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openspending/babbage
babbage/cube.py
https://github.com/openspending/babbage/blob/9e03efe62e0be0cceabafd4de2a09cb8ec794b92/babbage/cube.py#L182-L188
def compute_cardinalities(self): """ This will count the number of distinct values for each dimension in the dataset and add that count to the model so that it can be used as a hint by UI components. """ for dimension in self.model.dimensions: result = self.members(dimension.ref, page_size=0) dimension.spec['cardinality'] = result.get('total_member_count')
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This will count the number of distinct values for each dimension in the dataset and add that count to the model so that it can be used as a hint by UI components.
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python
train
linkedin/naarad
src/naarad/__init__.py
https://github.com/linkedin/naarad/blob/261e2c0760fd6a6b0ee59064180bd8e3674311fe/src/naarad/__init__.py#L224-L266
def analyze(self, input_directory, output_directory, **kwargs): """ Run all the analysis saved in self._analyses, sorted by test_id. This is useful when Naarad() is used by other programs and multiple analyses are run In naarad CLI mode, len(_analyses) == 1 :param: input_directory: location of log files :param: output_directory: root directory for analysis output :param: **kwargs: Optional keyword args :return: int: status code. """ is_api_call = True if len(self._analyses) == 0: if 'config' not in kwargs.keys(): return CONSTANTS.ERROR self.create_analysis(kwargs['config']) if 'args' in kwargs: self._process_args(self._analyses[0], kwargs['args']) is_api_call = False error_count = 0 self._input_directory = input_directory self._output_directory = output_directory for test_id in sorted(self._analyses.keys()): # Setup if not self._analyses[test_id].input_directory: self._analyses[test_id].input_directory = input_directory if not self._analyses[test_id].output_directory: if len(self._analyses) > 1: self._analyses[test_id].output_directory = os.path.join(output_directory, str(test_id)) else: self._analyses[test_id].output_directory = output_directory if('config' in kwargs.keys()) and (not self._analyses[test_id].config): self._analyses[test_id].config = kwargs['config'] self._create_output_directories(self._analyses[test_id]) # Actually run analysis self._analyses[test_id].status = self.run(self._analyses[test_id], is_api_call, **kwargs) if self._analyses[test_id].status != CONSTANTS.OK: error_count += 1 if len(self._analyses) == 1: return self._analyses[0].status elif error_count > 0: return CONSTANTS.ERROR else: return CONSTANTS.OK
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python
valid
spyder-ide/spyder
spyder/app/mainwindow.py
https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/app/mainwindow.py#L2874-L2902
def edit_preferences(self): """Edit Spyder preferences""" from spyder.preferences.configdialog import ConfigDialog dlg = ConfigDialog(self) dlg.size_change.connect(self.set_prefs_size) if self.prefs_dialog_size is not None: dlg.resize(self.prefs_dialog_size) for PrefPageClass in self.general_prefs: widget = PrefPageClass(dlg, main=self) widget.initialize() dlg.add_page(widget) for plugin in [self.workingdirectory, self.editor, self.projects, self.ipyconsole, self.historylog, self.help, self.variableexplorer, self.onlinehelp, self.explorer, self.findinfiles ]+self.thirdparty_plugins: if plugin is not None: try: widget = plugin.create_configwidget(dlg) if widget is not None: dlg.add_page(widget) except Exception: traceback.print_exc(file=sys.stderr) if self.prefs_index is not None: dlg.set_current_index(self.prefs_index) dlg.show() dlg.check_all_settings() dlg.pages_widget.currentChanged.connect(self.__preference_page_changed) dlg.exec_()
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Edit Spyder preferences
[ "Edit", "Spyder", "preferences" ]
python
train
Unidata/siphon
siphon/ncss.py
https://github.com/Unidata/siphon/blob/53fb0d84fbce1c18c8e81c9e68bc81620ee0a6ac/siphon/ncss.py#L334-L345
def combine_xml_points(l, units, handle_units): """Combine multiple Point tags into an array.""" ret = {} for item in l: for key, value in item.items(): ret.setdefault(key, []).append(value) for key, value in ret.items(): if key != 'date': ret[key] = handle_units(value, units.get(key, None)) return ret
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Combine multiple Point tags into an array.
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python
train
dev-pipeline/dev-pipeline-core
lib/devpipeline_core/env.py
https://github.com/dev-pipeline/dev-pipeline-core/blob/fa40c050a56202485070b0300bb8695e9388c34f/lib/devpipeline_core/env.py#L41-L55
def create_environment(component_config): """ Create a modified environment. Arguments component_config - The configuration for a component. """ ret = os.environ.copy() for env in component_config.get_list("dp.env_list"): real_env = env.upper() value = os.environ.get(real_env) value = _prepend_env(component_config, env, value) value = _append_env(component_config, env, value) _apply_change(ret, real_env, value, component_config) return ret
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Create a modified environment. Arguments component_config - The configuration for a component.
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python
train
appknox/google-chartwrapper
GChartWrapper/GChart.py
https://github.com/appknox/google-chartwrapper/blob/3769aecbef6c83b6cd93ee72ece478ffe433ac57/GChartWrapper/GChart.py#L396-L406
def label(self, *args): """ Add a simple label to your chart call each time for each dataset APIPARAM: chl """ if self['cht'] == 'qr': self['chl'] = ''.join(map(str,args)) else: self['chl'] = '|'.join(map(str,args)) return self
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Add a simple label to your chart call each time for each dataset APIPARAM: chl
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python
test
rstoneback/pysat
pysat/instruments/nasa_cdaweb_methods.py
https://github.com/rstoneback/pysat/blob/4ae1afd80e15e4449397d39dce8c3e969c32c422/pysat/instruments/nasa_cdaweb_methods.py#L15-L85
def list_files(tag=None, sat_id=None, data_path=None, format_str=None, supported_tags=None, fake_daily_files_from_monthly=False, two_digit_year_break=None): """Return a Pandas Series of every file for chosen satellite data. This routine is intended to be used by pysat instrument modules supporting a particular NASA CDAWeb dataset. Parameters ----------- tag : (string or NoneType) Denotes type of file to load. Accepted types are <tag strings>. (default=None) sat_id : (string or NoneType) Specifies the satellite ID for a constellation. Not used. (default=None) data_path : (string or NoneType) Path to data directory. If None is specified, the value previously set in Instrument.files.data_path is used. (default=None) format_str : (string or NoneType) User specified file format. If None is specified, the default formats associated with the supplied tags are used. (default=None) supported_tags : (dict or NoneType) keys are tags supported by list_files routine. Values are the default format_str values for key. (default=None) fake_daily_files_from_monthly : bool Some CDAWeb instrument data files are stored by month, interfering with pysat's functionality of loading by day. This flag, when true, appends daily dates to monthly files internally. These dates are used by load routine in this module to provide data by day. Returns -------- pysat.Files.from_os : (pysat._files.Files) A class containing the verified available files Examples -------- :: fname = 'cnofs_vefi_bfield_1sec_{year:04d}{month:02d}{day:02d}_v05.cdf' supported_tags = {'dc_b':fname} list_files = functools.partial(nasa_cdaweb_methods.list_files, supported_tags=supported_tags) ivm_fname = 'cnofs_cindi_ivm_500ms_{year:4d}{month:02d}{day:02d}_v01.cdf' supported_tags = {'':ivm_fname} list_files = functools.partial(cdw.list_files, supported_tags=supported_tags) """ if data_path is not None: if format_str is None: try: format_str = supported_tags[sat_id][tag] except KeyError: raise ValueError('Unknown tag') out = pysat.Files.from_os(data_path=data_path, format_str=format_str) if (not out.empty) and fake_daily_files_from_monthly: out.ix[out.index[-1] + pds.DateOffset(months=1) - pds.DateOffset(days=1)] = out.iloc[-1] out = out.asfreq('D', 'pad') out = out + '_' + out.index.strftime('%Y-%m-%d') return out return out else: estr = 'A directory must be passed to the loading routine for <Instrument Code>' raise ValueError (estr)
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Return a Pandas Series of every file for chosen satellite data. This routine is intended to be used by pysat instrument modules supporting a particular NASA CDAWeb dataset. Parameters ----------- tag : (string or NoneType) Denotes type of file to load. Accepted types are <tag strings>. (default=None) sat_id : (string or NoneType) Specifies the satellite ID for a constellation. Not used. (default=None) data_path : (string or NoneType) Path to data directory. If None is specified, the value previously set in Instrument.files.data_path is used. (default=None) format_str : (string or NoneType) User specified file format. If None is specified, the default formats associated with the supplied tags are used. (default=None) supported_tags : (dict or NoneType) keys are tags supported by list_files routine. Values are the default format_str values for key. (default=None) fake_daily_files_from_monthly : bool Some CDAWeb instrument data files are stored by month, interfering with pysat's functionality of loading by day. This flag, when true, appends daily dates to monthly files internally. These dates are used by load routine in this module to provide data by day. Returns -------- pysat.Files.from_os : (pysat._files.Files) A class containing the verified available files Examples -------- :: fname = 'cnofs_vefi_bfield_1sec_{year:04d}{month:02d}{day:02d}_v05.cdf' supported_tags = {'dc_b':fname} list_files = functools.partial(nasa_cdaweb_methods.list_files, supported_tags=supported_tags) ivm_fname = 'cnofs_cindi_ivm_500ms_{year:4d}{month:02d}{day:02d}_v01.cdf' supported_tags = {'':ivm_fname} list_files = functools.partial(cdw.list_files, supported_tags=supported_tags)
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python
train
saltstack/salt
salt/utils/aggregation.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/aggregation.py#L188-L199
def mark(obj, map_class=Map, sequence_class=Sequence): ''' Convert obj into an Aggregate instance ''' if isinstance(obj, Aggregate): return obj if isinstance(obj, dict): return map_class(obj) if isinstance(obj, (list, tuple, set)): return sequence_class(obj) else: return sequence_class([obj])
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Convert obj into an Aggregate instance
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python
train
djgagne/hagelslag
hagelslag/evaluation/ProbabilityMetrics.py
https://github.com/djgagne/hagelslag/blob/6fb6c3df90bf4867e13a97d3460b14471d107df1/hagelslag/evaluation/ProbabilityMetrics.py#L148-L153
def auc(self): """ Calculate the Area Under the ROC Curve (AUC). """ roc_curve = self.roc_curve() return np.abs(np.trapz(roc_curve['POD'], x=roc_curve['POFD']))
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Calculate the Area Under the ROC Curve (AUC).
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python
train
artefactual-labs/mets-reader-writer
metsrw/fsentry.py
https://github.com/artefactual-labs/mets-reader-writer/blob/d95939cabdfdc25cb1bf67df0c84bd0d6e6a73ff/metsrw/fsentry.py#L210-L220
def group_id(self): """ Returns the @GROUPID. If derived_from is set, returns that group_id. """ if self.derived_from is not None: return self.derived_from.group_id() if self.file_uuid is None: return None return utils.GROUP_ID_PREFIX + self.file_uuid
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Returns the @GROUPID. If derived_from is set, returns that group_id.
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python
train
apache/incubator-mxnet
python/mxnet/gluon/trainer.py
https://github.com/apache/incubator-mxnet/blob/1af29e9c060a4c7d60eeaacba32afdb9a7775ba7/python/mxnet/gluon/trainer.py#L272-L286
def _row_sparse_pull(self, parameter, out, row_id, full_idx=False): """Internal method to invoke pull operations on KVStore. If `full_idx` is set to True, `kv.pull` is preferred instead of `kv.row_sparse_pull`. """ # initialize kv and params if not already if not self._kv_initialized: self._init_kvstore() if self._params_to_init: self._init_params() idx = self._param2idx[parameter.name] if full_idx and 'dist' not in self._kvstore.type: assert row_id.size == out.shape[0] self._kvstore.pull(idx, out=out, priority=-idx, ignore_sparse=False) else: self._kvstore.row_sparse_pull(idx, out=out, row_ids=row_id, priority=-idx)
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Internal method to invoke pull operations on KVStore. If `full_idx` is set to True, `kv.pull` is preferred instead of `kv.row_sparse_pull`.
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python
train
pdkit/pdkit
pdkit/utils.py
https://github.com/pdkit/pdkit/blob/c7120263da2071bb139815fbdb56ca77b544f340/pdkit/utils.py#L26-L66
def load_cloudupdrs_data(filename, convert_times=1000000000.0): """ This method loads data in the cloudupdrs format Usually the data will be saved in a csv file and it should look like this: .. code-block:: json timestamp_0, x_0, y_0, z_0 timestamp_1, x_1, y_1, z_1 timestamp_2, x_2, y_2, z_2 . . . timestamp_n, x_n, y_n, z_n where x, y, z are the components of the acceleration :param filename: The path to load data from :type filename: string :param convert_times: Convert times. The default is from from nanoseconds to seconds. :type convert_times: float """ # data_m = pd.read_table(filename, sep=',', header=None) try: data_m = np.genfromtxt(filename, delimiter=',', invalid_raise=False) date_times = pd.to_datetime((data_m[:, 0] - data_m[0, 0])) time_difference = (data_m[:, 0] - data_m[0, 0]) / convert_times magnitude_sum_acceleration = \ np.sqrt(data_m[:, 1] ** 2 + data_m[:, 2] ** 2 + data_m[:, 3] ** 2) data = {'td': time_difference, 'x': data_m[:, 1], 'y': data_m[:, 2], 'z': data_m[:, 3], 'mag_sum_acc': magnitude_sum_acceleration} data_frame = pd.DataFrame(data, index=date_times, columns=['td', 'x', 'y', 'z', 'mag_sum_acc']) return data_frame except IOError as e: ierr = "({}): {}".format(e.errno, e.strerror) logging.error("load data, file not found, I/O error %s", ierr) except ValueError as verr: logging.error("load data ValueError ->%s", verr.message) except: logging.error("Unexpected error on load data method: %s", sys.exc_info()[0])
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python
train
user-cont/colin
colin/core/result.py
https://github.com/user-cont/colin/blob/00bb80e6e91522e15361935f813e8cf13d7e76dc/colin/core/result.py#L133-L171
def generate_pretty_output(self, stat, verbose, output_function, logs=True): """ Send the formated to the provided function :param stat: if True print stat instead of full output :param verbose: bool :param output_function: function to send output to """ has_check = False for r in self.results: has_check = True if stat: output_function(OUTPUT_CHARS[r.status], fg=COLOURS[r.status], nl=False) else: output_function(str(r), fg=COLOURS[r.status]) if verbose: output_function(" -> {}\n" " -> {}".format(r.description, r.reference_url), fg=COLOURS[r.status]) if logs and r.logs: output_function(" -> logs:", fg=COLOURS[r.status]) for l in r.logs: output_function(" -> {}".format(l), fg=COLOURS[r.status]) if not has_check: output_function("No check found.") elif stat and not verbose: output_function("") else: output_function("") for status, count in six.iteritems(self.statistics): output_function("{}:{} ".format(status, count), nl=False) output_function("")
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Send the formated to the provided function :param stat: if True print stat instead of full output :param verbose: bool :param output_function: function to send output to
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python
train
Ouranosinc/xclim
xclim/indices.py
https://github.com/Ouranosinc/xclim/blob/2080d139188bd8de2aeca097a025c2d89d6e0e09/xclim/indices.py#L2113-L2159
def warm_spell_duration_index(tasmax, tx90, window=6, freq='YS'): r"""Warm spell duration index Number of days with at least six consecutive days where the daily maximum temperature is above the 90th percentile. The 90th percentile should be computed for a 5-day window centred on each calendar day in the 1961-1990 period. Parameters ---------- tasmax : xarray.DataArray Maximum daily temperature [℃] or [K] tx90 : float 90th percentile of daily maximum temperature [℃] or [K] window : int Minimum number of days with temperature below threshold to qualify as a warm spell. freq : str, optional Resampling frequency Returns ------- xarray.DataArray Count of days with at least six consecutive days where the daily maximum temperature is above the 90th percentile [days]. References ---------- From the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Used in Alexander, L. V., et al. (2006), Global observed changes in daily climate extremes of temperature and precipitation, J. Geophys. Res., 111, D05109, doi: 10.1029/2005JD006290. """ if 'dayofyear' not in tx90.coords.keys(): raise AttributeError("tx90 should have dayofyear coordinates.") # The day of year value of the tasmax series. doy = tasmax.indexes['time'].dayofyear # adjustment of tx90 to tasmax doy range tx90 = utils.adjust_doy_calendar(tx90, tasmax) # Create an array with the shape and coords of tasmax, but with values set to tx90 according to the doy index. thresh = xr.full_like(tasmax, np.nan) thresh.data = tx90.sel(dayofyear=doy) above = (tasmax > thresh) return above.resample(time=freq).apply(rl.windowed_run_count, window=window, dim='time')
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r"""Warm spell duration index Number of days with at least six consecutive days where the daily maximum temperature is above the 90th percentile. The 90th percentile should be computed for a 5-day window centred on each calendar day in the 1961-1990 period. Parameters ---------- tasmax : xarray.DataArray Maximum daily temperature [℃] or [K] tx90 : float 90th percentile of daily maximum temperature [℃] or [K] window : int Minimum number of days with temperature below threshold to qualify as a warm spell. freq : str, optional Resampling frequency Returns ------- xarray.DataArray Count of days with at least six consecutive days where the daily maximum temperature is above the 90th percentile [days]. References ---------- From the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Used in Alexander, L. V., et al. (2006), Global observed changes in daily climate extremes of temperature and precipitation, J. Geophys. Res., 111, D05109, doi: 10.1029/2005JD006290.
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python
train
raamana/hiwenet
hiwenet/pairwise_dist.py
https://github.com/raamana/hiwenet/blob/b12699b3722fd0a6a835e7d7ca4baf58fb181809/hiwenet/pairwise_dist.py#L498-L554
def check_weight_method(weight_method_spec, use_orig_distr=False, allow_non_symmetric=False): "Check if weight_method is recognized and implemented, or ensure it is callable." if not isinstance(use_orig_distr, bool): raise TypeError('use_original_distribution flag must be boolean!') if not isinstance(allow_non_symmetric, bool): raise TypeError('allow_non_symmetric flag must be boolean') if isinstance(weight_method_spec, str): weight_method_spec = weight_method_spec.lower() if weight_method_spec in list_medpy_histogram_metrics: from medpy.metric import histogram as medpy_hist_metrics weight_func = getattr(medpy_hist_metrics, weight_method_spec) if use_orig_distr: warnings.warn('use_original_distribution must be False when using builtin histogram metrics, ' 'which expect histograms as input - setting it to False.', HiwenetWarning) use_orig_distr = False elif weight_method_spec in metrics_on_original_features: weight_func = getattr(more_metrics, weight_method_spec) if not use_orig_distr: warnings.warn('use_original_distribution must be True when using builtin non-histogram metrics, ' 'which expect original feature values in ROI/node as input ' '- setting it to True.', HiwenetWarning) use_orig_distr = True if weight_method_spec in symmetric_metrics_on_original_features: print('Chosen metric is symmetric. Ignoring asymmetric=False flag.') allow_non_symmetric=False else: raise NotImplementedError('Chosen histogram distance/metric not implemented or invalid.') elif callable(weight_method_spec): # ensure 1) takes two ndarrays try: dummy_weight = weight_method_spec(make_random_histogram(), make_random_histogram()) except: raise TypeError('Error applying given callable on two input arrays.\n' '{} must accept two arrays and return a single scalar value!') else: # and 2) returns only one number if not np.isscalar(dummy_weight): raise TypeError('Given callable does not return a single scalar as output.') weight_func = weight_method_spec else: raise ValueError('Supplied method to compute edge weight is not recognized:\n' 'must be a string identifying one of the implemented methods\n{}' '\n or a valid callable that accepts that two arrays ' 'and returns 1 scalar.'.format(list_medpy_histogram_metrics)) return weight_func, use_orig_distr, allow_non_symmetric
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Check if weight_method is recognized and implemented, or ensure it is callable.
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python
train
adafruit/Adafruit_Python_BluefruitLE
Adafruit_BluefruitLE/corebluetooth/provider.py
https://github.com/adafruit/Adafruit_Python_BluefruitLE/blob/34fc6f596371b961628369d78ce836950514062f/Adafruit_BluefruitLE/corebluetooth/provider.py#L179-L188
def peripheral_didUpdateValueForCharacteristic_error_(self, peripheral, characteristic, error): """Called when characteristic value was read or updated.""" logger.debug('peripheral_didUpdateValueForCharacteristic_error called') # Stop if there was some kind of error. if error is not None: return # Notify the device about the updated characteristic value. device = device_list().get(peripheral) if device is not None: device._characteristic_changed(characteristic)
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Called when characteristic value was read or updated.
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python
valid
BerkeleyAutomation/perception
perception/image.py
https://github.com/BerkeleyAutomation/perception/blob/03d9b37dd6b66896cdfe173905c9413c8c3c5df6/perception/image.py#L2902-L2924
def transform(self, translation, theta, method='opencv'): """Create a new image by translating and rotating the current image. Parameters ---------- translation : :obj:`numpy.ndarray` of float The XY translation vector. theta : float Rotation angle in radians, with positive meaning counter-clockwise. method : :obj:`str` Method to use for image transformations (opencv or scipy) Returns ------- :obj:`Image` An image of the same type that has been rotated and translated. """ # transform channels separately color_im_tf = self.color.transform(translation, theta, method=method) depth_im_tf = self.depth.transform(translation, theta, method=method) # return combination of cropped data return RgbdImage.from_color_and_depth(color_im_tf, depth_im_tf)
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Create a new image by translating and rotating the current image. Parameters ---------- translation : :obj:`numpy.ndarray` of float The XY translation vector. theta : float Rotation angle in radians, with positive meaning counter-clockwise. method : :obj:`str` Method to use for image transformations (opencv or scipy) Returns ------- :obj:`Image` An image of the same type that has been rotated and translated.
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python
train
fermiPy/fermipy
fermipy/roi_model.py
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/roi_model.py#L398-L401
def is_free(self): """ returns True if any of the spectral model parameters is set to free, else False """ return bool(np.array([int(value.get("free", False)) for key, value in self.spectral_pars.items()]).sum())
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returns True if any of the spectral model parameters is set to free, else False
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python
train
Asana/python-asana
asana/resources/gen/projects.py
https://github.com/Asana/python-asana/blob/6deb7a34495db23f44858e53b6bb2c9eccff7872/asana/resources/gen/projects.py#L136-L147
def find_by_team(self, team, params={}, **options): """Returns the compact project records for all projects in the team. Parameters ---------- team : {Id} The team to find projects in. [params] : {Object} Parameters for the request - [archived] : {Boolean} Only return projects whose `archived` field takes on the value of this parameter. """ path = "/teams/%s/projects" % (team) return self.client.get_collection(path, params, **options)
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Returns the compact project records for all projects in the team. Parameters ---------- team : {Id} The team to find projects in. [params] : {Object} Parameters for the request - [archived] : {Boolean} Only return projects whose `archived` field takes on the value of this parameter.
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python
train
kennydo/nyaalib
nyaalib/__init__.py
https://github.com/kennydo/nyaalib/blob/ab787b7ba141ed53d2ad978bf13eb7b8bcdd4b0d/nyaalib/__init__.py#L38-L65
def _get_page_content(self, response): """Given a :class:`requests.Response`, return the :class:`xml.etree.Element` of the content `div`. :param response: a :class:`requests.Response` to parse :returns: the :class:`Element` of the first content `div` or `None` """ document = html5lib.parse( response.content, encoding=response.encoding, treebuilder='etree', namespaceHTMLElements=False ) # etree doesn't fully support XPath, so we can't just search # the attribute values for "content" divs = document.findall( ".//body//div[@class]") content_div = None for div in divs: if "content" in div.attrib['class'].split(' '): content_div = div break # The `Element` object is False-y when there are no subelements, # so compare to `None` if content_div is None: return None return content_div
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Given a :class:`requests.Response`, return the :class:`xml.etree.Element` of the content `div`. :param response: a :class:`requests.Response` to parse :returns: the :class:`Element` of the first content `div` or `None`
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python
train
metagriffin/asset
asset/resource.py
https://github.com/metagriffin/asset/blob/f2c5e599cd4688f82216d4b5cfa87aab96d8bb8c/asset/resource.py#L244-L276
def load(pattern, *args, **kw): ''' Given a package asset-spec glob-pattern `pattern`, returns an :class:`AssetGroup` object, which in turn can act as a generator of :class:`Asset` objects that match the pattern. Example: .. code-block:: python import asset # concatenate all 'css' files into one string: css = asset.load('mypackage:static/style/**.css').read() ''' spec = pattern if ':' not in pattern: raise ValueError('`pattern` must be in the format "PACKAGE:GLOB"') pkgname, pkgpat = pattern.split(':', 1) pkgdir, pattern = globre.compile(pkgpat, split_prefix=True, flags=globre.EXACT) if pkgdir: idx = pkgdir.rfind('/') pkgdir = pkgdir[:idx] if idx >= 0 else '' group = AssetGroup(pkgname, pkgdir, pattern, spec) if globre.iswild(pkgpat): return group return Asset(group, pkgname, pkgpat)
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Given a package asset-spec glob-pattern `pattern`, returns an :class:`AssetGroup` object, which in turn can act as a generator of :class:`Asset` objects that match the pattern. Example: .. code-block:: python import asset # concatenate all 'css' files into one string: css = asset.load('mypackage:static/style/**.css').read()
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python
train
open-mmlab/mmcv
mmcv/image/transforms/colorspace.py
https://github.com/open-mmlab/mmcv/blob/0d77f61450aab4dde8b8585a577cc496acb95d7f/mmcv/image/transforms/colorspace.py#L33-L44
def gray2bgr(img): """Convert a grayscale image to BGR image. Args: img (ndarray or str): The input image. Returns: ndarray: The converted BGR image. """ img = img[..., None] if img.ndim == 2 else img out_img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) return out_img
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Convert a grayscale image to BGR image. Args: img (ndarray or str): The input image. Returns: ndarray: The converted BGR image.
[ "Convert", "a", "grayscale", "image", "to", "BGR", "image", "." ]
python
test
misli/django-cms-articles
cms_articles/models/managers.py
https://github.com/misli/django-cms-articles/blob/d96ac77e049022deb4c70d268e4eab74d175145c/cms_articles/models/managers.py#L19-L60
def search(self, q, language=None, current_site_only=True): """Simple search function Plugins can define a 'search_fields' tuple similar to ModelAdmin classes """ from cms.plugin_pool import plugin_pool qs = self.get_queryset() qs = qs.public() if current_site_only: site = Site.objects.get_current() qs = qs.filter(tree__site=site) qt = Q(title_set__title__icontains=q) # find 'searchable' plugins and build query qp = Q() plugins = plugin_pool.get_all_plugins() for plugin in plugins: cmsplugin = plugin.model if not ( hasattr(cmsplugin, 'search_fields') and hasattr(cmsplugin, 'cmsplugin_ptr') ): continue field = cmsplugin.cmsplugin_ptr.field related_query_name = field.related_query_name() if related_query_name and not related_query_name.startswith('+'): for field in cmsplugin.search_fields: qp |= Q(**{ 'placeholders__cmsplugin__{0}__{1}__icontains'.format( related_query_name, field, ): q}) if language: qt &= Q(title_set__language=language) qp &= Q(cmsplugin__language=language) qs = qs.filter(qt | qp) return qs.distinct()
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Simple search function Plugins can define a 'search_fields' tuple similar to ModelAdmin classes
[ "Simple", "search", "function" ]
python
train
tensorflow/hub
examples/text_embeddings/export.py
https://github.com/tensorflow/hub/blob/09f45963f6787322967b6fec61459f3ac56fbb27/examples/text_embeddings/export.py#L62-L90
def load(file_path, parse_line_fn): """Loads a text embedding into memory as a numpy matrix. Args: file_path: Path to the text embedding file. parse_line_fn: callback function to parse each file line. Returns: A tuple of (list of vocabulary tokens, numpy matrix of embedding vectors). Raises: ValueError: if the data in the sstable is inconsistent. """ vocabulary = [] embeddings = [] embeddings_dim = None for line in tf.gfile.GFile(file_path): token, embedding = parse_line_fn(line) if not embeddings_dim: embeddings_dim = len(embedding) elif embeddings_dim != len(embedding): raise ValueError( "Inconsistent embedding dimension detected, %d != %d for token %s", embeddings_dim, len(embedding), token) vocabulary.append(token) embeddings.append(embedding) return vocabulary, np.array(embeddings)
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Loads a text embedding into memory as a numpy matrix. Args: file_path: Path to the text embedding file. parse_line_fn: callback function to parse each file line. Returns: A tuple of (list of vocabulary tokens, numpy matrix of embedding vectors). Raises: ValueError: if the data in the sstable is inconsistent.
[ "Loads", "a", "text", "embedding", "into", "memory", "as", "a", "numpy", "matrix", "." ]
python
train
lepture/flask-oauthlib
flask_oauthlib/provider/oauth1.py
https://github.com/lepture/flask-oauthlib/blob/9e6f152a5bb360e7496210da21561c3e6d41b0e1/flask_oauthlib/provider/oauth1.py#L657-L671
def get_access_token_secret(self, client_key, token, request): """Get access token secret. The access token object should a ``secret`` attribute. """ log.debug('Get access token secret of %r for %r', token, client_key) tok = request.access_token or self._tokengetter( client_key=client_key, token=token, ) if tok: request.access_token = tok return tok.secret return None
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Get access token secret. The access token object should a ``secret`` attribute.
[ "Get", "access", "token", "secret", "." ]
python
test
mzucker/noteshrink
noteshrink.py
https://github.com/mzucker/noteshrink/blob/7d876e5b43923c6bf8d64b7ef18f6855bfb30ce3/noteshrink.py#L371-L396
def get_palette(samples, options, return_mask=False, kmeans_iter=40): '''Extract the palette for the set of sampled RGB values. The first palette entry is always the background color; the rest are determined from foreground pixels by running K-means clustering. Returns the palette, as well as a mask corresponding to the foreground pixels. ''' if not options.quiet: print(' getting palette...') bg_color = get_bg_color(samples, 6) fg_mask = get_fg_mask(bg_color, samples, options) centers, _ = kmeans(samples[fg_mask].astype(np.float32), options.num_colors-1, iter=kmeans_iter) palette = np.vstack((bg_color, centers)).astype(np.uint8) if not return_mask: return palette else: return palette, fg_mask
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Extract the palette for the set of sampled RGB values. The first palette entry is always the background color; the rest are determined from foreground pixels by running K-means clustering. Returns the palette, as well as a mask corresponding to the foreground pixels.
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python
train
yunojuno/elasticsearch-django
elasticsearch_django/models.py
https://github.com/yunojuno/elasticsearch-django/blob/e8d98d32bcd77f1bedb8f1a22b6523ca44ffd489/elasticsearch_django/models.py#L59-L80
def in_search_queryset(self, instance_id, index="_all"): """ Return True if an object is part of the search index queryset. Sometimes it's useful to know if an object _should_ be indexed. If an object is saved, how do you know if you should push that change to the search index? The simplest (albeit not most efficient) way is to check if it appears in the underlying search queryset. NB this method doesn't evaluate the entire dataset, it chains an additional queryset filter expression on the end. That's why it's important that the `get_search_queryset` method returns a queryset. Args: instance_id: the id of model object that we are looking for. Kwargs: index: string, the name of the index in which to check. Defaults to '_all'. """ return self.get_search_queryset(index=index).filter(pk=instance_id).exists()
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Return True if an object is part of the search index queryset. Sometimes it's useful to know if an object _should_ be indexed. If an object is saved, how do you know if you should push that change to the search index? The simplest (albeit not most efficient) way is to check if it appears in the underlying search queryset. NB this method doesn't evaluate the entire dataset, it chains an additional queryset filter expression on the end. That's why it's important that the `get_search_queryset` method returns a queryset. Args: instance_id: the id of model object that we are looking for. Kwargs: index: string, the name of the index in which to check. Defaults to '_all'.
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python
train
joeblackwaslike/pricing
pricing/metaconfigure.py
https://github.com/joeblackwaslike/pricing/blob/be988b0851b4313af81f1db475bc33248700e39c/pricing/metaconfigure.py#L37-L46
def currencyFormat(_context, code, symbol, format, currency_digits=True, decimal_quantization=True, name=''): """Handle currencyFormat subdirectives.""" _context.action( discriminator=('currency', name, code), callable=_register_currency, args=(name, code, symbol, format, currency_digits, decimal_quantization) )
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Handle currencyFormat subdirectives.
[ "Handle", "currencyFormat", "subdirectives", "." ]
python
test
latchset/jwcrypto
jwcrypto/jws.py
https://github.com/latchset/jwcrypto/blob/961df898dc08f63fe3d900f2002618740bc66b4a/jwcrypto/jws.py#L419-L510
def add_signature(self, key, alg=None, protected=None, header=None): """Adds a new signature to the object. :param key: A (:class:`jwcrypto.jwk.JWK`) key of appropriate for the "alg" provided. :param alg: An optional algorithm name. If already provided as an element of the protected or unprotected header it can be safely omitted. :param potected: The Protected Header (optional) :param header: The Unprotected Header (optional) :raises InvalidJWSObject: if no payload has been set on the object, or invalid headers are provided. :raises ValueError: if the key is not a :class:`JWK` object. :raises ValueError: if the algorithm is missing or is not provided by one of the headers. :raises InvalidJWAAlgorithm: if the algorithm is not valid, is unknown or otherwise not yet implemented. """ if not self.objects.get('payload', None): raise InvalidJWSObject('Missing Payload') b64 = True p = dict() if protected: if isinstance(protected, dict): p = protected protected = json_encode(p) else: p = json_decode(protected) # If b64 is present we must enforce criticality if 'b64' in list(p.keys()): crit = p.get('crit', []) if 'b64' not in crit: raise InvalidJWSObject('b64 header must always be critical') b64 = p['b64'] if 'b64' in self.objects: if b64 != self.objects['b64']: raise InvalidJWSObject('Mixed b64 headers on signatures') h = None if header: if isinstance(header, dict): h = header header = json_encode(header) else: h = json_decode(header) p = self._merge_check_headers(p, h) if 'alg' in p: if alg is None: alg = p['alg'] elif alg != p['alg']: raise ValueError('"alg" value mismatch, specified "alg" ' 'does not match JOSE header value') if alg is None: raise ValueError('"alg" not specified') c = JWSCore(alg, key, protected, self.objects['payload']) sig = c.sign() o = dict() o['signature'] = base64url_decode(sig['signature']) if protected: o['protected'] = protected if header: o['header'] = h o['valid'] = True if 'signatures' in self.objects: self.objects['signatures'].append(o) elif 'signature' in self.objects: self.objects['signatures'] = list() n = dict() n['signature'] = self.objects.pop('signature') if 'protected' in self.objects: n['protected'] = self.objects.pop('protected') if 'header' in self.objects: n['header'] = self.objects.pop('header') if 'valid' in self.objects: n['valid'] = self.objects.pop('valid') self.objects['signatures'].append(n) self.objects['signatures'].append(o) else: self.objects.update(o) self.objects['b64'] = b64
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Adds a new signature to the object. :param key: A (:class:`jwcrypto.jwk.JWK`) key of appropriate for the "alg" provided. :param alg: An optional algorithm name. If already provided as an element of the protected or unprotected header it can be safely omitted. :param potected: The Protected Header (optional) :param header: The Unprotected Header (optional) :raises InvalidJWSObject: if no payload has been set on the object, or invalid headers are provided. :raises ValueError: if the key is not a :class:`JWK` object. :raises ValueError: if the algorithm is missing or is not provided by one of the headers. :raises InvalidJWAAlgorithm: if the algorithm is not valid, is unknown or otherwise not yet implemented.
[ "Adds", "a", "new", "signature", "to", "the", "object", "." ]
python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/zmq/kernelmanager.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/zmq/kernelmanager.py#L195-L206
def run(self): """The thread's main activity. Call start() instead.""" self.socket = self.context.socket(zmq.DEALER) self.socket.setsockopt(zmq.IDENTITY, self.session.bsession) self.socket.connect('tcp://%s:%i' % self.address) self.stream = zmqstream.ZMQStream(self.socket, self.ioloop) self.stream.on_recv(self._handle_recv) self._run_loop() try: self.socket.close() except: pass
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The thread's main activity. Call start() instead.
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python
test
OnroerendErfgoed/oe_utils
oe_utils/views/atom.py
https://github.com/OnroerendErfgoed/oe_utils/blob/7b2014bda8ac6bb71b7138eaa06ac17ef3ff4a6d/oe_utils/views/atom.py#L147-L157
def _generate_atom_feed(self, feed): """ A function returning a feed like `feedgen.feed.FeedGenerator`. The function can be overwritten when used in other applications. :param feed: a feed object :return: an atom feed `feedgen.feed.FeedGenerator` """ atom_feed = self.init_atom_feed(feed) atom_feed.title("Feed") return atom_feed
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A function returning a feed like `feedgen.feed.FeedGenerator`. The function can be overwritten when used in other applications. :param feed: a feed object :return: an atom feed `feedgen.feed.FeedGenerator`
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python
train
codeghar/brokerlso
brokerlso/qmfv2.py
https://github.com/codeghar/brokerlso/blob/e110e12502b090e12b06c7615dd0a96a14a92585/brokerlso/qmfv2.py#L157-L166
def list_queues(self): """Create message content and properties to list all queues with QMFv2 :returns: Tuple containing content and query properties """ content = {"_what": "OBJECT", "_schema_id": {"_class_name": "queue"}} logger.debug("Message content -> {0}".format(content)) return content, self.query_properties
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Create message content and properties to list all queues with QMFv2 :returns: Tuple containing content and query properties
[ "Create", "message", "content", "and", "properties", "to", "list", "all", "queues", "with", "QMFv2" ]
python
test
Netflix-Skunkworks/cloudaux
cloudaux/orchestration/aws/iam/group.py
https://github.com/Netflix-Skunkworks/cloudaux/blob/c4b0870c3ac68b1c69e71d33cf78b6a8bdf437ea/cloudaux/orchestration/aws/iam/group.py#L74-L103
def get_group(group, flags=FLAGS.BASE | FLAGS.INLINE_POLICIES | FLAGS.MANAGED_POLICIES, **conn): """ Orchestrates all the calls required to fully build out an IAM Group in the following format: { "Arn": ..., "GroupName": ..., "Path": ..., "GroupId": ..., "CreateDate": ..., # str "InlinePolicies": ..., "ManagedPolicies": ..., # These are just the names of the Managed Policies. "Users": ..., # False by default -- these are just the names of the users. "_version": 1 } :param flags: By default, Users is disabled. This is somewhat expensive as it has to call the `get_group` call multiple times. :param group: dict MUST contain the GroupName and also a combination of either the ARN or the account_number. :param output: Determines whether keys should be returned camelized or underscored. :param conn: dict containing enough information to make a connection to the desired account. Must at least have 'assume_role' key. :return: dict containing fully built out Group. """ if not group.get('GroupName'): raise MissingFieldException('Must include GroupName.') group = modify(group, output='camelized') _conn_from_args(group, conn) return registry.build_out(flags, start_with=group, pass_datastructure=True, **conn)
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Orchestrates all the calls required to fully build out an IAM Group in the following format: { "Arn": ..., "GroupName": ..., "Path": ..., "GroupId": ..., "CreateDate": ..., # str "InlinePolicies": ..., "ManagedPolicies": ..., # These are just the names of the Managed Policies. "Users": ..., # False by default -- these are just the names of the users. "_version": 1 } :param flags: By default, Users is disabled. This is somewhat expensive as it has to call the `get_group` call multiple times. :param group: dict MUST contain the GroupName and also a combination of either the ARN or the account_number. :param output: Determines whether keys should be returned camelized or underscored. :param conn: dict containing enough information to make a connection to the desired account. Must at least have 'assume_role' key. :return: dict containing fully built out Group.
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python
valid
JdeRobot/base
src/drivers/MAVLinkServer/MAVProxy/pymavlink/generator/mavparse.py
https://github.com/JdeRobot/base/blob/303b18992785b2fe802212f2d758a60873007f1f/src/drivers/MAVLinkServer/MAVProxy/pymavlink/generator/mavparse.py#L396-L427
def merge_enums(xml): '''merge enums between XML files''' emap = {} for x in xml: newenums = [] for enum in x.enum: if enum.name in emap: emapitem = emap[enum.name] # check for possible conflicting auto-assigned values after merge if (emapitem.start_value <= enum.highest_value and emapitem.highest_value >= enum.start_value): for entry in emapitem.entry: # correct the value if necessary, but only if it was auto-assigned to begin with if entry.value <= enum.highest_value and entry.autovalue == True: entry.value = enum.highest_value + 1 enum.highest_value = entry.value # merge the entries emapitem.entry.extend(enum.entry) if not emapitem.description: emapitem.description = enum.description print("Merged enum %s" % enum.name) else: newenums.append(enum) emap[enum.name] = enum x.enum = newenums for e in emap: # sort by value emap[e].entry = sorted(emap[e].entry, key=operator.attrgetter('value'), reverse=False) # add a ENUM_END emap[e].entry.append(MAVEnumEntry("%s_ENUM_END" % emap[e].name, emap[e].entry[-1].value+1, end_marker=True))
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merge enums between XML files
[ "merge", "enums", "between", "XML", "files" ]
python
train
supercoderz/pyflightdata
pyflightdata/flightdata.py
https://github.com/supercoderz/pyflightdata/blob/2caf9f429288f9a171893d1b8377d0c6244541cc/pyflightdata/flightdata.py#L556-L577
def decode_metar(self, metar): """ Simple method that decodes a given metar string. Args: metar (str): The metar data Returns: The metar data in readable format Example:: from pyflightdata import FlightData f=FlightData() f.decode_metar('WSSS 181030Z 04009KT 010V080 9999 FEW018TCU BKN300 29/22 Q1007 NOSIG') """ try: from metar import Metar except: return "Unable to parse metars. Please install parser from https://github.com/tomp/python-metar." m = Metar.Metar(metar) return m.string()
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Simple method that decodes a given metar string. Args: metar (str): The metar data Returns: The metar data in readable format Example:: from pyflightdata import FlightData f=FlightData() f.decode_metar('WSSS 181030Z 04009KT 010V080 9999 FEW018TCU BKN300 29/22 Q1007 NOSIG')
[ "Simple", "method", "that", "decodes", "a", "given", "metar", "string", "." ]
python
train
SBRG/ssbio
ssbio/biopython/Bio/Struct/WWW/WHATIFXML.py
https://github.com/SBRG/ssbio/blob/e9449e64ffc1a1f5ad07e5849aa12a650095f8a2/ssbio/biopython/Bio/Struct/WWW/WHATIFXML.py#L81-L182
def _parse(self): """ Parse atomic data of the XML file. """ atom_counter = 0 structure_build = self.structure_builder residues = self._extract_residues() cur_model = None cur_chain = None structure_build.init_seg(' ') # There is never a SEGID present for r in residues: # New model? if cur_model != r['model']: cur_model = r['model'] try: structure_build.init_model(cur_model) except PDBConstructionException, message: self._handle_builder_exception(message, r) # New chain? if cur_chain != r['chain']: cur_chain = r['chain'] try: structure_build.init_chain(cur_chain) except PDBConstructionException, message: self._handle_builder_exception(message, r) # Create residue if r['name'] in AA_LIST: # Get residue type crudely since there is no HETATM / ATOM hetero_flag = ' ' elif r['name'] == 'WAT' or r['name'] == 'HOH': hetero_flag = 'W' else: hetero_flag = 'H' # Some terminal atoms are added at residue 0. This residue has a small number of atoms. # Protonated non-terminal glycine has 7 atoms. Any of these residues is smaller. # HETATMs have only a couple of atoms (3 for water for example) and they are ok. if (len(r['atoms']) >= 7) or (hetero_flag != " "): try: structure_build.init_residue(r['name'], hetero_flag, r['number'], r['icode']) except PDBConstructionException, message: self._handle_builder_exception(message, r) # Create Atoms for atom in r['atoms']: a = self._parse_atom(atom) if not sum(a['coord']): # e.g. HG of metal bound CYS coords are 0,0,0. continue try: atom_counter += 1 # fullname = name; altloc is empty; structure_build.init_atom(a['name'], a['coord'], a['bfactor'], a['occupancy'], ' ', a['name'], atom_counter, a['element'], hetero_flag) except PDBConstructionException, message: self._handle_builder_exception(message, r) elif len(r['atoms']) < 7: # Terminal Residues for atom in r['atoms']: a = self._parse_atom(atom) if not sum(a['coord']): # e.g. HG of metal bound CYS coords are 0,0,0. continue atom_counter += 1 ter_atom = Atom(a['name'], a['coord'], a['bfactor'], a['occupancy'], ' ', a['name'], atom_counter, a['element'], hetero_flag) if a['name'] in N_TERMINAL_ATOMS: inc_struct = self.structure_builder.get_structure() for model in inc_struct: for chain in model: if chain.id == r['chain']: for residue in chain: # Find First residue matching name if residue.resname == r['name']: residue.add(ter_atom) break elif a['name'] in C_TERMINAL_ATOMS: inc_struct = self.structure_builder.get_structure() c_ter = None for model in inc_struct: for chain in model: if chain.id == r['chain']: for residue in chain: # Find Last residue matching name if residue.resname == r['name']: c_ter = residue if c_ter: c_ter.add(ter_atom)
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Parse atomic data of the XML file.
[ "Parse", "atomic", "data", "of", "the", "XML", "file", "." ]
python
train
sunlightlabs/django-locksmith
locksmith/hub/views.py
https://github.com/sunlightlabs/django-locksmith/blob/eef5b7c25404560aaad50b6e622594f89239b74b/locksmith/hub/views.py#L180-L208
def profile(request): ''' Viewing of signup details and editing of password ''' context = {} if request.method == 'POST': form = PasswordChangeForm(request.user, request.POST) if form.is_valid(): form.save() messages.info(request, 'Password Changed.') else: form = PasswordChangeForm(request.user) key = Key.objects.get(email=request.user.email) #analytics endpoint_q = key.reports.values('api__name', 'endpoint').annotate(calls=Sum('calls')).order_by('-calls') endpoints = [{'endpoint':'.'.join((d['api__name'], d['endpoint'])), 'calls': d['calls']} for d in endpoint_q] date_q = key.reports.values('date').annotate(calls=Sum('calls')).order_by('date') context['endpoints'], context['endpoint_calls'] = _dictlist_to_lists(endpoints, 'endpoint', 'calls') context['timeline'] = date_q context['form'] = form context['key'] = key context['password_is_key'] = request.user.check_password(key.key) return render_to_response('locksmith/profile.html', context, context_instance=RequestContext(request))
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Viewing of signup details and editing of password
[ "Viewing", "of", "signup", "details", "and", "editing", "of", "password" ]
python
train
dnanexus/dx-toolkit
src/python/dxpy/bindings/search.py
https://github.com/dnanexus/dx-toolkit/blob/74befb53ad90fcf902d8983ae6d74580f402d619/src/python/dxpy/bindings/search.py#L73-L108
def _find(api_method, query, limit, return_handler, first_page_size, **kwargs): ''' Takes an API method handler (dxpy.api.find*) and calls it with *query*, and then wraps a generator around its output. Used by the methods below. Note that this function may only be used for /system/find* methods. ''' num_results = 0 if "limit" not in query: query["limit"] = first_page_size while True: resp = api_method(query, **kwargs) by_parent = resp.get('byParent') descriptions = resp.get('describe') def format_result(result): if return_handler: result = dxpy.get_handler(result['id'], project=result.get('project')) if by_parent is not None: return result, by_parent, descriptions else: return result for i in resp["results"]: if num_results == limit: return num_results += 1 yield format_result(i) # set up next query if resp["next"] is not None: query["starting"] = resp["next"] query["limit"] = min(query["limit"]*2, 1000) else: return
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python
train
cloudendpoints/endpoints-management-python
endpoints_management/control/vendor/py3/sched.py
https://github.com/cloudendpoints/endpoints-management-python/blob/ec3c4a330ae9d65738861ce6df4dd6c3cb9f7731/endpoints_management/control/vendor/py3/sched.py#L94-L103
def cancel(self, event): """Remove an event from the queue. This must be presented the ID as returned by enter(). If the event is not in the queue, this raises ValueError. """ with self._lock: self._queue.remove(event) heapq.heapify(self._queue)
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Remove an event from the queue. This must be presented the ID as returned by enter(). If the event is not in the queue, this raises ValueError.
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/frontend/html/notebook/notebookmanager.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/frontend/html/notebook/notebookmanager.py#L268-L276
def new_notebook(self): """Create a new notebook and return its notebook_id.""" path, name = self.increment_filename('Untitled') notebook_id = self.new_notebook_id(name) metadata = current.new_metadata(name=name) nb = current.new_notebook(metadata=metadata) with open(path,'w') as f: current.write(nb, f, u'json') return notebook_id
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Create a new notebook and return its notebook_id.
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python
test
shoebot/shoebot
shoebot/grammar/nodebox.py
https://github.com/shoebot/shoebot/blob/d554c1765c1899fa25727c9fc6805d221585562b/shoebot/grammar/nodebox.py#L432-L439
def transform(self, mode=None): ''' Set the current transform mode. :param mode: CENTER or CORNER''' if mode: self._canvas.mode = mode return self._canvas.mode
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Set the current transform mode. :param mode: CENTER or CORNER
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python
valid
spacetelescope/stsci.tools
lib/stsci/tools/vtor_checks.py
https://github.com/spacetelescope/stsci.tools/blob/9a022503ad24ca54ce83331482dfa3ff6de9f403/lib/stsci/tools/vtor_checks.py#L18-L40
def sigStrToKwArgsDict(checkFuncSig): """ Take a check function signature (string), and parse it to get a dict of the keyword args and their values. """ p1 = checkFuncSig.find('(') p2 = checkFuncSig.rfind(')') assert p1 > 0 and p2 > 0 and p2 > p1, "Invalid signature: "+checkFuncSig argParts = irafutils.csvSplit(checkFuncSig[p1+1:p2], ',', True) argParts = [x.strip() for x in argParts] retval = {} for argPair in argParts: argSpl = argPair.split('=', 1) if len(argSpl) > 1: if argSpl[0] in retval: if isinstance(retval[argSpl[0]], (list,tuple)): retval[argSpl[0]]+=(irafutils.stripQuotes(argSpl[1]),) # 3rd else: # 2nd in, so convert to tuple retval[argSpl[0]] = (retval[argSpl[0]], irafutils.stripQuotes(argSpl[1]),) else: retval[argSpl[0]] = irafutils.stripQuotes(argSpl[1]) # 1st in else: retval[argSpl[0]] = None # eg. found "triggers=, max=6, ..." return retval
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Take a check function signature (string), and parse it to get a dict of the keyword args and their values.
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python
train
cocagne/txdbus
txdbus/marshal.py
https://github.com/cocagne/txdbus/blob/eb424918764b7b93eecd2a4e2e5c2d0b2944407b/txdbus/marshal.py#L221-L240
def validateMemberName(n): """ Verifies that the supplied name is a valid DBus member name. Throws an L{error.MarshallingError} if the format is invalid @type n: C{string} @param n: A DBus member name """ try: if len(n) < 1: raise Exception('Name must be at least one byte in length') if len(n) > 255: raise Exception('Name exceeds maximum length of 255') if n[0].isdigit(): raise Exception('Names may not begin with a digit') if mbr_re.search(n): raise Exception( 'Names contains a character outside the set [A-Za-z0-9_]') except Exception as e: raise MarshallingError('Invalid member name "%s": %s' % (n, str(e)))
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Verifies that the supplied name is a valid DBus member name. Throws an L{error.MarshallingError} if the format is invalid @type n: C{string} @param n: A DBus member name
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python
train
pytroll/satpy
satpy/readers/eps_l1b.py
https://github.com/pytroll/satpy/blob/1f21d20ac686b745fb0da9b4030d139893e066dd/satpy/readers/eps_l1b.py#L291-L394
def get_dataset(self, key, info): """Get calibrated channel data.""" if self.mdrs is None: self._read_all(self.filename) if key.name in ['longitude', 'latitude']: lons, lats = self.get_full_lonlats() if key.name == 'longitude': dataset = create_xarray(lons) else: dataset = create_xarray(lats) elif key.name in ['solar_zenith_angle', 'solar_azimuth_angle', 'satellite_zenith_angle', 'satellite_azimuth_angle']: sun_azi, sun_zen, sat_azi, sat_zen = self.get_full_angles() if key.name == 'solar_zenith_angle': dataset = create_xarray(sun_zen) elif key.name == 'solar_azimuth_angle': dataset = create_xarray(sun_azi) if key.name == 'satellite_zenith_angle': dataset = create_xarray(sat_zen) elif key.name == 'satellite_azimuth_angle': dataset = create_xarray(sat_azi) else: mask = None if key.calibration == 'counts': raise ValueError('calibration=counts is not supported! ' + 'This reader cannot return counts') elif key.calibration not in ['reflectance', 'brightness_temperature', 'radiance']: raise ValueError('calibration type ' + str(key.calibration) + ' is not supported!') if key.name in ['3A', '3a'] and self.three_a_mask is None: self.three_a_mask = ((self["FRAME_INDICATOR"] & 2 ** 16) != 2 ** 16) if key.name in ['3B', '3b'] and self.three_b_mask is None: self.three_b_mask = ((self["FRAME_INDICATOR"] & 2 ** 16) != 0) if key.name not in ["1", "2", "3a", "3A", "3b", "3B", "4", "5"]: LOG.info("Can't load channel in eps_l1b: " + str(key.name)) return if key.name == "1": if key.calibration == 'reflectance': array = radiance_to_refl(self["SCENE_RADIANCES"][:, 0, :], self["CH1_SOLAR_FILTERED_IRRADIANCE"]) else: array = self["SCENE_RADIANCES"][:, 0, :] if key.name == "2": if key.calibration == 'reflectance': array = radiance_to_refl(self["SCENE_RADIANCES"][:, 1, :], self["CH2_SOLAR_FILTERED_IRRADIANCE"]) else: array = self["SCENE_RADIANCES"][:, 1, :] if key.name.lower() == "3a": if key.calibration == 'reflectance': array = radiance_to_refl(self["SCENE_RADIANCES"][:, 2, :], self["CH3A_SOLAR_FILTERED_IRRADIANCE"]) else: array = self["SCENE_RADIANCES"][:, 2, :] mask = np.empty(array.shape, dtype=bool) mask[:, :] = self.three_a_mask[:, np.newaxis] if key.name.lower() == "3b": if key.calibration == 'brightness_temperature': array = radiance_to_bt(self["SCENE_RADIANCES"][:, 2, :], self["CH3B_CENTRAL_WAVENUMBER"], self["CH3B_CONSTANT1"], self["CH3B_CONSTANT2_SLOPE"]) else: array = self["SCENE_RADIANCES"][:, 2, :] mask = np.empty(array.shape, dtype=bool) mask[:, :] = self.three_b_mask[:, np.newaxis] if key.name == "4": if key.calibration == 'brightness_temperature': array = radiance_to_bt(self["SCENE_RADIANCES"][:, 3, :], self["CH4_CENTRAL_WAVENUMBER"], self["CH4_CONSTANT1"], self["CH4_CONSTANT2_SLOPE"]) else: array = self["SCENE_RADIANCES"][:, 3, :] if key.name == "5": if key.calibration == 'brightness_temperature': array = radiance_to_bt(self["SCENE_RADIANCES"][:, 4, :], self["CH5_CENTRAL_WAVENUMBER"], self["CH5_CONSTANT1"], self["CH5_CONSTANT2_SLOPE"]) else: array = self["SCENE_RADIANCES"][:, 4, :] dataset = create_xarray(array) if mask is not None: dataset = dataset.where(~mask) dataset.attrs['platform_name'] = self.platform_name dataset.attrs['sensor'] = self.sensor_name dataset.attrs.update(info) dataset.attrs.update(key.to_dict()) return dataset
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Get calibrated channel data.
[ "Get", "calibrated", "channel", "data", "." ]
python
train
saltstack/salt
salt/states/win_iis.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/states/win_iis.py#L783-L871
def set_app(name, site, settings=None): # pylint: disable=anomalous-backslash-in-string ''' .. versionadded:: 2017.7.0 Set the value of the setting for an IIS web application. .. note:: This function only configures existing app. Params are case sensitive. :param str name: The IIS application. :param str site: The IIS site name. :param str settings: A dictionary of the setting names and their values. Available settings: - ``physicalPath`` - The physical path of the webapp - ``applicationPool`` - The application pool for the webapp - ``userName`` "connectAs" user - ``password`` "connectAs" password for user :rtype: bool Example of usage: .. code-block:: yaml site0-webapp-setting: win_iis.set_app: - name: app0 - site: Default Web Site - settings: userName: domain\\user password: pass physicalPath: c:\inetpub\wwwroot applicationPool: appPool0 ''' # pylint: enable=anomalous-backslash-in-string ret = {'name': name, 'changes': {}, 'comment': str(), 'result': None} if not settings: ret['comment'] = 'No settings to change provided.' ret['result'] = True return ret ret_settings = { 'changes': {}, 'failures': {}, } current_settings = __salt__['win_iis.get_webapp_settings'](name=name, site=site, settings=settings.keys()) for setting in settings: if str(settings[setting]) != str(current_settings[setting]): ret_settings['changes'][setting] = {'old': current_settings[setting], 'new': settings[setting]} if not ret_settings['changes']: ret['comment'] = 'Settings already contain the provided values.' ret['result'] = True return ret elif __opts__['test']: ret['comment'] = 'Settings will be changed.' ret['changes'] = ret_settings return ret __salt__['win_iis.set_webapp_settings'](name=name, site=site, settings=settings) new_settings = __salt__['win_iis.get_webapp_settings'](name=name, site=site, settings=settings.keys()) for setting in settings: if str(settings[setting]) != str(new_settings[setting]): ret_settings['failures'][setting] = {'old': current_settings[setting], 'new': new_settings[setting]} ret_settings['changes'].pop(setting, None) if ret_settings['failures']: ret['comment'] = 'Some settings failed to change.' ret['changes'] = ret_settings ret['result'] = False else: ret['comment'] = 'Set settings to contain the provided values.' ret['changes'] = ret_settings['changes'] ret['result'] = True return ret
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.. versionadded:: 2017.7.0 Set the value of the setting for an IIS web application. .. note:: This function only configures existing app. Params are case sensitive. :param str name: The IIS application. :param str site: The IIS site name. :param str settings: A dictionary of the setting names and their values. Available settings: - ``physicalPath`` - The physical path of the webapp - ``applicationPool`` - The application pool for the webapp - ``userName`` "connectAs" user - ``password`` "connectAs" password for user :rtype: bool Example of usage: .. code-block:: yaml site0-webapp-setting: win_iis.set_app: - name: app0 - site: Default Web Site - settings: userName: domain\\user password: pass physicalPath: c:\inetpub\wwwroot applicationPool: appPool0
[ "..", "versionadded", "::", "2017", ".", "7", ".", "0" ]
python
train
authomatic/authomatic
authomatic/providers/oauth2.py
https://github.com/authomatic/authomatic/blob/90a9ce60cc405ae8a2bf5c3713acd5d78579a04e/authomatic/providers/oauth2.py#L115-L215
def create_request_elements( cls, request_type, credentials, url, method='GET', params=None, headers=None, body='', secret=None, redirect_uri='', scope='', csrf='', user_state='' ): """ Creates |oauth2| request elements. """ headers = headers or {} params = params or {} consumer_key = credentials.consumer_key or '' consumer_secret = credentials.consumer_secret or '' token = credentials.token or '' refresh_token = credentials.refresh_token or credentials.token or '' # Separate url base and query parameters. url, base_params = cls._split_url(url) # Add params extracted from URL. params.update(dict(base_params)) if request_type == cls.USER_AUTHORIZATION_REQUEST_TYPE: # User authorization request. # TODO: Raise error for specific message for each missing argument. if consumer_key and redirect_uri and ( csrf or not cls.supports_csrf_protection): params['client_id'] = consumer_key params['redirect_uri'] = redirect_uri params['scope'] = scope if cls.supports_user_state: params['state'] = base64.urlsafe_b64encode( json.dumps( {"csrf": csrf, "user_state": user_state} ).encode('utf-8') ) else: params['state'] = csrf params['response_type'] = 'code' # Add authorization header headers.update(cls._authorization_header(credentials)) else: raise OAuth2Error( 'Credentials with valid consumer_key and arguments ' 'redirect_uri, scope and state are required to create ' 'OAuth 2.0 user authorization request elements!') elif request_type == cls.ACCESS_TOKEN_REQUEST_TYPE: # Access token request. if consumer_key and consumer_secret: params['code'] = token params['client_id'] = consumer_key params['client_secret'] = consumer_secret params['redirect_uri'] = redirect_uri params['grant_type'] = 'authorization_code' # TODO: Check whether all providers accept it headers.update(cls._authorization_header(credentials)) else: raise OAuth2Error( 'Credentials with valid token, consumer_key, ' 'consumer_secret and argument redirect_uri are required ' 'to create OAuth 2.0 access token request elements!') elif request_type == cls.REFRESH_TOKEN_REQUEST_TYPE: # Refresh access token request. if refresh_token and consumer_key and consumer_secret: params['refresh_token'] = refresh_token params['client_id'] = consumer_key params['client_secret'] = consumer_secret params['grant_type'] = 'refresh_token' else: raise OAuth2Error( 'Credentials with valid refresh_token, consumer_key, ' 'consumer_secret are required to create OAuth 2.0 ' 'refresh token request elements!') elif request_type == cls.PROTECTED_RESOURCE_REQUEST_TYPE: # Protected resource request. # Add Authorization header. See: # http://tools.ietf.org/html/rfc6749#section-7.1 if credentials.token_type == cls.BEARER: # http://tools.ietf.org/html/rfc6750#section-2.1 headers.update( {'Authorization': 'Bearer {0}'.format(credentials.token)}) elif token: params['access_token'] = token else: raise OAuth2Error( 'Credentials with valid token are required to create ' 'OAuth 2.0 protected resources request elements!') request_elements = core.RequestElements( url, method, params, headers, body) return cls._x_request_elements_filter( request_type, request_elements, credentials)
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Creates |oauth2| request elements.
[ "Creates", "|oauth2|", "request", "elements", "." ]
python
test
bitesofcode/projexui
projexui/widgets/xviewwidget/xview.py
https://github.com/bitesofcode/projexui/blob/f18a73bec84df90b034ca69b9deea118dbedfc4d/projexui/widgets/xviewwidget/xview.py#L492-L502
def setMaximumWidth(self, width): """ Sets the maximum width value to the inputed width and emits the \ sizeConstraintChanged signal. :param width | <int> """ super(XView, self).setMaximumWidth(width) if ( not self.signalsBlocked() ): self.sizeConstraintChanged.emit()
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Sets the maximum width value to the inputed width and emits the \ sizeConstraintChanged signal. :param width | <int>
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/IPython/parallel/controller/scheduler.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/IPython/parallel/controller/scheduler.py#L477-L531
def maybe_run(self, job): """check location dependencies, and run if they are met.""" msg_id = job.msg_id self.log.debug("Attempting to assign task %s", msg_id) if not self.targets: # no engines, definitely can't run return False if job.follow or job.targets or job.blacklist or self.hwm: # we need a can_run filter def can_run(idx): # check hwm if self.hwm and self.loads[idx] == self.hwm: return False target = self.targets[idx] # check blacklist if target in job.blacklist: return False # check targets if job.targets and target not in job.targets: return False # check follow return job.follow.check(self.completed[target], self.failed[target]) indices = filter(can_run, range(len(self.targets))) if not indices: # couldn't run if job.follow.all: # check follow for impossibility dests = set() relevant = set() if job.follow.success: relevant = self.all_completed if job.follow.failure: relevant = relevant.union(self.all_failed) for m in job.follow.intersection(relevant): dests.add(self.destinations[m]) if len(dests) > 1: self.depending[msg_id] = job self.fail_unreachable(msg_id) return False if job.targets: # check blacklist+targets for impossibility job.targets.difference_update(job.blacklist) if not job.targets or not job.targets.intersection(self.targets): self.depending[msg_id] = job self.fail_unreachable(msg_id) return False return False else: indices = None self.submit_task(job, indices) return True
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check location dependencies, and run if they are met.
[ "check", "location", "dependencies", "and", "run", "if", "they", "are", "met", "." ]
python
test
wmayner/pyphi
pyphi/actual.py
https://github.com/wmayner/pyphi/blob/deeca69a084d782a6fde7bf26f59e93b593c5d77/pyphi/actual.py#L366-L383
def potential_purviews(self, direction, mechanism, purviews=False): """Return all purviews that could belong to the |MIC|/|MIE|. Filters out trivially-reducible purviews. Args: direction (str): Either |CAUSE| or |EFFECT|. mechanism (tuple[int]): The mechanism of interest. Keyword Args: purviews (tuple[int]): Optional subset of purviews of interest. """ system = self.system[direction] return [ purview for purview in system.potential_purviews( direction, mechanism, purviews) if set(purview).issubset(self.purview_indices(direction)) ]
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Return all purviews that could belong to the |MIC|/|MIE|. Filters out trivially-reducible purviews. Args: direction (str): Either |CAUSE| or |EFFECT|. mechanism (tuple[int]): The mechanism of interest. Keyword Args: purviews (tuple[int]): Optional subset of purviews of interest.
[ "Return", "all", "purviews", "that", "could", "belong", "to", "the", "|MIC|", "/", "|MIE|", "." ]
python
train
saltstack/salt
salt/modules/win_file.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/win_file.py#L1110-L1161
def symlink(src, link): ''' Create a symbolic link to a file This is only supported with Windows Vista or later and must be executed by a user with the SeCreateSymbolicLink privilege. The behavior of this function matches the Unix equivalent, with one exception - invalid symlinks cannot be created. The source path must exist. If it doesn't, an error will be raised. Args: src (str): The path to a file or directory link (str): The path to the link Returns: bool: True if successful, otherwise False CLI Example: .. code-block:: bash salt '*' file.symlink /path/to/file /path/to/link ''' # When Python 3.2 or later becomes the minimum version, this function can be # replaced with the built-in os.symlink function, which supports Windows. if sys.getwindowsversion().major < 6: raise SaltInvocationError('Symlinks are only supported on Windows Vista or later.') if not os.path.exists(src): raise SaltInvocationError('The given source path does not exist.') if not os.path.isabs(src): raise SaltInvocationError('File path must be absolute.') # ensure paths are using the right slashes src = os.path.normpath(src) link = os.path.normpath(link) is_dir = os.path.isdir(src) try: win32file.CreateSymbolicLink(link, src, int(is_dir)) return True except pywinerror as exc: raise CommandExecutionError( 'Could not create \'{0}\' - [{1}] {2}'.format( link, exc.winerror, exc.strerror ) )
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Create a symbolic link to a file This is only supported with Windows Vista or later and must be executed by a user with the SeCreateSymbolicLink privilege. The behavior of this function matches the Unix equivalent, with one exception - invalid symlinks cannot be created. The source path must exist. If it doesn't, an error will be raised. Args: src (str): The path to a file or directory link (str): The path to the link Returns: bool: True if successful, otherwise False CLI Example: .. code-block:: bash salt '*' file.symlink /path/to/file /path/to/link
[ "Create", "a", "symbolic", "link", "to", "a", "file" ]
python
train
Chilipp/docrep
docrep/__init__.py
https://github.com/Chilipp/docrep/blob/637971f76e1a6e1c70e36dcd1b02bbc37ba02487/docrep/__init__.py#L641-L727
def keep_params(self, base_key, *params): """ Method to keep only specific parameters from a parameter documentation. This method extracts the given `param` from the `base_key` item in the :attr:`params` dictionary and creates a new item with the original documentation with only the description of the param. This method works for ``'Parameters'`` like sections. The new docstring with the selected parts will be accessible as ``base_key + '.' + '|'.join(params)``, e.g. ``'original_key.param1|param2'`` Parameters ---------- base_key: str key in the :attr:`params` dictionary ``*params`` str. Parameter identifier of which the documentations shall be in the new section See Also -------- keep_types, delete_params Examples -------- To extract just two parameters from a function and reuse their docstrings, you can type:: >>> from docrep import DocstringProcessor >>> d = DocstringProcessor() >>> @d.get_sectionsf('do_something') ... def do_something(a=1, b=2, c=3): ... ''' ... That's %(doc_key)s ... ... Parameters ... ---------- ... a: int, optional ... A dummy parameter description ... b: int, optional ... A second dummy parameter that will be excluded ... c: float, optional ... A third parameter''' ... print(a) >>> d.keep_params('do_something.parameters', 'a', 'c') >>> @d.dedent ... def do_less(a=1, c=4): ... ''' ... My second function with only `a` and `c` ... ... Parameters ... ---------- ... %(do_something.parameters.a|c)s''' ... pass >>> print(do_less.__doc__) My second function with only `a` and `c` <BLANKLINE> Parameters ---------- a: int, optional A dummy parameter description c: float, optional A third parameter Equivalently, you can use the :meth:`delete_params` method to remove parameters:: >>> d.delete_params('do_something.parameters', 'b') >>> @d.dedent ... def do_less(a=1, c=4): ... ''' ... My second function with only `a` and `c` ... ... Parameters ... ---------- ... %(do_something.parameters.no_b)s''' ... pass """ self.params[base_key + '.' + '|'.join(params)] = self.keep_params_s( self.params[base_key], params)
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Method to keep only specific parameters from a parameter documentation. This method extracts the given `param` from the `base_key` item in the :attr:`params` dictionary and creates a new item with the original documentation with only the description of the param. This method works for ``'Parameters'`` like sections. The new docstring with the selected parts will be accessible as ``base_key + '.' + '|'.join(params)``, e.g. ``'original_key.param1|param2'`` Parameters ---------- base_key: str key in the :attr:`params` dictionary ``*params`` str. Parameter identifier of which the documentations shall be in the new section See Also -------- keep_types, delete_params Examples -------- To extract just two parameters from a function and reuse their docstrings, you can type:: >>> from docrep import DocstringProcessor >>> d = DocstringProcessor() >>> @d.get_sectionsf('do_something') ... def do_something(a=1, b=2, c=3): ... ''' ... That's %(doc_key)s ... ... Parameters ... ---------- ... a: int, optional ... A dummy parameter description ... b: int, optional ... A second dummy parameter that will be excluded ... c: float, optional ... A third parameter''' ... print(a) >>> d.keep_params('do_something.parameters', 'a', 'c') >>> @d.dedent ... def do_less(a=1, c=4): ... ''' ... My second function with only `a` and `c` ... ... Parameters ... ---------- ... %(do_something.parameters.a|c)s''' ... pass >>> print(do_less.__doc__) My second function with only `a` and `c` <BLANKLINE> Parameters ---------- a: int, optional A dummy parameter description c: float, optional A third parameter Equivalently, you can use the :meth:`delete_params` method to remove parameters:: >>> d.delete_params('do_something.parameters', 'b') >>> @d.dedent ... def do_less(a=1, c=4): ... ''' ... My second function with only `a` and `c` ... ... Parameters ... ---------- ... %(do_something.parameters.no_b)s''' ... pass
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python
train
MagicStack/asyncpg
asyncpg/connresource.py
https://github.com/MagicStack/asyncpg/blob/92c2d81256a1efd8cab12c0118d74ccd1c18131b/asyncpg/connresource.py#L14-L22
def guarded(meth): """A decorator to add a sanity check to ConnectionResource methods.""" @functools.wraps(meth) def _check(self, *args, **kwargs): self._check_conn_validity(meth.__name__) return meth(self, *args, **kwargs) return _check
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A decorator to add a sanity check to ConnectionResource methods.
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python
train
pylp/pylp
pylp/utils/paths.py
https://github.com/pylp/pylp/blob/7ebaa55fbaf61cb8175f211dd41ef2928c22d4d4/pylp/utils/paths.py#L13-L19
def make_readable_path(path): """Make a path more "readable""" home = os.path.expanduser("~") if path.startswith(home): path = "~" + path[len(home):] return path
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Make a path more "readable
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python
train
genialis/resolwe
resolwe/flow/models/utils.py
https://github.com/genialis/resolwe/blob/f7bb54932c81ec0cfc5b5e80d238fceaeaa48d86/resolwe/flow/models/utils.py#L235-L292
def _hydrate_values(output, output_schema, data): """Hydrate basic:file and basic:json values. Find fields with basic:file type and assign a full path to the file. Find fields with basic:json type and assign a JSON object from storage. """ def hydrate_path(file_name): """Hydrate file paths.""" from resolwe.flow.managers import manager class HydratedPath(str): """String wrapper, which also stores the original filename.""" __slots__ = ('data_id', 'file_name') def __new__(cls, value=''): """Initialize hydrated path.""" hydrated = str.__new__(cls, value) hydrated.data_id = data.id hydrated.file_name = file_name return hydrated return HydratedPath(manager.get_executor().resolve_data_path(data, file_name)) def hydrate_storage(storage_id): """Hydrate storage fields.""" from .storage import LazyStorageJSON # Prevent circular import. return LazyStorageJSON(pk=storage_id) for field_schema, fields in iterate_fields(output, output_schema): name = field_schema['name'] value = fields[name] if 'type' in field_schema: if field_schema['type'].startswith('basic:file:'): value['file'] = hydrate_path(value['file']) value['refs'] = [hydrate_path(ref) for ref in value.get('refs', [])] elif field_schema['type'].startswith('list:basic:file:'): for obj in value: obj['file'] = hydrate_path(obj['file']) obj['refs'] = [hydrate_path(ref) for ref in obj.get('refs', [])] if field_schema['type'].startswith('basic:dir:'): value['dir'] = hydrate_path(value['dir']) value['refs'] = [hydrate_path(ref) for ref in value.get('refs', [])] elif field_schema['type'].startswith('list:basic:dir:'): for obj in value: obj['dir'] = hydrate_path(obj['dir']) obj['refs'] = [hydrate_path(ref) for ref in obj.get('refs', [])] elif field_schema['type'].startswith('basic:json:'): fields[name] = hydrate_storage(value) elif field_schema['type'].startswith('list:basic:json:'): fields[name] = [hydrate_storage(storage_id) for storage_id in value]
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Hydrate basic:file and basic:json values. Find fields with basic:file type and assign a full path to the file. Find fields with basic:json type and assign a JSON object from storage.
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python
train
mitsei/dlkit
dlkit/json_/resource/objects.py
https://github.com/mitsei/dlkit/blob/445f968a175d61c8d92c0f617a3c17dc1dc7c584/dlkit/json_/resource/objects.py#L192-L202
def get_group_metadata(self): """Gets the metadata for a group. return: (osid.Metadata) - metadata for the group *compliance: mandatory -- This method must be implemented.* """ # Implemented from template for osid.resource.ResourceForm.get_group_metadata_template metadata = dict(self._mdata['group']) metadata.update({'existing_boolean_values': self._my_map['group']}) return Metadata(**metadata)
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Gets the metadata for a group. return: (osid.Metadata) - metadata for the group *compliance: mandatory -- This method must be implemented.*
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python
train
jobovy/galpy
galpy/potential/MovingObjectPotential.py
https://github.com/jobovy/galpy/blob/9c5b9fe65d58835624dffe432be282060918ee08/galpy/potential/MovingObjectPotential.py#L63-L83
def _evaluate(self,R,z,phi=0.,t=0.): """ NAME: _evaluate PURPOSE: evaluate the potential at R,z, phi INPUT: R - Galactocentric cylindrical radius z - vertical height phi - azimuth t - time OUTPUT: Phi(R,z,phi) HISTORY: 2011-04-10 - Started - Bovy (NYU) 2018-10-18 - Updated for general object potential - James Lane (UofT) """ #Cylindrical distance Rdist = _cylR(R,phi,self._orb.R(t),self._orb.phi(t)) #Evaluate potential return evaluatePotentials( self._pot, Rdist, self._orb.z(t)-z, use_physical=False)
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NAME: _evaluate PURPOSE: evaluate the potential at R,z, phi INPUT: R - Galactocentric cylindrical radius z - vertical height phi - azimuth t - time OUTPUT: Phi(R,z,phi) HISTORY: 2011-04-10 - Started - Bovy (NYU) 2018-10-18 - Updated for general object potential - James Lane (UofT)
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python
train
aaugustin/websockets
src/websockets/http.py
https://github.com/aaugustin/websockets/blob/17b3f47549b6f752a1be07fa1ba3037cb59c7d56/src/websockets/http.py#L187-L204
async def read_line(stream: asyncio.StreamReader) -> bytes: """ Read a single line from ``stream``. ``stream`` is an :class:`~asyncio.StreamReader`. Return :class:`bytes` without CRLF. """ # Security: this is bounded by the StreamReader's limit (default = 32 KiB). line = await stream.readline() # Security: this guarantees header values are small (hard-coded = 4 KiB) if len(line) > MAX_LINE: raise ValueError("Line too long") # Not mandatory but safe - https://tools.ietf.org/html/rfc7230#section-3.5 if not line.endswith(b"\r\n"): raise ValueError("Line without CRLF") return line[:-2]
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Read a single line from ``stream``. ``stream`` is an :class:`~asyncio.StreamReader`. Return :class:`bytes` without CRLF.
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python
train
MolSSI-BSE/basis_set_exchange
basis_set_exchange/cli/bse_handlers.py
https://github.com/MolSSI-BSE/basis_set_exchange/blob/e79110aaeb65f392ed5032420322dee3336948f7/basis_set_exchange/cli/bse_handlers.py#L52-L61
def _bse_cli_list_roles(args): '''Handles the list-roles subcommand''' all_roles = api.get_roles() if args.no_description: liststr = all_roles.keys() else: liststr = format_columns(all_roles.items()) return '\n'.join(liststr)
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Handles the list-roles subcommand
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python
train
IdentityPython/pysaml2
src/saml2/mcache.py
https://github.com/IdentityPython/pysaml2/blob/d3aa78eeb7d37c12688f783cb4db1c7263a14ad6/src/saml2/mcache.py#L153-L174
def active(self, subject_id, entity_id): """ Returns the status of assertions from a specific entity_id. :param subject_id: The ID of the subject :param entity_id: The entity ID of the entity_id of the assertion :return: True or False depending on if the assertion is still valid or not. """ try: (timestamp, info) = self._cache.get(_key(subject_id, entity_id)) except ValueError: return False except TypeError: return False # if not info: # return False try: return time_util.not_on_or_after(timestamp) except ToOld: return False
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Returns the status of assertions from a specific entity_id. :param subject_id: The ID of the subject :param entity_id: The entity ID of the entity_id of the assertion :return: True or False depending on if the assertion is still valid or not.
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python
train
nion-software/nionswift
nion/swift/model/Symbolic.py
https://github.com/nion-software/nionswift/blob/d43693eaf057b8683b9638e575000f055fede452/nion/swift/model/Symbolic.py#L886-L891
def unbind(self): """Unlisten and close each bound item.""" for variable in self.variables: self.__unbind_variable(variable) for result in self.results: self.__unbind_result(result)
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Unlisten and close each bound item.
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python
train
swift-nav/libsbp
python/sbp/client/drivers/cdc_driver.py
https://github.com/swift-nav/libsbp/blob/5a950608506b23e31b73ef7065da905b646055c1/python/sbp/client/drivers/cdc_driver.py#L27-L48
def read(self, size): """ Read wrapper. Parameters ---------- size : int Number of bytes to read. """ try: return_val = self.handle.read(size) if return_val == '': print() print("Piksi disconnected") print() raise IOError return return_val except OSError: print() print("Piksi disconnected") print() raise IOError
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Read wrapper. Parameters ---------- size : int Number of bytes to read.
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python
train
stephrdev/django-formwizard
formwizard/views.py
https://github.com/stephrdev/django-formwizard/blob/7b35165f0340aae4e8302d5b05b0cb443f6c9904/formwizard/views.py#L303-L325
def render_done(self, form, **kwargs): """ This method gets called when all forms passed. The method should also re-validate all steps to prevent manipulation. If any form don't validate, `render_revalidation_failure` should get called. If everything is fine call `done`. """ final_form_list = [] # walk through the form list and try to validate the data again. for form_key in self.get_form_list(): form_obj = self.get_form(step=form_key, data=self.storage.get_step_data(form_key), files=self.storage.get_step_files(form_key)) if not form_obj.is_valid(): return self.render_revalidation_failure(form_key, form_obj, **kwargs) final_form_list.append(form_obj) # render the done view and reset the wizard before returning the # response. This is needed to prevent from rendering done with the # same data twice. done_response = self.done(final_form_list, **kwargs) self.storage.reset() return done_response
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python
train
Azure/azure-cli-extensions
src/storage-preview/azext_storage_preview/_validators.py
https://github.com/Azure/azure-cli-extensions/blob/3d4854205b0f0d882f688cfa12383d14506c2e35/src/storage-preview/azext_storage_preview/_validators.py#L388-L398
def resource_type_type(loader): """ Returns a function which validates that resource types string contains only a combination of service, container, and object. Their shorthand representations are s, c, and o. """ def impl(string): t_resources = loader.get_models('common.models#ResourceTypes') if set(string) - set("sco"): raise ValueError return t_resources(_str=''.join(set(string))) return impl
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Returns a function which validates that resource types string contains only a combination of service, container, and object. Their shorthand representations are s, c, and o.
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python
train
softlayer/softlayer-python
SoftLayer/CLI/block/lun.py
https://github.com/softlayer/softlayer-python/blob/9f181be08cc3668353b05a6de0cb324f52cff6fa/SoftLayer/CLI/block/lun.py#L14-L36
def cli(env, volume_id, lun_id): """Set the LUN ID on an existing block storage volume. The LUN ID only takes effect during the Host Authorization process. It is recommended (but not necessary) to de-authorize all hosts before using this method. See `block access-revoke`. VOLUME_ID - the volume ID on which to set the LUN ID. LUN_ID - recommended range is an integer between 0 and 255. Advanced users can use an integer between 0 and 4095. """ block_storage_manager = SoftLayer.BlockStorageManager(env.client) res = block_storage_manager.create_or_update_lun_id(volume_id, lun_id) if 'value' in res and lun_id == res['value']: click.echo( 'Block volume with id %s is reporting LUN ID %s' % (res['volumeId'], res['value'])) else: click.echo( 'Failed to confirm the new LUN ID on volume %s' % (volume_id))
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Set the LUN ID on an existing block storage volume. The LUN ID only takes effect during the Host Authorization process. It is recommended (but not necessary) to de-authorize all hosts before using this method. See `block access-revoke`. VOLUME_ID - the volume ID on which to set the LUN ID. LUN_ID - recommended range is an integer between 0 and 255. Advanced users can use an integer between 0 and 4095.
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python
train
zenodo/zenodo-accessrequests
zenodo_accessrequests/models.py
https://github.com/zenodo/zenodo-accessrequests/blob/ce2cf3f1425d02ba4f3ad3202cfca43a1892558a/zenodo_accessrequests/models.py#L360-L369
def create_secret_link(self, title, description=None, expires_at=None): """Create a secret link from request.""" self.link = SecretLink.create( title, self.receiver, extra_data=dict(recid=self.recid), description=description, expires_at=expires_at, ) return self.link
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Create a secret link from request.
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python
test
yunojuno/elasticsearch-django
elasticsearch_django/settings.py
https://github.com/yunojuno/elasticsearch-django/blob/e8d98d32bcd77f1bedb8f1a22b6523ca44ffd489/elasticsearch_django/settings.py#L29-L34
def get_setting(key, *default): """Return specific search setting from Django conf.""" if default: return get_settings().get(key, default[0]) else: return get_settings()[key]
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Return specific search setting from Django conf.
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python
train
ask/carrot
carrot/backends/queue.py
https://github.com/ask/carrot/blob/5889a25cd2e274642071c9bba39772f4b3e3d9da/carrot/backends/queue.py#L33-L45
def get(self, *args, **kwargs): """Get the next waiting message from the queue. :returns: A :class:`Message` instance, or ``None`` if there is no messages waiting. """ if not mqueue.qsize(): return None message_data, content_type, content_encoding = mqueue.get() return self.Message(backend=self, body=message_data, content_type=content_type, content_encoding=content_encoding)
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Get the next waiting message from the queue. :returns: A :class:`Message` instance, or ``None`` if there is no messages waiting.
[ "Get", "the", "next", "waiting", "message", "from", "the", "queue", "." ]
python
train
swharden/PyOriginTools
PyOriginTools/highlevel.py
https://github.com/swharden/PyOriginTools/blob/536fb8e11234ffdc27e26b1800e0358179ca7d26/PyOriginTools/highlevel.py#L227-L254
def getSheet(book=None,sheet=None): """returns the pyorigin object for a sheet.""" # figure out what book to use if book and not book.lower() in [x.lower() for x in bookNames()]: print("book %s doesn't exist"%book) return if book is None: book=activeBook().lower() if book is None: print("no book given or selected") return # figure out what sheet to use if sheet and not sheet.lower() in [x.lower() for x in sheetNames(book)]: print("sheet %s doesn't exist"%sheet) return if sheet is None: sheet=activeSheet().lower() if sheet is None: return("no sheet given or selected") print # by now, we know the book/sheet exists and can be found for poSheet in PyOrigin.WorksheetPages(book).Layers(): if poSheet.GetName().lower()==sheet.lower(): return poSheet return False
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returns the pyorigin object for a sheet.
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python
train
PmagPy/PmagPy
pmagpy/contribution_builder.py
https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/pmagpy/contribution_builder.py#L1689-L1712
def drop_stub_rows(self, ignore_cols=('specimen', 'sample', 'software_packages', 'num')): """ Drop self.df rows that have only null values, ignoring certain columns. Parameters ---------- ignore_cols : list-like list of column names to ignore for Returns --------- self.df : pandas DataFrame """ # ignore citations if they just say 'This study' if 'citations' in self.df.columns: if list(self.df['citations'].unique()) == ['This study']: ignore_cols = ignore_cols + ('citations',) drop_cols = self.df.columns.difference(ignore_cols) self.df.dropna(axis='index', subset=drop_cols, how='all', inplace=True) return self.df
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Drop self.df rows that have only null values, ignoring certain columns. Parameters ---------- ignore_cols : list-like list of column names to ignore for Returns --------- self.df : pandas DataFrame
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python
train
econ-ark/HARK
HARK/utilities.py
https://github.com/econ-ark/HARK/blob/3d184153a189e618a87c9540df1cd12044039cc5/HARK/utilities.py#L259-L279
def CRRAutility_invP(u, gam): ''' Evaluates the derivative of the inverse of the CRRA utility function (with risk aversion parameter gam) at a given utility level u. Parameters ---------- u : float Utility value gam : float Risk aversion Returns ------- (unnamed) : float Marginal consumption corresponding to given utility value ''' if gam == 1: return np.exp(u) else: return( ((1.0-gam)*u)**(gam/(1.0-gam)) )
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Evaluates the derivative of the inverse of the CRRA utility function (with risk aversion parameter gam) at a given utility level u. Parameters ---------- u : float Utility value gam : float Risk aversion Returns ------- (unnamed) : float Marginal consumption corresponding to given utility value
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python
train
AkihikoITOH/capybara
capybara/virtualenv/lib/python2.7/site-packages/lxml/html/diff.py
https://github.com/AkihikoITOH/capybara/blob/e86c2173ea386654f4ae061148e8fbe3f25e715c/capybara/virtualenv/lib/python2.7/site-packages/lxml/html/diff.py#L100-L113
def compress_tokens(tokens): """ Combine adjacent tokens when there is no HTML between the tokens, and they share an annotation """ result = [tokens[0]] for tok in tokens[1:]: if (not result[-1].post_tags and not tok.pre_tags and result[-1].annotation == tok.annotation): compress_merge_back(result, tok) else: result.append(tok) return result
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Combine adjacent tokens when there is no HTML between the tokens, and they share an annotation
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python
test
SeattleTestbed/seash
seash_modules.py
https://github.com/SeattleTestbed/seash/blob/40f9d2285662ff8b61e0468b4196acee089b273b/seash_modules.py#L598-L608
def _ensure_module_folder_exists(): """ Checks to see if the module folder exists. If it does not, create it. If there is an existing file with the same name, we raise a RuntimeError. """ if not os.path.isdir(MODULES_FOLDER_PATH): try: os.mkdir(MODULES_FOLDER_PATH) except OSError, e: if "file already exists" in str(e): raise RuntimeError("Could not create modules folder: file exists with the same name")
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Checks to see if the module folder exists. If it does not, create it. If there is an existing file with the same name, we raise a RuntimeError.
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python
train
TheHive-Project/Cortex-Analyzers
analyzers/Malpedia/malpedia_analyzer.py
https://github.com/TheHive-Project/Cortex-Analyzers/blob/8dae6a8c4cf9af5554ae8c844985c4b44d4bd4bf/analyzers/Malpedia/malpedia_analyzer.py#L58-L92
def check(self, file): """ Checks a given file against all available yara rules :param file: Path to file :type file:str :returns: Python list with matched rules info :rtype: list """ result = [] all_matches = [] for filerules in os.listdir(self.rulepaths): try: rule = yara.compile(os.path.join(self.rulepaths, filerules)) except yara.SyntaxError: continue matches = rule.match(file) if len(matches) > 0: for rulem in matches: rule_family = "_".join([x for x in rulem.rule.replace("_", ".", 1).split("_")[:-1]]) if rule_family not in all_matches: all_matches.append(rule_family) for rule_family in all_matches: rules_info_txt = requests.get('{}/family/{}'.format(self.baseurl, rule_family), auth=HTTPBasicAuth(self.user, self.pwd)) rules_info_json = json.loads(rules_info_txt.text) result.append({ 'family': rule_family, 'common_name': rules_info_json['common_name'], 'description': rules_info_json['description'], 'attribution': rules_info_json['attribution'], 'alt_names': rules_info_json['alt_names'], 'urls': rules_info_json['urls'] }) return result
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Checks a given file against all available yara rules :param file: Path to file :type file:str :returns: Python list with matched rules info :rtype: list
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python
train
wummel/patool
patoolib/programs/rzip.py
https://github.com/wummel/patool/blob/d7e64d9fd60faaa4b3f824bd97c43ce59b185c40/patoolib/programs/rzip.py#L19-L26
def extract_rzip (archive, compression, cmd, verbosity, interactive, outdir): """Extract an RZIP archive.""" cmdlist = [cmd, '-d', '-k'] if verbosity > 1: cmdlist.append('-v') outfile = util.get_single_outfile(outdir, archive) cmdlist.extend(["-o", outfile, archive]) return cmdlist
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Extract an RZIP archive.
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python
train
aboSamoor/polyglot
polyglot/__main__.py
https://github.com/aboSamoor/polyglot/blob/d0d2aa8d06cec4e03bd96618ae960030f7069a17/polyglot/__main__.py#L68-L76
def transliterate(args): """Transliterate words according to the target language.""" t = Transliterator(source_lang=args.lang, target_lang=args.target) for l in args.input: words = l.strip().split() line_annotations = [u"{:<16}{:<16}".format(w, t.transliterate(w)) for w in words] _print(u"\n".join(line_annotations)) _print(u"")
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Transliterate words according to the target language.
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python
train
ArchiveTeam/wpull
wpull/network/pool.py
https://github.com/ArchiveTeam/wpull/blob/ddf051aa3322479325ba20aa778cb2cb97606bf5/wpull/network/pool.py#L251-L272
def session(self, host: str, port: int, use_ssl: bool=False): '''Return a context manager that returns a connection. Usage:: session = yield from connection_pool.session('example.com', 80) with session as connection: connection.write(b'blah') connection.close() Coroutine. ''' connection = yield from self.acquire(host, port, use_ssl) @contextlib.contextmanager def context_wrapper(): try: yield connection finally: self.no_wait_release(connection) return context_wrapper()
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Return a context manager that returns a connection. Usage:: session = yield from connection_pool.session('example.com', 80) with session as connection: connection.write(b'blah') connection.close() Coroutine.
[ "Return", "a", "context", "manager", "that", "returns", "a", "connection", "." ]
python
train
gholt/swiftly
swiftly/cli/cli.py
https://github.com/gholt/swiftly/blob/5bcc1c65323b1caf1f85adbefd9fc4988c072149/swiftly/cli/cli.py#L433-L458
def _resolve_option(self, options, option_name, section_name): """Resolves an option value into options. Sets options.<option_name> to a resolved value. Any value already in options overrides a value in os.environ which overrides self.context.conf. :param options: The options instance as returned by optparse. :param option_name: The name of the option, such as ``auth_url``. :param section_name: The name of the section, such as ``swiftly``. """ if getattr(options, option_name, None) is not None: return if option_name.startswith(section_name + '_'): environ_name = option_name.upper() conf_name = option_name[len(section_name) + 1:] else: environ_name = (section_name + '_' + option_name).upper() conf_name = option_name setattr( options, option_name, os.environ.get( environ_name, (self.context.conf.get(section_name, {})).get(conf_name)))
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Resolves an option value into options. Sets options.<option_name> to a resolved value. Any value already in options overrides a value in os.environ which overrides self.context.conf. :param options: The options instance as returned by optparse. :param option_name: The name of the option, such as ``auth_url``. :param section_name: The name of the section, such as ``swiftly``.
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python
test
campbellr/smashrun-client
smashrun/client.py
https://github.com/campbellr/smashrun-client/blob/2522cb4d0545cf482a49a9533f12aac94c5aecdc/smashrun/client.py#L129-L138
def get_splits(self, id_num, unit='mi'): """Return the splits of the activity with the given id. :param unit: The unit to use for splits. May be one of 'mi' or 'km'. """ url = self._build_url('my', 'activities', id_num, 'splits', unit) return self._json(url)
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Return the splits of the activity with the given id. :param unit: The unit to use for splits. May be one of 'mi' or 'km'.
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python
train
vvangelovski/django-audit-log
audit_log/models/managers.py
https://github.com/vvangelovski/django-audit-log/blob/f1bee75360a67390fbef67c110e9a245b41ebb92/audit_log/models/managers.py#L128-L186
def copy_fields(self, model): """ Creates copies of the fields we are keeping track of for the provided model, returning a dictionary mapping field name to a copied field object. """ fields = {'__module__' : model.__module__} for field in model._meta.fields: if not field.name in self._exclude: field = copy.deepcopy(field) if isinstance(field, models.AutoField): #we replace the AutoField of the original model #with an IntegerField because a model can #have only one autofield. field.__class__ = models.IntegerField if field.primary_key: field.serialize = True #OneToOne fields should really be tracked #as ForeignKey fields if isinstance(field, models.OneToOneField): field.__class__ = models.ForeignKey if field.primary_key or field.unique: #unique fields of the original model #can not be guaranteed to be unique #in the audit log entry but they #should still be indexed for faster lookups. field.primary_key = False field._unique = False field.db_index = True if field.remote_field and field.remote_field.related_name: field.remote_field.related_name = '_auditlog_{}_{}'.format( model._meta.model_name, field.remote_field.related_name ) elif field.remote_field: try: if field.remote_field.get_accessor_name(): field.remote_field.related_name = '_auditlog_{}_{}'.format( model._meta.model_name, field.remote_field.get_accessor_name() ) except e: pass fields[field.name] = field return fields
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Creates copies of the fields we are keeping track of for the provided model, returning a dictionary mapping field name to a copied field object.
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python
train
skyfielders/python-skyfield
skyfield/precessionlib.py
https://github.com/skyfielders/python-skyfield/blob/51d9e042e06457f6b1f2415296d50a38cb3a300f/skyfield/precessionlib.py#L5-L69
def compute_precession(jd_tdb): """Return the rotation matrices for precessing to an array of epochs. `jd_tdb` - array of TDB Julian dates The array returned has the shape `(3, 3, n)` where `n` is the number of dates that have been provided as input. """ eps0 = 84381.406 # 't' is time in TDB centuries. t = (jd_tdb - T0) / 36525.0 # Numerical coefficients of psi_a, omega_a, and chi_a, along with # epsilon_0, the obliquity at J2000.0, are 4-angle formulation from # Capitaine et al. (2003), eqs. (4), (37), & (39). psia = ((((- 0.0000000951 * t + 0.000132851 ) * t - 0.00114045 ) * t - 1.0790069 ) * t + 5038.481507 ) * t omegaa = ((((+ 0.0000003337 * t - 0.000000467 ) * t - 0.00772503 ) * t + 0.0512623 ) * t - 0.025754 ) * t + eps0 chia = ((((- 0.0000000560 * t + 0.000170663 ) * t - 0.00121197 ) * t - 2.3814292 ) * t + 10.556403 ) * t eps0 = eps0 * ASEC2RAD psia = psia * ASEC2RAD omegaa = omegaa * ASEC2RAD chia = chia * ASEC2RAD sa = sin(eps0) ca = cos(eps0) sb = sin(-psia) cb = cos(-psia) sc = sin(-omegaa) cc = cos(-omegaa) sd = sin(chia) cd = cos(chia) # Compute elements of precession rotation matrix equivalent to # R3(chi_a) R1(-omega_a) R3(-psi_a) R1(epsilon_0). rot3 = array(((cd * cb - sb * sd * cc, cd * sb * ca + sd * cc * cb * ca - sa * sd * sc, cd * sb * sa + sd * cc * cb * sa + ca * sd * sc), (-sd * cb - sb * cd * cc, -sd * sb * ca + cd * cc * cb * ca - sa * cd * sc, -sd * sb * sa + cd * cc * cb * sa + ca * cd * sc), (sb * sc, -sc * cb * ca - sa * cc, -sc * cb * sa + cc * ca))) return rot3
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Return the rotation matrices for precessing to an array of epochs. `jd_tdb` - array of TDB Julian dates The array returned has the shape `(3, 3, n)` where `n` is the number of dates that have been provided as input.
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python
train
frictionlessdata/datapackage-py
datapackage/package.py
https://github.com/frictionlessdata/datapackage-py/blob/aca085ea54541b087140b58a81332f8728baeeb2/datapackage/package.py#L396-L405
def iter_errors(self): """"Lazily yields each ValidationError for the received data dict. """ # Deprecate warnings.warn( 'Property "package.iter_errors" is deprecated.', UserWarning) return self.profile.iter_errors(self.to_dict())
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Lazily yields each ValidationError for the received data dict.
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python
valid
fprimex/zdesk
zdesk/zdesk_api.py
https://github.com/fprimex/zdesk/blob/851611c13b4d530e9df31390b3ec709baf0a0188/zdesk/zdesk_api.py#L2403-L2407
def nps_survey_show(self, id, **kwargs): "https://developer.zendesk.com/rest_api/docs/nps-api/surveys#show-survey" api_path = "/api/v2/nps/surveys/{id}" api_path = api_path.format(id=id) return self.call(api_path, **kwargs)
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https://developer.zendesk.com/rest_api/docs/nps-api/surveys#show-survey
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python
train
portfoliome/postpy
postpy/admin.py
https://github.com/portfoliome/postpy/blob/fe26199131b15295fc5f669a0ad2a7f47bf490ee/postpy/admin.py#L24-L44
def get_primary_keys(conn, table: str, schema='public'): """Returns primary key columns for a specific table.""" query = """\ SELECT c.constraint_name AS pkey_constraint_name, c.column_name AS column_name FROM information_schema.key_column_usage AS c JOIN information_schema.table_constraints AS t ON t.constraint_name = c.constraint_name AND t.table_catalog = c.table_catalog AND t.table_schema = c.table_schema AND t.table_name = c.table_name WHERE t.constraint_type = 'PRIMARY KEY' AND c.table_schema=%s AND c.table_name=%s ORDER BY c.ordinal_position""" for record in select_dict(conn, query, params=(schema, table)): yield record['column_name']
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Returns primary key columns for a specific table.
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python
train
vanheeringen-lab/gimmemotifs
gimmemotifs/scanner.py
https://github.com/vanheeringen-lab/gimmemotifs/blob/1dc0572179e5d0c8f96958060133c1f8d92c6675/gimmemotifs/scanner.py#L515-L522
def count(self, seqs, nreport=100, scan_rc=True): """ count the number of matches above the cutoff returns an iterator of lists containing integer counts """ for matches in self.scan(seqs, nreport, scan_rc): counts = [len(m) for m in matches] yield counts
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count the number of matches above the cutoff returns an iterator of lists containing integer counts
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python
train
zmathew/django-backbone
backbone/views.py
https://github.com/zmathew/django-backbone/blob/53505a247fb058e64a103c4f11da66993037bd6b/backbone/views.py#L90-L101
def post(self, request, id=None, **kwargs): """ Handles post requests. """ if id: # No posting to an object detail page return HttpResponseForbidden() else: if not self.has_add_permission(request): return HttpResponseForbidden(_('You do not have permission to perform this action.')) else: return self.add_object(request)
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Handles post requests.
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python
train
juju/theblues
theblues/charmstore.py
https://github.com/juju/theblues/blob/f4431f29e43d04fc32f38f4f86cea45cd4e6ae98/theblues/charmstore.py#L66-L106
def _get(self, url): """Make a get request against the charmstore. This method is used by other API methods to standardize querying. @param url The full url to query (e.g. https://api.jujucharms.com/charmstore/v4/macaroon) """ try: response = requests.get(url, verify=self.verify, cookies=self.cookies, timeout=self.timeout, auth=self._client.auth()) response.raise_for_status() return response except HTTPError as exc: if exc.response.status_code in (404, 407): raise EntityNotFound(url) else: message = ('Error during request: {url} ' 'status code:({code}) ' 'message: {message}').format( url=url, code=exc.response.status_code, message=exc.response.text) logging.error(message) raise ServerError(exc.response.status_code, exc.response.text, message) except Timeout: message = 'Request timed out: {url} timeout: {timeout}' message = message.format(url=url, timeout=self.timeout) logging.error(message) raise ServerError(message) except RequestException as exc: message = ('Error during request: {url} ' 'message: {message}').format( url=url, message=exc) logging.error(message) raise ServerError(exc.args[0][1].errno, exc.args[0][1].strerror, message)
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Make a get request against the charmstore. This method is used by other API methods to standardize querying. @param url The full url to query (e.g. https://api.jujucharms.com/charmstore/v4/macaroon)
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python
train
craffel/mir_eval
mir_eval/chord.py
https://github.com/craffel/mir_eval/blob/f41c8dafaea04b411252a516d1965af43c7d531b/mir_eval/chord.py#L1238-L1290
def sevenths(reference_labels, estimated_labels): """Compare chords along MIREX 'sevenths' rules. Chords with qualities outside [maj, maj7, 7, min, min7, N] are ignored. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.sevenths(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut. """ validate(reference_labels, estimated_labels) seventh_qualities = ['maj', 'min', 'maj7', '7', 'min7', ''] valid_semitones = np.array([QUALITIES[name] for name in seventh_qualities]) ref_roots, ref_semitones = encode_many(reference_labels, False)[:2] est_roots, est_semitones = encode_many(estimated_labels, False)[:2] eq_root = ref_roots == est_roots eq_semitones = np.all(np.equal(ref_semitones, est_semitones), axis=1) comparison_scores = (eq_root * eq_semitones).astype(np.float) # Test for reference chord inclusion is_valid = np.array([np.all(np.equal(ref_semitones, semitones), axis=1) for semitones in valid_semitones]) # Drop if NOR comparison_scores[np.sum(is_valid, axis=0) == 0] = -1 return comparison_scores
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Compare chords along MIREX 'sevenths' rules. Chords with qualities outside [maj, maj7, 7, min, min7, N] are ignored. Examples -------- >>> (ref_intervals, ... ref_labels) = mir_eval.io.load_labeled_intervals('ref.lab') >>> (est_intervals, ... est_labels) = mir_eval.io.load_labeled_intervals('est.lab') >>> est_intervals, est_labels = mir_eval.util.adjust_intervals( ... est_intervals, est_labels, ref_intervals.min(), ... ref_intervals.max(), mir_eval.chord.NO_CHORD, ... mir_eval.chord.NO_CHORD) >>> (intervals, ... ref_labels, ... est_labels) = mir_eval.util.merge_labeled_intervals( ... ref_intervals, ref_labels, est_intervals, est_labels) >>> durations = mir_eval.util.intervals_to_durations(intervals) >>> comparisons = mir_eval.chord.sevenths(ref_labels, est_labels) >>> score = mir_eval.chord.weighted_accuracy(comparisons, durations) Parameters ---------- reference_labels : list, len=n Reference chord labels to score against. estimated_labels : list, len=n Estimated chord labels to score against. Returns ------- comparison_scores : np.ndarray, shape=(n,), dtype=float Comparison scores, in [0.0, 1.0], or -1 if the comparison is out of gamut.
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python
train
pjuren/pyokit
src/pyokit/datastruct/read.py
https://github.com/pjuren/pyokit/blob/fddae123b5d817daa39496183f19c000d9c3791f/src/pyokit/datastruct/read.py#L232-L256
def merge(self, other, forceMerge=False): """ Merge two reads by concatenating their sequence data and their quality data (<self> first, then <other>); <self> and <other> must have the same sequence name. A new merged FastqSequence object is returned; <Self> and <other> are left unaltered. :param other: the other sequence to merge with self. :param forceMerge: force the merge to occur, even if sequences names don't match. In this case, <self> takes precedence. :return: A new FastqSequence that represents the merging of <self> and <other> :raise: FastqSequenceError if the sequences names do not match, and the forceMerge parameter is not set. """ if self.sequenceName != other.sequenceName and not forceMerge: raise NGSReadError("cannot merge " + self.sequenceName + " with " + other.sequenceName + " -- different " + "sequence names") name = self.sequenceName seq = self.sequenceData + other.sequenceData qual = self.sequenceQual + other.sequenceQual return NGSReadError(name, seq, qual)
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Merge two reads by concatenating their sequence data and their quality data (<self> first, then <other>); <self> and <other> must have the same sequence name. A new merged FastqSequence object is returned; <Self> and <other> are left unaltered. :param other: the other sequence to merge with self. :param forceMerge: force the merge to occur, even if sequences names don't match. In this case, <self> takes precedence. :return: A new FastqSequence that represents the merging of <self> and <other> :raise: FastqSequenceError if the sequences names do not match, and the forceMerge parameter is not set.
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python
train
reingart/pyafipws
utils.py
https://github.com/reingart/pyafipws/blob/ee87cfe4ac12285ab431df5fec257f103042d1ab/utils.py#L566-L614
def leer(linea, formato, expandir_fechas=False): "Analiza una linea de texto dado un formato, devuelve un diccionario" dic = {} comienzo = 1 for fmt in formato: clave, longitud, tipo = fmt[0:3] dec = (len(fmt)>3 and isinstance(fmt[3], int)) and fmt[3] or 2 valor = linea[comienzo-1:comienzo-1+longitud].strip() try: if chr(8) in valor or chr(127) in valor or chr(255) in valor: valor = None # nulo elif tipo == N: if valor: valor = long(valor) else: valor = 0 elif tipo == I: if valor: try: if '.' in valor: valor = float(valor) else: valor = valor.strip(" ") if valor[0] == "-": sign = -1 valor = valor[1:] else: sign = +1 valor = sign * float(("%%s.%%0%sd" % dec) % (long(valor[:-dec] or '0'), int(valor[-dec:] or '0'))) except ValueError: raise ValueError("Campo invalido: %s = '%s'" % (clave, valor)) else: valor = 0.00 elif expandir_fechas and clave.lower().startswith("fec") and longitud <= 8: if valor: valor = "%s-%s-%s" % (valor[0:4], valor[4:6], valor[6:8]) else: valor = None else: valor = valor.decode("ascii","ignore") if not valor and clave in dic and len(linea) <= comienzo: pass # ignorar - compatibilidad hacia atrás (cambios tamaño) else: dic[clave] = valor comienzo += longitud except Exception, e: raise ValueError("Error al leer campo %s pos %s val '%s': %s" % ( clave, comienzo, valor, str(e))) return dic
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Analiza una linea de texto dado un formato, devuelve un diccionario
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python
train
vertexproject/synapse
synapse/lib/syntax.py
https://github.com/vertexproject/synapse/blob/22e67c5a8f6d7caddbcf34b39ab1bd2d6c4a6e0b/synapse/lib/syntax.py#L328-L347
def parse_cmd_kwlist(text, off=0): ''' Parse a foo:bar=<valu>[,...] kwarg list into (prop,valu),off ''' kwlist = [] _, off = nom(text, off, whites) while off < len(text): (p, v), off = parse_cmd_kwarg(text, off=off) kwlist.append((p, v)) _, off = nom(text, off, whites) if not nextchar(text, off, ','): break _, off = nom(text, off, whites) return kwlist, off
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Parse a foo:bar=<valu>[,...] kwarg list into (prop,valu),off
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python
train
anjishnu/ask-alexa-pykit
examples/twitter/lambda_function.py
https://github.com/anjishnu/ask-alexa-pykit/blob/a47c278ca7a60532bbe1a9b789f6c37e609fea8b/examples/twitter/lambda_function.py#L322-L337
def next_intent_handler(request): """ Takes care of things whenver the user says 'next' """ message = "Sorry, couldn't find anything in your next queue" end_session = True if True: user_queue = twitter_cache.user_queue(request.access_token()) if not user_queue.is_finished(): message = user_queue.read_out_next(MAX_RESPONSE_TWEETS) if not user_queue.is_finished(): end_session = False message = message + ". Please, say 'next' if you want me to read out more. " return alexa.create_response(message=message, end_session=end_session)
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Takes care of things whenver the user says 'next'
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python
train
saltstack/salt
salt/returners/influxdb_return.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/returners/influxdb_return.py#L313-L326
def get_minions(): ''' Return a list of minions ''' serv = _get_serv(ret=None) sql = "select distinct(id) from returns" data = serv.query(sql) ret = [] if data: for jid in data[0]['points']: ret.append(jid[1]) return ret
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Return a list of minions
[ "Return", "a", "list", "of", "minions" ]
python
train
scanny/python-pptx
pptx/chart/data.py
https://github.com/scanny/python-pptx/blob/d6ab8234f8b03953d2f831ff9394b1852db34130/pptx/chart/data.py#L711-L719
def add_series(self, name, number_format=None): """ Return a |BubbleSeriesData| object newly created and added at the end of this sequence, and having series named *name* and values formatted with *number_format*. """ series_data = BubbleSeriesData(self, name, number_format) self.append(series_data) return series_data
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Return a |BubbleSeriesData| object newly created and added at the end of this sequence, and having series named *name* and values formatted with *number_format*.
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python
train
lemieuxl/pyplink
pyplink/pyplink.py
https://github.com/lemieuxl/pyplink/blob/31d47c86f589064bda98206314a2d0b20e7fd2f0/pyplink/pyplink.py#L410-L414
def _write_bed_header(self): """Writes the BED first 3 bytes.""" # Writing the first three bytes final_byte = 1 if self._bed_format == "SNP-major" else 0 self._bed.write(bytearray((108, 27, final_byte)))
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Writes the BED first 3 bytes.
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python
train
aetros/aetros-cli
aetros/client.py
https://github.com/aetros/aetros-cli/blob/a2a1f38d6af1660e1e2680c7d413ec2aef45faab/aetros/client.py#L496-L537
def wait_until_queue_empty(self, channels, report=True, clear_end=True): """ Waits until all queues of channels are empty. """ state = {'message': ''} self.logger.debug("wait_until_queue_empty: report=%s %s" % (str(report), str([channel+':'+str(len(self.queues[channel])) for channel in channels]), )) queues = [] for channel in channels: queues += self.queues[channel][:] def print_progress(): if report: self.logger.debug("all_empty=%s" % (str(all_empty),)) sys.__stderr__.write('\b' * len(state['message'])) sys.__stderr__.write("\033[K") state['message'] = "%.2f kB/s // %.2fkB of %.2fkB // %.2f%%" \ % (self.bytes_speed / 1024, self.bytes_sent / 1024, self.bytes_total / 1024, (self.bytes_sent / self.bytes_total * 100) if self.bytes_total else 0) sys.__stderr__.write(state['message']) sys.__stderr__.flush() while True: all_empty = all(m['_sent'] for m in queues) print_progress() if all_empty: break time.sleep(0.2) print_progress() if report and clear_end: sys.__stderr__.write('\b' * len(state['message'])) sys.__stderr__.write("\033[K") sys.__stderr__.flush()
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Waits until all queues of channels are empty.
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python
train
portfoliome/foil
foil/deserializers.py
https://github.com/portfoliome/foil/blob/b66d8cf4ab048a387d8c7a033b47e922ed6917d6/foil/deserializers.py#L45-L65
def json_decoder_hook(dct, str_decoders=STRING_DECODERS, converters=MappingProxyType(dict())) -> dict: """Decoder for parsing typical objects like uuid's and dates.""" for k, v in dct.items(): if k in converters: parse_func = converters[k] dct[k] = parse_func(v) elif isinstance(v, str): for decode_func in str_decoders: v = decode_func(v) if not isinstance(v, str): break dct[k] = v elif isinstance(v, collections.Mapping): dct[k] = json_decoder_hook(v, str_decoders, converters) return dct
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Decoder for parsing typical objects like uuid's and dates.
[ "Decoder", "for", "parsing", "typical", "objects", "like", "uuid", "s", "and", "dates", "." ]
python
train
tanghaibao/jcvi
jcvi/formats/fasta.py
https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/formats/fasta.py#L2209-L2257
def tidy(args): """ %prog tidy fastafile Trim terminal Ns, normalize gap sizes and remove small components. """ p = OptionParser(tidy.__doc__) p.add_option("--gapsize", dest="gapsize", default=0, type="int", help="Set all gaps to the same size [default: %default]") p.add_option("--minlen", dest="minlen", default=100, type="int", help="Minimum component size [default: %default]") opts, args = p.parse_args(args) if len(args) != 1: sys.exit(not p.print_help()) fastafile, = args gapsize = opts.gapsize minlen = opts.minlen tidyfastafile = fastafile.rsplit(".", 1)[0] + ".tidy.fasta" fw = must_open(tidyfastafile, "w") removed = normalized = 0 fasta = Fasta(fastafile, lazy=True) for name, rec in fasta.iteritems_ordered(): rec.seq = rec.seq.upper() if minlen: removed += remove_small_components(rec, minlen) trim_terminal_Ns(rec) if gapsize: normalized += normalize_gaps(rec, gapsize) if len(rec) == 0: logging.debug("Drop seq {0}".format(rec.id)) continue SeqIO.write([rec], fw, "fasta") # Print statistics if removed: logging.debug("Total discarded bases: {0}".format(removed)) if normalized: logging.debug("Gaps normalized: {0}".format(normalized)) logging.debug("Tidy FASTA written to `{0}`.".format(tidyfastafile)) fw.close() return tidyfastafile
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%prog tidy fastafile Trim terminal Ns, normalize gap sizes and remove small components.
[ "%prog", "tidy", "fastafile" ]
python
train
carpedm20/fbchat
fbchat/_client.py
https://github.com/carpedm20/fbchat/blob/f480d68b5773473e6daba7f66075ee30e8d737a8/fbchat/_client.py#L2319-L2332
def deleteMessages(self, message_ids): """ Deletes specifed messages :param message_ids: Message IDs to delete :return: Whether the request was successful :raises: FBchatException if request failed """ message_ids = require_list(message_ids) data = dict() for i, message_id in enumerate(message_ids): data["message_ids[{}]".format(i)] = message_id r = self._post(self.req_url.DELETE_MESSAGES, data) return r.ok
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Deletes specifed messages :param message_ids: Message IDs to delete :return: Whether the request was successful :raises: FBchatException if request failed
[ "Deletes", "specifed", "messages" ]
python
train
szairis/sakmapper
sakmapper/network.py
https://github.com/szairis/sakmapper/blob/ac462fd2674e6aa1aa3b209222d8ac4e9268a790/sakmapper/network.py#L173-L220
def mapper_graph(df, lens_data=None, lens='pca', resolution=10, gain=0.5, equalize=True, clust='kmeans', stat='db', max_K=5): """ input: N x n_dim image of of raw data under lens function, as a dataframe output: (undirected graph, list of node contents, dictionary of patches) """ if lens_data is None: lens_data = apply_lens(df, lens=lens) patch_clusterings = {} counter = 0 patches = covering_patches(lens_data, resolution=resolution, gain=gain, equalize=equalize) for key, patch in patches.items(): if len(patch) > 0: patch_clusterings[key] = optimal_clustering(df, patch, method=clust, statistic=stat, max_K=max_K) counter += 1 print 'total of {} patches required clustering'.format(counter) all_clusters = [] for key in patch_clusterings: all_clusters += patch_clusterings[key] num_nodes = len(all_clusters) print 'this implies {} nodes in the mapper graph'.format(num_nodes) A = np.zeros((num_nodes, num_nodes)) for i in range(num_nodes): for j in range(i): overlap = set(all_clusters[i]).intersection(set(all_clusters[j])) if len(overlap) > 0: A[i, j] = 1 A[j, i] = 1 G = nx.from_numpy_matrix(A) total = [] all_clusters_new = [] mapping = {} cont = 0 for m in all_clusters: total += m for n, m in enumerate(all_clusters): if len(m) == 1 and total.count(m) > 1: G.remove_node(n) else: all_clusters_new.append(m) mapping[n] = cont cont += 1 H = nx.relabel_nodes(G, mapping) return H, all_clusters_new, patches
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input: N x n_dim image of of raw data under lens function, as a dataframe output: (undirected graph, list of node contents, dictionary of patches)
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python
train
KnowledgeLinks/rdfframework
rdfframework/search/esmappings.py
https://github.com/KnowledgeLinks/rdfframework/blob/9ec32dcc4bed51650a4b392cc5c15100fef7923a/rdfframework/search/esmappings.py#L71-L88
def list_indexes(cls): """ Returns a dictionary with the key as the es_index name and the object is a list of rdfclasses for that index args: None """ cls_list = cls.list_mapped_classes() rtn_obj = {} for key, value in cls_list.items(): idx = value.es_defs.get('kds_esIndex')[0] try: rtn_obj[idx].append(value) except KeyError: rtn_obj[idx] = [value] return rtn_obj
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Returns a dictionary with the key as the es_index name and the object is a list of rdfclasses for that index args: None
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python
train