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def fake2db_mysql_initiator(self, host, port, password, username, number_of_rows, name=None, custom=None): '''Main handler for the operation ''' rows = number_of_rows if name: cursor, conn = self.database_caller_creator(host, port, password, username, name) else: cursor, conn = self.database_caller_creator(host, port, password, username) if custom: self.custom_db_creator(rows, cursor, conn, custom) cursor.close() conn.close() sys.exit(0) tables = self.mysql_table_creator() keys = tables.keys() for key in keys: try: cursor.execute(tables[key]) conn.commit() except mysql.connector.Error as err: logger.error(err.msg, extra=extra_information) else: logger.info("OK", extra=extra_information) logger.warning('Table creation ops finished', extra=extra_information) self.data_filler_simple_registration(rows, cursor, conn) self.data_filler_detailed_registration(rows, cursor, conn) self.data_filler_company(rows, cursor, conn) self.data_filler_user_agent(rows, cursor, conn) self.data_filler_customer(rows, cursor, conn) cursor.close() conn.close()
Main handler for the operation
def save_config( self, cmd="save configuration primary", confirm=False, confirm_response="" ): """Saves configuration.""" return super(ExtremeExosBase, self).save_config( cmd=cmd, confirm=confirm, confirm_response=confirm_response )
Saves configuration.
def view_plugins(category=None): """ return a view of the loaded plugin names and descriptions Parameters ---------- category : None or str if str, apply for single plugin category Examples -------- >>> from pprint import pprint >>> pprint(view_plugins()) {'decoders': {}, 'encoders': {}, 'parsers': {}} >>> class DecoderPlugin(object): ... plugin_name = 'example' ... plugin_descript = 'a decoder for dicts containing _example_ key' ... dict_signature = ('_example_',) ... >>> errors = load_plugin_classes([DecoderPlugin]) >>> pprint(view_plugins()) {'decoders': {'example': 'a decoder for dicts containing _example_ key'}, 'encoders': {}, 'parsers': {}} >>> view_plugins('decoders') {'example': 'a decoder for dicts containing _example_ key'} >>> unload_all_plugins() """ if category is not None: if category == 'parsers': return { name: {"descript": klass.plugin_descript, "regex": klass.file_regex} for name, klass in _all_plugins[category].items() } return { name: klass.plugin_descript for name, klass in _all_plugins[category].items() } else: return {cat: {name: klass.plugin_descript for name, klass in plugins.items()} for cat, plugins in _all_plugins.items()}
return a view of the loaded plugin names and descriptions Parameters ---------- category : None or str if str, apply for single plugin category Examples -------- >>> from pprint import pprint >>> pprint(view_plugins()) {'decoders': {}, 'encoders': {}, 'parsers': {}} >>> class DecoderPlugin(object): ... plugin_name = 'example' ... plugin_descript = 'a decoder for dicts containing _example_ key' ... dict_signature = ('_example_',) ... >>> errors = load_plugin_classes([DecoderPlugin]) >>> pprint(view_plugins()) {'decoders': {'example': 'a decoder for dicts containing _example_ key'}, 'encoders': {}, 'parsers': {}} >>> view_plugins('decoders') {'example': 'a decoder for dicts containing _example_ key'} >>> unload_all_plugins()
def publish_message(self, exchange, routing_key, properties, body, no_serialization=False, no_encoding=False, channel=None, connection=None): """Publish a message to RabbitMQ on the same channel the original message was received on. By default, if you pass a non-string object to the body and the properties have a supported ``content_type`` set, the body will be auto-serialized in the specified ``content_type``. If the properties do not have a timestamp set, it will be set to the current time. If you specify a ``content_encoding`` in the properties and the encoding is supported, the body will be auto-encoded. Both of these behaviors can be disabled by setting ``no_serialization`` or ``no_encoding`` to ``True``. If you pass an unsupported content-type or content-encoding when using the auto-serialization and auto-encoding features, a :exc:`ValueError` will be raised. .. versionchanged:: 4.0.0 The method returns a :py:class:`~tornado.concurrent.Future` if `publisher confirmations <https://www.rabbitmq.com/confirms.html>`_ are enabled on for the connection. In addition, The ``channel`` parameter is deprecated and will be removed in a future release. :param str exchange: The exchange to publish to :param str routing_key: The routing key to publish with :param dict properties: The message properties :param mixed body: The message body to publish :param bool no_serialization: Turn off auto-serialization of the body :param bool no_encoding: Turn off auto-encoding of the body :param str channel: **Deprecated in 4.0.0** Specify the connection parameter instead. :param str connection: The connection to use. If it is not specified, the channel that the message was delivered on is used. :rtype: tornado.concurrent.Future or None :raises: ValueError """ # Auto-serialize the content if needed is_string = (isinstance(body, str) or isinstance(body, bytes) or isinstance(body, unicode)) if not no_serialization and not is_string and \ properties.get('content_type'): body = self._serialize( body, headers.parse_content_type(properties['content_type'])) # Auto-encode the message body if needed if not no_encoding and \ properties.get('content_encoding') in self._CODEC_MAP.keys(): body = self._compress( body, self._CODEC_MAP[properties['content_encoding']]) return super(SmartConsumer, self).publish_message( exchange, routing_key, properties, body, channel or connection)
Publish a message to RabbitMQ on the same channel the original message was received on. By default, if you pass a non-string object to the body and the properties have a supported ``content_type`` set, the body will be auto-serialized in the specified ``content_type``. If the properties do not have a timestamp set, it will be set to the current time. If you specify a ``content_encoding`` in the properties and the encoding is supported, the body will be auto-encoded. Both of these behaviors can be disabled by setting ``no_serialization`` or ``no_encoding`` to ``True``. If you pass an unsupported content-type or content-encoding when using the auto-serialization and auto-encoding features, a :exc:`ValueError` will be raised. .. versionchanged:: 4.0.0 The method returns a :py:class:`~tornado.concurrent.Future` if `publisher confirmations <https://www.rabbitmq.com/confirms.html>`_ are enabled on for the connection. In addition, The ``channel`` parameter is deprecated and will be removed in a future release. :param str exchange: The exchange to publish to :param str routing_key: The routing key to publish with :param dict properties: The message properties :param mixed body: The message body to publish :param bool no_serialization: Turn off auto-serialization of the body :param bool no_encoding: Turn off auto-encoding of the body :param str channel: **Deprecated in 4.0.0** Specify the connection parameter instead. :param str connection: The connection to use. If it is not specified, the channel that the message was delivered on is used. :rtype: tornado.concurrent.Future or None :raises: ValueError
def set_editor_doc(self, doc, force_refresh=False): """ Use the help plugin to show docstring dictionary computed with introspection plugin from the Editor plugin """ if (self.locked and not force_refresh): return self.switch_to_editor_source() self._last_editor_doc = doc self.object_edit.setText(doc['obj_text']) if self.rich_help: self.render_sphinx_doc(doc) else: self.set_plain_text(doc, is_code=False) if self.dockwidget is not None: self.dockwidget.blockSignals(True) self.__eventually_raise_help(doc['docstring'], force=force_refresh) if self.dockwidget is not None: self.dockwidget.blockSignals(False)
Use the help plugin to show docstring dictionary computed with introspection plugin from the Editor plugin
def is_valid_ip_pattern(ip): """Check whether a string matches the outline of an IPv4 address, allowing "*" as a wildcard""" ip = ip.replace('*', '1') try: socket.inet_aton(ip) return True except socket.error: # Not a valid IPv4 address pattern return False
Check whether a string matches the outline of an IPv4 address, allowing "*" as a wildcard
def draw(self): """ Renders ROC-AUC plot. Called internally by score, possibly more than once Returns ------- ax : the axis with the plotted figure """ colors = self.colors[0:len(self.classes_)] n_classes = len(colors) # If it's a binary decision, plot the single ROC curve if self._binary_decision == True: self.ax.plot( self.fpr[0], self.tpr[0], label='ROC for binary decision, AUC = {:0.2f}'.format( self.roc_auc[0] ) ) # If per-class plotting is requested, plot ROC curves for each class if self.per_class: for i, color in zip(range(n_classes), colors): self.ax.plot( self.fpr[i], self.tpr[i], color=color, label='ROC of class {}, AUC = {:0.2f}'.format( self.classes_[i], self.roc_auc[i], ) ) # If requested, plot the ROC curve for the micro average if self.micro: self.ax.plot( self.fpr[MICRO], self.tpr[MICRO], linestyle="--", color= self.colors[len(self.classes_)-1], label='micro-average ROC curve, AUC = {:0.2f}'.format( self.roc_auc["micro"], ) ) # If requested, plot the ROC curve for the macro average if self.macro: self.ax.plot( self.fpr[MACRO], self.tpr[MACRO], linestyle="--", color= self.colors[len(self.classes_)-1], label='macro-average ROC curve, AUC = {:0.2f}'.format( self.roc_auc["macro"], ) ) # Plot the line of no discrimination to compare the curve to. self.ax.plot([0,1], [0,1], linestyle=':', c=LINE_COLOR) return self.ax
Renders ROC-AUC plot. Called internally by score, possibly more than once Returns ------- ax : the axis with the plotted figure
def fmt_number(p): """Format a number. It will be printed as a fraction if the denominator isn't too big and as a decimal otherwise. """ formatted = '{:n}'.format(p) if not config.PRINT_FRACTIONS: return formatted fraction = Fraction(p) nice = fraction.limit_denominator(128) return ( str(nice) if (abs(fraction - nice) < constants.EPSILON and nice.denominator in NICE_DENOMINATORS) else formatted )
Format a number. It will be printed as a fraction if the denominator isn't too big and as a decimal otherwise.
def clear_callbacks(obj): """Remove all callbacks from an object.""" callbacks = obj._callbacks if isinstance(callbacks, dllist): # Help the garbage collector by clearing all links. callbacks.clear() obj._callbacks = None
Remove all callbacks from an object.
def get_option(self, key, subkey, in_path_none=False): """Get the current value of the option. :param str key: First identifier of the option. :param str subkey: Second identifier of the option. :param bool in_path_none: Allows for ``in_path`` values of :data:`None` to be retrieved. :return: Current value of the option (type varies). :raise: :NotRegisteredError: If ``key`` or ``subkey`` do not define any option. :ValueError: If a ``in_path`` type with :data:`None` value is requested. """ key, subkey = _lower_keys(key, subkey) _entry_must_exist(self.gc, key, subkey) df = self.gc[(self.gc["k1"] == key) & (self.gc["k2"] == subkey)] if df["type"].values[0] == "bool": return bool(df["value"].values[0]) elif df["type"].values[0] == "int": return int(df["value"].values[0]) elif df["type"].values[0] == "path_in": if df["value"].values[0] is None and not in_path_none: raise ValueError('Unspecified path for {0}.{1}'.format(key, subkey)) return df["value"].values[0] else: return df["value"].values[0]
Get the current value of the option. :param str key: First identifier of the option. :param str subkey: Second identifier of the option. :param bool in_path_none: Allows for ``in_path`` values of :data:`None` to be retrieved. :return: Current value of the option (type varies). :raise: :NotRegisteredError: If ``key`` or ``subkey`` do not define any option. :ValueError: If a ``in_path`` type with :data:`None` value is requested.
def save_hdf(self,filename,path=''): """Save to .h5 file. """ self.orbpop_long.save_hdf(filename,'{}/long'.format(path)) self.orbpop_short.save_hdf(filename,'{}/short'.format(path))
Save to .h5 file.
def entity_delete(args): """ Delete entity in a workspace. """ msg = "WARNING: this will delete {0} {1} in {2}/{3}".format( args.entity_type, args.entity, args.project, args.workspace) if not (args.yes or _confirm_prompt(msg)): return json_body=[{"entityType": args.entity_type, "entityName": args.entity}] r = fapi.delete_entities(args.project, args.workspace, json_body) fapi._check_response_code(r, 204) if fcconfig.verbosity: print("Succesfully deleted " + args.type + " " + args.entity)
Delete entity in a workspace.
def t_heredocvar_ENCAPSED_AND_WHITESPACE(t): r'( [^\n\\${] | \\. | \$(?![A-Za-z_{]) | \{(?!\$) )+\n? | \\?\n' t.lexer.lineno += t.value.count("\n") t.lexer.pop_state() return t
r'( [^\n\\${] | \\. | \$(?![A-Za-z_{]) | \{(?!\$) )+\n? | \\?\n
def append_to_arg_count(self, data): """ Add digit to the input argument. :param data: the typed digit as string """ assert data in '-0123456789' current = self._arg if data == '-': assert current is None or current == '-' result = data elif current is None: result = data else: result = "%s%s" % (current, data) self.input_processor.arg = result
Add digit to the input argument. :param data: the typed digit as string
def validate(self): """ Validates the state of this XBlock. Subclasses should override validate_field_data() to validate fields and override this only for validation not related to this block's field values. """ validation = super(StudioEditableXBlockMixin, self).validate() self.validate_field_data(validation, self) return validation
Validates the state of this XBlock. Subclasses should override validate_field_data() to validate fields and override this only for validation not related to this block's field values.
def flash(self, duration=0.0): """ Flash a group. :param duration: How quickly to flash (in seconds). """ for _ in range(2): self.on = not self.on time.sleep(duration)
Flash a group. :param duration: How quickly to flash (in seconds).
def fetch_post_data(self): ''' fetch post accessed data. post_data, and ext_dic. ''' post_data = {} ext_dic = {} for key in self.request.arguments: if key.startswith('def_'): ext_dic[key] = self.get_argument(key) else: post_data[key] = self.get_arguments(key)[0] post_data['user_name'] = self.userinfo.user_name ext_dic = dict(ext_dic, **self.ext_post_data(postdata=post_data)) return (post_data, ext_dic)
fetch post accessed data. post_data, and ext_dic.
def process_entry(self, defect_entry): """ Process a given Defect entry with qualifiers given from initialization of class. Order of processing is: 1) perform all possible defect corrections with information given 2) consider delocalization analyses based on qualifier metrics given initialization of class. If delocalized, flag entry as delocalized 3) update corrections to defect entry and flag as del Corrections are applied based on: i) if free charges are more than free_chg_cutoff then will not apply charge correction, because it no longer is applicable ii) use charge correction set by preferred_cc iii) only use BandFilling correction if use_bandfilling is set to True iv) only use BandEdgeShift correction if use_bandedgeshift is set to True """ self.perform_all_corrections(defect_entry) self.delocalization_analysis(defect_entry) # apply corrections based on delocalization analysis corrections = {} skip_charge_corrections = False if "num_hole_vbm" in defect_entry.parameters.keys(): if (self.free_chg_cutoff < defect_entry.parameters["num_hole_vbm"]) or ( self.free_chg_cutoff < defect_entry.parameters["num_elec_cbm"]): print('Will not use charge correction because too many free charges') # TODO: should the potential alignment correction still be used in this scenario? # TODO: with too much charge delocalized should probably not use? skip_charge_corrections = True if skip_charge_corrections: corrections.update({'charge_correction': 0.}) else: if ('freysoldt' in self.preferred_cc.lower()) and ('freysoldt_meta' in defect_entry.parameters.keys()): frey_meta = defect_entry.parameters['freysoldt_meta'] frey_corr = frey_meta["freysoldt_electrostatic"] + frey_meta["freysoldt_potential_alignment_correction"] corrections.update({'charge_correction': frey_corr}) elif ('kumagai_meta' in defect_entry.parameters.keys()): kumagai_meta = defect_entry.parameters['kumagai_meta'] kumagai_corr = kumagai_meta["kumagai_electrostatic"] + \ kumagai_meta["kumagai_potential_alignment_correction"] corrections.update({'charge_correction': kumagai_corr}) else: print('Could not use any charge correction because insufficient metadata was supplied.') if self.use_bandfilling: if "bandfilling_meta" in defect_entry.parameters.keys(): bfc_corr = defect_entry.parameters["bandfilling_meta"]["bandfilling_correction"] corrections.update({'bandfilling_correction': bfc_corr}) else: print('Could not use band filling correction because insufficient metadata was supplied.') else: corrections.update({'bandfilling_correction': 0.}) if self.use_bandedgeshift: if "bandshift_meta" in defect_entry.parameters.keys(): bandfill_meta = defect_entry.parameters["bandshift_meta"] bes_corr = bandfill_meta["vbm_shift_correction"] + bandfill_meta["hole_vbm_shift_correction"] + \ bandfill_meta["elec_cbm_shift_correction"] corrections.update({'bandedgeshifting_correction': bes_corr}) # also want to update relevant data for phase diagram defect_entry.parameters.update({ 'phasediagram_meta': { 'vbm': defect_entry.parameters['hybrid_vbm'], 'gap': defect_entry.parameters['hybrid_cbm'] - defect_entry.parameters['hybrid_vbm'] } }) else: print("Could not use band edge shifting correction because insufficient metadata was supplied.") defect_entry.parameters.update({ 'phasediagram_meta': { 'vbm': defect_entry.parameters['vbm'], 'gap': defect_entry.parameters['cbm'] - defect_entry.parameters['vbm'] } }) else: # if not using bandedge shift -> still want to have vbm and gap ready for phase diagram corrections.update({'bandedgeshifting_correction': 0.}) defect_entry.parameters.update({ 'phasediagram_meta': { 'vbm': defect_entry.parameters['vbm'], 'gap': defect_entry.parameters['cbm'] - defect_entry.parameters['vbm'] } }) defect_entry.corrections.update(corrections) return defect_entry
Process a given Defect entry with qualifiers given from initialization of class. Order of processing is: 1) perform all possible defect corrections with information given 2) consider delocalization analyses based on qualifier metrics given initialization of class. If delocalized, flag entry as delocalized 3) update corrections to defect entry and flag as del Corrections are applied based on: i) if free charges are more than free_chg_cutoff then will not apply charge correction, because it no longer is applicable ii) use charge correction set by preferred_cc iii) only use BandFilling correction if use_bandfilling is set to True iv) only use BandEdgeShift correction if use_bandedgeshift is set to True
def hashdata(self, subject): _data = bytearray() if isinstance(subject, six.string_types): subject = subject.encode('charmap') """ All signatures are formed by producing a hash over the signature data, and then using the resulting hash in the signature algorithm. """ if self.type == SignatureType.BinaryDocument: """ For binary document signatures (type 0x00), the document data is hashed directly. """ if isinstance(subject, (SKEData, IntegrityProtectedSKEData)): _data += subject.__bytearray__() else: _data += bytearray(subject) if self.type == SignatureType.CanonicalDocument: """ For text document signatures (type 0x01), the document is canonicalized by converting line endings to <CR><LF>, and the resulting data is hashed. """ _data += re.subn(br'\r?\n', b'\r\n', subject)[0] if self.type in {SignatureType.Generic_Cert, SignatureType.Persona_Cert, SignatureType.Casual_Cert, SignatureType.Positive_Cert, SignatureType.CertRevocation, SignatureType.Subkey_Binding, SignatureType.PrimaryKey_Binding}: """ When a signature is made over a key, the hash data starts with the octet 0x99, followed by a two-octet length of the key, and then body of the key packet. (Note that this is an old-style packet header for a key packet with two-octet length.) ... Key revocation signatures (types 0x20 and 0x28) hash only the key being revoked. """ _s = b'' if isinstance(subject, PGPUID): _s = subject._parent.hashdata elif isinstance(subject, PGPKey) and not subject.is_primary: _s = subject._parent.hashdata elif isinstance(subject, PGPKey) and subject.is_primary: _s = subject.hashdata if len(_s) > 0: _data += b'\x99' + self.int_to_bytes(len(_s), 2) + _s if self.type in {SignatureType.Subkey_Binding, SignatureType.PrimaryKey_Binding}: """ A subkey binding signature (type 0x18) or primary key binding signature (type 0x19) then hashes the subkey using the same format as the main key (also using 0x99 as the first octet). """ if subject.is_primary: _s = subject.subkeys[self.signer].hashdata else: _s = subject.hashdata _data += b'\x99' + self.int_to_bytes(len(_s), 2) + _s if self.type in {SignatureType.KeyRevocation, SignatureType.SubkeyRevocation, SignatureType.DirectlyOnKey}: """ The signature is calculated directly on the key being revoked. A revoked key is not to be used. Only revocation signatures by the key being revoked, or by an authorized revocation key, should be considered valid revocation signatures. Subkey revocation signature The signature is calculated directly on the subkey being revoked. A revoked subkey is not to be used. Only revocation signatures by the top-level signature key that is bound to this subkey, or by an authorized revocation key, should be considered valid revocation signatures. - clarification from draft-ietf-openpgp-rfc4880bis-02: Primary key revocation signatures (type 0x20) hash only the key being revoked. Subkey revocation signature (type 0x28) hash first the primary key and then the subkey being revoked Signature directly on a key This signature is calculated directly on a key. It binds the information in the Signature subpackets to the key, and is appropriate to be used for subpackets that provide information about the key, such as the Revocation Key subpacket. It is also appropriate for statements that non-self certifiers want to make about the key itself, rather than the binding between a key and a name. """ if self.type == SignatureType.SubkeyRevocation: # hash the primary key first if this is a Subkey Revocation signature _s = subject.parent.hashdata _data += b'\x99' + self.int_to_bytes(len(_s), 2) + _s _s = subject.hashdata _data += b'\x99' + self.int_to_bytes(len(_s), 2) + _s if self.type in {SignatureType.Generic_Cert, SignatureType.Persona_Cert, SignatureType.Casual_Cert, SignatureType.Positive_Cert, SignatureType.CertRevocation}: """ A certification signature (type 0x10 through 0x13) hashes the User ID being bound to the key into the hash context after the above data. ... A V4 certification hashes the constant 0xB4 for User ID certifications or the constant 0xD1 for User Attribute certifications, followed by a four-octet number giving the length of the User ID or User Attribute data, and then the User ID or User Attribute data. ... The [certificate revocation] signature is computed over the same data as the certificate that it revokes, and should have a later creation date than that certificate. """ _s = subject.hashdata if subject.is_uid: _data += b'\xb4' else: _data += b'\xd1' _data += self.int_to_bytes(len(_s), 4) + _s # if this is a new signature, do update_hlen if 0 in list(self._signature.signature): self._signature.update_hlen() """ Once the data body is hashed, then a trailer is hashed. (...) A V4 signature hashes the packet body starting from its first field, the version number, through the end of the hashed subpacket data. Thus, the fields hashed are the signature version, the signature type, the public-key algorithm, the hash algorithm, the hashed subpacket length, and the hashed subpacket body. V4 signatures also hash in a final trailer of six octets: the version of the Signature packet, i.e., 0x04; 0xFF; and a four-octet, big-endian number that is the length of the hashed data from the Signature packet (note that this number does not include these final six octets). """ hcontext = bytearray() hcontext.append(self._signature.header.version if not self.embedded else self._signature._sig.header.version) hcontext.append(self.type) hcontext.append(self.key_algorithm) hcontext.append(self.hash_algorithm) hcontext += self._signature.subpackets.__hashbytearray__() hlen = len(hcontext) _data += hcontext _data += b'\x04\xff' _data += self.int_to_bytes(hlen, 4) return bytes(_data)
All signatures are formed by producing a hash over the signature data, and then using the resulting hash in the signature algorithm.
def local_filename( self, url=None, filename=None, decompress=False): """ What local filename will we use within the cache directory for the given URL/filename/decompress options. """ return common.build_local_filename(url, filename, decompress)
What local filename will we use within the cache directory for the given URL/filename/decompress options.
def correspondent_id(self): """ :returns: The id assigned to the correspondent of this message. """ try: return int(self._thread_element.attrib['data-personid']) except (ValueError, KeyError): try: return int(self.correspondent_profile.id) except: pass
:returns: The id assigned to the correspondent of this message.
def hourly_solar_radiation(self): """Three data collections containing hourly direct normal, diffuse horizontal, and global horizontal radiation. """ dir_norm, diff_horiz, glob_horiz = \ self._sky_condition.radiation_values(self._location) dir_norm_data = self._get_daily_data_collections( energyintensity.DirectNormalRadiation(), 'Wh/m2', dir_norm) diff_horiz_data = self._get_daily_data_collections( energyintensity.DiffuseHorizontalRadiation(), 'Wh/m2', diff_horiz) glob_horiz_data = self._get_daily_data_collections( energyintensity.GlobalHorizontalRadiation(), 'Wh/m2', glob_horiz) return dir_norm_data, diff_horiz_data, glob_horiz_data
Three data collections containing hourly direct normal, diffuse horizontal, and global horizontal radiation.
def write_gtiff_file(f_name, n_rows, n_cols, data, geotransform, srs, nodata_value, gdal_type=GDT_Float32): """Output Raster to GeoTiff format file. Args: f_name: output gtiff file name. n_rows: Row count. n_cols: Col count. data: 2D array data. geotransform: geographic transformation. srs: coordinate system. nodata_value: nodata value. gdal_type (:obj:`pygeoc.raster.GDALDataType`): output raster data type, GDT_Float32 as default. """ UtilClass.mkdir(os.path.dirname(FileClass.get_file_fullpath(f_name))) driver = gdal_GetDriverByName(str('GTiff')) try: ds = driver.Create(f_name, n_cols, n_rows, 1, gdal_type) except Exception: print('Cannot create output file %s' % f_name) return ds.SetGeoTransform(geotransform) try: ds.SetProjection(srs.ExportToWkt()) except AttributeError or Exception: ds.SetProjection(srs) ds.GetRasterBand(1).SetNoDataValue(nodata_value) # if data contains numpy.nan, then replaced by nodata_value if isinstance(data, numpy.ndarray) and data.dtype in [numpy.dtype('int'), numpy.dtype('float')]: data = numpy.where(numpy.isnan(data), nodata_value, data) ds.GetRasterBand(1).WriteArray(data) ds = None
Output Raster to GeoTiff format file. Args: f_name: output gtiff file name. n_rows: Row count. n_cols: Col count. data: 2D array data. geotransform: geographic transformation. srs: coordinate system. nodata_value: nodata value. gdal_type (:obj:`pygeoc.raster.GDALDataType`): output raster data type, GDT_Float32 as default.
def is_valid_catalog(catalog, validator=None): """Valida que un archivo `data.json` cumpla con el schema definido. Chequea que el data.json tiene todos los campos obligatorios y que tanto los campos obligatorios como los opcionales siguen la estructura definida en el schema. Args: catalog (str o dict): Catálogo (dict, JSON o XLSX) a ser validado. Returns: bool: True si el data.json cumple con el schema, sino False. """ catalog = readers.read_catalog(catalog) if not validator: if hasattr(catalog, "validator"): validator = catalog.validator else: validator = create_validator() jsonschema_res = validator.is_valid(catalog) custom_errors = iter_custom_errors(catalog) return jsonschema_res and len(list(custom_errors)) == 0
Valida que un archivo `data.json` cumpla con el schema definido. Chequea que el data.json tiene todos los campos obligatorios y que tanto los campos obligatorios como los opcionales siguen la estructura definida en el schema. Args: catalog (str o dict): Catálogo (dict, JSON o XLSX) a ser validado. Returns: bool: True si el data.json cumple con el schema, sino False.
def _fix_next_url(next_url): """Remove max=null parameter from URL. Patch for Webex Teams Defect: 'next' URL returned in the Link headers of the responses contain an errant 'max=null' parameter, which causes the next request (to this URL) to fail if the URL is requested as-is. This patch parses the next_url to remove the max=null parameter. Args: next_url(basestring): The 'next' URL to be parsed and cleaned. Returns: basestring: The clean URL to be used for the 'next' request. Raises: AssertionError: If the parameter types are incorrect. ValueError: If 'next_url' does not contain a valid API endpoint URL (scheme, netloc and path). """ next_url = str(next_url) parsed_url = urllib.parse.urlparse(next_url) if not parsed_url.scheme or not parsed_url.netloc or not parsed_url.path: raise ValueError( "'next_url' must be a valid API endpoint URL, minimally " "containing a scheme, netloc and path." ) if parsed_url.query: query_list = parsed_url.query.split('&') if 'max=null' in query_list: query_list.remove('max=null') warnings.warn("`max=null` still present in next-URL returned " "from Webex Teams", RuntimeWarning) new_query = '&'.join(query_list) parsed_url = list(parsed_url) parsed_url[4] = new_query return urllib.parse.urlunparse(parsed_url)
Remove max=null parameter from URL. Patch for Webex Teams Defect: 'next' URL returned in the Link headers of the responses contain an errant 'max=null' parameter, which causes the next request (to this URL) to fail if the URL is requested as-is. This patch parses the next_url to remove the max=null parameter. Args: next_url(basestring): The 'next' URL to be parsed and cleaned. Returns: basestring: The clean URL to be used for the 'next' request. Raises: AssertionError: If the parameter types are incorrect. ValueError: If 'next_url' does not contain a valid API endpoint URL (scheme, netloc and path).
def get_region(self, ip): ''' Get region ''' rec = self.get_all(ip) return rec and rec.region
Get region
def choose_type(cls, content_type): """Choose object type from content type.""" return cls.type_cls.SUBDIR if content_type in cls.subdir_types \ else cls.type_cls.FILE
Choose object type from content type.
def plot_eeg_erp_topo(all_epochs, colors=None): """ Plot butterfly plot. DOCS INCOMPLETE :( """ all_evokeds = eeg_to_all_evokeds(all_epochs) data = {} for participant, epochs in all_evokeds.items(): for cond, epoch in epochs.items(): data[cond] = [] for participant, epochs in all_evokeds.items(): for cond, epoch in epochs.items(): data[cond].append(epoch) if colors is not None: color_list = [] else: color_list = None evokeds = [] for condition, evoked in data.items(): grand_average = mne.grand_average(evoked) grand_average.comment = condition evokeds += [grand_average] if colors is not None: color_list.append(colors[condition]) plot = mne.viz.plot_evoked_topo(evokeds, background_color="w", color=color_list) return(plot)
Plot butterfly plot. DOCS INCOMPLETE :(
def gcp_conn(service, service_type='client', future_expiration_minutes=15): """ service_type: not currently used. """ def decorator(f): @wraps(f) def decorated_function(*args, **kwargs): # Import here to avoid circular import issue from cloudaux.gcp.auth import get_client (conn_args, kwargs) = get_creds_from_kwargs(kwargs) client_details, client = get_client( service, service_type=service_type, future_expiration_minutes=15, **conn_args) if client_details: kwargs = rewrite_kwargs(client_details['client_type'], kwargs, client_details['module_name']) kwargs['client'] = client return f(*args, **kwargs) return decorated_function return decorator
service_type: not currently used.
def get_target_dimensions(self): """ Returns the target dimensions and calculates them if necessary. The target dimensions are display independent. :return: Target dimensions as a tuple (width, height) :rtype: (int, int) """ if self.target_height is None: self._calculate_target_dimensions() return int(self.target_width), int(self.target_height)
Returns the target dimensions and calculates them if necessary. The target dimensions are display independent. :return: Target dimensions as a tuple (width, height) :rtype: (int, int)
def __parse_config(self): """ Invoke the config file parser. """ if self.should_parse_config and (self.args.config or self.config_file): self.config = ConfigParser.SafeConfigParser() self.config.read(self.args.config or self.config_file)
Invoke the config file parser.
def lkendalltau(x,y): """ Calculates Kendall's tau ... correlation of ordinal data. Adapted from function kendl1 in Numerical Recipies. Needs good test-routine.@@@ Usage: lkendalltau(x,y) Returns: Kendall's tau, two-tailed p-value """ n1 = 0 n2 = 0 iss = 0 for j in range(len(x)-1): for k in range(j,len(y)): a1 = x[j] - x[k] a2 = y[j] - y[k] aa = a1 * a2 if (aa): # neither list has a tie n1 = n1 + 1 n2 = n2 + 1 if aa > 0: iss = iss + 1 else: iss = iss -1 else: if (a1): n1 = n1 + 1 else: n2 = n2 + 1 tau = iss / math.sqrt(n1*n2) svar = (4.0*len(x)+10.0) / (9.0*len(x)*(len(x)-1)) z = tau / math.sqrt(svar) prob = erfcc(abs(z)/1.4142136) return tau, prob
Calculates Kendall's tau ... correlation of ordinal data. Adapted from function kendl1 in Numerical Recipies. Needs good test-routine.@@@ Usage: lkendalltau(x,y) Returns: Kendall's tau, two-tailed p-value
def get_bel_versions() -> List[str]: """Get BEL Language versions supported Get the list of all BEL Language versions supported. The file this depends on is generated by belspec_yaml2json and is kept up to date using `make update_ebnf` or `make update_parsers`. You can also run `belspec_yaml2json` directly as it's added as a command by pip install. Returns: List[str]: list of versions """ spec_dir = config["bel"]["lang"]["specifications"] fn = f"{spec_dir}/versions.json" with open(fn, "r") as f: versions = json.load(f) return versions
Get BEL Language versions supported Get the list of all BEL Language versions supported. The file this depends on is generated by belspec_yaml2json and is kept up to date using `make update_ebnf` or `make update_parsers`. You can also run `belspec_yaml2json` directly as it's added as a command by pip install. Returns: List[str]: list of versions
def export(self, top=True): """Exports object to its string representation. Args: top (bool): if True appends `internal_name` before values. All non list objects should be exported with value top=True, all list objects, that are embedded in as fields inlist objects should be exported with `top`=False Returns: str: The objects string representation """ out = [] if top: out.append(self._internal_name) out.append(self._to_str(self.typical_or_extreme_period_name)) out.append(self._to_str(self.typical_or_extreme_period_type)) out.append(self._to_str(self.period_start_day)) out.append(self._to_str(self.period_end_day)) return ",".join(out)
Exports object to its string representation. Args: top (bool): if True appends `internal_name` before values. All non list objects should be exported with value top=True, all list objects, that are embedded in as fields inlist objects should be exported with `top`=False Returns: str: The objects string representation
def split_data(self): """ Split data according to baseline and projection time period values. """ try: # Extract data ranging in time_period1 time_period1 = (slice(self.baseline_period[0], self.baseline_period[1])) self.baseline_in = self.original_data.loc[time_period1, self.input_col] self.baseline_out = self.original_data.loc[time_period1, self.output_col] if self.exclude_time_period: for i in range(0, len(self.exclude_time_period), 2): # Drop data ranging in exclude_time_period1 exclude_time_period1 = (slice(self.exclude_time_period[i], self.exclude_time_period[i+1])) self.baseline_in.drop(self.baseline_in.loc[exclude_time_period1].index, axis=0, inplace=True) self.baseline_out.drop(self.baseline_out.loc[exclude_time_period1].index, axis=0, inplace=True) except Exception as e: raise e # CHECK: Can optimize this part # Error checking to ensure time_period values are valid if self.projection_period: for i in range(0, len(self.projection_period), 2): period = (slice(self.projection_period[i], self.projection_period[i+1])) try: self.original_data.loc[period, self.input_col] self.original_data.loc[period, self.output_col] except Exception as e: raise e
Split data according to baseline and projection time period values.
def check_engine(handle): """Check availability of requested template engine.""" if handle == 'help': dump_engines() sys.exit(0) if handle not in engines.engines: print('Engine "%s" is not available.' % (handle,), file=sys.stderr) sys.exit(1)
Check availability of requested template engine.
def _checkpoint_and_erase(self, trial): """Checkpoints the model and erases old checkpoints if needed. Parameters ---------- trial : trial to save """ with warn_if_slow("save_to_disk"): trial._checkpoint.value = ray.get(trial.runner.save.remote()) if len(trial.history) >= trial.keep_checkpoints_num: ray.get(trial.runner.delete_checkpoint.remote(trial.history[-1])) trial.history.pop() trial.history.insert(0, trial._checkpoint.value)
Checkpoints the model and erases old checkpoints if needed. Parameters ---------- trial : trial to save
def sample_given_context(self, c, c_dims): ''' Sample the region with max progress among regions that have the same context c: context value on c_dims dimensions c_dims: w.r.t sensory space dimensions ''' index = self.discrete_progress.sample_given_context(c, c_dims, self.space) return self.space.rand_value(index).flatten()[list(set(range(len(self.space.cardinalities))) - set(c_dims))]
Sample the region with max progress among regions that have the same context c: context value on c_dims dimensions c_dims: w.r.t sensory space dimensions
def registration(uri): """Responses handler registration. Registers a handler for a given URI with Responses so that it can be intercepted and handed to Stack-In-A-Box. :param uri: URI used for the base of the HTTP requests :returns: n/a """ # log the URI that is used to access the Stack-In-A-Box services logger.debug('Registering Stack-In-A-Box at {0} under Python Responses' .format(uri)) # tell Stack-In-A-Box what URI to match with StackInABox.update_uri(uri) # Build the regex for the URI and register all HTTP verbs # with Responses regex = re.compile('(http)?s?(://)?{0}:?(\d+)?/'.format(uri), re.I) METHODS = [ responses.DELETE, responses.GET, responses.HEAD, responses.OPTIONS, responses.PATCH, responses.POST, responses.PUT ] for method in METHODS: responses.add_callback(method, regex, callback=responses_callback)
Responses handler registration. Registers a handler for a given URI with Responses so that it can be intercepted and handed to Stack-In-A-Box. :param uri: URI used for the base of the HTTP requests :returns: n/a
def normalize(X, mean=None, std=None): """ Normalize X. If mean OR std is None, normalizes X to have mean 0 and std 1. """ if mean is None or std is None: mean = X.mean(0) std = X.std(0) return (X - mean) / std
Normalize X. If mean OR std is None, normalizes X to have mean 0 and std 1.
def column_max_width(self, column_number): """Return the maximum width of a column based on the current terminal width. :param int column_number: The column number to query. :return: The max width of the column. :rtype: int """ inner_widths = max_dimensions(self.table_data)[0] outer_border = 2 if self.outer_border else 0 inner_border = 1 if self.inner_column_border else 0 padding = self.padding_left + self.padding_right return column_max_width(inner_widths, column_number, outer_border, inner_border, padding)
Return the maximum width of a column based on the current terminal width. :param int column_number: The column number to query. :return: The max width of the column. :rtype: int
def inflate_analysis_group(self, identifier, definition): """ Inflate a whole analysis group. An analysis group is a section defined in the YAML file. Args: identifier (str): the group identifier. definition (list/dict): the group definition. Returns: AnalysisGroup: an instance of AnalysisGroup. Raises: ValueError: when identifier targets a plugin of a certain type, and the definition does not contain the entry for the other-type plugins (providers <-> checkers). """ providers_definition = definition.pop('providers', None) checkers_definition = definition.pop('checkers', None) analysis_group = AnalysisGroup() try: first_plugin = self.inflate_plugin(identifier, definition) if isinstance(first_plugin, Checker): analysis_group.checkers.append(first_plugin) if providers_definition is None: raise ValueError( 'when declaring an analysis group with a checker ' 'identifier, you must also declare providers with ' 'the "providers" key.') analysis_group.providers.extend( self.inflate_providers(providers_definition)) elif isinstance(first_plugin, Provider): analysis_group.providers.append(first_plugin) if checkers_definition is None: raise ValueError( 'when declaring an analysis group with a provider ' 'identifier, you must also declare checkers with ' 'the "checkers" key.') analysis_group.checkers.extend( self.inflate_checkers(checkers_definition)) except PluginNotFoundError as e: logger.warning( 'Could not find any plugin identified by %s, ' 'considering entry as group name. Exception: %s.', identifier, e) analysis_group.name = definition.pop('name', identifier) analysis_group.description = definition.pop('description', None) if bool(providers_definition) != bool(checkers_definition): raise ValueError( 'when declaring an analysis group with a name, you must ' 'either declare both "providers" and "checkers" or none.') if providers_definition and checkers_definition: analysis_group.providers.extend( self.inflate_providers(providers_definition)) analysis_group.checkers.extend( self.inflate_checkers(checkers_definition)) self.cleanup_definition(definition) for nd_identifier, nd_definition in definition.items(): analysis_group.checkers.append( self.inflate_nd_checker(nd_identifier, nd_definition)) return analysis_group
Inflate a whole analysis group. An analysis group is a section defined in the YAML file. Args: identifier (str): the group identifier. definition (list/dict): the group definition. Returns: AnalysisGroup: an instance of AnalysisGroup. Raises: ValueError: when identifier targets a plugin of a certain type, and the definition does not contain the entry for the other-type plugins (providers <-> checkers).
def enqueue_task(self, task): """Enqueues a task directly. This is used when a task is retried or if a task was manually created. Note that this does not store the task. """ data = dumps(task) if self._async: self.publisher_client.publish(self.topic_path, data=data) logger.info('Task {} queued.'.format(task.id)) else: unpickled_task = unpickle(data) logger.info( 'Executing task {} synchronously.'.format(unpickled_task.id) ) with measure_time() as summary, self.queue_context(): unpickled_task.execute(queue=self) summary(unpickled_task.summary()) return TaskResult(task.id, self)
Enqueues a task directly. This is used when a task is retried or if a task was manually created. Note that this does not store the task.
def get_wegobject_by_id(self, id): ''' Retrieve a `Wegobject` by the Id. :param integer id: the Id of the `Wegobject` :rtype: :class:`Wegobject` ''' def creator(): res = crab_gateway_request( self.client, 'GetWegobjectByIdentificatorWegobject', id ) if res == None: raise GatewayResourceNotFoundException() return Wegobject( res.IdentificatorWegobject, res.AardWegobject, (res.CenterX, res.CenterY), (res.MinimumX, res.MinimumY, res.MaximumX, res.MaximumY), Metadata( res.BeginDatum, res.BeginTijd, self.get_bewerking(res.BeginBewerking), self.get_organisatie(res.BeginOrganisatie) ) ) if self.caches['short'].is_configured: key = 'GetWegobjectByIdentificatorWegobject#%s' % (id) wegobject = self.caches['short'].get_or_create(key, creator) else: wegobject = creator() wegobject.set_gateway(self) return wegobject
Retrieve a `Wegobject` by the Id. :param integer id: the Id of the `Wegobject` :rtype: :class:`Wegobject`
def data_request(self, payload, timeout=TIMEOUT): """Perform a data_request and return the result.""" request_url = self.base_url + "/data_request" return requests.get(request_url, timeout=timeout, params=payload)
Perform a data_request and return the result.
def libvlc_audio_set_mute(p_mi, status): '''Set mute status. @param p_mi: media player. @param status: If status is true then mute, otherwise unmute @warning This function does not always work. If there are no active audio playback stream, the mute status might not be available. If digital pass-through (S/PDIF, HDMI...) is in use, muting may be unapplicable. Also some audio output plugins do not support muting at all. @note To force silent playback, disable all audio tracks. This is more efficient and reliable than mute. ''' f = _Cfunctions.get('libvlc_audio_set_mute', None) or \ _Cfunction('libvlc_audio_set_mute', ((1,), (1,),), None, None, MediaPlayer, ctypes.c_int) return f(p_mi, status)
Set mute status. @param p_mi: media player. @param status: If status is true then mute, otherwise unmute @warning This function does not always work. If there are no active audio playback stream, the mute status might not be available. If digital pass-through (S/PDIF, HDMI...) is in use, muting may be unapplicable. Also some audio output plugins do not support muting at all. @note To force silent playback, disable all audio tracks. This is more efficient and reliable than mute.
def markdown_filter(value, typogrify=True, extensions=('extra', 'codehilite')): """ A smart wrapper around the ``markdown`` and ``typogrify`` functions that automatically removes leading whitespace before every line. This is necessary because Markdown is whitespace-sensitive. Consider some Markdown content in a template that looks like this: .. codeblock:: html+jinja <article> {% filter markdown %} ## A Heading Some content here. Code goes here. More lines of code And more. Closing thoughts {% endfilter %} </article> In this example, a typical Markdown filter would see the leading whitespace before the first heading and assume it was a code block, which would then cause the entire Markdown document to be rendered incorrectly. You may have a document with spacing like this because your text editor automatically 'pretty-prints' the markup, including the content within the filter tag. This filter automatically removes the leading whitespace - leaving code block and other expected offsets in place of course - so that rendering occurs correctly regardless of the nested spacing of the source document. """ # Determine how many leading spaces there are, then remove that number from the beginning of each line. match = re.match(r'(\n*)(\s*)', value) s, e = match.span(2) pattern = re.compile(r'^ {%s}' % (e - s), # use ^ in the pattern so mid-string matches won't be removed flags=re.MULTILINE) # use multi-line mode so ^ will match the start of each line output = pattern.sub(u'', value) if typogrify: return jinja_filters.typogrify(markdown(output, extensions=extensions)) else: return markdown(output, extensions=extensions)
A smart wrapper around the ``markdown`` and ``typogrify`` functions that automatically removes leading whitespace before every line. This is necessary because Markdown is whitespace-sensitive. Consider some Markdown content in a template that looks like this: .. codeblock:: html+jinja <article> {% filter markdown %} ## A Heading Some content here. Code goes here. More lines of code And more. Closing thoughts {% endfilter %} </article> In this example, a typical Markdown filter would see the leading whitespace before the first heading and assume it was a code block, which would then cause the entire Markdown document to be rendered incorrectly. You may have a document with spacing like this because your text editor automatically 'pretty-prints' the markup, including the content within the filter tag. This filter automatically removes the leading whitespace - leaving code block and other expected offsets in place of course - so that rendering occurs correctly regardless of the nested spacing of the source document.
def list_build_configurations_for_product(id=None, name=None, page_size=200, page_index=0, sort="", q=""): """ List all BuildConfigurations associated with the given Product. """ data = list_build_configurations_for_product_raw(id, name, page_size, page_index, sort, q) if data: return utils.format_json_list(data)
List all BuildConfigurations associated with the given Product.
def get_timestamp(self, **kwargs): """Retrieves the timestamp for a given set of data""" timestamp = kwargs.get('timestamp') if not timestamp: now = datetime.datetime.utcnow() timestamp = now.strftime("%Y-%m-%dT%H:%M:%S") + ".%03d" % (now.microsecond / 1000) + "Z" return timestamp
Retrieves the timestamp for a given set of data
def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=10000, max_iters=300, optimize=True, plot=True): """ Show an example of a multimodal error surface for Gaussian process regression. Gene 939 has bimodal behaviour where the noisy mode is higher. """ # Contour over a range of length scales and signal/noise ratios. length_scales = np.linspace(0.1, 60., resolution) log_SNRs = np.linspace(-3., 4., resolution) try:import pods except ImportError: print('pods unavailable, see https://github.com/sods/ods for example datasets') return data = pods.datasets.della_gatta_TRP63_gene_expression(data_set='della_gatta',gene_number=gene_number) # data['Y'] = data['Y'][0::2, :] # data['X'] = data['X'][0::2, :] data['Y'] = data['Y'] - np.mean(data['Y']) lls = GPy.examples.regression._contour_data(data, length_scales, log_SNRs, GPy.kern.RBF) if plot: pb.contour(length_scales, log_SNRs, np.exp(lls), 20, cmap=pb.cm.jet) ax = pb.gca() pb.xlabel('length scale') pb.ylabel('log_10 SNR') xlim = ax.get_xlim() ylim = ax.get_ylim() # Now run a few optimizations models = [] optim_point_x = np.empty(2) optim_point_y = np.empty(2) np.random.seed(seed=seed) for i in range(0, model_restarts): # kern = GPy.kern.RBF(1, variance=np.random.exponential(1.), lengthscale=np.random.exponential(50.)) kern = GPy.kern.RBF(1, variance=np.random.uniform(1e-3, 1), lengthscale=np.random.uniform(5, 50)) m = GPy.models.GPRegression(data['X'], data['Y'], kernel=kern) m.likelihood.variance = np.random.uniform(1e-3, 1) optim_point_x[0] = m.rbf.lengthscale optim_point_y[0] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance); # optimize if optimize: m.optimize('scg', xtol=1e-6, ftol=1e-6, max_iters=max_iters) optim_point_x[1] = m.rbf.lengthscale optim_point_y[1] = np.log10(m.rbf.variance) - np.log10(m.likelihood.variance); if plot: pb.arrow(optim_point_x[0], optim_point_y[0], optim_point_x[1] - optim_point_x[0], optim_point_y[1] - optim_point_y[0], label=str(i), head_length=1, head_width=0.5, fc='k', ec='k') models.append(m) if plot: ax.set_xlim(xlim) ax.set_ylim(ylim) return m
Show an example of a multimodal error surface for Gaussian process regression. Gene 939 has bimodal behaviour where the noisy mode is higher.
def _populate_and_save_user_profile(self): """ Populates a User profile object with fields from the LDAP directory. """ try: app_label, class_name = django.conf.settings.AUTH_PROFILE_MODULE.split('.') profile_model = apps.get_model(app_label, class_name) profile, created = profile_model.objects.get_or_create(user=self._user) save_profile = False logger.debug("Populating Django user profile for %s", get_user_username(self._user)) save_profile = self._populate_profile_from_attributes(profile) or save_profile save_profile = self._populate_profile_flags_from_dn_regex(profile) or save_profile save_profile = self._populate_profile_from_group_memberships(profile) or save_profile signal_responses = populate_user_profile.send(self.backend.__class__, profile=profile, ldap_user=self) if len(signal_responses) > 0: save_profile = True if save_profile: profile.save() except ObjectDoesNotExist: logger.debug("Django user %s does not have a profile to populate", get_user_username(self._user)) except LookupError: logger.debug('User Profile model defined in settings.AUTH_PROFILE_MODULE is invalid')
Populates a User profile object with fields from the LDAP directory.
def listen_on_udp_port(): """listen_on_udp_port Run a simple server for processing messages over ``UDP``. ``UDP_LISTEN_ON_HOST`` - listen on this host ip address ``UDP_LISTEN_ON_PORT`` - listen on this ``UDP`` port ``UDP_LISTEN_SIZE`` - listen on to packets of this size ``UDP_LISTEN_SLEEP`` - sleep this number of seconds per loop ``UDP_LISTEN_SHUTDOWN_HOOK`` - shutdown if file is found on disk """ host = os.getenv( "UDP_LISTEN_ON_HOST", "127.0.0.1").strip().lstrip() port = int(os.getenv( "UDP_LISTEN_ON_PORT", "17000").strip().lstrip()) backlog = int(os.getenv( "UDP_LISTEN_BACKLOG", "5").strip().lstrip()) size = int(os.getenv( "UDP_LISTEN_SIZE", "1024").strip().lstrip()) sleep_in_seconds = float(os.getenv( "UDP_LISTEN_SLEEP", "0.5").strip().lstrip()) shutdown_hook = os.getenv( "UDP_LISTEN_SHUTDOWN_HOOK", "/tmp/udp-shutdown-listen-server-{}-{}".format( host, port)).strip().lstrip() if os.path.exists(shutdown_hook): print(("Please remove the UDP shutdown hook file: " "\nrm -f {}") .format(shutdown_hook)) sys.exit(1) now = datetime.datetime.now().isoformat() print(("{} - Starting UDP Server address={}:{} " "backlog={} size={} sleep={} shutdown={}") .format( now, host, port, backlog, size, sleep_in_seconds, shutdown_hook)) s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) s.bind((host, port)) msg = 0 while 1: data = None address = None data, address = s.recvfrom(4096) if data: now = datetime.datetime.now().isoformat() print(("{} received UDP data={} ") .format( now, data)) msg += 1 if msg > 1000000: msg = 0 # if address: # client.sendto("PROCESSED", address) else: time.sleep(sleep_in_seconds) if os.path.exists(shutdown_hook): now = datetime.datetime.now().isoformat() print(("{} detected shutdown " "file={}") .format( now, shutdown_hook)) # end of loop print("Shutting down")
listen_on_udp_port Run a simple server for processing messages over ``UDP``. ``UDP_LISTEN_ON_HOST`` - listen on this host ip address ``UDP_LISTEN_ON_PORT`` - listen on this ``UDP`` port ``UDP_LISTEN_SIZE`` - listen on to packets of this size ``UDP_LISTEN_SLEEP`` - sleep this number of seconds per loop ``UDP_LISTEN_SHUTDOWN_HOOK`` - shutdown if file is found on disk
def set_resource_type(resource, type_id, types={}, **kwargs): """ Set this resource to be a certain type. Type objects (a dictionary keyed on type_id) may be passed in to save on loading. This function does not call save. It must be done afterwards. New resource attributes are added to the resource if the template requires them. Resource attributes on the resource but not used by the template are not removed. @returns list of new resource attributes ,new resource type object """ ref_key = resource.ref_key existing_attr_ids = [] for res_attr in resource.attributes: existing_attr_ids.append(res_attr.attr_id) if type_id in types: type_i = types[type_id] else: type_i = db.DBSession.query(TemplateType).filter(TemplateType.id==type_id).options(joinedload_all('typeattrs')).one() type_attrs = dict() for typeattr in type_i.typeattrs: type_attrs[typeattr.attr_id]={ 'is_var':typeattr.attr_is_var, 'default_dataset_id': typeattr.default_dataset.id if typeattr.default_dataset else None} # check if attributes exist missing_attr_ids = set(type_attrs.keys()) - set(existing_attr_ids) # add attributes if necessary new_res_attrs = [] #This is a dict as the length of the list may not match the new_res_attrs #Keyed on attr_id, as resource_attr_id doesn't exist yet, and there should only #be one attr_id per template. new_res_scenarios = {} for attr_id in missing_attr_ids: ra_dict = dict( ref_key = ref_key, attr_id = attr_id, attr_is_var = type_attrs[attr_id]['is_var'], node_id = resource.id if ref_key == 'NODE' else None, link_id = resource.id if ref_key == 'LINK' else None, group_id = resource.id if ref_key == 'GROUP' else None, network_id = resource.id if ref_key == 'NETWORK' else None, ) new_res_attrs.append(ra_dict) if type_attrs[attr_id]['default_dataset_id'] is not None: if hasattr(resource, 'network'): for s in resource.network.scenarios: if new_res_scenarios.get(attr_id) is None: new_res_scenarios[attr_id] = {} new_res_scenarios[attr_id][s.id] = dict( dataset_id = type_attrs[attr_id]['default_dataset_id'], scenario_id = s.id, #Not stored in the DB, but needed to connect the RA ID later. attr_id = attr_id, ref_key = ref_key, node_id = ra_dict['node_id'], link_id = ra_dict['link_id'], group_id = ra_dict['group_id'], network_id = ra_dict['network_id'], ) resource_type = None for rt in resource.types: if rt.type_id == type_i.id: break else: errors = check_type_compatibility(rt.type_id, type_i.id) if len(errors) > 0: raise HydraError("Cannot apply type %s to resource as it " "conflicts with type %s. Errors are: %s" %(type_i.name, resource.get_name(), rt.templatetype.name, ','.join(errors))) else: # add type to tResourceType if it doesn't exist already resource_type = dict( node_id = resource.id if ref_key == 'NODE' else None, link_id = resource.id if ref_key == 'LINK' else None, group_id = resource.id if ref_key == 'GROUP' else None, network_id = resource.id if ref_key == 'NETWORK' else None, ref_key = ref_key, type_id = type_id, ) return new_res_attrs, resource_type, new_res_scenarios
Set this resource to be a certain type. Type objects (a dictionary keyed on type_id) may be passed in to save on loading. This function does not call save. It must be done afterwards. New resource attributes are added to the resource if the template requires them. Resource attributes on the resource but not used by the template are not removed. @returns list of new resource attributes ,new resource type object
def download(self, bucket_name, object_name, filename=None): """ Get a file from Google Cloud Storage. :param bucket_name: The bucket to fetch from. :type bucket_name: str :param object_name: The object to fetch. :type object_name: str :param filename: If set, a local file path where the file should be written to. :type filename: str """ client = self.get_conn() bucket = client.get_bucket(bucket_name) blob = bucket.blob(blob_name=object_name) if filename: blob.download_to_filename(filename) self.log.info('File downloaded to %s', filename) return blob.download_as_string()
Get a file from Google Cloud Storage. :param bucket_name: The bucket to fetch from. :type bucket_name: str :param object_name: The object to fetch. :type object_name: str :param filename: If set, a local file path where the file should be written to. :type filename: str
def _new_stream(self, idx): '''Randomly select and create a new stream. Parameters ---------- idx : int, [0:n_streams - 1] The stream index to replace ''' # Don't activate the stream if the weight is 0 or None if self.stream_weights_[idx]: self.streams_[idx] = self.streamers[idx].iterate() else: self.streams_[idx] = None # Reset the sample count to zero self.stream_counts_[idx] = 0
Randomly select and create a new stream. Parameters ---------- idx : int, [0:n_streams - 1] The stream index to replace
def move_into(self, destination_folder): # type: (Folder) -> None """Move the Folder into a different folder. This makes the Folder provided a child folder of the destination_folder. Raises: AuthError: Raised if Outlook returns a 401, generally caused by an invalid or expired access token. Args: destination_folder: A :class:`Folder <pyOutlook.core.folder.Folder>` that should become the parent Returns: A new :class:`Folder <pyOutlook.core.folder.Folder>` that is now inside of the destination_folder. """ headers = self.headers endpoint = 'https://outlook.office.com/api/v2.0/me/MailFolders/' + self.id + '/move' payload = '{ "DestinationId": "' + destination_folder.id + '"}' r = requests.post(endpoint, headers=headers, data=payload) if check_response(r): return_folder = r.json() return self._json_to_folder(self.account, return_folder)
Move the Folder into a different folder. This makes the Folder provided a child folder of the destination_folder. Raises: AuthError: Raised if Outlook returns a 401, generally caused by an invalid or expired access token. Args: destination_folder: A :class:`Folder <pyOutlook.core.folder.Folder>` that should become the parent Returns: A new :class:`Folder <pyOutlook.core.folder.Folder>` that is now inside of the destination_folder.
def aggcv(rlist, show_stdv=True, show_progress=None, as_pandas=True): # pylint: disable=invalid-name """ Aggregate cross-validation results. """ cvmap = {} idx = rlist[0].split()[0] for line in rlist: arr = line.split() assert idx == arr[0] for it in arr[1:]: if not isinstance(it, STRING_TYPES): it = it.decode() k, v = it.split(':') if k not in cvmap: cvmap[k] = [] cvmap[k].append(float(v)) msg = idx if show_stdv: fmt = '\tcv-{0}:{1}+{2}' else: fmt = '\tcv-{0}:{1}' index = [] results = [] for k, v in sorted(cvmap.items(), key=lambda x: x[0]): v = np.array(v) if not isinstance(msg, STRING_TYPES): msg = msg.decode() mean, std = np.mean(v), np.std(v) msg += fmt.format(k, mean, std) index.extend([k + '-mean', k + '-std']) results.extend([mean, std]) if as_pandas: try: import pandas as pd results = pd.Series(results, index=index) except ImportError: if show_progress is None: show_progress = True else: # if show_progress is default (None), # result will be np.ndarray as it can't hold column name if show_progress is None: show_progress = True if show_progress: sys.stderr.write(msg + '\n') return results
Aggregate cross-validation results.
def plot_isotherm(self, T, zs, ws, Pmin=None, Pmax=None, methods=[], pts=50, only_valid=True): # pragma: no cover r'''Method to create a plot of the property vs pressure at a specified temperature and composition according to either a specified list of methods, or the user methods (if set), or all methods. User-selectable number of points, and pressure range. If only_valid is set, `test_method_validity` will be used to check if each condition in the specified range is valid, and `test_property_validity` will be used to test the answer, and the method is allowed to fail; only the valid points will be plotted. Otherwise, the result will be calculated and displayed as-is. This will not suceed if the method fails. Parameters ---------- T : float Temperature at which to create the plot, [K] zs : list[float] Mole fractions of all species in the mixture, [-] ws : list[float] Weight fractions of all species in the mixture, [-] Pmin : float Minimum pressure, to begin calculating the property, [Pa] Pmax : float Maximum pressure, to stop calculating the property, [Pa] methods : list, optional List of methods to consider pts : int, optional A list of points to calculate the property at; if Pmin to Pmax covers a wide range of method validities, only a few points may end up calculated for a given method so this may need to be large only_valid : bool If True, only plot successful methods and calculated properties, and handle errors; if False, attempt calculation without any checking and use methods outside their bounds ''' # This function cannot be tested if not has_matplotlib: raise Exception('Optional dependency matplotlib is required for plotting') if Pmin is None: if self.Pmin is not None: Pmin = self.Pmin else: raise Exception('Minimum pressure could not be auto-detected; please provide it') if Pmax is None: if self.Pmax is not None: Pmax = self.Pmax else: raise Exception('Maximum pressure could not be auto-detected; please provide it') if not methods: if self.user_methods: methods = self.user_methods else: methods = self.all_methods Ps = np.linspace(Pmin, Pmax, pts) for method in methods: if only_valid: properties, Ps2 = [], [] for P in Ps: if self.test_method_validity(T, P, zs, ws, method): try: p = self.calculate(T, P, zs, ws, method) if self.test_property_validity(p): properties.append(p) Ps2.append(P) except: pass plt.plot(Ps2, properties, label=method) else: properties = [self.calculate(T, P, zs, ws, method) for P in Ps] plt.plot(Ps, properties, label=method) plt.legend(loc='best') plt.ylabel(self.name + ', ' + self.units) plt.xlabel('Pressure, Pa') plt.title(self.name + ' of a mixture of ' + ', '.join(self.CASs) + ' at mole fractions of ' + ', '.join(str(round(i, 4)) for i in zs) + '.') plt.show()
r'''Method to create a plot of the property vs pressure at a specified temperature and composition according to either a specified list of methods, or the user methods (if set), or all methods. User-selectable number of points, and pressure range. If only_valid is set, `test_method_validity` will be used to check if each condition in the specified range is valid, and `test_property_validity` will be used to test the answer, and the method is allowed to fail; only the valid points will be plotted. Otherwise, the result will be calculated and displayed as-is. This will not suceed if the method fails. Parameters ---------- T : float Temperature at which to create the plot, [K] zs : list[float] Mole fractions of all species in the mixture, [-] ws : list[float] Weight fractions of all species in the mixture, [-] Pmin : float Minimum pressure, to begin calculating the property, [Pa] Pmax : float Maximum pressure, to stop calculating the property, [Pa] methods : list, optional List of methods to consider pts : int, optional A list of points to calculate the property at; if Pmin to Pmax covers a wide range of method validities, only a few points may end up calculated for a given method so this may need to be large only_valid : bool If True, only plot successful methods and calculated properties, and handle errors; if False, attempt calculation without any checking and use methods outside their bounds
def block_verify( block_data ): """ Given block data (a dict with 'merkleroot' hex string and 'tx' list of hex strings--i.e. a block compatible with bitcoind's getblock JSON RPC method), verify that the transactions are consistent. Return True on success Return False if not. """ # verify block data txs m = merkle.MerkleTree( block_data['tx'] ) root_hash = str(m.root()) return root_hash == str(block_data['merkleroot'])
Given block data (a dict with 'merkleroot' hex string and 'tx' list of hex strings--i.e. a block compatible with bitcoind's getblock JSON RPC method), verify that the transactions are consistent. Return True on success Return False if not.
def python(self, cmd): """Execute a python script using the virtual environment python.""" python_bin = self.cmd_path('python') cmd = '{0} {1}'.format(python_bin, cmd) return self._execute(cmd)
Execute a python script using the virtual environment python.
def serializer_for(self, obj): """ Searches for a serializer for the provided object Serializers will be searched in this order; 1-NULL serializer 2-Default serializers, like primitives, arrays, string and some default types 3-Custom registered types by user 4-Global serializer if registered by user 4-pickle serialization as a fallback :param obj: input object :return: Serializer """ # 1-NULL serializer if obj is None: return self._null_serializer obj_type = type(obj) # 2-Default serializers, Dataserializable, Portable, primitives, arrays, String and some helper types(BigInteger etc) serializer = self.lookup_default_serializer(obj_type, obj) # 3-Custom registered types by user if serializer is None: serializer = self.lookup_custom_serializer(obj_type) # 5-Global serializer if registered by user if serializer is None: serializer = self.lookup_global_serializer(obj_type) # 4 Internal serializer if serializer is None: serializer = self.lookup_python_serializer(obj_type) if serializer is None: raise HazelcastSerializationError("There is no suitable serializer for:" + str(obj_type)) return serializer
Searches for a serializer for the provided object Serializers will be searched in this order; 1-NULL serializer 2-Default serializers, like primitives, arrays, string and some default types 3-Custom registered types by user 4-Global serializer if registered by user 4-pickle serialization as a fallback :param obj: input object :return: Serializer
def _check_values(self, values): """Check values whenever they come through the values setter.""" assert isinstance(values, Iterable) and not \ isinstance(values, (str, dict, bytes, bytearray)), \ 'values should be a list or tuple. Got {}'.format(type(values)) assert len(values) == len(self.datetimes), \ 'Length of values list must match length of datetimes list. {} != {}'.format( len(values), len(self.datetimes)) assert len(values) > 0, 'Data Collection must include at least one value'
Check values whenever they come through the values setter.
def removeChild(self, child_id): """Remove a child from current workitem :param child_id: the child workitem id/number (integer or equivalent string) """ self.log.debug("Try to remove a child <Workitem %s> from current " "<Workitem %s>", child_id, self) self._removeChildren([child_id]) self.log.info("Successfully remove a child <Workitem %s> from " "current <Workitem %s>", child_id, self)
Remove a child from current workitem :param child_id: the child workitem id/number (integer or equivalent string)
def construct_error_message(driver_id, error_type, message, timestamp): """Construct a serialized ErrorTableData object. Args: driver_id: The ID of the driver that the error should go to. If this is nil, then the error will go to all drivers. error_type: The type of the error. message: The error message. timestamp: The time of the error. Returns: The serialized object. """ builder = flatbuffers.Builder(0) driver_offset = builder.CreateString(driver_id.binary()) error_type_offset = builder.CreateString(error_type) message_offset = builder.CreateString(message) ray.core.generated.ErrorTableData.ErrorTableDataStart(builder) ray.core.generated.ErrorTableData.ErrorTableDataAddDriverId( builder, driver_offset) ray.core.generated.ErrorTableData.ErrorTableDataAddType( builder, error_type_offset) ray.core.generated.ErrorTableData.ErrorTableDataAddErrorMessage( builder, message_offset) ray.core.generated.ErrorTableData.ErrorTableDataAddTimestamp( builder, timestamp) error_data_offset = ray.core.generated.ErrorTableData.ErrorTableDataEnd( builder) builder.Finish(error_data_offset) return bytes(builder.Output())
Construct a serialized ErrorTableData object. Args: driver_id: The ID of the driver that the error should go to. If this is nil, then the error will go to all drivers. error_type: The type of the error. message: The error message. timestamp: The time of the error. Returns: The serialized object.
def find_suitable_encoding(self, char): """The order of our search is a specific one: 1. code pages that we already tried before; there is a good chance they might work again, reducing the search space, and by re-using already used encodings we might also reduce the number of codepage change instructiosn we have to send. Still, any performance gains will presumably be fairly minor. 2. code pages in lower ESCPOS slots first. Presumably, they are more likely to be supported, so if a printer profile is missing or incomplete, we might increase our change that the code page we pick for this character is actually supported. """ sorted_encodings = sorted( self.codepages.items(), key=self.__encoding_sort_func) for encoding, _ in sorted_encodings: if self.can_encode(encoding, char): # This encoding worked; at it to the set of used ones. self.used_encodings.add(encoding) return encoding
The order of our search is a specific one: 1. code pages that we already tried before; there is a good chance they might work again, reducing the search space, and by re-using already used encodings we might also reduce the number of codepage change instructiosn we have to send. Still, any performance gains will presumably be fairly minor. 2. code pages in lower ESCPOS slots first. Presumably, they are more likely to be supported, so if a printer profile is missing or incomplete, we might increase our change that the code page we pick for this character is actually supported.
def write_biom(self, sample_names, read_taxonomies, biom_file_io): '''Write the OTU info to a biom IO output stream Parameters ---------- sample_names: String names of each sample (sample_ids for biom) read_taxonomies: Array of hashes as per _iterate_otu_table_rows() biom_file_io: io open writeable stream to write biom contents to Returns True if successful, else False''' counts = [] observ_metadata = [] otu_ids = [] for otu_id, tax, count in self._iterate_otu_table_rows(read_taxonomies): if len(count) != len(sample_names): raise Exception("Programming error: mismatched sample names and counts") counts.append(count) observ_metadata.append({'taxonomy': tax}) otu_ids.append(str(otu_id)) if len(counts) == 0: logging.info("Not writing BIOM file since no sequences were assigned taxonomy") return True table = Table(np.array(counts), otu_ids, sample_names, observ_metadata, [{}]*len(sample_names), table_id='GraftM Taxonomy Count Table') try: table.to_hdf5(biom_file_io, 'GraftM graft') return True except RuntimeError as e: logging.warn("Error writing BIOM output, file not written. The specific error was: %s" % e) return False
Write the OTU info to a biom IO output stream Parameters ---------- sample_names: String names of each sample (sample_ids for biom) read_taxonomies: Array of hashes as per _iterate_otu_table_rows() biom_file_io: io open writeable stream to write biom contents to Returns True if successful, else False
def check_schedule(): """Helper routine to easily test if the schedule is valid""" all_items = prefetch_schedule_items() for validator, _type, _msg in SCHEDULE_ITEM_VALIDATORS: if validator(all_items): return False all_slots = prefetch_slots() for validator, _type, _msg in SLOT_VALIDATORS: if validator(all_slots): return False return True
Helper routine to easily test if the schedule is valid
def _query_select_options(self, query, select_columns=None): """ Add select load options to query. The goal is to only SQL select what is requested :param query: SQLAlchemy Query obj :param select_columns: (list) of columns :return: SQLAlchemy Query obj """ if select_columns: _load_options = list() for column in select_columns: if "." in column: model_relation = self.get_related_model(column.split(".")[0]) if not self.is_model_already_joinded(query, model_relation): query = query.join(model_relation) _load_options.append( Load(model_relation).load_only(column.split(".")[1]) ) else: if not self.is_relation(column) and not hasattr( getattr(self.obj, column), "__call__" ): _load_options.append(Load(self.obj).load_only(column)) else: _load_options.append(Load(self.obj)) query = query.options(*tuple(_load_options)) return query
Add select load options to query. The goal is to only SQL select what is requested :param query: SQLAlchemy Query obj :param select_columns: (list) of columns :return: SQLAlchemy Query obj
def retry_on_exception(tries=6, delay=1, backoff=2, max_delay=32): ''' Decorator for implementing exponential backoff for retrying on failures. tries: Max number of tries to execute the wrapped function before failing. delay: Delay time in seconds before the FIRST retry. backoff: Multiplier to extend the initial delay by for each retry. max_delay: Max time in seconds to wait between retries. ''' tries = math.floor(tries) if tries < 1: raise ValueError('"tries" must be greater than or equal to 1.') if delay < 0: raise ValueError('"delay" must be greater than or equal to 0.') if backoff < 1: raise ValueError('"backoff" must be greater than or equal to 1.') if max_delay < delay: raise ValueError('"max_delay" must be greater than or equal to delay.') def decorated_function_with_retry(func): @wraps(func) def function_to_retry(*args, **kwargs): local_tries, local_delay = tries, delay while local_tries > 1: try: return func(*args, **kwargs) except Exception as e: if local_delay > max_delay: local_delay = max_delay logging.exception('%s: Retrying in %d seconds...' % (str(e), local_delay)) time.sleep(local_delay) local_tries -= 1 local_delay *= backoff return func(*args, **kwargs) return function_to_retry return decorated_function_with_retry
Decorator for implementing exponential backoff for retrying on failures. tries: Max number of tries to execute the wrapped function before failing. delay: Delay time in seconds before the FIRST retry. backoff: Multiplier to extend the initial delay by for each retry. max_delay: Max time in seconds to wait between retries.
def from_name(cls, name, all_fallback=True): """Gets a vocation filter from a vocation's name. Parameters ---------- name: :class:`str` The name of the vocation. all_fallback: :class:`bool` Whether to return :py:attr:`ALL` if no match is found. Otherwise, ``None`` will be returned. Returns ------- VocationFilter, optional: The matching vocation filter. """ name = name.upper() for vocation in cls: # type: VocationFilter if vocation.name in name or vocation.name[:-1] in name and vocation != cls.ALL: return vocation if all_fallback or name.upper() == "ALL": return cls.ALL return None
Gets a vocation filter from a vocation's name. Parameters ---------- name: :class:`str` The name of the vocation. all_fallback: :class:`bool` Whether to return :py:attr:`ALL` if no match is found. Otherwise, ``None`` will be returned. Returns ------- VocationFilter, optional: The matching vocation filter.
def path(self, *args: typing.List[str]) -> typing.Union[None, str]: """ Creates an absolute path in the project source directory from the relative path components. :param args: Relative components for creating a path within the project source directory :return: An absolute path to the specified file or directory within the project source directory. """ if not self._project: return None return environ.paths.clean(os.path.join( self._project.source_directory, *args ))
Creates an absolute path in the project source directory from the relative path components. :param args: Relative components for creating a path within the project source directory :return: An absolute path to the specified file or directory within the project source directory.
def _updateCallSetIds(self, variantFile): """ Updates the call set IDs based on the specified variant file. """ if len(self._callSetIdMap) == 0: for sample in variantFile.header.samples: self.addCallSetFromName(sample)
Updates the call set IDs based on the specified variant file.
def items(self): "Returns a list of (key, value) pairs as 2-tuples." return (list(self._pb.IntMap.items()) + list(self._pb.StringMap.items()) + list(self._pb.FloatMap.items()) + list(self._pb.BoolMap.items()))
Returns a list of (key, value) pairs as 2-tuples.
def get_transitions(self, indexes): """ Get dictionary of transition data """ assert indexes.shape[1] == self.state_buffer.shape[1], \ "Must have the same number of indexes as there are environments" frame_batch_shape = ( [indexes.shape[0], indexes.shape[1]] + list(self.state_buffer.shape[2:-1]) + [self.state_buffer.shape[-1] * self.frame_history] ) past_frame_buffer = np.zeros(frame_batch_shape, dtype=self.state_buffer.dtype) future_frame_buffer = np.zeros(frame_batch_shape, dtype=self.state_buffer.dtype) for buffer_idx, frame_row in enumerate(indexes): for env_idx, frame_idx in enumerate(frame_row): past_frame_buffer[buffer_idx, env_idx], future_frame_buffer[buffer_idx, env_idx] = ( self.get_frame_with_future(frame_idx, env_idx) ) actions = take_along_axis(self.action_buffer, indexes) rewards = take_along_axis(self.reward_buffer, indexes) dones = take_along_axis(self.dones_buffer, indexes) transition_tensors = { 'observations': past_frame_buffer, 'actions': actions, 'rewards': rewards, 'observations_next': future_frame_buffer, 'dones': dones.astype(np.float32), } for name in self.extra_data: transition_tensors[name] = take_along_axis(self.extra_data[name], indexes) return transition_tensors
Get dictionary of transition data
def get_data_csv(file_name, encoding='utf-8', file_contents=None, on_demand=False): ''' Gets good old csv data from a file. Args: file_name: The name of the local file, or the holder for the extension type when the file_contents are supplied. encoding: Loads the file with the specified cell encoding. file_contents: The file-like object holding contents of file_name. If left as None, then file_name is directly loaded. on_demand: Requests that a yielder be used in place of a full data copy. ''' def yield_csv(csv_contents, csv_file): try: for line in csv_contents: yield line finally: try: csv_file.close() except: pass def process_csv(csv_contents, csv_file): return [line for line in yield_csv(csv_contents, csv_file)] if file_contents: csv_file = BytesIO(file_contents) else: # Don't use 'open as' format, as on_demand loads shouldn't close the file early csv_file = open(file_name, 'rb') reader = csv.reader(csv_file, dialect=csv.excel, encoding=encoding) if on_demand: table = yield_csv(reader, csv_file) else: table = process_csv(reader, csv_file) return [table]
Gets good old csv data from a file. Args: file_name: The name of the local file, or the holder for the extension type when the file_contents are supplied. encoding: Loads the file with the specified cell encoding. file_contents: The file-like object holding contents of file_name. If left as None, then file_name is directly loaded. on_demand: Requests that a yielder be used in place of a full data copy.
def init_app(self, app): """Initialize the extension. It will create the `index_path_root` directory upon initalization but it will **not** create the index. Please use :meth:`reindex` for this. :param app: The application instance for which the extension should be initialized. """ if not hasattr(app, 'extensions'): app.extensions = {} config = app.extensions.setdefault('whooshee', {}) # mapping that caches whoosheers to their indexes; used by `get_or_create_index` config['whoosheers_indexes'] = {} # store a reference to self whoosheers; this way, even whoosheers created after init_app # was called will be found config['whoosheers'] = self.whoosheers config['index_path_root'] = app.config.get('WHOOSHEE_DIR', '') or 'whooshee' config['writer_timeout'] = app.config.get('WHOOSHEE_WRITER_TIMEOUT', 2) config['search_string_min_len'] = app.config.get('WHOOSHEE_MIN_STRING_LEN', 3) config['memory_storage'] = app.config.get("WHOOSHEE_MEMORY_STORAGE", False) config['enable_indexing'] = app.config.get('WHOOSHEE_ENABLE_INDEXING', True) if app.config.get('WHOOSHE_MIN_STRING_LEN', None) is not None: warnings.warn(WhoosheeDeprecationWarning("The config key WHOOSHE_MIN_STRING_LEN has been renamed to WHOOSHEE_MIN_STRING_LEN. The mispelled config key is deprecated and will be removed in upcoming releases. Change it to WHOOSHEE_MIN_STRING_LEN to suppress this warning")) config['search_string_min_len'] = app.config.get('WHOOSHE_MIN_STRING_LEN') if not os.path.exists(config['index_path_root']): os.makedirs(config['index_path_root'])
Initialize the extension. It will create the `index_path_root` directory upon initalization but it will **not** create the index. Please use :meth:`reindex` for this. :param app: The application instance for which the extension should be initialized.
def recover_chain_id(storage: SQLiteStorage) -> ChainID: """We can reasonably assume, that any database has only one value for `chain_id` at this point in time. """ action_init_chain = json.loads(storage.get_state_changes(limit=1, offset=0)[0]) assert action_init_chain['_type'] == 'raiden.transfer.state_change.ActionInitChain' return action_init_chain['chain_id']
We can reasonably assume, that any database has only one value for `chain_id` at this point in time.
def get_storage_id_for_state(state): """ Calculates the storage id of a state. This ID can be used for generating the file path for a state. :param rafcon.core.states.state.State state: state the storage_id should is composed for """ if global_config.get_config_value('STORAGE_PATH_WITH_STATE_NAME'): max_length = global_config.get_config_value('MAX_LENGTH_FOR_STATE_NAME_IN_STORAGE_PATH') max_length_of_state_name_in_folder_name = 255 - len(ID_NAME_DELIMITER + state.state_id) # TODO: should we allow "None" in config file? if max_length is None or max_length == "None" or max_length > max_length_of_state_name_in_folder_name: if max_length_of_state_name_in_folder_name < len(state.name): logger.info("The storage folder name is forced to be maximal 255 characters in length.") max_length = max_length_of_state_name_in_folder_name return limit_text_to_be_path_element(state.name, max_length) + ID_NAME_DELIMITER + state.state_id else: return state.state_id
Calculates the storage id of a state. This ID can be used for generating the file path for a state. :param rafcon.core.states.state.State state: state the storage_id should is composed for
def loop(self): """ main game loop. returns the final score. """ pause_key = self.board.PAUSE margins = {'left': 4, 'top': 4, 'bottom': 4} atexit.register(self.showCursor) try: self.hideCursor() while True: self.clearScreen() print(self.__str__(margins=margins)) if self.board.won() or not self.board.canMove(): break m = self.readMove() if m == pause_key: self.saveBestScore() if self.store(): print("Game successfully saved. " "Resume it with `term2048 --resume`.") return self.score print("An error ocurred while saving your game.") return None self.incScore(self.board.move(m)) except KeyboardInterrupt: self.saveBestScore() return None self.saveBestScore() print('You won!' if self.board.won() else 'Game Over') return self.score
main game loop. returns the final score.
def parse_query(self, query): """Parse query string using given grammar""" tree = pypeg2.parse(query, Main, whitespace="") return tree.accept(self.converter)
Parse query string using given grammar
def trimLeft(self, amount): """ Trim this fastqSequence in-place by removing <amount> nucleotides from the 5' end (left end). :param amount: the number of nucleotides to trim from the left-side of this sequence. """ if amount == 0: return self.sequenceData = self.sequenceData[amount:] self.sequenceQual = self.sequenceQual[amount:]
Trim this fastqSequence in-place by removing <amount> nucleotides from the 5' end (left end). :param amount: the number of nucleotides to trim from the left-side of this sequence.
def connect(host, default_protocol='telnet', **kwargs): """ Like :class:`prepare()`, but also connects to the host by calling :class:`Protocol.connect()`. If the URL or host contain any login info, this function also logs into the host using :class:`Protocol.login()`. :type host: str or Host :param host: A URL-formatted hostname or a :class:`Exscript.Host` object. :type default_protocol: str :param default_protocol: Protocol that is used if the URL specifies none. :type kwargs: dict :param kwargs: Passed to the protocol constructor. :rtype: Protocol :return: An instance of the protocol. """ host = to_host(host) conn = prepare(host, default_protocol, **kwargs) account = host.get_account() conn.connect(host.get_address(), host.get_tcp_port()) if account is not None: conn.login(account) return conn
Like :class:`prepare()`, but also connects to the host by calling :class:`Protocol.connect()`. If the URL or host contain any login info, this function also logs into the host using :class:`Protocol.login()`. :type host: str or Host :param host: A URL-formatted hostname or a :class:`Exscript.Host` object. :type default_protocol: str :param default_protocol: Protocol that is used if the URL specifies none. :type kwargs: dict :param kwargs: Passed to the protocol constructor. :rtype: Protocol :return: An instance of the protocol.
def main(self, spin, data): """ The function which uses irc rfc regex to extract the basic arguments from the msg. """ data = data.decode(self.encoding) field = re.match(RFC_REG, data) if not field: return prefix = self.extract_prefix(field.group('prefix')) command = field.group('command').upper() args = self.extract_args(field.group('arguments')) spawn(spin, command, *(prefix + args))
The function which uses irc rfc regex to extract the basic arguments from the msg.
def get_pathway(self, pathway_name=None, pathway_id=None, limit=None, as_df=False): """Get pathway .. note:: Format of pathway_id is KEGG:X* or REACTOME:X* . X* stands for a sequence of digits :param bool as_df: if set to True result returns as `pandas.DataFrame` :param str pathway_name: pathway name :param str pathway_id: KEGG or REACTOME identifier :param int limit: maximum number of results :return: list of :class:`pyctd.manager.models.Pathway` objects .. seealso:: :class:`pyctd.manager.models.Pathway` """ q = self.session.query(models.Pathway) if pathway_name: q = q.filter(models.Pathway.pathway_name.like(pathway_name)) if pathway_id: q = q.filter(models.Pathway.pathway_id.like(pathway_id)) return self._limit_and_df(q, limit, as_df)
Get pathway .. note:: Format of pathway_id is KEGG:X* or REACTOME:X* . X* stands for a sequence of digits :param bool as_df: if set to True result returns as `pandas.DataFrame` :param str pathway_name: pathway name :param str pathway_id: KEGG or REACTOME identifier :param int limit: maximum number of results :return: list of :class:`pyctd.manager.models.Pathway` objects .. seealso:: :class:`pyctd.manager.models.Pathway`
def debug(self, debug_commands): """Run a debug command.""" if isinstance(debug_commands, sc_debug.DebugCommand): debug_commands = [debug_commands] return self._client.send(debug=sc_pb.RequestDebug(debug=debug_commands))
Run a debug command.
def get(self, key): """ simple `select` """ if not Log: _late_import() return FlatList(vals=[unwrap(coalesce(_datawrap(v), Null)[key]) for v in _get_list(self)])
simple `select`
def _traverse_command(self, name, *args, **kwargs): """ Add the key to the args and call the Redis command. """ if not name in self.available_commands: raise AttributeError("%s is not an available command for %s" % (name, self.__class__.__name__)) attr = getattr(self.connection, "%s" % name) key = self.key log.debug(u"Requesting %s with key %s and args %s" % (name, key, args)) result = attr(key, *args, **kwargs) result = self.post_command( sender=self, name=name, result=result, args=args, kwargs=kwargs ) return result
Add the key to the args and call the Redis command.
def _translate(teleport_value): """Translate a teleport value in to a val subschema.""" if isinstance(teleport_value, dict): return _translate_composite(teleport_value) if teleport_value in PRIMITIVES: return PRIMITIVES[teleport_value] raise DeserializationError( "Could not interpret %r as a teleport schema." % teleport_value)
Translate a teleport value in to a val subschema.
def registration_id_chunks(self, registration_ids): """ Splits registration ids in several lists of max 1000 registration ids per list Args: registration_ids (list): FCM device registration ID Yields: generator: list including lists with registration ids """ try: xrange except NameError: xrange = range # Yield successive 1000-sized (max fcm recipients per request) chunks from registration_ids for i in xrange(0, len(registration_ids), self.FCM_MAX_RECIPIENTS): yield registration_ids[i:i + self.FCM_MAX_RECIPIENTS]
Splits registration ids in several lists of max 1000 registration ids per list Args: registration_ids (list): FCM device registration ID Yields: generator: list including lists with registration ids
def metalarchives(song): """ Returns the lyrics found in MetalArchives for the specified mp3 file or an empty string if not found. """ artist = normalize(song.artist) title = normalize(song.title) url = 'https://www.metal-archives.com/search/ajax-advanced/searching/songs' url += f'/?songTitle={title}&bandName={artist}&ExactBandMatch=1' soup = get_url(url, parser='json') if not soup: return '' song_id_re = re.compile(r'lyricsLink_([0-9]*)') ids = set(re.search(song_id_re, a) for sub in soup['aaData'] for a in sub) if not ids: return '' if None in ids: ids.remove(None) ids = map(lambda a: a.group(1), ids) for song_id in ids: url = 'https://www.metal-archives.com/release/ajax-view-lyrics/id/{}' lyrics = get_url(url.format(song_id), parser='html') lyrics = lyrics.get_text().strip() if not re.search('lyrics not available', lyrics): return lyrics return ''
Returns the lyrics found in MetalArchives for the specified mp3 file or an empty string if not found.
def warn_message(self, message, fh=None, prefix="[warn]:", suffix="..."): """ print warn type message, if file handle is `sys.stdout`, print color message :param str message: message to print :param file fh: file handle,default is `sys.stdout` :param str prefix: message prefix,default is `[warn]` :param str suffix: message suffix ,default is `...` :return: None """ msg = prefix + message + suffix fh = fh or sys.stdout if fh is sys.stdout: termcolor.cprint(msg, color="yellow") else: fh.write(msg) pass
print warn type message, if file handle is `sys.stdout`, print color message :param str message: message to print :param file fh: file handle,default is `sys.stdout` :param str prefix: message prefix,default is `[warn]` :param str suffix: message suffix ,default is `...` :return: None
def filter_featured_apps(admin_apps, request): """ Given a list of apps return a set of pseudo-apps considered featured. Apps are considered featured if the are defined in the settings property called `DASHBOARD_FEATURED_APPS` which contains a list of the apps that are considered to be featured. :param admin_apps: A list of apps. :param request: Django request. :return: Subset of app like objects that are listed in the settings `DASHBOARD_FEATURED_APPS` setting. """ featured_apps = [] # Build the featured apps list based upon settings. for orig_app_spec in appsettings.DASHBOARD_FEATURED_APPS: # make a copy that we can write to, to fix deprecations without # changing settings app_spec = orig_app_spec.copy() if "verbose_name" in app_spec: warnings.warn( "DASHBOARD_FEATURED_APPS[]['verbose_name'] = '%s' is deprecated. " "Use 'name' instead)" % app_spec['verbose_name'], DeprecationWarning, stacklevel=2 ) app_spec['name'] = app_spec['verbose_name'] if hasattr(app_spec['models'], 'items'): warnings.warn( "DASHBOARD_FEATURED_APPS[]['models'] for '%s' should now be a " "list of tuples, not a dict." % app_spec['name'], DeprecationWarning, stacklevel=2 ) app_spec['models'] = app_spec['models'].items() # lookup the models from the names app_spec['models'] = _build_app_models( request, admin_apps, app_spec['models'] ) # Only add the panel if at least one model is listed. if app_spec['models']: featured_apps.append(app_spec) return featured_apps
Given a list of apps return a set of pseudo-apps considered featured. Apps are considered featured if the are defined in the settings property called `DASHBOARD_FEATURED_APPS` which contains a list of the apps that are considered to be featured. :param admin_apps: A list of apps. :param request: Django request. :return: Subset of app like objects that are listed in the settings `DASHBOARD_FEATURED_APPS` setting.
def get_interfaces_ip(self): """ Get interface IP details. Returns a dictionary of dictionaries. Sample output: { "Ethernet2/3": { "ipv4": { "4.4.4.4": { "prefix_length": 16 } }, "ipv6": { "2001:db8::1": { "prefix_length": 10 }, "fe80::2ec2:60ff:fe4f:feb2": { "prefix_length": "128" } } }, "Ethernet2/2": { "ipv4": { "2.2.2.2": { "prefix_length": 27 } } } } """ interfaces_ip = {} ipv4_command = "show ip interface vrf all" ipv6_command = "show ipv6 interface vrf all" output_v4 = self._send_command(ipv4_command) output_v6 = self._send_command(ipv6_command) v4_interfaces = {} for line in output_v4.splitlines(): # Ethernet2/2, Interface status: protocol-up/link-up/admin-up, iod: 38, # IP address: 2.2.2.2, IP subnet: 2.2.2.0/27 route-preference: 0, tag: 0 # IP address: 3.3.3.3, IP subnet: 3.3.3.0/25 secondary route-preference: 0, tag: 0 if "Interface status" in line: interface = line.split(",")[0] continue if "IP address" in line: ip_address = line.split(",")[0].split()[2] try: prefix_len = int(line.split()[5].split("/")[1]) except ValueError: prefix_len = "N/A" val = {"prefix_length": prefix_len} v4_interfaces.setdefault(interface, {})[ip_address] = val v6_interfaces = {} for line in output_v6.splitlines(): # Ethernet2/4, Interface status: protocol-up/link-up/admin-up, iod: 40 # IPv6 address: # 2001:11:2233::a1/24 [VALID] # 2001:cc11:22bb:0:2ec2:60ff:fe4f:feb2/64 [VALID] # IPv6 subnet: 2001::/24 # IPv6 link-local address: fe80::2ec2:60ff:fe4f:feb2 (default) [VALID] # IPv6 address: fe80::a293:51ff:fe5f:5ce9 [VALID] if "Interface status" in line: interface = line.split(",")[0] continue if "VALID" in line: line = line.strip() if "link-local address" in line: # match the following format: # IPv6 link-local address: fe80::2ec2:60ff:fe4f:feb2 (default) [VALID] ip_address = line.split()[3] prefix_len = "64" elif "IPv6 address" in line: # match the following format: # IPv6 address: fe80::a293:51ff:fe5f:5ce9 [VALID] ip_address = line.split()[2] prefix_len = "64" else: ip_address, prefix_len = line.split()[0].split("/") prefix_len = int(prefix_len) val = {"prefix_length": prefix_len} v6_interfaces.setdefault(interface, {})[ip_address] = val # Join data from intermediate dictionaries. for interface, data in v4_interfaces.items(): interfaces_ip.setdefault(interface, {"ipv4": {}})["ipv4"] = data for interface, data in v6_interfaces.items(): interfaces_ip.setdefault(interface, {"ipv6": {}})["ipv6"] = data return interfaces_ip
Get interface IP details. Returns a dictionary of dictionaries. Sample output: { "Ethernet2/3": { "ipv4": { "4.4.4.4": { "prefix_length": 16 } }, "ipv6": { "2001:db8::1": { "prefix_length": 10 }, "fe80::2ec2:60ff:fe4f:feb2": { "prefix_length": "128" } } }, "Ethernet2/2": { "ipv4": { "2.2.2.2": { "prefix_length": 27 } } } }
def build(self, path=None, tag=None, quiet=False, fileobj=None, nocache=False, rm=False, timeout=None, custom_context=False, encoding=None, pull=False, forcerm=False, dockerfile=None, container_limits=None, decode=False, buildargs=None, gzip=False, shmsize=None, labels=None, cache_from=None, target=None, network_mode=None, squash=None, extra_hosts=None, platform=None, isolation=None, use_config_proxy=False): """ Similar to the ``docker build`` command. Either ``path`` or ``fileobj`` needs to be set. ``path`` can be a local path (to a directory containing a Dockerfile) or a remote URL. ``fileobj`` must be a readable file-like object to a Dockerfile. If you have a tar file for the Docker build context (including a Dockerfile) already, pass a readable file-like object to ``fileobj`` and also pass ``custom_context=True``. If the stream is compressed also, set ``encoding`` to the correct value (e.g ``gzip``). Example: >>> from io import BytesIO >>> from docker import APIClient >>> dockerfile = ''' ... # Shared Volume ... FROM busybox:buildroot-2014.02 ... VOLUME /data ... CMD ["/bin/sh"] ... ''' >>> f = BytesIO(dockerfile.encode('utf-8')) >>> cli = APIClient(base_url='tcp://127.0.0.1:2375') >>> response = [line for line in cli.build( ... fileobj=f, rm=True, tag='yourname/volume' ... )] >>> response ['{"stream":" ---\\u003e a9eb17255234\\n"}', '{"stream":"Step 1 : VOLUME /data\\n"}', '{"stream":" ---\\u003e Running in abdc1e6896c6\\n"}', '{"stream":" ---\\u003e 713bca62012e\\n"}', '{"stream":"Removing intermediate container abdc1e6896c6\\n"}', '{"stream":"Step 2 : CMD [\\"/bin/sh\\"]\\n"}', '{"stream":" ---\\u003e Running in dba30f2a1a7e\\n"}', '{"stream":" ---\\u003e 032b8b2855fc\\n"}', '{"stream":"Removing intermediate container dba30f2a1a7e\\n"}', '{"stream":"Successfully built 032b8b2855fc\\n"}'] Args: path (str): Path to the directory containing the Dockerfile fileobj: A file object to use as the Dockerfile. (Or a file-like object) tag (str): A tag to add to the final image quiet (bool): Whether to return the status nocache (bool): Don't use the cache when set to ``True`` rm (bool): Remove intermediate containers. The ``docker build`` command now defaults to ``--rm=true``, but we have kept the old default of `False` to preserve backward compatibility timeout (int): HTTP timeout custom_context (bool): Optional if using ``fileobj`` encoding (str): The encoding for a stream. Set to ``gzip`` for compressing pull (bool): Downloads any updates to the FROM image in Dockerfiles forcerm (bool): Always remove intermediate containers, even after unsuccessful builds dockerfile (str): path within the build context to the Dockerfile buildargs (dict): A dictionary of build arguments container_limits (dict): A dictionary of limits applied to each container created by the build process. Valid keys: - memory (int): set memory limit for build - memswap (int): Total memory (memory + swap), -1 to disable swap - cpushares (int): CPU shares (relative weight) - cpusetcpus (str): CPUs in which to allow execution, e.g., ``"0-3"``, ``"0,1"`` decode (bool): If set to ``True``, the returned stream will be decoded into dicts on the fly. Default ``False`` shmsize (int): Size of `/dev/shm` in bytes. The size must be greater than 0. If omitted the system uses 64MB labels (dict): A dictionary of labels to set on the image cache_from (:py:class:`list`): A list of images used for build cache resolution target (str): Name of the build-stage to build in a multi-stage Dockerfile network_mode (str): networking mode for the run commands during build squash (bool): Squash the resulting images layers into a single layer. extra_hosts (dict): Extra hosts to add to /etc/hosts in building containers, as a mapping of hostname to IP address. platform (str): Platform in the format ``os[/arch[/variant]]`` isolation (str): Isolation technology used during build. Default: `None`. use_config_proxy (bool): If ``True``, and if the docker client configuration file (``~/.docker/config.json`` by default) contains a proxy configuration, the corresponding environment variables will be set in the container being built. Returns: A generator for the build output. Raises: :py:class:`docker.errors.APIError` If the server returns an error. ``TypeError`` If neither ``path`` nor ``fileobj`` is specified. """ remote = context = None headers = {} container_limits = container_limits or {} buildargs = buildargs or {} if path is None and fileobj is None: raise TypeError("Either path or fileobj needs to be provided.") if gzip and encoding is not None: raise errors.DockerException( 'Can not use custom encoding if gzip is enabled' ) for key in container_limits.keys(): if key not in constants.CONTAINER_LIMITS_KEYS: raise errors.DockerException( 'Invalid container_limits key {0}'.format(key) ) if custom_context: if not fileobj: raise TypeError("You must specify fileobj with custom_context") context = fileobj elif fileobj is not None: context = utils.mkbuildcontext(fileobj) elif path.startswith(('http://', 'https://', 'git://', 'github.com/', 'git@')): remote = path elif not os.path.isdir(path): raise TypeError("You must specify a directory to build in path") else: dockerignore = os.path.join(path, '.dockerignore') exclude = None if os.path.exists(dockerignore): with open(dockerignore, 'r') as f: exclude = list(filter( lambda x: x != '' and x[0] != '#', [l.strip() for l in f.read().splitlines()] )) dockerfile = process_dockerfile(dockerfile, path) context = utils.tar( path, exclude=exclude, dockerfile=dockerfile, gzip=gzip ) encoding = 'gzip' if gzip else encoding u = self._url('/build') params = { 't': tag, 'remote': remote, 'q': quiet, 'nocache': nocache, 'rm': rm, 'forcerm': forcerm, 'pull': pull, 'dockerfile': dockerfile, } params.update(container_limits) if use_config_proxy: proxy_args = self._proxy_configs.get_environment() for k, v in proxy_args.items(): buildargs.setdefault(k, v) if buildargs: params.update({'buildargs': json.dumps(buildargs)}) if shmsize: if utils.version_gte(self._version, '1.22'): params.update({'shmsize': shmsize}) else: raise errors.InvalidVersion( 'shmsize was only introduced in API version 1.22' ) if labels: if utils.version_gte(self._version, '1.23'): params.update({'labels': json.dumps(labels)}) else: raise errors.InvalidVersion( 'labels was only introduced in API version 1.23' ) if cache_from: if utils.version_gte(self._version, '1.25'): params.update({'cachefrom': json.dumps(cache_from)}) else: raise errors.InvalidVersion( 'cache_from was only introduced in API version 1.25' ) if target: if utils.version_gte(self._version, '1.29'): params.update({'target': target}) else: raise errors.InvalidVersion( 'target was only introduced in API version 1.29' ) if network_mode: if utils.version_gte(self._version, '1.25'): params.update({'networkmode': network_mode}) else: raise errors.InvalidVersion( 'network_mode was only introduced in API version 1.25' ) if squash: if utils.version_gte(self._version, '1.25'): params.update({'squash': squash}) else: raise errors.InvalidVersion( 'squash was only introduced in API version 1.25' ) if extra_hosts is not None: if utils.version_lt(self._version, '1.27'): raise errors.InvalidVersion( 'extra_hosts was only introduced in API version 1.27' ) if isinstance(extra_hosts, dict): extra_hosts = utils.format_extra_hosts(extra_hosts) params.update({'extrahosts': extra_hosts}) if platform is not None: if utils.version_lt(self._version, '1.32'): raise errors.InvalidVersion( 'platform was only introduced in API version 1.32' ) params['platform'] = platform if isolation is not None: if utils.version_lt(self._version, '1.24'): raise errors.InvalidVersion( 'isolation was only introduced in API version 1.24' ) params['isolation'] = isolation if context is not None: headers = {'Content-Type': 'application/tar'} if encoding: headers['Content-Encoding'] = encoding self._set_auth_headers(headers) response = self._post( u, data=context, params=params, headers=headers, stream=True, timeout=timeout, ) if context is not None and not custom_context: context.close() return self._stream_helper(response, decode=decode)
Similar to the ``docker build`` command. Either ``path`` or ``fileobj`` needs to be set. ``path`` can be a local path (to a directory containing a Dockerfile) or a remote URL. ``fileobj`` must be a readable file-like object to a Dockerfile. If you have a tar file for the Docker build context (including a Dockerfile) already, pass a readable file-like object to ``fileobj`` and also pass ``custom_context=True``. If the stream is compressed also, set ``encoding`` to the correct value (e.g ``gzip``). Example: >>> from io import BytesIO >>> from docker import APIClient >>> dockerfile = ''' ... # Shared Volume ... FROM busybox:buildroot-2014.02 ... VOLUME /data ... CMD ["/bin/sh"] ... ''' >>> f = BytesIO(dockerfile.encode('utf-8')) >>> cli = APIClient(base_url='tcp://127.0.0.1:2375') >>> response = [line for line in cli.build( ... fileobj=f, rm=True, tag='yourname/volume' ... )] >>> response ['{"stream":" ---\\u003e a9eb17255234\\n"}', '{"stream":"Step 1 : VOLUME /data\\n"}', '{"stream":" ---\\u003e Running in abdc1e6896c6\\n"}', '{"stream":" ---\\u003e 713bca62012e\\n"}', '{"stream":"Removing intermediate container abdc1e6896c6\\n"}', '{"stream":"Step 2 : CMD [\\"/bin/sh\\"]\\n"}', '{"stream":" ---\\u003e Running in dba30f2a1a7e\\n"}', '{"stream":" ---\\u003e 032b8b2855fc\\n"}', '{"stream":"Removing intermediate container dba30f2a1a7e\\n"}', '{"stream":"Successfully built 032b8b2855fc\\n"}'] Args: path (str): Path to the directory containing the Dockerfile fileobj: A file object to use as the Dockerfile. (Or a file-like object) tag (str): A tag to add to the final image quiet (bool): Whether to return the status nocache (bool): Don't use the cache when set to ``True`` rm (bool): Remove intermediate containers. The ``docker build`` command now defaults to ``--rm=true``, but we have kept the old default of `False` to preserve backward compatibility timeout (int): HTTP timeout custom_context (bool): Optional if using ``fileobj`` encoding (str): The encoding for a stream. Set to ``gzip`` for compressing pull (bool): Downloads any updates to the FROM image in Dockerfiles forcerm (bool): Always remove intermediate containers, even after unsuccessful builds dockerfile (str): path within the build context to the Dockerfile buildargs (dict): A dictionary of build arguments container_limits (dict): A dictionary of limits applied to each container created by the build process. Valid keys: - memory (int): set memory limit for build - memswap (int): Total memory (memory + swap), -1 to disable swap - cpushares (int): CPU shares (relative weight) - cpusetcpus (str): CPUs in which to allow execution, e.g., ``"0-3"``, ``"0,1"`` decode (bool): If set to ``True``, the returned stream will be decoded into dicts on the fly. Default ``False`` shmsize (int): Size of `/dev/shm` in bytes. The size must be greater than 0. If omitted the system uses 64MB labels (dict): A dictionary of labels to set on the image cache_from (:py:class:`list`): A list of images used for build cache resolution target (str): Name of the build-stage to build in a multi-stage Dockerfile network_mode (str): networking mode for the run commands during build squash (bool): Squash the resulting images layers into a single layer. extra_hosts (dict): Extra hosts to add to /etc/hosts in building containers, as a mapping of hostname to IP address. platform (str): Platform in the format ``os[/arch[/variant]]`` isolation (str): Isolation technology used during build. Default: `None`. use_config_proxy (bool): If ``True``, and if the docker client configuration file (``~/.docker/config.json`` by default) contains a proxy configuration, the corresponding environment variables will be set in the container being built. Returns: A generator for the build output. Raises: :py:class:`docker.errors.APIError` If the server returns an error. ``TypeError`` If neither ``path`` nor ``fileobj`` is specified.
def ensure_dim(core, dim, dim_): """Ensure that dim is correct.""" if dim is None: dim = dim_ if not dim: return core, 1 if dim_ == dim: return core, int(dim) if dim > dim_: key_convert = lambda vari: vari[:dim_] else: key_convert = lambda vari: vari + (0,)*(dim-dim_) new_core = {} for key, val in core.items(): key_ = key_convert(key) if key_ in new_core: new_core[key_] += val else: new_core[key_] = val return new_core, int(dim)
Ensure that dim is correct.
def load(self, callback=None, errback=None, reload=False): """ Load network data from the API. """ if not reload and self.data: raise NetworkException('Network already loaded') def success(result, *args): self.data = result self.id = result['id'] self.name = result['name'] self.report = self._rest.report(self.id) if callback: return callback(self) else: return self if self.id is None: if self.name is None: raise NetworkException('Must at least specify an id or name') else: self.id = [network for network in self._rest.list() if network['name'] == self.name][0]['id'] return self._rest.retrieve(self.id, callback=success, errback=errback)
Load network data from the API.
def send_venue(chat_id, latitude, longitude, title, address, foursquare_id=None, reply_to_message_id=None, reply_markup=None, disable_notification=False, **kwargs): """ Use this method to send information about a venue. :param chat_id: Unique identifier for the target chat or username of the target channel (in the format @channelusername) :param latitude: Latitude of location. :param longitude: Longitude of location. :param title: Name of the venue. :param address: Address of the venue. :param foursquare_id: Foursquare identifier of the venue. :param reply_to_message_id: If the message is a reply, ID of the original message :param reply_markup: Additional interface options. A JSON-serialized object for a custom reply keyboard, instructions to hide keyboard or to force a reply from the user. :param disable_notification: Sends the message silently. iOS users will not receive a notification, Android users will receive a notification with no sound. Other apps coming soon. :param kwargs: Args that get passed down to :class:`TelegramBotRPCRequest` :type chat_id: int or str :type latitude: float :type longitude: float :type title: str :type address: str :type foursquare_id: str :type reply_to_message_id: int :type reply_markup: ReplyKeyboardMarkup or ReplyKeyboardHide or ForceReply :type disable_notification: bool :returns: On success, the sent Message is returned. :rtype: TelegramBotRPCRequest """ # required args params = dict( chat_id=chat_id, latitude=latitude, longitude=longitude, title=title, address=address, ) # optional args params.update( _clean_params( foursquare_id=foursquare_id, reply_to_message_id=reply_to_message_id, reply_markup=reply_markup, disable_notification=disable_notification, ) ) return TelegramBotRPCRequest('sendVenue', params=params, on_result=Message.from_result, **kwargs)
Use this method to send information about a venue. :param chat_id: Unique identifier for the target chat or username of the target channel (in the format @channelusername) :param latitude: Latitude of location. :param longitude: Longitude of location. :param title: Name of the venue. :param address: Address of the venue. :param foursquare_id: Foursquare identifier of the venue. :param reply_to_message_id: If the message is a reply, ID of the original message :param reply_markup: Additional interface options. A JSON-serialized object for a custom reply keyboard, instructions to hide keyboard or to force a reply from the user. :param disable_notification: Sends the message silently. iOS users will not receive a notification, Android users will receive a notification with no sound. Other apps coming soon. :param kwargs: Args that get passed down to :class:`TelegramBotRPCRequest` :type chat_id: int or str :type latitude: float :type longitude: float :type title: str :type address: str :type foursquare_id: str :type reply_to_message_id: int :type reply_markup: ReplyKeyboardMarkup or ReplyKeyboardHide or ForceReply :type disable_notification: bool :returns: On success, the sent Message is returned. :rtype: TelegramBotRPCRequest
def user_open(url_or_command): """Open the specified paramater in the web browser if a URL is detected, othewrise pass the paramater to the shell as a subprocess. This function is inteded to bu used in on_leftclick/on_rightclick callbacks. :param url_or_command: String containing URL or command """ from urllib.parse import urlparse scheme = urlparse(url_or_command).scheme if scheme == 'http' or scheme == 'https': import webbrowser import os # webbrowser.open() sometimes prints a message for some reason and confuses i3 # Redirect stdout briefly to prevent this from happening. savout = os.dup(1) os.close(1) os.open(os.devnull, os.O_RDWR) try: webbrowser.open(url_or_command) finally: os.dup2(savout, 1) else: import subprocess subprocess.Popen(url_or_command, shell=True)
Open the specified paramater in the web browser if a URL is detected, othewrise pass the paramater to the shell as a subprocess. This function is inteded to bu used in on_leftclick/on_rightclick callbacks. :param url_or_command: String containing URL or command
def mtanh(alpha, z): """Modified hyperbolic tangent function mtanh(z; alpha). Parameters ---------- alpha : float The core slope of the mtanh. z : float or array The coordinate of the mtanh. """ z = scipy.asarray(z) ez = scipy.exp(z) enz = 1.0 / ez return ((1 + alpha * z) * ez - enz) / (ez + enz)
Modified hyperbolic tangent function mtanh(z; alpha). Parameters ---------- alpha : float The core slope of the mtanh. z : float or array The coordinate of the mtanh.
def get_jids(): ''' Return a list of all job ids ''' cb_ = _get_connection() _verify_views() ret = {} for result in cb_.query(DESIGN_NAME, 'jids', include_docs=True): ret[result.key] = _format_jid_instance(result.key, result.doc.value['load']) return ret
Return a list of all job ids