = list(args) elif kwargs: options = {type(self).__name__: kwargs} from ..util import opts if options is None: expanded_backends = [(backend, {})] elif isinstance(options, list): # assuming a flat list of Options objects expanded_backends = opts._expand_by_backend(options, backend) else: expanded_backends = [(backend, opts._expand_options(options, backend))] obj = self for backend, expanded in expanded_backends: obj = obj.opts._dispatch_opts(expanded, backend=backend, clone=clone) return obj
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Applies simplified option definition returning a new object. Applies options on an object or nested group of objects in a flat format returning a new object with the options applied. If the options are to be set directly on the object a simple format may be used, e.g.: obj.options(cmap='viridis', show_title=False) If the object is nested the options must be qualified using a type[.group][.label] specification, e.g.: obj.options('Image', cmap='viridis', show_title=False) or using: obj.options({'Image': dict(cmap='viridis', show_title=False)}) Identical to the .opts method but returns a clone of the object by default. Args: *args: Sets of options to apply to object Supports a number of formats including lists of Options objects, a type[.group][.label] followed by a set of keyword options to apply and a dictionary indexed by type[.group][.label] specs. backend (optional): Backend to apply options to Defaults to current selected backend clone (bool, optional): Whether to clone object Options can be applied inplace with clone=False **kwargs: Keywords of options Set of options to apply to the object Returns: Returns the cloned object with the options applied
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python
train
spyder-ide/spyder
spyder/plugins/editor/panels/debugger.py
https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/plugins/editor/panels/debugger.py#L51-L66
def _draw_breakpoint_icon(self, top, painter, icon_name): """Draw the given breakpoint pixmap. Args: top (int): top of the line to draw the breakpoint icon. painter (QPainter) icon_name (srt): key of icon to draw (see: self.icons) """ rect = QRect(0, top, self.sizeHint().width(), self.sizeHint().height()) try: icon = self.icons[icon_name] except KeyError as e: debug_print("Breakpoint icon doen't exist, {}".format(e)) else: icon.paint(painter, rect)
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Draw the given breakpoint pixmap. Args: top (int): top of the line to draw the breakpoint icon. painter (QPainter) icon_name (srt): key of icon to draw (see: self.icons)
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python
train
jtmoulia/switchboard-python
examples/lamsonworker.py
https://github.com/jtmoulia/switchboard-python/blob/c9b0cb74cb12a64385465091be633e78d39f08b1/examples/lamsonworker.py#L37-L44
def received_new(self, msg): """ As new messages arrive, deliver them to the lamson relay. """ logger.info("Receiving msg, delivering to Lamson...") logger.debug("Relaying msg to lamson: From: %s, To: %s", msg['From'], msg['To']) self._relay.deliver(msg)
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As new messages arrive, deliver them to the lamson relay.
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python
train
slickqa/python-client
slickqa/connection.py
https://github.com/slickqa/python-client/blob/1d36b4977cd4140d7d24917cab2b3f82b60739c2/slickqa/connection.py#L321-L348
def upload_local_file(self, local_file_path, file_obj=None): """Create a Stored File and upload it's data. This is a one part do it all type method. Here is what it does: 1. "Discover" information about the file (mime-type, size) 2. Create the stored file object in slick 3. Upload (chunked) all the data in the local file 4. re-fetch the stored file object from slick, and return it """ if file_obj is None and not os.path.exists(local_file_path): return storedfile = StoredFile() storedfile.mimetype = mimetypes.guess_type(local_file_path)[0] storedfile.filename = os.path.basename(local_file_path) if file_obj is None: storedfile.length = os.stat(local_file_path).st_size else: file_obj.seek(0,os.SEEK_END) storedfile.length = file_obj.tell() file_obj.seek(0) storedfile = self(storedfile).create() md5 = hashlib.md5() url = self(storedfile).getUrl() + "/addchunk" if file_obj is None: with open(local_file_path, 'rb') as filecontents: upload_chunks(url, storedfile, filecontents) else: upload_chunks(url, storedfile, file_obj) return self(storedfile).update()
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python
train
ehansis/ozelot
ozelot/client.py
https://github.com/ehansis/ozelot/blob/948675e02eb6fca940450f5cb814f53e97159e5b/ozelot/client.py#L102-L115
def store_password(params, password): """Store the password for a database connection using :mod:`keyring` Use the ``user`` field as the user name and ``<host>:<driver>`` as service name. Args: params (dict): database configuration, as defined in :mod:`ozelot.config` password (str): password to store """ user_name = params['user'] service_name = params['host'] + ':' + params['driver'] keyring.set_password(service_name=service_name, username=user_name, password=password)
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Store the password for a database connection using :mod:`keyring` Use the ``user`` field as the user name and ``<host>:<driver>`` as service name. Args: params (dict): database configuration, as defined in :mod:`ozelot.config` password (str): password to store
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python
train
yeraydiazdiaz/lunr.py
lunr/pipeline.py
https://github.com/yeraydiazdiaz/lunr.py/blob/28ec3f6d4888295eed730211ee9617aa488d6ba3/lunr/pipeline.py#L43-L56
def load(cls, serialised): """Loads a previously serialised pipeline.""" pipeline = cls() for fn_name in serialised: try: fn = cls.registered_functions[fn_name] except KeyError: raise BaseLunrException( "Cannot load unregistered function ".format(fn_name) ) else: pipeline.add(fn) return pipeline
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Loads a previously serialised pipeline.
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python
train
iamteem/redisco
redisco/containers.py
https://github.com/iamteem/redisco/blob/a7ba19ff3c38061d6d8bc0c10fa754baadcfeb91/redisco/containers.py#L457-L464
def lt(self, v, limit=None, offset=None): """Returns the list of the members of the set that have scores less than v. """ if limit is not None and offset is None: offset = 0 return self.zrangebyscore(self._min_score, "(%f" % v, start=offset, num=limit)
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Returns the list of the members of the set that have scores less than v.
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python
train
dantezhu/haven
haven/gevent_impl.py
https://github.com/dantezhu/haven/blob/7bf7edab07fa2ade7644a548d6ab9d89cf3d259d/haven/gevent_impl.py#L88-L112
def set(self, interval, callback, repeat=False, force=True): """ 添加timer """ if self.timer: if force: # 如果已经存在,那么先要把现在的清空 self.clear() else: # 已经存在的话,就返回了 return def callback_wrapper(): # 必须要确定,这次调用就是这个timer引起的 if self.timer == timer: # 必须加这句,否则如果在callback中有clear操作,会出现GreenletExit self.timer = None # 不可以加 timer = None,否则会导致判断self.timer == timer 报错找不到timer result = safe_call(callback) if repeat and not self.timer: # 之所以还要判断timer,是因为callback中可能设置了新的回调 self.set(interval, callback, repeat, True) return result self.timer = timer = gevent.spawn_later(interval, callback_wrapper)
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添加timer
[ "添加timer" ]
python
train
reanahub/reana-commons
reana_commons/utils.py
https://github.com/reanahub/reana-commons/blob/abf31d9f495e0d93171c43fc4a414cd292091b11/reana_commons/utils.py#L210-L216
def render_cvmfs_sc(cvmfs_volume): """Render REANA_CVMFS_SC_TEMPLATE.""" name = CVMFS_REPOSITORIES[cvmfs_volume] rendered_template = dict(REANA_CVMFS_SC_TEMPLATE) rendered_template['metadata']['name'] = "csi-cvmfs-{}".format(name) rendered_template['parameters']['repository'] = cvmfs_volume return rendered_template
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Render REANA_CVMFS_SC_TEMPLATE.
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python
train
lrq3000/pyFileFixity
pyFileFixity/lib/gooey/gui/lang/i18n.py
https://github.com/lrq3000/pyFileFixity/blob/fd5ef23bb13835faf1e3baa773619b86a1cc9bdf/pyFileFixity/lib/gooey/gui/lang/i18n.py#L23-L29
def get_path(language): ''' Returns the full path to the language file ''' filename = language.lower() + '.json' lang_file_path = os.path.join(_DEFAULT_DIR, filename) if not os.path.exists(lang_file_path): raise IOError('Could not find {} language file'.format(language)) return lang_file_path
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Returns the full path to the language file
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python
train
aodag/WebDispatch
webdispatch/uritemplate.py
https://github.com/aodag/WebDispatch/blob/55f8658a2b4100498e098a80303a346c3940f1bc/webdispatch/uritemplate.py#L93-L97
def new_named_args(self, cur_named_args: Dict[str, Any]) -> Dict[str, Any]: """ create new named args updating current name args""" named_args = cur_named_args.copy() named_args.update(self.matchdict) return named_args
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create new named args updating current name args
[ "create", "new", "named", "args", "updating", "current", "name", "args" ]
python
train
CI-WATER/gsshapy
gsshapy/orm/gag.py
https://github.com/CI-WATER/gsshapy/blob/00fd4af0fd65f1614d75a52fe950a04fb0867f4c/gsshapy/orm/gag.py#L150-L186
def _createGsshaPyObjects(self, eventChunk): """ Create GSSHAPY PrecipEvent, PrecipValue, and PrecipGage Objects Method """ ## TODO: Add Support for RADAR file format type values # Create GSSHAPY PrecipEvent event = PrecipEvent(description=eventChunk['description'], nrGag=eventChunk['nrgag'], nrPds=eventChunk['nrpds']) # Associate PrecipEvent with PrecipFile event.precipFile = self gages = [] for coord in eventChunk['coords']: # Create GSSHAPY PrecipGage object gage = PrecipGage(description=coord['description'], x=coord['x'], y=coord['y']) # Associate PrecipGage with PrecipEvent gage.event = event # Append to gages list for association with PrecipValues gages.append(gage) for valLine in eventChunk['valLines']: for index, value in enumerate(valLine['values']): # Create GSSHAPY PrecipValue object val = PrecipValue(valueType=valLine['type'], dateTime=valLine['dateTime'], value=value) # Associate PrecipValue with PrecipEvent and PrecipGage val.event = event val.gage = gages[index]
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Create GSSHAPY PrecipEvent, PrecipValue, and PrecipGage Objects Method
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python
train
uw-it-aca/uw-restclients-sws
uw_sws/department.py
https://github.com/uw-it-aca/uw-restclients-sws/blob/4d36776dcca36855fc15c1b8fe7650ae045194cf/uw_sws/department.py#L14-L22
def get_departments_by_college(college): """ Returns a list of restclients.Department models, for the passed College model. """ url = "{}?{}".format( dept_search_url_prefix, urlencode({"college_abbreviation": college.label})) return _json_to_departments(get_resource(url), college)
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Returns a list of restclients.Department models, for the passed College model.
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python
train
Workiva/furious
example/complex_workflow.py
https://github.com/Workiva/furious/blob/c29823ec8b98549e7439d7273aa064d1e5830632/example/complex_workflow.py#L76-L91
def state_machine_success(): """A positive result! Iterate!""" from furious.async import Async from furious.context import get_current_async result = get_current_async().result if result == 'ALPHA': logging.info('Inserting continuation for state %s.', result) return Async(target=complex_state_generator_alpha, args=[result]) elif result == 'BRAVO': logging.info('Inserting continuation for state %s.', result) return Async(target=complex_state_generator_bravo, args=[result]) logging.info('Done working, stop now.')
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A positive result! Iterate!
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python
train
JoeVirtual/KonFoo
konfoo/core.py
https://github.com/JoeVirtual/KonFoo/blob/0c62ef5c2bed4deaf908b34082e4de2544532fdc/konfoo/core.py#L1046-L1055
def insert(self, index, item): """ Inserts the *item* before the *index* into the `Sequence`. :param int index: `Sequence` index. :param item: any :class:`Structure`, :class:`Sequence`, :class:`Array` or :class:`Field` instance. """ if not is_any(item): raise MemberTypeError(self, item, member=len(self)) self._data.insert(index, item)
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Inserts the *item* before the *index* into the `Sequence`. :param int index: `Sequence` index. :param item: any :class:`Structure`, :class:`Sequence`, :class:`Array` or :class:`Field` instance.
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python
train
base4sistemas/pyescpos
escpos/conn/serial.py
https://github.com/base4sistemas/pyescpos/blob/621bd00f1499aff700f37d8d36d04e0d761708f1/escpos/conn/serial.py#L349-L382
def as_from(value): """ Constructs an instance of :class:`SerialSettings` from a string representation, that looks like ``/dev/ttyS0:9600,8,1,N,RTSCTS``, describing, in order, the serial port name, baud rate, byte size, stop bits, parity and flow control protocol. Valid string representations are (in cases where protocol is not specified, RTS/CTS is assumed):: COM1:115000,8,1,E COM1:115000:8:1:E COM4:9600:8:2:O:DSRDTR /dev/ttyS0:9600,8,1,N,RTSCTS /dev/ttyS0,9600,8,1,N """ keys = ['port','baudrate','databits','stopbits','parity','protocol'] values = value.replace(',', ':').split(':') if len(values) == 5: values.append(RTSCTS) if len(keys) != len(values): raise ValueError('Unknown serial port string format: %s ' '(expecting something like "COM1:9600,8,1,N,RTSCTS")' % ( value,)) kwargs = dict(zip(keys, values)) kwargs['baudrate'] = int(kwargs['baudrate']) kwargs['databits'] = int(kwargs['databits']) kwargs['stopbits'] = int(kwargs['stopbits']) return SerialSettings(**kwargs)
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python
train
DataDog/integrations-core
openstack_controller/datadog_checks/openstack_controller/openstack_controller.py
https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/openstack_controller/datadog_checks/openstack_controller/openstack_controller.py#L601-L669
def init_api(self, instance_config, custom_tags): """ Guarantees a valid auth scope for this instance, and returns it Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly removed due to token expiry """ custom_tags = custom_tags or [] keystone_server_url = instance_config.get("keystone_server_url") proxy_config = self.get_instance_proxy(instance_config, keystone_server_url) if self._api is None: # We are missing the entire instance scope either because it is the first time we initialize it or because # authentication previously failed and got removed from the cache # Let's populate it now try: self.log.debug("Fetch scope for instance {}".format(self.instance_name)) # Set keystone api with proper token self._api = ApiFactory.create(self.log, proxy_config, instance_config) self.service_check( self.IDENTITY_API_SC, AgentCheck.OK, tags=["keystone_server: {}".format(keystone_server_url)] + custom_tags, ) except KeystoneUnreachable as e: self.warning( "The agent could not contact the specified identity server at {} . " "Are you sure it is up at that address?".format(keystone_server_url) ) self.log.debug("Problem grabbing auth token: %s", e) self.service_check( self.IDENTITY_API_SC, AgentCheck.CRITICAL, tags=["keystone_server: {}".format(keystone_server_url)] + custom_tags, ) # If Keystone is down/unreachable, we default the # Nova and Neutron APIs to UNKNOWN since we cannot access the service catalog self.service_check( self.NETWORK_API_SC, AgentCheck.UNKNOWN, tags=["keystone_server: {}".format(keystone_server_url)] + custom_tags, ) self.service_check( self.COMPUTE_API_SC, AgentCheck.UNKNOWN, tags=["keystone_server: {}".format(keystone_server_url)] + custom_tags, ) except MissingNovaEndpoint as e: self.warning("The agent could not find a compatible Nova endpoint in your service catalog!") self.log.debug("Failed to get nova endpoint for response catalog: %s", e) self.service_check( self.COMPUTE_API_SC, AgentCheck.CRITICAL, tags=["keystone_server: {}".format(keystone_server_url)] + custom_tags, ) except MissingNeutronEndpoint: self.warning("The agent could not find a compatible Neutron endpoint in your service catalog!") self.service_check( self.NETWORK_API_SC, AgentCheck.CRITICAL, tags=["keystone_server: {}".format(keystone_server_url)] + custom_tags, ) if self._api is None: # Fast fail in the absence of an api raise IncompleteConfig()
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Guarantees a valid auth scope for this instance, and returns it Communicates with the identity server and initializes a new scope when one is absent, or has been forcibly removed due to token expiry
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python
train
PyGithub/PyGithub
github/AuthenticatedUser.py
https://github.com/PyGithub/PyGithub/blob/f716df86bbe7dc276c6596699fa9712b61ef974c/github/AuthenticatedUser.py#L383-L393
def add_to_following(self, following): """ :calls: `PUT /user/following/:user <http://developer.github.com/v3/users/followers>`_ :param following: :class:`github.NamedUser.NamedUser` :rtype: None """ assert isinstance(following, github.NamedUser.NamedUser), following headers, data = self._requester.requestJsonAndCheck( "PUT", "/user/following/" + following._identity )
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:calls: `PUT /user/following/:user <http://developer.github.com/v3/users/followers>`_ :param following: :class:`github.NamedUser.NamedUser` :rtype: None
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python
train
getpelican/pelican-plugins
render_math/math.py
https://github.com/getpelican/pelican-plugins/blob/cfc7a3f224f1743063b034561f89a6a712d13587/render_math/math.py#L319-L330
def rst_add_mathjax(content): """Adds mathjax script for reStructuredText""" # .rst is the only valid extension for reStructuredText files _, ext = os.path.splitext(os.path.basename(content.source_path)) if ext != '.rst': return # If math class is present in text, add the javascript # note that RST hardwires mathjax to be class "math" if 'class="math"' in content._content: content._content += "<script type='text/javascript'>%s</script>" % rst_add_mathjax.mathjax_script
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Adds mathjax script for reStructuredText
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python
train
ace0/pyrelic
pyrelic/ecqv.py
https://github.com/ace0/pyrelic/blob/f23d4e6586674675f72304d5938548267d6413bf/pyrelic/ecqv.py#L48-L81
def validate(idText, alpha, r, cert, caPubkey): """ A server can validate an implicit certificate response using identity string @idText, private value @alpha (used to generate cert request), and the certificate response @r (private key component) and implicit @cert. @raises Exception if the certificate response is invalid. @returns (privkey, pubkey) """ # Verify parameter types assertScalarType(alpha) assertScalarType(r) assertType(cert, ec1Element) assertType(caPubkey, ec1Element) G = generatorEc() # Compute the private key @s e = _exp(cert, idText) s = (e*alpha + r) % orderEc() # Compute the public key two ways: using the privkey and using the cert # (the way a client will compute it) # The easy way S1 = s*G # Using the cert S2 = e*cert + caPubkey # The two techniques should produce the same pubkey value -- raise an # exception if they don't match if S1 != S2: raise Exception("Implicit certification response failed validation") return s, S1
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python
train
Iotic-Labs/py-IoticAgent
src/IoticAgent/Core/Client.py
https://github.com/Iotic-Labs/py-IoticAgent/blob/893e8582ad1dacfe32dfc0ee89452bbd6f57d28d/src/IoticAgent/Core/Client.py#L1225-L1235
def __fire_callback(self, type_, *args, **kwargs): """Returns True if at least one callback was called""" called = False plain_submit = self.__threadpool.submit with self.__callbacks: submit = self.__crud_threadpool.submit if type_ in _CB_CRUD_TYPES else plain_submit for func, serialised_if_crud in self.__callbacks[type_]: called = True # allow CRUD callbacks to not be serialised if requested (submit if serialised_if_crud else plain_submit)(func, *args, **kwargs) return called
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Returns True if at least one callback was called
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python
train
DataONEorg/d1_python
lib_client/src/d1_client/cnclient.py
https://github.com/DataONEorg/d1_python/blob/3ac4d4f3ca052d3e8641a6a329cab526c8ddcb0d/lib_client/src/d1_client/cnclient.py#L622-L640
def listSubjectsResponse( self, query, status=None, start=None, count=None, vendorSpecific=None ): """CNIdentity.listSubjects(session, query, status, start, count) → SubjectList https://releases.dataone.org/online/api- documentation-v2.0.1/apis/CN_APIs.html#CNIdentity.listSubjects. Args: query: status: start: count: vendorSpecific: Returns: """ url_query = {'status': status, 'start': start, 'count': count, 'query': query} return self.GET('accounts', query=url_query, headers=vendorSpecific)
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CNIdentity.listSubjects(session, query, status, start, count) → SubjectList https://releases.dataone.org/online/api- documentation-v2.0.1/apis/CN_APIs.html#CNIdentity.listSubjects. Args: query: status: start: count: vendorSpecific: Returns:
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python
train
d0c-s4vage/pfp
pfp/interp.py
https://github.com/d0c-s4vage/pfp/blob/32f2d34fdec1c70019fa83c7006d5e3be0f92fcd/pfp/interp.py#L340-L351
def get_var(self, name, recurse=True): """Return the first var of name ``name`` in the current scope stack (remember, vars are the ones that parse the input stream) :name: The name of the id :recurse: Whether parent scopes should also be searched (defaults to True) :returns: TODO """ self._dlog("getting var '{}'".format(name)) return self._search("vars", name, recurse)
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Return the first var of name ``name`` in the current scope stack (remember, vars are the ones that parse the input stream) :name: The name of the id :recurse: Whether parent scopes should also be searched (defaults to True) :returns: TODO
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python
train
awslabs/aws-greengrass-group-setup
gg_group_setup/cmd.py
https://github.com/awslabs/aws-greengrass-group-setup/blob/06189ceccb794fedf80e0e7649938c18792e16c9/gg_group_setup/cmd.py#L773-L837
def create_devices(self, thing_names, config_file, region=None, cert_dir=None, append=False, account_id=None, policy_name='ggd-discovery-policy', profile_name=None): """ Using the `thing_names` values, creates Things in AWS IoT, attaches and downloads new keys & certs to the certificate directory, then records the created information in the local config file for inclusion in the Greengrass Group as Greengrass Devices. :param thing_names: the thing name or list of thing names to create and use as Greengrass Devices :param config_file: config file used to track the Greengrass Devices in the group :param region: the region in which to create the new devices. [default: us-west-2] :param cert_dir: the directory in which to store the thing's keys and certs. If `None` then use the current directory. :param append: append the created devices to the list of devices in the config file. [default: False] :param account_id: the account ID in which to create devices. If 'None' the config_file will be checked for an `account_id` value in the `misc` section. :param policy_name: the name of the policy to associate with the device. [default: 'ggd-discovery-policy'] :param profile_name: the name of the `awscli` profile to use. [default: None] """ logging.info("create_devices thing_names:{0}".format(thing_names)) config = GroupConfigFile(config_file=config_file) if append is False and config.is_device_fresh() is False: raise ValueError( "Config file tracking previously created devices. Append " "devices instead" ) if region is None: region = self._region if account_id is None: account_id = self._account_id devices = dict() if append: devices = config['devices'] if type(thing_names) is str: thing_names = [thing_names] iot_client = _get_iot_session(region=region, profile_name=profile_name) for thing_name in thing_names: keys_cert, thing = self.create_thing(thing_name, region, cert_dir) cert_arn = keys_cert['certificateArn'] devices[thing_name] = { 'thing_arn': thing['thingArn'], 'cert_arn': cert_arn, 'cert_id': keys_cert['certificateId'], 'thing_name': thing_name } logging.info("Thing:'{0}' associated with cert:'{1}'".format( thing_name, cert_arn)) device_policy = self.get_device_policy( device_name=thing_name, account_id=account_id, region=region ) self._create_attach_thing_policy(cert_arn, device_policy, iot_client, policy_name) config['devices'] = devices logging.info("create_devices cfg:{0}".format(config))
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Using the `thing_names` values, creates Things in AWS IoT, attaches and downloads new keys & certs to the certificate directory, then records the created information in the local config file for inclusion in the Greengrass Group as Greengrass Devices. :param thing_names: the thing name or list of thing names to create and use as Greengrass Devices :param config_file: config file used to track the Greengrass Devices in the group :param region: the region in which to create the new devices. [default: us-west-2] :param cert_dir: the directory in which to store the thing's keys and certs. If `None` then use the current directory. :param append: append the created devices to the list of devices in the config file. [default: False] :param account_id: the account ID in which to create devices. If 'None' the config_file will be checked for an `account_id` value in the `misc` section. :param policy_name: the name of the policy to associate with the device. [default: 'ggd-discovery-policy'] :param profile_name: the name of the `awscli` profile to use. [default: None]
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python
train
tomplus/kubernetes_asyncio
kubernetes_asyncio/client/api/extensions_v1beta1_api.py
https://github.com/tomplus/kubernetes_asyncio/blob/f9ab15317ec921409714c7afef11aeb0f579985d/kubernetes_asyncio/client/api/extensions_v1beta1_api.py#L1243-L1272
def delete_collection_namespaced_network_policy(self, namespace, **kwargs): # noqa: E501 """delete_collection_namespaced_network_policy # noqa: E501 delete collection of NetworkPolicy # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_collection_namespaced_network_policy(namespace, async_req=True) >>> result = thread.get() :param async_req bool :param str namespace: object name and auth scope, such as for teams and projects (required) :param bool include_uninitialized: If true, partially initialized resources are included in the response. :param str pretty: If 'true', then the output is pretty printed. :param str _continue: The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a previous query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the next key, but from the latest snapshot, which is inconsistent from the previous list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the \"next key\". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. :param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything. :param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything. :param int limit: limit is a maximum number of responses to return for a list call. If more items exist, the server will set the `continue` field on the list metadata to a value that can be used with the same initial query to retrieve the next set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. :param str resource_version: When specified with a watch call, shows changes that occur after that particular version of a resource. Defaults to changes from the beginning of history. When specified for list: - if unset, then the result is returned from remote storage based on quorum-read flag; - if it's 0, then we simply return what we currently have in cache, no guarantee; - if set to non zero, then the result is at least as fresh as given rv. :param int timeout_seconds: Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. :param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. :return: V1Status If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_collection_namespaced_network_policy_with_http_info(namespace, **kwargs) # noqa: E501 else: (data) = self.delete_collection_namespaced_network_policy_with_http_info(namespace, **kwargs) # noqa: E501 return data
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delete_collection_namespaced_network_policy # noqa: E501 delete collection of NetworkPolicy # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_collection_namespaced_network_policy(namespace, async_req=True) >>> result = thread.get() :param async_req bool :param str namespace: object name and auth scope, such as for teams and projects (required) :param bool include_uninitialized: If true, partially initialized resources are included in the response. :param str pretty: If 'true', then the output is pretty printed. :param str _continue: The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a previous query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the next key, but from the latest snapshot, which is inconsistent from the previous list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the \"next key\". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. :param str field_selector: A selector to restrict the list of returned objects by their fields. Defaults to everything. :param str label_selector: A selector to restrict the list of returned objects by their labels. Defaults to everything. :param int limit: limit is a maximum number of responses to return for a list call. If more items exist, the server will set the `continue` field on the list metadata to a value that can be used with the same initial query to retrieve the next set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. :param str resource_version: When specified with a watch call, shows changes that occur after that particular version of a resource. Defaults to changes from the beginning of history. When specified for list: - if unset, then the result is returned from remote storage based on quorum-read flag; - if it's 0, then we simply return what we currently have in cache, no guarantee; - if set to non zero, then the result is at least as fresh as given rv. :param int timeout_seconds: Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. :param bool watch: Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. :return: V1Status If the method is called asynchronously, returns the request thread.
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python
train
datacamp/antlr-ast
antlr_ast/ast.py
https://github.com/datacamp/antlr-ast/blob/d08d5eb2e663bd40501d0eeddc8a731ac7e96b11/antlr_ast/ast.py#L629-L632
def visitTerminal(self, ctx): """Converts case insensitive keywords and identifiers to lowercase""" text = ctx.getText() return Terminal.from_text(text, ctx)
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Converts case insensitive keywords and identifiers to lowercase
[ "Converts", "case", "insensitive", "keywords", "and", "identifiers", "to", "lowercase" ]
python
train
gmr/tinman
tinman/application.py
https://github.com/gmr/tinman/blob/98f0acd15a228d752caa1864cdf02aaa3d492a9f/tinman/application.py#L216-L219
def _prepare_transforms(self): """Prepare the list of transforming objects""" for offset, value in enumerate(self._config.get(config.TRANSFORMS, [])): self._config[config.TRANSFORMS][offset] = self._import_class(value)
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Prepare the list of transforming objects
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python
train
matthew-brett/delocate
delocate/delocating.py
https://github.com/matthew-brett/delocate/blob/ed48de15fce31c3f52f1a9f32cae1b02fc55aa60/delocate/delocating.py#L508-L552
def bads_report(bads, path_prefix=None): """ Return a nice report of bad architectures in `bads` Parameters ---------- bads : set set of length 2 or 3 tuples. A length 2 tuple is of form ``(depending_lib, missing_archs)`` meaning that an arch in `require_archs` was missing from ``depending_lib``. A length 3 tuple is of form ``(depended_lib, depending_lib, missing_archs)`` where ``depended_lib`` is the filename of the library depended on, ``depending_lib`` is the library depending on ``depending_lib`` and ``missing_archs`` is a set of missing architecture strings giving architectures present in ``depending_lib`` and missing in ``depended_lib``. An empty set means all architectures were present as required. path_prefix : None or str, optional Path prefix to strip from ``depended_lib`` and ``depending_lib``. None means do not strip anything. Returns ------- report : str A nice report for printing """ path_processor = ((lambda x : x) if path_prefix is None else get_rp_stripper(path_prefix)) reports = [] for result in bads: if len(result) == 3: depended_lib, depending_lib, missing_archs = result reports.append("{0} needs {1} {2} missing from {3}".format( path_processor(depending_lib), 'archs' if len(missing_archs) > 1 else 'arch', ', '.join(sorted(missing_archs)), path_processor(depended_lib))) elif len(result) == 2: depending_lib, missing_archs = result reports.append("Required {0} {1} missing from {2}".format( 'archs' if len(missing_archs) > 1 else 'arch', ', '.join(sorted(missing_archs)), path_processor(depending_lib))) else: raise ValueError('Report tuple should be length 2 or 3') return '\n'.join(sorted(reports))
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Return a nice report of bad architectures in `bads` Parameters ---------- bads : set set of length 2 or 3 tuples. A length 2 tuple is of form ``(depending_lib, missing_archs)`` meaning that an arch in `require_archs` was missing from ``depending_lib``. A length 3 tuple is of form ``(depended_lib, depending_lib, missing_archs)`` where ``depended_lib`` is the filename of the library depended on, ``depending_lib`` is the library depending on ``depending_lib`` and ``missing_archs`` is a set of missing architecture strings giving architectures present in ``depending_lib`` and missing in ``depended_lib``. An empty set means all architectures were present as required. path_prefix : None or str, optional Path prefix to strip from ``depended_lib`` and ``depending_lib``. None means do not strip anything. Returns ------- report : str A nice report for printing
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python
train
GreatFruitOmsk/tailhead
tailhead/__init__.py
https://github.com/GreatFruitOmsk/tailhead/blob/a3b1324a39935f8ffcfda59328a9a458672889d9/tailhead/__init__.py#L143-L196
def seek_previous_line(self): """ Seek previous line relative to the current file position. :return: Position of the line or -1 if previous line was not found. """ where = self.file.tell() offset = 0 while True: if offset == where: break read_size = self.read_size if self.read_size <= where else where self.file.seek(where - offset - read_size, SEEK_SET) data_len, data = self.read(read_size) # Consider the following example: Foo\r | \nBar where " | " denotes current position, # '\nBar' is the read part and 'Foo\r' is the remaining part. # We should completely consume terminator "\r\n" by reading one extra byte. if b'\r\n' in self.LINE_TERMINATORS and data[0] == b'\n'[0]: terminator_where = self.file.tell() if terminator_where > data_len + 1: self.file.seek(where - offset - data_len - 1, SEEK_SET) terminator_len, terminator_data = self.read(1) if terminator_data[0] == b'\r'[0]: data_len += 1 data = b'\r' + data self.file.seek(terminator_where) data_where = data_len while data_where > 0: terminator = self.suffix_line_terminator(data[:data_where]) if terminator and offset == 0 and data_where == data_len: # The last character is a line terminator that finishes current line. Ignore it. data_where -= len(terminator) elif terminator: self.file.seek(where - offset - (data_len - data_where)) return self.file.tell() else: data_where -= 1 offset += data_len if where == 0: # Nothing more to read. return -1 else: # Very first line. self.file.seek(0) return 0
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Seek previous line relative to the current file position. :return: Position of the line or -1 if previous line was not found.
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python
test
fprimex/zdesk
zdesk/zdesk_api.py
https://github.com/fprimex/zdesk/blob/851611c13b4d530e9df31390b3ec709baf0a0188/zdesk/zdesk_api.py#L822-L825
def community_post_create(self, data, **kwargs): "https://developer.zendesk.com/rest_api/docs/help_center/posts#create-post" api_path = "/api/v2/community/posts.json" return self.call(api_path, method="POST", data=data, **kwargs)
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https://developer.zendesk.com/rest_api/docs/help_center/posts#create-post
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python
train
molmod/molmod
molmod/unit_cells.py
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/unit_cells.py#L203-L218
def alignment_a(self): """Computes the rotation matrix that aligns the unit cell with the Cartesian axes, starting with cell vector a. * a parallel to x * b in xy-plane with b_y positive * c with c_z positive """ from molmod.transformations import Rotation new_x = self.matrix[:, 0].copy() new_x /= np.linalg.norm(new_x) new_z = np.cross(new_x, self.matrix[:, 1]) new_z /= np.linalg.norm(new_z) new_y = np.cross(new_z, new_x) new_y /= np.linalg.norm(new_y) return Rotation(np.array([new_x, new_y, new_z]))
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Computes the rotation matrix that aligns the unit cell with the Cartesian axes, starting with cell vector a. * a parallel to x * b in xy-plane with b_y positive * c with c_z positive
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python
train
hatemile/hatemile-for-python
hatemile/implementation/assoc.py
https://github.com/hatemile/hatemile-for-python/blob/1e914f9aa09f6f8d78282af131311546ecba9fb8/hatemile/implementation/assoc.py#L136-L158
def _validate_header(self, hed): """ Validate the list that represents the table header. :param hed: The list that represents the table header. :type hed: list(list(hatemile.util.html.htmldomelement.HTMLDOMElement)) :return: True if the table header is valid or False if the table header is not valid. :rtype: bool """ # pylint: disable=no-self-use if not bool(hed): return False length = -1 for row in hed: if not bool(row): return False elif length == -1: length = len(row) elif len(row) != length: return False return True
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Validate the list that represents the table header. :param hed: The list that represents the table header. :type hed: list(list(hatemile.util.html.htmldomelement.HTMLDOMElement)) :return: True if the table header is valid or False if the table header is not valid. :rtype: bool
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python
train
mattupstate/cubric
cubric/tasks.py
https://github.com/mattupstate/cubric/blob/a648ce00e4467cd14d71e754240ef6c1f87a34b5/cubric/tasks.py#L11-L17
def create_server(initialize=True): """Create a server""" with provider() as p: host_string = p.create_server() if initialize: env.host_string = host_string initialize_server()
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Create a server
[ "Create", "a", "server" ]
python
train
dswah/pyGAM
pygam/pygam.py
https://github.com/dswah/pyGAM/blob/b3e5c3cd580f0a3ad69f9372861624f67760c325/pygam/pygam.py#L2686-L2718
def predict(self, X, exposure=None): """ preduct expected value of target given model and input X often this is done via expected value of GAM given input X Parameters --------- X : array-like of shape (n_samples, m_features), default: None containing the input dataset exposure : array-like shape (n_samples,) or None, default: None containing exposures if None, defaults to array of ones Returns ------- y : np.array of shape (n_samples,) containing predicted values under the model """ if not self._is_fitted: raise AttributeError('GAM has not been fitted. Call fit first.') X = check_X(X, n_feats=self.statistics_['m_features'], edge_knots=self.edge_knots_, dtypes=self.dtype, features=self.feature, verbose=self.verbose) if exposure is not None: exposure = np.array(exposure).astype('f') else: exposure = np.ones(X.shape[0]).astype('f') check_lengths(X, exposure) return self.predict_mu(X) * exposure
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preduct expected value of target given model and input X often this is done via expected value of GAM given input X Parameters --------- X : array-like of shape (n_samples, m_features), default: None containing the input dataset exposure : array-like shape (n_samples,) or None, default: None containing exposures if None, defaults to array of ones Returns ------- y : np.array of shape (n_samples,) containing predicted values under the model
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python
train
saltstack/salt
salt/states/pip_state.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/states/pip_state.py#L964-L1019
def removed(name, requirements=None, bin_env=None, log=None, proxy=None, timeout=None, user=None, cwd=None, use_vt=False): ''' Make sure that a package is not installed. name The name of the package to uninstall user The user under which to run pip bin_env : None the pip executable or virtualenenv to use use_vt Use VT terminal emulation (see output while installing) ''' ret = {'name': name, 'result': None, 'comment': '', 'changes': {}} try: pip_list = __salt__['pip.list'](bin_env=bin_env, user=user, cwd=cwd) except (CommandExecutionError, CommandNotFoundError) as err: ret['result'] = False ret['comment'] = 'Error uninstalling \'{0}\': {1}'.format(name, err) return ret if name not in pip_list: ret['result'] = True ret['comment'] = 'Package is not installed.' return ret if __opts__['test']: ret['result'] = None ret['comment'] = 'Package {0} is set to be removed'.format(name) return ret if __salt__['pip.uninstall'](pkgs=name, requirements=requirements, bin_env=bin_env, log=log, proxy=proxy, timeout=timeout, user=user, cwd=cwd, use_vt=use_vt): ret['result'] = True ret['changes'][name] = 'Removed' ret['comment'] = 'Package was successfully removed.' else: ret['result'] = False ret['comment'] = 'Could not remove package.' return ret
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python
train
dgraph-io/pydgraph
pydgraph/client_stub.py
https://github.com/dgraph-io/pydgraph/blob/0fe85f6593cb2148475750bc8555a6fdf509054b/pydgraph/client_stub.py#L58-L62
def commit_or_abort(self, ctx, timeout=None, metadata=None, credentials=None): """Runs commit or abort operation.""" return self.stub.CommitOrAbort(ctx, timeout=timeout, metadata=metadata, credentials=credentials)
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Runs commit or abort operation.
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python
train
thoth-station/solver
thoth/solver/compile.py
https://github.com/thoth-station/solver/blob/de9bd6e744cb4d5f70320ba77d6875ccb8b876c4/thoth/solver/compile.py#L30-L52
def pip_compile(*packages: str): """Run pip-compile to pin down packages, also resolve their transitive dependencies.""" result = None packages = "\n".join(packages) with tempfile.TemporaryDirectory() as tmp_dirname, cwd(tmp_dirname): with open("requirements.in", "w") as requirements_file: requirements_file.write(packages) runner = CliRunner() try: result = runner.invoke(cli, ["requirements.in"], catch_exceptions=False) except Exception as exc: raise ThothPipCompileError(str(exc)) from exc if result.exit_code != 0: error_msg = ( f"pip-compile returned non-zero ({result.exit_code:d}) " f"output: {result.output_bytes.decode():s}" ) raise ThothPipCompileError(error_msg) return result.output_bytes.decode()
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Run pip-compile to pin down packages, also resolve their transitive dependencies.
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python
train
pytroll/satpy
satpy/readers/hrpt.py
https://github.com/pytroll/satpy/blob/1f21d20ac686b745fb0da9b4030d139893e066dd/satpy/readers/hrpt.py#L66-L82
def time_seconds(tc_array, year): """Return the time object from the timecodes """ tc_array = np.array(tc_array, copy=True) word = tc_array[:, 0] day = word >> 1 word = tc_array[:, 1].astype(np.uint64) msecs = ((127) & word) * 1024 word = tc_array[:, 2] msecs += word & 1023 msecs *= 1024 word = tc_array[:, 3] msecs += word & 1023 return (np.datetime64( str(year) + '-01-01T00:00:00Z', 's') + msecs[:].astype('timedelta64[ms]') + (day - 1)[:].astype('timedelta64[D]'))
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Return the time object from the timecodes
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python
train
saltstack/salt
salt/modules/boto3_sns.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/boto3_sns.py#L350-L383
def unsubscribe(SubscriptionArn, region=None, key=None, keyid=None, profile=None): ''' Unsubscribe a specific SubscriptionArn of a topic. CLI Example: .. code-block:: bash salt myminion boto3_sns.unsubscribe my_subscription_arn region=us-east-1 ''' if not SubscriptionArn.startswith('arn:aws:sns:'): # Grrr, AWS sent us an ARN that's NOT and ARN.... # This can happen if, for instance, a subscription is left in PendingAcceptance or similar # Note that anything left in PendingConfirmation will be auto-deleted by AWS after 30 days # anyway, so this isn't as ugly a hack as it might seem at first... log.info('Invalid subscription ARN `%s` passed - likely a PendingConfirmaton or such. ' 'Skipping unsubscribe attempt as it would almost certainly fail...', SubscriptionArn) return True subs = list_subscriptions(region=region, key=key, keyid=keyid, profile=profile) sub = [s for s in subs if s.get('SubscriptionArn') == SubscriptionArn] if not sub: log.error('Subscription ARN %s not found', SubscriptionArn) return False TopicArn = sub[0]['TopicArn'] conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) try: conn.unsubscribe(SubscriptionArn=SubscriptionArn) log.info('Deleted subscription %s from SNS topic %s', SubscriptionArn, TopicArn) return True except botocore.exceptions.ClientError as e: log.error('Failed to delete subscription %s: %s', SubscriptionArn, e) return False
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Unsubscribe a specific SubscriptionArn of a topic. CLI Example: .. code-block:: bash salt myminion boto3_sns.unsubscribe my_subscription_arn region=us-east-1
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python
train
SiLab-Bonn/pyBAR
pybar/fei4/register_utils.py
https://github.com/SiLab-Bonn/pyBAR/blob/5ad95bbcd41cd358825823fb78f396cfce23593e/pybar/fei4/register_utils.py#L770-L797
def make_box_pixel_mask_from_col_row(column, row, default=0, value=1): '''Generate box shaped mask from column and row lists. Takes the minimum and maximum value from each list. Parameters ---------- column : iterable, int List of colums values. row : iterable, int List of row values. default : int Value of pixels that are not selected by the mask. value : int Value of pixels that are selected by the mask. Returns ------- numpy.ndarray ''' # FE columns and rows start from 1 col_array = np.array(column) - 1 row_array = np.array(row) - 1 if np.any(col_array >= 80) or np.any(col_array < 0) or np.any(row_array >= 336) or np.any(row_array < 0): raise ValueError('Column and/or row out of range') shape = (80, 336) mask = np.full(shape, default, dtype=np.uint8) if column and row: mask[col_array.min():col_array.max() + 1, row_array.min():row_array.max() + 1] = value # advanced indexing return mask
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python
train
ArduPilot/MAVProxy
MAVProxy/modules/mavproxy_heliplane.py
https://github.com/ArduPilot/MAVProxy/blob/f50bdeff33064876f7dc8dc4683d278ff47f75d5/MAVProxy/modules/mavproxy_heliplane.py#L102-L130
def update_channels(self): '''update which channels provide input''' self.interlock_channel = -1 self.override_channel = -1 self.zero_I_channel = -1 self.no_vtol_channel = -1 # output channels self.rsc_out_channel = 9 self.fwd_thr_channel = 10 for ch in range(1,16): option = self.get_mav_param("RC%u_OPTION" % ch, 0) if option == 32: self.interlock_channel = ch; elif option == 63: self.override_channel = ch; elif option == 64: self.zero_I_channel = ch; elif option == 65: self.override_channel = ch; elif option == 66: self.no_vtol_channel = ch; function = self.get_mav_param("SERVO%u_FUNCTION" % ch, 0) if function == 32: self.rsc_out_channel = ch if function == 70: self.fwd_thr_channel = ch
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update which channels provide input
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python
train
OpenTreeOfLife/peyotl
peyotl/amendments/amendments_shard.py
https://github.com/OpenTreeOfLife/peyotl/blob/5e4e52a0fdbd17f490aa644ad79fda6ea2eda7c0/peyotl/amendments/amendments_shard.py#L161-L177
def _mint_new_ott_ids(self, how_many=1): """ ASSUMES the caller holds the _doc_counter_lock ! Checks the current int value of the next ottid, reserves a block of {how_many} ids, advances the counter to the next available value, stores the counter in a file in case the server is restarted. Checks out master branch as a side effect.""" first_minted_id = self._next_ott_id self._next_ott_id = first_minted_id + how_many content = u'{"next_ott_id": %d}\n' % self._next_ott_id # The content is JSON, but we hand-rolled the string above # so that we can use it as a commit_msg self._write_master_branch_resource(content, self._id_minting_file, commit_msg=content, is_json=False) last_minted_id = self._next_ott_id - 1 return first_minted_id, last_minted_id
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ASSUMES the caller holds the _doc_counter_lock ! Checks the current int value of the next ottid, reserves a block of {how_many} ids, advances the counter to the next available value, stores the counter in a file in case the server is restarted. Checks out master branch as a side effect.
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python
train
square/pylink
pylink/__main__.py
https://github.com/square/pylink/blob/81dda0a191d923a8b2627c52cb778aba24d279d7/pylink/__main__.py#L172-L184
def run(self, args): """Erases the device connected to the J-Link. Args: self (EraseCommand): the ``EraseCommand`` instance args (Namespace): the arguments passed on the command-line Returns: ``None`` """ jlink = self.create_jlink(args) erased = jlink.erase() print('Bytes Erased: %d' % erased)
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Erases the device connected to the J-Link. Args: self (EraseCommand): the ``EraseCommand`` instance args (Namespace): the arguments passed on the command-line Returns: ``None``
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python
train
honzajavorek/redis-collections
redis_collections/lists.py
https://github.com/honzajavorek/redis-collections/blob/07ca8efe88fb128f7dc7319dfa6a26cd39b3776b/redis_collections/lists.py#L739-L744
def append(self, value): """Add *value* to the right side of the collection.""" def append_trans(pipe): self._append_helper(value, pipe) self._transaction(append_trans)
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Add *value* to the right side of the collection.
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python
train
Qiskit/qiskit-api-py
IBMQuantumExperience/IBMQuantumExperience.py
https://github.com/Qiskit/qiskit-api-py/blob/2ab240110fb7e653254e44c4833f3643e8ae7f0f/IBMQuantumExperience/IBMQuantumExperience.py#L22-L34
def get_job_url(config, hub, group, project): """ Util method to get job url """ if ((config is not None) and ('hub' in config) and (hub is None)): hub = config["hub"] if ((config is not None) and ('group' in config) and (group is None)): group = config["group"] if ((config is not None) and ('project' in config) and (project is None)): project = config["project"] if ((hub is not None) and (group is not None) and (project is not None)): return '/Network/{}/Groups/{}/Projects/{}/jobs'.format(hub, group, project) return '/Jobs'
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Util method to get job url
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python
train