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saltstack/salt
salt/thorium/reg.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/thorium/reg.py#L95-L133
def mean(name, add, match): ''' Accept a numeric value from the matched events and store a running average of the values in the given register. If the specified value is not numeric it will be skipped USAGE: .. code-block:: yaml foo: reg.mean: - add: data_field - match: my/custom/event ''' ret = {'name': name, 'changes': {}, 'comment': '', 'result': True} if name not in __reg__: __reg__[name] = {} __reg__[name]['val'] = 0 __reg__[name]['total'] = 0 __reg__[name]['count'] = 0 for event in __events__: try: event_data = event['data']['data'] except KeyError: event_data = event['data'] if salt.utils.stringutils.expr_match(event['tag'], match): if add in event_data: try: comp = int(event_data) except ValueError: continue __reg__[name]['total'] += comp __reg__[name]['count'] += 1 __reg__[name]['val'] = __reg__[name]['total'] / __reg__[name]['count'] return ret
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Accept a numeric value from the matched events and store a running average of the values in the given register. If the specified value is not numeric it will be skipped USAGE: .. code-block:: yaml foo: reg.mean: - add: data_field - match: my/custom/event
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python
train
KenjiTakahashi/td
td/model.py
https://github.com/KenjiTakahashi/td/blob/7311eabc63efe6fe6600687c3026f0837454c2e4/td/model.py#L361-L371
def setOptions(self, glob=False, **kwargs): """Set option(s). :glob: If True, stores specified options globally. :kwargs: Dictionary of options and values to set. """ if glob: self.globalOptions.update(kwargs) else: self.options.update(kwargs)
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Set option(s). :glob: If True, stores specified options globally. :kwargs: Dictionary of options and values to set.
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python
train
klahnakoski/pyLibrary
jx_python/flat_list.py
https://github.com/klahnakoski/pyLibrary/blob/fa2dcbc48fda8d26999baef400e9a98149e0b982/jx_python/flat_list.py#L124-L138
def _select1(data, field, depth, output): """ SELECT A SINGLE FIELD """ for d in data: for i, f in enumerate(field[depth:]): d = d[f] if d == None: output.append(None) break elif is_list(d): _select1(d, field, i + 1, output) break else: output.append(d)
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SELECT A SINGLE FIELD
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python
train
Clinical-Genomics/scout
scout/adapter/mongo/index.py
https://github.com/Clinical-Genomics/scout/blob/90a551e2e1653a319e654c2405c2866f93d0ebb9/scout/adapter/mongo/index.py#L54-L72
def update_indexes(self): """Update the indexes If there are any indexes that are not added to the database, add those. """ LOG.info("Updating indexes...") nr_updated = 0 for collection_name in INDEXES: existing_indexes = self.indexes(collection_name) indexes = INDEXES[collection_name] for index in indexes: index_name = index.document.get('name') if index_name not in existing_indexes: nr_updated += 1 LOG.info("Adding index : %s" % index_name) self.db[collection_name].create_indexes(indexes) if nr_updated == 0: LOG.info("All indexes in place")
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Update the indexes If there are any indexes that are not added to the database, add those.
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python
test
coleifer/peewee
playhouse/sqlite_ext.py
https://github.com/coleifer/peewee/blob/ea9403b01acb039adb3a2472186d795c796b77a0/playhouse/sqlite_ext.py#L719-L807
def ClosureTable(model_class, foreign_key=None, referencing_class=None, referencing_key=None): """Model factory for the transitive closure extension.""" if referencing_class is None: referencing_class = model_class if foreign_key is None: for field_obj in model_class._meta.refs: if field_obj.rel_model is model_class: foreign_key = field_obj break else: raise ValueError('Unable to find self-referential foreign key.') source_key = model_class._meta.primary_key if referencing_key is None: referencing_key = source_key class BaseClosureTable(VirtualModel): depth = VirtualField(IntegerField) id = VirtualField(IntegerField) idcolumn = VirtualField(TextField) parentcolumn = VirtualField(TextField) root = VirtualField(IntegerField) tablename = VirtualField(TextField) class Meta: extension_module = 'transitive_closure' @classmethod def descendants(cls, node, depth=None, include_node=False): query = (model_class .select(model_class, cls.depth.alias('depth')) .join(cls, on=(source_key == cls.id)) .where(cls.root == node) .objects()) if depth is not None: query = query.where(cls.depth == depth) elif not include_node: query = query.where(cls.depth > 0) return query @classmethod def ancestors(cls, node, depth=None, include_node=False): query = (model_class .select(model_class, cls.depth.alias('depth')) .join(cls, on=(source_key == cls.root)) .where(cls.id == node) .objects()) if depth: query = query.where(cls.depth == depth) elif not include_node: query = query.where(cls.depth > 0) return query @classmethod def siblings(cls, node, include_node=False): if referencing_class is model_class: # self-join fk_value = node.__data__.get(foreign_key.name) query = model_class.select().where(foreign_key == fk_value) else: # siblings as given in reference_class siblings = (referencing_class .select(referencing_key) .join(cls, on=(foreign_key == cls.root)) .where((cls.id == node) & (cls.depth == 1))) # the according models query = (model_class .select() .where(source_key << siblings) .objects()) if not include_node: query = query.where(source_key != node) return query class Meta: database = referencing_class._meta.database options = { 'tablename': referencing_class._meta.table_name, 'idcolumn': referencing_key.column_name, 'parentcolumn': foreign_key.column_name} primary_key = False name = '%sClosure' % model_class.__name__ return type(name, (BaseClosureTable,), {'Meta': Meta})
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Model factory for the transitive closure extension.
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python
train
StackStorm/pybind
pybind/nos/v7_2_0/isns/isns_vrf/__init__.py
https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/nos/v7_2_0/isns/isns_vrf/__init__.py#L143-L166
def _set_isns_ipaddress(self, v, load=False): """ Setter method for isns_ipaddress, mapped from YANG variable /isns/isns_vrf/isns_ipaddress (inet:ip-address) If this variable is read-only (config: false) in the source YANG file, then _set_isns_ipaddress is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_isns_ipaddress() directly. YANG Description: This specifies the IP address of the vrf instance. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=[RestrictedClassType(base_type=unicode, restriction_dict={'pattern': u'(([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])\\.){3}([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])(%[\\p{N}\\p{L}]+)?'}),RestrictedClassType(base_type=unicode, restriction_dict={'pattern': u'((:|[0-9a-fA-F]{0,4}):)([0-9a-fA-F]{0,4}:){0,5}((([0-9a-fA-F]{0,4}:)?(:|[0-9a-fA-F]{0,4}))|(((25[0-5]|2[0-4][0-9]|[01]?[0-9]?[0-9])\\.){3}(25[0-5]|2[0-4][0-9]|[01]?[0-9]?[0-9])))(%[\\p{N}\\p{L}]+)?'}),], is_leaf=True, yang_name="isns-ipaddress", rest_name="isns-ipaddress", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'iSNS VRF forwarding IP address A.B.C.D format', u'hidden': u'isns-ipaddress'}}, namespace='urn:brocade.com:mgmt:brocade-isns', defining_module='brocade-isns', yang_type='inet:ip-address', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """isns_ipaddress must be of a type compatible with inet:ip-address""", 'defined-type': "inet:ip-address", 'generated-type': """YANGDynClass(base=[RestrictedClassType(base_type=unicode, restriction_dict={'pattern': u'(([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])\\.){3}([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])(%[\\p{N}\\p{L}]+)?'}),RestrictedClassType(base_type=unicode, restriction_dict={'pattern': u'((:|[0-9a-fA-F]{0,4}):)([0-9a-fA-F]{0,4}:){0,5}((([0-9a-fA-F]{0,4}:)?(:|[0-9a-fA-F]{0,4}))|(((25[0-5]|2[0-4][0-9]|[01]?[0-9]?[0-9])\\.){3}(25[0-5]|2[0-4][0-9]|[01]?[0-9]?[0-9])))(%[\\p{N}\\p{L}]+)?'}),], is_leaf=True, yang_name="isns-ipaddress", rest_name="isns-ipaddress", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'iSNS VRF forwarding IP address A.B.C.D format', u'hidden': u'isns-ipaddress'}}, namespace='urn:brocade.com:mgmt:brocade-isns', defining_module='brocade-isns', yang_type='inet:ip-address', is_config=True)""", }) self.__isns_ipaddress = t if hasattr(self, '_set'): self._set()
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Setter method for isns_ipaddress, mapped from YANG variable /isns/isns_vrf/isns_ipaddress (inet:ip-address) If this variable is read-only (config: false) in the source YANG file, then _set_isns_ipaddress is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_isns_ipaddress() directly. YANG Description: This specifies the IP address of the vrf instance.
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python
train
sods/ods
pods/notebook.py
https://github.com/sods/ods/blob/3995c659f25a0a640f6009ed7fcc2559ce659b1d/pods/notebook.py#L68-L98
def code_toggle(start_show=False, message=None): """Toggling on and off code in a notebook. :param start_show: Whether to display the code or not on first load (default is False). :type start_show: bool :param message: the message used to toggle display of the code. :type message: string The tip that this idea is based on is from Damian Kao (http://blog.nextgenetics.net/?e=102).""" html ='<script>\n' if message is None: message = u'The raw code for this jupyter notebook can be hidden for easier reading.' if start_show: html += u'code_show=true;\n' else: html += u'code_show=false;\n' html+='''function code_toggle() { if (code_show){ $('div.input').show(); } else { $('div.input').hide(); } code_show = !code_show } $( document ).ready(code_toggle); </script> ''' html += message + ' To toggle on/off the raw code, click <a href="javascript:code_toggle()">here</a>.' display(HTML(html))
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Toggling on and off code in a notebook. :param start_show: Whether to display the code or not on first load (default is False). :type start_show: bool :param message: the message used to toggle display of the code. :type message: string The tip that this idea is based on is from Damian Kao (http://blog.nextgenetics.net/?e=102).
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python
train
GeospatialPython/pyshp
shapefile.py
https://github.com/GeospatialPython/pyshp/blob/71231ddc5aa54f155d4f0563c56006fffbfc84e7/shapefile.py#L1303-L1335
def __dbfHeader(self): """Writes the dbf header and field descriptors.""" f = self.__getFileObj(self.dbf) f.seek(0) version = 3 year, month, day = time.localtime()[:3] year -= 1900 # Remove deletion flag placeholder from fields for field in self.fields: if field[0].startswith("Deletion"): self.fields.remove(field) numRecs = self.recNum numFields = len(self.fields) headerLength = numFields * 32 + 33 if headerLength >= 65535: raise ShapefileException( "Shapefile dbf header length exceeds maximum length.") recordLength = sum([int(field[2]) for field in self.fields]) + 1 header = pack('<BBBBLHH20x', version, year, month, day, numRecs, headerLength, recordLength) f.write(header) # Field descriptors for field in self.fields: name, fieldType, size, decimal = field name = b(name, self.encoding, self.encodingErrors) name = name.replace(b' ', b'_') name = name.ljust(11).replace(b' ', b'\x00') fieldType = b(fieldType, 'ascii') size = int(size) fld = pack('<11sc4xBB14x', name, fieldType, size, decimal) f.write(fld) # Terminator f.write(b'\r')
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Writes the dbf header and field descriptors.
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python
train
theislab/scanpy
scanpy/neighbors/__init__.py
https://github.com/theislab/scanpy/blob/9e4e5ee02e04cf618872d9b098e24f0542e8b227/scanpy/neighbors/__init__.py#L862-L870
def _compute_Lp_matrix(self): """See Fouss et al. (2006) and von Luxburg et al. (2007). See Proposition 6 in von Luxburg (2007) and the inline equations right in the text above. """ self.Lp = sum([1/self.eigen_values[i] * np.outer(self.eigen_basis[:, i], self.eigen_basis[:, i]) for i in range(1, self.eigen_values.size)])
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See Fouss et al. (2006) and von Luxburg et al. (2007). See Proposition 6 in von Luxburg (2007) and the inline equations right in the text above.
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python
train
clalancette/pycdlib
pycdlib/headervd.py
https://github.com/clalancette/pycdlib/blob/1e7b77a809e905d67dc71e12d70e850be26b6233/pycdlib/headervd.py#L83-L195
def parse(self, vd, extent_loc): # type: (bytes, int) -> None ''' Parse a Volume Descriptor out of a string. Parameters: vd - The string containing the Volume Descriptor. extent_loc - The location on the ISO of this Volume Descriptor. Returns: Nothing. ''' ################ PVD VERSION ###################### (descriptor_type, identifier, self.version, self.flags, self.system_identifier, self.volume_identifier, unused1, space_size_le, space_size_be, self.escape_sequences, set_size_le, set_size_be, seqnum_le, seqnum_be, logical_block_size_le, logical_block_size_be, path_table_size_le, path_table_size_be, self.path_table_location_le, self.optional_path_table_location_le, self.path_table_location_be, self.optional_path_table_location_be, root_dir_record, self.volume_set_identifier, pub_ident_str, prepare_ident_str, app_ident_str, self.copyright_file_identifier, self.abstract_file_identifier, self.bibliographic_file_identifier, vol_create_date_str, vol_mod_date_str, vol_expire_date_str, vol_effective_date_str, self.file_structure_version, unused2, self.application_use, zero_unused) = struct.unpack_from(self.FMT, vd, 0) # According to Ecma-119, 8.4.1, the primary volume descriptor type # should be 1. if descriptor_type != self._vd_type: raise pycdlibexception.PyCdlibInvalidISO('Invalid volume descriptor') # According to Ecma-119, 8.4.2, the identifier should be 'CD001'. if identifier != b'CD001': raise pycdlibexception.PyCdlibInvalidISO('invalid CD isoIdentification') # According to Ecma-119, 8.4.3, the version should be 1 (or 2 for # ISO9660:1999) expected_versions = [1] if self._vd_type == VOLUME_DESCRIPTOR_TYPE_SUPPLEMENTARY: expected_versions.append(2) if self.version not in expected_versions: raise pycdlibexception.PyCdlibInvalidISO('Invalid volume descriptor version %d' % (self.version)) # According to Ecma-119, 8.4.4, the first flags field should be 0 for a Primary. if self._vd_type == VOLUME_DESCRIPTOR_TYPE_PRIMARY and self.flags != 0: raise pycdlibexception.PyCdlibInvalidISO('PVD flags field is not zero') # According to Ecma-119, 8.4.5, the first unused field (after the # system identifier and volume identifier) should be 0. if unused1 != 0: raise pycdlibexception.PyCdlibInvalidISO('data in 2nd unused field not zero') # According to Ecma-119, 8.4.9, the escape sequences for a PVD should # be 32 zero-bytes. However, we have seen ISOs in the wild (Fantastic # Night Dreams - Cotton Original (Japan).cue from the psx redump # collection) that don't have this set to 0, so allow anything here. # According to Ecma-119, 8.4.30, the file structure version should be 1. # However, we have seen ISOs in the wild that that don't have this # properly set to one. In those cases, forcibly set it to one and let # it pass. if self._vd_type == VOLUME_DESCRIPTOR_TYPE_PRIMARY: if self.file_structure_version != 1: self.file_structure_version = 1 elif self._vd_type == VOLUME_DESCRIPTOR_TYPE_SUPPLEMENTARY: if self.file_structure_version not in (1, 2): raise pycdlibexception.PyCdlibInvalidISO('File structure version expected to be 1') # According to Ecma-119, 8.4.31, the second unused field should be 0. if unused2 != 0: raise pycdlibexception.PyCdlibInvalidISO('data in 2nd unused field not zero') # According to Ecma-119, the last 653 bytes of the VD should be all 0. # However, we have seen ISOs in the wild that do not follow this, so # relax the check. # Check to make sure that the little-endian and big-endian versions # of the parsed data agree with each other. if space_size_le != utils.swab_32bit(space_size_be): raise pycdlibexception.PyCdlibInvalidISO('Little-endian and big-endian space size disagree') self.space_size = space_size_le if set_size_le != utils.swab_16bit(set_size_be): raise pycdlibexception.PyCdlibInvalidISO('Little-endian and big-endian set size disagree') self.set_size = set_size_le if seqnum_le != utils.swab_16bit(seqnum_be): raise pycdlibexception.PyCdlibInvalidISO('Little-endian and big-endian seqnum disagree') self.seqnum = seqnum_le if logical_block_size_le != utils.swab_16bit(logical_block_size_be): raise pycdlibexception.PyCdlibInvalidISO('Little-endian and big-endian logical block size disagree') self.log_block_size = logical_block_size_le if path_table_size_le != utils.swab_32bit(path_table_size_be): raise pycdlibexception.PyCdlibInvalidISO('Little-endian and big-endian path table size disagree') self.path_tbl_size = path_table_size_le self.path_table_num_extents = utils.ceiling_div(self.path_tbl_size, 4096) * 2 self.path_table_location_be = utils.swab_32bit(self.path_table_location_be) self.publisher_identifier = FileOrTextIdentifier() self.publisher_identifier.parse(pub_ident_str) self.preparer_identifier = FileOrTextIdentifier() self.preparer_identifier.parse(prepare_ident_str) self.application_identifier = FileOrTextIdentifier() self.application_identifier.parse(app_ident_str) self.volume_creation_date = dates.VolumeDescriptorDate() self.volume_creation_date.parse(vol_create_date_str) self.volume_modification_date = dates.VolumeDescriptorDate() self.volume_modification_date.parse(vol_mod_date_str) self.volume_expiration_date = dates.VolumeDescriptorDate() self.volume_expiration_date.parse(vol_expire_date_str) self.volume_effective_date = dates.VolumeDescriptorDate() self.volume_effective_date.parse(vol_effective_date_str) self.root_dir_record.parse(self, root_dir_record, None) self.orig_extent_loc = extent_loc self._initialized = True
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Parse a Volume Descriptor out of a string. Parameters: vd - The string containing the Volume Descriptor. extent_loc - The location on the ISO of this Volume Descriptor. Returns: Nothing.
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python
train
garethr/django-timelog
src/timelog/lib.py
https://github.com/garethr/django-timelog/blob/84c7015248a82faccb9d3fe4e6014645cc9ec103/src/timelog/lib.py#L72-L132
def analyze_log_file(logfile, pattern, reverse_paths=True, progress=True): "Given a log file and regex group and extract the performance data" if progress: lines = count_lines_in(logfile) pbar = ProgressBar(widgets=[Percentage(), Bar()], maxval=lines+1).start() counter = 0 data = {} compiled_pattern = compile(pattern) for line in fileinput.input([logfile]): if progress: counter = counter + 1 parsed = compiled_pattern.findall(line)[0] date = parsed[0] method = parsed[1] path = parsed[2] status = parsed[3] time = parsed[4] sql = parsed[5] sqltime = parsed[6] try: ignore = False for ignored_path in IGNORE_PATHS: compiled_path = compile(ignored_path) if compiled_path.match(path): ignore = True if not ignore: if reverse_paths: view = view_name_from(path) else: view = path key = "%s-%s-%s" % (view, status, method) try: data[key]['count'] = data[key]['count'] + 1 data[key]['times'].append(float(time)) data[key]['sql'].append(int(sql)) data[key]['sqltime'].append(float(sqltime)) except KeyError: data[key] = { 'count': 1, 'status': status, 'view': view, 'method': method, 'times': [float(time)], 'sql': [int(sql)], 'sqltime': [float(sqltime)], } except Resolver404: pass if progress: pbar.update(counter) if progress: pbar.finish() return data
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Given a log file and regex group and extract the performance data
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python
train
Gandi/gandi.cli
gandi/cli/modules/forward.py
https://github.com/Gandi/gandi.cli/blob/6ee5b8fc8ec44b0a6c232043ca610606ad8f693d/gandi/cli/modules/forward.py#L28-L34
def create(cls, domain, source, destinations): """Create a domain mail forward.""" cls.echo('Creating mail forward %s@%s' % (source, domain)) options = {'destinations': list(destinations)} result = cls.call('domain.forward.create', domain, source, options) return result
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Create a domain mail forward.
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python
train
LordDarkula/chess_py
chess_py/core/algebraic/converter.py
https://github.com/LordDarkula/chess_py/blob/14bebc2f8c49ae25c59375cc83d0b38d8ff7281d/chess_py/core/algebraic/converter.py#L308-L330
def make_legal(move, position): """ Converts an incomplete move (initial ``Location`` not specified) and the corresponding position into the a complete move with the most likely starting point specified. If no moves match, ``None`` is returned. :type: move: Move :type: position: Board :rtype: Move """ assert isinstance(move, Move) for legal_move in position.all_possible_moves(move.color): if move.status == notation_const.LONG_ALG: if move.end_loc == legal_move.end_loc and \ move.start_loc == legal_move.start_loc: return legal_move elif move == legal_move: return legal_move raise ValueError("Move {} not legal in \n{}".format(repr(move), position))
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Converts an incomplete move (initial ``Location`` not specified) and the corresponding position into the a complete move with the most likely starting point specified. If no moves match, ``None`` is returned. :type: move: Move :type: position: Board :rtype: Move
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python
train
henzk/django-productline
django_productline/tasks.py
https://github.com/henzk/django-productline/blob/24ff156924c1a8c07b99cbb8a1de0a42b8d81f60/django_productline/tasks.py#L260-L266
def export_context(target_zip): """ Append context.json to target_zip """ from django_productline import utils context_file = tasks.get_context_path() return utils.create_or_append_to_zip(context_file, target_zip, 'context.json')
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Append context.json to target_zip
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python
train
noxdafox/clipspy
clips/facts.py
https://github.com/noxdafox/clipspy/blob/b22d71a6da821c1715d8fa00d7d75cabc09ed364/clips/facts.py#L438-L441
def multifield(self): """True if the slot is a multifield slot.""" return bool(lib.EnvDeftemplateSlotMultiP( self._env, self._tpl, self._name))
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True if the slot is a multifield slot.
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python
train
pyQode/pyqode.core
pyqode/core/managers/backend.py
https://github.com/pyQode/pyqode.core/blob/a99ec6cd22d519394f613309412f8329dc4e90cb/pyqode/core/managers/backend.py#L161-L194
def send_request(self, worker_class_or_function, args, on_receive=None): """ Requests some work to be done by the backend. You can get notified of the work results by passing a callback (on_receive). :param worker_class_or_function: Worker class or function :param args: worker args, any Json serializable objects :param on_receive: an optional callback executed when we receive the worker's results. The callback will be called with one arguments: the results of the worker (object) :raise: backend.NotRunning if the backend process is not running. """ if not self.running: try: # try to restart the backend if it crashed. self.start(self.server_script, interpreter=self.interpreter, args=self.args) except AttributeError: pass # not started yet finally: # caller should try again, later raise NotRunning() else: comm('sending request, worker=%r' % worker_class_or_function) # create a socket, the request will be send as soon as the socket # has connected socket = JsonTcpClient( self.editor, self._port, worker_class_or_function, args, on_receive=on_receive) socket.finished.connect(self._rm_socket) self._sockets.append(socket) # restart heartbeat timer self._heartbeat_timer.start()
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Requests some work to be done by the backend. You can get notified of the work results by passing a callback (on_receive). :param worker_class_or_function: Worker class or function :param args: worker args, any Json serializable objects :param on_receive: an optional callback executed when we receive the worker's results. The callback will be called with one arguments: the results of the worker (object) :raise: backend.NotRunning if the backend process is not running.
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python
train
MDAnalysis/GridDataFormats
gridData/OpenDX.py
https://github.com/MDAnalysis/GridDataFormats/blob/3eeb0432f8cf856912436e4f3e7aba99d3c916be/gridData/OpenDX.py#L353-L393
def write(self, file): """Write the *class array* section. Parameters ---------- file : file Raises ------ ValueError If the `dxtype` is not a valid type, :exc:`ValueError` is raised. """ if self.type not in self.dx_types: raise ValueError(("DX type {} is not supported in the DX format. \n" "Supported valus are: {}\n" "Use the type=<type> keyword argument.").format( self.type, list(self.dx_types.keys()))) typelabel = (self.typequote+self.type+self.typequote) DXclass.write(self,file, 'type {0} rank 0 items {1} data follows'.format( typelabel, self.array.size)) # grid data, serialized as a C array (z fastest varying) # (flat iterator is equivalent to: for x: for y: for z: grid[x,y,z]) # VMD's DX reader requires exactly 3 values per line fmt_string = "{:d}" if (self.array.dtype.kind == 'f' or self.array.dtype.kind == 'c'): precision = numpy.finfo(self.array.dtype).precision fmt_string = "{:."+"{:d}".format(precision)+"f}" values_per_line = 3 values = self.array.flat while 1: try: for i in range(values_per_line): file.write(fmt_string.format(next(values)) + "\t") file.write('\n') except StopIteration: file.write('\n') break file.write('attribute "dep" string "positions"\n')
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Write the *class array* section. Parameters ---------- file : file Raises ------ ValueError If the `dxtype` is not a valid type, :exc:`ValueError` is raised.
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python
valid
tehmaze/natural
natural/phone.py
https://github.com/tehmaze/natural/blob/d7a1fc9de712f9bcf68884a80826a7977df356fb/natural/phone.py#L123-L142
def enum(number, zone='e164.arpa'): ''' Printable DNS ENUM (telephone number mapping) record. :param number: string :param zone: string >>> print(enum('+31 20 5423 1567')) 7.6.5.1.3.2.4.5.0.2.1.3.e164.arpa. >>> print(enum('+31 97 99 6642', zone='e164.spacephone.org')) 2.4.6.6.9.9.7.9.1.3.e164.spacephone.org. ''' number = e164(number).lstrip('+') return u'.'.join([ u'.'.join(number[::-1]), zone.strip(u'.'), '', ])
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Printable DNS ENUM (telephone number mapping) record. :param number: string :param zone: string >>> print(enum('+31 20 5423 1567')) 7.6.5.1.3.2.4.5.0.2.1.3.e164.arpa. >>> print(enum('+31 97 99 6642', zone='e164.spacephone.org')) 2.4.6.6.9.9.7.9.1.3.e164.spacephone.org.
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python
train
danilobellini/dose
dose/_legacy.py
https://github.com/danilobellini/dose/blob/141f48322f7812b7d32e3d5f065d4473a11102a4/dose/_legacy.py#L497-L510
def call_after(lag): """ Parametrized decorator for calling a function after a time ``lag`` given in milliseconds. This cancels simultaneous calls. """ def decorator(func): @wraps(func) def wrapper(*args, **kwargs): wrapper.timer.cancel() # Debounce wrapper.timer = threading.Timer(lag, func, args=args, kwargs=kwargs) wrapper.timer.start() wrapper.timer = threading.Timer(0, lambda: None) # timer.cancel now exists return wrapper return decorator
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Parametrized decorator for calling a function after a time ``lag`` given in milliseconds. This cancels simultaneous calls.
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python
train
cqparts/cqparts
src/cqparts/search.py
https://github.com/cqparts/cqparts/blob/018e87e14c2c4d1d40b4bfe6a7e22bcf9baf0a53/src/cqparts/search.py#L89-L117
def search(**criteria): """ Search registered *component* classes matching the given criteria. :param criteria: search criteria of the form: ``a='1', b='x'`` :return: parts registered with the given criteria :rtype: :class:`set` Will return an empty :class:`set` if nothing is found. :: from cqparts.search import search import cqparts_motors # example of a 3rd party lib # Get all DC motor classes dc_motors = search(type='motor', current_class='dc') # For more complex queries: air_cooled = search(cooling='air') non_aircooled_dcmotors = dc_motors - air_cooled # will be all DC motors that aren't air-cooled """ # Find all parts that match the given criteria results = copy(class_list) # start with full list for (category, value) in criteria.items(): results &= index[category][value] return results
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Search registered *component* classes matching the given criteria. :param criteria: search criteria of the form: ``a='1', b='x'`` :return: parts registered with the given criteria :rtype: :class:`set` Will return an empty :class:`set` if nothing is found. :: from cqparts.search import search import cqparts_motors # example of a 3rd party lib # Get all DC motor classes dc_motors = search(type='motor', current_class='dc') # For more complex queries: air_cooled = search(cooling='air') non_aircooled_dcmotors = dc_motors - air_cooled # will be all DC motors that aren't air-cooled
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python
train
GoogleCloudPlatform/appengine-mapreduce
python/src/mapreduce/status.py
https://github.com/GoogleCloudPlatform/appengine-mapreduce/blob/2045eb3605b6ecb40c83d11dd5442a89fe5c5dd6/python/src/mapreduce/status.py#L242-L262
def get_mapreduce_yaml(parse=parse_mapreduce_yaml): """Locates mapreduce.yaml, loads and parses its info. Args: parse: Used for testing. Returns: MapReduceYaml object. Raises: errors.BadYamlError: when contents is not a valid mapreduce.yaml file or the file is missing. """ mr_yaml_path = find_mapreduce_yaml() if not mr_yaml_path: raise errors.MissingYamlError() mr_yaml_file = open(mr_yaml_path) try: return parse(mr_yaml_file.read()) finally: mr_yaml_file.close()
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Locates mapreduce.yaml, loads and parses its info. Args: parse: Used for testing. Returns: MapReduceYaml object. Raises: errors.BadYamlError: when contents is not a valid mapreduce.yaml file or the file is missing.
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python
train
guaix-ucm/numina
numina/array/cosmetics.py
https://github.com/guaix-ucm/numina/blob/6c829495df8937f77c2de9383c1038ffb3e713e3/numina/array/cosmetics.py#L225-L268
def cosmetics(flat1, flat2 = None, mask=None, lowercut=6.0, uppercut=6.0, siglev=2.0): """Find cosmetic defects in a detector using two flat field images. Two arrays representing flat fields of different exposure times are required. Cosmetic defects are selected as points that deviate significantly of the expected normal distribution of pixels in the ratio between `flat2` and `flat1`. The median of the ratio array is computed and subtracted to it. The standard deviation of the distribution of pixels is computed obtaining the percentiles nearest the pixel values corresponding to `nsig` in the normal CDF. The standar deviation is then the distance between the pixel values divided by two times `nsig`. The ratio image is then normalized with this standard deviation. The values in the ratio above `uppercut` are flagged as hot pixels, and those below '-lowercut` are flagged as dead pixels in the output mask. :parameter flat1: an array representing a flat illuminated exposure. :parameter flat2: an array representing a flat illuminated exposure. :parameter mask: an integer array representing initial mask. :parameter lowercut: values bellow this sigma level are flagged as dead pixels. :parameter uppercut: values above this sigma level are flagged as hot pixels. :parameter siglev: level to estimate the standard deviation. :returns: the updated mask """ if flat2 is None: flat1, flat2 = flat2, flat1 flat1 = numpy.ones_like(flat2) if type(mask) is not numpy.ndarray: mask=numpy.zeros(flat1.shape,dtype='int') ratio, mask = comp_ratio(flat1, flat2, mask) fratio1 = ratio[~mask] central = numpy.median(fratio1) std = robust_std(fratio1, central, siglev) mask_u = ratio > central + uppercut * std mask_d = ratio < central - lowercut * std mask_final = mask_u | mask_d | mask return mask_final
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Find cosmetic defects in a detector using two flat field images. Two arrays representing flat fields of different exposure times are required. Cosmetic defects are selected as points that deviate significantly of the expected normal distribution of pixels in the ratio between `flat2` and `flat1`. The median of the ratio array is computed and subtracted to it. The standard deviation of the distribution of pixels is computed obtaining the percentiles nearest the pixel values corresponding to `nsig` in the normal CDF. The standar deviation is then the distance between the pixel values divided by two times `nsig`. The ratio image is then normalized with this standard deviation. The values in the ratio above `uppercut` are flagged as hot pixels, and those below '-lowercut` are flagged as dead pixels in the output mask. :parameter flat1: an array representing a flat illuminated exposure. :parameter flat2: an array representing a flat illuminated exposure. :parameter mask: an integer array representing initial mask. :parameter lowercut: values bellow this sigma level are flagged as dead pixels. :parameter uppercut: values above this sigma level are flagged as hot pixels. :parameter siglev: level to estimate the standard deviation. :returns: the updated mask
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python
train
wmayner/pyphi
pyphi/models/fmt.py
https://github.com/wmayner/pyphi/blob/deeca69a084d782a6fde7bf26f59e93b593c5d77/pyphi/models/fmt.py#L376-L398
def fmt_sia(sia, ces=True): """Format a |SystemIrreducibilityAnalysis|.""" if ces: body = ( '{ces}' '{partitioned_ces}'.format( ces=fmt_ces( sia.ces, 'Cause-effect structure'), partitioned_ces=fmt_ces( sia.partitioned_ces, 'Partitioned cause-effect structure'))) center_header = True else: body = '' center_header = False title = 'System irreducibility analysis: {BIG_PHI} = {phi}'.format( BIG_PHI=BIG_PHI, phi=fmt_number(sia.phi)) body = header(str(sia.subsystem), body, center=center_header) body = header(str(sia.cut), body, center=center_header) return box(header(title, body, center=center_header))
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Format a |SystemIrreducibilityAnalysis|.
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python
train
Oneiroe/PySimpleAutomata
PySimpleAutomata/NFA.py
https://github.com/Oneiroe/PySimpleAutomata/blob/0f9f2705fd8ddd5d8118bc31552a640f5d00c359/PySimpleAutomata/NFA.py#L232-L265
def nfa_nonemptiness_check(nfa: dict) -> bool: """ Checks if the input NFA reads any language other than the empty one, returning True/False. The language L(A) recognized by the automaton A is nonempty iff there are states :math:`s ∈ S_0` and :math:`t ∈ F` such that t is connected to s. Thus, automata nonemptiness is equivalent to graph reachability. A breadth-first-search algorithm can construct in linear time the set of all states connected to a state in :math:`S_0`. A is nonempty iff this set intersects F nontrivially. :param dict nfa: input NFA. :return: *(bool)*, True if the input nfa is nonempty, False otherwise. """ # BFS queue = list() visited = set() for state in nfa['initial_states']: visited.add(state) queue.append(state) while queue: state = queue.pop(0) visited.add(state) for a in nfa['alphabet']: if (state, a) in nfa['transitions']: for next_state in nfa['transitions'][state, a]: if next_state in nfa['accepting_states']: return True if next_state not in visited: queue.append(next_state) return False
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Checks if the input NFA reads any language other than the empty one, returning True/False. The language L(A) recognized by the automaton A is nonempty iff there are states :math:`s ∈ S_0` and :math:`t ∈ F` such that t is connected to s. Thus, automata nonemptiness is equivalent to graph reachability. A breadth-first-search algorithm can construct in linear time the set of all states connected to a state in :math:`S_0`. A is nonempty iff this set intersects F nontrivially. :param dict nfa: input NFA. :return: *(bool)*, True if the input nfa is nonempty, False otherwise.
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python
train
jbasko/configmanager
configmanager/items.py
https://github.com/jbasko/configmanager/blob/1d7229ce367143c7210d8e5f0782de03945a1721/configmanager/items.py#L315-L327
def get_path(self): """ Calculate item's path in configuration tree. Use this sparingly -- path is calculated by going up the configuration tree. For a large number of items, it is more efficient to use iterators that return paths as keys. Path value is stable only once the configuration tree is completely initialised. """ if self.section: return self.section.get_path() + (self.name,) else: return self.name,
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Calculate item's path in configuration tree. Use this sparingly -- path is calculated by going up the configuration tree. For a large number of items, it is more efficient to use iterators that return paths as keys. Path value is stable only once the configuration tree is completely initialised.
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python
train
belbio/bel
bel/lang/completion.py
https://github.com/belbio/bel/blob/60333e8815625b942b4836903f3b618cf44b3771/bel/lang/completion.py#L494-L582
def add_completions( replace_list: list, belstr: str, replace_span: Span, completion_text: str ) -> List[Mapping[str, Any]]: """Create completions to return given replacement list Args: replace_list: list of completion replacement values belstr: BEL String replace_span: start, stop of belstr to replace completion_text: text to use for completion - used for creating highlight Returns: [{ "replacement": replacement, "cursor_loc": cursor_loc, "highlight": highlight, "label": label, }] """ completions = [] for r in replace_list: # if '(' not in belstr: # replacement = f'{r["replacement"]}()' # cursor_loc = len(replacement) - 1 # inside parenthesis # elif r['type'] == 'Function' and replace_span[1] == len(belstr) - 1: if len(belstr) > 0: belstr_end = len(belstr) - 1 else: belstr_end = 0 log.debug( f'Replace list {r} Replace_span {replace_span} BELstr: {belstr} Len: {belstr_end} Test1 {r["type"] == "Function"} Test2 {replace_span[1] + 1 == len(belstr)}' ) # Put a space between comma and following function arg if ( r["type"] == "Function" and replace_span[0] > 0 and belstr[replace_span[0] - 1] == "," ): log.debug("prior char is a comma") replacement = ( belstr[0 : replace_span[0]] + " " + f"{r['replacement']}()" + belstr[replace_span[1] + 1 :] ) cursor_loc = len( belstr[0 : replace_span[0]] + " " + f"{r['replacement']}()" ) # Put a space between comman and following NSArg or StrArg elif replace_span[0] > 0 and belstr[replace_span[0] - 1] == ",": log.debug("prior char is a comma") replacement = ( belstr[0 : replace_span[0]] + " " + r["replacement"] + belstr[replace_span[1] + 1 :] ) cursor_loc = len(belstr[0 : replace_span[0]] + " " + r["replacement"]) # Add function to end of belstr elif r["type"] == "Function" and replace_span[1] >= belstr_end: replacement = belstr[0 : replace_span[0]] + f"{r['replacement']}()" cursor_loc = len(replacement) - 1 # inside parenthesis log.debug(f"Replacement: {replacement}") # Insert replacement in beginning or middle of belstr else: replacement = ( belstr[0 : replace_span[0]] + r["replacement"] + belstr[replace_span[1] + 1 :] ) cursor_loc = len( belstr[0 : replace_span[0]] + r["replacement"] ) # move cursor just past replacement completions.append( { "replacement": replacement, "cursor_loc": cursor_loc, "highlight": r["highlight"], "label": r["label"], } ) return completions
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Create completions to return given replacement list Args: replace_list: list of completion replacement values belstr: BEL String replace_span: start, stop of belstr to replace completion_text: text to use for completion - used for creating highlight Returns: [{ "replacement": replacement, "cursor_loc": cursor_loc, "highlight": highlight, "label": label, }]
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python
train
PGower/PyCanvas
pycanvas/apis/calendar_events.py
https://github.com/PGower/PyCanvas/blob/68520005382b440a1e462f9df369f54d364e21e8/pycanvas/apis/calendar_events.py#L321-L396
def update_calendar_event(self, id, calendar_event_child_event_data_X_context_code=None, calendar_event_child_event_data_X_end_at=None, calendar_event_child_event_data_X_start_at=None, calendar_event_context_code=None, calendar_event_description=None, calendar_event_end_at=None, calendar_event_location_address=None, calendar_event_location_name=None, calendar_event_start_at=None, calendar_event_time_zone_edited=None, calendar_event_title=None): """ Update a calendar event. Update and return a calendar event """ path = {} data = {} params = {} # REQUIRED - PATH - id """ID""" path["id"] = id # OPTIONAL - calendar_event[context_code] """Context code of the course/group/user to move this event to. Scheduler appointments and events with section-specific times cannot be moved between calendars.""" if calendar_event_context_code is not None: data["calendar_event[context_code]"] = calendar_event_context_code # OPTIONAL - calendar_event[title] """Short title for the calendar event.""" if calendar_event_title is not None: data["calendar_event[title]"] = calendar_event_title # OPTIONAL - calendar_event[description] """Longer HTML description of the event.""" if calendar_event_description is not None: data["calendar_event[description]"] = calendar_event_description # OPTIONAL - calendar_event[start_at] """Start date/time of the event.""" if calendar_event_start_at is not None: data["calendar_event[start_at]"] = calendar_event_start_at # OPTIONAL - calendar_event[end_at] """End date/time of the event.""" if calendar_event_end_at is not None: data["calendar_event[end_at]"] = calendar_event_end_at # OPTIONAL - calendar_event[location_name] """Location name of the event.""" if calendar_event_location_name is not None: data["calendar_event[location_name]"] = calendar_event_location_name # OPTIONAL - calendar_event[location_address] """Location address""" if calendar_event_location_address is not None: data["calendar_event[location_address]"] = calendar_event_location_address # OPTIONAL - calendar_event[time_zone_edited] """Time zone of the user editing the event. Allowed time zones are {http://www.iana.org/time-zones IANA time zones} or friendlier {http://api.rubyonrails.org/classes/ActiveSupport/TimeZone.html Ruby on Rails time zones}.""" if calendar_event_time_zone_edited is not None: data["calendar_event[time_zone_edited]"] = calendar_event_time_zone_edited # OPTIONAL - calendar_event[child_event_data][X][start_at] """Section-level start time(s) if this is a course event. X can be any identifier, provided that it is consistent across the start_at, end_at and context_code""" if calendar_event_child_event_data_X_start_at is not None: data["calendar_event[child_event_data][X][start_at]"] = calendar_event_child_event_data_X_start_at # OPTIONAL - calendar_event[child_event_data][X][end_at] """Section-level end time(s) if this is a course event.""" if calendar_event_child_event_data_X_end_at is not None: data["calendar_event[child_event_data][X][end_at]"] = calendar_event_child_event_data_X_end_at # OPTIONAL - calendar_event[child_event_data][X][context_code] """Context code(s) corresponding to the section-level start and end time(s).""" if calendar_event_child_event_data_X_context_code is not None: data["calendar_event[child_event_data][X][context_code]"] = calendar_event_child_event_data_X_context_code self.logger.debug("PUT /api/v1/calendar_events/{id} with query params: {params} and form data: {data}".format(params=params, data=data, **path)) return self.generic_request("PUT", "/api/v1/calendar_events/{id}".format(**path), data=data, params=params, no_data=True)
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Update a calendar event. Update and return a calendar event
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python
train
kplindegaard/smbus2
smbus2/smbus2.py
https://github.com/kplindegaard/smbus2/blob/a1088a03438dba84c266b73ad61b0c06750d0961/smbus2/smbus2.py#L409-L427
def read_word_data(self, i2c_addr, register, force=None): """ Read a single word (2 bytes) from a given register. :param i2c_addr: i2c address :type i2c_addr: int :param register: Register to read :type register: int :param force: :type force: Boolean :return: 2-byte word :rtype: int """ self._set_address(i2c_addr, force=force) msg = i2c_smbus_ioctl_data.create( read_write=I2C_SMBUS_READ, command=register, size=I2C_SMBUS_WORD_DATA ) ioctl(self.fd, I2C_SMBUS, msg) return msg.data.contents.word
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Read a single word (2 bytes) from a given register. :param i2c_addr: i2c address :type i2c_addr: int :param register: Register to read :type register: int :param force: :type force: Boolean :return: 2-byte word :rtype: int
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python
train
Kozea/wdb
client/wdb/__init__.py
https://github.com/Kozea/wdb/blob/6af7901b02e866d76f8b0a697a8c078e5b70d1aa/client/wdb/__init__.py#L813-L876
def interaction( self, frame, tb=None, exception='Wdb', exception_description='Stepping', init=None, shell=False, shell_vars=None, source=None, iframe_mode=False, timeout=None, post_mortem=False ): """User interaction handling blocking on socket receive""" log.info( 'Interaction %r %r %r %r' % (frame, tb, exception, exception_description) ) self.reconnect_if_needed() self.stepping = not shell if not iframe_mode: opts = {} if shell: opts['type_'] = 'shell' if post_mortem: opts['type_'] = 'pm' self.open_browser(**opts) lvl = len(self.interaction_stack) if lvl: exception_description += ' [recursive%s]' % ( '^%d' % lvl if lvl > 1 else '' ) interaction = Interaction( self, frame, tb, exception, exception_description, init=init, shell=shell, shell_vars=shell_vars, source=source, timeout=timeout ) self.interaction_stack.append(interaction) # For meta debugging purpose self._ui = interaction if self.begun: # Each new state sends the trace and selects a frame interaction.init() else: self.begun = True interaction.loop() self.interaction_stack.pop() if lvl: self.interaction_stack[-1].init()
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User interaction handling blocking on socket receive
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python
train
phn/lineid_plot
lineid_plot/lineid_plot.py
https://github.com/phn/lineid_plot/blob/7c7a1af53fe439b3a7c5a57f01680575837fb978/lineid_plot/lineid_plot.py#L124-L219
def adjust_boxes(line_wave, box_widths, left_edge, right_edge, max_iter=1000, adjust_factor=0.35, factor_decrement=3.0, fd_p=0.75): """Ajdust given boxes so that they don't overlap. Parameters ---------- line_wave: list or array of floats Line wave lengths. These are assumed to be the initial y (wave length) location of the boxes. box_widths: list or array of floats Width of box containing labels for each line identification. left_edge: float Left edge of valid data i.e., wave length minimum. right_edge: float Right edge of valid data i.e., wave lengths maximum. max_iter: int Maximum number of iterations to attempt. adjust_factor: float Gap between boxes are reduced or increased by this factor after each iteration. factor_decrement: float The `adjust_factor` itself if reduced by this factor, after certain number of iterations. This is useful for crowded regions. fd_p: float Percentage, given as a fraction between 0 and 1, after which adjust_factor must be reduced by a factor of `factor_decrement`. Default is set to 0.75. Returns ------- wlp, niter, changed: (float, float, float) The new y (wave length) location of the text boxes, the number of iterations used and a flag to indicated whether any changes to the input locations were made or not. Notes ----- This is a direct translation of the code in lineid_plot.pro file in NASA IDLAstro library. Positions are returned either when the boxes no longer overlap or when `max_iter` number of iterations are completed. So if there are many boxes, there is a possibility that the final box locations overlap. References ---------- + http://idlastro.gsfc.nasa.gov/ftp/pro/plot/lineid_plot.pro + http://idlastro.gsfc.nasa.gov/ """ # Adjust positions. niter = 0 changed = True nlines = len(line_wave) wlp = line_wave[:] while changed: changed = False for i in range(nlines): if i > 0: diff1 = wlp[i] - wlp[i - 1] separation1 = (box_widths[i] + box_widths[i - 1]) / 2.0 else: diff1 = wlp[i] - left_edge + box_widths[i] * 1.01 separation1 = box_widths[i] if i < nlines - 2: diff2 = wlp[i + 1] - wlp[i] separation2 = (box_widths[i] + box_widths[i + 1]) / 2.0 else: diff2 = right_edge + box_widths[i] * 1.01 - wlp[i] separation2 = box_widths[i] if diff1 < separation1 or diff2 < separation2: if wlp[i] == left_edge: diff1 = 0 if wlp[i] == right_edge: diff2 = 0 if diff2 > diff1: wlp[i] = wlp[i] + separation2 * adjust_factor wlp[i] = wlp[i] if wlp[i] < right_edge else \ right_edge else: wlp[i] = wlp[i] - separation1 * adjust_factor wlp[i] = wlp[i] if wlp[i] > left_edge else \ left_edge changed = True niter += 1 if niter == max_iter * fd_p: adjust_factor /= factor_decrement if niter >= max_iter: break return wlp, changed, niter
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Ajdust given boxes so that they don't overlap. Parameters ---------- line_wave: list or array of floats Line wave lengths. These are assumed to be the initial y (wave length) location of the boxes. box_widths: list or array of floats Width of box containing labels for each line identification. left_edge: float Left edge of valid data i.e., wave length minimum. right_edge: float Right edge of valid data i.e., wave lengths maximum. max_iter: int Maximum number of iterations to attempt. adjust_factor: float Gap between boxes are reduced or increased by this factor after each iteration. factor_decrement: float The `adjust_factor` itself if reduced by this factor, after certain number of iterations. This is useful for crowded regions. fd_p: float Percentage, given as a fraction between 0 and 1, after which adjust_factor must be reduced by a factor of `factor_decrement`. Default is set to 0.75. Returns ------- wlp, niter, changed: (float, float, float) The new y (wave length) location of the text boxes, the number of iterations used and a flag to indicated whether any changes to the input locations were made or not. Notes ----- This is a direct translation of the code in lineid_plot.pro file in NASA IDLAstro library. Positions are returned either when the boxes no longer overlap or when `max_iter` number of iterations are completed. So if there are many boxes, there is a possibility that the final box locations overlap. References ---------- + http://idlastro.gsfc.nasa.gov/ftp/pro/plot/lineid_plot.pro + http://idlastro.gsfc.nasa.gov/
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python
train
iLampard/x-utils
xutils/config_utils.py
https://github.com/iLampard/x-utils/blob/291d92832ee0e0c89bc22e10ecf2f44445e0d300/xutils/config_utils.py#L38-L73
def merge_configs(to_be_merged, default): """Merges two configuration dictionaries by overwriting values with same keys, with the priority on values given on the 'left' side, so the to_be_merged dict. Notice that with lists in the configuration, it skips from the default (right side) the tuples in that which already exist in the left side to_be_merged list. This is used to be able to override time intervals for default values in the configuration. Example: In [1]: x = [["get_stats_disk_usage_for_database", 180], ["get_stats_tx_rate_for_database", 500]] In [2]: y = [["get_stats_seconds_since_last_vacuum_per_table", 60], ["get_stats_tx_rate_for_database", 60]] In [3]: merge_configs(x, y) Out[3]: [['get_stats_disk_usage_for_database', 180], ['get_stats_tx_rate_for_database', 500], ['get_stats_seconds_since_last_vacuum_per_table', 60]] """ if isinstance(to_be_merged, dict) and isinstance(default, dict): for k, v in default.items(): if k not in to_be_merged: to_be_merged[k] = v else: to_be_merged[k] = merge_configs(to_be_merged[k], v) elif isinstance(to_be_merged, list) and isinstance(default, list): same_keys = set() for x in to_be_merged: for y in default: if isinstance(x, (list, set, tuple)) and isinstance(y, (list, set, tuple)) and len( x) > 0 and len(y) > 0 and x[0] == y[0]: same_keys.add(x[0]) for y in default: if not isinstance(y, (list, set, tuple)) or y[0] not in same_keys: to_be_merged.append(y) return to_be_merged
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Merges two configuration dictionaries by overwriting values with same keys, with the priority on values given on the 'left' side, so the to_be_merged dict. Notice that with lists in the configuration, it skips from the default (right side) the tuples in that which already exist in the left side to_be_merged list. This is used to be able to override time intervals for default values in the configuration. Example: In [1]: x = [["get_stats_disk_usage_for_database", 180], ["get_stats_tx_rate_for_database", 500]] In [2]: y = [["get_stats_seconds_since_last_vacuum_per_table", 60], ["get_stats_tx_rate_for_database", 60]] In [3]: merge_configs(x, y) Out[3]: [['get_stats_disk_usage_for_database', 180], ['get_stats_tx_rate_for_database', 500], ['get_stats_seconds_since_last_vacuum_per_table', 60]]
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python
train
senaite/senaite.core
bika/lims/content/analysisprofile.py
https://github.com/senaite/senaite.core/blob/7602ce2ea2f9e81eb34e20ce17b98a3e70713f85/bika/lims/content/analysisprofile.py#L212-L235
def remove_service(self, service): """Removes the service passed in from the services offered by the current Profile. If the Analysis Service passed in is not assigned to this Analysis Profile, returns False. :param service: the service to be removed from this Analysis Profile :type service: AnalysisService :return: True if the AnalysisService has been removed successfully """ obj = api.get_object(service) uid = api.get_uid(obj) # Remove the service from the referenced services services = self.getService() num_services = len(services) services.remove(obj) self.setService(services) removed = len(services) < num_services # Remove the service from the settings map settings = self.getAnalysisServicesSettings() settings = [item for item in settings if item.get('uid', '') != uid] self.setAnalysisServicesSettings(settings) return removed
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Removes the service passed in from the services offered by the current Profile. If the Analysis Service passed in is not assigned to this Analysis Profile, returns False. :param service: the service to be removed from this Analysis Profile :type service: AnalysisService :return: True if the AnalysisService has been removed successfully
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python
train
maas/python-libmaas
maas/client/viscera/block_devices.py
https://github.com/maas/python-libmaas/blob/4092c68ef7fb1753efc843569848e2bcc3415002/maas/client/viscera/block_devices.py#L130-L133
async def unformat(self): """Unformat this block device.""" self._data = await self._handler.unformat( system_id=self.node.system_id, id=self.id)
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Unformat this block device.
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python
train
tmux-python/tmuxp
tmuxp/cli.py
https://github.com/tmux-python/tmuxp/blob/f4aa2e26589a4311131898d2e4a85cb1876b5c9b/tmuxp/cli.py#L66-L84
def get_tmuxinator_dir(): """ Return tmuxinator configuration directory. Checks for ``TMUXINATOR_CONFIG`` environmental variable. Returns ------- str : absolute path to tmuxinator config directory See Also -------- :meth:`tmuxp.config.import_tmuxinator` """ if 'TMUXINATOR_CONFIG' in os.environ: return os.path.expanduser(os.environ['TMUXINATOR_CONFIG']) return os.path.expanduser('~/.tmuxinator/')
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Return tmuxinator configuration directory. Checks for ``TMUXINATOR_CONFIG`` environmental variable. Returns ------- str : absolute path to tmuxinator config directory See Also -------- :meth:`tmuxp.config.import_tmuxinator`
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python
train
readbeyond/aeneas
aeneas/diagnostics.py
https://github.com/readbeyond/aeneas/blob/9d95535ad63eef4a98530cfdff033b8c35315ee1/aeneas/diagnostics.py#L195-L209
def check_cdtw(cls): """ Check whether Python C extension ``cdtw`` can be imported. Return ``True`` on failure and ``False`` on success. :rtype: bool """ if gf.can_run_c_extension("cdtw"): gf.print_success(u"aeneas.cdtw AVAILABLE") return False gf.print_warning(u"aeneas.cdtw NOT AVAILABLE") gf.print_info(u" You can still run aeneas but it will be significantly slower") gf.print_info(u" Please refer to the installation documentation for details") return True
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Check whether Python C extension ``cdtw`` can be imported. Return ``True`` on failure and ``False`` on success. :rtype: bool
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python
train
magrathealabs/feito
feito/prospector.py
https://github.com/magrathealabs/feito/blob/4179e40233ccf6e5a6c9892e528595690ce9ef43/feito/prospector.py#L10-L16
def run(self): """ Runs prospector in the input files and returns a json with the analysis """ arg_prospector = f'prospector --output-format json {self.repo.diff_files()}' analysis = subprocess.run(arg_prospector, stdout=subprocess.PIPE, shell=True) return json.loads(analysis.stdout)
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Runs prospector in the input files and returns a json with the analysis
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python
train
diffeo/yakonfig
yakonfig/toplevel.py
https://github.com/diffeo/yakonfig/blob/412e195da29b4f4fc7b72967c192714a6f5eaeb5/yakonfig/toplevel.py#L414-L441
def fill_in_arguments(config, modules, args): """Fill in configuration fields from command-line arguments. `config` is a dictionary holding the initial configuration, probably the result of :func:`assemble_default_config`. It reads through `modules`, and for each, fills in any configuration values that are provided in `args`. `config` is modified in place. `args` may be either a dictionary or an object (as the result of :mod:`argparse`). :param dict config: configuration tree to update :param modules: modules or Configurable instances to use :type modules: iterable of :class:`~yakonfig.configurable.Configurable` :param args: command-line objects :paramtype args: dict or object :return: config """ def work_in(config, module, name): rkeys = getattr(module, 'runtime_keys', {}) for (attr, cname) in iteritems(rkeys): v = args.get(attr, None) if v is not None: config[cname] = v if not isinstance(args, collections.Mapping): args = vars(args) return _walk_config(config, modules, work_in)
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Fill in configuration fields from command-line arguments. `config` is a dictionary holding the initial configuration, probably the result of :func:`assemble_default_config`. It reads through `modules`, and for each, fills in any configuration values that are provided in `args`. `config` is modified in place. `args` may be either a dictionary or an object (as the result of :mod:`argparse`). :param dict config: configuration tree to update :param modules: modules or Configurable instances to use :type modules: iterable of :class:`~yakonfig.configurable.Configurable` :param args: command-line objects :paramtype args: dict or object :return: config
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python
train
Opentrons/opentrons
api/src/opentrons/protocol_api/contexts.py
https://github.com/Opentrons/opentrons/blob/a7c15cc2636ecb64ab56c7edc1d8a57163aaeadf/api/src/opentrons/protocol_api/contexts.py#L1063-L1082
def distribute(self, volume: float, source: Well, dest: List[Well], *args, **kwargs) -> 'InstrumentContext': """ Move a volume of liquid from one source to multiple destinations. :param volume: The amount of volume to distribute to each destination well. :param source: A single well from where liquid will be aspirated. :param dest: List of Wells where liquid will be dispensed to. :param kwargs: See :py:meth:`transfer`. :returns: This instance """ self._log.debug("Distributing {} from {} to {}" .format(volume, source, dest)) kwargs['mode'] = 'distribute' kwargs['disposal_volume'] = kwargs.get('disposal_vol', self.min_volume) return self.transfer(volume, source, dest, **kwargs)
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Move a volume of liquid from one source to multiple destinations. :param volume: The amount of volume to distribute to each destination well. :param source: A single well from where liquid will be aspirated. :param dest: List of Wells where liquid will be dispensed to. :param kwargs: See :py:meth:`transfer`. :returns: This instance
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python
train
saltstack/salt
salt/modules/ldap3.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/ldap3.py#L109-L306
def connect(connect_spec=None): '''Connect and optionally bind to an LDAP server. :param connect_spec: This can be an LDAP connection object returned by a previous call to :py:func:`connect` (in which case the argument is simply returned), ``None`` (in which case an empty dict is used), or a dict with the following keys: * ``'backend'`` Optional; default depends on which Python LDAP modules are installed. Name of the Python LDAP module to use. Only ``'ldap'`` is supported at the moment. * ``'url'`` Optional; defaults to ``'ldapi:///'``. URL to the LDAP server. * ``'bind'`` Optional; defaults to ``None``. Describes how to bind an identity to the LDAP connection. If ``None``, an anonymous connection is made. Valid keys: * ``'method'`` Optional; defaults to ``None``. The authentication method to use. Valid values include but are not necessarily limited to ``'simple'``, ``'sasl'``, and ``None``. If ``None``, an anonymous connection is made. Available methods depend on the chosen backend. * ``'mechanism'`` Optional; defaults to ``'EXTERNAL'``. The SASL mechanism to use. Ignored unless the method is ``'sasl'``. Available methods depend on the chosen backend and the server's capabilities. * ``'credentials'`` Optional; defaults to ``None``. An object specific to the chosen SASL mechanism and backend that represents the authentication credentials. Ignored unless the method is ``'sasl'``. For the ``'ldap'`` backend, this is a dictionary. If ``None``, an empty dict is used. Keys: * ``'args'`` Optional; defaults to an empty list. A list of arguments to pass to the SASL mechanism constructor. See the SASL mechanism constructor documentation in the ``ldap.sasl`` Python module. * ``'kwargs'`` Optional; defaults to an empty dict. A dict of keyword arguments to pass to the SASL mechanism constructor. See the SASL mechanism constructor documentation in the ``ldap.sasl`` Python module. * ``'dn'`` Optional; defaults to an empty string. The distinguished name to bind. * ``'password'`` Optional; defaults to an empty string. Password for binding. Ignored if the method is ``'sasl'``. * ``'tls'`` Optional; defaults to ``None``. A backend-specific object containing settings to override default TLS behavior. For the ``'ldap'`` backend, this is a dictionary. Not all settings in this dictionary are supported by all versions of ``python-ldap`` or the underlying TLS library. If ``None``, an empty dict is used. Possible keys: * ``'starttls'`` If present, initiate a TLS connection using StartTLS. (The value associated with this key is ignored.) * ``'cacertdir'`` Set the path of the directory containing CA certificates. * ``'cacertfile'`` Set the pathname of the CA certificate file. * ``'certfile'`` Set the pathname of the certificate file. * ``'cipher_suite'`` Set the allowed cipher suite. * ``'crlcheck'`` Set the CRL evaluation strategy. Valid values are ``'none'``, ``'peer'``, and ``'all'``. * ``'crlfile'`` Set the pathname of the CRL file. * ``'dhfile'`` Set the pathname of the file containing the parameters for Diffie-Hellman ephemeral key exchange. * ``'keyfile'`` Set the pathname of the certificate key file. * ``'newctx'`` If present, instruct the underlying TLS library to create a new TLS context. (The value associated with this key is ignored.) * ``'protocol_min'`` Set the minimum protocol version. * ``'random_file'`` Set the pathname of the random file when ``/dev/random`` and ``/dev/urandom`` are not available. * ``'require_cert'`` Set the certificate validation policy. Valid values are ``'never'``, ``'hard'``, ``'demand'``, ``'allow'``, and ``'try'``. * ``'opts'`` Optional; defaults to ``None``. A backend-specific object containing options for the backend. For the ``'ldap'`` backend, this is a dictionary of OpenLDAP options to set. If ``None``, an empty dict is used. Each key is a the name of an OpenLDAP option constant without the ``'LDAP_OPT_'`` prefix, then converted to lower case. :returns: an object representing an LDAP connection that can be used as the ``connect_spec`` argument to any of the functions in this module (to avoid the overhead of making and terminating multiple connections). This object should be used as a context manager. It is safe to nest ``with`` statements. CLI example: .. code-block:: bash salt '*' ldap3.connect "{ 'url': 'ldaps://ldap.example.com/', 'bind': { 'method': 'simple', 'dn': 'cn=admin,dc=example,dc=com', 'password': 'secret'} }" ''' if isinstance(connect_spec, _connect_ctx): return connect_spec if connect_spec is None: connect_spec = {} backend_name = connect_spec.get('backend', 'ldap') if backend_name not in available_backends: raise ValueError('unsupported backend or required Python module' + ' unavailable: {0}'.format(backend_name)) url = connect_spec.get('url', 'ldapi:///') try: l = ldap.initialize(url) l.protocol_version = ldap.VERSION3 # set up tls tls = connect_spec.get('tls', None) if tls is None: tls = {} vars = {} for k, v in six.iteritems(tls): if k in ('starttls', 'newctx'): vars[k] = True elif k in ('crlcheck', 'require_cert'): l.set_option(getattr(ldap, 'OPT_X_TLS_' + k.upper()), getattr(ldap, 'OPT_X_TLS_' + v.upper())) else: l.set_option(getattr(ldap, 'OPT_X_TLS_' + k.upper()), v) if vars.get('starttls', False): l.start_tls_s() if vars.get('newctx', False): l.set_option(ldap.OPT_X_TLS_NEWCTX, 0) # set up other options l.set_option(ldap.OPT_REFERRALS, 0) opts = connect_spec.get('opts', None) if opts is None: opts = {} for k, v in six.iteritems(opts): opt = getattr(ldap, 'OPT_' + k.upper()) l.set_option(opt, v) _bind(l, connect_spec.get('bind', None)) except ldap.LDAPError as e: _convert_exception(e) return _connect_ctx(l)
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Connect and optionally bind to an LDAP server. :param connect_spec: This can be an LDAP connection object returned by a previous call to :py:func:`connect` (in which case the argument is simply returned), ``None`` (in which case an empty dict is used), or a dict with the following keys: * ``'backend'`` Optional; default depends on which Python LDAP modules are installed. Name of the Python LDAP module to use. Only ``'ldap'`` is supported at the moment. * ``'url'`` Optional; defaults to ``'ldapi:///'``. URL to the LDAP server. * ``'bind'`` Optional; defaults to ``None``. Describes how to bind an identity to the LDAP connection. If ``None``, an anonymous connection is made. Valid keys: * ``'method'`` Optional; defaults to ``None``. The authentication method to use. Valid values include but are not necessarily limited to ``'simple'``, ``'sasl'``, and ``None``. If ``None``, an anonymous connection is made. Available methods depend on the chosen backend. * ``'mechanism'`` Optional; defaults to ``'EXTERNAL'``. The SASL mechanism to use. Ignored unless the method is ``'sasl'``. Available methods depend on the chosen backend and the server's capabilities. * ``'credentials'`` Optional; defaults to ``None``. An object specific to the chosen SASL mechanism and backend that represents the authentication credentials. Ignored unless the method is ``'sasl'``. For the ``'ldap'`` backend, this is a dictionary. If ``None``, an empty dict is used. Keys: * ``'args'`` Optional; defaults to an empty list. A list of arguments to pass to the SASL mechanism constructor. See the SASL mechanism constructor documentation in the ``ldap.sasl`` Python module. * ``'kwargs'`` Optional; defaults to an empty dict. A dict of keyword arguments to pass to the SASL mechanism constructor. See the SASL mechanism constructor documentation in the ``ldap.sasl`` Python module. * ``'dn'`` Optional; defaults to an empty string. The distinguished name to bind. * ``'password'`` Optional; defaults to an empty string. Password for binding. Ignored if the method is ``'sasl'``. * ``'tls'`` Optional; defaults to ``None``. A backend-specific object containing settings to override default TLS behavior. For the ``'ldap'`` backend, this is a dictionary. Not all settings in this dictionary are supported by all versions of ``python-ldap`` or the underlying TLS library. If ``None``, an empty dict is used. Possible keys: * ``'starttls'`` If present, initiate a TLS connection using StartTLS. (The value associated with this key is ignored.) * ``'cacertdir'`` Set the path of the directory containing CA certificates. * ``'cacertfile'`` Set the pathname of the CA certificate file. * ``'certfile'`` Set the pathname of the certificate file. * ``'cipher_suite'`` Set the allowed cipher suite. * ``'crlcheck'`` Set the CRL evaluation strategy. Valid values are ``'none'``, ``'peer'``, and ``'all'``. * ``'crlfile'`` Set the pathname of the CRL file. * ``'dhfile'`` Set the pathname of the file containing the parameters for Diffie-Hellman ephemeral key exchange. * ``'keyfile'`` Set the pathname of the certificate key file. * ``'newctx'`` If present, instruct the underlying TLS library to create a new TLS context. (The value associated with this key is ignored.) * ``'protocol_min'`` Set the minimum protocol version. * ``'random_file'`` Set the pathname of the random file when ``/dev/random`` and ``/dev/urandom`` are not available. * ``'require_cert'`` Set the certificate validation policy. Valid values are ``'never'``, ``'hard'``, ``'demand'``, ``'allow'``, and ``'try'``. * ``'opts'`` Optional; defaults to ``None``. A backend-specific object containing options for the backend. For the ``'ldap'`` backend, this is a dictionary of OpenLDAP options to set. If ``None``, an empty dict is used. Each key is a the name of an OpenLDAP option constant without the ``'LDAP_OPT_'`` prefix, then converted to lower case. :returns: an object representing an LDAP connection that can be used as the ``connect_spec`` argument to any of the functions in this module (to avoid the overhead of making and terminating multiple connections). This object should be used as a context manager. It is safe to nest ``with`` statements. CLI example: .. code-block:: bash salt '*' ldap3.connect "{ 'url': 'ldaps://ldap.example.com/', 'bind': { 'method': 'simple', 'dn': 'cn=admin,dc=example,dc=com', 'password': 'secret'} }"
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python
train
callowayproject/Transmogrify
transmogrify/images2gif.py
https://github.com/callowayproject/Transmogrify/blob/f1f891b8b923b3a1ede5eac7f60531c1c472379e/transmogrify/images2gif.py#L977-L991
def palette_image(self): """ PIL weird interface for making a paletted image: create an image which already has the palette, and use that in Image.quantize. This function returns this palette image. """ if self.pimage is None: palette = [] for i in range(self.NETSIZE): palette.extend(self.colormap[i][:3]) palette.extend([0] * (256 - self.NETSIZE) * 3) # a palette image to use for quant self.pimage = Image.new("P", (1, 1), 0) self.pimage.putpalette(palette) return self.pimage
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PIL weird interface for making a paletted image: create an image which already has the palette, and use that in Image.quantize. This function returns this palette image.
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python
train
timdiels/pytil
pytil/algorithms.py
https://github.com/timdiels/pytil/blob/086a3f8d52caecdd9d1c9f66c8d8a6d38667b00b/pytil/algorithms.py#L43-L71
def multi_way_partitioning(items, bin_count): #TODO rename bin_count -> bins ''' Greedily divide weighted items equally across bins. This approximately solves a multi-way partition problem, minimising the difference between the largest and smallest sum of weights in a bin. Parameters ---------- items : ~typing.Iterable[~typing.Tuple[~typing.Any, float]] Weighted items as ``(item, weight)`` tuples. bin_count : int Number of bins. Returns ------- bins : ~collections_extended.frozenbag[~collections_extended.frozenbag[~typing.Any]] Item bins as a bag of item bags. Notes ---------- - `A greedy solution <http://stackoverflow.com/a/6855546/1031434>`_ - `Problem definition and solutions <http://ijcai.org/Proceedings/09/Papers/096.pdf>`_ ''' bins = [_Bin() for _ in range(bin_count)] for item, weight in sorted(items, key=lambda x: x[1], reverse=True): bin_ = min(bins, key=lambda bin_: bin_.weights_sum) bin_.add(item, weight) return frozenbag(frozenbag(bin_.items) for bin_ in bins)
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Greedily divide weighted items equally across bins. This approximately solves a multi-way partition problem, minimising the difference between the largest and smallest sum of weights in a bin. Parameters ---------- items : ~typing.Iterable[~typing.Tuple[~typing.Any, float]] Weighted items as ``(item, weight)`` tuples. bin_count : int Number of bins. Returns ------- bins : ~collections_extended.frozenbag[~collections_extended.frozenbag[~typing.Any]] Item bins as a bag of item bags. Notes ---------- - `A greedy solution <http://stackoverflow.com/a/6855546/1031434>`_ - `Problem definition and solutions <http://ijcai.org/Proceedings/09/Papers/096.pdf>`_
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python
train
fabioz/PyDev.Debugger
pydevd_attach_to_process/winappdbg/thread.py
https://github.com/fabioz/PyDev.Debugger/blob/ed9c4307662a5593b8a7f1f3389ecd0e79b8c503/pydevd_attach_to_process/winappdbg/thread.py#L1172-L1232
def __get_stack_trace_manually(self, depth = 16, bUseLabels = True, bMakePretty = True): """ Tries to get a stack trace for the current function. Only works for functions with standard prologue and epilogue. @type depth: int @param depth: Maximum depth of stack trace. @type bUseLabels: bool @param bUseLabels: C{True} to use labels, C{False} to use addresses. @type bMakePretty: bool @param bMakePretty: C{True} for user readable labels, C{False} for labels that can be passed to L{Process.resolve_label}. "Pretty" labels look better when producing output for the user to read, while pure labels are more useful programatically. @rtype: tuple of tuple( int, int, str ) @return: Stack trace of the thread as a tuple of ( return address, frame pointer address, module filename ) when C{bUseLabels} is C{True}, or a tuple of ( return address, frame pointer label ) when C{bUseLabels} is C{False}. @raise WindowsError: Raises an exception on error. """ aProcess = self.get_process() st, sb = self.get_stack_range() # top, bottom fp = self.get_fp() trace = list() if aProcess.get_module_count() == 0: aProcess.scan_modules() bits = aProcess.get_bits() while depth > 0: if fp == 0: break if not st <= fp < sb: break ra = aProcess.peek_pointer(fp + 4) if ra == 0: break lib = aProcess.get_module_at_address(ra) if lib is None: lib = "" else: if lib.fileName: lib = lib.fileName else: lib = "%s" % HexDump.address(lib.lpBaseOfDll, bits) if bUseLabels: label = aProcess.get_label_at_address(ra) if bMakePretty: label = '%s (%s)' % (HexDump.address(ra, bits), label) trace.append( (fp, label) ) else: trace.append( (fp, ra, lib) ) fp = aProcess.peek_pointer(fp) return tuple(trace)
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Tries to get a stack trace for the current function. Only works for functions with standard prologue and epilogue. @type depth: int @param depth: Maximum depth of stack trace. @type bUseLabels: bool @param bUseLabels: C{True} to use labels, C{False} to use addresses. @type bMakePretty: bool @param bMakePretty: C{True} for user readable labels, C{False} for labels that can be passed to L{Process.resolve_label}. "Pretty" labels look better when producing output for the user to read, while pure labels are more useful programatically. @rtype: tuple of tuple( int, int, str ) @return: Stack trace of the thread as a tuple of ( return address, frame pointer address, module filename ) when C{bUseLabels} is C{True}, or a tuple of ( return address, frame pointer label ) when C{bUseLabels} is C{False}. @raise WindowsError: Raises an exception on error.
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python
train
sebdah/dynamic-dynamodb
dynamic_dynamodb/core/circuit_breaker.py
https://github.com/sebdah/dynamic-dynamodb/blob/bfd0ca806b1c3301e724696de90ef0f973410493/dynamic_dynamodb/core/circuit_breaker.py#L13-L97
def is_open(table_name=None, table_key=None, gsi_name=None, gsi_key=None): """ Checks whether the circuit breaker is open :param table_name: Name of the table being checked :param table_key: Configuration key for table :param gsi_name: Name of the GSI being checked :param gsi_key: Configuration key for the GSI :returns: bool -- True if the circuit is open """ logger.debug('Checking circuit breaker status') # Parse the URL to make sure it is OK pattern = re.compile( r'^(?P<scheme>http(s)?://)' r'((?P<username>.+):(?P<password>.+)@){0,1}' r'(?P<url>.*)$' ) url = timeout = None if gsi_name: url = get_gsi_option(table_key, gsi_key, 'circuit_breaker_url') timeout = get_gsi_option(table_key, gsi_key, 'circuit_breaker_timeout') elif table_name: url = get_table_option(table_key, 'circuit_breaker_url') timeout = get_table_option(table_key, 'circuit_breaker_timeout') if not url: url = get_global_option('circuit_breaker_url') timeout = get_global_option('circuit_breaker_timeout') match = pattern.match(url) if not match: logger.error('Malformatted URL: {0}'.format(url)) sys.exit(1) use_basic_auth = False if match.group('username') and match.group('password'): use_basic_auth = True # Make the actual URL to call auth = () if use_basic_auth: url = '{scheme}{url}'.format( scheme=match.group('scheme'), url=match.group('url')) auth = (match.group('username'), match.group('password')) headers = {} if table_name: headers["x-table-name"] = table_name if gsi_name: headers["x-gsi-name"] = gsi_name # Make the actual request try: response = requests.get( url, auth=auth, timeout=timeout / 1000.00, headers=headers) if int(response.status_code) >= 200 and int(response.status_code) < 300: logger.info('Circuit breaker is closed') return False else: logger.warning( 'Circuit breaker returned with status code {0:d}'.format( response.status_code)) except requests.exceptions.SSLError as error: logger.warning('Circuit breaker: {0}'.format(error)) except requests.exceptions.Timeout as error: logger.warning('Circuit breaker: {0}'.format(error)) except requests.exceptions.ConnectionError as error: logger.warning('Circuit breaker: {0}'.format(error)) except requests.exceptions.HTTPError as error: logger.warning('Circuit breaker: {0}'.format(error)) except requests.exceptions.TooManyRedirects as error: logger.warning('Circuit breaker: {0}'.format(error)) except Exception as error: logger.error('Unhandled exception: {0}'.format(error)) logger.error( 'Please file a bug at ' 'https://github.com/sebdah/dynamic-dynamodb/issues') return True
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Checks whether the circuit breaker is open :param table_name: Name of the table being checked :param table_key: Configuration key for table :param gsi_name: Name of the GSI being checked :param gsi_key: Configuration key for the GSI :returns: bool -- True if the circuit is open
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python
train
tanghaibao/jcvi
jcvi/formats/gff.py
https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/formats/gff.py#L663-L697
def sizes(args): """ %prog sizes gffile Given a gff file of features, calculate the sizes of chosen parent feature based on summation of sizes of child features. For example, for parent 'mRNA' and child 'CDS' feature types, calcuate sizes of mRNA by summing the sizes of the disjoint CDS parts. """ p = OptionParser(sizes.__doc__) p.set_outfile() p.add_option("--parents", dest="parents", default="mRNA", help="parent feature(s) for which size is to be calculated") p.add_option("--child", dest="child", default="CDS", help="child feature to use for size calculations") opts, args = p.parse_args(args) if len(args) != 1: sys.exit(not p.print_help()) gffile, = args parents, cftype = set(opts.parents.split(",")), opts.child gff = make_index(gffile) fw = must_open(opts.outfile, "w") for parent in parents: for feat in gff.features_of_type(parent, order_by=('seqid', 'start')): fsize = 0 fsize = feat.end - feat.start + 1 \ if cftype == parent else \ gff.children_bp(feat, child_featuretype=cftype) print("\t".join(str(x) for x in (feat.id, fsize)), file=fw) fw.close()
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%prog sizes gffile Given a gff file of features, calculate the sizes of chosen parent feature based on summation of sizes of child features. For example, for parent 'mRNA' and child 'CDS' feature types, calcuate sizes of mRNA by summing the sizes of the disjoint CDS parts.
[ "%prog", "sizes", "gffile" ]
python
train
noahbenson/pimms
pimms/util.py
https://github.com/noahbenson/pimms/blob/9051b86d6b858a7a13511b72c48dc21bc903dab2/pimms/util.py#L775-L793
def flatten_maps(*args, **kwargs): ''' flatten_maps(*args, **kwags) yields a tuple of the maps in the given arguments; this flattens over lists and iterables so long as all elements eventually yield True to is_map(el). The optional keyword arguments passed make up the final map. This funtion does not evaluate any values of any of the maps and thus implicitly respects the laziness of the provided maps. ''' def _recur(arg, work): if is_map(arg): work.append(arg) elif is_str(arg) or not hasattr(arg, '__iter__'): raise ValueError('Non-map given to flatten_maps') else: for a in arg: _recur(a, work) res = [] for arg in args: _recur(arg, res) if len(kwargs) > 0: res.append(kwargs) return tuple(res)
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flatten_maps(*args, **kwags) yields a tuple of the maps in the given arguments; this flattens over lists and iterables so long as all elements eventually yield True to is_map(el). The optional keyword arguments passed make up the final map. This funtion does not evaluate any values of any of the maps and thus implicitly respects the laziness of the provided maps.
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python
train
jreese/dotlink
dotlink/dotlink.py
https://github.com/jreese/dotlink/blob/5e48c1493c20fc6df4ad0144e80563915ce339b6/dotlink/dotlink.py#L366-L400
def deploy_local(self, dotfiles, target_root=None): """Deploy dotfiles to a local path.""" if target_root is None: target_root = self.args.path for source_path, target_path in dotfiles.items(): source_path = path.join(self.source, source_path) target_path = path.join(target_root, target_path) if path.isfile(target_path) or path.islink(target_path): self.log.debug('Removing existing file at %s', target_path) os.unlink(target_path) elif path.isdir(target_path): self.log.debug('Removing existing dir at %s', target_path) shutil.rmtree(target_path) parent_dir = path.dirname(target_path) if not path.isdir(parent_dir): self.log.debug('Creating parent dir %s', parent_dir) os.makedirs(parent_dir) if self.args.copy: if path.isdir(source_path): self.log.debug('Copying file %s to %s', source_path, target_path) shutil.copytree(source_path, target_path) else: self.log.debug('Copying dir %s to %s', source_path, target_path) shutil.copy(source_path, target_path) else: self.log.debug('Symlinking %s -> %s', target_path, source_path) os.symlink(source_path, target_path)
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Deploy dotfiles to a local path.
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python
train
eddiejessup/metropack
metropack/draw.py
https://github.com/eddiejessup/metropack/blob/528b47d0f2f70f39e1490e41433f2da8c8b9d63c/metropack/draw.py#L6-L37
def _unwrap_one_layer(r, L, n): """For a set of points in a 2 dimensional periodic system, extend the set of points to tile the points at a given period. Parameters ---------- r: float array, shape (:, 2). Set of points. L: float array, shape (2,) System lengths. n: integer. Period to unwrap. Returns ------- rcu: float array, shape (:, 2). The set of points. tiled at the periods at a distance `n` from the origin. """ try: L[0] except (TypeError, IndexError): L = np.ones([r.shape[1]]) * L if n == 0: return list(r) rcu = [] for x, y in r: for ix in range(-n, n + 1): for iy in range(-n, n + 1): if abs(ix) == n or abs(iy) == n: rcu.append(np.array([x + ix * L[0], y + iy * L[1]])) return rcu
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For a set of points in a 2 dimensional periodic system, extend the set of points to tile the points at a given period. Parameters ---------- r: float array, shape (:, 2). Set of points. L: float array, shape (2,) System lengths. n: integer. Period to unwrap. Returns ------- rcu: float array, shape (:, 2). The set of points. tiled at the periods at a distance `n` from the origin.
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python
train
KelSolaar/Umbra
umbra/components/addons/projects_explorer/projects_explorer.py
https://github.com/KelSolaar/Umbra/blob/66f45f08d9d723787f1191989f8b0dda84b412ce/umbra/components/addons/projects_explorer/projects_explorer.py#L1111-L1140
def add_new_directory(self, node): """ Adds a new directory next to given Node associated path. :param node: Node. :type node: ProjectNode or DirectoryNode or FileNode :return: Method success. :rtype: bool """ if self.__script_editor.model.is_authoring_node(node): return False directory, state = QInputDialog.getText(self, "Add Directory", "Enter your new directory name:") if not state: return False if node.family in ("Project", "Directory"): parent_directory = node.path elif node.family == "File": parent_directory = os.path.dirname(node.path) directory = foundations.strings.to_string(directory) if not directory in os.listdir(parent_directory): directory = os.path.join(parent_directory, directory) LOGGER.info("{0} | Adding '{1}' directory!".format(self.__class__.__name__, directory)) os.makedirs(directory) else: self.__raise_file_system_exception(file, parent_directory) return True
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python
train
aiidateam/aiida-codtools
aiida_codtools/workflows/cif_clean.py
https://github.com/aiidateam/aiida-codtools/blob/da5e4259b7a2e86cf0cc3f997e11dd36d445fa94/aiida_codtools/workflows/cif_clean.py#L112-L126
def run_select_calculation(self): """Run the CifSelectCalculation on the CifData output node of the CifFilterCalculation.""" inputs = { 'cif': self.ctx.cif, 'code': self.inputs.cif_select, 'parameters': self.inputs.cif_select_parameters, 'metadata': { 'options': self.inputs.options.get_dict(), } } calculation = self.submit(CifSelectCalculation, **inputs) self.report('submitted {}<{}>'.format(CifSelectCalculation.__name__, calculation.uuid)) return ToContext(cif_select=calculation)
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Run the CifSelectCalculation on the CifData output node of the CifFilterCalculation.
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python
train
saltstack/salt
salt/modules/win_lgpo.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/win_lgpo.py#L5637-L5695
def _checkListItem(policy_element, policy_name, policy_key, xpath_object, policy_file_data, test_items=True): ''' helper function to process an enabled/disabled/true/falseList set if test_items is True, it will determine if the policy is enabled or disabled returning True if all items are configured in the registry.pol file and false if they are not if test_items is False, the expected strings for the items will be returned as a list returns True if the enabled/disabledList is 100% configured in the registry.pol file, otherwise returns False ''' xpath_string = ('.//*[local-name() = "decimal" or local-name() = "delete"' ' or local-name() = "longDecimal" or local-name() = "string"]') value_item_child_xpath = etree.XPath(xpath_string) expected_strings = [] for list_element in xpath_object(policy_element): configured_items = 0 required_items = 0 for item in list_element.getchildren(): required_items = required_items + 1 if 'key' in item.attrib: item_key = item.attrib['key'] else: item_key = policy_key if 'valueName' in item.attrib: item_valuename = item.attrib['valueName'] else: log.error('%s item with attributes %s in policy %s does not ' 'have the required "valueName" attribute', etree.QName(list_element).localname, item.attrib, policy_element.attrib) break for value_item in value_item_child_xpath(item): search_string = _processValueItem(value_item, item_key, item_valuename, policy_element, item) if test_items: if _regexSearchRegPolData(re.escape(search_string), policy_file_data): configured_items = configured_items + 1 log.debug('found the search string in the pol file,' '%s of %s items for policy %s are ' 'configured in registry.pol', configured_items, required_items, policy_name) else: expected_strings.append(search_string) if test_items: if required_items > 0 and required_items == configured_items: log.debug('%s all items are set', policy_name) return True if test_items: return False else: return expected_strings
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helper function to process an enabled/disabled/true/falseList set if test_items is True, it will determine if the policy is enabled or disabled returning True if all items are configured in the registry.pol file and false if they are not if test_items is False, the expected strings for the items will be returned as a list returns True if the enabled/disabledList is 100% configured in the registry.pol file, otherwise returns False
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python
train
pandemicsyn/statsdpy
statsdpy/statsd.py
https://github.com/pandemicsyn/statsdpy/blob/9cfccf89121fd6a12df20f17fa3eb8f618a36455/statsdpy/statsd.py#L124-L144
def stats_flush(self): """ Periodically flush stats to graphite """ while True: try: eventlet.sleep(self.flush_interval) if self.debug: print "seen %d stats so far." % self.stats_seen print "current counters: %s" % self.counters if self.pickle_proto: payload = self.pickle_payload() if payload: for batch in payload: self.report_stats(batch) else: payload = self.plain_payload() if payload: self.report_stats(payload) except: # safety net self.logger.critical('Encountered error in stats_flush loop')
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Periodically flush stats to graphite
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python
train
PinLin/KCOJ_api
KCOJ_api/api.py
https://github.com/PinLin/KCOJ_api/blob/64f6ef0f9e64dc1efd692cbe6d5738ee7cfb78ec/KCOJ_api/api.py#L66-L107
def get_question(self, number: str=None) -> dict: """ 取得課程中的所有題目資訊 """ try: # 取得資料 response = self.__session.get( self.__url + '/HomeworkBoard', timeout=0.5, verify=False) soup = BeautifulSoup(response.text, 'html.parser') # 整理題目資訊 questions = {} for tag in soup.find_all('tr'): # 去除標題列 if tag.find('a') == None: continue # 儲存題目資訊 questions[tag.find('a').get_text().strip()] = { # 繳交期限 'deadline': tag.find_all('td')[3].get_text().strip(), # 是否已經過期限 'expired': tag.find_all('td')[4].get_text().strip() == '期限已過', # 是否繳交 'status': tag.find_all('td')[6].get_text().strip() == '已繳', # 程式語言種類 'language': tag.find_all('td')[5].get_text().strip(), } # 回傳結果 if number != None: return questions.get(number) else: return questions except requests.exceptions.Timeout: return { "Timeout": { 'deadline': "Timeout", 'expired': False, 'status': False, 'language': "Timeout", } }
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取得課程中的所有題目資訊
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python
train
exosite-labs/pyonep
pyonep/portals/endpoints.py
https://github.com/exosite-labs/pyonep/blob/d27b621b00688a542e0adcc01f3e3354c05238a1/pyonep/portals/endpoints.py#L212-L242
def add_device(self, model, serial): """ Returns 'device object' of newly created device. http://docs.exosite.com/portals/#create-device http://docs.exosite.com/portals/#device-object """ device = { 'model': model, 'vendor': self.vendor(), 'sn': serial, 'type': 'vendor' } headers = { 'User-Agent': self.user_agent(), } headers.update(self.headers()) r = requests.post( self.portals_url()+'/portals/'+self.portal_id()+'/devices', data=json.dumps(device), headers=headers, auth=self.auth()) if HTTP_STATUS.ADDED == r.status_code: # fix the 'meta' to be dictionary instead of string device_obj = r.json() return dictify_device_meta(device_obj) else: print("add_device: Something went wrong: <{0}>: {1}".format( r.status_code, r.reason)) r.raise_for_status()
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Returns 'device object' of newly created device. http://docs.exosite.com/portals/#create-device http://docs.exosite.com/portals/#device-object
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python
train
dcramer/peek
peek/tracer.py
https://github.com/dcramer/peek/blob/da7c086660fc870c6632c4dc5ccb2ff9bfbee52e/peek/tracer.py#L237-L248
def start(self, origin): """ Start this Tracer. Return a Python function suitable for use with sys.settrace(). """ self.start_time = time.time() self.pause_until = None self.data.update(self._get_struct(origin, 'origin')) self.data_stack.append(self.data) sys.settrace(self._trace) return self._trace
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Start this Tracer. Return a Python function suitable for use with sys.settrace().
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python
train
frascoweb/frasco
frasco/expression.py
https://github.com/frascoweb/frasco/blob/ea519d69dd5ca6deaf3650175692ee4a1a02518f/frasco/expression.py#L348-L368
def eval_expr(expr, context): """Recursively evaluates a compiled expression using the specified context. Dict instances can contain a "__kwargs" key which will be used to update the dict with its content """ if isinstance(expr, list): rv = [] for item in expr: rv.append(eval_expr(item, context)) return rv if isinstance(expr, dict): rv = {} for k, v in expr.iteritems(): rv[k] = eval_expr(v, context) kwargs = rv.pop("__kwargs", None) if kwargs: rv.update(kwargs) return rv if isinstance(expr, Expression): return expr.eval(context) return expr
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Recursively evaluates a compiled expression using the specified context. Dict instances can contain a "__kwargs" key which will be used to update the dict with its content
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python
train
kmike/django-generic-images
generic_images/admin.py
https://github.com/kmike/django-generic-images/blob/4e45068ed219ac35396758eb6b6e1fe5306147df/generic_images/admin.py#L10-L29
def attachedimage_form_factory(lang='en', debug=False): ''' Returns ModelForm class to be used in admin. 'lang' is the language for GearsUploader (can be 'en' and 'ru' at the moment). ''' yui = '' if debug else '.yui' class _AttachedImageAdminForm(forms.ModelForm): caption = forms.CharField(label=_('Caption'), required=False) class Media: js = [ 'generic_images/js/mootools-1.2.4-core-yc.js', 'generic_images/js/GearsUploader.%s%s.js' % (lang, yui,), 'generic_images/js/AttachedImageInline.js', ] class Meta: model = AttachedImage return _AttachedImageAdminForm
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Returns ModelForm class to be used in admin. 'lang' is the language for GearsUploader (can be 'en' and 'ru' at the moment).
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python
train
apache/incubator-mxnet
python/mxnet/image/image.py
https://github.com/apache/incubator-mxnet/blob/1af29e9c060a4c7d60eeaacba32afdb9a7775ba7/python/mxnet/image/image.py#L1409-L1428
def imdecode(self, s): """Decodes a string or byte string to an NDArray. See mx.img.imdecode for more details.""" def locate(): """Locate the image file/index if decode fails.""" if self.seq is not None: idx = self.seq[(self.cur % self.num_image) - 1] else: idx = (self.cur % self.num_image) - 1 if self.imglist is not None: _, fname = self.imglist[idx] msg = "filename: {}".format(fname) else: msg = "index: {}".format(idx) return "Broken image " + msg try: img = imdecode(s) except Exception as e: raise RuntimeError("{}, {}".format(locate(), e)) return img
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python
train
vberlier/nbtlib
nbtlib/literal/serializer.py
https://github.com/vberlier/nbtlib/blob/9c9d58b5c4a530b0f1ffd76dda176f00406c3547/nbtlib/literal/serializer.py#L142-L150
def serialize_list(self, tag): """Return the literal representation of a list tag.""" separator, fmt = self.comma, '[{}]' with self.depth(): if self.should_expand(tag): separator, fmt = self.expand(separator, fmt) return fmt.format(separator.join(map(self.serialize, tag)))
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Return the literal representation of a list tag.
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python
train
amzn/ion-python
amazon/ion/reader_text.py
https://github.com/amzn/ion-python/blob/0b21fa3ba7755f55f745e4aa970d86343b82449d/amazon/ion/reader_text.py#L2152-L2176
def _skip_trampoline(handler): """Intercepts events from container handlers, emitting them only if they should not be skipped.""" data_event, self = (yield None) delegate = handler event = None depth = 0 while True: def pass_through(): _trans = delegate.send(Transition(data_event, delegate)) return _trans, _trans.delegate, _trans.event if data_event is not None and data_event.type is ReadEventType.SKIP: while True: trans, delegate, event = pass_through() if event is not None: if event.event_type is IonEventType.CONTAINER_END and event.depth <= depth: break if event is None or event.event_type is IonEventType.INCOMPLETE: data_event, _ = yield Transition(event, self) else: trans, delegate, event = pass_through() if event is not None and (event.event_type is IonEventType.CONTAINER_START or event.event_type is IonEventType.CONTAINER_END): depth = event.depth data_event, _ = yield Transition(event, self)
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python
train
jason-weirather/pythologist
pythologist/__init__.py
https://github.com/jason-weirather/pythologist/blob/6eb4082be9dffa9570e4ceaa06d97845eac4c006/pythologist/__init__.py#L223-L237
def is_uniform(self,verbose=True): """ Check to make sure phenotype calls, or scored calls are consistent across all images / samples """ uni = pd.Series(self['phenotype_calls'].apply(lambda x: json.dumps(x)).unique()).\ apply(lambda x: json.loads(x)).apply(lambda x: tuple(sorted(x.keys()))).unique() if len(uni) > 1: if verbose: sys.stderr.write("WARNING: phenotypes differ across the dataframe \n"+str(uni)+"\n") return False uni = pd.Series(self['scored_calls'].apply(lambda x: json.dumps(x)).unique()).\ apply(lambda x: json.loads(x)).apply(lambda x: tuple(sorted(x.keys()))).unique() if len(uni) > 1: if verbose: sys.stderr.write("WARNING: scored_calls differ across the dataframe \n"+str(uni)+"\n") return False return True
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Check to make sure phenotype calls, or scored calls are consistent across all images / samples
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python
train
secdev/scapy
scapy/contrib/isotp.py
https://github.com/secdev/scapy/blob/3ffe757c184017dd46464593a8f80f85abc1e79a/scapy/contrib/isotp.py#L347-L370
def pop(self, identifier=None, ext_addr=None, basecls=ISOTP): """ Returns a built ISOTP message :param identifier: if not None, only return isotp messages with this destination :param ext_addr: if identifier is not None, only return isotp messages with this extended address for destination :param basecls: the class of packets that will be returned, defautls to ISOTP :return: an ISOTP packet, or None if no message is ready """ if identifier is not None: for i in range(len(self.ready)): b = self.ready[i] identifier = b[0] ea = b[1] if identifier == identifier and ext_addr == ea: return ISOTPMessageBuilder._build(self.ready.pop(i)) return None if len(self.ready) > 0: return ISOTPMessageBuilder._build(self.ready.pop(0)) return None
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python
train
tango-controls/pytango
tango/utils.py
https://github.com/tango-controls/pytango/blob/9cf78c517c9cdc1081ff6d080a9646a740cc1d36/tango/utils.py#L1264-L1271
def insert(self, i, x): """s.insert(i, x) same as s[i:i] = [x] Raises TypeError if x isn't a string.""" if not isinstance(x, str): raise TypeError( 'Members of this object must be strings. ' 'You supplied \"%s\"' % type(x)) list.insert(self, i, x)
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python
train
tamasgal/km3pipe
km3pipe/utils/streamds.py
https://github.com/tamasgal/km3pipe/blob/7a9b59ac899a28775b5bdc5d391d9a5340d08040/km3pipe/utils/streamds.py#L165-L203
def convert_runsummary_to_json( df, comment='Uploaded via km3pipe.StreamDS', prefix='TEST_' ): """Convert a Pandas DataFrame with runsummary to JSON for DB upload""" data_field = [] comment += ", by {}".format(getpass.getuser()) for det_id, det_data in df.groupby('det_id'): runs_field = [] data_field.append({"DetectorId": det_id, "Runs": runs_field}) for run, run_data in det_data.groupby('run'): parameters_field = [] runs_field.append({ "Run": int(run), "Parameters": parameters_field }) parameter_dict = {} for row in run_data.itertuples(): for parameter_name in run_data.columns: if parameter_name in REQUIRED_COLUMNS: continue if parameter_name not in parameter_dict: entry = {'Name': prefix + parameter_name, 'Data': []} parameter_dict[parameter_name] = entry data_value = getattr(row, parameter_name) try: data_value = float(data_value) except ValueError as e: log.critical("Data values has to be floats!") raise ValueError(e) value = {'S': str(getattr(row, 'source')), 'D': data_value} parameter_dict[parameter_name]['Data'].append(value) for parameter_data in parameter_dict.values(): parameters_field.append(parameter_data) data_to_upload = {"Comment": comment, "Data": data_field} file_data_to_upload = json.dumps(data_to_upload) return file_data_to_upload
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Convert a Pandas DataFrame with runsummary to JSON for DB upload
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python
train
apple/turicreate
src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py
https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/coremltools/models/neural_network/builder.py#L2612-L2657
def add_resize_bilinear(self, name, input_name, output_name, target_height=1, target_width=1, mode='ALIGN_ENDPOINTS_MODE'): """ Add resize bilinear layer to the model. A layer that resizes the input to a given spatial size using bilinear interpolation. Parameters ---------- name: str The name of this layer. input_name: str The input blob name of this layer. output_name: str The output blob name of this layer. target_height: int Output height dimension. target_width: int Output width dimension. mode: str Following values are supported: 'STRICT_ALIGN_ENDPOINTS_MODE', 'ALIGN_ENDPOINTS_MODE', 'UPSAMPLE_MODE', 'ROI_ALIGN_MODE'. This parameter determines the sampling grid used for bilinear interpolation. Kindly refer to NeuralNetwork.proto for details. See Also -------- add_upsample """ spec = self.spec nn_spec = self.nn_spec # Add a new inner-product layer spec_layer = nn_spec.layers.add() spec_layer.name = name spec_layer.input.append(input_name) spec_layer.output.append(output_name) spec_layer_params = spec_layer.resizeBilinear spec_layer_params.targetSize.append(target_height) spec_layer_params.targetSize.append(target_width) if mode == 'ALIGN_ENDPOINTS_MODE': spec_layer_params.mode.samplingMethod = _NeuralNetwork_pb2.SamplingMode.Method.Value('ALIGN_ENDPOINTS_MODE') elif mode == 'STRICT_ALIGN_ENDPOINTS_MODE': spec_layer_params.mode.samplingMethod = _NeuralNetwork_pb2.SamplingMode.Method.Value('STRICT_ALIGN_ENDPOINTS_MODE') elif mode == 'UPSAMPLE_MODE': spec_layer_params.mode.samplingMethod = _NeuralNetwork_pb2.SamplingMode.Method.Value('UPSAMPLE_MODE') elif mode == 'ROI_ALIGN_MODE': spec_layer_params.mode.samplingMethod = _NeuralNetwork_pb2.SamplingMode.Method.Value('ROI_ALIGN_MODE') else: raise ValueError("Unspported resize bilinear mode %s" % mode)
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Add resize bilinear layer to the model. A layer that resizes the input to a given spatial size using bilinear interpolation. Parameters ---------- name: str The name of this layer. input_name: str The input blob name of this layer. output_name: str The output blob name of this layer. target_height: int Output height dimension. target_width: int Output width dimension. mode: str Following values are supported: 'STRICT_ALIGN_ENDPOINTS_MODE', 'ALIGN_ENDPOINTS_MODE', 'UPSAMPLE_MODE', 'ROI_ALIGN_MODE'. This parameter determines the sampling grid used for bilinear interpolation. Kindly refer to NeuralNetwork.proto for details. See Also -------- add_upsample
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python
train
sio2project/filetracker
filetracker/client/data_store.py
https://github.com/sio2project/filetracker/blob/359b474850622e3d0c25ee2596d7242c02f84efb/filetracker/client/data_store.py#L80-L98
def get_file(self, name, filename): """Saves the content of file named ``name`` to ``filename``. Works like :meth:`get_stream`, but ``filename`` is the name of a file which will be created (or overwritten). Returns the full versioned name of the retrieved file. """ stream, vname = self.get_stream(name) path, version = split_name(vname) dir_path = os.path.dirname(filename) if dir_path: mkdir(dir_path) with open(filename, 'wb') as f: shutil.copyfileobj(stream, f) return vname
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Saves the content of file named ``name`` to ``filename``. Works like :meth:`get_stream`, but ``filename`` is the name of a file which will be created (or overwritten). Returns the full versioned name of the retrieved file.
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python
train
google/grr
grr/core/grr_response_core/lib/parsers/linux_file_parser.py
https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/core/grr_response_core/lib/parsers/linux_file_parser.py#L679-L711
def ParseFileset(self, fileset=None): """Process linux system login files. Orchestrates collection of account entries from /etc/passwd and /etc/shadow. The passwd and shadow entries are reconciled and group memberships are mapped to the account. Args: fileset: A dict of files mapped from path to an open file. Yields: - A series of User entries, each of which is populated with group memberships and indications of the shadow state of the account. - A series of anomalies in cases where there are mismatches between passwd and shadow state. """ self.AddPassword(fileset) self.AddShadow(fileset) self.ReconcileShadow(self.shadow_store) # Get group memberships using the files that were already collected. # Separate out groups and anomalies. for rdf in LinuxSystemGroupParser().ParseFileset(fileset): if isinstance(rdf, rdf_client.Group): self.groups[rdf.name] = rdf else: yield rdf self.AddGroupMemberships() for user in itervalues(self.entry): yield user for grp in itervalues(self.groups): yield grp for anom in self.FindAnomalies(): yield anom
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Process linux system login files. Orchestrates collection of account entries from /etc/passwd and /etc/shadow. The passwd and shadow entries are reconciled and group memberships are mapped to the account. Args: fileset: A dict of files mapped from path to an open file. Yields: - A series of User entries, each of which is populated with group memberships and indications of the shadow state of the account. - A series of anomalies in cases where there are mismatches between passwd and shadow state.
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python
train
Autodesk/aomi
aomi/model/context.py
https://github.com/Autodesk/aomi/blob/84da2dfb0424837adf9c4ddc1aa352e942bb7a4a/aomi/model/context.py#L155-L159
def thaw(self, tmp_dir): """Will thaw every secret into an appropriate temporary location""" for resource in self.resources(): if resource.present: resource.thaw(tmp_dir)
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Will thaw every secret into an appropriate temporary location
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python
train
bwohlberg/sporco
sporco/linalg.py
https://github.com/bwohlberg/sporco/blob/8946a04331106f4e39904fbdf2dc7351900baa04/sporco/linalg.py#L1379-L1413
def rfl2norm2(xf, xs, axis=(0, 1)): r""" Compute the squared :math:`\ell_2` norm in the DFT domain, taking into account the unnormalised DFT scaling, i.e. given the DFT of a multi-dimensional array computed via :func:`rfftn`, return the squared :math:`\ell_2` norm of the original array. Parameters ---------- xf : array_like Input array xs : sequence of ints Shape of original array to which :func:`rfftn` was applied to obtain the input array axis : sequence of ints, optional (default (0,1)) Axes on which the input is in the frequency domain Returns ------- x : float :math:`\|\mathbf{x}\|_2^2` where the input array is the result of applying :func:`rfftn` to the specified axes of multi-dimensional array :math:`\mathbf{x}` """ scl = 1.0 / np.prod(np.array([xs[k] for k in axis])) slc0 = (slice(None),) * axis[-1] nrm0 = np.linalg.norm(xf[slc0 + (0,)]) idx1 = (xs[axis[-1]] + 1) // 2 nrm1 = np.linalg.norm(xf[slc0 + (slice(1, idx1),)]) if xs[axis[-1]] % 2 == 0: nrm2 = np.linalg.norm(xf[slc0 + (slice(-1, None),)]) else: nrm2 = 0.0 return scl*(nrm0**2 + 2.0*nrm1**2 + nrm2**2)
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r""" Compute the squared :math:`\ell_2` norm in the DFT domain, taking into account the unnormalised DFT scaling, i.e. given the DFT of a multi-dimensional array computed via :func:`rfftn`, return the squared :math:`\ell_2` norm of the original array. Parameters ---------- xf : array_like Input array xs : sequence of ints Shape of original array to which :func:`rfftn` was applied to obtain the input array axis : sequence of ints, optional (default (0,1)) Axes on which the input is in the frequency domain Returns ------- x : float :math:`\|\mathbf{x}\|_2^2` where the input array is the result of applying :func:`rfftn` to the specified axes of multi-dimensional array :math:`\mathbf{x}`
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python
train
iotile/coretools
transport_plugins/bled112/iotile_transport_bled112/bled112_cmd.py
https://github.com/iotile/coretools/blob/2d794f5f1346b841b0dcd16c9d284e9bf2f3c6ec/transport_plugins/bled112/iotile_transport_bled112/bled112_cmd.py#L163-L215
def _probe_services(self, handle): """Probe for all primary services and characteristics in those services Args: handle (int): the connection handle to probe """ code = 0x2800 def event_filter_func(event): if (event.command_class == 4 and event.command == 2): event_handle, = unpack("B", event.payload[0:1]) return event_handle == handle return False def end_filter_func(event): if (event.command_class == 4 and event.command == 1): event_handle, = unpack("B", event.payload[0:1]) return event_handle == handle return False payload = struct.pack('<BHHBH', handle, 1, 0xFFFF, 2, code) try: response = self._send_command(4, 1, payload) except InternalTimeoutError: return False, {'reason': 'Timeout waiting for command response'} handle, result = unpack("<BH", response.payload) if result != 0: return False, None events = self._wait_process_events(0.5, event_filter_func, end_filter_func) gatt_events = [x for x in events if event_filter_func(x)] end_events = [x for x in events if end_filter_func(x)] if len(end_events) == 0: return False, None #Make sure we successfully probed the gatt table end_event = end_events[0] _, result, _ = unpack("<BHH", end_event.payload) if result != 0: self._logger.warn("Error enumerating GATT table, protocol error code = %d (0x%X)" % (result, result)) return False, None services = {} for event in gatt_events: process_gatt_service(services, event) return True, {'services': services}
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Probe for all primary services and characteristics in those services Args: handle (int): the connection handle to probe
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python
train
datadesk/django-bakery
bakery/management/commands/publish.py
https://github.com/datadesk/django-bakery/blob/e2feb13a66552a388fbcfaaacdd504bba08d3c69/bakery/management/commands/publish.py#L313-L319
def get_md5(self, filename): """ Returns the md5 checksum of the provided file name. """ with open(filename, 'rb') as f: m = hashlib.md5(f.read()) return m.hexdigest()
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Returns the md5 checksum of the provided file name.
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python
train
markovmodel/PyEMMA
pyemma/coordinates/pipelines.py
https://github.com/markovmodel/PyEMMA/blob/5c3124398217de05ba5ce9c8fb01519222481ab8/pyemma/coordinates/pipelines.py#L74-L90
def add_element(self, e): r""" Appends a pipeline stage. Appends the given element to the end of the current chain. """ if not isinstance(e, Iterable): raise TypeError("given element {} is not iterable in terms of " "PyEMMAs coordinate pipeline.".format(e)) # only if we have more than one element if not e.is_reader and len(self._chain) >= 1: data_producer = self._chain[-1] # avoid calling the setter of StreamingTransformer.data_producer, since this # triggers a re-parametrization even on readers (where it makes not sense) e._data_producer = data_producer e.chunksize = self.chunksize self._chain.append(e)
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r""" Appends a pipeline stage. Appends the given element to the end of the current chain.
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python
train
vsoch/helpme
helpme/action/submit.py
https://github.com/vsoch/helpme/blob/e609172260b10cddadb2d2023ab26da8082a9feb/helpme/action/submit.py#L24-L64
def upload_asciinema(filename): '''a wrapper around generation of an asciinema.api.Api to call the upload command given an already existing asciinema file. Parameters ========== filename: the asciinema file to upload, can be generated with function record_asciinema in record.py ''' if os.path.exists(filename): import asciinema.config as aconfig from asciinema.api import Api # Load the API class cfg = aconfig.load() api = Api(cfg.api_url, os.environ.get("USER"), cfg.install_id) # Perform the upload, return the url uploader = UploadCommand(api, filename) try: url, warn = uploader.api.upload_asciicast(filename) if warn: uploader.print_warning(warn) # Extract just the url, if provided (always is https) if url: match = re.search('https://.+', url) if match: url = match.group() return url except: bot.error('Problem with upload, skipping') else: bot.warning('Cannot find %s, skipping submission.' %filename)
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a wrapper around generation of an asciinema.api.Api to call the upload command given an already existing asciinema file. Parameters ========== filename: the asciinema file to upload, can be generated with function record_asciinema in record.py
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python
train
barrust/pyspellchecker
spellchecker/spellchecker.py
https://github.com/barrust/pyspellchecker/blob/fa96024c0cdeba99e10e11060d5fd7aba796b271/spellchecker/spellchecker.py#L398-L404
def load_words(self, words): """ Load a list of words from which to generate a word frequency list Args: words (list): The list of words to be loaded """ self._dictionary.update([word.lower() for word in words]) self._update_dictionary()
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python
train
suds-community/suds
suds/client.py
https://github.com/suds-community/suds/blob/6fb0a829337b5037a66c20aae6f89b41acd77e40/suds/client.py#L852-L868
def __headers(self): """ Get HTTP headers for a HTTP/HTTPS SOAP request. @return: A dictionary of header/values. @rtype: dict """ action = self.method.soap.action if isinstance(action, unicode): action = action.encode("utf-8") result = { "Content-Type": "text/xml; charset=utf-8", "SOAPAction": action} result.update(**self.options.headers) log.debug("headers = %s", result) return result
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Get HTTP headers for a HTTP/HTTPS SOAP request. @return: A dictionary of header/values. @rtype: dict
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python
train
ntucllab/libact
libact/base/dataset.py
https://github.com/ntucllab/libact/blob/e37e9ed6c36febe701d84b2d495c958ab02f0bc8/libact/base/dataset.py#L104-L119
def update(self, entry_id, new_label): """ Updates an entry with entry_id with the given label Parameters ---------- entry_id : int entry id of the sample to update. label : {int, None} Label of the sample to be update. """ self.data[entry_id] = (self.data[entry_id][0], new_label) self.modified = True for callback in self._update_callback: callback(entry_id, new_label)
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Updates an entry with entry_id with the given label Parameters ---------- entry_id : int entry id of the sample to update. label : {int, None} Label of the sample to be update.
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python
train
jgorset/facebook
facebook/user.py
https://github.com/jgorset/facebook/blob/90f035ae1828e4eeb7af428964fedf0ee99ec2ad/facebook/user.py#L85-L106
def work(self): """ A list of :class:`Employment` instances describing the user's work history. Each structure has attributes ``employer``, ``position``, ``started_at`` and ``ended_at``. ``employer`` and ``position`` reference ``Page`` instances, while ``started_at`` and ``ended_at`` are datetime objects. """ employments = [] for work in self.cache['work']: employment = Employment( employer = work.get('employer'), position = work.get('position'), started_at = work.get('start_date'), ended_at = work.get('end_date') ) employments.append(employment) return employments
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python
train
realitix/vulkan
generator/generate.py
https://github.com/realitix/vulkan/blob/07285387092aaa61d2d71fa2913d60a73f022cbe/generator/generate.py#L325-L445
def model_functions(vk, model): """Fill the model with functions""" def get_vk_extension_functions(): names = set() for extension in get_extensions_filtered(vk): for req in extension['require']: if 'command' not in req: continue for command in req['command']: cn = command['@name'] names.add(cn) # add alias command too for alias, n in model['alias'].items(): if n == cn: names.add(alias) return names def get_count_param(command): for param in command['param']: if param['type'] + param.get('#text', '') == 'uint32_t*': return param return None def member_has_str(name): c = next(iter([x for x in model['constructors'] if x['name'] == name]), None) if c and any(['char' in x['type'] for x in c['members']]): return True return False def format_member(member): type_name = member['type'] if '#text' in member: text = member['#text'].replace('const ', '').strip() type_name += ' ' + text return {'name': member['name'], 'type': member['type'], 'none': member['name'] in NULL_MEMBERS, 'force_array': True if '@len' in member else False, 'to_create': False, 'has_str': member_has_str(member['type'])} def format_return_member(member): t = member['type'] static_count = None if '@len' in member and '::' in member['@len']: lens = member['@len'].split('::') static_count = {'key': lens[0], 'value': lens[1]} is_handle = t in get_handle_names(vk) is_enum = t in get_enum_names(vk) is_struct = t in get_struct_names(vk) return {'name': member['name'], 'type': t, 'handle': is_handle, 'enum': is_enum, 'struct': is_struct, 'static_count': static_count, 'has_str': member_has_str(member['type'])} ALLOCATE_PREFIX = ('vkCreate', 'vkGet', 'vkEnumerate', 'vkAllocate', 'vkMap', 'vkAcquire') ALLOCATE_EXCEPTION = ('vkGetFenceStatus', 'vkGetEventStatus', 'vkGetQueryPoolResults', 'vkGetPhysicalDeviceXlibPresentationSupportKHR') COUNT_EXCEPTION = ('vkAcquireNextImageKHR', 'vkEnumerateInstanceVersion') model['functions'] = [] model['extension_functions'] = [] functions = [f for f in vk['registry']['commands']['command']] extension_function_names = get_vk_extension_functions() for function in functions: if '@alias' in function: continue fname = function['proto']['name'] ftype = function['proto']['type'] if fname in CUSTOM_FUNCTIONS: continue if type(function['param']) is not list: function['param'] = [function['param']] count_param = get_count_param(function) if fname in COUNT_EXCEPTION: count_param = None is_allocate = any([fname.startswith(a) for a in ALLOCATE_PREFIX]) is_count = is_allocate and count_param is not None if fname in ALLOCATE_EXCEPTION or ftype == 'VkBool32': is_allocate = is_count = False members = [] for member in function['param']: members.append(format_member(member)) return_member = None if is_allocate: return_member = format_return_member(function['param'][-1]) members[-1]['to_create'] = True if is_count: members[-2]['to_create'] = True f = { 'name': fname, 'members': members, 'allocate': is_allocate, 'count': is_count, 'return_boolean': True if ftype == 'VkBool32' else False, 'return_result': True if ftype == 'VkResult' else False, 'return_member': return_member, 'is_extension': fname in extension_function_names } model['functions'].append(f)
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Fill the model with functions
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python
train
quantopian/zipline
zipline/finance/commission.py
https://github.com/quantopian/zipline/blob/77ad15e6dc4c1cbcdc133653bac8a63fc704f7fe/zipline/finance/commission.py#L364-L369
def calculate(self, order, transaction): """ Pay commission based on dollar value of shares. """ cost_per_share = transaction.price * self.cost_per_dollar return abs(transaction.amount) * cost_per_share
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Pay commission based on dollar value of shares.
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python
train
zxylvlp/PingPHP
pingphp/grammar.py
https://github.com/zxylvlp/PingPHP/blob/2e9a5f1ef4b5b13310e3f8ff350fa91032357bc5/pingphp/grammar.py#L1095-L1103
def p_InterfaceDefList(p): ''' InterfaceDefList : InterfaceDef | InterfaceDefList InterfaceDef ''' if len(p) < 3: p[0] = InterfaceDefList(None, p[1]) else: p[0] = InterfaceDefList(p[1], p[2])
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InterfaceDefList : InterfaceDef | InterfaceDefList InterfaceDef
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python
train
astropy/astropy-healpix
astropy_healpix/high_level.py
https://github.com/astropy/astropy-healpix/blob/c7fbe36305aadda9946dd37969d5dcb9ff6b1440/astropy_healpix/high_level.py#L272-L298
def healpix_to_skycoord(self, healpix_index, dx=None, dy=None): """ Convert HEALPix indices (optionally with offsets) to celestial coordinates. Note that this method requires that a celestial frame was specified when initializing HEALPix. If you don't know or need the celestial frame, you can instead use :meth:`~astropy_healpix.HEALPix.healpix_to_lonlat`. Parameters ---------- healpix_index : `~numpy.ndarray` 1-D array of HEALPix indices dx, dy : `~numpy.ndarray`, optional 1-D arrays of offsets inside the HEALPix pixel, which must be in the range [0:1] (0.5 is the center of the HEALPix pixels). If not specified, the position at the center of the pixel is used. Returns ------- coord : :class:`~astropy.coordinates.SkyCoord` The resulting celestial coordinates """ if self.frame is None: raise NoFrameError("healpix_to_skycoord") lon, lat = self.healpix_to_lonlat(healpix_index, dx=dx, dy=dy) representation = UnitSphericalRepresentation(lon, lat, copy=False) return SkyCoord(self.frame.realize_frame(representation))
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Convert HEALPix indices (optionally with offsets) to celestial coordinates. Note that this method requires that a celestial frame was specified when initializing HEALPix. If you don't know or need the celestial frame, you can instead use :meth:`~astropy_healpix.HEALPix.healpix_to_lonlat`. Parameters ---------- healpix_index : `~numpy.ndarray` 1-D array of HEALPix indices dx, dy : `~numpy.ndarray`, optional 1-D arrays of offsets inside the HEALPix pixel, which must be in the range [0:1] (0.5 is the center of the HEALPix pixels). If not specified, the position at the center of the pixel is used. Returns ------- coord : :class:`~astropy.coordinates.SkyCoord` The resulting celestial coordinates
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python
train
obriencj/python-javatools
javatools/__init__.py
https://github.com/obriencj/python-javatools/blob/9e2332b452ddc508bed0615937dddcb2cf051557/javatools/__init__.py#L2226-L2277
def _pretty_type(s, offset=0): # pylint: disable=R0911, R0912 # too many returns, too many branches. Not converting this to a # dict lookup. Waiving instead. """ returns the pretty version of a type code """ tc = s[offset] if tc == "V": return "void" elif tc == "Z": return "boolean" elif tc == "C": return "char" elif tc == "B": return "byte" elif tc == "S": return "short" elif tc == "I": return "int" elif tc == "J": return "long" elif tc == "D": return "double" elif tc == "F": return "float" elif tc == "L": return _pretty_class(s[offset + 1:-1]) elif tc == "[": return "%s[]" % _pretty_type(s, offset + 1) elif tc == "(": return "(%s)" % ",".join(_pretty_typeseq(s[offset + 1:-1])) elif tc == "T": return "generic " + s[offset + 1:] else: raise Unimplemented("unknown type, %r" % tc)
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returns the pretty version of a type code
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python
train
theonion/django-bulbs
bulbs/api/views.py
https://github.com/theonion/django-bulbs/blob/0c0e6e3127a7dc487b96677fab95cacd2b3806da/bulbs/api/views.py#L204-L216
def status(self, request, **kwargs): """This endpoint returns a status text, currently one of: - "Draft" (If no publish date is set, and no item exists in the editor queue) - "Waiting for Editor" (If no publish date is set, and an item exists in the editor queue) - "Published" (The published date is in the past) - "Scheduled" (The published date is set in the future) :param request: a WSGI request object :param kwargs: keyword arguments (optional) :return: `rest_framework.response.Response` """ content = self.get_object() return Response({"status": content.get_status()})
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This endpoint returns a status text, currently one of: - "Draft" (If no publish date is set, and no item exists in the editor queue) - "Waiting for Editor" (If no publish date is set, and an item exists in the editor queue) - "Published" (The published date is in the past) - "Scheduled" (The published date is set in the future) :param request: a WSGI request object :param kwargs: keyword arguments (optional) :return: `rest_framework.response.Response`
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python
train
timothydmorton/isochrones
isochrones/observation.py
https://github.com/timothydmorton/isochrones/blob/d84495573044c66db2fd6b959fe69e370757ea14/isochrones/observation.py#L827-L856
def save_hdf(self, filename, path='', overwrite=False, append=False): """ Writes all info necessary to recreate object to HDF file Saves table of photometry in DataFrame Saves model specification, spectroscopy, parallax to attrs """ if os.path.exists(filename): store = pd.HDFStore(filename) if path in store: store.close() if overwrite: os.remove(filename) elif not append: raise IOError('{} in {} exists. Set either overwrite or append option.'.format(path,filename)) else: store.close() df = self.to_df() df.to_hdf(filename, path+'/df') with pd.HDFStore(filename) as store: # store = pd.HDFStore(filename) attrs = store.get_storer(path+'/df').attrs attrs.spectroscopy = self.spectroscopy attrs.parallax = self.parallax attrs.N = self._N attrs.index = self._index store.close()
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Writes all info necessary to recreate object to HDF file Saves table of photometry in DataFrame Saves model specification, spectroscopy, parallax to attrs
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python
train
satellogic/telluric
telluric/georaster.py
https://github.com/satellogic/telluric/blob/e752cd3ee71e339f79717e526fde362e80055d9e/telluric/georaster.py#L838-L934
def save(self, filename, tags=None, **kwargs): """ Save GeoRaster to a file. :param filename: url :param tags: tags to add to default namespace optional parameters: * GDAL_TIFF_INTERNAL_MASK: specifies whether mask is within image file, or additional .msk * overviews: if True, will save with previews. default: True * factors: list of factors for the overview, default: calculated based on raster width and height * resampling: to build overviews. default: cubic * tiled: if True raster will be saved tiled, default: False * compress: any supported rasterio.enums.Compression value, default to LZW * blockxsize: int, tile x size, default:256 * blockysize: int, tile y size, default:256 * creation_options: dict, key value of additional creation options * nodata: if passed, will save with nodata value (e.g. useful for qgis) """ if not filename.startswith("/vsi"): folder = os.path.abspath(os.path.join(filename, os.pardir)) os.makedirs(folder, exist_ok=True) internal_mask = kwargs.get('GDAL_TIFF_INTERNAL_MASK', True) nodata_value = kwargs.get('nodata', None) compression = kwargs.get('compression', Compression.lzw) rasterio_envs = {'GDAL_TIFF_INTERNAL_MASK': internal_mask} if os.environ.get('DEBUG', False): rasterio_envs['CPL_DEBUG'] = True with rasterio.Env(**rasterio_envs): try: size = self.shape extension = os.path.splitext(filename)[1].lower()[1:] driver = gdal_drivers[extension] # tiled tiled = kwargs.get('tiled', False) blockxsize = kwargs.get('blockxsize', 256) blockysize = kwargs.get('blockysize', 256) params = { 'mode': "w", 'transform': self.affine, 'crs': self.crs, 'driver': driver, 'width': size[2], 'height': size[1], 'count': size[0], 'dtype': dtype_map[self.dtype.type], 'nodata': nodata_value, 'masked': True, 'blockxsize': min(blockxsize, size[2]), 'blockysize': min(blockysize, size[1]), 'tiled': tiled, 'compress': compression.name if compression in Compression else compression, } # additional creation options # -co COPY_SRC_OVERVIEWS=YES -co COMPRESS=DEFLATE -co PHOTOMETRIC=MINISBLACK creation_options = kwargs.get('creation_options', {}) if creation_options: params.update(**creation_options) if self._image is None and self._filename is not None: creation_options["blockxsize"] = params["blockxsize"] creation_options["blockysize"] = params["blockysize"] creation_options["tiled"] = params["tiled"] creation_options["compress"] = params["compress"] rasterio.shutil.copy(self.source_file, filename, creation_options=creation_options) self._cleanup() with GeoRaster2._raster_opener(filename, "r+",) as r: self._add_overviews_and_tags(r, tags, kwargs) else: with GeoRaster2._raster_opener(filename, **params) as r: # write data: for band in range(self.shape[0]): img = self.image.data r.write_band(1 + band, img[band, :, :]) # write mask: if not ( np.ma.getmaskarray(self.image) == np.ma.getmaskarray(self.image)[0] ).all(): warnings.warn( "Saving different masks per band is not supported, " "the union of the masked values will be performed.", GeoRaster2Warning ) if params.get('masked'): mask = _mask_from_masked_array(self.image) r.write_mask(mask) self._add_overviews_and_tags(r, tags, kwargs) return GeoRaster2.open(filename) except (rasterio.errors.RasterioIOError, rasterio._err.CPLE_BaseError, KeyError) as e: raise GeoRaster2IOError(e)
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Save GeoRaster to a file. :param filename: url :param tags: tags to add to default namespace optional parameters: * GDAL_TIFF_INTERNAL_MASK: specifies whether mask is within image file, or additional .msk * overviews: if True, will save with previews. default: True * factors: list of factors for the overview, default: calculated based on raster width and height * resampling: to build overviews. default: cubic * tiled: if True raster will be saved tiled, default: False * compress: any supported rasterio.enums.Compression value, default to LZW * blockxsize: int, tile x size, default:256 * blockysize: int, tile y size, default:256 * creation_options: dict, key value of additional creation options * nodata: if passed, will save with nodata value (e.g. useful for qgis)
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python
train
saltstack/salt
salt/utils/cache.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/utils/cache.py#L244-L248
def put_cache(self, minions): ''' published the given minions to the ConCache ''' self.cupd_out.send(self.serial.dumps(minions))
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published the given minions to the ConCache
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python
train
openvax/pepdata
pepdata/iedb/alleles.py
https://github.com/openvax/pepdata/blob/2f1bad79f8084545227f4a7f895bbf08a6fb6fdc/pepdata/iedb/alleles.py#L25-L31
def local_path(force_download=False): """Downloads allele database from IEDB, returns local path to XML file.""" return cache.fetch( filename=ALLELE_XML_FILENAME, url=ALLELE_XML_URL, decompress=ALLELE_XML_DECOMPRESS, force=force_download)
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Downloads allele database from IEDB, returns local path to XML file.
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python
train
petl-developers/petl
petl/util/vis.py
https://github.com/petl-developers/petl/blob/1d33ca055f7e04e0d28a772041c9fd30c8d415d6/petl/util/vis.py#L155-L162
def lookstr(table, limit=0, **kwargs): """Like :func:`petl.util.vis.look` but use str() rather than repr() for data values. """ kwargs['vrepr'] = str return look(table, limit=limit, **kwargs)
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Like :func:`petl.util.vis.look` but use str() rather than repr() for data values.
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python
train
yandex/yandex-tank
yandextank/common/interfaces.py
https://github.com/yandex/yandex-tank/blob/d71d63b6ab5de8b8a5ea2b728b6ab9ac0b1ba71b/yandextank/common/interfaces.py#L98-L102
def publish(self, key, value): """publish value to status""" self.log.debug( "Publishing status: %s/%s: %s", self.__class__.__name__, key, value) self.core.publish(self.__class__.__name__, key, value)
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publish value to status
[ "publish", "value", "to", "status" ]
python
test
rosenbrockc/fortpy
fortpy/msg.py
https://github.com/rosenbrockc/fortpy/blob/1ed0757c52d549e41d9d44bdea68cb89529293a5/fortpy/msg.py#L27-L40
def printer(text, color=None, **kwargs): """Prints using color or standard print() depending on the value of 'nocolor'. """ if nocolor: # import sys # sys.stdout.write(text + "" if ("end" in kwargs and kwargs["end"] == "") else '\n') # sys.stdout.flush() print(text, **kwargs) else: if color is None: cprint(text, **kwargs) else: cprint(text, color, **kwargs)
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Prints using color or standard print() depending on the value of 'nocolor'.
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python
train
xapple/plumbing
plumbing/slurm/job.py
https://github.com/xapple/plumbing/blob/4a7706c7722f5996d0ca366f191aff9ac145880a/plumbing/slurm/job.py#L121-L136
def set_paths(self, base_dir, script_path): """Set the directory, the script path and the outfile path""" # Make absolute paths # if 'change_dir' in self.kwargs: self.kwargs['change_dir'] = DirectoryPath(os.path.abspath(self.kwargs['change_dir'])) if 'out_file' in self.kwargs: self.kwargs['out_file'] = FilePath(os.path.abspath(self.kwargs['out_file'])) # In case there is a base directory # if base_dir is not None: self.base_dir = DirectoryPath(os.path.abspath(base_dir)) self.script_path = FilePath(base_dir + "run." + self.extensions[self.language]) self.kwargs['change_dir'] = base_dir self.kwargs['out_file'] = FilePath(base_dir + "run.out") # Other cases # if base_dir is None and script_path is None: self.script_path = FilePath(new_temp_path()) if script_path is not None: self.script_path = FilePath(os.path.abspath(script_path))
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Set the directory, the script path and the outfile path
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python
train
MacHu-GWU/uszipcode-project
uszipcode/search.py
https://github.com/MacHu-GWU/uszipcode-project/blob/96282b779a3efb422802de83c48ca284598ba952/uszipcode/search.py#L616-L631
def by_state(self, state, zipcode_type=ZipcodeType.Standard, sort_by=SimpleZipcode.zipcode.name, ascending=True, returns=DEFAULT_LIMIT): """ Search zipcode information by fuzzy State name. My engine use fuzzy match and guess what is the state you want. """ return self.query( state=state, sort_by=sort_by, zipcode_type=zipcode_type, ascending=ascending, returns=returns, )
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Search zipcode information by fuzzy State name. My engine use fuzzy match and guess what is the state you want.
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python
train
fhamborg/news-please
newsplease/helper_classes/url_extractor.py
https://github.com/fhamborg/news-please/blob/731837c2a6c223cfb3e1d7f5fdc4f4eced2310f9/newsplease/helper_classes/url_extractor.py#L68-L107
def get_sitemap_url(url, allow_subdomains): """ Determines the domain's robot.txt :param str url: the url to work on :param bool allow_subdomains: Determines if the robot.txt may be the subdomain's :return: the robot.txt's address :raises Exception: if there's no robot.txt on the site's domain """ if allow_subdomains: redirect = UrlExtractor.follow_redirects( "http://" + UrlExtractor.get_allowed_domain(url) ) else: redirect = UrlExtractor.follow_redirects( "http://" + UrlExtractor.get_allowed_domain(url, False) ) redirect = UrlExtractor.follow_redirects(url) # Get robots.txt parsed = urlparse(redirect) if allow_subdomains: url_netloc = parsed.netloc else: url_netloc = UrlExtractor.get_allowed_domain( parsed.netloc, False) robots = '{url.scheme}://{url_netloc}/robots.txt'.format( url=parsed, url_netloc=url_netloc) try: urllib2.urlopen(robots) return robots except: if allow_subdomains: return UrlExtractor.get_sitemap_url(url, False) else: raise Exception('Fatal: no robots.txt found.')
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Determines the domain's robot.txt :param str url: the url to work on :param bool allow_subdomains: Determines if the robot.txt may be the subdomain's :return: the robot.txt's address :raises Exception: if there's no robot.txt on the site's domain
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python
train
openstack/networking-cisco
networking_cisco/plugins/cisco/device_manager/config.py
https://github.com/openstack/networking-cisco/blob/aa58a30aec25b86f9aa5952b0863045975debfa9/networking_cisco/plugins/cisco/device_manager/config.py#L148-L199
def verify_resource_dict(res_dict, is_create, attr_info): """Verifies required attributes are in resource dictionary, res_dict. Also checking that an attribute is only specified if it is allowed for the given operation (create/update). Attribute with default values are considered to be optional. This function contains code taken from function 'prepare_request_body' in attributes.py. """ if ((bc.NEUTRON_VERSION >= bc.NEUTRON_NEWTON_VERSION) and 'tenant_id' in res_dict): res_dict['project_id'] = res_dict['tenant_id'] if is_create: # POST for attr, attr_vals in six.iteritems(attr_info): if attr_vals['allow_post']: if 'default' not in attr_vals and attr not in res_dict: msg = _("Failed to parse request. Required attribute '%s' " "not specified") % attr raise webob.exc.HTTPBadRequest(msg) res_dict[attr] = res_dict.get(attr, attr_vals.get('default')) else: if attr in res_dict: msg = _("Attribute '%s' not allowed in POST") % attr raise webob.exc.HTTPBadRequest(msg) else: # PUT for attr, attr_vals in six.iteritems(attr_info): if attr in res_dict and not attr_vals['allow_put']: msg = _("Cannot update read-only attribute %s") % attr raise webob.exc.HTTPBadRequest(msg) for attr, attr_vals in six.iteritems(attr_info): if (attr not in res_dict or res_dict[attr] is bc.constants.ATTR_NOT_SPECIFIED): continue # Convert values if necessary if 'convert_to' in attr_vals: res_dict[attr] = attr_vals['convert_to'](res_dict[attr]) # Check that configured values are correct if 'validate' not in attr_vals: continue for rule in attr_vals['validate']: _ensure_format(rule, attr, res_dict) res = bc.validators[rule](res_dict[attr], attr_vals['validate'][rule]) if res: msg_dict = dict(attr=attr, reason=res) msg = (_("Invalid input for %(attr)s. Reason: %(reason)s.") % msg_dict) raise webob.exc.HTTPBadRequest(msg) return res_dict
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Verifies required attributes are in resource dictionary, res_dict. Also checking that an attribute is only specified if it is allowed for the given operation (create/update). Attribute with default values are considered to be optional. This function contains code taken from function 'prepare_request_body' in attributes.py.
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python
train
mlperf/training
object_detection/pytorch/maskrcnn_benchmark/structures/boxlist_ops.py
https://github.com/mlperf/training/blob/1c6ae725a81d15437a2b2df05cac0673fde5c3a4/object_detection/pytorch/maskrcnn_benchmark/structures/boxlist_ops.py#L102-L128
def cat_boxlist(bboxes): """ Concatenates a list of BoxList (having the same image size) into a single BoxList Arguments: bboxes (list[BoxList]) """ assert isinstance(bboxes, (list, tuple)) assert all(isinstance(bbox, BoxList) for bbox in bboxes) size = bboxes[0].size assert all(bbox.size == size for bbox in bboxes) mode = bboxes[0].mode assert all(bbox.mode == mode for bbox in bboxes) fields = set(bboxes[0].fields()) assert all(set(bbox.fields()) == fields for bbox in bboxes) cat_boxes = BoxList(_cat([bbox.bbox for bbox in bboxes], dim=0), size, mode) for field in fields: data = _cat([bbox.get_field(field) for bbox in bboxes], dim=0) cat_boxes.add_field(field, data) return cat_boxes
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Concatenates a list of BoxList (having the same image size) into a single BoxList Arguments: bboxes (list[BoxList])
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python
train
globality-corp/microcosm-postgres
microcosm_postgres/store.py
https://github.com/globality-corp/microcosm-postgres/blob/43dd793b1fc9b84e4056700f350e79e0df5ff501/microcosm_postgres/store.py#L211-L217
def _filter(self, query, **kwargs): """ Filter a query with user-supplied arguments. """ query = self._auto_filter(query, **kwargs) return query
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Filter a query with user-supplied arguments.
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python
train
Cadasta/django-tutelary
tutelary/models.py
https://github.com/Cadasta/django-tutelary/blob/66bb05de7098777c0a383410c287bf48433cde87/tutelary/models.py#L363-L377
def assign_user_policies(user, *policies_roles): """Assign a sequence of policies to a user (or the anonymous user is ``user`` is ``None``). (Also installed as ``assign_policies`` method on ``User`` model. """ clear_user_policies(user) pset = PermissionSet.objects.by_policies_and_roles(policies_roles) pset.refresh() if user is None: pset.anonymous_user = True else: pset.users.add(user) pset.save() cache.set(user_cache_key(user), None)
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Assign a sequence of policies to a user (or the anonymous user is ``user`` is ``None``). (Also installed as ``assign_policies`` method on ``User`` model.
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python
train
materialsproject/pymatgen
pymatgen/io/abinit/pseudos.py
https://github.com/materialsproject/pymatgen/blob/4ca558cf72f8d5f8a1f21dfdfc0181a971c186da/pymatgen/io/abinit/pseudos.py#L1786-L1797
def print_table(self, stream=sys.stdout, filter_function=None): """ A pretty ASCII printer for the periodic table, based on some filter_function. Args: stream: file-like object filter_function: A filtering function that take a Pseudo as input and returns a boolean. For example, setting filter_function = lambda p: p.Z_val > 2 will print a periodic table containing only pseudos with Z_val > 2. """ print(self.to_table(filter_function=filter_function), file=stream)
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A pretty ASCII printer for the periodic table, based on some filter_function. Args: stream: file-like object filter_function: A filtering function that take a Pseudo as input and returns a boolean. For example, setting filter_function = lambda p: p.Z_val > 2 will print a periodic table containing only pseudos with Z_val > 2.
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python
train
dmlc/xgboost
python-package/xgboost/core.py
https://github.com/dmlc/xgboost/blob/253fdd8a42d5ec6b819788199584d27bf9ea6253/python-package/xgboost/core.py#L1072-L1087
def set_param(self, params, value=None): """Set parameters into the Booster. Parameters ---------- params: dict/list/str list of key,value pairs, dict of key to value or simply str key value: optional value of the specified parameter, when params is str key """ if isinstance(params, Mapping): params = params.items() elif isinstance(params, STRING_TYPES) and value is not None: params = [(params, value)] for key, val in params: _check_call(_LIB.XGBoosterSetParam(self.handle, c_str(key), c_str(str(val))))
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Set parameters into the Booster. Parameters ---------- params: dict/list/str list of key,value pairs, dict of key to value or simply str key value: optional value of the specified parameter, when params is str key
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python
train
akfullfo/taskforce
taskforce/utils.py
https://github.com/akfullfo/taskforce/blob/bc6dd744bd33546447d085dbd18a350532220193/taskforce/utils.py#L282-L307
def module_description(module__name__, module__doc__, module__file__): """ Return formatted text that lists the module-level and class-level embedded documentation. The function should be called exactly as: taskforce.utils.module_description(__name__, __doc__, __file__) The most common use for this function is to produce the help message for test code in a library module, which might look something like: if __name__ == "__main__": import ns_utils, argparse p = argparse.ArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter, description=taskforce.utils.module_description(__name__, __doc__, __file__)) """ mod_name = os.path.splitext(os.path.basename(module__file__))[0] mod_desc = (lambda x: x + '\n' + '='*len(x) + '\n')('Module '+mod_name) if mod_name else '' for name, obj in inspect.getmembers(sys.modules[module__name__]): if inspect.isclass(obj) and '__doc__' in dir(obj) and obj.__doc__: mod_desc += '\n' + (lambda x: x + '\n' + '-'*len(x) + '\n')('Class '+name) mod_desc += obj.__doc__.lstrip() return mod_desc
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Return formatted text that lists the module-level and class-level embedded documentation. The function should be called exactly as: taskforce.utils.module_description(__name__, __doc__, __file__) The most common use for this function is to produce the help message for test code in a library module, which might look something like: if __name__ == "__main__": import ns_utils, argparse p = argparse.ArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter, description=taskforce.utils.module_description(__name__, __doc__, __file__))
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python
train
EliotBerriot/django-dynamic-preferences
dynamic_preferences/managers.py
https://github.com/EliotBerriot/django-dynamic-preferences/blob/12eab4f17b960290525b215d954d1b5fb91199df/dynamic_preferences/managers.py#L47-L49
def by_name(self): """Return a dictionary with preferences identifiers and values, but without the section name in the identifier""" return {key.split(preferences_settings.SECTION_KEY_SEPARATOR)[-1]: value for key, value in self.all().items()}
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Return a dictionary with preferences identifiers and values, but without the section name in the identifier
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python
train