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dict
q242000
Versioned.get_remote
train
def get_remote(self, remote='origin'): """Get a git remote object for this instance.""" repo = self.get_repo() if repo is not None: remotes = {r.name: r for r in repo.remotes} r = repo.remotes[0] if remote not in remotes else remotes[remote] else: r = ...
python
{ "resource": "" }
q242001
Versioned.get_remote_url
train
def get_remote_url(self, remote='origin', cached=True): """Get a git remote URL for this instance.""" if hasattr(self.__class__, '_remote_url') and cached: url = self.__class__._remote_url else: r = self.get_remote(remote) try: url = list(r.url...
python
{ "resource": "" }
q242002
ObservationValidator._validate_iterable
train
def _validate_iterable(self, is_iterable, key, value): """Validate fields with `iterable` key in schema set to True""" if is_iterable: try: iter(value) except TypeError: self._error(key, "Must be iterable (e.g. a list or array)")
python
{ "resource": "" }
q242003
ObservationValidator._validate_units
train
def _validate_units(self, has_units, key, value): """Validate fields with `units` key in schema set to True. The rule's arguments are validated against this schema: {'type': 'boolean'} """ if has_units: if isinstance(self.test.units, dict): required_u...
python
{ "resource": "" }
q242004
ParametersValidator.validate_quantity
train
def validate_quantity(self, value): """Validate that the value is of the `Quantity` type.""" if not isinstance(value, pq.quantity.Quantity): self._error('%s' % value, "Must be a Python quantity.")
python
{ "resource": "" }
q242005
ZScore.compute
train
def compute(cls, observation, prediction): """Compute a z-score from an observation and a prediction.""" assert isinstance(observation, dict) try: p_value = prediction['mean'] # Use the prediction's mean. except (TypeError, KeyError, IndexError): # If there isn't one... ...
python
{ "resource": "" }
q242006
ZScore.norm_score
train
def norm_score(self): """Return the normalized score. Equals 1.0 for a z-score of 0, falling to 0.0 for extremely positive or negative values. """ cdf = (1.0 + math.erf(self.score / math.sqrt(2.0))) / 2.0 return 1 - 2*math.fabs(0.5 - cdf)
python
{ "resource": "" }
q242007
CohenDScore.compute
train
def compute(cls, observation, prediction): """Compute a Cohen's D from an observation and a prediction.""" assert isinstance(observation, dict) assert isinstance(prediction, dict) p_mean = prediction['mean'] # Use the prediction's mean. p_std = prediction['std'] o_mean =...
python
{ "resource": "" }
q242008
RatioScore.compute
train
def compute(cls, observation, prediction, key=None): """Compute a ratio from an observation and a prediction.""" assert isinstance(observation, (dict, float, int, pq.Quantity)) assert isinstance(prediction, (dict, float, int, pq.Quantity)) obs, pred = cls.extract_means_or_values(observa...
python
{ "resource": "" }
q242009
FloatScore.compute_ssd
train
def compute_ssd(cls, observation, prediction): """Compute sum-squared diff between observation and prediction.""" # The sum of the squared differences. value = ((observation - prediction)**2).sum() score = FloatScore(value) return score
python
{ "resource": "" }
q242010
read_requirements
train
def read_requirements(): '''parses requirements from requirements.txt''' reqs_path = os.path.join('.', 'requirements.txt') install_reqs = parse_requirements(reqs_path, session=PipSession()) reqs = [str(ir.req) for ir in install_reqs] return reqs
python
{ "resource": "" }
q242011
register_backends
train
def register_backends(vars): """Register backends for use with models. `vars` should be a dictionary of variables obtained from e.g. `locals()`, at least some of which are Backend classes, e.g. from imports. """ new_backends = {x.replace('Backend', ''): cls for x, cls in vars.it...
python
{ "resource": "" }
q242012
Backend.init_backend
train
def init_backend(self, *args, **kwargs): """Initialize the backend.""" self.model.attrs = {} self.use_memory_cache = kwargs.get('use_memory_cache', True) if self.use_memory_cache: self.init_memory_cache() self.use_disk_cache = kwargs.get('use_disk_cache', False) ...
python
{ "resource": "" }
q242013
Backend.init_disk_cache
train
def init_disk_cache(self): """Initialize the on-disk version of the cache.""" try: # Cleanup old disk cache files path = self.disk_cache_location os.remove(path) except Exception: pass self.disk_cache_location = os.path.join(tempfile.mkdtem...
python
{ "resource": "" }
q242014
Backend.get_memory_cache
train
def get_memory_cache(self, key=None): """Return result in memory cache for key 'key' or None if not found.""" key = self.model.hash if key is None else key self._results = self.memory_cache.get(key) return self._results
python
{ "resource": "" }
q242015
Backend.get_disk_cache
train
def get_disk_cache(self, key=None): """Return result in disk cache for key 'key' or None if not found.""" key = self.model.hash if key is None else key if not getattr(self, 'disk_cache_location', False): self.init_disk_cache() disk_cache = shelve.open(self.disk_cache_location...
python
{ "resource": "" }
q242016
Backend.set_memory_cache
train
def set_memory_cache(self, results, key=None): """Store result in memory cache with key matching model state.""" key = self.model.hash if key is None else key self.memory_cache[key] = results
python
{ "resource": "" }
q242017
Backend.set_disk_cache
train
def set_disk_cache(self, results, key=None): """Store result in disk cache with key matching model state.""" if not getattr(self, 'disk_cache_location', False): self.init_disk_cache() disk_cache = shelve.open(self.disk_cache_location) key = self.model.hash if key is None else...
python
{ "resource": "" }
q242018
Backend.backend_run
train
def backend_run(self): """Check for cached results; then run the model if needed.""" key = self.model.hash if self.use_memory_cache and self.get_memory_cache(key): return self._results if self.use_disk_cache and self.get_disk_cache(key): return self._results ...
python
{ "resource": "" }
q242019
Backend.save_results
train
def save_results(self, path='.'): """Save results on disk.""" with open(path, 'wb') as f: pickle.dump(self.results, f)
python
{ "resource": "" }
q242020
Capability.check
train
def check(cls, model, require_extra=False): """Check whether the provided model has this capability. By default, uses isinstance. If `require_extra`, also requires that an instance check be present in `model.extra_capability_checks`. """ class_capable = isinstance(model, cls) ...
python
{ "resource": "" }
q242021
RunnableModel.set_backend
train
def set_backend(self, backend): """Set the simulation backend.""" if isinstance(backend, str): name = backend args = [] kwargs = {} elif isinstance(backend, (tuple, list)): name = '' args = [] kwargs = {} for i i...
python
{ "resource": "" }
q242022
Score.color
train
def color(self, value=None): """Turn the score intp an RGB color tuple of three 8-bit integers.""" if value is None: value = self.norm_score rgb = Score.value_color(value) return rgb
python
{ "resource": "" }
q242023
Score.extract_means_or_values
train
def extract_means_or_values(cls, observation, prediction, key=None): """Extracts the mean, value, or user-provided key from the observation and prediction dictionaries. """ obs_mv = cls.extract_mean_or_value(observation, key) pred_mv = cls.extract_mean_or_value(prediction, key) ...
python
{ "resource": "" }
q242024
Score.extract_mean_or_value
train
def extract_mean_or_value(cls, obs_or_pred, key=None): """Extracts the mean, value, or user-provided key from an observation or prediction dictionary. """ result = None if not isinstance(obs_or_pred, dict): result = obs_or_pred else: keys = ([key]...
python
{ "resource": "" }
q242025
ErrorScore.summary
train
def summary(self): """Summarize the performance of a model on a test.""" return "== Model %s did not complete test %s due to error '%s'. ==" %\ (str(self.model), str(self.test), str(self.score))
python
{ "resource": "" }
q242026
ImageCanvas.load
train
def load(self, draw_bbox = False, **kwargs): ''' Makes the canvas. This could be far speedier if it copied raw pixels, but that would take far too much time to write vs using Image inbuilts ''' im = Image.new('RGBA', self.img_size) draw = None if draw_bbox: ...
python
{ "resource": "" }
q242027
match_window
train
def match_window(in_data, offset): '''Find the longest match for the string starting at offset in the preceeding data ''' window_start = max(offset - WINDOW_MASK, 0) for n in range(MAX_LEN, THRESHOLD-1, -1): window_end = min(offset + n, len(in_data)) # we've not got enough data left for...
python
{ "resource": "" }
q242028
_merge_args_opts
train
def _merge_args_opts(args_opts_dict, **kwargs): """Merge options with their corresponding arguments. Iterates over the dictionary holding arguments (keys) and options (values). Merges each options string with its corresponding argument. :param dict args_opts_dict: a dictionary of arguments and options...
python
{ "resource": "" }
q242029
FFmpeg.run
train
def run(self, input_data=None, stdout=None, stderr=None): """Execute FFmpeg command line. ``input_data`` can contain input for FFmpeg in case ``pipe`` protocol is used for input. ``stdout`` and ``stderr`` specify where to redirect the ``stdout`` and ``stderr`` of the process. By default...
python
{ "resource": "" }
q242030
_get_usage
train
def _get_usage(ctx): """Alternative, non-prefixed version of 'get_usage'.""" formatter = ctx.make_formatter() pieces = ctx.command.collect_usage_pieces(ctx) formatter.write_usage(ctx.command_path, ' '.join(pieces), prefix='') return formatter.getvalue().rstrip('\n')
python
{ "resource": "" }
q242031
_get_help_record
train
def _get_help_record(opt): """Re-implementation of click.Opt.get_help_record. The variant of 'get_help_record' found in Click makes uses of slashes to separate multiple opts, and formats option arguments using upper case. This is not compatible with Sphinx's 'option' directive, which expects comma-...
python
{ "resource": "" }
q242032
_format_description
train
def _format_description(ctx): """Format the description for a given `click.Command`. We parse this as reStructuredText, allowing users to embed rich information in their help messages if they so choose. """ help_string = ctx.command.help or ctx.command.short_help if not help_string: ret...
python
{ "resource": "" }
q242033
_format_option
train
def _format_option(opt): """Format the output for a `click.Option`.""" opt = _get_help_record(opt) yield '.. option:: {}'.format(opt[0]) if opt[1]: yield '' for line in statemachine.string2lines( opt[1], tab_width=4, convert_whitespace=True): yield _indent(li...
python
{ "resource": "" }
q242034
_format_options
train
def _format_options(ctx): """Format all `click.Option` for a `click.Command`.""" # the hidden attribute is part of click 7.x only hence use of getattr params = [ x for x in ctx.command.params if isinstance(x, click.Option) and not getattr(x, 'hidden', False) ] for param in params: ...
python
{ "resource": "" }
q242035
_format_argument
train
def _format_argument(arg): """Format the output of a `click.Argument`.""" yield '.. option:: {}'.format(arg.human_readable_name) yield '' yield _indent('{} argument{}'.format( 'Required' if arg.required else 'Optional', '(s)' if arg.nargs != 1 else ''))
python
{ "resource": "" }
q242036
_format_arguments
train
def _format_arguments(ctx): """Format all `click.Argument` for a `click.Command`.""" params = [x for x in ctx.command.params if isinstance(x, click.Argument)] for param in params: for line in _format_argument(param): yield line yield ''
python
{ "resource": "" }
q242037
_format_envvar
train
def _format_envvar(param): """Format the envvars of a `click.Option` or `click.Argument`.""" yield '.. envvar:: {}'.format(param.envvar) yield ' :noindex:' yield '' if isinstance(param, click.Argument): param_ref = param.human_readable_name else: # if a user has defined an opt ...
python
{ "resource": "" }
q242038
_format_envvars
train
def _format_envvars(ctx): """Format all envvars for a `click.Command`.""" params = [x for x in ctx.command.params if getattr(x, 'envvar')] for param in params: yield '.. _{command_name}-{param_name}-{envvar}:'.format( command_name=ctx.command_path.replace(' ', '-'), param_na...
python
{ "resource": "" }
q242039
_format_subcommand
train
def _format_subcommand(command): """Format a sub-command of a `click.Command` or `click.Group`.""" yield '.. object:: {}'.format(command.name) # click 7.0 stopped setting short_help by default if CLICK_VERSION < (7, 0): short_help = command.short_help else: short_help = command.get_...
python
{ "resource": "" }
q242040
_filter_commands
train
def _filter_commands(ctx, commands=None): """Return list of used commands.""" lookup = getattr(ctx.command, 'commands', {}) if not lookup and isinstance(ctx.command, click.MultiCommand): lookup = _get_lazyload_commands(ctx.command) if commands is None: return sorted(lookup.values(), key...
python
{ "resource": "" }
q242041
_format_command
train
def _format_command(ctx, show_nested, commands=None): """Format the output of `click.Command`.""" # the hidden attribute is part of click 7.x only hence use of getattr if getattr(ctx.command, 'hidden', False): return # description for line in _format_description(ctx): yield line ...
python
{ "resource": "" }
q242042
ClickDirective._load_module
train
def _load_module(self, module_path): """Load the module.""" # __import__ will fail on unicode, # so we ensure module path is a string here. module_path = str(module_path) try: module_name, attr_name = module_path.split(':', 1) except ValueError: # noqa ...
python
{ "resource": "" }
q242043
DataCursor._show_annotation_box
train
def _show_annotation_box(self, event): """Update an existing box or create an annotation box for an event.""" ax = event.artist.axes # Get the pre-created annotation box for the axes or create a new one. if self.display != 'multiple': annotation = self.annotations[ax] ...
python
{ "resource": "" }
q242044
DataCursor.event_info
train
def event_info(self, event): """Get a dict of info for the artist selected by "event".""" def default_func(event): return {} registry = { AxesImage : [pick_info.image_props], PathCollection : [pick_info.scatter_props, self._contour_info, ...
python
{ "resource": "" }
q242045
DataCursor._formatter
train
def _formatter(self, x=None, y=None, z=None, s=None, label=None, **kwargs): """ Default formatter function, if no `formatter` kwarg is specified. Takes information about the pick event as a series of kwargs and returns the string to be displayed. """ def is_date(axis): ...
python
{ "resource": "" }
q242046
DataCursor._format_coord
train
def _format_coord(self, x, limits): """ Handles display-range-specific formatting for the x and y coords. Parameters ---------- x : number The number to be formatted limits : 2-item sequence The min and max of the current display limits for the ax...
python
{ "resource": "" }
q242047
DataCursor._hide_box
train
def _hide_box(self, annotation): """Remove a specific annotation box.""" annotation.set_visible(False) if self.display == 'multiple': annotation.axes.figure.texts.remove(annotation) # Remove the annotation from self.annotations. lookup = dict((self.annotation...
python
{ "resource": "" }
q242048
DataCursor.enable
train
def enable(self): """Connects callbacks and makes artists pickable. If the datacursor has already been enabled, this function has no effect.""" def connect(fig): if self.hover: event = 'motion_notify_event' else: event = 'button_press_event...
python
{ "resource": "" }
q242049
DataCursor._increment_index
train
def _increment_index(self, di=1): """ Move the most recently displayed annotation to the next item in the series, if possible. If ``di`` is -1, move it to the previous item. """ if self._last_event is None: return if not hasattr(self._last_event, 'ind'): ...
python
{ "resource": "" }
q242050
HighlightingDataCursor.show_highlight
train
def show_highlight(self, artist): """Show or create a highlight for a givent artist.""" # This is a separate method to make subclassing easier. if artist in self.highlights: self.highlights[artist].set_visible(True) else: self.highlights[artist] = self.create_high...
python
{ "resource": "" }
q242051
HighlightingDataCursor.create_highlight
train
def create_highlight(self, artist): """Create a new highlight for the given artist.""" highlight = copy.copy(artist) highlight.set(color=self.highlight_color, mec=self.highlight_color, lw=self.highlight_width, mew=self.highlight_width) artist.axes.add_artist(highlig...
python
{ "resource": "" }
q242052
_coords2index
train
def _coords2index(im, x, y, inverted=False): """ Converts data coordinates to index coordinates of the array. Parameters ----------- im : An AxesImage instance The image artist to operation on x : number The x-coordinate in data coordinates. y : number The y-coordina...
python
{ "resource": "" }
q242053
_interleave
train
def _interleave(a, b): """Interleave arrays a and b; b may have multiple columns and must be shorter by 1. """ b = np.column_stack([b]) # Turn b into a column array. nx, ny = b.shape c = np.zeros((nx + 1, ny + 1)) c[:, 0] = a c[:-1, 1:] = b return c.ravel()[:-(c.shape[1] - 1)]
python
{ "resource": "" }
q242054
three_dim_props
train
def three_dim_props(event): """ Get information for a pick event on a 3D artist. Parameters ----------- event : PickEvent The pick event to process Returns -------- A dict with keys: `x`: The estimated x-value of the click on the artist `y`: The estimated y-valu...
python
{ "resource": "" }
q242055
rectangle_props
train
def rectangle_props(event): """ Returns the width, height, left, and bottom of a rectangle artist. Parameters ----------- event : PickEvent The pick event to process Returns -------- A dict with keys: `width` : The width of the rectangle `height` : The height of...
python
{ "resource": "" }
q242056
get_xy
train
def get_xy(artist): """ Attempts to get the x,y data for individual items subitems of the artist. Returns None if this is not possible. At present, this only supports Line2D's and basic collections. """ xy = None if hasattr(artist, 'get_offsets'): xy = artist.get_offsets().T el...
python
{ "resource": "" }
q242057
datacursor
train
def datacursor(artists=None, axes=None, **kwargs): """ Create an interactive data cursor for the specified artists or specified axes. The data cursor displays information about a selected artist in a "popup" annotation box. If a specific sequence of artists is given, only the specified artists will...
python
{ "resource": "" }
q242058
wrap_exception
train
def wrap_exception(func: Callable) -> Callable: """Decorator to wrap pygatt exceptions into BluetoothBackendException.""" try: # only do the wrapping if pygatt is installed. # otherwise it's pointless anyway from pygatt.backends.bgapi.exceptions import BGAPIError from pygatt.exce...
python
{ "resource": "" }
q242059
PygattBackend.write_handle
train
def write_handle(self, handle: int, value: bytes): """Write a handle to the device.""" if not self.is_connected(): raise BluetoothBackendException('Not connected to device!') self._device.char_write_handle(handle, value, True) return True
python
{ "resource": "" }
q242060
wrap_exception
train
def wrap_exception(func: Callable) -> Callable: """Decorator to wrap BTLEExceptions into BluetoothBackendException.""" try: # only do the wrapping if bluepy is installed. # otherwise it's pointless anyway from bluepy.btle import BTLEException except ImportError: return func ...
python
{ "resource": "" }
q242061
BluepyBackend.write_handle
train
def write_handle(self, handle: int, value: bytes): """Write a handle from the device. You must be connected to do this. """ if self._peripheral is None: raise BluetoothBackendException('not connected to backend') return self._peripheral.writeCharacteristic(handle, va...
python
{ "resource": "" }
q242062
BluepyBackend.check_backend
train
def check_backend() -> bool: """Check if the backend is available.""" try: import bluepy.btle # noqa: F401 #pylint: disable=unused-import return True except ImportError as importerror: _LOGGER.error('bluepy not found: %s', str(importerror)) return Fal...
python
{ "resource": "" }
q242063
BluepyBackend.scan_for_devices
train
def scan_for_devices(timeout: float) -> List[Tuple[str, str]]: """Scan for bluetooth low energy devices. Note this must be run as root!""" from bluepy.btle import Scanner scanner = Scanner() result = [] for device in scanner.scan(timeout): result.append((dev...
python
{ "resource": "" }
q242064
wrap_exception
train
def wrap_exception(func: Callable) -> Callable: """Wrap all IOErrors to BluetoothBackendException""" def _func_wrapper(*args, **kwargs): try: return func(*args, **kwargs) except IOError as exception: raise BluetoothBackendException() from exception return _func_wrapp...
python
{ "resource": "" }
q242065
GatttoolBackend.write_handle
train
def write_handle(self, handle: int, value: bytes): # noqa: C901 # pylint: disable=arguments-differ """Read from a BLE address. @param: mac - MAC address in format XX:XX:XX:XX:XX:XX @param: handle - BLE characteristics handle in format 0xXX @param: value - value to write...
python
{ "resource": "" }
q242066
GatttoolBackend.wait_for_notification
train
def wait_for_notification(self, handle: int, delegate, notification_timeout: float): """Listen for characteristics changes from a BLE address. @param: mac - MAC address in format XX:XX:XX:XX:XX:XX @param: handle - BLE characteristics handle in format 0xXX a value of 0x0...
python
{ "resource": "" }
q242067
GatttoolBackend.check_backend
train
def check_backend() -> bool: """Check if gatttool is available on the system.""" try: call('gatttool', stdout=PIPE, stderr=PIPE) return True except OSError as os_err: msg = 'gatttool not found: {}'.format(str(os_err)) _LOGGER.error(msg) ret...
python
{ "resource": "" }
q242068
GatttoolBackend.bytes_to_string
train
def bytes_to_string(raw_data: bytes, prefix: bool = False) -> str: """Convert a byte array to a hex string.""" prefix_string = '' if prefix: prefix_string = '0x' suffix = ''.join([format(c, "02x") for c in raw_data]) return prefix_string + suffix.upper()
python
{ "resource": "" }
q242069
decode_ast
train
def decode_ast(registry, ast_json): """JSON decoder for BaseNodes""" if ast_json.get("@type"): subclass = registry.get_cls(ast_json["@type"], tuple(ast_json["@fields"])) return subclass( ast_json["children"], ast_json["field_references"], ast_json["label_refer...
python
{ "resource": "" }
q242070
simplify_tree
train
def simplify_tree(tree, unpack_lists=True, in_list=False): """Recursively unpack single-item lists and objects where fields and labels only reference a single child :param tree: the tree to simplify (mutating!) :param unpack_lists: whether single-item lists should be replaced by that item :param in_lis...
python
{ "resource": "" }
q242071
get_field
train
def get_field(ctx, field): """Helper to get the value of a field""" # field can be a string or a node attribute if isinstance(field, str): field = getattr(ctx, field, None) # when not alias needs to be called if callable(field): field = field() # when alias set on token, need to ...
python
{ "resource": "" }
q242072
get_field_names
train
def get_field_names(ctx): """Get fields defined in an ANTLR context for a parser rule""" # this does not include labels and literals, only rule names and token names # TODO: check ANTLR parser template for full exclusion list fields = [ field for field in type(ctx).__dict__ if no...
python
{ "resource": "" }
q242073
get_label_names
train
def get_label_names(ctx): """Get labels defined in an ANTLR context for a parser rule""" labels = [ label for label in ctx.__dict__ if not label.startswith("_") and label not in [ "children", "exception", "invokingState", "p...
python
{ "resource": "" }
q242074
Speaker.get_info
train
def get_info(node_cfg): """Return a tuple with the verbal name of a node, and a dict of field names.""" node_cfg = node_cfg if isinstance(node_cfg, dict) else {"name": node_cfg} return node_cfg.get("name"), node_cfg.get("fields", {})
python
{ "resource": "" }
q242075
BaseNodeRegistry.isinstance
train
def isinstance(self, instance, class_name): """Check if a BaseNode is an instance of a registered dynamic class""" if isinstance(instance, BaseNode): klass = self.dynamic_node_classes.get(class_name, None) if klass: return isinstance(instance, klass) #...
python
{ "resource": "" }
q242076
AliasNode.get_transformer
train
def get_transformer(cls, method_name): """Get method to bind to visitor""" transform_function = getattr(cls, method_name) assert callable(transform_function) def transformer_method(self, node): kwargs = {} if inspect.signature(transform_function).parameters.get("...
python
{ "resource": "" }
q242077
BaseAstVisitor.visitTerminal
train
def visitTerminal(self, ctx): """Converts case insensitive keywords and identifiers to lowercase""" text = ctx.getText() return Terminal.from_text(text, ctx)
python
{ "resource": "" }
q242078
Blacklist.run
train
def run(self, *args): """List, add or delete entries from the blacklist. By default, it prints the list of entries available on the blacklist. """ params = self.parser.parse_args(args) entry = params.entry if params.add: code = self.add(entry) ...
python
{ "resource": "" }
q242079
Blacklist.add
train
def add(self, entry): """Add entries to the blacklist. This method adds the given 'entry' to the blacklist. :param entry: entry to add to the blacklist """ # Empty or None values for organizations are not allowed if not entry: return CMD_SUCCESS try...
python
{ "resource": "" }
q242080
Blacklist.delete
train
def delete(self, entry): """Remove entries from the blacklist. The method removes the given 'entry' from the blacklist. :param entry: entry to remove from the blacklist """ if not entry: return CMD_SUCCESS try: api.delete_from_matching_blacklist...
python
{ "resource": "" }
q242081
Blacklist.blacklist
train
def blacklist(self, term=None): """List blacklisted entries. When no term is given, the method will list the entries that exist in the blacklist. If 'term' is set, the method will list only those entries that match with that term. :param term: term to match """ ...
python
{ "resource": "" }
q242082
Config.run
train
def run(self, *args): """Get and set configuration parameters. This command gets or sets parameter values from the user configuration file. On Linux systems, configuration will be stored in the file '~/.sortinghat'. """ params = self.parser.parse_args(args) conf...
python
{ "resource": "" }
q242083
Config.get
train
def get(self, key, filepath): """Get configuration parameter. Reads 'key' configuration parameter from the configuration file given in 'filepath'. Configuration parameter in 'key' must follow the schema <section>.<option> . :param key: key to get :param filepath: config...
python
{ "resource": "" }
q242084
Config.set
train
def set(self, key, value, filepath): """Set configuration parameter. Writes 'value' on 'key' to the configuration file given in 'filepath'. Configuration parameter in 'key' must follow the schema <section>.<option> . :param key: key to set :param value: value to set ...
python
{ "resource": "" }
q242085
Config.__check_config_key
train
def __check_config_key(self, key): """Check whether the key is valid. A valid key has the schema <section>.<option>. Keys supported are listed in CONFIG_OPTIONS dict. :param key: <section>.<option> key """ try: section, option = key.split('.') except...
python
{ "resource": "" }
q242086
Export.run
train
def run(self, *args): """Export data from the registry. By default, it writes the data to the standard output. If a positional argument is given, it will write the data on that file. """ params = self.parser.parse_args(args) with params.outfile as outfile: ...
python
{ "resource": "" }
q242087
Export.export_identities
train
def export_identities(self, outfile, source=None): """Export identities information to a file. The method exports information related to unique identities, to the given 'outfile' output file. When 'source' parameter is given, only those unique identities which have one or more ...
python
{ "resource": "" }
q242088
Export.export_organizations
train
def export_organizations(self, outfile): """Export organizations information to a file. The method exports information related to organizations, to the given 'outfile' output file. :param outfile: destination file object """ exporter = SortingHatOrganizationsExporter(se...
python
{ "resource": "" }
q242089
SortingHatIdentitiesExporter.export
train
def export(self, source=None): """Export a set of unique identities. Method to export unique identities from the registry. Identities schema will follow Sorting Hat JSON format. When source parameter is given, only those unique identities which have one or more identities from ...
python
{ "resource": "" }
q242090
SortingHatOrganizationsExporter.export
train
def export(self): """Export a set of organizations. Method to export organizations from the registry. Organizations schema will follow Sorting Hat JSON format. :returns: a JSON formatted str """ organizations = {} orgs = api.registry(self.db) for org i...
python
{ "resource": "" }
q242091
AutoProfile.run
train
def run(self, *args): """Autocomplete profile information.""" params = self.parser.parse_args(args) sources = params.source code = self.autocomplete(sources) return code
python
{ "resource": "" }
q242092
AutoProfile.autocomplete
train
def autocomplete(self, sources): """Autocomplete unique identities profiles. Autocomplete unique identities profiles using the information of their identities. The selection of the data used to fill the profile is prioritized using a list of sources. """ email_pattern = ...
python
{ "resource": "" }
q242093
AutoProfile.__select_autocomplete_identities
train
def __select_autocomplete_identities(self, sources): """Select the identities used for autocompleting""" MIN_PRIORITY = 99999999 checked = {} for source in sources: uids = api.unique_identities(self.db, source=source) for uid in uids: if uid.uu...
python
{ "resource": "" }
q242094
Show.run
train
def run(self, *args): """Show information about unique identities.""" params = self.parser.parse_args(args) code = self.show(params.uuid, params.term) return code
python
{ "resource": "" }
q242095
Show.show
train
def show(self, uuid=None, term=None): """Show the information related to unique identities. This method prints information related to unique identities such as identities or enrollments. When <uuid> is given, it will only show information about the unique identity related to <u...
python
{ "resource": "" }
q242096
StackalyticsParser.__parse_organizations
train
def __parse_organizations(self, json): """Parse Stackalytics organizations. The Stackalytics organizations format is a JSON document stored under the "companies" key. The next JSON shows the structure of the document: { "companies" : [ { ...
python
{ "resource": "" }
q242097
StackalyticsParser.__parse_identities
train
def __parse_identities(self, json): """Parse identities using Stackalytics format. The Stackalytics identities format is a JSON document under the "users" key. The document should follow the next schema: { "users": [ { "launchpad_id": "0-...
python
{ "resource": "" }
q242098
StackalyticsParser.__parse_enrollments
train
def __parse_enrollments(self, user): """Parse user enrollments""" enrollments = [] for company in user['companies']: name = company['company_name'] org = self._organizations.get(name, None) if not org: org = Organization(name=name) ...
python
{ "resource": "" }
q242099
StackalyticsParser.__load_json
train
def __load_json(self, stream): """Load json stream into a dict object """ import json try: return json.loads(stream) except ValueError as e: cause = "invalid json format. %s" % str(e) raise InvalidFormatError(cause=cause)
python
{ "resource": "" }