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thiagopbueno/rddl2tf
rddl2tf/compiler.py
https://github.com/thiagopbueno/rddl2tf/blob/f7c03d3a74d2663807c1e23e04eeed2e85166b71/rddl2tf/compiler.py#L441-L461
def reward_scope(self, state: Sequence[tf.Tensor], action: Sequence[tf.Tensor], next_state: Sequence[tf.Tensor]) -> Dict[str, TensorFluent]: '''Returns the complete reward fluent scope for the current `state`, `action` fluents, and `next_state` fluents. Args: state (Sequence[tf.Tensor]): The current state fluents. action (Sequence[tf.Tensor]): The action fluents. next_state (Sequence[tf.Tensor]): The next state fluents. Returns: A mapping from fluent names to :obj:`rddl2tf.fluent.TensorFluent`. ''' scope = {} scope.update(self.non_fluents_scope()) scope.update(self.state_scope(state)) scope.update(self.action_scope(action)) scope.update(self.next_state_scope(next_state)) return scope
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Returns the complete reward fluent scope for the current `state`, `action` fluents, and `next_state` fluents. Args: state (Sequence[tf.Tensor]): The current state fluents. action (Sequence[tf.Tensor]): The action fluents. next_state (Sequence[tf.Tensor]): The next state fluents. Returns: A mapping from fluent names to :obj:`rddl2tf.fluent.TensorFluent`.
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python
train
Azure/blobxfer
blobxfer/operations/upload.py
https://github.com/Azure/blobxfer/blob/3eccbe7530cc6a20ab2d30f9e034b6f021817f34/blobxfer/operations/upload.py#L260-L281
def _check_for_uploads_from_md5(self): # type: (Uploader) -> None """Check queue for a file to upload :param Uploader self: this """ cv = self._md5_offload.done_cv while not self.termination_check_md5: result = None cv.acquire() while True: result = self._md5_offload.pop_done_queue() if result is None: # use cv timeout due to possible non-wake while running cv.wait(1) # check for terminating conditions if self.termination_check_md5: break else: break cv.release() if result is not None: self._post_md5_skip_on_check(result[0], result[3])
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Check queue for a file to upload :param Uploader self: this
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python
train
fermiPy/fermipy
fermipy/hpx_utils.py
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/hpx_utils.py#L559-L571
def create_from_hdu(cls, hdu, ebins=None): """ Creates an HPX object from a FITS header. hdu : The FITS hdu ebins : Energy bin edges [optional] """ convname = HPX.identify_HPX_convention(hdu.header) conv = HPX_FITS_CONVENTIONS[convname] try: pixels = hdu.data[conv.idxstring] except KeyError: pixels = None return cls.create_from_header(hdu.header, ebins, pixels)
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Creates an HPX object from a FITS header. hdu : The FITS hdu ebins : Energy bin edges [optional]
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python
train
fbcotter/py3nvml
py3nvml/py3nvml.py
https://github.com/fbcotter/py3nvml/blob/47f0f2c0eee56dec4e4beebec26b734e01d357b7/py3nvml/py3nvml.py#L2128-L2154
def nvmlDeviceGetMultiGpuBoard(handle): r""" /** * Retrieves whether the device is on a Multi-GPU Board * Devices that are on multi-GPU boards will set \a multiGpuBool to a non-zero value. * * For Fermi &tm; or newer fully supported devices. * * @param device The identifier of the target device * @param multiGpuBool Reference in which to return a zero or non-zero value * to indicate whether the device is on a multi GPU board * * @return * - \ref NVML_SUCCESS if \a multiGpuBool has been set * - \ref NVML_ERROR_UNINITIALIZED if the library has not been successfully initialized * - \ref NVML_ERROR_INVALID_ARGUMENT if \a device is invalid or \a multiGpuBool is NULL * - \ref NVML_ERROR_NOT_SUPPORTED if the device does not support this feature * - \ref NVML_ERROR_GPU_IS_LOST if the target GPU has fallen off the bus or is otherwise inaccessible * - \ref NVML_ERROR_UNKNOWN on any unexpected error */ nvmlReturn_t DECLDIR nvmlDeviceGetMultiGpuBoard """ c_multiGpu = c_uint(); fn = _nvmlGetFunctionPointer("nvmlDeviceGetMultiGpuBoard") ret = fn(handle, byref(c_multiGpu)) _nvmlCheckReturn(ret) return bytes_to_str(c_multiGpu.value)
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r""" /** * Retrieves whether the device is on a Multi-GPU Board * Devices that are on multi-GPU boards will set \a multiGpuBool to a non-zero value. * * For Fermi &tm; or newer fully supported devices. * * @param device The identifier of the target device * @param multiGpuBool Reference in which to return a zero or non-zero value * to indicate whether the device is on a multi GPU board * * @return * - \ref NVML_SUCCESS if \a multiGpuBool has been set * - \ref NVML_ERROR_UNINITIALIZED if the library has not been successfully initialized * - \ref NVML_ERROR_INVALID_ARGUMENT if \a device is invalid or \a multiGpuBool is NULL * - \ref NVML_ERROR_NOT_SUPPORTED if the device does not support this feature * - \ref NVML_ERROR_GPU_IS_LOST if the target GPU has fallen off the bus or is otherwise inaccessible * - \ref NVML_ERROR_UNKNOWN on any unexpected error */ nvmlReturn_t DECLDIR nvmlDeviceGetMultiGpuBoard
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python
train
dwavesystems/dimod
dimod/higherorder/polynomial.py
https://github.com/dwavesystems/dimod/blob/beff1b7f86b559d923ac653c1de6d593876d6d38/dimod/higherorder/polynomial.py#L461-L491
def to_binary(self, copy=False): """Return a binary polynomial over `{0, 1}` variables. Args: copy (optional, default=False): If True, the returned polynomial is always a copy. Otherwise, if the polynomial is binary-valued already it returns itself. Returns: :obj:`.BinaryPolynomial` """ if self.vartype is Vartype.BINARY: if copy: return self.copy() else: return self new = BinaryPolynomial({}, Vartype.BINARY) # s = 2x - 1 for term, bias in self.items(): for t in map(frozenset, powerset(term)): newbias = bias * 2**len(t) * (-1)**(len(term) - len(t)) if t in new: new[t] += newbias else: new[t] = newbias return new
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Return a binary polynomial over `{0, 1}` variables. Args: copy (optional, default=False): If True, the returned polynomial is always a copy. Otherwise, if the polynomial is binary-valued already it returns itself. Returns: :obj:`.BinaryPolynomial`
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python
train
apple/turicreate
src/unity/python/turicreate/data_structures/sframe.py
https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/unity/python/turicreate/data_structures/sframe.py#L1845-L1942
def to_sql(self, conn, table_name, dbapi_module=None, use_python_type_specifiers=False, use_exact_column_names=True): """ Convert an SFrame to a single table in a SQL database. This function does not attempt to create the table or check if a table named `table_name` exists in the database. It simply assumes that `table_name` exists in the database and appends to it. `to_sql` can be thought of as a convenience wrapper around parameterized SQL insert statements. Parameters ---------- conn : dbapi2.Connection A DBAPI2 connection object. Any connection object originating from the 'connect' method of a DBAPI2-compliant package can be used. table_name : str The name of the table to append the data in this SFrame. dbapi_module : module | package, optional The top-level DBAPI2 module/package that constructed the given connection object. By default, a best guess of which module the connection came from is made. In the event that this guess is wrong, this will need to be specified. use_python_type_specifiers : bool, optional If the DBAPI2 module's parameter marker style is 'format' or 'pyformat', attempt to use accurate type specifiers for each value ('s' for string, 'd' for integer, etc.). Many DBAPI2 modules simply use 's' for all types if they use these parameter markers, so this is False by default. use_exact_column_names : bool, optional Specify the column names of the SFrame when inserting its contents into the DB. If the specified table does not have the exact same column names as the SFrame, inserting the data will fail. If False, the columns in the SFrame are inserted in order without care of the schema of the DB table. True by default. """ mod_info = _get_global_dbapi_info(dbapi_module, conn) c = conn.cursor() col_info = list(zip(self.column_names(), self.column_types())) if not use_python_type_specifiers: _pytype_to_printf = lambda x: 's' # DBAPI2 standard allows for five different ways to specify parameters sql_param = { 'qmark' : lambda name,col_num,col_type: '?', 'numeric' : lambda name,col_num,col_type:':'+str(col_num+1), 'named' : lambda name,col_num,col_type:':'+str(name), 'format' : lambda name,col_num,col_type:'%'+_pytype_to_printf(col_type), 'pyformat': lambda name,col_num,col_type:'%('+str(name)+')'+_pytype_to_printf(col_type), } get_sql_param = sql_param[mod_info['paramstyle']] # form insert string ins_str = "INSERT INTO " + str(table_name) value_str = " VALUES (" col_str = " (" count = 0 for i in col_info: col_str += i[0] value_str += get_sql_param(i[0],count,i[1]) if count < len(col_info)-1: col_str += "," value_str += "," count += 1 col_str += ")" value_str += ")" if use_exact_column_names: ins_str += col_str ins_str += value_str # Some formats require values in an iterable, some a dictionary if (mod_info['paramstyle'] == 'named' or\ mod_info['paramstyle'] == 'pyformat'): prepare_sf_row = lambda x:x else: col_names = self.column_names() prepare_sf_row = lambda x: [x[i] for i in col_names] for i in self: try: c.execute(ins_str, prepare_sf_row(i)) except mod_info['Error'] as e: if hasattr(conn, 'rollback'): conn.rollback() raise e conn.commit() c.close()
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Convert an SFrame to a single table in a SQL database. This function does not attempt to create the table or check if a table named `table_name` exists in the database. It simply assumes that `table_name` exists in the database and appends to it. `to_sql` can be thought of as a convenience wrapper around parameterized SQL insert statements. Parameters ---------- conn : dbapi2.Connection A DBAPI2 connection object. Any connection object originating from the 'connect' method of a DBAPI2-compliant package can be used. table_name : str The name of the table to append the data in this SFrame. dbapi_module : module | package, optional The top-level DBAPI2 module/package that constructed the given connection object. By default, a best guess of which module the connection came from is made. In the event that this guess is wrong, this will need to be specified. use_python_type_specifiers : bool, optional If the DBAPI2 module's parameter marker style is 'format' or 'pyformat', attempt to use accurate type specifiers for each value ('s' for string, 'd' for integer, etc.). Many DBAPI2 modules simply use 's' for all types if they use these parameter markers, so this is False by default. use_exact_column_names : bool, optional Specify the column names of the SFrame when inserting its contents into the DB. If the specified table does not have the exact same column names as the SFrame, inserting the data will fail. If False, the columns in the SFrame are inserted in order without care of the schema of the DB table. True by default.
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python
train
not-na/peng3d
peng3d/gui/__init__.py
https://github.com/not-na/peng3d/blob/1151be665b26cc8a479f6307086ba919e4d32d85/peng3d/gui/__init__.py#L68-L84
def changeSubMenu(self,submenu): """ Changes the submenu that is displayed. :raises ValueError: if the name was not previously registered """ if submenu not in self.submenus: raise ValueError("Submenu %s does not exist!"%submenu) elif submenu == self.activeSubMenu: return # Ignore double submenu activation to prevent bugs in submenu initializer old = self.activeSubMenu self.activeSubMenu = submenu if old is not None: self.submenus[old].on_exit(submenu) self.submenus[old].doAction("exit") self.submenu.on_enter(old) self.submenu.doAction("enter")
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Changes the submenu that is displayed. :raises ValueError: if the name was not previously registered
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python
test
elastic/elasticsearch-py
elasticsearch/transport.py
https://github.com/elastic/elasticsearch-py/blob/2aab285c8f506f3863cbdaba3c90a685c510ba00/elasticsearch/transport.py#L258-L350
def perform_request(self, method, url, headers=None, params=None, body=None): """ Perform the actual request. Retrieve a connection from the connection pool, pass all the information to it's perform_request method and return the data. If an exception was raised, mark the connection as failed and retry (up to `max_retries` times). If the operation was succesful and the connection used was previously marked as dead, mark it as live, resetting it's failure count. :arg method: HTTP method to use :arg url: absolute url (without host) to target :arg headers: dictionary of headers, will be handed over to the underlying :class:`~elasticsearch.Connection` class :arg params: dictionary of query parameters, will be handed over to the underlying :class:`~elasticsearch.Connection` class for serialization :arg body: body of the request, will be serializes using serializer and passed to the connection """ if body is not None: body = self.serializer.dumps(body) # some clients or environments don't support sending GET with body if method in ('HEAD', 'GET') and self.send_get_body_as != 'GET': # send it as post instead if self.send_get_body_as == 'POST': method = 'POST' # or as source parameter elif self.send_get_body_as == 'source': if params is None: params = {} params['source'] = body body = None if body is not None: try: body = body.encode('utf-8', 'surrogatepass') except (UnicodeDecodeError, AttributeError): # bytes/str - no need to re-encode pass ignore = () timeout = None if params: timeout = params.pop('request_timeout', None) ignore = params.pop('ignore', ()) if isinstance(ignore, int): ignore = (ignore, ) for attempt in range(self.max_retries + 1): connection = self.get_connection() try: # add a delay before attempting the next retry # 0, 1, 3, 7, etc... delay = 2**attempt - 1 time.sleep(delay) status, headers_response, data = connection.perform_request(method, url, params, body, headers=headers, ignore=ignore, timeout=timeout) except TransportError as e: if method == 'HEAD' and e.status_code == 404: return False retry = False if isinstance(e, ConnectionTimeout): retry = self.retry_on_timeout elif isinstance(e, ConnectionError): retry = True elif e.status_code in self.retry_on_status: retry = True if retry: # only mark as dead if we are retrying self.mark_dead(connection) # raise exception on last retry if attempt == self.max_retries: raise else: raise else: # connection didn't fail, confirm it's live status self.connection_pool.mark_live(connection) if method == 'HEAD': return 200 <= status < 300 if data: data = self.deserializer.loads(data, headers_response.get('content-type')) return data
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Perform the actual request. Retrieve a connection from the connection pool, pass all the information to it's perform_request method and return the data. If an exception was raised, mark the connection as failed and retry (up to `max_retries` times). If the operation was succesful and the connection used was previously marked as dead, mark it as live, resetting it's failure count. :arg method: HTTP method to use :arg url: absolute url (without host) to target :arg headers: dictionary of headers, will be handed over to the underlying :class:`~elasticsearch.Connection` class :arg params: dictionary of query parameters, will be handed over to the underlying :class:`~elasticsearch.Connection` class for serialization :arg body: body of the request, will be serializes using serializer and passed to the connection
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python
train
threeML/astromodels
astromodels/core/parameter.py
https://github.com/threeML/astromodels/blob/9aac365a372f77603039533df9a6b694c1e360d5/astromodels/core/parameter.py#L325-L346
def in_unit_of(self, unit, as_quantity=False): """ Return the current value transformed to the new units :param unit: either an astropy.Unit instance, or a string which can be converted to an astropy.Unit instance, like "1 / (erg cm**2 s)" :param as_quantity: if True, the method return an astropy.Quantity, if False just a floating point number. Default is False :return: either a floating point or a astropy.Quantity depending on the value of "as_quantity" """ new_unit = u.Unit(unit) new_quantity = self.as_quantity.to(new_unit) if as_quantity: return new_quantity else: return new_quantity.value
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Return the current value transformed to the new units :param unit: either an astropy.Unit instance, or a string which can be converted to an astropy.Unit instance, like "1 / (erg cm**2 s)" :param as_quantity: if True, the method return an astropy.Quantity, if False just a floating point number. Default is False :return: either a floating point or a astropy.Quantity depending on the value of "as_quantity"
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/psutil/_common.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/psutil/_common.py#L106-L119
def isfile_strict(path): """Same as os.path.isfile() but does not swallow EACCES / EPERM exceptions, see: http://mail.python.org/pipermail/python-dev/2012-June/120787.html """ try: st = os.stat(path) except OSError: err = sys.exc_info()[1] if err.errno in (errno.EPERM, errno.EACCES): raise return False else: return stat.S_ISREG(st.st_mode)
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Same as os.path.isfile() but does not swallow EACCES / EPERM exceptions, see: http://mail.python.org/pipermail/python-dev/2012-June/120787.html
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python
test
pjmark/NIMPA
niftypet/nimpa/prc/imio.py
https://github.com/pjmark/NIMPA/blob/3f4231fed2934a1d92e4cd8e9e153b0118e29d86/niftypet/nimpa/prc/imio.py#L130-L187
def array2nii(im, A, fnii, descrip='', trnsp=(), flip=(), storage_as=[]): '''Store the numpy array 'im' to a NIfTI file 'fnii'. ---- Arguments: 'im': image to be stored in NIfTI 'A': affine transformation 'fnii': output NIfTI file name. 'descrip': the description given to the file 'trsnp': transpose/permute the dimensions. In NIfTI it has to be in this order: [x,y,z,t,...]) 'flip': flip tupple for flipping the direction of x,y,z axes. (1: no flip, -1: flip) 'storage_as': uses the flip and displacement as given by the following NifTI dictionary, obtained using nimpa.getnii(filepath, output='all'). ''' if not len(trnsp) in [0,3,4] and not len(flip) in [0,3]: raise ValueError('e> number of flip and/or transpose elements is incorrect.') #--------------------------------------------------------------------------- #> TRANSLATIONS and FLIPS #> get the same geometry as the input NIfTI file in the form of dictionary, #>>as obtained from getnii(..., output='all') #> permute the axis order in the image array if isinstance(storage_as, dict) and 'transpose' in storage_as \ and 'flip' in storage_as: trnsp = (storage_as['transpose'].index(0), storage_as['transpose'].index(1), storage_as['transpose'].index(2)) flip = storage_as['flip'] if trnsp==(): im = im.transpose() #> check if the image is 4D (dynamic) and modify as needed elif len(trnsp)==3 and im.ndim==4: trnsp = tuple([t+1 for t in trnsp] + [0]) im = im.transpose(trnsp) else: im = im.transpose(trnsp) #> perform flip of x,y,z axes after transposition into proper NIfTI order if flip!=() and len(flip)==3: im = im[::-flip[0], ::-flip[1], ::-flip[2], ...] #--------------------------------------------------------------------------- nii = nib.Nifti1Image(im, A) hdr = nii.header hdr.set_sform(None, code='scanner') hdr['cal_max'] = np.max(im) #np.percentile(im, 90) # hdr['cal_min'] = np.min(im) hdr['descrip'] = descrip nib.save(nii, fnii)
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Store the numpy array 'im' to a NIfTI file 'fnii'. ---- Arguments: 'im': image to be stored in NIfTI 'A': affine transformation 'fnii': output NIfTI file name. 'descrip': the description given to the file 'trsnp': transpose/permute the dimensions. In NIfTI it has to be in this order: [x,y,z,t,...]) 'flip': flip tupple for flipping the direction of x,y,z axes. (1: no flip, -1: flip) 'storage_as': uses the flip and displacement as given by the following NifTI dictionary, obtained using nimpa.getnii(filepath, output='all').
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python
train
mschwager/cohesion
lib/cohesion/parser.py
https://github.com/mschwager/cohesion/blob/b242ad59770940f3a0904931f27755ede009f491/lib/cohesion/parser.py#L32-L36
def get_attribute_name_id(attr): """ Return the attribute name identifier """ return attr.value.id if isinstance(attr.value, ast.Name) else None
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Return the attribute name identifier
[ "Return", "the", "attribute", "name", "identifier" ]
python
train
bwesterb/mirte
src/mirteFile.py
https://github.com/bwesterb/mirte/blob/c58db8c993cd15ffdc64b52703cd466213913200/src/mirteFile.py#L95-L109
def load_mirteFile(path, m, logger=None): """ Loads the mirte-file at <path> into the manager <m>. """ l = logging.getLogger('load_mirteFile') if logger is None else logger had = set() for name, path, d in walk_mirteFiles(path, logger): if os.path.realpath(path) in m.loaded_mirteFiles: continue identifier = name if name in had: identifier = path else: had.add(name) l.info('loading %s' % identifier) m.loaded_mirteFiles.add(os.path.realpath(path)) _load_mirteFile(d, m)
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Loads the mirte-file at <path> into the manager <m>.
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python
train
OCR-D/core
ocrd_validators/ocrd_validators/page_validator.py
https://github.com/OCR-D/core/blob/57e68c578526cb955fd2e368207f5386c459d91d/ocrd_validators/ocrd_validators/page_validator.py#L100-L114
def get_text(node, strategy): """ Get the most confident text results, either those with @index = 1 or the first text results or empty string. """ textEquivs = node.get_TextEquiv() if not textEquivs: log.debug("No text results on %s %s", node, node.id) return '' # elif strategy == 'index1': else: if len(textEquivs) > 1: index1 = [x for x in textEquivs if x.index == 1] if index1: return index1[0].get_Unicode().strip() return textEquivs[0].get_Unicode().strip()
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Get the most confident text results, either those with @index = 1 or the first text results or empty string.
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python
train
HttpRunner/HttpRunner
httprunner/logger.py
https://github.com/HttpRunner/HttpRunner/blob/f259551bf9c8ba905eae5c1afcf2efea20ae0871/httprunner/logger.py#L21-L46
def setup_logger(log_level, log_file=None): """setup root logger with ColoredFormatter.""" level = getattr(logging, log_level.upper(), None) if not level: color_print("Invalid log level: %s" % log_level, "RED") sys.exit(1) # hide traceback when log level is INFO/WARNING/ERROR/CRITICAL if level >= logging.INFO: sys.tracebacklimit = 0 formatter = ColoredFormatter( u"%(log_color)s%(bg_white)s%(levelname)-8s%(reset)s %(message)s", datefmt=None, reset=True, log_colors=log_colors_config ) if log_file: handler = logging.FileHandler(log_file, encoding="utf-8") else: handler = logging.StreamHandler() handler.setFormatter(formatter) logger.addHandler(handler) logger.setLevel(level)
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setup root logger with ColoredFormatter.
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python
train
saltstack/salt
salt/modules/debian_ip.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/debian_ip.py#L1453-L1463
def _read_temp(data): ''' Return what would be written to disk ''' tout = StringIO() tout.write(data) tout.seek(0) output = tout.readlines() tout.close() return output
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Return what would be written to disk
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python
train
weld-project/weld
python/numpy/weldnumpy/weldnumpy.py
https://github.com/weld-project/weld/blob/8ddd6db6b28878bef0892da44b1d2002b564389c/python/numpy/weldnumpy/weldnumpy.py#L44-L53
def get_supported_binary_ops(): ''' Returns a dictionary of the Weld supported binary ops, with values being their Weld symbol. ''' binary_ops = {} binary_ops[np.add.__name__] = '+' binary_ops[np.subtract.__name__] = '-' binary_ops[np.multiply.__name__] = '*' binary_ops[np.divide.__name__] = '/' return binary_ops
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Returns a dictionary of the Weld supported binary ops, with values being their Weld symbol.
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python
train
ecederstrand/exchangelib
exchangelib/folders.py
https://github.com/ecederstrand/exchangelib/blob/736347b337c239fcd6d592db5b29e819f753c1ba/exchangelib/folders.py#L1594-L1602
def folder_cls_from_folder_name(cls, folder_name, locale): """Returns the folder class that matches a localized folder name. locale is a string, e.g. 'da_DK' """ for folder_cls in cls.WELLKNOWN_FOLDERS + NON_DELETEABLE_FOLDERS: if folder_name.lower() in folder_cls.localized_names(locale): return folder_cls raise KeyError()
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Returns the folder class that matches a localized folder name. locale is a string, e.g. 'da_DK'
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python
train
noxdafox/pebble
pebble/common.py
https://github.com/noxdafox/pebble/blob/d8f3d989655715754f0a65d7419cfa584491f614/pebble/common.py#L177-L183
def send_result(pipe, data): """Send result handling pickling and communication errors.""" try: pipe.send(data) except (pickle.PicklingError, TypeError) as error: error.traceback = format_exc() pipe.send(RemoteException(error, error.traceback))
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Send result handling pickling and communication errors.
[ "Send", "result", "handling", "pickling", "and", "communication", "errors", "." ]
python
train
codenerix/django-codenerix
codenerix/templatetags/codenerix_common.py
https://github.com/codenerix/django-codenerix/blob/1f5527b352141caaee902b37b2648791a06bd57d/codenerix/templatetags/codenerix_common.py#L241-L262
def objectatrib(instance, atrib): ''' this filter is going to be useful to execute an object method or get an object attribute dynamically. this method is going to take into account the atrib param can contains underscores ''' atrib = atrib.replace("__", ".") atribs = [] atribs = atrib.split(".") obj = instance for atrib in atribs: if type(obj) == dict: result = obj[atrib] else: try: result = getattr(obj, atrib)() except Exception: result = getattr(obj, atrib) obj = result return result
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this filter is going to be useful to execute an object method or get an object attribute dynamically. this method is going to take into account the atrib param can contains underscores
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python
train
projectshift/shift-schema
shiftschema/validators/email.py
https://github.com/projectshift/shift-schema/blob/07787b540d3369bb37217ffbfbe629118edaf0eb/shiftschema/validators/email.py#L26-L43
def validate(self, value, model=None, context=None): """ Validate Perform value validation and return result :param value: value to check :param model: parent model being validated :param context: object or None, validation context :return: shiftschema.results.SimpleResult """ regex = self.regex() match = regex.match(value) if not match: return Error(self.not_email) # success otherwise return Error()
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Validate Perform value validation and return result :param value: value to check :param model: parent model being validated :param context: object or None, validation context :return: shiftschema.results.SimpleResult
[ "Validate", "Perform", "value", "validation", "and", "return", "result" ]
python
train
cggh/scikit-allel
allel/model/ndarray.py
https://github.com/cggh/scikit-allel/blob/3c979a57a100240ba959dd13f98839349530f215/allel/model/ndarray.py#L2510-L2520
def distinct_counts(self): """Return counts for each distinct haplotype.""" # hash the haplotypes k = [hash(self.values[:, i].tobytes()) for i in range(self.shape[1])] # count and sort # noinspection PyArgumentList counts = sorted(collections.Counter(k).values(), reverse=True) return np.asarray(counts)
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Return counts for each distinct haplotype.
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python
train
gwpy/gwpy
gwpy/timeseries/timeseries.py
https://github.com/gwpy/gwpy/blob/7a92b917e7dd2d99b15895293a1fa1d66cdb210a/gwpy/timeseries/timeseries.py#L968-L1003
def zpk(self, zeros, poles, gain, analog=True, **kwargs): """Filter this `TimeSeries` by applying a zero-pole-gain filter Parameters ---------- zeros : `array-like` list of zero frequencies (in Hertz) poles : `array-like` list of pole frequencies (in Hertz) gain : `float` DC gain of filter analog : `bool`, optional type of ZPK being applied, if `analog=True` all parameters will be converted in the Z-domain for digital filtering Returns ------- timeseries : `TimeSeries` the filtered version of the input data See Also -------- TimeSeries.filter for details on how a digital ZPK-format filter is applied Examples -------- To apply a zpk filter with file poles at 100 Hz, and five zeros at 1 Hz (giving an overall DC gain of 1e-10):: >>> data2 = data.zpk([100]*5, [1]*5, 1e-10) """ return self.filter(zeros, poles, gain, analog=analog, **kwargs)
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Filter this `TimeSeries` by applying a zero-pole-gain filter Parameters ---------- zeros : `array-like` list of zero frequencies (in Hertz) poles : `array-like` list of pole frequencies (in Hertz) gain : `float` DC gain of filter analog : `bool`, optional type of ZPK being applied, if `analog=True` all parameters will be converted in the Z-domain for digital filtering Returns ------- timeseries : `TimeSeries` the filtered version of the input data See Also -------- TimeSeries.filter for details on how a digital ZPK-format filter is applied Examples -------- To apply a zpk filter with file poles at 100 Hz, and five zeros at 1 Hz (giving an overall DC gain of 1e-10):: >>> data2 = data.zpk([100]*5, [1]*5, 1e-10)
[ "Filter", "this", "TimeSeries", "by", "applying", "a", "zero", "-", "pole", "-", "gain", "filter" ]
python
train
portfors-lab/sparkle
sparkle/gui/stim/stim_detail.py
https://github.com/portfors-lab/sparkle/blob/5fad1cf2bec58ec6b15d91da20f6236a74826110/sparkle/gui/stim/stim_detail.py#L24-L36
def setDoc(self, doc): """Presents the documentation :param doc: documentation for StimulusModel. i.e. returned from :meth:`componentDoc<sparkle.stim.stimulus_model.StimulusModel.componentDoc>` or :meth:`templateDoc<sparkle.stim.stimulus_model.StimulusModel.templateDoc>` """ self.ui.overAtten.setNum(doc['overloaded_attenuation']) # also set composite stim type # self.ui.traceType.setText(doc['testtype']) self.ui.componentDetails.clearDoc() self.ui.componentDetails.setDoc(doc['components'])
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Presents the documentation :param doc: documentation for StimulusModel. i.e. returned from :meth:`componentDoc<sparkle.stim.stimulus_model.StimulusModel.componentDoc>` or :meth:`templateDoc<sparkle.stim.stimulus_model.StimulusModel.templateDoc>`
[ "Presents", "the", "documentation" ]
python
train
nvdv/vprof
vprof/flame_graph.py
https://github.com/nvdv/vprof/blob/4c3ff78f8920ab10cb9c00b14143452aa09ff6bb/vprof/flame_graph.py#L75-L79
def _fill_sample_count(self, node): """Counts and fills sample counts inside call tree.""" node['sampleCount'] += sum( self._fill_sample_count(child) for child in node['children']) return node['sampleCount']
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Counts and fills sample counts inside call tree.
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python
test
glottobank/python-newick
src/newick.py
https://github.com/glottobank/python-newick/blob/e8d4d1e4610f271d0f0e5cb86c0e0360b43bd702/src/newick.py#L360-L371
def loads(s, strip_comments=False, **kw): """ Load a list of trees from a Newick formatted string. :param s: Newick formatted string. :param strip_comments: Flag signaling whether to strip comments enclosed in square \ brackets. :param kw: Keyword arguments are passed through to `Node.create`. :return: List of Node objects. """ kw['strip_comments'] = strip_comments return [parse_node(ss.strip(), **kw) for ss in s.split(';') if ss.strip()]
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Load a list of trees from a Newick formatted string. :param s: Newick formatted string. :param strip_comments: Flag signaling whether to strip comments enclosed in square \ brackets. :param kw: Keyword arguments are passed through to `Node.create`. :return: List of Node objects.
[ "Load", "a", "list", "of", "trees", "from", "a", "Newick", "formatted", "string", "." ]
python
test
swistakm/graceful
src/graceful/authentication.py
https://github.com/swistakm/graceful/blob/d4678cb6349a5c843a5e58002fc80140821609e4/src/graceful/authentication.py#L288-L314
def process_resource(self, req, resp, resource, uri_kwargs=None): """Process resource after routing to it. This is basic falcon middleware handler. Args: req (falcon.Request): request object resp (falcon.Response): response object resource (object): resource object matched by falcon router uri_kwargs (dict): additional keyword argument from uri template. For ``falcon<1.0.0`` this is always ``None`` """ if 'user' in req.context: return identifier = self.identify(req, resp, resource, uri_kwargs) user = self.try_storage(identifier, req, resp, resource, uri_kwargs) if user is not None: req.context['user'] = user # if did not succeed then we need to add this to list of available # challenges. elif self.challenge is not None: req.context.setdefault( 'challenges', list() ).append(self.challenge)
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Process resource after routing to it. This is basic falcon middleware handler. Args: req (falcon.Request): request object resp (falcon.Response): response object resource (object): resource object matched by falcon router uri_kwargs (dict): additional keyword argument from uri template. For ``falcon<1.0.0`` this is always ``None``
[ "Process", "resource", "after", "routing", "to", "it", "." ]
python
train
qiniu/python-sdk
qiniu/services/compute/qcos_api.py
https://github.com/qiniu/python-sdk/blob/a69fbef4e3e6ea1ebe09f4610a5b18bb2c17de59/qiniu/services/compute/qcos_api.py#L128-L142
def start_stack(self, stack): """启动服务组 启动服务组中的所有停止状态的服务。 Args: - stack: 服务所属的服务组名称 Returns: 返回一个tuple对象,其格式为(<result>, <ResponseInfo>) - result 成功返回空dict{},失败返回{"error": "<errMsg string>"} - ResponseInfo 请求的Response信息 """ url = '{0}/v3/stacks/{1}/start'.format(self.host, stack) return self.__post(url)
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启动服务组 启动服务组中的所有停止状态的服务。 Args: - stack: 服务所属的服务组名称 Returns: 返回一个tuple对象,其格式为(<result>, <ResponseInfo>) - result 成功返回空dict{},失败返回{"error": "<errMsg string>"} - ResponseInfo 请求的Response信息
[ "启动服务组" ]
python
train
mrstephenneal/pdfconduit
pdf/gui/config/images.py
https://github.com/mrstephenneal/pdfconduit/blob/993421cc087eefefe01ff09afabd893bcc2718ec/pdf/gui/config/images.py#L25-L29
def remove(image): """Remove an image to the GUI img library.""" path = os.path.join(IMG_DIR, image) if os.path.isfile(path): os.remove(path)
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Remove an image to the GUI img library.
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python
train
sveetch/boussole
boussole/watcher.py
https://github.com/sveetch/boussole/blob/22cc644e9d633f41ebfc167d427a71c1726cee21/boussole/watcher.py#L236-L252
def on_deleted(self, event): """ Called when a file or directory is deleted. Todo: May be bugged with inspector and sass compiler since the does not exists anymore. Args: event: Watchdog event, ``watchdog.events.DirDeletedEvent`` or ``watchdog.events.FileDeletedEvent``. """ if not self._event_error: self.logger.info(u"Change detected from deletion of: %s", event.src_path) # Never try to compile the deleted source self.compile_dependencies(event.src_path, include_self=False)
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Called when a file or directory is deleted. Todo: May be bugged with inspector and sass compiler since the does not exists anymore. Args: event: Watchdog event, ``watchdog.events.DirDeletedEvent`` or ``watchdog.events.FileDeletedEvent``.
[ "Called", "when", "a", "file", "or", "directory", "is", "deleted", "." ]
python
train
silver-castle/mach9
mach9/static.py
https://github.com/silver-castle/mach9/blob/7a623aab3c70d89d36ade6901b6307e115400c5e/mach9/static.py#L19-L104
def register(app, uri, file_or_directory, pattern, use_modified_since, use_content_range): # TODO: Though mach9 is not a file server, I feel like we should at least # make a good effort here. Modified-since is nice, but we could # also look into etags, expires, and caching """ Register a static directory handler with Mach9 by adding a route to the router and registering a handler. :param app: Mach9 :param file_or_directory: File or directory path to serve from :param uri: URL to serve from :param pattern: regular expression used to match files in the URL :param use_modified_since: If true, send file modified time, and return not modified if the browser's matches the server's :param use_content_range: If true, process header for range requests and sends the file part that is requested """ # If we're not trying to match a file directly, # serve from the folder if not path.isfile(file_or_directory): uri += '<file_uri:' + pattern + '>' async def _handler(request, file_uri=None): # Using this to determine if the URL is trying to break out of the path # served. os.path.realpath seems to be very slow if file_uri and '../' in file_uri: raise InvalidUsage("Invalid URL") # Merge served directory and requested file if provided # Strip all / that in the beginning of the URL to help prevent python # from herping a derp and treating the uri as an absolute path root_path = file_path = file_or_directory if file_uri: file_path = path.join( file_or_directory, sub('^[/]*', '', file_uri)) # URL decode the path sent by the browser otherwise we won't be able to # match filenames which got encoded (filenames with spaces etc) file_path = path.abspath(unquote(file_path)) if not file_path.startswith(path.abspath(unquote(root_path))): raise FileNotFound('File not found', path=file_or_directory, relative_url=file_uri) try: headers = {} # Check if the client has been sent this file before # and it has not been modified since stats = None if use_modified_since: stats = await stat(file_path) modified_since = strftime( '%a, %d %b %Y %H:%M:%S GMT', gmtime(stats.st_mtime)) if request.headers.get('If-Modified-Since') == modified_since: return HTTPResponse(status=304) headers['Last-Modified'] = modified_since _range = None if use_content_range: _range = None if not stats: stats = await stat(file_path) headers['Accept-Ranges'] = 'bytes' headers['Content-Length'] = str(stats.st_size) if request.method != 'HEAD': try: _range = ContentRangeHandler(request, stats) except HeaderNotFound: pass else: del headers['Content-Length'] for key, value in _range.headers.items(): headers[key] = value if request.method == 'HEAD': return HTTPResponse( headers=headers, content_type=guess_type(file_path)[0] or 'text/plain') else: return await file(file_path, headers=headers, _range=_range) except ContentRangeError: raise except Exception: raise FileNotFound('File not found', path=file_or_directory, relative_url=file_uri) app.route(uri, methods=['GET', 'HEAD'])(_handler)
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Register a static directory handler with Mach9 by adding a route to the router and registering a handler. :param app: Mach9 :param file_or_directory: File or directory path to serve from :param uri: URL to serve from :param pattern: regular expression used to match files in the URL :param use_modified_since: If true, send file modified time, and return not modified if the browser's matches the server's :param use_content_range: If true, process header for range requests and sends the file part that is requested
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python
train
radical-cybertools/radical.entk
setup.py
https://github.com/radical-cybertools/radical.entk/blob/945f6c93c9a62db90ad191b306418d5c1cdd9d24/setup.py#L155-L174
def visit((prefix, strip, found), dirname, names): """ Visit directory, create distutil tuple Add distutil tuple for each directory using this format: (destination, [dirname/file1, dirname/file2, ...]) distutil will copy later file1, file2, ... info destination. """ files = [] # Iterate over a copy of names, modify names for name in names[:]: path = os.path.join(dirname, name) # Ignore directories - we will visit later if os.path.isdir(path): # Remove directories we don't want to visit later if isbad(name): names.remove(name) continue elif isgood(name): files.append(path) destination = os.path.join(prefix, dirname[strip:]) found.append((destination, files))
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Visit directory, create distutil tuple Add distutil tuple for each directory using this format: (destination, [dirname/file1, dirname/file2, ...]) distutil will copy later file1, file2, ... info destination.
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python
train
scott-griffiths/bitstring
bitstring.py
https://github.com/scott-griffiths/bitstring/blob/ab40ae7f0b43fe223a39b63cbc0529b09f3ef653/bitstring.py#L1784-L1802
def _readsie(self, pos): """Return interpretation of next bits as a signed interleaved exponential-Golomb code. Advances position to after the read code. Raises ReadError if the end of the bitstring is encountered while reading the code. """ codenum, pos = self._readuie(pos) if not codenum: return 0, pos try: if self[pos]: return -codenum, pos + 1 else: return codenum, pos + 1 except IndexError: raise ReadError("Read off end of bitstring trying to read code.")
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Return interpretation of next bits as a signed interleaved exponential-Golomb code. Advances position to after the read code. Raises ReadError if the end of the bitstring is encountered while reading the code.
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python
train
blazelibs/blazeutils
blazeutils/rst.py
https://github.com/blazelibs/blazeutils/blob/c94476325146007553cbddeeb9ef83394756babf/blazeutils/rst.py#L182-L190
def rst2html(rst_src, **kwargs): """ Convert a reStructuredText string into a unicode HTML fragment. For `kwargs`, see `default_rst_opts` and http://docutils.sourceforge.net/docs/user/config.html """ pub = rst2pub(rst_src, settings_overrides=kwargs, writer_name='html') return pub.writer.parts['body']
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Convert a reStructuredText string into a unicode HTML fragment. For `kwargs`, see `default_rst_opts` and http://docutils.sourceforge.net/docs/user/config.html
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python
train
mlperf/training
object_detection/pytorch/maskrcnn_benchmark/data/datasets/evaluation/coco/coco_eval.py
https://github.com/mlperf/training/blob/1c6ae725a81d15437a2b2df05cac0673fde5c3a4/object_detection/pytorch/maskrcnn_benchmark/data/datasets/evaluation/coco/coco_eval.py#L189-L302
def evaluate_box_proposals( predictions, dataset, thresholds=None, area="all", limit=None ): """Evaluate detection proposal recall metrics. This function is a much faster alternative to the official COCO API recall evaluation code. However, it produces slightly different results. """ # Record max overlap value for each gt box # Return vector of overlap values areas = { "all": 0, "small": 1, "medium": 2, "large": 3, "96-128": 4, "128-256": 5, "256-512": 6, "512-inf": 7, } area_ranges = [ [0 ** 2, 1e5 ** 2], # all [0 ** 2, 32 ** 2], # small [32 ** 2, 96 ** 2], # medium [96 ** 2, 1e5 ** 2], # large [96 ** 2, 128 ** 2], # 96-128 [128 ** 2, 256 ** 2], # 128-256 [256 ** 2, 512 ** 2], # 256-512 [512 ** 2, 1e5 ** 2], ] # 512-inf assert area in areas, "Unknown area range: {}".format(area) area_range = area_ranges[areas[area]] gt_overlaps = [] num_pos = 0 for image_id, prediction in enumerate(predictions): original_id = dataset.id_to_img_map[image_id] img_info = dataset.get_img_info(image_id) image_width = img_info["width"] image_height = img_info["height"] prediction = prediction.resize((image_width, image_height)) # sort predictions in descending order # TODO maybe remove this and make it explicit in the documentation inds = prediction.get_field("objectness").sort(descending=True)[1] prediction = prediction[inds] ann_ids = dataset.coco.getAnnIds(imgIds=original_id) anno = dataset.coco.loadAnns(ann_ids) gt_boxes = [obj["bbox"] for obj in anno if obj["iscrowd"] == 0] gt_boxes = torch.as_tensor(gt_boxes).reshape(-1, 4) # guard against no boxes gt_boxes = BoxList(gt_boxes, (image_width, image_height), mode="xywh").convert( "xyxy" ) gt_areas = torch.as_tensor([obj["area"] for obj in anno if obj["iscrowd"] == 0]) if len(gt_boxes) == 0: continue valid_gt_inds = (gt_areas >= area_range[0]) & (gt_areas <= area_range[1]) gt_boxes = gt_boxes[valid_gt_inds] num_pos += len(gt_boxes) if len(gt_boxes) == 0: continue if len(prediction) == 0: continue if limit is not None and len(prediction) > limit: prediction = prediction[:limit] overlaps = boxlist_iou(prediction, gt_boxes) _gt_overlaps = torch.zeros(len(gt_boxes)) for j in range(min(len(prediction), len(gt_boxes))): # find which proposal box maximally covers each gt box # and get the iou amount of coverage for each gt box max_overlaps, argmax_overlaps = overlaps.max(dim=0) # find which gt box is 'best' covered (i.e. 'best' = most iou) gt_ovr, gt_ind = max_overlaps.max(dim=0) assert gt_ovr >= 0 # find the proposal box that covers the best covered gt box box_ind = argmax_overlaps[gt_ind] # record the iou coverage of this gt box _gt_overlaps[j] = overlaps[box_ind, gt_ind] assert _gt_overlaps[j] == gt_ovr # mark the proposal box and the gt box as used overlaps[box_ind, :] = -1 overlaps[:, gt_ind] = -1 # append recorded iou coverage level gt_overlaps.append(_gt_overlaps) gt_overlaps = torch.cat(gt_overlaps, dim=0) gt_overlaps, _ = torch.sort(gt_overlaps) if thresholds is None: step = 0.05 thresholds = torch.arange(0.5, 0.95 + 1e-5, step, dtype=torch.float32) recalls = torch.zeros_like(thresholds) # compute recall for each iou threshold for i, t in enumerate(thresholds): recalls[i] = (gt_overlaps >= t).float().sum() / float(num_pos) # ar = 2 * np.trapz(recalls, thresholds) ar = recalls.mean() return { "ar": ar, "recalls": recalls, "thresholds": thresholds, "gt_overlaps": gt_overlaps, "num_pos": num_pos, }
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Evaluate detection proposal recall metrics. This function is a much faster alternative to the official COCO API recall evaluation code. However, it produces slightly different results.
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python
train
totalgood/nlpia
src/nlpia/loaders.py
https://github.com/totalgood/nlpia/blob/efa01126275e9cd3c3a5151a644f1c798a9ec53f/src/nlpia/loaders.py#L820-L858
def download_unzip(names=None, normalize_filenames=False, verbose=True): r""" Download CSV or HTML tables listed in `names`, unzip and to DATA_PATH/`names`.csv .txt etc TODO: move to web or data_utils or futils Also normalizes file name extensions (.bin.gz -> .w2v.bin.gz). Uses table in data_info.csv (internal DATA_INFO) to determine URL or file path from dataset name. Also looks If names or [names] is a valid URL then download it and create a name from the url in BIG_URLS (not yet pushed to data_info.csv) """ names = [names] if isinstance(names, (str, basestring)) else names # names = names or list(BIG_URLS.keys()) # download them all, if none specified! file_paths = {} for name in names: created = create_big_url(name) name = (created or name).lower().strip() if name in BIG_URLS: filepath = download_name(name, verbose=verbose) if not filepath: continue file_paths[name] = normalize_ext_rename(filepath) logger.debug('downloaded name={} to filepath={}'.format(name, file_paths[name])) fplower = file_paths[name].lower() if fplower.endswith('.tar.gz'): logger.info('Extracting {}'.format(file_paths[name])) file_paths[name] = untar(file_paths[name], verbose=verbose) logger.debug('download_untar.filepaths=' + str(file_paths)) elif file_paths[name].lower().endswith('.zip'): file_paths[name] = unzip(file_paths[name], verbose=verbose) logger.debug('download_unzip.filepaths=' + str(file_paths)) else: df = pd.read_html(DATA_INFO['url'][name], **DATA_INFO['downloader_kwargs'][name])[-1] df.columns = clean_columns(df.columns) file_paths[name] = os.path.join(DATA_PATH, name + '.csv') df.to_csv(file_paths[name]) file_paths[name] = normalize_ext_rename(file_paths[name]) return file_paths
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r""" Download CSV or HTML tables listed in `names`, unzip and to DATA_PATH/`names`.csv .txt etc TODO: move to web or data_utils or futils Also normalizes file name extensions (.bin.gz -> .w2v.bin.gz). Uses table in data_info.csv (internal DATA_INFO) to determine URL or file path from dataset name. Also looks If names or [names] is a valid URL then download it and create a name from the url in BIG_URLS (not yet pushed to data_info.csv)
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python
train
cloudendpoints/endpoints-python
endpoints/users_id_token.py
https://github.com/cloudendpoints/endpoints-python/blob/00dd7c7a52a9ee39d5923191c2604b8eafdb3f24/endpoints/users_id_token.py#L750-L794
def get_verified_jwt( providers, audiences, check_authorization_header=True, check_query_arg=True, request=None, cache=memcache): """ This function will extract, verify, and parse a JWT token from the Authorization header or access_token query argument. The JWT is assumed to contain an issuer and audience claim, as well as issued-at and expiration timestamps. The signature will be cryptographically verified, the claims and timestamps will be checked, and the resulting parsed JWT body is returned. If at any point the JWT is missing or found to be invalid, the return result will be None. Arguments: providers - An iterable of dicts each containing 'issuer' and 'cert_uri' keys audiences - An iterable of valid audiences check_authorization_header - Boolean; check 'Authorization: Bearer' header check_query_arg - Boolean; check 'access_token' query arg request - Must be the request object if check_query_arg is true; otherwise ignored. cache - In testing, override the certificate cache """ if not (check_authorization_header or check_query_arg): raise ValueError( 'Either check_authorization_header or check_query_arg must be True.') if check_query_arg and request is None: raise ValueError( 'Cannot check query arg without request object.') schemes = ('Bearer',) if check_authorization_header else () keys = ('access_token',) if check_query_arg else () token = _get_token( request=request, allowed_auth_schemes=schemes, allowed_query_keys=keys) if token is None: return None time_now = long(time.time()) for provider in providers: parsed_token = _parse_and_verify_jwt( token, time_now, (provider['issuer'],), audiences, provider['cert_uri'], cache) if parsed_token is not None: return parsed_token return None
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This function will extract, verify, and parse a JWT token from the Authorization header or access_token query argument. The JWT is assumed to contain an issuer and audience claim, as well as issued-at and expiration timestamps. The signature will be cryptographically verified, the claims and timestamps will be checked, and the resulting parsed JWT body is returned. If at any point the JWT is missing or found to be invalid, the return result will be None. Arguments: providers - An iterable of dicts each containing 'issuer' and 'cert_uri' keys audiences - An iterable of valid audiences check_authorization_header - Boolean; check 'Authorization: Bearer' header check_query_arg - Boolean; check 'access_token' query arg request - Must be the request object if check_query_arg is true; otherwise ignored. cache - In testing, override the certificate cache
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python
train
dwavesystems/dwave_networkx
dwave_networkx/drawing/chimera_layout.py
https://github.com/dwavesystems/dwave_networkx/blob/9ea1223ddbc7e86db2f90b8b23e250e6642c3d68/dwave_networkx/drawing/chimera_layout.py#L122-L203
def chimera_node_placer_2d(m, n, t, scale=1., center=None, dim=2): """Generates a function that converts Chimera indices to x, y coordinates for a plot. Parameters ---------- m : int Number of rows in the Chimera lattice. n : int Number of columns in the Chimera lattice. t : int Size of the shore within each Chimera tile. scale : float (default 1.) Scale factor. When scale = 1, all positions fit within [0, 1] on the x-axis and [-1, 0] on the y-axis. center : None or array (default None) Coordinates of the top left corner. dim : int (default 2) Number of dimensions. When dim > 2, all extra dimensions are set to 0. Returns ------- xy_coords : function A function that maps a Chimera index (i, j, u, k) in an (m, n, t) Chimera lattice to x,y coordinates such as used by a plot. """ import numpy as np tile_center = t // 2 tile_length = t + 3 # 1 for middle of cross, 2 for spacing between tiles # want the enter plot to fill in [0, 1] when scale=1 scale /= max(m, n) * tile_length - 3 grid_offsets = {} if center is None: center = np.zeros(dim) else: center = np.asarray(center) paddims = dim - 2 if paddims < 0: raise ValueError("layout must have at least two dimensions") if len(center) != dim: raise ValueError("length of center coordinates must match dimension of layout") def _xy_coords(i, j, u, k): # row, col, shore, shore index # first get the coordinatiates within the tile if k < tile_center: p = k else: p = k + 1 if u: xy = np.array([tile_center, -1 * p]) else: xy = np.array([p, -1 * tile_center]) # next offset the corrdinates based on the which tile if i > 0 or j > 0: if (i, j) in grid_offsets: xy += grid_offsets[(i, j)] else: off = np.array([j * tile_length, -1 * i * tile_length]) xy += off grid_offsets[(i, j)] = off # convention for Chimera-lattice pictures is to invert the y-axis return np.hstack((xy * scale, np.zeros(paddims))) + center return _xy_coords
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Generates a function that converts Chimera indices to x, y coordinates for a plot. Parameters ---------- m : int Number of rows in the Chimera lattice. n : int Number of columns in the Chimera lattice. t : int Size of the shore within each Chimera tile. scale : float (default 1.) Scale factor. When scale = 1, all positions fit within [0, 1] on the x-axis and [-1, 0] on the y-axis. center : None or array (default None) Coordinates of the top left corner. dim : int (default 2) Number of dimensions. When dim > 2, all extra dimensions are set to 0. Returns ------- xy_coords : function A function that maps a Chimera index (i, j, u, k) in an (m, n, t) Chimera lattice to x,y coordinates such as used by a plot.
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python
train
oasis-open/cti-stix-validator
stix2validator/validator.py
https://github.com/oasis-open/cti-stix-validator/blob/a607014e3fa500a7678f8b61b278456ca581f9d0/stix2validator/validator.py#L309-L339
def get_json_files(files, recursive=False): """Return a list of files to validate from `files`. If a member of `files` is a directory, its children with a ``.json`` extension will be added to the return value. Args: files: A list of file paths and/or directory paths. recursive: If ``true``, this will descend into any subdirectories of input directories. Returns: A list of file paths to validate. """ json_files = [] if not files: return json_files for fn in files: if os.path.isdir(fn): children = list_json_files(fn, recursive) json_files.extend(children) elif is_json(fn): json_files.append(fn) else: continue if not json_files: raise NoJSONFileFoundError("No JSON files found!") return json_files
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Return a list of files to validate from `files`. If a member of `files` is a directory, its children with a ``.json`` extension will be added to the return value. Args: files: A list of file paths and/or directory paths. recursive: If ``true``, this will descend into any subdirectories of input directories. Returns: A list of file paths to validate.
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python
train
KnowledgeLinks/rdfframework
rdfframework/rdfclass/rdffactories.py
https://github.com/KnowledgeLinks/rdfframework/blob/9ec32dcc4bed51650a4b392cc5c15100fef7923a/rdfframework/rdfclass/rdffactories.py#L178-L265
def make(self): """ reads through the definitions and generates an python class for each definition """ log.setLevel(self.log_level) created = [] self.set_class_dict() start = datetime.datetime.now() log.info(" # of classes to create: %s" % len(self.class_dict)) log.debug(" creating classes that are not subclassed") for name, cls_defs in self.class_dict.items(): # if name in ['bf_Organization', 'bf_Agent']: # pdb.set_trace() if not self.class_dict[name].get('rdfs_subClassOf'): created.append(name) setattr(MODULE.rdfclass, name, types.new_class(name, (RdfClassBase,), {#'metaclass': RdfClassMeta, 'cls_defs': cls_defs})) log.debug(" created %s classes in: %s", len(created), (datetime.datetime.now() - start)) for name in created: del self.class_dict[name] left = len(self.class_dict) classes = [] while left > 0: new = [] for name, cls_defs in self.class_dict.items(): # if name in ['bf_Organization', 'bf_Agent']: # pdb.set_trace() parents = self.class_dict[name].get('rdfs_subClassOf') if not parents: bases += (RdfClassBase, ) else: for parent in make_list(parents): bases = tuple() if parent in created or parent in classes: if parent in classes: bases += (RdfClassBase, ) else: base = getattr(MODULE.rdfclass, parent) bases += (base,) + base.__bases__ if len(bases) > 0: created.append(name) setattr(MODULE.rdfclass, name, types.new_class(name, bases, {#'metaclass': RdfClassMeta, 'cls_defs': cls_defs})) for name in created: try: del self.class_dict[name] except KeyError: pass if left == len(self.class_dict): # c_list = [self.class_dict[name].get('rdfs_subClassOf') \ # for name in self.class_dict] missing_parents = [] for name in self.class_dict: missing_parents += \ self.class_dict[name].get('rdfs_subClassOf', []) missing_parents = set(missing_parents) still_valid = set([name for name in self.class_dict if name not in missing_parents]) classes = list(missing_parents.difference(\ set(self.class_dict.keys()))) # classess = [] # for cl in c_list: # for item in cl: # classes.append(item) for name in self.class_dict: if name in classes: classes.remove(name) for p_name in self.class_dict[name].get('rdfs_subClassOf', []).copy(): if p_name in classes: self.class_dict[name]['rdfs_subClassOf'].remove(\ p_name) # pdb.set_trace() left = len(self.class_dict) # self.tie_properties(created) log.info(" created all classes in %s", (datetime.datetime.now() - start))
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reads through the definitions and generates an python class for each definition
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python
train
dnanexus/dx-toolkit
src/python/dxpy/bindings/dxanalysis.py
https://github.com/dnanexus/dx-toolkit/blob/74befb53ad90fcf902d8983ae6d74580f402d619/src/python/dxpy/bindings/dxanalysis.py#L148-L165
def get_output_ref(self, field, index=None, metadata=None): ''' :param field: Output field name of this analysis :type field: string :param index: If the referenced field is an array, optionally specify an index (starting from 0) to indicate a particular member of the array :type index: int :param metadata: If the referenced field is of a data object class, a string indicating the metadata that should be read, e.g. "name", "properties.propkey", "details.refgenome" :type metadata: string Returns a dict containing a valid reference to an output of this analysis. ''' link = {"$dnanexus_link": {"analysis": self._dxid, "field": field}} if index is not None: link["$dnanexus_link"]["index"] = index if metadata is not None: link["$dnanexus_link"]["metadata"] = metadata return link
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:param field: Output field name of this analysis :type field: string :param index: If the referenced field is an array, optionally specify an index (starting from 0) to indicate a particular member of the array :type index: int :param metadata: If the referenced field is of a data object class, a string indicating the metadata that should be read, e.g. "name", "properties.propkey", "details.refgenome" :type metadata: string Returns a dict containing a valid reference to an output of this analysis.
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python
train
JarryShaw/PyPCAPKit
src/protocols/internet/hip.py
https://github.com/JarryShaw/PyPCAPKit/blob/c7f0da9aebc2cf210bf8f8b912f7d3cbb98ca10e/src/protocols/internet/hip.py#L1523-L1555
def _read_para_echo_response_signed(self, code, cbit, clen, *, desc, length, version): """Read HIP ECHO_RESPONSE_SIGNED parameter. Structure of HIP ECHO_RESPONSE_SIGNED parameter [RFC 7401]: 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Length | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Opaque data (variable length) | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ Octets Bits Name Description 0 0 echo_response_signed.type Parameter Type 1 15 echo_response_signed.critical Critical Bit 2 16 echo_response_signed.length Length of Contents 4 32 echo_response_signed.data Opaque Data """ _data = self._read_fileng(clen) echo_response_signed = dict( type=desc, critical=cbit, length=clen, data=_data, ) _plen = length - clen if _plen: self._read_fileng(_plen) return echo_response_signed
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Read HIP ECHO_RESPONSE_SIGNED parameter. Structure of HIP ECHO_RESPONSE_SIGNED parameter [RFC 7401]: 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Length | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Opaque data (variable length) | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ Octets Bits Name Description 0 0 echo_response_signed.type Parameter Type 1 15 echo_response_signed.critical Critical Bit 2 16 echo_response_signed.length Length of Contents 4 32 echo_response_signed.data Opaque Data
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python
train
diux-dev/ncluster
ncluster/aws_util.py
https://github.com/diux-dev/ncluster/blob/2fd359621896717197b479c7174d06d80df1529b/ncluster/aws_util.py#L369-L398
def ssh_to_task(task) -> paramiko.SSHClient: """Create ssh connection to task's machine returns Paramiko SSH client connected to host. """ username = task.ssh_username hostname = task.public_ip ssh_key_fn = get_keypair_fn() print(f"ssh -i {ssh_key_fn} {username}@{hostname}") pkey = paramiko.RSAKey.from_private_key_file(ssh_key_fn) ssh_client = paramiko.SSHClient() ssh_client.set_missing_host_key_policy(paramiko.AutoAddPolicy()) assert ssh_client counter = 1 while True: try: ssh_client.connect(hostname=hostname, username=username, pkey=pkey) if counter % 11 == 0: # occasionally re-obtain public ip, machine could've gotten restarted hostname = task.public_ip break except Exception as e: print( f'{task.name}: Exception connecting to {hostname} via ssh (could be a timeout): {e}') time.sleep(RETRY_INTERVAL_SEC) return ssh_client
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Create ssh connection to task's machine returns Paramiko SSH client connected to host.
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python
train
LogicalDash/LiSE
ELiDE/ELiDE/board/arrow.py
https://github.com/LogicalDash/LiSE/blob/fe6fd4f0a7c1780e065f4c9babb9bc443af6bb84/ELiDE/ELiDE/board/arrow.py#L366-L392
def add_widget(self, wid, index=0, canvas=None): """Put the :class:`Pawn` at a point along my length proportionate to how close it is to finishing its travel through me. Only :class:`Pawn` should ever be added as a child of :class:`Arrow`. """ super().add_widget(wid, index, canvas) if not hasattr(wid, 'group'): return wid._no_use_canvas = True mycanvas = ( self.canvas.before if canvas == 'before' else self.canvas.after if canvas == 'after' else self.canvas ) mycanvas.remove(wid.canvas) pawncanvas = ( self.board.spotlayout.canvas.before if canvas == 'before' else self.board.spotlayout.canvas.after if canvas == 'after' else self.board.spotlayout.canvas ) for child in self.children: if hasattr(child, 'group') and child.group in pawncanvas.children: pawncanvas.remove(child.group) pawncanvas.add(child.group) self.pospawn(wid)
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Put the :class:`Pawn` at a point along my length proportionate to how close it is to finishing its travel through me. Only :class:`Pawn` should ever be added as a child of :class:`Arrow`.
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python
train
honzajavorek/redis-collections
redis_collections/sortedsets.py
https://github.com/honzajavorek/redis-collections/blob/07ca8efe88fb128f7dc7319dfa6a26cd39b3776b/redis_collections/sortedsets.py#L538-L587
def update(self, other): """ Update the collection with items from *other*. Accepts other :class:`GeoDB` instances, dictionaries mapping places to ``{'latitude': latitude, 'longitude': longitude}`` dicts, or sequences of ``(place, latitude, longitude)`` tuples. """ # other is another Sorted Set def update_sortedset_trans(pipe): items = other._data(pipe=pipe) if use_redis else other._data() pipe.multi() for member, score in items: pipe.zadd(self.key, {self._pickle(member): float(score)}) # other is dict-like def update_mapping_trans(pipe): items = other.items(pipe=pipe) if use_redis else other.items() pipe.multi() for place, value in items: self.set_location( place, value['latitude'], value['longitude'], pipe=pipe ) # other is a list of tuples def update_tuples_trans(pipe): items = ( other.__iter__(pipe=pipe) if use_redis else other.__iter__() ) pipe.multi() for place, latitude, longitude in items: self.set_location(place, latitude, longitude, pipe=pipe) watches = [] if self._same_redis(other, RedisCollection): use_redis = True watches.append(other.key) else: use_redis = False if isinstance(other, SortedSetBase): func = update_sortedset_trans elif hasattr(other, 'items'): func = update_mapping_trans elif hasattr(other, '__iter__'): func = update_tuples_trans self._transaction(func, *watches)
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Update the collection with items from *other*. Accepts other :class:`GeoDB` instances, dictionaries mapping places to ``{'latitude': latitude, 'longitude': longitude}`` dicts, or sequences of ``(place, latitude, longitude)`` tuples.
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python
train
trendmicro/flask-ini
flask_ini.py
https://github.com/trendmicro/flask-ini/blob/a1e4baa598c9a01021a1333d9c15e4d99c8334dd/flask_ini.py#L12-L16
def read(self, *args, **kwargs): '''Overridden read() method to call parse_flask_section() at the end''' ret = configparser.SafeConfigParser.read(self, *args, **kwargs) self.parse_flask_section() return ret
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Overridden read() method to call parse_flask_section() at the end
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python
train
chrisrink10/basilisp
src/basilisp/lang/runtime.py
https://github.com/chrisrink10/basilisp/blob/3d82670ee218ec64eb066289c82766d14d18cc92/src/basilisp/lang/runtime.py#L881-L893
def update(m, k, f, *args): """Updates the value for key k in associative data structure m with the return value from calling f(old_v, *args). If m is None, use an empty map. If k is not in m, old_v will be None.""" if m is None: return lmap.Map.empty().assoc(k, f(None, *args)) if isinstance(m, IAssociative): old_v = m.entry(k) new_v = f(old_v, *args) return m.assoc(k, new_v) raise TypeError( f"Object of type {type(m)} does not implement Associative interface" )
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Updates the value for key k in associative data structure m with the return value from calling f(old_v, *args). If m is None, use an empty map. If k is not in m, old_v will be None.
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python
test
dask/dask-ml
dask_ml/model_selection/_incremental.py
https://github.com/dask/dask-ml/blob/cc4837c2c2101f9302cac38354b55754263cd1f3/dask_ml/model_selection/_incremental.py#L569-L578
def fit(self, X, y, **fit_params): """Find the best parameters for a particular model. Parameters ---------- X, y : array-like **fit_params Additional partial fit keyword arguments for the estimator. """ return default_client().sync(self._fit, X, y, **fit_params)
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Find the best parameters for a particular model. Parameters ---------- X, y : array-like **fit_params Additional partial fit keyword arguments for the estimator.
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python
train
rwl/pylon
pylon/opf.py
https://github.com/rwl/pylon/blob/916514255db1ae1661406f0283df756baf960d14/pylon/opf.py#L294-L309
def _power_mismatch_dc(self, buses, generators, B, Pbusinj, base_mva): """ Returns the power mismatch constraint (B*Va + Pg = Pd). """ nb, ng = len(buses), len(generators) # Negative bus-generator incidence matrix. gen_bus = array([g.bus._i for g in generators]) neg_Cg = csr_matrix((-ones(ng), (gen_bus, range(ng))), (nb, ng)) Amis = hstack([B, neg_Cg], format="csr") Pd = array([bus.p_demand for bus in buses]) Gs = array([bus.g_shunt for bus in buses]) bmis = -(Pd - Gs) / base_mva - Pbusinj return LinearConstraint("Pmis", Amis, bmis, bmis, ["Va", "Pg"])
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Returns the power mismatch constraint (B*Va + Pg = Pd).
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python
train
Yelp/kafka-utils
kafka_utils/util/protocol.py
https://github.com/Yelp/kafka-utils/blob/cdb4d64308f3079ee0873250bf7b34d0d94eca50/kafka_utils/util/protocol.py#L27-L46
def encode_offset_commit_request_kafka(cls, group, payloads): """ Encode an OffsetCommitRequest struct Arguments: group: string, the consumer group you are committing offsets for payloads: list of OffsetCommitRequestPayload """ return kafka.protocol.commit.OffsetCommitRequest[2]( consumer_group=group, consumer_group_generation_id=kafka.protocol.commit.OffsetCommitRequest[2].DEFAULT_GENERATION_ID, consumer_id='', retention_time=kafka.protocol.commit.OffsetCommitRequest[2].DEFAULT_RETENTION_TIME, topics=[( topic, [( partition, payload.offset, payload.metadata) for partition, payload in six.iteritems(topic_payloads)]) for topic, topic_payloads in six.iteritems(group_by_topic_and_partition(payloads))])
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Encode an OffsetCommitRequest struct Arguments: group: string, the consumer group you are committing offsets for payloads: list of OffsetCommitRequestPayload
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python
train
yt-project/unyt
unyt/array.py
https://github.com/yt-project/unyt/blob/7a4eafc229f83784f4c63d639aee554f9a6b1ca0/unyt/array.py#L1738-L1772
def copy(self, order="C"): """ Return a copy of the array. Parameters ---------- order : {'C', 'F', 'A', 'K'}, optional Controls the memory layout of the copy. 'C' means C-order, 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous, 'C' otherwise. 'K' means match the layout of `a` as closely as possible. (Note that this function and :func:`numpy.copy` are very similar, but have different default values for their order= arguments.) See also -------- numpy.copy numpy.copyto Examples -------- >>> from unyt import km >>> x = [[1,2,3],[4,5,6]] * km >>> y = x.copy() >>> x.fill(0) >>> print(x) [[0 0 0] [0 0 0]] km >>> print(y) [[1 2 3] [4 5 6]] km """ return type(self)(np.copy(np.asarray(self)), self.units)
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Return a copy of the array. Parameters ---------- order : {'C', 'F', 'A', 'K'}, optional Controls the memory layout of the copy. 'C' means C-order, 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous, 'C' otherwise. 'K' means match the layout of `a` as closely as possible. (Note that this function and :func:`numpy.copy` are very similar, but have different default values for their order= arguments.) See also -------- numpy.copy numpy.copyto Examples -------- >>> from unyt import km >>> x = [[1,2,3],[4,5,6]] * km >>> y = x.copy() >>> x.fill(0) >>> print(x) [[0 0 0] [0 0 0]] km >>> print(y) [[1 2 3] [4 5 6]] km
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python
train
edeposit/edeposit.amqp.ftp
src/edeposit/amqp/ftp/settings.py
https://github.com/edeposit/edeposit.amqp.ftp/blob/fcdcbffb6e5d194e1bb4f85f0b8eaa9dbb08aa71/src/edeposit/amqp/ftp/settings.py#L121-L133
def conf_merger(user_dict, variable): """ Merge global configuration with user's personal configuration. Global configuration has always higher priority. """ if variable not in globals().keys(): raise NameError("Unknown variable '%s'." % variable) if variable not in user_dict: return globals()[variable] return globals()[variable] and user_dict[variable]
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Merge global configuration with user's personal configuration. Global configuration has always higher priority.
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python
train
jobovy/galpy
galpy/orbit/OrbitTop.py
https://github.com/jobovy/galpy/blob/9c5b9fe65d58835624dffe432be282060918ee08/galpy/orbit/OrbitTop.py#L372-L394
def y(self,*args,**kwargs): """ NAME: y PURPOSE: return y INPUT: t - (optional) time at which to get y ro= (Object-wide default) physical scale for distances to use to convert use_physical= use to override Object-wide default for using a physical scale for output OUTPUT: y(t) HISTORY: 2010-09-21 - Written - Bovy (NYU) """ thiso= self(*args,**kwargs) if not len(thiso.shape) == 2: thiso= thiso.reshape((thiso.shape[0],1)) if len(thiso[:,0]) != 4 and len(thiso[:,0]) != 6: raise AttributeError("orbit must track azimuth to use x()") elif len(thiso[:,0]) == 4: return thiso[0,:]*nu.sin(thiso[3,:]) else: return thiso[0,:]*nu.sin(thiso[5,:])
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NAME: y PURPOSE: return y INPUT: t - (optional) time at which to get y ro= (Object-wide default) physical scale for distances to use to convert use_physical= use to override Object-wide default for using a physical scale for output OUTPUT: y(t) HISTORY: 2010-09-21 - Written - Bovy (NYU)
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python
train
mfitzp/padua
padua/normalization.py
https://github.com/mfitzp/padua/blob/8b14bf4d2f895da6aea5d7885d409315bd303ec6/padua/normalization.py#L4-L22
def subtract_column_median(df, prefix='Intensity '): """ Apply column-wise normalisation to expression columns. Default is median transform to expression columns beginning with Intensity :param df: :param prefix: The column prefix for expression columns :return: """ df = df.copy() df.replace([np.inf, -np.inf], np.nan, inplace=True) mask = [l.startswith(prefix) for l in df.columns.values] df.iloc[:, mask] = df.iloc[:, mask] - df.iloc[:, mask].median(axis=0) return df
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Apply column-wise normalisation to expression columns. Default is median transform to expression columns beginning with Intensity :param df: :param prefix: The column prefix for expression columns :return:
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python
train
Jajcus/pyxmpp2
pyxmpp2/ext/disco.py
https://github.com/Jajcus/pyxmpp2/blob/14a40a3950910a9cd008b55f0d8905aa0186ce18/pyxmpp2/ext/disco.py#L501-L517
def add_item(self,jid,node=None,name=None,action=None): """Add a new item to the `DiscoItems` object. :Parameters: - `jid`: item JID. - `node`: item node name. - `name`: item name. - `action`: action for a "disco push". :Types: - `jid`: `pyxmpp.JID` - `node`: `unicode` - `name`: `unicode` - `action`: `unicode` :returns: the item created. :returntype: `DiscoItem`.""" return DiscoItem(self,jid,node,name,action)
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Add a new item to the `DiscoItems` object. :Parameters: - `jid`: item JID. - `node`: item node name. - `name`: item name. - `action`: action for a "disco push". :Types: - `jid`: `pyxmpp.JID` - `node`: `unicode` - `name`: `unicode` - `action`: `unicode` :returns: the item created. :returntype: `DiscoItem`.
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python
valid
wavycloud/pyboto3
pyboto3/elasticbeanstalk.py
https://github.com/wavycloud/pyboto3/blob/924957ccf994303713a4eed90b775ff2ab95b2e5/pyboto3/elasticbeanstalk.py#L585-L755
def create_environment(ApplicationName=None, EnvironmentName=None, GroupName=None, Description=None, CNAMEPrefix=None, Tier=None, Tags=None, VersionLabel=None, TemplateName=None, SolutionStackName=None, PlatformArn=None, OptionSettings=None, OptionsToRemove=None): """ Launches an environment for the specified application using the specified configuration. See also: AWS API Documentation Examples The following operation creates a new environment for version v1 of a java application named my-app: Expected Output: :example: response = client.create_environment( ApplicationName='string', EnvironmentName='string', GroupName='string', Description='string', CNAMEPrefix='string', Tier={ 'Name': 'string', 'Type': 'string', 'Version': 'string' }, Tags=[ { 'Key': 'string', 'Value': 'string' }, ], VersionLabel='string', TemplateName='string', SolutionStackName='string', PlatformArn='string', OptionSettings=[ { 'ResourceName': 'string', 'Namespace': 'string', 'OptionName': 'string', 'Value': 'string' }, ], OptionsToRemove=[ { 'ResourceName': 'string', 'Namespace': 'string', 'OptionName': 'string' }, ] ) :type ApplicationName: string :param ApplicationName: [REQUIRED] The name of the application that contains the version to be deployed. If no application is found with this name, CreateEnvironment returns an InvalidParameterValue error. :type EnvironmentName: string :param EnvironmentName: A unique name for the deployment environment. Used in the application URL. Constraint: Must be from 4 to 40 characters in length. The name can contain only letters, numbers, and hyphens. It cannot start or end with a hyphen. This name must be unique in your account. If the specified name already exists, AWS Elastic Beanstalk returns an InvalidParameterValue error. Default: If the CNAME parameter is not specified, the environment name becomes part of the CNAME, and therefore part of the visible URL for your application. :type GroupName: string :param GroupName: The name of the group to which the target environment belongs. Specify a group name only if the environment's name is specified in an environment manifest and not with the environment name parameter. See Environment Manifest (env.yaml) for details. :type Description: string :param Description: Describes this environment. :type CNAMEPrefix: string :param CNAMEPrefix: If specified, the environment attempts to use this value as the prefix for the CNAME. If not specified, the CNAME is generated automatically by appending a random alphanumeric string to the environment name. :type Tier: dict :param Tier: This specifies the tier to use for creating this environment. Name (string) --The name of this environment tier. Type (string) --The type of this environment tier. Version (string) --The version of this environment tier. :type Tags: list :param Tags: This specifies the tags applied to resources in the environment. (dict) --Describes a tag applied to a resource in an environment. Key (string) --The key of the tag. Value (string) --The value of the tag. :type VersionLabel: string :param VersionLabel: The name of the application version to deploy. If the specified application has no associated application versions, AWS Elastic Beanstalk UpdateEnvironment returns an InvalidParameterValue error. Default: If not specified, AWS Elastic Beanstalk attempts to launch the sample application in the container. :type TemplateName: string :param TemplateName: The name of the configuration template to use in deployment. If no configuration template is found with this name, AWS Elastic Beanstalk returns an InvalidParameterValue error. :type SolutionStackName: string :param SolutionStackName: This is an alternative to specifying a template name. If specified, AWS Elastic Beanstalk sets the configuration values to the default values associated with the specified solution stack. :type PlatformArn: string :param PlatformArn: The ARN of the custom platform. :type OptionSettings: list :param OptionSettings: If specified, AWS Elastic Beanstalk sets the specified configuration options to the requested value in the configuration set for the new environment. These override the values obtained from the solution stack or the configuration template. (dict) --A specification identifying an individual configuration option along with its current value. For a list of possible option values, go to Option Values in the AWS Elastic Beanstalk Developer Guide . ResourceName (string) --A unique resource name for a time-based scaling configuration option. Namespace (string) --A unique namespace identifying the option's associated AWS resource. OptionName (string) --The name of the configuration option. Value (string) --The current value for the configuration option. :type OptionsToRemove: list :param OptionsToRemove: A list of custom user-defined configuration options to remove from the configuration set for this new environment. (dict) --A specification identifying an individual configuration option. ResourceName (string) --A unique resource name for a time-based scaling configuration option. Namespace (string) --A unique namespace identifying the option's associated AWS resource. OptionName (string) --The name of the configuration option. :rtype: dict :return: { 'EnvironmentName': 'string', 'EnvironmentId': 'string', 'ApplicationName': 'string', 'VersionLabel': 'string', 'SolutionStackName': 'string', 'PlatformArn': 'string', 'TemplateName': 'string', 'Description': 'string', 'EndpointURL': 'string', 'CNAME': 'string', 'DateCreated': datetime(2015, 1, 1), 'DateUpdated': datetime(2015, 1, 1), 'Status': 'Launching'|'Updating'|'Ready'|'Terminating'|'Terminated', 'AbortableOperationInProgress': True|False, 'Health': 'Green'|'Yellow'|'Red'|'Grey', 'HealthStatus': 'NoData'|'Unknown'|'Pending'|'Ok'|'Info'|'Warning'|'Degraded'|'Severe', 'Resources': { 'LoadBalancer': { 'LoadBalancerName': 'string', 'Domain': 'string', 'Listeners': [ { 'Protocol': 'string', 'Port': 123 }, ] } }, 'Tier': { 'Name': 'string', 'Type': 'string', 'Version': 'string' }, 'EnvironmentLinks': [ { 'LinkName': 'string', 'EnvironmentName': 'string' }, ] } :returns: Launching : Environment is in the process of initial deployment. Updating : Environment is in the process of updating its configuration settings or application version. Ready : Environment is available to have an action performed on it, such as update or terminate. Terminating : Environment is in the shut-down process. Terminated : Environment is not running. """ pass
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Launches an environment for the specified application using the specified configuration. See also: AWS API Documentation Examples The following operation creates a new environment for version v1 of a java application named my-app: Expected Output: :example: response = client.create_environment( ApplicationName='string', EnvironmentName='string', GroupName='string', Description='string', CNAMEPrefix='string', Tier={ 'Name': 'string', 'Type': 'string', 'Version': 'string' }, Tags=[ { 'Key': 'string', 'Value': 'string' }, ], VersionLabel='string', TemplateName='string', SolutionStackName='string', PlatformArn='string', OptionSettings=[ { 'ResourceName': 'string', 'Namespace': 'string', 'OptionName': 'string', 'Value': 'string' }, ], OptionsToRemove=[ { 'ResourceName': 'string', 'Namespace': 'string', 'OptionName': 'string' }, ] ) :type ApplicationName: string :param ApplicationName: [REQUIRED] The name of the application that contains the version to be deployed. If no application is found with this name, CreateEnvironment returns an InvalidParameterValue error. :type EnvironmentName: string :param EnvironmentName: A unique name for the deployment environment. Used in the application URL. Constraint: Must be from 4 to 40 characters in length. The name can contain only letters, numbers, and hyphens. It cannot start or end with a hyphen. This name must be unique in your account. If the specified name already exists, AWS Elastic Beanstalk returns an InvalidParameterValue error. Default: If the CNAME parameter is not specified, the environment name becomes part of the CNAME, and therefore part of the visible URL for your application. :type GroupName: string :param GroupName: The name of the group to which the target environment belongs. Specify a group name only if the environment's name is specified in an environment manifest and not with the environment name parameter. See Environment Manifest (env.yaml) for details. :type Description: string :param Description: Describes this environment. :type CNAMEPrefix: string :param CNAMEPrefix: If specified, the environment attempts to use this value as the prefix for the CNAME. If not specified, the CNAME is generated automatically by appending a random alphanumeric string to the environment name. :type Tier: dict :param Tier: This specifies the tier to use for creating this environment. Name (string) --The name of this environment tier. Type (string) --The type of this environment tier. Version (string) --The version of this environment tier. :type Tags: list :param Tags: This specifies the tags applied to resources in the environment. (dict) --Describes a tag applied to a resource in an environment. Key (string) --The key of the tag. Value (string) --The value of the tag. :type VersionLabel: string :param VersionLabel: The name of the application version to deploy. If the specified application has no associated application versions, AWS Elastic Beanstalk UpdateEnvironment returns an InvalidParameterValue error. Default: If not specified, AWS Elastic Beanstalk attempts to launch the sample application in the container. :type TemplateName: string :param TemplateName: The name of the configuration template to use in deployment. If no configuration template is found with this name, AWS Elastic Beanstalk returns an InvalidParameterValue error. :type SolutionStackName: string :param SolutionStackName: This is an alternative to specifying a template name. If specified, AWS Elastic Beanstalk sets the configuration values to the default values associated with the specified solution stack. :type PlatformArn: string :param PlatformArn: The ARN of the custom platform. :type OptionSettings: list :param OptionSettings: If specified, AWS Elastic Beanstalk sets the specified configuration options to the requested value in the configuration set for the new environment. These override the values obtained from the solution stack or the configuration template. (dict) --A specification identifying an individual configuration option along with its current value. For a list of possible option values, go to Option Values in the AWS Elastic Beanstalk Developer Guide . ResourceName (string) --A unique resource name for a time-based scaling configuration option. Namespace (string) --A unique namespace identifying the option's associated AWS resource. OptionName (string) --The name of the configuration option. Value (string) --The current value for the configuration option. :type OptionsToRemove: list :param OptionsToRemove: A list of custom user-defined configuration options to remove from the configuration set for this new environment. (dict) --A specification identifying an individual configuration option. ResourceName (string) --A unique resource name for a time-based scaling configuration option. Namespace (string) --A unique namespace identifying the option's associated AWS resource. OptionName (string) --The name of the configuration option. :rtype: dict :return: { 'EnvironmentName': 'string', 'EnvironmentId': 'string', 'ApplicationName': 'string', 'VersionLabel': 'string', 'SolutionStackName': 'string', 'PlatformArn': 'string', 'TemplateName': 'string', 'Description': 'string', 'EndpointURL': 'string', 'CNAME': 'string', 'DateCreated': datetime(2015, 1, 1), 'DateUpdated': datetime(2015, 1, 1), 'Status': 'Launching'|'Updating'|'Ready'|'Terminating'|'Terminated', 'AbortableOperationInProgress': True|False, 'Health': 'Green'|'Yellow'|'Red'|'Grey', 'HealthStatus': 'NoData'|'Unknown'|'Pending'|'Ok'|'Info'|'Warning'|'Degraded'|'Severe', 'Resources': { 'LoadBalancer': { 'LoadBalancerName': 'string', 'Domain': 'string', 'Listeners': [ { 'Protocol': 'string', 'Port': 123 }, ] } }, 'Tier': { 'Name': 'string', 'Type': 'string', 'Version': 'string' }, 'EnvironmentLinks': [ { 'LinkName': 'string', 'EnvironmentName': 'string' }, ] } :returns: Launching : Environment is in the process of initial deployment. Updating : Environment is in the process of updating its configuration settings or application version. Ready : Environment is available to have an action performed on it, such as update or terminate. Terminating : Environment is in the shut-down process. Terminated : Environment is not running.
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python
train
juju/juju-bundlelib
jujubundlelib/validation.py
https://github.com/juju/juju-bundlelib/blob/c2efa614f53675ed9526027776448bfbb0454ca6/jujubundlelib/validation.py#L37-L62
def validate(bundle): """Validate a bundle object and all of its components. The bundle must be passed as a YAML decoded object. Return a list of bundle errors, or an empty list if the bundle is valid. """ errors = [] add_error = errors.append # Check that the bundle sections are well formed. series, services, machines, relations = _validate_sections( bundle, add_error) # If there are errors already, there is no point in proceeding with the # validation process. if errors: return errors # Validate each individual section. _validate_series(series, 'bundle', add_error) _validate_services(services, machines, add_error) _validate_machines(machines, add_error) _validate_relations(relations, services, add_error) # Return all the collected errors. return errors
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Validate a bundle object and all of its components. The bundle must be passed as a YAML decoded object. Return a list of bundle errors, or an empty list if the bundle is valid.
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python
train
stevearc/dql
dql/cli.py
https://github.com/stevearc/dql/blob/e9d3aa22873076dae5ebd02e35318aa996b1e56a/dql/cli.py#L254-L260
def save_config(self): """ Save the conf file """ if not os.path.exists(self._conf_dir): os.makedirs(self._conf_dir) conf_file = os.path.join(self._conf_dir, "dql.json") with open(conf_file, "w") as ofile: json.dump(self.conf, ofile, indent=2)
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Save the conf file
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python
train
mitsei/dlkit
dlkit/json_/hierarchy/sessions.py
https://github.com/mitsei/dlkit/blob/445f968a175d61c8d92c0f617a3c17dc1dc7c584/dlkit/json_/hierarchy/sessions.py#L978-L1001
def can_create_hierarchy_with_record_types(self, hierarchy_record_types): """Tests if this user can create a single ``Hierarchy`` using the desired record types. While ``HierarchyManager.getHierarchyRecordTypes()`` can be used to examine which records are supported, this method tests which record(s) are required for creating a specific ``Hierarchy``. Providing an empty array tests if a ``Hierarchy`` can be created with no records. arg: hierarchy_record_types (osid.type.Type[]): array of hierarchy record types return: (boolean) - ``true`` if ``Hierarchy`` creation using the specified ``Types`` is supported, ``false`` otherwise raise: NullArgument - ``hierarchy_record_types`` is ``null`` *compliance: mandatory -- This method must be implemented.* """ # Implemented from template for # osid.resource.BinAdminSession.can_create_bin_with_record_types # NOTE: It is expected that real authentication hints will be # handled in a service adapter above the pay grade of this impl. if self._catalog_session is not None: return self._catalog_session.can_create_catalog_with_record_types(catalog_record_types=hierarchy_record_types) return True
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python
train
bitesofcode/projexui
projexui/widgets/xwalkthroughwidget/xwalkthrough.py
https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xwalkthroughwidget/xwalkthrough.py#L133-L145
def fromXml(xml): """ Creates a new slide from XML. :return <XWalkthroughSlide> """ slide = XWalkthroughSlide(**xml.attrib) # create the items for xgraphic in xml: slide.addItem(XWalkthroughItem.fromXml(xgraphic)) return slide
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Creates a new slide from XML. :return <XWalkthroughSlide>
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python
train
zhmcclient/python-zhmcclient
zhmcclient/_hba.py
https://github.com/zhmcclient/python-zhmcclient/blob/9657563e5d9184c51d3c903442a58b9725fdf335/zhmcclient/_hba.py#L302-L331
def reassign_port(self, port): """ Reassign this HBA to a new underlying :term:`FCP port`. This method performs the HMC operation "Reassign Storage Adapter Port". Authorization requirements: * Object-access permission to the Partition containing this HBA. * Object-access permission to the Adapter with the new Port. * Task permission to the "Partition Details" task. Parameters: port (:class:`~zhmcclient.Port`): :term:`FCP port` to be used. Raises: :exc:`~zhmcclient.HTTPError`: See the HTTP status and reason codes of operation "Reassign Storage Adapter Port" in the :term:`HMC API` book. :exc:`~zhmcclient.ParseError` :exc:`~zhmcclient.AuthError` :exc:`~zhmcclient.ConnectionError` """ body = {'adapter-port-uri': port.uri} self.manager.session.post( self._uri + '/operations/reassign-storage-adapter-port', body=body) self.properties.update(body)
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Reassign this HBA to a new underlying :term:`FCP port`. This method performs the HMC operation "Reassign Storage Adapter Port". Authorization requirements: * Object-access permission to the Partition containing this HBA. * Object-access permission to the Adapter with the new Port. * Task permission to the "Partition Details" task. Parameters: port (:class:`~zhmcclient.Port`): :term:`FCP port` to be used. Raises: :exc:`~zhmcclient.HTTPError`: See the HTTP status and reason codes of operation "Reassign Storage Adapter Port" in the :term:`HMC API` book. :exc:`~zhmcclient.ParseError` :exc:`~zhmcclient.AuthError` :exc:`~zhmcclient.ConnectionError`
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python
train
reiinakano/xcessiv
xcessiv/functions.py
https://github.com/reiinakano/xcessiv/blob/a48dff7d370c84eb5c243bde87164c1f5fd096d5/xcessiv/functions.py#L16-L28
def hash_file(path, block_size=65536): """Returns SHA256 checksum of a file Args: path (string): Absolute file path of file to hash block_size (int, optional): Number of bytes to read per block """ sha256 = hashlib.sha256() with open(path, 'rb') as f: for block in iter(lambda: f.read(block_size), b''): sha256.update(block) return sha256.hexdigest()
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Returns SHA256 checksum of a file Args: path (string): Absolute file path of file to hash block_size (int, optional): Number of bytes to read per block
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python
train
saulpw/visidata
visidata/vdtui.py
https://github.com/saulpw/visidata/blob/32771e0cea6c24fc7902683d14558391395c591f/visidata/vdtui.py#L2258-L2263
def getMaxWidth(self, rows): 'Return the maximum length of any cell in column or its header.' w = 0 if len(rows) > 0: w = max(max(len(self.getDisplayValue(r)) for r in rows), len(self.name))+2 return max(w, len(self.name))
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Return the maximum length of any cell in column or its header.
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python
train
django-userena-ce/django-userena-ce
userena/decorators.py
https://github.com/django-userena-ce/django-userena-ce/blob/2d8b745eed25128134e961ca96c270802e730256/userena/decorators.py#L9-L29
def secure_required(view_func): """ Decorator to switch an url from http to https. If a view is accessed through http and this decorator is applied to that view, than it will return a permanent redirect to the secure (https) version of the same view. The decorator also must check that ``USERENA_USE_HTTPS`` is enabled. If disabled, it should not redirect to https because the project doesn't support it. """ def _wrapped_view(request, *args, **kwargs): if not request.is_secure(): if getattr(settings, 'USERENA_USE_HTTPS', userena_settings.DEFAULT_USERENA_USE_HTTPS): request_url = request.build_absolute_uri(request.get_full_path()) secure_url = request_url.replace('http://', 'https://') return HttpResponsePermanentRedirect(secure_url) return view_func(request, *args, **kwargs) return wraps(view_func, assigned=available_attrs(view_func))(_wrapped_view)
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Decorator to switch an url from http to https. If a view is accessed through http and this decorator is applied to that view, than it will return a permanent redirect to the secure (https) version of the same view. The decorator also must check that ``USERENA_USE_HTTPS`` is enabled. If disabled, it should not redirect to https because the project doesn't support it.
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python
train
StackStorm/pybind
pybind/slxos/v17s_1_02/mpls_state/rsvp/sessions/psbs/__init__.py
https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/slxos/v17s_1_02/mpls_state/rsvp/sessions/psbs/__init__.py#L254-L277
def _set_session_type(self, v, load=False): """ Setter method for session_type, mapped from YANG variable /mpls_state/rsvp/sessions/psbs/session_type (session-type) If this variable is read-only (config: false) in the source YANG file, then _set_session_type is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_session_type() directly. YANG Description: Session type """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'session-type-none': {'value': 0}, u'merged-backup': {'value': 6}, u'ingress-detour': {'value': 1}, u'egress-backup': {'value': 7}, u'repaired-session': {'value': 8}, u'bypass-ingress': {'value': 9}, u'transit-detour': {'value': 2}, u'egress-detour': {'value': 4}, u'ingress-backup': {'value': 5}, u'merged-detour': {'value': 3}},), is_leaf=True, yang_name="session-type", rest_name="session-type", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='session-type', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """session_type must be of a type compatible with session-type""", 'defined-type': "brocade-mpls-operational:session-type", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_type="dict_key", restriction_arg={u'session-type-none': {'value': 0}, u'merged-backup': {'value': 6}, u'ingress-detour': {'value': 1}, u'egress-backup': {'value': 7}, u'repaired-session': {'value': 8}, u'bypass-ingress': {'value': 9}, u'transit-detour': {'value': 2}, u'egress-detour': {'value': 4}, u'ingress-backup': {'value': 5}, u'merged-detour': {'value': 3}},), is_leaf=True, yang_name="session-type", rest_name="session-type", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='session-type', is_config=False)""", }) self.__session_type = t if hasattr(self, '_set'): self._set()
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python
train
MrYsLab/PyMata
PyMata/pymata_command_handler.py
https://github.com/MrYsLab/PyMata/blob/7e0ec34670b5a0d3d6b74bcbe4f3808c845cc429/PyMata/pymata_command_handler.py#L704-L730
def i2c_reply(self, data): """ This method receives replies to i2c_read requests. It stores the data for each i2c device address in a dictionary called i2c_map. The data is retrieved via a call to i2c_get_read_data() in pymata.py It a callback was specified in pymata.i2c_read, the raw data is sent through the callback :param data: raw data returned from i2c device """ reply_data = [] address = (data[0] & 0x7f) + (data[1] << 7) register = data[2] & 0x7f + data[3] << 7 reply_data.append(register) for i in range(4, len(data), 2): data_item = (data[i] & 0x7f) + (data[i + 1] << 7) reply_data.append(data_item) # retrieve the data entry for this address from the i2c map if address in self.i2c_map: i2c_data = self.i2c_map.get(address, None) i2c_data[1] = reply_data self.i2c_map[address] = i2c_data # is there a call back for this entry? # if yes, return a list of bytes through the callback if i2c_data[0] is not None: i2c_data[0]([self.pymata.I2C, address, reply_data])
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python
valid
SatelliteQE/nailgun
nailgun/entities.py
https://github.com/SatelliteQE/nailgun/blob/c36d8c20862e87bf6975bd48ac1ca40a9e634eaa/nailgun/entities.py#L7346-L7351
def update_payload(self, fields=None): """Convert ``sync_date`` to a string if datetime object provided.""" data = super(SyncPlan, self).update_payload(fields) if isinstance(data.get('sync_date'), datetime): data['sync_date'] = data['sync_date'].strftime('%Y-%m-%d %H:%M:%S') return data
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Convert ``sync_date`` to a string if datetime object provided.
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python
train
cuihantao/andes
andes/models/base.py
https://github.com/cuihantao/andes/blob/7067898d4f26ce7534e968b8486c4aa8fe3a511a/andes/models/base.py#L417-L455
def get_field(self, field, idx=None, astype=None): """ Return `self.field` for the elements labeled by `idx` :param astype: type cast of the return value :param field: field name of this model :param idx: element indices, will be the whole list if not specified :return: field values """ assert astype in (None, list, matrix) ret = None if idx is None: idx = self.idx # ===================disable warning ============================== # if field in self._service: # logger.warning( # 'Reading service variable <{model}.{field}> could be unsafe.' # .format(field=field, model=self._name) # ) # ================================================================= uid = self.get_uid(idx) field_data = self.__dict__[field] if isinstance(field_data, matrix): ret = field_data[uid] elif isinstance(field_data, list): if isinstance(idx, (float, int, str)): ret = field_data[uid] else: ret = [field_data[x] for x in uid] if astype is not None: ret = astype(ret) return ret
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python
train
sods/paramz
paramz/core/index_operations.py
https://github.com/sods/paramz/blob/ae6fc6274b70fb723d91e48fc5026a9bc5a06508/paramz/core/index_operations.py#L145-L159
def properties_dict_for(self, index): """ Return a dictionary, containing properties as keys and indices as index Thus, the indices for each constraint, which is contained will be collected as one dictionary Example: let properties: 'one':[1,2,3,4], 'two':[3,5,6] >>> properties_dict_for([2,3,5]) {'one':[2,3], 'two':[3,5]} """ props = self.properties_for(index) prop_index = extract_properties_to_index(index, props) return prop_index
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Return a dictionary, containing properties as keys and indices as index Thus, the indices for each constraint, which is contained will be collected as one dictionary Example: let properties: 'one':[1,2,3,4], 'two':[3,5,6] >>> properties_dict_for([2,3,5]) {'one':[2,3], 'two':[3,5]}
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python
train
airspeed-velocity/asv
asv/plugins/virtualenv.py
https://github.com/airspeed-velocity/asv/blob/d23bb8b74e8adacbfa3cf5724bda55fb39d56ba6/asv/plugins/virtualenv.py#L124-L140
def _setup(self): """ Setup the environment on disk using virtualenv. Then, all of the requirements are installed into it using `pip install`. """ log.info("Creating virtualenv for {0}".format(self.name)) util.check_call([ sys.executable, "-mvirtualenv", '--no-site-packages', "-p", self._executable, self._path]) log.info("Installing requirements for {0}".format(self.name)) self._install_requirements()
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Setup the environment on disk using virtualenv. Then, all of the requirements are installed into it using `pip install`.
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python
train
RedHatInsights/insights-core
insights/client/mount.py
https://github.com/RedHatInsights/insights-core/blob/b57cbf8ed7c089672426ede0441e0a4f789ef4a1/insights/client/mount.py#L112-L118
def _get_fs(thin_pathname): """ Returns the file system type (xfs, ext4) of a given device """ cmd = ['lsblk', '-o', 'FSTYPE', '-n', thin_pathname] fs_return = util.subp(cmd) return fs_return.stdout.strip()
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Returns the file system type (xfs, ext4) of a given device
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python
train
jreese/aiosqlite
aiosqlite/core.py
https://github.com/jreese/aiosqlite/blob/3f548b568b8db9a57022b6e2c9627f5cdefb983f/aiosqlite/core.py#L169-L173
async def _connect(self) -> "Connection": """Connect to the actual sqlite database.""" if self._connection is None: self._connection = await self._execute(self._connector) return self
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Connect to the actual sqlite database.
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python
train
schapman1974/tinymongo
tinymongo/tinymongo.py
https://github.com/schapman1974/tinymongo/blob/993048059dc0aa789d879b69feb79a0f237a60b3/tinymongo/tinymongo.py#L441-L469
def find(self, filter=None, sort=None, skip=None, limit=None, *args, **kwargs): """ Finds all matching results :param query: dictionary representing the mongo query :return: cursor containing the search results """ if self.table is None: self.build_table() if filter is None: result = self.table.all() else: allcond = self.parse_query(filter) try: result = self.table.search(allcond) except (AttributeError, TypeError): result = [] result = TinyMongoCursor( result, sort=sort, skip=skip, limit=limit ) return result
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python
train
tanghaibao/jcvi
jcvi/apps/base.py
https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/apps/base.py#L921-L931
def need_update(a, b): """ Check if file a is newer than file b and decide whether or not to update file b. Can generalize to two lists. """ a = listify(a) b = listify(b) return any((not op.exists(x)) for x in b) or \ all((os.stat(x).st_size == 0 for x in b)) or \ any(is_newer_file(x, y) for x in a for y in b)
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Check if file a is newer than file b and decide whether or not to update file b. Can generalize to two lists.
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python
train
saltstack/salt
salt/states/libcloud_storage.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/states/libcloud_storage.py#L175-L195
def file_present(container, name, path, profile, overwrite_existing=False): ''' Ensures a object is downloaded locally. :param container: Container name :type container: ``str`` :param name: Object name in cloud :type name: ``str`` :param path: Local path to file :type path: ``str`` :param profile: The profile key :type profile: ``str`` :param overwrite_existing: Replace if already exists :type overwrite_existing: ``bool`` ''' result = __salt__['libcloud_storage.download_object'](path, container, name, profile, overwrite_existing) return state_result(result, "Downloaded object", name, {})
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Ensures a object is downloaded locally. :param container: Container name :type container: ``str`` :param name: Object name in cloud :type name: ``str`` :param path: Local path to file :type path: ``str`` :param profile: The profile key :type profile: ``str`` :param overwrite_existing: Replace if already exists :type overwrite_existing: ``bool``
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python
train
base4sistemas/satcfe
satcfe/base.py
https://github.com/base4sistemas/satcfe/blob/cb8e8815f4133d3e3d94cf526fa86767b4521ed9/satcfe/base.py#L326-L347
def cancelar_ultima_venda(self, chave_cfe, dados_cancelamento): """Função ``CancelarUltimaVenda`` conforme ER SAT, item 6.1.4. Envia o CF-e de cancelamento para o equipamento SAT, que o enviará para autorização e cancelamento do CF-e pela SEFAZ. :param chave_cfe: String contendo a chave do CF-e a ser cancelado, prefixada com o literal ``CFe``. :param dados_cancelamento: Uma instância de :class:`~satcfe.entidades.CFeCancelamento` ou uma string contendo o XML do CF-e de cancelamento. :return: Retorna *verbatim* a resposta da função SAT. :rtype: string """ cfe_canc = dados_cancelamento \ if isinstance(dados_cancelamento, basestring) \ else dados_cancelamento.documento() return self.invocar__CancelarUltimaVenda( self.gerar_numero_sessao(), self._codigo_ativacao, chave_cfe, cfe_canc)
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Função ``CancelarUltimaVenda`` conforme ER SAT, item 6.1.4. Envia o CF-e de cancelamento para o equipamento SAT, que o enviará para autorização e cancelamento do CF-e pela SEFAZ. :param chave_cfe: String contendo a chave do CF-e a ser cancelado, prefixada com o literal ``CFe``. :param dados_cancelamento: Uma instância de :class:`~satcfe.entidades.CFeCancelamento` ou uma string contendo o XML do CF-e de cancelamento. :return: Retorna *verbatim* a resposta da função SAT. :rtype: string
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python
train
ejeschke/ginga
ginga/rv/Control.py
https://github.com/ejeschke/ginga/blob/a78c893ec6f37a837de851947e9bb4625c597915/ginga/rv/Control.py#L2609-L2614
def motion_cb(self, viewer, button, data_x, data_y): """Motion event in the channel viewer window. Show the pointing information under the cursor. """ self.showxy(viewer, data_x, data_y) return True
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Motion event in the channel viewer window. Show the pointing information under the cursor.
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python
train
boriel/zxbasic
arch/zx48k/backend/__array.py
https://github.com/boriel/zxbasic/blob/23b28db10e41117805bdb3c0f78543590853b132/arch/zx48k/backend/__array.py#L189-L243
def _astore16(ins): ''' Stores 2º operand content into address of 1st operand. store16 a, x => *(&a) = x Use '*' for indirect store on 1st operand. ''' output = _addr(ins.quad[1]) op = ins.quad[2] indirect = op[0] == '*' if indirect: op = op[1:] immediate = op[0] == '#' if immediate: op = op[1:] if is_int(op): op = str(int(op) & 0xFFFF) # Truncate to 16bit pointer if indirect: if immediate: output.append('ld de, (%s)' % op) else: output.append('ld de, (%s)' % op) output.append('call __LOAD_DE_DE') REQUIRES.add('lddede.asm') else: H = int(op) >> 8 L = int(op) & 0xFF output.append('ld (hl), %i' % L) output.append('inc hl') output.append('ld (hl), %i' % H) return output elif op[0] == '_': if indirect: if immediate: output.append('ld de, (%s)' % op) # redundant: *#_id == _id else: output.append('ld de, (%s)' % op) # *_id output.append('call __LOAD_DE_DE') REQUIRES.add('lddede.asm') else: if immediate: output.append('ld de, %s' % op) else: output.append('ld de, (%s)' % op) else: output.append('pop de') output.append('ld (hl), e') output.append('inc hl') output.append('ld (hl), d') return output
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python
train
awslabs/serverless-application-model
examples/apps/lex-make-appointment-python/lambda_function.py
https://github.com/awslabs/serverless-application-model/blob/cccb0c96b5c91e53355ebc07e542467303a5eedd/examples/apps/lex-make-appointment-python/lambda_function.py#L192-L207
def get_availabilities_for_duration(duration, availabilities): """ Helper function to return the windows of availability of the given duration, when provided a set of 30 minute windows. """ duration_availabilities = [] start_time = '10:00' while start_time != '17:00': if start_time in availabilities: if duration == 30: duration_availabilities.append(start_time) elif increment_time_by_thirty_mins(start_time) in availabilities: duration_availabilities.append(start_time) start_time = increment_time_by_thirty_mins(start_time) return duration_availabilities
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Helper function to return the windows of availability of the given duration, when provided a set of 30 minute windows.
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python
train
spotify/luigi
luigi/contrib/hadoop.py
https://github.com/spotify/luigi/blob/c5eca1c3c3ee2a7eb612486192a0da146710a1e9/luigi/contrib/hadoop.py#L989-L1004
def _map_input(self, input_stream): """ Iterate over input and call the mapper for each item. If the job has a parser defined, the return values from the parser will be passed as arguments to the mapper. If the input is coded output from a previous run, the arguments will be splitted in key and value. """ for record in self.reader(input_stream): for output in self.mapper(*record): yield output if self.final_mapper != NotImplemented: for output in self.final_mapper(): yield output self._flush_batch_incr_counter()
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Iterate over input and call the mapper for each item. If the job has a parser defined, the return values from the parser will be passed as arguments to the mapper. If the input is coded output from a previous run, the arguments will be splitted in key and value.
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python
train
juju/charm-helpers
charmhelpers/core/hookenv.py
https://github.com/juju/charm-helpers/blob/aa785c40c3b7a8c69dbfbc7921d6b9f30142e171/charmhelpers/core/hookenv.py#L676-L688
def relation_to_role_and_interface(relation_name): """ Given the name of a relation, return the role and the name of the interface that relation uses (where role is one of ``provides``, ``requires``, or ``peers``). :returns: A tuple containing ``(role, interface)``, or ``(None, None)``. """ _metadata = metadata() for role in ('provides', 'requires', 'peers'): interface = _metadata.get(role, {}).get(relation_name, {}).get('interface') if interface: return role, interface return None, None
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Given the name of a relation, return the role and the name of the interface that relation uses (where role is one of ``provides``, ``requires``, or ``peers``). :returns: A tuple containing ``(role, interface)``, or ``(None, None)``.
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python
train
chemlab/chemlab
chemlab/libs/cirpy.py
https://github.com/chemlab/chemlab/blob/c8730966316d101e24f39ac3b96b51282aba0abe/chemlab/libs/cirpy.py#L33-L39
def resolve(input, representation, resolvers=None, **kwargs): """ Resolve input to the specified output representation """ resultdict = query(input, representation, resolvers, **kwargs) result = resultdict[0]['value'] if resultdict else None if result and len(result) == 1: result = result[0] return result
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Resolve input to the specified output representation
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python
train
tchellomello/python-arlo
pyarlo/base_station.py
https://github.com/tchellomello/python-arlo/blob/db70aeb81705309c56ad32bbab1094f6cd146524/pyarlo/base_station.py#L408-L418
def get_cameras_signal_strength(self): """Return a list of signal strength of all cameras.""" signal_strength = {} if not self.camera_properties: return None for camera in self.camera_properties: serialnum = camera.get('serialNumber') cam_strength = camera.get('signalStrength') signal_strength[serialnum] = cam_strength return signal_strength
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Return a list of signal strength of all cameras.
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python
train
rsmuc/health_monitoring_plugins
health_monitoring_plugins/newtecmodem.py
https://github.com/rsmuc/health_monitoring_plugins/blob/7ac29dfb9fe46c055b018cb72ad0d7d8065589b9/health_monitoring_plugins/newtecmodem.py#L74-L79
def process_alarms(self, snmp_data): "Build list with active alarms" self.active_alarms = [] for i in range(0, len(self.models[self.modem_type]['alarms'])): if bool(int(snmp_data[i])) == True: self.active_alarms.append(self.models[self.modem_type]['alarms'][i])
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Build list with active alarms
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python
train
jazzband/django-axes
axes/attempts.py
https://github.com/jazzband/django-axes/blob/3e215a174030e43e7ab8c2a79c395eb0eeddc667/axes/attempts.py#L76-L86
def reset_user_attempts(request: AxesHttpRequest, credentials: dict = None) -> int: """ Reset all user attempts that match the given request and credentials. """ attempts = filter_user_attempts(request, credentials) count, _ = attempts.delete() log.info('AXES: Reset %s access attempts from database.', count) return count
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Reset all user attempts that match the given request and credentials.
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python
train
apple/turicreate
deps/src/libxml2-2.9.1/python/libxml2.py
https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/deps/src/libxml2-2.9.1/python/libxml2.py#L1994-L1999
def schemaNewMemParserCtxt(buffer, size): """Create an XML Schemas parse context for that memory buffer expected to contain an XML Schemas file. """ ret = libxml2mod.xmlSchemaNewMemParserCtxt(buffer, size) if ret is None:raise parserError('xmlSchemaNewMemParserCtxt() failed') return SchemaParserCtxt(_obj=ret)
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Create an XML Schemas parse context for that memory buffer expected to contain an XML Schemas file.
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python
train
opencobra/cobrapy
cobra/core/reaction.py
https://github.com/opencobra/cobrapy/blob/9d1987cdb3a395cf4125a3439c3b002ff2be2009/cobra/core/reaction.py#L107-L111
def reverse_id(self): """Generate the id of reverse_variable from the reaction's id.""" return '_'.join((self.id, 'reverse', hashlib.md5( self.id.encode('utf-8')).hexdigest()[0:5]))
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Generate the id of reverse_variable from the reaction's id.
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python
valid
googleapis/google-cloud-python
bigtable/google/cloud/bigtable_admin_v2/gapic/bigtable_instance_admin_client.py
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable_admin_v2/gapic/bigtable_instance_admin_client.py#L413-L485
def list_instances( self, parent, page_token=None, retry=google.api_core.gapic_v1.method.DEFAULT, timeout=google.api_core.gapic_v1.method.DEFAULT, metadata=None, ): """ Lists information about instances in a project. Example: >>> from google.cloud import bigtable_admin_v2 >>> >>> client = bigtable_admin_v2.BigtableInstanceAdminClient() >>> >>> parent = client.project_path('[PROJECT]') >>> >>> response = client.list_instances(parent) Args: parent (str): The unique name of the project for which a list of instances is requested. Values are of the form ``projects/<project>``. page_token (str): DEPRECATED: This field is unused and ignored. retry (Optional[google.api_core.retry.Retry]): A retry object used to retry requests. If ``None`` is specified, requests will not be retried. timeout (Optional[float]): The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata that is provided to the method. Returns: A :class:`~google.cloud.bigtable_admin_v2.types.ListInstancesResponse` instance. Raises: google.api_core.exceptions.GoogleAPICallError: If the request failed for any reason. google.api_core.exceptions.RetryError: If the request failed due to a retryable error and retry attempts failed. ValueError: If the parameters are invalid. """ # Wrap the transport method to add retry and timeout logic. if "list_instances" not in self._inner_api_calls: self._inner_api_calls[ "list_instances" ] = google.api_core.gapic_v1.method.wrap_method( self.transport.list_instances, default_retry=self._method_configs["ListInstances"].retry, default_timeout=self._method_configs["ListInstances"].timeout, client_info=self._client_info, ) request = bigtable_instance_admin_pb2.ListInstancesRequest( parent=parent, page_token=page_token ) if metadata is None: metadata = [] metadata = list(metadata) try: routing_header = [("parent", parent)] except AttributeError: pass else: routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata( routing_header ) metadata.append(routing_metadata) return self._inner_api_calls["list_instances"]( request, retry=retry, timeout=timeout, metadata=metadata )
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Lists information about instances in a project. Example: >>> from google.cloud import bigtable_admin_v2 >>> >>> client = bigtable_admin_v2.BigtableInstanceAdminClient() >>> >>> parent = client.project_path('[PROJECT]') >>> >>> response = client.list_instances(parent) Args: parent (str): The unique name of the project for which a list of instances is requested. Values are of the form ``projects/<project>``. page_token (str): DEPRECATED: This field is unused and ignored. retry (Optional[google.api_core.retry.Retry]): A retry object used to retry requests. If ``None`` is specified, requests will not be retried. timeout (Optional[float]): The amount of time, in seconds, to wait for the request to complete. Note that if ``retry`` is specified, the timeout applies to each individual attempt. metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata that is provided to the method. Returns: A :class:`~google.cloud.bigtable_admin_v2.types.ListInstancesResponse` instance. Raises: google.api_core.exceptions.GoogleAPICallError: If the request failed for any reason. google.api_core.exceptions.RetryError: If the request failed due to a retryable error and retry attempts failed. ValueError: If the parameters are invalid.
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python
train
DataDog/integrations-core
haproxy/datadog_checks/haproxy/haproxy.py
https://github.com/DataDog/integrations-core/blob/ebd41c873cf9f97a8c51bf9459bc6a7536af8acd/haproxy/datadog_checks/haproxy/haproxy.py#L193-L217
def _fetch_socket_data(self, parsed_url): ''' Hit a given stats socket and return the stats lines ''' self.log.debug("Fetching haproxy stats from socket: %s" % parsed_url.geturl()) if parsed_url.scheme == 'tcp': sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) splitted_loc = parsed_url.netloc.split(':') host = splitted_loc[0] port = int(splitted_loc[1]) sock.connect((host, port)) else: sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) sock.connect(parsed_url.path) sock.send(b"show stat\r\n") response = "" output = sock.recv(BUFSIZE) while output: response += output.decode("ASCII") output = sock.recv(BUFSIZE) sock.close() return response.splitlines()
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Hit a given stats socket and return the stats lines
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python
train
benley/butcher
butcher/gitrepo.py
https://github.com/benley/butcher/blob/8b18828ea040af56b7835beab5fd03eab23cc9ee/butcher/gitrepo.py#L147-L158
def sethead(self, ref): """Set head to a git ref.""" log.debug('[%s] Setting to ref %s', self.name, ref) try: ref = self.repo.rev_parse(ref) except gitdb.exc.BadObject: # Probably means we don't have it cached yet. # So maybe we can fetch it. ref = self.fetchref(ref) log.debug('[%s] Setting head to %s', self.name, ref) self.repo.head.reset(ref, working_tree=True) log.debug('[%s] Head object: %s', self.name, self.currenthead)
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Set head to a git ref.
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python
train
hasgeek/coaster
coaster/sqlalchemy/statemanager.py
https://github.com/hasgeek/coaster/blob/07f7eb5d5f516e22fa14fdf4dc70e0ae13ee398d/coaster/sqlalchemy/statemanager.py#L870-L878
def transitions_for(self, roles=None, actor=None, anchors=[]): """ For use on :class:`~coaster.sqlalchemy.mixins.RoleMixin` classes: returns currently available transitions for the specified roles or actor as a dictionary of name: :class:`StateTransitionWrapper`. """ proxy = self.obj.access_for(roles, actor, anchors) return {name: transition for name, transition in self.transitions(current=False).items() if name in proxy}
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For use on :class:`~coaster.sqlalchemy.mixins.RoleMixin` classes: returns currently available transitions for the specified roles or actor as a dictionary of name: :class:`StateTransitionWrapper`.
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python
train
cisco-sas/kitty
kitty/model/low_level/container.py
https://github.com/cisco-sas/kitty/blob/cb0760989dcdfe079e43ac574d872d0b18953a32/kitty/model/low_level/container.py#L709-L717
def get_rendered_fields(self, ctx=None): ''' :param ctx: rendering context in which the method was called :return: ordered list of the fields that will be rendered ''' times = self._min_times if self._mutating() and self._in_repeat_stage(): times += (self._current_index) * self._step return super(Repeat, self).get_rendered_fields(ctx) * times
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:param ctx: rendering context in which the method was called :return: ordered list of the fields that will be rendered
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python
train
mozilla/treeherder
treeherder/client/thclient/perfherder.py
https://github.com/mozilla/treeherder/blob/cc47bdec872e5c668d0f01df89517390a164cda3/treeherder/client/thclient/perfherder.py#L16-L26
def all_valid_time_intervals(): ''' Helper method to return all possible valid time intervals for data stored by Perfherder ''' return [PerformanceTimeInterval.DAY, PerformanceTimeInterval.WEEK, PerformanceTimeInterval.TWO_WEEKS, PerformanceTimeInterval.SIXTY_DAYS, PerformanceTimeInterval.NINETY_DAYS, PerformanceTimeInterval.ONE_YEAR]
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Helper method to return all possible valid time intervals for data stored by Perfherder
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python
train
googleapis/google-cloud-python
datastore/google/cloud/datastore/batch.py
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/datastore/google/cloud/datastore/batch.py#L159-L200
def put(self, entity): """Remember an entity's state to be saved during :meth:`commit`. .. note:: Any existing properties for the entity will be replaced by those currently set on this instance. Already-stored properties which do not correspond to keys set on this instance will be removed from the datastore. .. note:: Property values which are "text" ('unicode' in Python2, 'str' in Python3) map to 'string_value' in the datastore; values which are "bytes" ('str' in Python2, 'bytes' in Python3) map to 'blob_value'. When an entity has a partial key, calling :meth:`commit` sends it as an ``insert`` mutation and the key is completed. On return, the key for the ``entity`` passed in is updated to match the key ID assigned by the server. :type entity: :class:`google.cloud.datastore.entity.Entity` :param entity: the entity to be saved. :raises: :class:`~exceptions.ValueError` if the batch is not in progress, if entity has no key assigned, or if the key's ``project`` does not match ours. """ if self._status != self._IN_PROGRESS: raise ValueError("Batch must be in progress to put()") if entity.key is None: raise ValueError("Entity must have a key") if self.project != entity.key.project: raise ValueError("Key must be from same project as batch") if entity.key.is_partial: entity_pb = self._add_partial_key_entity_pb() self._partial_key_entities.append(entity) else: entity_pb = self._add_complete_key_entity_pb() _assign_entity_to_pb(entity_pb, entity)
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python
train
XuShaohua/bcloud
bcloud/IconWindow.py
https://github.com/XuShaohua/bcloud/blob/4b54e0fdccf2b3013285fef05c97354cfa31697b/bcloud/IconWindow.py#L758-L782
def on_drag_data_received(self, widget, context, x, y, data, info, time): '''拖放结束''' if not data: return bx, by = self.iconview.convert_widget_to_bin_window_coords(x, y) selected = Gtk.TreeView.get_path_at_pos(self.iconview, bx, by) if not selected: return tree_path = selected[0] if tree_path is None: return target_path = self.liststore[tree_path][PATH_COL] is_dir = self.liststore[tree_path][ISDIR_COL] if not is_dir or info != TargetInfo.PLAIN_TEXT: return filelist_str = data.get_text() filelist = json.loads(filelist_str) for file_item in filelist: if file_item['path'] == target_path: self.app.toast(_('Error: Move folder to itself!')) return for file_item in filelist: file_item['dest'] = target_path gutil.async_call(pcs.move, self.app.cookie, self.app.tokens, filelist, callback=self.parent.reload)
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拖放结束
[ "拖放结束" ]
python
train
obulpathi/cdn-fastly-python
fastly/__init__.py
https://github.com/obulpathi/cdn-fastly-python/blob/db2564b047e8af4bce72c3b88d6c27d3d0291425/fastly/__init__.py#L436-L439
def check_domain(self, service_id, version_number, name): """Checks the status of a domain's DNS record. Returns an array of 3 items. The first is the details for the domain. The second is the current CNAME of the domain. The third is a boolean indicating whether or not it has been properly setup to use Fastly.""" content = self._fetch("/service/%s/version/%d/domain/%s/check" % (service_id, version_number, name)) return FastlyDomainCheck(self, content)
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Checks the status of a domain's DNS record. Returns an array of 3 items. The first is the details for the domain. The second is the current CNAME of the domain. The third is a boolean indicating whether or not it has been properly setup to use Fastly.
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python
train
timster/peewee-validates
peewee_validates.py
https://github.com/timster/peewee-validates/blob/417f0fafb87fe9209439d65bc279d86a3d9e8028/peewee_validates.py#L886-L935
def convert_field(self, name, field): """ Convert a single field from a Peewee model field to a validator field. :param name: Name of the field as defined on this validator. :param name: Peewee field instance. :return: Validator field. """ if PEEWEE3: field_type = field.field_type.lower() else: field_type = field.db_field pwv_field = ModelValidator.FIELD_MAP.get(field_type, StringField) print('pwv_field', field_type, pwv_field) validators = [] required = not bool(getattr(field, 'null', True)) choices = getattr(field, 'choices', ()) default = getattr(field, 'default', None) max_length = getattr(field, 'max_length', None) unique = getattr(field, 'unique', False) if required: validators.append(validate_required()) if choices: print('CHOICES', choices) validators.append(validate_one_of([c[0] for c in choices])) if max_length: validators.append(validate_length(high=max_length)) if unique: validators.append(validate_model_unique(field, self.instance.select(), self.pk_field, self.pk_value)) if isinstance(field, peewee.ForeignKeyField): if PEEWEE3: rel_field = field.rel_field else: rel_field = field.to_field return ModelChoiceField(field.rel_model, rel_field, default=default, validators=validators) if isinstance(field, ManyToManyField): return ManyModelChoiceField( field.rel_model, field.rel_model._meta.primary_key, default=default, validators=validators) return pwv_field(default=default, validators=validators)
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Convert a single field from a Peewee model field to a validator field. :param name: Name of the field as defined on this validator. :param name: Peewee field instance. :return: Validator field.
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python
train
saltstack/salt
salt/modules/opkg.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/opkg.py#L1329-L1346
def get_repo(repo, **kwargs): # pylint: disable=unused-argument ''' Display a repo from the ``/etc/opkg/*.conf`` CLI Examples: .. code-block:: bash salt '*' pkg.get_repo repo ''' repos = list_repos() if repos: for source in six.itervalues(repos): for sub in source: if sub['name'] == repo: return sub return {}
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Display a repo from the ``/etc/opkg/*.conf`` CLI Examples: .. code-block:: bash salt '*' pkg.get_repo repo
[ "Display", "a", "repo", "from", "the", "/", "etc", "/", "opkg", "/", "*", ".", "conf" ]
python
train
apache/airflow
airflow/contrib/hooks/sagemaker_hook.py
https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/sagemaker_hook.py#L519-L572
def describe_training_job_with_log(self, job_name, positions, stream_names, instance_count, state, last_description, last_describe_job_call): """ Return the training job info associated with job_name and print CloudWatch logs """ log_group = '/aws/sagemaker/TrainingJobs' if len(stream_names) < instance_count: # Log streams are created whenever a container starts writing to stdout/err, so this list # may be dynamic until we have a stream for every instance. logs_conn = self.get_log_conn() try: streams = logs_conn.describe_log_streams( logGroupName=log_group, logStreamNamePrefix=job_name + '/', orderBy='LogStreamName', limit=instance_count ) stream_names = [s['logStreamName'] for s in streams['logStreams']] positions.update([(s, Position(timestamp=0, skip=0)) for s in stream_names if s not in positions]) except logs_conn.exceptions.ResourceNotFoundException: # On the very first training job run on an account, there's no log group until # the container starts logging, so ignore any errors thrown about that pass if len(stream_names) > 0: for idx, event in self.multi_stream_iter(log_group, stream_names, positions): self.log.info(event['message']) ts, count = positions[stream_names[idx]] if event['timestamp'] == ts: positions[stream_names[idx]] = Position(timestamp=ts, skip=count + 1) else: positions[stream_names[idx]] = Position(timestamp=event['timestamp'], skip=1) if state == LogState.COMPLETE: return state, last_description, last_describe_job_call if state == LogState.JOB_COMPLETE: state = LogState.COMPLETE elif time.time() - last_describe_job_call >= 30: description = self.describe_training_job(job_name) last_describe_job_call = time.time() if secondary_training_status_changed(description, last_description): self.log.info(secondary_training_status_message(description, last_description)) last_description = description status = description['TrainingJobStatus'] if status not in self.non_terminal_states: state = LogState.JOB_COMPLETE return state, last_description, last_describe_job_call
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Return the training job info associated with job_name and print CloudWatch logs
[ "Return", "the", "training", "job", "info", "associated", "with", "job_name", "and", "print", "CloudWatch", "logs" ]
python
test
thunlp/THULAC-Python
thulac/__init__.py
https://github.com/thunlp/THULAC-Python/blob/3f1f126cd92c3d2aebdf4ab4850de3c9428a3b66/thulac/__init__.py#L208-L227
def __cutRaw(self, oiraw, maxLength): '''现将句子按句子完结符号切分,如果切分完后一个句子长度超过限定值 ,再对该句子进行切分''' vec = [] m = re.findall(u".*?[。?!;;!?]", oiraw) num, l, last = 0, 0, 0 for i in range(len(m)): if(num + len(m[i]) >= maxLength): vec.append("".join(m[last:i])) last = i num = len(m[i]) else: num += len(m[i]) l += len(m[i]) if(len(oiraw)-l + num >= maxLength): vec.append("".join(m[last:len(m)])) vec.append(oiraw[l:]) else: vec.append(oiraw[l-num:]) return vec
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现将句子按句子完结符号切分,如果切分完后一个句子长度超过限定值 ,再对该句子进行切分
[ "现将句子按句子完结符号切分,如果切分完后一个句子长度超过限定值", ",再对该句子进行切分" ]
python
train