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project-rig/rig
rig/machine_control/bmp_controller.py
https://github.com/project-rig/rig/blob/3a3e053d3214899b6d68758685835de0afd5542b/rig/machine_control/bmp_controller.py#L125-L145
def send_scp(self, *args, **kwargs): """Transmit an SCP Packet to a specific board. Automatically determines the appropriate connection to use. See the arguments for :py:meth:`~rig.machine_control.scp_connection.SCPConnection` for details. Parameters ---------- cabinet : int frame : int board : int """ # Retrieve contextual arguments from the keyword arguments. The # context system ensures that these values are present. cabinet = kwargs.pop("cabinet") frame = kwargs.pop("frame") board = kwargs.pop("board") return self._send_scp(cabinet, frame, board, *args, **kwargs)
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Transmit an SCP Packet to a specific board. Automatically determines the appropriate connection to use. See the arguments for :py:meth:`~rig.machine_control.scp_connection.SCPConnection` for details. Parameters ---------- cabinet : int frame : int board : int
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python
train
DataDog/integrations-core
ntp/datadog_checks/ntp/ntp.py
https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/ntp/datadog_checks/ntp/ntp.py#L23-L36
def _get_service_port(self, instance): """ Get the ntp server port """ host = instance.get('host', DEFAULT_HOST) port = instance.get('port', DEFAULT_PORT) # default port is the name of the service but lookup would fail # if the /etc/services file is missing. In that case, fallback to numeric try: socket.getaddrinfo(host, port) except socket.gaierror: port = DEFAULT_PORT_NUM return port
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Get the ntp server port
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python
train
eruvanos/openbrokerapi
openbrokerapi/service_broker.py
https://github.com/eruvanos/openbrokerapi/blob/29d514e5932f2eac27e03995dd41c8cecf40bb10/openbrokerapi/service_broker.py#L296-L306
def update(self, instance_id: str, details: UpdateDetails, async_allowed: bool) -> UpdateServiceSpec: """ Further readings `CF Broker API#Update <https://docs.cloudfoundry.org/services/api.html#updating_service_instance>`_ :param instance_id: Instance id provided by the platform :param details: Details about the service to update :param async_allowed: Client allows async creation :rtype: UpdateServiceSpec :raises ErrAsyncRequired: If async is required but not supported """ raise NotImplementedError()
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Further readings `CF Broker API#Update <https://docs.cloudfoundry.org/services/api.html#updating_service_instance>`_ :param instance_id: Instance id provided by the platform :param details: Details about the service to update :param async_allowed: Client allows async creation :rtype: UpdateServiceSpec :raises ErrAsyncRequired: If async is required but not supported
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python
train
gwastro/pycbc-glue
pycbc_glue/segments.py
https://github.com/gwastro/pycbc-glue/blob/a3e906bae59fbfd707c3ff82e5d008d939ec5e24/pycbc_glue/segments.py#L1141-L1152
def all_intersects_all(self, other): """ Returns True if self and other have the same keys, and each segmentlist intersects the corresponding segmentlist in the other; returns False if this is not the case or if either dictionary is empty. See also: .intersects(), .all_intersects(), .intersects_all() """ return set(self) == set(other) and all(other[key].intersects(value) for key, value in self.iteritems()) and bool(self)
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Returns True if self and other have the same keys, and each segmentlist intersects the corresponding segmentlist in the other; returns False if this is not the case or if either dictionary is empty. See also: .intersects(), .all_intersects(), .intersects_all()
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python
train
openpaperwork/paperwork-backend
paperwork_backend/img/page.py
https://github.com/openpaperwork/paperwork-backend/blob/114b831e94e039e68b339751fd18250877abad76/paperwork_backend/img/page.py#L95-L120
def __get_boxes(self): """ Get all the word boxes of this page. """ boxfile = self.__box_path try: box_builder = pyocr.builders.LineBoxBuilder() with self.fs.open(boxfile, 'r') as file_desc: boxes = box_builder.read_file(file_desc) if boxes != []: return boxes # fallback: old format: word boxes # shouldn't be used anymore ... box_builder = pyocr.builders.WordBoxBuilder() with self.fs.open(boxfile, 'r') as file_desc: boxes = box_builder.read_file(file_desc) if len(boxes) <= 0: return [] logger.warning("WARNING: Doc %s uses old box format" % (str(self.doc))) return [pyocr.builders.LineBox(boxes, boxes[0].position)] except IOError as exc: logger.error("Unable to get boxes for '%s': %s" % (self.doc.docid, exc)) return []
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Get all the word boxes of this page.
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python
train
jantman/awslimitchecker
awslimitchecker/services/elb.py
https://github.com/jantman/awslimitchecker/blob/e50197f70f3d0abcc5cfc7fde6336f548b790e34/awslimitchecker/services/elb.py#L225-L249
def _update_usage_for_nlb(self, conn, nlb_arn, nlb_name): """ Update usage for a single NLB. :param conn: elbv2 API connection :type conn: :py:class:`ElasticLoadBalancing.Client` :param nlb_arn: Load Balancer ARN :type nlb_arn: str :param nlb_name: Load Balancer Name :type nlb_name: str """ logger.debug('Updating usage for NLB %s', nlb_arn) listeners = paginate_dict( conn.describe_listeners, LoadBalancerArn=nlb_arn, alc_marker_path=['NextMarker'], alc_data_path=['Listeners'], alc_marker_param='Marker' )['Listeners'] self.limits[ 'Listeners per network load balancer']._add_current_usage( len(listeners), aws_type='AWS::ElasticLoadBalancingV2::NetworkLoadBalancer', resource_id=nlb_name )
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Update usage for a single NLB. :param conn: elbv2 API connection :type conn: :py:class:`ElasticLoadBalancing.Client` :param nlb_arn: Load Balancer ARN :type nlb_arn: str :param nlb_name: Load Balancer Name :type nlb_name: str
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python
train
mohamedattahri/PyXMLi
pyxmli/__init__.py
https://github.com/mohamedattahri/PyXMLi/blob/a81a245be822d62f1a20c734ca14b42c786ae81e/pyxmli/__init__.py#L624-L632
def __set_identifier(self, value): ''' Sets the ID of the invoice. @param value:str ''' if not value or not len(value): raise ValueError("Invalid invoice ID") self.__identifier = value
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Sets the ID of the invoice. @param value:str
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/zmq/session.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/zmq/session.py#L438-L492
def serialize(self, msg, ident=None): """Serialize the message components to bytes. This is roughly the inverse of unserialize. The serialize/unserialize methods work with full message lists, whereas pack/unpack work with the individual message parts in the message list. Parameters ---------- msg : dict or Message The nexted message dict as returned by the self.msg method. Returns ------- msg_list : list The list of bytes objects to be sent with the format: [ident1,ident2,...,DELIM,HMAC,p_header,p_parent,p_content, buffer1,buffer2,...]. In this list, the p_* entities are the packed or serialized versions, so if JSON is used, these are utf8 encoded JSON strings. """ content = msg.get('content', {}) if content is None: content = self.none elif isinstance(content, dict): content = self.pack(content) elif isinstance(content, bytes): # content is already packed, as in a relayed message pass elif isinstance(content, unicode): # should be bytes, but JSON often spits out unicode content = content.encode('utf8') else: raise TypeError("Content incorrect type: %s"%type(content)) real_message = [self.pack(msg['header']), self.pack(msg['parent_header']), content ] to_send = [] if isinstance(ident, list): # accept list of idents to_send.extend(ident) elif ident is not None: to_send.append(ident) to_send.append(DELIM) signature = self.sign(real_message) to_send.append(signature) to_send.extend(real_message) return to_send
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Serialize the message components to bytes. This is roughly the inverse of unserialize. The serialize/unserialize methods work with full message lists, whereas pack/unpack work with the individual message parts in the message list. Parameters ---------- msg : dict or Message The nexted message dict as returned by the self.msg method. Returns ------- msg_list : list The list of bytes objects to be sent with the format: [ident1,ident2,...,DELIM,HMAC,p_header,p_parent,p_content, buffer1,buffer2,...]. In this list, the p_* entities are the packed or serialized versions, so if JSON is used, these are utf8 encoded JSON strings.
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python
test
prompt-toolkit/pymux
pymux/client/posix.py
https://github.com/prompt-toolkit/pymux/blob/3f66e62b9de4b2251c7f9afad6c516dc5a30ec67/pymux/client/posix.py#L160-L173
def _process_stdin(self): """ Received data on stdin. Read and send to server. """ with nonblocking(sys.stdin.fileno()): data = self._stdin_reader.read() # Send input in chunks of 4k. step = 4056 for i in range(0, len(data), step): self._send_packet({ 'cmd': 'in', 'data': data[i:i + step], })
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Received data on stdin. Read and send to server.
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python
train
tcalmant/ipopo
pelix/ipopo/handlers/provides.py
https://github.com/tcalmant/ipopo/blob/2f9ae0c44cd9c34ef1a9d50837b3254e75678eb1/pelix/ipopo/handlers/provides.py#L154-L187
def _field_controller_generator(self): """ Generates the methods called by the injected controller """ # Local variable, to avoid messing with "self" stored_instance = self._ipopo_instance def get_value(self, name): # pylint: disable=W0613 """ Retrieves the controller value, from the iPOPO dictionaries :param name: The property name :return: The property value """ return stored_instance.get_controller_state(name) def set_value(self, name, new_value): # pylint: disable=W0613 """ Sets the property value and trigger an update event :param name: The property name :param new_value: The new property value """ # Get the previous value old_value = stored_instance.get_controller_state(name) if new_value != old_value: # Update the controller state stored_instance.set_controller_state(name, new_value) return new_value return get_value, set_value
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Generates the methods called by the injected controller
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python
train
mukulhase/WebWhatsapp-Wrapper
sample/flask/webapi.py
https://github.com/mukulhase/WebWhatsapp-Wrapper/blob/81b918ee4e0cd0cb563807a72baa167f670d70cb/sample/flask/webapi.py#L518-L527
def get_unread_messages(): """Get all unread messages""" mark_seen = request.args.get('mark_seen', True) unread_msg = g.driver.get_unread() if mark_seen: for msg in unread_msg: msg.chat.send_seen() return jsonify(unread_msg)
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Get all unread messages
[ "Get", "all", "unread", "messages" ]
python
train
numenta/nupic
examples/opf/experiments/missing_record/make_datasets.py
https://github.com/numenta/nupic/blob/5922fafffdccc8812e72b3324965ad2f7d4bbdad/examples/opf/experiments/missing_record/make_datasets.py#L35-L110
def _generateSimple(filename="simple.csv", numSequences=1, elementsPerSeq=3, numRepeats=10): """ Generate a simple dataset. This contains a bunch of non-overlapping sequences. At the end of the dataset, we introduce missing records so that test code can insure that the model didn't get confused by them. Parameters: ---------------------------------------------------- filename: name of the file to produce, including extension. It will be created in a 'datasets' sub-directory within the directory containing this script. numSequences: how many sequences to generate elementsPerSeq: length of each sequence numRepeats: how many times to repeat each sequence in the output """ # Create the output file scriptDir = os.path.dirname(__file__) pathname = os.path.join(scriptDir, 'datasets', filename) print "Creating %s..." % (pathname) fields = [('timestamp', 'datetime', 'T'), ('field1', 'string', ''), ('field2', 'float', '')] outFile = FileRecordStream(pathname, write=True, fields=fields) # Create the sequences sequences = [] for i in range(numSequences): seq = [x for x in range(i*elementsPerSeq, (i+1)*elementsPerSeq)] sequences.append(seq) # Write out the sequences in random order seqIdxs = [] for i in range(numRepeats): seqIdxs += range(numSequences) random.shuffle(seqIdxs) # Put 1 hour between each record timestamp = datetime.datetime(year=2012, month=1, day=1, hour=0, minute=0, second=0) timeDelta = datetime.timedelta(hours=1) # Write out the sequences without missing records for seqIdx in seqIdxs: seq = sequences[seqIdx] for x in seq: outFile.appendRecord([timestamp, str(x), x]) timestamp += timeDelta # Now, write some out with missing records for seqIdx in seqIdxs: seq = sequences[seqIdx] for i,x in enumerate(seq): if i != 1: outFile.appendRecord([timestamp, str(x), x]) timestamp += timeDelta for seqIdx in seqIdxs: seq = sequences[seqIdx] for i,x in enumerate(seq): if i != 1: outFile.appendRecord([timestamp, str(x), x]) timestamp += timeDelta # Write out some more of the sequences *without* missing records for seqIdx in seqIdxs: seq = sequences[seqIdx] for x in seq: outFile.appendRecord([timestamp, str(x), x]) timestamp += timeDelta outFile.close()
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Generate a simple dataset. This contains a bunch of non-overlapping sequences. At the end of the dataset, we introduce missing records so that test code can insure that the model didn't get confused by them. Parameters: ---------------------------------------------------- filename: name of the file to produce, including extension. It will be created in a 'datasets' sub-directory within the directory containing this script. numSequences: how many sequences to generate elementsPerSeq: length of each sequence numRepeats: how many times to repeat each sequence in the output
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python
valid
NetEaseGame/ATX
atx/cmds/tkgui.py
https://github.com/NetEaseGame/ATX/blob/f4415c57b45cb0730e08899cbc92a2af1c047ffb/atx/cmds/tkgui.py#L41-L58
def insert_code(filename, code, save=True, marker='# ATX CODE END'): """ Auto append code """ content = '' found = False for line in open(filename, 'rb'): if not found and line.strip() == marker: found = True cnt = line.find(marker) content += line[:cnt] + code content += line if not found: if not content.endswith('\n'): content += '\n' content += code + marker + '\n' if save: with open(filename, 'wb') as f: f.write(content) return content
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Auto append code
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python
train
hydraplatform/hydra-base
hydra_base/db/model.py
https://github.com/hydraplatform/hydra-base/blob/9251ff7946505f7a272c87837390acd1c435bc6e/hydra_base/db/model.py#L909-L928
def add_group(self, name, desc, status): """ Add a new group to a network. """ existing_group = get_session().query(ResourceGroup).filter(ResourceGroup.name==name, ResourceGroup.network_id==self.id).first() if existing_group is not None: raise HydraError("A resource group with name %s is already in network %s"%(name, self.id)) group_i = ResourceGroup() group_i.name = name group_i.description = desc group_i.status = status get_session().add(group_i) self.resourcegroups.append(group_i) return group_i
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Add a new group to a network.
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python
train
saltstack/salt
salt/modules/xml.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/xml.py#L85-L103
def set_attribute(file, element, key, value): ''' Set the requested attribute key and value for matched xpath element. CLI Example: .. code-block:: bash salt '*' xml.set_attribute /tmp/test.xml ".//element[@id='3']" editedby "gal" ''' try: root = ET.parse(file) element = root.find(element) except AttributeError: log.error("Unable to find element matching %s", element) return False element.set(key, str(value)) root.write(file) return True
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Set the requested attribute key and value for matched xpath element. CLI Example: .. code-block:: bash salt '*' xml.set_attribute /tmp/test.xml ".//element[@id='3']" editedby "gal"
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python
train
mcocdawc/chemcoord
src/chemcoord/internal_coordinates/_zmat_class_core.py
https://github.com/mcocdawc/chemcoord/blob/95561ce387c142227c38fb14a1d182179aef8f5f/src/chemcoord/internal_coordinates/_zmat_class_core.py#L663-L778
def get_grad_cartesian(self, as_function=True, chain=True, drop_auto_dummies=True): r"""Return the gradient for the transformation to a Cartesian. If ``as_function`` is True, a function is returned that can be directly applied onto instances of :class:`~Zmat`, which contain the applied distortions in Zmatrix space. In this case the user does not have to worry about indexing and correct application of the tensor product. Basically this is the function :func:`zmat_functions.apply_grad_cartesian_tensor` with partially replaced arguments. If ``as_function`` is False, a ``(3, n, n, 3)`` tensor is returned, which contains the values of the derivatives. Since a ``n * 3`` matrix is deriven after a ``n * 3`` matrix, it is important to specify the used rules for indexing the resulting tensor. The rule is very simple: The indices of the numerator are used first then the indices of the denominator get swapped and appended: .. math:: \left( \frac{\partial \mathbf{Y}}{\partial \mathbf{X}} \right)_{i, j, k, l} = \frac{\partial \mathbf{Y}_{i, j}}{\partial \mathbf{X}_{l, k}} Applying this rule to an example function: .. math:: f \colon \mathbb{R}^3 \rightarrow \mathbb{R} Gives as derivative the known row-vector gradient: .. math:: (\nabla f)_{1, i} = \frac{\partial f}{\partial x_i} \qquad i \in \{1, 2, 3\} .. note:: The row wise alignment of the zmat files makes sense for these CSV like files. But it is mathematically advantageous and sometimes (depending on the memory layout) numerically better to use a column wise alignment of the coordinates. In this function the resulting tensor assumes a ``3 * n`` array for the coordinates. If .. math:: \mathbf{C}_{i, j} &\qquad 1 \leq i \leq 3, \quad 1 \leq j \leq n \\ \mathbf{X}_{i, j} &\qquad 1 \leq i \leq 3, \quad 1 \leq j \leq n denote the positions in Zmatrix and cartesian space, The complete tensor may be written as: .. math:: \left( \frac{\partial \mathbf{X}}{\partial \mathbf{C}} \right)_{i, j, k, l} = \frac{\partial \mathbf{X}_{i, j}}{\partial \mathbf{C}_{l, k}} Args: construction_table (pandas.DataFrame): as_function (bool): Return a tensor or :func:`xyz_functions.apply_grad_zmat_tensor` with partially replaced arguments. chain (bool): drop_auto_dummies (bool): Drop automatically created dummies from the gradient. This means, that only changes in regularly placed atoms are considered for the gradient. Returns: (func, :class:`numpy.ndarray`): Depending on ``as_function`` return a tensor or :func:`~chemcoord.zmat_functions.apply_grad_cartesian_tensor` with partially replaced arguments. """ zmat = self.change_numbering() c_table = zmat.loc[:, ['b', 'a', 'd']] c_table = c_table.replace(constants.int_label).values.T C = zmat.loc[:, ['bond', 'angle', 'dihedral']].values.T if C.dtype == np.dtype('i8'): C = C.astype('f8') C[[1, 2], :] = np.radians(C[[1, 2], :]) grad_X = transformation.get_grad_X(C, c_table, chain=chain) if drop_auto_dummies: def drop_dummies(grad_X, zmolecule): rename = dict(zip(zmolecule.index, range(len(zmolecule)))) dummies = [rename[v['dummy_d']] for v in self._metadata['has_dummies'].values()] excluded = np.full(grad_X.shape[1], True) excluded[dummies] = False coord_rows = np.full(3, True) selection = np.ix_(coord_rows, excluded, excluded, coord_rows) return grad_X[selection] grad_X = drop_dummies(grad_X, self) if as_function: from chemcoord.internal_coordinates.zmat_functions import ( apply_grad_cartesian_tensor) return partial(apply_grad_cartesian_tensor, grad_X) else: return grad_X
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r"""Return the gradient for the transformation to a Cartesian. If ``as_function`` is True, a function is returned that can be directly applied onto instances of :class:`~Zmat`, which contain the applied distortions in Zmatrix space. In this case the user does not have to worry about indexing and correct application of the tensor product. Basically this is the function :func:`zmat_functions.apply_grad_cartesian_tensor` with partially replaced arguments. If ``as_function`` is False, a ``(3, n, n, 3)`` tensor is returned, which contains the values of the derivatives. Since a ``n * 3`` matrix is deriven after a ``n * 3`` matrix, it is important to specify the used rules for indexing the resulting tensor. The rule is very simple: The indices of the numerator are used first then the indices of the denominator get swapped and appended: .. math:: \left( \frac{\partial \mathbf{Y}}{\partial \mathbf{X}} \right)_{i, j, k, l} = \frac{\partial \mathbf{Y}_{i, j}}{\partial \mathbf{X}_{l, k}} Applying this rule to an example function: .. math:: f \colon \mathbb{R}^3 \rightarrow \mathbb{R} Gives as derivative the known row-vector gradient: .. math:: (\nabla f)_{1, i} = \frac{\partial f}{\partial x_i} \qquad i \in \{1, 2, 3\} .. note:: The row wise alignment of the zmat files makes sense for these CSV like files. But it is mathematically advantageous and sometimes (depending on the memory layout) numerically better to use a column wise alignment of the coordinates. In this function the resulting tensor assumes a ``3 * n`` array for the coordinates. If .. math:: \mathbf{C}_{i, j} &\qquad 1 \leq i \leq 3, \quad 1 \leq j \leq n \\ \mathbf{X}_{i, j} &\qquad 1 \leq i \leq 3, \quad 1 \leq j \leq n denote the positions in Zmatrix and cartesian space, The complete tensor may be written as: .. math:: \left( \frac{\partial \mathbf{X}}{\partial \mathbf{C}} \right)_{i, j, k, l} = \frac{\partial \mathbf{X}_{i, j}}{\partial \mathbf{C}_{l, k}} Args: construction_table (pandas.DataFrame): as_function (bool): Return a tensor or :func:`xyz_functions.apply_grad_zmat_tensor` with partially replaced arguments. chain (bool): drop_auto_dummies (bool): Drop automatically created dummies from the gradient. This means, that only changes in regularly placed atoms are considered for the gradient. Returns: (func, :class:`numpy.ndarray`): Depending on ``as_function`` return a tensor or :func:`~chemcoord.zmat_functions.apply_grad_cartesian_tensor` with partially replaced arguments.
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python
train
jstitch/MambuPy
MambuPy/rest/mambustruct.py
https://github.com/jstitch/MambuPy/blob/2af98cc12e7ed5ec183b3e97644e880e70b79ee8/MambuPy/rest/mambustruct.py#L837-L878
def setCustomField(mambuentity, customfield="", *args, **kwargs): """Modifies the customField field for the given object with something related to the value of the given field. If the dataType == "USER_LINK" then instead of using the value of the CF, it will be a MambuUser object. Same if dataType == "CLIENT_LINK", but with a MambuClient. Default case: just uses the same value the CF already had. Returns the number of requests done to Mambu. """ from . import mambuuser from . import mambuclient try: customFieldValue = mambuentity[customfield] # find the dataType customfield by name or id datatype = [ l['customField']['dataType'] for l in mambuentity[mambuentity.customFieldName] if (l['name'] == customfield or l['id'] == customfield) ][0] except IndexError as ierr: # if no customfield found with the given name, assume it is a # grouped custom field, name must have an index suffix that must # be removed try: # find the dataType customfield by name or id datatype = [ l['customField']['dataType'] for l in mambuentity[mambuentity.customFieldName] if (l['name'] == customfield.split('_')[0] or l['id'] == customfield.split('_')[0]) ][0] except IndexError: err = MambuError("Object %s has no custom field '%s'" % (mambuentity['id'], customfield)) raise err except AttributeError: err = MambuError("Object does not have a custom field to set") raise err if datatype == "USER_LINK": mambuentity[customfield] = mambuuser.MambuUser(entid=customFieldValue, *args, **kwargs) elif datatype == "CLIENT_LINK": mambuentity[customfield] = mambuclient.MambuClient(entid=customFieldValue, *args, **kwargs) else: mambuentity[customfield] = customFieldValue return 0 return 1
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Modifies the customField field for the given object with something related to the value of the given field. If the dataType == "USER_LINK" then instead of using the value of the CF, it will be a MambuUser object. Same if dataType == "CLIENT_LINK", but with a MambuClient. Default case: just uses the same value the CF already had. Returns the number of requests done to Mambu.
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python
train
neurosynth/neurosynth
neurosynth/analysis/decode.py
https://github.com/neurosynth/neurosynth/blob/948ce7edce15d7df693446e76834e0c23bfe8f11/neurosynth/analysis/decode.py#L216-L219
def _dot_product(self, imgs_to_decode): """ Decoding using the dot product. """ return np.dot(imgs_to_decode.T, self.feature_images).T
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Decoding using the dot product.
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python
test
NoviceLive/pat
pat/utils.py
https://github.com/NoviceLive/pat/blob/bd223fc5e758213662befbebdf9538f3fbf58ad6/pat/utils.py#L49-L57
def window(seq, count=2): """Slide window.""" iseq = iter(seq) result = tuple(islice(iseq, count)) if len(result) == count: yield result for elem in iseq: result = result[1:] + (elem,) yield result
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Slide window.
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python
train
edx/edx-enterprise
enterprise/utils.py
https://github.com/edx/edx-enterprise/blob/aea91379ab0a87cd3bc798961fce28b60ee49a80/enterprise/utils.py#L715-L730
def is_course_run_enrollable(course_run): """ Return true if the course run is enrollable, false otherwise. We look for the following criteria: - end is greater than now OR null - enrollment_start is less than now OR null - enrollment_end is greater than now OR null """ now = datetime.datetime.now(pytz.UTC) end = parse_datetime_handle_invalid(course_run.get('end')) enrollment_start = parse_datetime_handle_invalid(course_run.get('enrollment_start')) enrollment_end = parse_datetime_handle_invalid(course_run.get('enrollment_end')) return (not end or end > now) and \ (not enrollment_start or enrollment_start < now) and \ (not enrollment_end or enrollment_end > now)
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Return true if the course run is enrollable, false otherwise. We look for the following criteria: - end is greater than now OR null - enrollment_start is less than now OR null - enrollment_end is greater than now OR null
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python
valid
tchellomello/python-amcrest
src/amcrest/ptz.py
https://github.com/tchellomello/python-amcrest/blob/ed842139e234de2eaf6ee8fb480214711cde1249/src/amcrest/ptz.py#L210-L221
def go_to_preset(self, action=None, channel=0, preset_point_number=1): """ Params: action - start or stop channel - channel number preset_point_number - preset point number """ ret = self.command( 'ptz.cgi?action={0}&channel={1}&code=GotoPreset&arg1=0' '&arg2={2}&arg3=0'.format(action, channel, preset_point_number) ) return ret.content.decode('utf-8')
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Params: action - start or stop channel - channel number preset_point_number - preset point number
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python
train
jedie/django-cms-tools
django_cms_tools/fixture_helper/pages.py
https://github.com/jedie/django-cms-tools/blob/0a70dbbb6f770f5a73c8ecd174d5559a37262792/django_cms_tools/fixture_helper/pages.py#L47-L60
def publish_page(page, languages): """ Publish a CMS page in all given languages. """ for language_code, lang_name in iter_languages(languages): url = page.get_absolute_url() if page.publisher_is_draft: page.publish(language_code) log.info('page "%s" published in %s: %s', page, lang_name, url) else: log.info('published page "%s" already exists in %s: %s', page, lang_name, url) return page.reload()
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Publish a CMS page in all given languages.
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python
train
genepattern/genepattern-notebook
genepattern/remote_widgets.py
https://github.com/genepattern/genepattern-notebook/blob/953168bd08c5332412438cbc5bb59993a07a6911/genepattern/remote_widgets.py#L23-L51
def register(self, server, username, password): """ Register a new GenePattern server session for the provided server, username and password. Return the session. :param server: :param username: :param password: :return: """ # Create the session session = gp.GPServer(server, username, password) # Validate username if not empty valid_username = username != "" and username is not None # Validate that the server is not already registered index = self._get_index(server) new_server = index == -1 # Add the new session to the list if valid_username and new_server: self.sessions.append(session) # Replace old session is one exists if valid_username and not new_server: self.sessions[index] = session return session
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Register a new GenePattern server session for the provided server, username and password. Return the session. :param server: :param username: :param password: :return:
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python
valid
python-cmd2/cmd2
cmd2/cmd2.py
https://github.com/python-cmd2/cmd2/blob/b22c0bd891ed08c8b09df56df9d91f48166a5e2a/cmd2/cmd2.py#L194-L241
def with_argparser_and_unknown_args(argparser: argparse.ArgumentParser, preserve_quotes: bool = False) -> \ Callable[[argparse.Namespace, List], Optional[bool]]: """A decorator to alter a cmd2 method to populate its ``args`` argument by parsing arguments with the given instance of argparse.ArgumentParser, but also returning unknown args as a list. :param argparser: unique instance of ArgumentParser :param preserve_quotes: if True, then arguments passed to argparse maintain their quotes :return: function that gets passed argparse-parsed args in a Namespace and a list of unknown argument strings A member called __statement__ is added to the Namespace to provide command functions access to the Statement object. This can be useful if the command function needs to know the command line. """ import functools # noinspection PyProtectedMember def arg_decorator(func: Callable): @functools.wraps(func) def cmd_wrapper(cmd2_instance, statement: Union[Statement, str]): statement, parsed_arglist = cmd2_instance.statement_parser.get_command_arg_list(command_name, statement, preserve_quotes) try: args, unknown = argparser.parse_known_args(parsed_arglist) except SystemExit: return else: setattr(args, '__statement__', statement) return func(cmd2_instance, args, unknown) # argparser defaults the program name to sys.argv[0] # we want it to be the name of our command command_name = func.__name__[len(COMMAND_FUNC_PREFIX):] argparser.prog = command_name # If the description has not been set, then use the method docstring if one exists if argparser.description is None and func.__doc__: argparser.description = func.__doc__ # Set the command's help text as argparser.description (which can be None) cmd_wrapper.__doc__ = argparser.description # Mark this function as having an argparse ArgumentParser setattr(cmd_wrapper, 'argparser', argparser) return cmd_wrapper return arg_decorator
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A decorator to alter a cmd2 method to populate its ``args`` argument by parsing arguments with the given instance of argparse.ArgumentParser, but also returning unknown args as a list. :param argparser: unique instance of ArgumentParser :param preserve_quotes: if True, then arguments passed to argparse maintain their quotes :return: function that gets passed argparse-parsed args in a Namespace and a list of unknown argument strings A member called __statement__ is added to the Namespace to provide command functions access to the Statement object. This can be useful if the command function needs to know the command line.
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python
train
ybrs/pydisque
pydisque/client.py
https://github.com/ybrs/pydisque/blob/ea5ce1576b66398c1cce32cad0f15709b1ea8df8/pydisque/client.py#L402-L415
def show(self, job_id, return_dict=False): """ Describe the job. :param job_id: """ rtn = self.execute_command('SHOW', job_id) if return_dict: grouped = self._grouper(rtn, 2) rtn = dict((a, b) for a, b in grouped) return rtn
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Describe the job. :param job_id:
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python
train
jobovy/galpy
galpy/util/bovy_coords.py
https://github.com/jobovy/galpy/blob/9c5b9fe65d58835624dffe432be282060918ee08/galpy/util/bovy_coords.py#L1991-L2037
def Rz_to_lambdanu(R,z,ac=5.,Delta=1.): """ NAME: Rz_to_lambdanu PURPOSE: calculate the prolate spheroidal coordinates (lambda,nu) from galactocentric cylindrical coordinates (R,z) by solving eq. (2.2) in Dejonghe & de Zeeuw (1988a) for (lambda,nu): R^2 = (l+a) * (n+a) / (a-g) z^2 = (l+g) * (n+g) / (g-a) Delta^2 = g-a INPUT: R - Galactocentric cylindrical radius z - vertical height ac - axis ratio of the coordinate surfaces (a/c) = sqrt(-a) / sqrt(-g) (default: 5.) Delta - focal distance that defines the spheroidal coordinate system (default: 1.) Delta=sqrt(g-a) OUTPUT: (lambda,nu) HISTORY: 2015-02-13 - Written - Trick (MPIA) """ g = Delta**2 / (1.-ac**2) a = g - Delta**2 term = R**2 + z**2 - a - g discr = (R**2 + z**2 - Delta**2)**2 + (4. * Delta**2 * R**2) l = 0.5 * (term + nu.sqrt(discr)) n = 0.5 * (term - nu.sqrt(discr)) if isinstance(z,float) and z == 0.: l = R**2 - a n = -g elif isinstance(z,nu.ndarray) and nu.sum(z == 0.) > 0: if isinstance(R,float): l[z==0.] = R**2 - a if isinstance(R,sc.ndarray): l[z==0.] = R[z==0.]**2 - a n[z==0.] = -g return (l,n)
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NAME: Rz_to_lambdanu PURPOSE: calculate the prolate spheroidal coordinates (lambda,nu) from galactocentric cylindrical coordinates (R,z) by solving eq. (2.2) in Dejonghe & de Zeeuw (1988a) for (lambda,nu): R^2 = (l+a) * (n+a) / (a-g) z^2 = (l+g) * (n+g) / (g-a) Delta^2 = g-a INPUT: R - Galactocentric cylindrical radius z - vertical height ac - axis ratio of the coordinate surfaces (a/c) = sqrt(-a) / sqrt(-g) (default: 5.) Delta - focal distance that defines the spheroidal coordinate system (default: 1.) Delta=sqrt(g-a) OUTPUT: (lambda,nu) HISTORY: 2015-02-13 - Written - Trick (MPIA)
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python
train
mitsei/dlkit
dlkit/json_/repository/objects.py
https://github.com/mitsei/dlkit/blob/445f968a175d61c8d92c0f617a3c17dc1dc7c584/dlkit/json_/repository/objects.py#L948-L960
def clear_distribute_compositions(self): """Removes the distribution rights. raise: NoAccess - ``Metadata.isRequired()`` is ``true`` or ``Metadata.isReadOnly()`` is ``true`` *compliance: mandatory -- This method must be implemented.* """ # Implemented from template for osid.resource.ResourceForm.clear_group_template if (self.get_distribute_compositions_metadata().is_read_only() or self.get_distribute_compositions_metadata().is_required()): raise errors.NoAccess() self._my_map['distributeCompositions'] = self._distribute_compositions_default
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Removes the distribution rights. raise: NoAccess - ``Metadata.isRequired()`` is ``true`` or ``Metadata.isReadOnly()`` is ``true`` *compliance: mandatory -- This method must be implemented.*
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python
train
unt-libraries/pyuntl
pyuntl/untl_structure.py
https://github.com/unt-libraries/pyuntl/blob/f92413302897dab948aac18ee9e482ace0187bd4/pyuntl/untl_structure.py#L358-L369
def create_xml_string(self): """Create a UNTL document in a string from a UNTL metadata root object. untl_xml_string = metadata_root_object.create_xml_string() """ root = self.create_xml() xml = '<?xml version="1.0" encoding="UTF-8"?>\n' + tostring( root, pretty_print=True ) return xml
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Create a UNTL document in a string from a UNTL metadata root object. untl_xml_string = metadata_root_object.create_xml_string()
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python
train
gem/oq-engine
openquake/hazardlib/gsim/edwards_fah_2013a.py
https://github.com/gem/oq-engine/blob/8294553a0b8aba33fd96437a35065d03547d0040/openquake/hazardlib/gsim/edwards_fah_2013a.py#L219-L227
def _compute_mean(self, C, mag, term_dist_r): """ compute mean """ return (self._compute_term_1(C, mag) + self._compute_term_2(C, mag, term_dist_r) + self._compute_term_3(C, mag, term_dist_r) + self._compute_term_4(C, mag, term_dist_r) + self._compute_term_5(C, mag, term_dist_r))
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compute mean
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python
train
tensorflow/tensor2tensor
tensor2tensor/models/mtf_resnet.py
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/mtf_resnet.py#L145-L204
def block_layer(inputs, filters, blocks, strides, is_training, name, row_blocks_dim=None, col_blocks_dim=None): """Creates one layer of blocks for the ResNet model. Args: inputs: `Tensor` of size `[batch, channels, height, width]`. filters: `int` number of filters for the first convolution of the layer. blocks: `int` number of blocks contained in the layer. strides: `int` stride to use for the first convolution of the layer. If greater than 1, this layer will downsample the input. is_training: `bool` for whether the model is training. name: `str`name for the Tensor output of the block layer. row_blocks_dim: a mtf.Dimension, row dimension which is spatially partitioned along mesh axis col_blocks_dim: a mtf.Dimension, row dimension which is spatially partitioned along mesh axis Returns: The output `Tensor` of the block layer. """ with tf.variable_scope(name, default_name="block_layer"): # Only the first block per block_layer uses projection_shortcut and strides def projection_shortcut(inputs, kernel): """Project identity branch.""" inputs = mtf.conv2d_with_blocks( inputs, kernel, strides=strides, padding="SAME", h_blocks_dim=None, w_blocks_dim=col_blocks_dim) return batch_norm_relu( inputs, is_training, relu=False) inputs = bottleneck_block( inputs, filters, is_training, strides=strides, projection_shortcut=projection_shortcut, row_blocks_dim=row_blocks_dim, col_blocks_dim=col_blocks_dim) for i in range(1, blocks): with tf.variable_scope("bottleneck_%d" % i): inputs = bottleneck_block( inputs, filters, is_training, strides=[1, 1, 1, 1], projection_shortcut=None, row_blocks_dim=row_blocks_dim, col_blocks_dim=col_blocks_dim) return inputs
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Creates one layer of blocks for the ResNet model. Args: inputs: `Tensor` of size `[batch, channels, height, width]`. filters: `int` number of filters for the first convolution of the layer. blocks: `int` number of blocks contained in the layer. strides: `int` stride to use for the first convolution of the layer. If greater than 1, this layer will downsample the input. is_training: `bool` for whether the model is training. name: `str`name for the Tensor output of the block layer. row_blocks_dim: a mtf.Dimension, row dimension which is spatially partitioned along mesh axis col_blocks_dim: a mtf.Dimension, row dimension which is spatially partitioned along mesh axis Returns: The output `Tensor` of the block layer.
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python
train
vpelletier/python-libusb1
usb1/__init__.py
https://github.com/vpelletier/python-libusb1/blob/740c9778e28523e4ec3543415d95f5400ae0fa24/usb1/__init__.py#L1118-L1127
def unregister(self, fd): """ Unregister an USB-unrelated fd from poller. Convenience method. """ if fd in self.__fd_set: raise ValueError( 'This fd is a special USB event fd, it must stay registered.' ) self.__poller.unregister(fd)
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Unregister an USB-unrelated fd from poller. Convenience method.
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python
train
RedHatInsights/insights-core
insights/specs/default.py
https://github.com/RedHatInsights/insights-core/blob/b57cbf8ed7c089672426ede0441e0a4f789ef4a1/insights/specs/default.py#L121-L131
def tomcat_base(broker): """Path: Tomcat base path""" ps = broker[DefaultSpecs.ps_auxww].content results = [] findall = re.compile(r"\-Dcatalina\.base=(\S+)").findall for p in ps: found = findall(p) if found: # Only get the path which is absolute results.extend(f for f in found if f[0] == '/') return list(set(results))
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Path: Tomcat base path
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python
train
pybel/pybel
src/pybel/cli.py
https://github.com/pybel/pybel/blob/c8a7a1bdae4c475fa2a8c77f3a9a5f6d79556ca0/src/pybel/cli.py#L421-L429
def prune(manager: Manager): """Prune nodes not belonging to any edges.""" nodes_to_delete = [ node for node in tqdm(manager.session.query(Node), total=manager.count_nodes()) if not node.networks ] manager.session.delete(nodes_to_delete) manager.session.commit()
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Prune nodes not belonging to any edges.
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python
train
mrcagney/gtfstk
gtfstk/validators.py
https://github.com/mrcagney/gtfstk/blob/c91494e6fefc02523889655a0dc92d1c0eee8d03/gtfstk/validators.py#L138-L181
def check_for_required_columns( problems: List, table: str, df: DataFrame ) -> List: """ Check that the given GTFS table has the required columns. Parameters ---------- problems : list A four-tuple containing 1. A problem type (string) equal to ``'error'`` or ``'warning'``; ``'error'`` means the GTFS is violated; ``'warning'`` means there is a problem but it is not a GTFS violation 2. A message (string) that describes the problem 3. A GTFS table name, e.g. ``'routes'``, in which the problem occurs 4. A list of rows (integers) of the table's DataFrame where the problem occurs table : string Name of a GTFS table df : DataFrame The GTFS table corresponding to ``table`` Returns ------- list The ``problems`` list extended as follows. Check that the DataFrame contains the colums required by GTFS and append to the problems list one error for each column missing. """ r = cs.GTFS_REF req_columns = r.loc[ (r["table"] == table) & r["column_required"], "column" ].values for col in req_columns: if col not in df.columns: problems.append(["error", f"Missing column {col}", table, []]) return problems
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Check that the given GTFS table has the required columns. Parameters ---------- problems : list A four-tuple containing 1. A problem type (string) equal to ``'error'`` or ``'warning'``; ``'error'`` means the GTFS is violated; ``'warning'`` means there is a problem but it is not a GTFS violation 2. A message (string) that describes the problem 3. A GTFS table name, e.g. ``'routes'``, in which the problem occurs 4. A list of rows (integers) of the table's DataFrame where the problem occurs table : string Name of a GTFS table df : DataFrame The GTFS table corresponding to ``table`` Returns ------- list The ``problems`` list extended as follows. Check that the DataFrame contains the colums required by GTFS and append to the problems list one error for each column missing.
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python
train
estnltk/estnltk
estnltk/mw_verbs/verbchain_nom_vinf_extender.py
https://github.com/estnltk/estnltk/blob/28ae334a68a0673072febc318635f04da0dcc54a/estnltk/mw_verbs/verbchain_nom_vinf_extender.py#L120-L130
def extendChainsInSentence( self, sentence, foundChains ): ''' Rakendab meetodit self.extendChainsInClause() antud lause igal osalausel. ''' # 1) Preprocessing clauses = getClausesByClauseIDs( sentence ) # 2) Extend verb chains in each clause allDetectedVerbChains = [] for clauseID in clauses: clause = clauses[clauseID] self.extendChainsInClause(clause, clauseID, foundChains)
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Rakendab meetodit self.extendChainsInClause() antud lause igal osalausel.
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python
train
wesyoung/pyzyre
czmq/_czmq_ctypes.py
https://github.com/wesyoung/pyzyre/blob/22d4c757acefcfdb700d3802adaf30b402bb9eea/czmq/_czmq_ctypes.py#L1214-L1220
def append(self, data, size): """ Append user-supplied data to chunk, return resulting chunk size. If the data would exceeded the available space, it is truncated. If you want to grow the chunk to accommodate new data, use the zchunk_extend method. """ return lib.zchunk_append(self._as_parameter_, data, size)
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Append user-supplied data to chunk, return resulting chunk size. If the data would exceeded the available space, it is truncated. If you want to grow the chunk to accommodate new data, use the zchunk_extend method.
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python
train
iotile/coretools
iotileemulate/iotile/emulate/reference/controller_features/config_database.py
https://github.com/iotile/coretools/blob/2d794f5f1346b841b0dcd16c9d284e9bf2f3c6ec/iotileemulate/iotile/emulate/reference/controller_features/config_database.py#L39-L47
def dump(self): """Serialize this object.""" return { 'target': str(self.target), 'data': base64.b64encode(self.data).decode('utf-8'), 'var_id': self.var_id, 'valid': self.valid }
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Serialize this object.
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python
train
cmbruns/pyopenvr
src/openvr/__init__.py
https://github.com/cmbruns/pyopenvr/blob/68395d26bb3df6ab1f0f059c38d441f962938be6/src/openvr/__init__.py#L3339-L3346
def getVideoStreamTextureGL(self, hTrackedCamera, eFrameType, nFrameHeaderSize): """Access a shared GL texture for the specified tracked camera stream""" fn = self.function_table.getVideoStreamTextureGL pglTextureId = glUInt_t() pFrameHeader = CameraVideoStreamFrameHeader_t() result = fn(hTrackedCamera, eFrameType, byref(pglTextureId), byref(pFrameHeader), nFrameHeaderSize) return result, pglTextureId, pFrameHeader
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Access a shared GL texture for the specified tracked camera stream
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python
train
alfred82santa/dirty-models
dirty_models/models.py
https://github.com/alfred82santa/dirty-models/blob/354becdb751b21f673515eae928c256c7e923c50/dirty_models/models.py#L494-L499
def clear(self): """ Clears all the data in the object, keeping original data """ self.__modified_data__ = {} self.__deleted_fields__ = [field for field in self.__original_data__.keys()]
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Clears all the data in the object, keeping original data
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python
train
jnrbsn/daemonocle
daemonocle/core.py
https://github.com/jnrbsn/daemonocle/blob/a1e09bc99608eab8dfe024c6741b7ecb7143f717/daemonocle/core.py#L395-L421
def _run(self): """Run the worker function with some custom exception handling.""" try: # Run the worker self.worker() except SystemExit as ex: # sys.exit() was called if isinstance(ex.code, int): if ex.code is not None and ex.code != 0: # A custom exit code was specified self._shutdown( 'Exiting with non-zero exit code {exitcode}'.format( exitcode=ex.code), ex.code) else: # A message was passed to sys.exit() self._shutdown( 'Exiting with message: {msg}'.format(msg=ex.code), 1) except Exception as ex: if self.detach: self._shutdown('Dying due to unhandled {cls}: {msg}'.format( cls=ex.__class__.__name__, msg=str(ex)), 127) else: # We're not detached so just raise the exception raise self._shutdown('Shutting down normally')
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Run the worker function with some custom exception handling.
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python
train
mcieslik-mctp/papy
src/papy/core.py
https://github.com/mcieslik-mctp/papy/blob/708e50827b5db46bbea081982cb74b9b0e464064/src/papy/core.py#L631-L648
def load(self, filename): """ Instanciates (loads) pipeline from a source code file. Arguments: - filename(``path``) location of the pipeline source code. """ dir_name = os.path.dirname(filename) mod_name = os.path.basename(filename).split('.')[0] self.filename = mod_name sys.path.insert(0, dir_name) mod = __import__(mod_name) sys.path.remove(dir_name) # do not pollute the path. pipers, xtras, pipes = mod.pipeline() self.add_pipers(pipers, xtras) self.add_pipes(pipes)
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Instanciates (loads) pipeline from a source code file. Arguments: - filename(``path``) location of the pipeline source code.
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python
train
mlenzen/collections-extended
collections_extended/range_map.py
https://github.com/mlenzen/collections-extended/blob/ee9e86f6bbef442dbebcb3a5970642c5c969e2cf/collections_extended/range_map.py#L348-L353
def empty(self, start=None, stop=None): """Empty the range from start to stop. Like delete, but no Error is raised if the entire range isn't mapped. """ self.set(NOT_SET, start=start, stop=stop)
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Empty the range from start to stop. Like delete, but no Error is raised if the entire range isn't mapped.
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python
train
reincubate/ricloud
ricloud/utils.py
https://github.com/reincubate/ricloud/blob/e46bce4529fbdca34a4190c18c7219e937e2b697/ricloud/utils.py#L90-L102
def print_prompt_values(values, message=None, sub_attr=None): """Prints prompt title and choices with a bit of formatting.""" if message: prompt_message(message) for index, entry in enumerate(values): if sub_attr: line = '{:2d}: {}'.format(index, getattr(utf8(entry), sub_attr)) else: line = '{:2d}: {}'.format(index, utf8(entry)) with indent(3): print_message(line)
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Prints prompt title and choices with a bit of formatting.
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python
train
scopus-api/scopus
scopus/scopus_search.py
https://github.com/scopus-api/scopus/blob/27ce02dd3095bfdab9d3e8475543d7c17767d1ab/scopus/scopus_search.py#L196-L200
def _join(lst, key, sep=";"): """Auxiliary function to join same elements of a list of dictionaries if the elements are not None. """ return sep.join([d[key] for d in lst if d[key]])
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Auxiliary function to join same elements of a list of dictionaries if the elements are not None.
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python
train
mailgun/talon
talon/quotations.py
https://github.com/mailgun/talon/blob/cdd84563dd329c4f887591807870d10015e0c7a7/talon/quotations.py#L601-L609
def is_splitter(line): ''' Returns Matcher object if provided string is a splitter and None otherwise. ''' for pattern in SPLITTER_PATTERNS: matcher = re.match(pattern, line) if matcher: return matcher
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Returns Matcher object if provided string is a splitter and None otherwise.
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python
train
markovmodel/PyEMMA
pyemma/_ext/variational/estimators/moments.py
https://github.com/markovmodel/PyEMMA/blob/5c3124398217de05ba5ce9c8fb01519222481ab8/pyemma/_ext/variational/estimators/moments.py#L386-L401
def _M2_dense(X, Y, weights=None, diag_only=False): """ 2nd moment matrix using dense matrix computations. This function is encapsulated such that we can make easy modifications of the basic algorithms """ if weights is not None: if diag_only: return np.sum(weights[:, None] * X * Y, axis=0) else: return np.dot((weights[:, None] * X).T, Y) else: if diag_only: return np.sum(X * Y, axis=0) else: return np.dot(X.T, Y)
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2nd moment matrix using dense matrix computations. This function is encapsulated such that we can make easy modifications of the basic algorithms
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python
train
google/tangent
tangent/utils.py
https://github.com/google/tangent/blob/6533e83af09de7345d1b438512679992f080dcc9/tangent/utils.py#L700-L722
def push_stack(stack, substack, op_id): """Proxy of push, where we know we're pushing a stack onto a stack. Used when differentiating call trees,where sub-functions get their own stack. See push() for more. Args: stack: The stack object, which must support appending values. substack: The stack to append. op_id: A unique variable that is also passed into the corresponding pop. Allows optimization passes to track pairs of pushes and pops. Raises: ValueError: If a non-stack value for `substack` is passed. """ if substack is not None and not isinstance(substack, Stack): raise ValueError( 'Substack should be type tangent.Stack or None, instead found %s' % type(substack)) if __debug__: stack.append((substack, op_id)) else: stack.append(substack)
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Proxy of push, where we know we're pushing a stack onto a stack. Used when differentiating call trees,where sub-functions get their own stack. See push() for more. Args: stack: The stack object, which must support appending values. substack: The stack to append. op_id: A unique variable that is also passed into the corresponding pop. Allows optimization passes to track pairs of pushes and pops. Raises: ValueError: If a non-stack value for `substack` is passed.
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python
train
PyCQA/astroid
astroid/as_string.py
https://github.com/PyCQA/astroid/blob/e0a298df55b15abcb77c2a93253f5ab7be52d0fb/astroid/as_string.py#L363-L367
def visit_keyword(self, node): """return an astroid.Keyword node as string""" if node.arg is None: return "**%s" % node.value.accept(self) return "%s=%s" % (node.arg, node.value.accept(self))
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return an astroid.Keyword node as string
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python
train
xflr6/gsheets
gsheets/tools.py
https://github.com/xflr6/gsheets/blob/ca4f1273044704e529c1138e3f942836fc496e1b/gsheets/tools.py#L133-L140
def uniqued(iterable): """Return unique list of ``iterable`` items preserving order. >>> uniqued('spameggs') ['s', 'p', 'a', 'm', 'e', 'g'] """ seen = set() return [item for item in iterable if item not in seen and not seen.add(item)]
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Return unique list of ``iterable`` items preserving order. >>> uniqued('spameggs') ['s', 'p', 'a', 'm', 'e', 'g']
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/extensions/autoreload.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/extensions/autoreload.py#L132-L136
def _get_compiled_ext(): """Official way to get the extension of compiled files (.pyc or .pyo)""" for ext, mode, typ in imp.get_suffixes(): if typ == imp.PY_COMPILED: return ext
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Official way to get the extension of compiled files (.pyc or .pyo)
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python
test
jbasko/configmanager
configmanager/items.py
https://github.com/jbasko/configmanager/blob/1d7229ce367143c7210d8e5f0782de03945a1721/configmanager/items.py#L178-L197
def _get_envvar_value(self): """ Internal helper to get item value from an environment variable if item is controlled by one, and if the variable is set. Returns not_set otherwise. """ envvar_name = None if self.envvar is True: envvar_name = self.envvar_name if envvar_name is None: envvar_name = '_'.join(self.get_path()).upper() elif self.envvar: envvar_name = self.envvar if envvar_name and envvar_name in os.environ: return self.type.deserialize(os.environ[envvar_name]) else: return not_set
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Internal helper to get item value from an environment variable if item is controlled by one, and if the variable is set. Returns not_set otherwise.
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python
train
miku/gluish
gluish/intervals.py
https://github.com/miku/gluish/blob/56d3ac4f41a944e31ecac0aa3b6d1dc2ce705e29/gluish/intervals.py#L73-L77
def biweekly(date=datetime.date.today()): """ Every two weeks. """ return datetime.date(date.year, date.month, 1 if date.day < 15 else 15)
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Every two weeks.
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python
train
LionelAuroux/pyrser
pyrser/type_system/scope.py
https://github.com/LionelAuroux/pyrser/blob/f153a97ef2b6bf915a1ed468c0252a9a59b754d5/pyrser/type_system/scope.py#L406-L504
def get_by_params(self, params: [Scope]) -> (Scope, [[Scope]]): """ Retrieve a Set of all signature that match the parameter list. Return a pair: pair[0] the overloads for the functions pair[1] the overloads for the parameters (a list of candidate list of parameters) """ lst = [] scopep = [] # for each of our signatures for s in self.values(): # for each params of this signature if hasattr(s, 'tparams'): # number of matched params mcnt = 0 # temporary collect nbparam_sig = (0 if s.tparams is None else len(s.tparams)) nbparam_candidates = len(params) # don't treat signature too short if nbparam_sig > nbparam_candidates: continue # don't treat call signature too long if not variadic if nbparam_candidates > nbparam_sig and not s.variadic: continue tmp = [None] * nbparam_candidates variadic_types = [] for i in range(nbparam_candidates): tmp[i] = Scope(state=StateScope.LINKED) tmp[i].set_parent(self) # match param of the expr if i < nbparam_sig: if params[i].state == StateScope.EMBEDDED: raise ValueError( ("params[%d] of get_by_params is a StateScope." + "EMBEDDED scope... " + "read the doc and try a StateScope.FREE" + " or StateScope.LINKED.") % i ) m = params[i].get_by_return_type(s.tparams[i]) if len(m) > 0: mcnt += 1 tmp[i].update(m) else: # co/contra-variance # we just need to search a t1->t2 # and add it into the tree (with/without warnings) t1 = params[i] t2 = s.tparams[i] # if exist a fun (t1) -> t2 (is_convertible, signature, translator ) = t1.findTranslationTo(t2) if is_convertible: # add a translator in the EvalCtx signature.use_translator(translator) mcnt += 1 nscope = Scope( sig=[signature], state=StateScope.LINKED, is_namespace=False ) nscope.set_parent(self) tmp[i].update(nscope) elif s.tparams[i].is_polymorphic: # handle polymorphic parameter mcnt += 1 if not isinstance(params[i], Scope): raise Exception( "params[%d] must be a Scope" % i ) tmp[i].update(params[i]) else: # handle polymorphic return type m = params[i].get_all_polymorphic_return() if len(m) > 0: mcnt += 1 tmp[i].update(m) # for variadic extra parameters else: mcnt += 1 if not isinstance(params[i], Scope): raise Exception("params[%d] must be a Scope" % i) variadic_types.append(params[i].first().tret) tmp[i].update(params[i]) # we have match all candidates if mcnt == len(params): # select this signature but # box it (with EvalCtx) for type resolution lst.append(EvalCtx.from_sig(s)) lastentry = lst[-1] if lastentry.variadic: lastentry.use_variadic_types(variadic_types) scopep.append(tmp) rscope = Scope(sig=lst, state=StateScope.LINKED, is_namespace=False) # inherit type/translation from parent rscope.set_parent(self) return (rscope, scopep)
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Retrieve a Set of all signature that match the parameter list. Return a pair: pair[0] the overloads for the functions pair[1] the overloads for the parameters (a list of candidate list of parameters)
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python
test
benhoff/vexbot
vexbot/util/messaging.py
https://github.com/benhoff/vexbot/blob/9b844eb20e84eea92a0e7db7d86a90094956c38f/vexbot/util/messaging.py#L3-L17
def get_addresses(message: list) -> list: """ parses a raw list from zmq to get back the components that are the address messages are broken by the addresses in the beginning and then the message, like this: ```addresses | '' | message ``` """ # Need the address so that we know who to send the message back to addresses = [] for address in message: # if we hit a blank string, then we've got all the addresses if address == b'': break addresses.append(address) return addresses
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parses a raw list from zmq to get back the components that are the address messages are broken by the addresses in the beginning and then the message, like this: ```addresses | '' | message ```
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python
train
IdentityPython/fedoidcmsg
src/fedoidcmsg/operator.py
https://github.com/IdentityPython/fedoidcmsg/blob/d30107be02521fa6cdfe285da3b6b0cdd153c8cc/src/fedoidcmsg/operator.py#L237-L329
def _unpack(self, ms_dict, keyjar, cls, jwt_ms=None, liss=None): """ :param ms_dict: Metadata statement as a dictionary :param keyjar: A keyjar with the necessary FO keys :param cls: What class to map the metadata into :param jwt_ms: Metadata statement as a JWS :param liss: List of FO issuer IDs :return: ParseInfo instance """ if liss is None: liss = [] _pr = ParseInfo() _pr.input = ms_dict ms_flag = False if 'metadata_statements' in ms_dict: ms_flag = True for iss, _ms in ms_dict['metadata_statements'].items(): if liss and iss not in liss: continue _pr = self._ums(_pr, _ms, keyjar) if 'metadata_statement_uris' in ms_dict: ms_flag = True if self.httpcli: for iss, url in ms_dict['metadata_statement_uris'].items(): if liss and iss not in liss: continue rsp = self.httpcli(method='GET', url=url, verify=self.verify_ssl) if rsp.status_code == 200: _pr = self._ums(_pr, rsp.text, keyjar) else: raise ParseError( 'Could not fetch jws from {}'.format(url)) for _ms in _pr.parsed_statement: if _ms: # can be None loaded = False try: keyjar.import_jwks_as_json(_ms['signing_keys'], ms_dict['iss']) except KeyError: pass except TypeError: try: keyjar.import_jwks(_ms['signing_keys'], ms_dict['iss']) except Exception as err: logger.error(err) raise else: loaded = True else: loaded = True if loaded: logger.debug( 'Loaded signing keys belonging to {} into the ' 'keyjar'.format(ms_dict['iss'])) if ms_flag is True and not _pr.parsed_statement: return _pr if jwt_ms: logger.debug("verifying signed JWT: {}".format(jwt_ms)) try: _pr.result = cls().from_jwt(jwt_ms, keyjar=keyjar) except MissingSigningKey: if 'signing_keys' in ms_dict: try: _pr.result = self.self_signed(ms_dict, jwt_ms, cls) except MissingSigningKey as err: logger.error('Encountered: {}'.format(err)) _pr.error[jwt_ms] = err except (JWSException, BadSignature, KeyError) as err: logger.error('Encountered: {}'.format(err)) _pr.error[jwt_ms] = err else: _pr.result = ms_dict if _pr.result and _pr.parsed_statement: _prr = _pr.result _res = {} for x in _pr.parsed_statement: if x: _res[get_fo(x)] = x _msg = Message(**_res) logger.debug('Resulting metadata statement: {}'.format(_msg)) _pr.result['metadata_statements'] = _msg return _pr
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:param ms_dict: Metadata statement as a dictionary :param keyjar: A keyjar with the necessary FO keys :param cls: What class to map the metadata into :param jwt_ms: Metadata statement as a JWS :param liss: List of FO issuer IDs :return: ParseInfo instance
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python
test
jepegit/cellpy
cellpy/readers/dbreader.py
https://github.com/jepegit/cellpy/blob/9f4a84cdd11f72cfa02cda8c2d7b5174abbb7370/cellpy/readers/dbreader.py#L122-L151
def _open_sheet(self, dtypes_dict=None): """Opens sheets and returns it""" table_name = self.db_sheet_table header_row = self.db_header_row nrows = self.nrows if dtypes_dict is None: dtypes_dict = self.dtypes_dict rows_to_skip = self.skiprows logging.debug(f"Trying to open the file {self.db_file}") logging.debug(f"Number of rows: {nrows}") logging.debug(f"Skipping the following rows: {rows_to_skip}") logging.debug(f"Declaring the following dtyps: {dtypes_dict}") work_book = pd.ExcelFile(self.db_file) try: sheet = work_book.parse( table_name, header=header_row, skiprows=rows_to_skip, dtype=dtypes_dict, nrows=nrows, ) except ValueError as e: logging.debug("Could not parse all the columns (ValueError) " "using given dtypes. Trying without dtypes.") logging.debug(str(e)) sheet = work_book.parse( table_name, header=header_row, skiprows=rows_to_skip, nrows=nrows, ) return sheet
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Opens sheets and returns it
[ "Opens", "sheets", "and", "returns", "it" ]
python
train
marcomusy/vtkplotter
vtkplotter/actors.py
https://github.com/marcomusy/vtkplotter/blob/692c3396782722ec525bc1346a26999868c650c6/vtkplotter/actors.py#L1002-L1011
def centerOfMass(self): """Get the center of mass of actor. .. hint:: |fatlimb| |fatlimb.py|_ """ cmf = vtk.vtkCenterOfMass() cmf.SetInputData(self.polydata(True)) cmf.Update() c = cmf.GetCenter() return np.array(c)
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Get the center of mass of actor. .. hint:: |fatlimb| |fatlimb.py|_
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python
train
ajslater/picopt
picopt/files.py
https://github.com/ajslater/picopt/blob/261da837027563c1dc3ed07b70e1086520a60402/picopt/files.py#L19-L48
def _cleanup_after_optimize_aux(filename, new_filename, old_format, new_format): """ Replace old file with better one or discard new wasteful file. """ bytes_in = 0 bytes_out = 0 final_filename = filename try: bytes_in = os.stat(filename).st_size bytes_out = os.stat(new_filename).st_size if (bytes_out > 0) and ((bytes_out < bytes_in) or Settings.bigger): if old_format != new_format: final_filename = replace_ext(filename, new_format.lower()) rem_filename = filename + REMOVE_EXT if not Settings.test: os.rename(filename, rem_filename) os.rename(new_filename, final_filename) os.remove(rem_filename) else: os.remove(new_filename) else: os.remove(new_filename) bytes_out = bytes_in except OSError as ex: print(ex) return final_filename, bytes_in, bytes_out
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Replace old file with better one or discard new wasteful file.
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python
train
pypa/pipenv
pipenv/vendor/orderedmultidict/orderedmultidict.py
https://github.com/pypa/pipenv/blob/cae8d76c210b9777e90aab76e9c4b0e53bb19cde/pipenv/vendor/orderedmultidict/orderedmultidict.py#L353-L392
def setlist(self, key, values): """ Sets <key>'s list of values to <values>. Existing items with key <key> are first replaced with new values from <values>. Any remaining old items that haven't been replaced with new values are deleted, and any new values from <values> that don't have corresponding items with <key> to replace are appended to the end of the list of all items. If values is an empty list, [], <key> is deleted, equivalent in action to del self[<key>]. Example: omd = omdict([(1,1), (2,2)]) omd.setlist(1, [11, 111]) omd.allitems() == [(1,11), (2,2), (1,111)] omd = omdict([(1,1), (1,11), (2,2), (1,111)]) omd.setlist(1, [None]) omd.allitems() == [(1,None), (2,2)] omd = omdict([(1,1), (1,11), (2,2), (1,111)]) omd.setlist(1, []) omd.allitems() == [(2,2)] Returns: <self>. """ if not values and key in self: self.pop(key) else: it = zip_longest( list(self._map.get(key, [])), values, fillvalue=_absent) for node, value in it: if node is not _absent and value is not _absent: node.value = value elif node is _absent: self.add(key, value) elif value is _absent: self._map[key].remove(node) self._items.removenode(node) return self
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Sets <key>'s list of values to <values>. Existing items with key <key> are first replaced with new values from <values>. Any remaining old items that haven't been replaced with new values are deleted, and any new values from <values> that don't have corresponding items with <key> to replace are appended to the end of the list of all items. If values is an empty list, [], <key> is deleted, equivalent in action to del self[<key>]. Example: omd = omdict([(1,1), (2,2)]) omd.setlist(1, [11, 111]) omd.allitems() == [(1,11), (2,2), (1,111)] omd = omdict([(1,1), (1,11), (2,2), (1,111)]) omd.setlist(1, [None]) omd.allitems() == [(1,None), (2,2)] omd = omdict([(1,1), (1,11), (2,2), (1,111)]) omd.setlist(1, []) omd.allitems() == [(2,2)] Returns: <self>.
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python
train
ricequant/rqalpha
rqalpha/interface.py
https://github.com/ricequant/rqalpha/blob/ac40a62d4e7eca9494b4d0a14f46facf5616820c/rqalpha/interface.py#L360-L398
def history_bars(self, instrument, bar_count, frequency, fields, dt, skip_suspended=True, include_now=False, adjust_type='pre', adjust_orig=None): """ 获取历史数据 :param instrument: 合约对象 :type instrument: :class:`~Instrument` :param int bar_count: 获取的历史数据数量 :param str frequency: 周期频率,`1d` 表示日周期, `1m` 表示分钟周期 :param str fields: 返回数据字段 ========================= =================================================== fields 字段名 ========================= =================================================== datetime 时间戳 open 开盘价 high 最高价 low 最低价 close 收盘价 volume 成交量 total_turnover 成交额 datetime int类型时间戳 open_interest 持仓量(期货专用) basis_spread 期现差(股指期货专用) settlement 结算价(期货日线专用) prev_settlement 结算价(期货日线专用) ========================= =================================================== :param datetime.datetime dt: 时间 :param bool skip_suspended: 是否跳过停牌日 :param bool include_now: 是否包含当天最新数据 :param str adjust_type: 复权类型,'pre', 'none', 'post' :param datetime.datetime adjust_orig: 复权起点; :return: `numpy.ndarray` """ raise NotImplementedError
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获取历史数据 :param instrument: 合约对象 :type instrument: :class:`~Instrument` :param int bar_count: 获取的历史数据数量 :param str frequency: 周期频率,`1d` 表示日周期, `1m` 表示分钟周期 :param str fields: 返回数据字段 ========================= =================================================== fields 字段名 ========================= =================================================== datetime 时间戳 open 开盘价 high 最高价 low 最低价 close 收盘价 volume 成交量 total_turnover 成交额 datetime int类型时间戳 open_interest 持仓量(期货专用) basis_spread 期现差(股指期货专用) settlement 结算价(期货日线专用) prev_settlement 结算价(期货日线专用) ========================= =================================================== :param datetime.datetime dt: 时间 :param bool skip_suspended: 是否跳过停牌日 :param bool include_now: 是否包含当天最新数据 :param str adjust_type: 复权类型,'pre', 'none', 'post' :param datetime.datetime adjust_orig: 复权起点; :return: `numpy.ndarray`
[ "获取历史数据" ]
python
train
EventTeam/beliefs
src/beliefs/beliefstate.py
https://github.com/EventTeam/beliefs/blob/c07d22b61bebeede74a72800030dde770bf64208/src/beliefs/beliefstate.py#L460-L473
def number_of_singleton_referents(self): """ Returns the number of singleton elements of the referential domain that are compatible with the current belief state. This is the size of the union of all referent sets. """ if self.__dict__['referential_domain']: ct = 0 for i in self.iter_singleton_referents(): ct += 1 return ct else: raise Exception("self.referential_domain must be defined")
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Returns the number of singleton elements of the referential domain that are compatible with the current belief state. This is the size of the union of all referent sets.
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python
train
LogicalDash/LiSE
allegedb/allegedb/cache.py
https://github.com/LogicalDash/LiSE/blob/fe6fd4f0a7c1780e065f4c9babb9bc443af6bb84/allegedb/allegedb/cache.py#L931-L938
def iter_predecessors(self, graph, dest, branch, turn, tick, *, forward=None): """Iterate over predecessors to a given destination node at a given time.""" if self.db._no_kc: yield from self._adds_dels_sucpred(self.predecessors[graph, dest], branch, turn, tick)[0] return if forward is None: forward = self.db._forward yield from self._get_origcache(graph, dest, branch, turn, tick, forward=forward)
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Iterate over predecessors to a given destination node at a given time.
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python
train
nugget/python-insteonplm
insteonplm/address.py
https://github.com/nugget/python-insteonplm/blob/65548041f1b0729ae1ae904443dd81b0c6cbf1bf/insteonplm/address.py#L116-L121
def hex(self): """Emit the address in bare hex format (aabbcc).""" addrstr = '000000' if self.addr is not None: addrstr = binascii.hexlify(self.addr).decode() return addrstr
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Emit the address in bare hex format (aabbcc).
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python
train
bspaans/python-mingus
mingus/midi/sequencer.py
https://github.com/bspaans/python-mingus/blob/aa5a5d992d45ada61be0f9f86261380731bd7749/mingus/midi/sequencer.py#L98-L102
def detach(self, listener): """Detach a listening object so that it won't receive any events anymore.""" if listener in self.listeners: self.listeners.remove(listener)
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Detach a listening object so that it won't receive any events anymore.
[ "Detach", "a", "listening", "object", "so", "that", "it", "won", "t", "receive", "any", "events", "anymore", "." ]
python
train
angr/claripy
claripy/ast/fp.py
https://github.com/angr/claripy/blob/4ed61924880af1ea8fb778047d896ec0156412a6/claripy/ast/fp.py#L16-L27
def to_fp(self, sort, rm=None): """ Convert this float to a different sort :param sort: The sort to convert to :param rm: Optional: The rounding mode to use :return: An FP AST """ if rm is None: rm = fp.RM.default() return fpToFP(rm, self, sort)
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Convert this float to a different sort :param sort: The sort to convert to :param rm: Optional: The rounding mode to use :return: An FP AST
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python
train
72squared/redpipe
redpipe/keyspaces.py
https://github.com/72squared/redpipe/blob/e6ee518bc9f3e2fee323c8c53d08997799bd9b1b/redpipe/keyspaces.py#L1503-L1531
def zrange(self, name, start, end, desc=False, withscores=False, score_cast_func=float): """ Returns all the elements including between ``start`` (non included) and ``stop`` (included). :param name: str the name of the redis key :param start: :param end: :param desc: :param withscores: :param score_cast_func: :return: """ with self.pipe as pipe: f = Future() res = pipe.zrange( self.redis_key(name), start, end, desc=desc, withscores=withscores, score_cast_func=score_cast_func) def cb(): if withscores: f.set([(self.valueparse.decode(v), s) for v, s in res.result]) else: f.set([self.valueparse.decode(v) for v in res.result]) pipe.on_execute(cb) return f
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Returns all the elements including between ``start`` (non included) and ``stop`` (included). :param name: str the name of the redis key :param start: :param end: :param desc: :param withscores: :param score_cast_func: :return:
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python
train
shmir/PyIxExplorer
ixexplorer/ixe_port.py
https://github.com/shmir/PyIxExplorer/blob/d6946b9ce0e8961507cc912062e10c365d4beee2/ixexplorer/ixe_port.py#L169-L181
def reserve(self, force=False): """ Reserve port. :param force: True - take forcefully, False - fail if port is reserved by other user """ if not force: try: self.api.call_rc('ixPortTakeOwnership {}'.format(self.uri)) except Exception as _: raise TgnError('Failed to take ownership for port {} current owner is {}'.format(self, self.owner)) else: self.api.call_rc('ixPortTakeOwnership {} force'.format(self.uri))
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Reserve port. :param force: True - take forcefully, False - fail if port is reserved by other user
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python
train
ejeschke/ginga
ginga/Bindings.py
https://github.com/ejeschke/ginga/blob/a78c893ec6f37a837de851947e9bb4625c597915/ginga/Bindings.py#L2658-L2704
def mode_key_down(self, viewer, keyname): """This method is called when a key is pressed and was not handled by some other handler with precedence, such as a subcanvas. """ # Is this a mode key? if keyname not in self.mode_map: if (keyname not in self.mode_tbl) or (self._kbdmode != 'meta'): # No return False bnch = self.mode_tbl[keyname] else: bnch = self.mode_map[keyname] mode_name = bnch.name self.logger.debug("cur mode='%s' mode pressed='%s'" % ( self._kbdmode, mode_name)) if mode_name == self._kbdmode: # <== same key was pressed that started the mode we're in # standard handling is to close the mode when we press the # key again that started that mode self.reset_mode(viewer) return True if self._delayed_reset: # <== this shouldn't happen, but put here to reset handling # of delayed_reset just in case (see cursor up handling) self._delayed_reset = False return True if ((self._kbdmode in (None, 'meta')) or (self._kbdmode_type != 'locked') or (mode_name == 'meta')): if self._kbdmode is not None: self.reset_mode(viewer) # activate this mode if self._kbdmode in (None, 'meta'): mode_type = bnch.type if mode_type is None: mode_type = self._kbdmode_type_default self.set_mode(mode_name, mode_type) if bnch.msg is not None: viewer.onscreen_message(bnch.msg) return True return False
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This method is called when a key is pressed and was not handled by some other handler with precedence, such as a subcanvas.
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python
train
mathiasertl/xmpp-backends
xmpp_backends/base.py
https://github.com/mathiasertl/xmpp-backends/blob/214ef0664dbf90fa300c2483b9b3416559e5d171/xmpp_backends/base.py#L174-L192
def module(self): """The module specified by the ``library`` attribute.""" if self._module is None: if self.library is None: raise ValueError( "Backend '%s' doesn't specify a library attribute" % self.__class__) try: if '.' in self.library: mod_path, cls_name = self.library.rsplit('.', 1) mod = import_module(mod_path) self._module = getattr(mod, cls_name) else: self._module = import_module(self.library) except (AttributeError, ImportError): raise ValueError("Couldn't load %s backend library" % cls_name) return self._module
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The module specified by the ``library`` attribute.
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python
train
jaegertracing/jaeger-client-python
jaeger_client/span.py
https://github.com/jaegertracing/jaeger-client-python/blob/06face094757c645a6d81f0e073c001931a22a05/jaeger_client/span.py#L76-L90
def set_tag(self, key, value): """ :param key: :param value: """ with self.update_lock: if key == ext_tags.SAMPLING_PRIORITY and not self._set_sampling_priority(value): return self if self.is_sampled(): tag = thrift.make_tag( key=key, value=value, max_length=self.tracer.max_tag_value_length, ) self.tags.append(tag) return self
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:param key: :param value:
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python
train
annoviko/pyclustering
pyclustering/cluster/xmeans.py
https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/xmeans.py#L412-L460
def __bayesian_information_criterion(self, clusters, centers): """! @brief Calculates splitting criterion for input clusters using bayesian information criterion. @param[in] clusters (list): Clusters for which splitting criterion should be calculated. @param[in] centers (list): Centers of the clusters. @return (double) Splitting criterion in line with bayesian information criterion. High value of splitting criterion means that current structure is much better. @see __minimum_noiseless_description_length(clusters, centers) """ scores = [float('inf')] * len(clusters) # splitting criterion dimension = len(self.__pointer_data[0]) # estimation of the noise variance in the data set sigma_sqrt = 0.0 K = len(clusters) N = 0.0 for index_cluster in range(0, len(clusters), 1): for index_object in clusters[index_cluster]: sigma_sqrt += euclidean_distance_square(self.__pointer_data[index_object], centers[index_cluster]); N += len(clusters[index_cluster]) if N - K > 0: sigma_sqrt /= (N - K) p = (K - 1) + dimension * K + 1 # in case of the same points, sigma_sqrt can be zero (issue: #407) sigma_multiplier = 0.0 if sigma_sqrt <= 0.0: sigma_multiplier = float('-inf') else: sigma_multiplier = dimension * 0.5 * log(sigma_sqrt) # splitting criterion for index_cluster in range(0, len(clusters), 1): n = len(clusters[index_cluster]) L = n * log(n) - n * log(N) - n * 0.5 * log(2.0 * numpy.pi) - n * sigma_multiplier - (n - K) * 0.5 # BIC calculation scores[index_cluster] = L - p * 0.5 * log(N) return sum(scores)
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! @brief Calculates splitting criterion for input clusters using bayesian information criterion. @param[in] clusters (list): Clusters for which splitting criterion should be calculated. @param[in] centers (list): Centers of the clusters. @return (double) Splitting criterion in line with bayesian information criterion. High value of splitting criterion means that current structure is much better. @see __minimum_noiseless_description_length(clusters, centers)
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python
valid
casebeer/audiogen
audiogen/sampler.py
https://github.com/casebeer/audiogen/blob/184dee2ca32c2bb4315a0f18e62288728fcd7881/audiogen/sampler.py#L189-L197
def cache_finite_samples(f): '''Decorator to cache audio samples produced by the wrapped generator.''' cache = {} def wrap(*args): key = FRAME_RATE, args if key not in cache: cache[key] = [sample for sample in f(*args)] return (sample for sample in cache[key]) return wrap
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Decorator to cache audio samples produced by the wrapped generator.
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python
train
booktype/python-ooxml
ooxml/serialize.py
https://github.com/booktype/python-ooxml/blob/b56990a5bee2e1bc46839cec5161ff3726dc4d87/ooxml/serialize.py#L776-L794
def serialize_endnote(ctx, document, el, root): "Serializes endnotes." footnote_num = el.rid if el.rid not in ctx.endnote_list: ctx.endnote_id += 1 ctx.endnote_list[el.rid] = ctx.endnote_id footnote_num = ctx.endnote_list[el.rid] note = etree.SubElement(root, 'sup') link = etree.SubElement(note, 'a') link.set('href', '#') link.text = u'{}'.format(footnote_num) fire_hooks(ctx, document, el, note, ctx.get_hook('endnote')) return root
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Serializes endnotes.
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python
train
kivy/python-for-android
pythonforandroid/recipe.py
https://github.com/kivy/python-for-android/blob/8e0e8056bc22e4d5bd3398a6b0301f38ff167933/pythonforandroid/recipe.py#L1167-L1173
def md5sum(filen): '''Calculate the md5sum of a file. ''' with open(filen, 'rb') as fileh: md5 = hashlib.md5(fileh.read()) return md5.hexdigest()
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Calculate the md5sum of a file.
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python
train
idmillington/layout
layout/managers/root.py
https://github.com/idmillington/layout/blob/c452d1d7a74c9a74f7639c1b49e2a41c4e354bb5/layout/managers/root.py#L55-L65
def _get_smallest_dimensions(self, data): """A utility method to return the minimum size needed to fit all the elements in.""" min_width = 0 min_height = 0 for element in self.elements: if not element: continue size = element.get_minimum_size(data) min_width = max(min_width, size.x) min_height = max(min_height, size.y) return datatypes.Point(min_width, min_height)
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A utility method to return the minimum size needed to fit all the elements in.
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python
train
ethereum/py-evm
eth/db/header.py
https://github.com/ethereum/py-evm/blob/58346848f076116381d3274bbcea96b9e2cfcbdf/eth/db/header.py#L286-L320
def _set_as_canonical_chain_head(cls, db: BaseDB, block_hash: Hash32 ) -> Tuple[Tuple[BlockHeader, ...], Tuple[BlockHeader, ...]]: """ Sets the canonical chain HEAD to the block header as specified by the given block hash. :return: a tuple of the headers that are newly in the canonical chain, and the headers that are no longer in the canonical chain """ try: header = cls._get_block_header_by_hash(db, block_hash) except HeaderNotFound: raise ValueError( "Cannot use unknown block hash as canonical head: {}".format(block_hash) ) new_canonical_headers = tuple(reversed(cls._find_new_ancestors(db, header))) old_canonical_headers = [] for h in new_canonical_headers: try: old_canonical_hash = cls._get_canonical_block_hash(db, h.block_number) except HeaderNotFound: # no old_canonical block, and no more possible break else: old_canonical_header = cls._get_block_header_by_hash(db, old_canonical_hash) old_canonical_headers.append(old_canonical_header) for h in new_canonical_headers: cls._add_block_number_to_hash_lookup(db, h) db.set(SchemaV1.make_canonical_head_hash_lookup_key(), header.hash) return new_canonical_headers, tuple(old_canonical_headers)
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Sets the canonical chain HEAD to the block header as specified by the given block hash. :return: a tuple of the headers that are newly in the canonical chain, and the headers that are no longer in the canonical chain
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python
train
saltstack/salt
salt/cloud/clouds/linode.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/cloud/clouds/linode.py#L1661-L1671
def _get_status_descr_by_id(status_id): ''' Return linode status by ID status_id linode VM status ID ''' for status_name, status_data in six.iteritems(LINODE_STATUS): if status_data['code'] == int(status_id): return status_data['descr'] return LINODE_STATUS.get(status_id, None)
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Return linode status by ID status_id linode VM status ID
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python
train
openvax/varcode
varcode/effects/effect_ordering.py
https://github.com/openvax/varcode/blob/981633db45ca2b31f76c06894a7360ea5d70a9b8/varcode/effects/effect_ordering.py#L316-L331
def select_between_exonic_splice_site_and_alternate_effect(effect): """ If the given effect is an ExonicSpliceSite then it might contain an alternate effect of higher priority. In that case, return the alternate effect. Otherwise, this acts as an identity function. """ if effect.__class__ is not ExonicSpliceSite: return effect if effect.alternate_effect is None: return effect splice_priority = effect_priority(effect) alternate_priority = effect_priority(effect.alternate_effect) if splice_priority > alternate_priority: return effect else: return effect.alternate_effect
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If the given effect is an ExonicSpliceSite then it might contain an alternate effect of higher priority. In that case, return the alternate effect. Otherwise, this acts as an identity function.
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python
train
AmesCornish/buttersink
buttersink/S3Store.py
https://github.com/AmesCornish/buttersink/blob/5cc37e30d9f8071fcf3497dca8b8a91b910321ea/buttersink/S3Store.py#L195-L203
def receiveVolumeInfo(self, paths): """ Return Context Manager for a file-like (stream) object to store volume info. """ path = self.selectReceivePath(paths) path = path + Store.theInfoExtension if self._skipDryRun(logger)("receive info in '%s'", path): return None return _Uploader(self.bucket, path, bufferSize=theInfoBufferSize)
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Return Context Manager for a file-like (stream) object to store volume info.
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python
train
tuomas2/automate
src/automate/statusobject.py
https://github.com/tuomas2/automate/blob/d8a8cd03cd0da047e033a2d305f3f260f8c4e017/src/automate/statusobject.py#L354-L366
def _do_change_status(self, status, force=False): """ This function is called by - set_status - _update_program_stack if active program is being changed - thia may be launched by sensor status change. status lock is necessary because these happen from different threads. This does not directly change status, but adds change request to queue. """ self.system.worker_thread.put(DummyStatusWorkerTask(self._request_status_change_in_queue, status, force=force))
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This function is called by - set_status - _update_program_stack if active program is being changed - thia may be launched by sensor status change. status lock is necessary because these happen from different threads. This does not directly change status, but adds change request to queue.
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python
train
project-ncl/pnc-cli
pnc_cli/projects.py
https://github.com/project-ncl/pnc-cli/blob/3dc149bf84928f60a8044ac50b58bbaddd451902/pnc_cli/projects.py#L44-L50
def update_project(id, **kwargs): """ Update an existing Project with new information """ content = update_project_raw(id, **kwargs) if content: return utils.format_json(content)
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Update an existing Project with new information
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python
train
Karaage-Cluster/karaage
karaage/plugins/kgapplications/views/states.py
https://github.com/Karaage-Cluster/karaage/blob/2f4c8b4e2d728b3fcbb151160c49000f1c04f5c9/karaage/plugins/kgapplications/views/states.py#L391-L459
def get_next_action(self, request, application, label, roles): """ Process the get_next_action request at the current step. """ actions = self.get_actions(request, application, roles) # if the user is not the applicant, the steps don't apply. if 'is_applicant' not in roles: return super(StateWithSteps, self).get_next_action( request, application, label, roles) # was label supplied? if label is None: # no label given, find first step and redirect to it. this_id = self._order[0] url = base.get_url(request, application, roles, this_id) return HttpResponseRedirect(url) else: # label was given, get the step position and id for it this_id = label if this_id not in self._steps: return HttpResponseBadRequest("<h1>Bad Request</h1>") position = self._order.index(this_id) # get the step given the label this_step = self._steps[this_id] # define list of allowed actions for step step_actions = {} if 'cancel' in actions: step_actions['cancel'] = "state:cancel" if 'submit' in actions and position == len(self._order) - 1: step_actions['submit'] = "state:submit" if position > 0: step_actions['prev'] = self._order[position - 1] if position < len(self._order) - 1: step_actions['next'] = self._order[position + 1] # process the request if request.method == "GET": # if GET request, state changes are not allowed response = this_step.view( request, application, this_id, roles, step_actions.keys()) assert isinstance(response, HttpResponse) return response elif request.method == "POST": # if POST request, state changes are allowed response = this_step.view( request, application, this_id, roles, step_actions.keys()) assert response is not None # If it was a HttpResponse, just return it if isinstance(response, HttpResponse): return response else: # try to lookup the response if response not in step_actions: raise RuntimeError( "Invalid response '%s' from step '%s'" % (response, this_step)) action = step_actions[response] # process the required action if action.startswith("state:"): return action[6:] else: url = base.get_url(request, application, roles, action) return HttpResponseRedirect(url) # Something went wrong. return HttpResponseBadRequest("<h1>Bad Request</h1>")
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Process the get_next_action request at the current step.
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python
train
The-Politico/politico-civic-almanac
almanac/utils/auth.py
https://github.com/The-Politico/politico-civic-almanac/blob/f97521fabd445c8a0fa97a435f6d39f517ef3892/almanac/utils/auth.py#L8-L21
def secure(view): """ Authentication decorator for views. If DEBUG is on, we serve the view without authenticating. Default is 'django.contrib.auth.decorators.login_required'. Can also be 'django.contrib.admin.views.decorators.staff_member_required' or a custom decorator. """ auth_decorator = import_class(settings.AUTH_DECORATOR) return ( view if project_settings.DEBUG else method_decorator(auth_decorator, name='dispatch')(view) )
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Authentication decorator for views. If DEBUG is on, we serve the view without authenticating. Default is 'django.contrib.auth.decorators.login_required'. Can also be 'django.contrib.admin.views.decorators.staff_member_required' or a custom decorator.
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python
train
Crypto-toolbox/bitex
bitex/api/WSS/bitfinex.py
https://github.com/Crypto-toolbox/bitex/blob/56d46ea3db6de5219a72dad9b052fbabc921232f/bitex/api/WSS/bitfinex.py#L307-L364
def process(self): """ Processes the Client queue, and passes the data to the respective methods. :return: """ while self.running: if self._processor_lock.acquire(blocking=False): if self.ping_timer: try: self._check_ping() except TimeoutError: log.exception("BitfinexWSS.ping(): TimedOut! (%ss)" % self.ping_timer) except (WebSocketConnectionClosedException, ConnectionResetError): log.exception("BitfinexWSS.ping(): Connection Error!") self.conn = None if not self.conn: # The connection was killed - initiate restart self._controller_q.put('restart') skip_processing = False try: ts, data = self.receiver_q.get(timeout=0.1) except queue.Empty: skip_processing = True ts = time.time() data = None if not skip_processing: log.debug("Processing Data: %s", data) if isinstance(data, list): self.handle_data(ts, data) else: # Not a list, hence it could be a response try: self.handle_response(ts, data) except UnknownEventError: # We don't know what event this is- Raise an # error & log data! log.exception("main() - UnknownEventError: %s", data) log.info("main() - Shutting Down due to " "Unknown Error!") self._controller_q.put('stop') except ConnectionResetError: log.info("processor Thread: Connection Was reset, " "initiating restart") self._controller_q.put('restart') self._check_heartbeats(ts) self._processor_lock.release() else: time.sleep(0.5)
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Processes the Client queue, and passes the data to the respective methods. :return:
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python
train
radjkarl/imgProcessor
imgProcessor/transformations.py
https://github.com/radjkarl/imgProcessor/blob/7c5a28718f81c01a430152c60a686ac50afbfd7c/imgProcessor/transformations.py#L78-L87
def toFloatArray(img): ''' transform an unsigned integer array into a float array of the right size ''' _D = {1: np.float32, # uint8 2: np.float32, # uint16 4: np.float64, # uint32 8: np.float64} # uint64 return img.astype(_D[img.itemsize])
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transform an unsigned integer array into a float array of the right size
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python
train
pkkid/python-plexapi
plexapi/sync.py
https://github.com/pkkid/python-plexapi/blob/9efbde96441c2bfbf410eacfb46e811e108e8bbc/plexapi/sync.py#L93-L101
def markDownloaded(self, media): """ Mark the file as downloaded (by the nature of Plex it will be marked as downloaded within any SyncItem where it presented). Parameters: media (base.Playable): the media to be marked as downloaded. """ url = '/sync/%s/item/%s/downloaded' % (self.clientIdentifier, media.ratingKey) media._server.query(url, method=requests.put)
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Mark the file as downloaded (by the nature of Plex it will be marked as downloaded within any SyncItem where it presented). Parameters: media (base.Playable): the media to be marked as downloaded.
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python
train
wonambi-python/wonambi
wonambi/trans/select.py
https://github.com/wonambi-python/wonambi/blob/1d8e3d7e53df8017c199f703bcab582914676e76/wonambi/trans/select.py#L690-L715
def _create_subepochs(x, nperseg, step): """Transform the data into a matrix for easy manipulation Parameters ---------- x : 1d ndarray actual data values nperseg : int number of samples in each row to create step : int distance in samples between rows Returns ------- 2d ndarray a view (i.e. doesn't copy data) of the original x, with shape determined by nperseg and step. You should use the last dimension """ axis = x.ndim - 1 # last dim nsmp = x.shape[axis] stride = x.strides[axis] noverlap = nperseg - step v_shape = *x.shape[:axis], (nsmp - noverlap) // step, nperseg v_strides = *x.strides[:axis], stride * step, stride v = as_strided(x, shape=v_shape, strides=v_strides, writeable=False) # much safer return v
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Transform the data into a matrix for easy manipulation Parameters ---------- x : 1d ndarray actual data values nperseg : int number of samples in each row to create step : int distance in samples between rows Returns ------- 2d ndarray a view (i.e. doesn't copy data) of the original x, with shape determined by nperseg and step. You should use the last dimension
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/zmq/kernelapp.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/zmq/kernelapp.py#L267-L270
def init_session(self): """create our session object""" default_secure(self.config) self.session = Session(config=self.config, username=u'kernel')
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create our session object
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python
test
Unidata/MetPy
examples/gridding/Point_Interpolation.py
https://github.com/Unidata/MetPy/blob/16f68a94919b9a82dcf9cada2169cf039129e67b/examples/gridding/Point_Interpolation.py#L24-L34
def basic_map(proj): """Make our basic default map for plotting""" fig = plt.figure(figsize=(15, 10)) add_metpy_logo(fig, 0, 80, size='large') view = fig.add_axes([0, 0, 1, 1], projection=proj) view.set_extent([-120, -70, 20, 50]) view.add_feature(cfeature.STATES.with_scale('50m')) view.add_feature(cfeature.OCEAN) view.add_feature(cfeature.COASTLINE) view.add_feature(cfeature.BORDERS, linestyle=':') return fig, view
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Make our basic default map for plotting
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python
train
PmagPy/PmagPy
pmagpy/pmag.py
https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/pmag.py#L10888-L10971
def chart_maker(Int, Top, start=100, outfile='chart.txt'): """ Makes a chart for performing IZZI experiments. Print out the file and tape it to the oven. This chart will help keep track of the different steps. Z : performed in zero field - enter the temperature XXX.0 in the sio formatted measurement file created by the LabView program I : performed in the lab field written at the top of the form P : a pTRM step - performed at the temperature and in the lab field. Parameters __________ Int : list of intervals [e.g., 50,10,5] Top : list of upper bounds for each interval [e.g., 500, 550, 600] start : first temperature step, default is 100 outfile : name of output file, default is 'chart.txt' Output _________ creates a file with: file: write down the name of the measurement file field: write down the lab field for the infield steps (in uT) the type of step (Z: zerofield, I: infield, P: pTRM step temperature of the step and code for SIO-like treatment steps XXX.0 [zero field] XXX.1 [in field] XXX.2 [pTRM check] - done in a lab field date : date the step was performed run # : an optional run number zones I-III : field in the zones in the oven start : time the run was started sp : time the setpoint was reached cool : time cooling started """ low, k, iz = start, 0, 0 Tzero = [] f = open('chart.txt', 'w') vline = '\t%s\n' % ( ' | | | | | | | |') hline = '______________________________________________________________________________\n' f.write('file:_________________ field:___________uT\n\n\n') f.write('%s\n' % ( ' date | run# | zone I | zone II | zone III | start | sp | cool|')) f.write(hline) f.write('\t%s' % (' 0.0')) f.write(vline) f.write(hline) for k in range(len(Top)): for t in range(low, Top[k]+Int[k], Int[k]): if iz == 0: Tzero.append(t) # zero field first step f.write('%s \t %s' % ('Z', str(t)+'.'+str(iz))) f.write(vline) f.write(hline) if len(Tzero) > 1: f.write('%s \t %s' % ('P', str(Tzero[-2])+'.'+str(2))) f.write(vline) f.write(hline) iz = 1 # infield after zero field first f.write('%s \t %s' % ('I', str(t)+'.'+str(iz))) f.write(vline) f.write(hline) # f.write('%s \t %s'%('T',str(t)+'.'+str(3))) # print second zero field (tail check) # f.write(vline) # f.write(hline) elif iz == 1: # infield first step f.write('%s \t %s' % ('I', str(t)+'.'+str(iz))) f.write(vline) f.write(hline) iz = 0 # zero field step (after infield) f.write('%s \t %s' % ('Z', str(t)+'.'+str(iz))) f.write(vline) f.write(hline) try: low = Top[k]+Int[k+1] # increment to next temp step except: f.close() print("output stored in: chart.txt")
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Makes a chart for performing IZZI experiments. Print out the file and tape it to the oven. This chart will help keep track of the different steps. Z : performed in zero field - enter the temperature XXX.0 in the sio formatted measurement file created by the LabView program I : performed in the lab field written at the top of the form P : a pTRM step - performed at the temperature and in the lab field. Parameters __________ Int : list of intervals [e.g., 50,10,5] Top : list of upper bounds for each interval [e.g., 500, 550, 600] start : first temperature step, default is 100 outfile : name of output file, default is 'chart.txt' Output _________ creates a file with: file: write down the name of the measurement file field: write down the lab field for the infield steps (in uT) the type of step (Z: zerofield, I: infield, P: pTRM step temperature of the step and code for SIO-like treatment steps XXX.0 [zero field] XXX.1 [in field] XXX.2 [pTRM check] - done in a lab field date : date the step was performed run # : an optional run number zones I-III : field in the zones in the oven start : time the run was started sp : time the setpoint was reached cool : time cooling started
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python
train
fboender/ansible-cmdb
lib/mako/lexer.py
https://github.com/fboender/ansible-cmdb/blob/ebd960ac10684e8c9ec2b12751bba2c4c9504ab7/lib/mako/lexer.py#L66-L94
def match_reg(self, reg): """match the given regular expression object to the current text position. if a match occurs, update the current text and line position. """ mp = self.match_position match = reg.match(self.text, self.match_position) if match: (start, end) = match.span() if end == start: self.match_position = end + 1 else: self.match_position = end self.matched_lineno = self.lineno lines = re.findall(r"\n", self.text[mp:self.match_position]) cp = mp - 1 while (cp >= 0 and cp < self.textlength and self.text[cp] != '\n'): cp -= 1 self.matched_charpos = mp - cp self.lineno += len(lines) #print "MATCHED:", match.group(0), "LINE START:", # self.matched_lineno, "LINE END:", self.lineno #print "MATCH:", regexp, "\n", self.text[mp : mp + 15], \ # (match and "TRUE" or "FALSE") return match
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match the given regular expression object to the current text position. if a match occurs, update the current text and line position.
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python
train
python-beaver/python-beaver
beaver/transports/stomp_transport.py
https://github.com/python-beaver/python-beaver/blob/93941e968016c5a962dffed9e7a9f6dc1d23236c/beaver/transports/stomp_transport.py#L64-L74
def reconnect(self): """Allows reconnection from when a handled TransportException is thrown""" try: self.conn.close() except Exception,e: self.logger.warn(e) self.createConnection() return True
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Allows reconnection from when a handled TransportException is thrown
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python
train
novopl/peltak
src/peltak/extra/docker/logic.py
https://github.com/novopl/peltak/blob/b627acc019e3665875fe76cdca0a14773b69beaa/src/peltak/extra/docker/logic.py#L58-L84
def docker_list(registry_pass): # type: (str) -> None """ List docker images stored in the remote registry. Args: registry_pass (str): Remote docker registry password. """ registry = conf.get('docker.registry', None) if registry is None: log.err("You must define docker.registry conf variable to list images") sys.exit(-1) registry_user = conf.get('docker.registry_user', None) if registry_user is None: registry_user = click.prompt("Username") rc = client.RegistryClient(registry, registry_user, registry_pass) images = {x: rc.list_tags(x) for x in rc.list_images()} shell.cprint("<32>Images in <34>{} <32>registry:", registry) for image, tags in images.items(): shell.cprint(' <92>{}', image) for tag in tags: shell.cprint(' <90>{}:<35>{}', image, tag)
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List docker images stored in the remote registry. Args: registry_pass (str): Remote docker registry password.
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python
train
spyder-ide/spyder
spyder/dependencies.py
https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/dependencies.py#L66-L75
def add(modname, features, required_version, installed_version=None, optional=False): """Add Spyder dependency""" global DEPENDENCIES for dependency in DEPENDENCIES: if dependency.modname == modname: raise ValueError("Dependency has already been registered: %s"\ % modname) DEPENDENCIES += [Dependency(modname, features, required_version, installed_version, optional)]
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Add Spyder dependency
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python
train
has2k1/plydata
plydata/dataframe/common.py
https://github.com/has2k1/plydata/blob/d8ca85ff70eee621e96f7c74034e90fec16e8b61/plydata/dataframe/common.py#L440-L445
def _all(cls, verb): """ A verb """ groups = set(_get_groups(verb)) return [col for col in verb.data if col not in groups]
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A verb
[ "A", "verb" ]
python
train
4degrees/clique
source/clique/collection.py
https://github.com/4degrees/clique/blob/af1d4fef1d60c30a870257199a4d98597d15417d/source/clique/collection.py#L77-L82
def _update_expression(self): '''Update internal expression.''' self._expression = re.compile( '^{0}(?P<index>(?P<padding>0*)\d+?){1}$' .format(re.escape(self.head), re.escape(self.tail)) )
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Update internal expression.
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python
train
StackStorm/pybind
pybind/nos/v6_0_2f/brocade_vcs_rpc/__init__.py
https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/nos/v6_0_2f/brocade_vcs_rpc/__init__.py#L158-L182
def _set_get_last_config_update_time(self, v, load=False): """ Setter method for get_last_config_update_time, mapped from YANG variable /brocade_vcs_rpc/get_last_config_update_time (rpc) If this variable is read-only (config: false) in the source YANG file, then _set_get_last_config_update_time is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_get_last_config_update_time() directly. YANG Description: This rpc function provides time-stamp of the last configutation change done on the managed device. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=get_last_config_update_time.get_last_config_update_time, is_leaf=True, yang_name="get-last-config-update-time", rest_name="get-last-config-update-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions={u'tailf-common': {u'hidden': u'rpccmd', u'actionpoint': u'last-config-update-time-action-point'}}, namespace='urn:brocade.com:mgmt:brocade-vcs', defining_module='brocade-vcs', yang_type='rpc', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """get_last_config_update_time must be of a type compatible with rpc""", 'defined-type': "rpc", 'generated-type': """YANGDynClass(base=get_last_config_update_time.get_last_config_update_time, is_leaf=True, yang_name="get-last-config-update-time", rest_name="get-last-config-update-time", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=False, extensions={u'tailf-common': {u'hidden': u'rpccmd', u'actionpoint': u'last-config-update-time-action-point'}}, namespace='urn:brocade.com:mgmt:brocade-vcs', defining_module='brocade-vcs', yang_type='rpc', is_config=True)""", }) self.__get_last_config_update_time = t if hasattr(self, '_set'): self._set()
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Setter method for get_last_config_update_time, mapped from YANG variable /brocade_vcs_rpc/get_last_config_update_time (rpc) If this variable is read-only (config: false) in the source YANG file, then _set_get_last_config_update_time is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_get_last_config_update_time() directly. YANG Description: This rpc function provides time-stamp of the last configutation change done on the managed device.
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python
train
rsgalloway/grit
grit/repo/proxy.py
https://github.com/rsgalloway/grit/blob/e6434ad8a1f4ac5d0903ebad630c81f8a5164d78/grit/repo/proxy.py#L90-L112
def __request(self, url, params): """ Make an HTTP POST request to the server and return JSON data. :param url: HTTP URL to object. :returns: Response as dict. """ log.debug('request: %s %s' %(url, str(params))) try: response = urlopen(url, urlencode(params)).read() if params.get('action') != 'data': log.debug('response: %s' % response) if params.get('action', None) == 'data': return response else: return json.loads(response) except TypeError, e: log.exception('request error') raise ServerError(e) except IOError, e: log.error('request error: %s' % str(e)) raise ServerError(e)
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Make an HTTP POST request to the server and return JSON data. :param url: HTTP URL to object. :returns: Response as dict.
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python
train
edx/edx-oauth2-provider
edx_oauth2_provider/oidc/core.py
https://github.com/edx/edx-oauth2-provider/blob/73e7569a8369e74c345022ccba634365e24befab/edx_oauth2_provider/oidc/core.py#L39-L56
def encode(self, secret, algorithm='HS256'): """ Encode the set of claims to the JWT (JSON Web Token) format according to the OpenID Connect specification: http://openid.net/specs/openid-connect-basic-1_0.html#IDToken Arguments: claims (dict): A dictionary with the OpenID Connect claims. secret (str): Secret used to encode the id_token. algorithm (str): Algorithm used for encoding. Defaults to HS256. Returns encoded JWT token string. """ return jwt.encode(self.claims, secret, algorithm)
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Encode the set of claims to the JWT (JSON Web Token) format according to the OpenID Connect specification: http://openid.net/specs/openid-connect-basic-1_0.html#IDToken Arguments: claims (dict): A dictionary with the OpenID Connect claims. secret (str): Secret used to encode the id_token. algorithm (str): Algorithm used for encoding. Defaults to HS256. Returns encoded JWT token string.
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python
train
aparo/pyes
pyes/orm/queryset.py
https://github.com/aparo/pyes/blob/712eb6095961755067b2b5baa262008ade6584b3/pyes/orm/queryset.py#L643-L647
def none(self): """ Returns an empty QuerySet. """ return EmptyQuerySet(model=self.model, using=self._using, connection=self._connection)
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Returns an empty QuerySet.
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python
train