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globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.find_ips_by_equip
def find_ips_by_equip(self, id_equip): """ Get Ips related to equipment by its identifier :param id_equip: Equipment identifier. Integer value and greater than zero. :return: Dictionary with the following structure: { ips: { ipv4:[ id: <id_ip4>, oct1: <oct1>, oct2: <oct2>, oct3: <oct3>, oct4: <oct4>, descricao: <descricao> ] ipv6:[ id: <id_ip6>, block1: <block1>, block2: <block2>, block3: <block3>, block4: <block4>, block5: <block5>, block6: <block6>, block7: <block7>, block8: <block8>, descricao: <descricao> ] } } :raise UserNotAuthorizedError: User dont have permission to list ips. :raise InvalidParameterError: Equipment identifier is none or invalid. :raise XMLError: Networkapi failed to generate the XML response. :raise DataBaseError: Networkapi failed to access the database. """ url = 'ip/getbyequip/' + str(id_equip) + "/" code, xml = self.submit(None, 'GET', url) return self.response(code, xml, ['ipv4', 'ipv6'])
python
def find_ips_by_equip(self, id_equip): """ Get Ips related to equipment by its identifier :param id_equip: Equipment identifier. Integer value and greater than zero. :return: Dictionary with the following structure: { ips: { ipv4:[ id: <id_ip4>, oct1: <oct1>, oct2: <oct2>, oct3: <oct3>, oct4: <oct4>, descricao: <descricao> ] ipv6:[ id: <id_ip6>, block1: <block1>, block2: <block2>, block3: <block3>, block4: <block4>, block5: <block5>, block6: <block6>, block7: <block7>, block8: <block8>, descricao: <descricao> ] } } :raise UserNotAuthorizedError: User dont have permission to list ips. :raise InvalidParameterError: Equipment identifier is none or invalid. :raise XMLError: Networkapi failed to generate the XML response. :raise DataBaseError: Networkapi failed to access the database. """ url = 'ip/getbyequip/' + str(id_equip) + "/" code, xml = self.submit(None, 'GET', url) return self.response(code, xml, ['ipv4', 'ipv6'])
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Get Ips related to equipment by its identifier :param id_equip: Equipment identifier. Integer value and greater than zero. :return: Dictionary with the following structure: { ips: { ipv4:[ id: <id_ip4>, oct1: <oct1>, oct2: <oct2>, oct3: <oct3>, oct4: <oct4>, descricao: <descricao> ] ipv6:[ id: <id_ip6>, block1: <block1>, block2: <block2>, block3: <block3>, block4: <block4>, block5: <block5>, block6: <block6>, block7: <block7>, block8: <block8>, descricao: <descricao> ] } } :raise UserNotAuthorizedError: User dont have permission to list ips. :raise InvalidParameterError: Equipment identifier is none or invalid. :raise XMLError: Networkapi failed to generate the XML response. :raise DataBaseError: Networkapi failed to access the database.
[ "Get", "Ips", "related", "to", "equipment", "by", "its", "identifier" ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L535-L572
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.find_ip6_by_id
def find_ip6_by_id(self, id_ip): """ Get an IP6 by ID :param id_ip: IP6 identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ip': {'id': < id >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description >, 'equipamento': [ { all name equipamentos related} ], }} :raise IpNotAvailableError: Network dont have available IPv6. :raise NetworkIPv4NotFoundError: Network was not found. :raise UserNotAuthorizedError: User dont have permission to perform operation. :raise InvalidParameterError: IPv6 identifier is none or invalid. :raise XMLError: Networkapi failed to generate the XML response. :raise DataBaseError: Networkapi failed to access the database. """ if not is_valid_int_param(id_ip): raise InvalidParameterError( u'Ipv6 identifier is invalid or was not informed.') url = 'ipv6/get/' + str(id_ip) + "/" code, xml = self.submit(None, 'GET', url) return self.response(code, xml)
python
def find_ip6_by_id(self, id_ip): """ Get an IP6 by ID :param id_ip: IP6 identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ip': {'id': < id >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description >, 'equipamento': [ { all name equipamentos related} ], }} :raise IpNotAvailableError: Network dont have available IPv6. :raise NetworkIPv4NotFoundError: Network was not found. :raise UserNotAuthorizedError: User dont have permission to perform operation. :raise InvalidParameterError: IPv6 identifier is none or invalid. :raise XMLError: Networkapi failed to generate the XML response. :raise DataBaseError: Networkapi failed to access the database. """ if not is_valid_int_param(id_ip): raise InvalidParameterError( u'Ipv6 identifier is invalid or was not informed.') url = 'ipv6/get/' + str(id_ip) + "/" code, xml = self.submit(None, 'GET', url) return self.response(code, xml)
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Get an IP6 by ID :param id_ip: IP6 identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ip': {'id': < id >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description >, 'equipamento': [ { all name equipamentos related} ], }} :raise IpNotAvailableError: Network dont have available IPv6. :raise NetworkIPv4NotFoundError: Network was not found. :raise UserNotAuthorizedError: User dont have permission to perform operation. :raise InvalidParameterError: IPv6 identifier is none or invalid. :raise XMLError: Networkapi failed to generate the XML response. :raise DataBaseError: Networkapi failed to access the database.
[ "Get", "an", "IP6", "by", "ID" ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L574-L614
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.save_ipv6
def save_ipv6(self, ip6, id_equip, descricao, id_net): """ Save an IP6 and associate with equipment :param ip6: An IP6 available to save in format xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx. :param id_equip: Equipment identifier. Integer value and greater than zero. :param descricao: IPv6 description. :param id_net: Network identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ipv6': {'id': < id >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description >, 'equipamento': [ { all name equipamentos related } ], }} """ if not is_valid_int_param(id_net): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') if not is_valid_int_param(id_equip): raise InvalidParameterError( u'Equipment identifier is invalid or was not informed.') if ip6 is None or ip6 == "": raise InvalidParameterError( u'IPv6 is invalid or was not informed.') ip_map = dict() ip_map['id_net'] = id_net ip_map['descricao'] = descricao ip_map['ip6'] = ip6 ip_map['id_equip'] = id_equip url = "ipv6/save/" code, xml = self.submit({'ip_map': ip_map}, 'POST', url) return self.response(code, xml)
python
def save_ipv6(self, ip6, id_equip, descricao, id_net): """ Save an IP6 and associate with equipment :param ip6: An IP6 available to save in format xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx. :param id_equip: Equipment identifier. Integer value and greater than zero. :param descricao: IPv6 description. :param id_net: Network identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ipv6': {'id': < id >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description >, 'equipamento': [ { all name equipamentos related } ], }} """ if not is_valid_int_param(id_net): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') if not is_valid_int_param(id_equip): raise InvalidParameterError( u'Equipment identifier is invalid or was not informed.') if ip6 is None or ip6 == "": raise InvalidParameterError( u'IPv6 is invalid or was not informed.') ip_map = dict() ip_map['id_net'] = id_net ip_map['descricao'] = descricao ip_map['ip6'] = ip6 ip_map['id_equip'] = id_equip url = "ipv6/save/" code, xml = self.submit({'ip_map': ip_map}, 'POST', url) return self.response(code, xml)
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Save an IP6 and associate with equipment :param ip6: An IP6 available to save in format xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx:xxxx. :param id_equip: Equipment identifier. Integer value and greater than zero. :param descricao: IPv6 description. :param id_net: Network identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ipv6': {'id': < id >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description >, 'equipamento': [ { all name equipamentos related } ], }}
[ "Save", "an", "IP6", "and", "associate", "with", "equipment" ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L616-L663
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.delete_ip4
def delete_ip4(self, id_ip): """ Delete an IP4 :param id_ip: Ipv4 identifier. Integer value and greater than zero. :return: None :raise IpNotFoundError: IP is not registered. :raise DataBaseError: Networkapi failed to access the database. """ if not is_valid_int_param(id_ip): raise InvalidParameterError(u'Ipv4 identifier is invalid or was not informed.') url = 'ip4/delete/' + str(id_ip) + "/" code, xml = self.submit(None, 'DELETE', url) return self.response(code, xml)
python
def delete_ip4(self, id_ip): """ Delete an IP4 :param id_ip: Ipv4 identifier. Integer value and greater than zero. :return: None :raise IpNotFoundError: IP is not registered. :raise DataBaseError: Networkapi failed to access the database. """ if not is_valid_int_param(id_ip): raise InvalidParameterError(u'Ipv4 identifier is invalid or was not informed.') url = 'ip4/delete/' + str(id_ip) + "/" code, xml = self.submit(None, 'DELETE', url) return self.response(code, xml)
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Delete an IP4 :param id_ip: Ipv4 identifier. Integer value and greater than zero. :return: None :raise IpNotFoundError: IP is not registered. :raise DataBaseError: Networkapi failed to access the database.
[ "Delete", "an", "IP4" ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L665-L684
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.find_ip6_by_network
def find_ip6_by_network(self, id_network): """List IPv6 from network. :param id_network: Network ipv6 identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ip': {'id': < id >, 'id_vlan': < id_vlan >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description > 'equipamento': [ { all name equipamentos related } ], }} :raise IpNaoExisteError: Network does not have any ips. :raise InvalidParameterError: Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. """ if not is_valid_int_param(id_network): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') url = 'ip/id_network_ipv6/' + str(id_network) + "/" code, xml = self.submit(None, 'GET', url) key = "ips" return get_list_map(self.response(code, xml, [key]), key)
python
def find_ip6_by_network(self, id_network): """List IPv6 from network. :param id_network: Network ipv6 identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ip': {'id': < id >, 'id_vlan': < id_vlan >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description > 'equipamento': [ { all name equipamentos related } ], }} :raise IpNaoExisteError: Network does not have any ips. :raise InvalidParameterError: Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. """ if not is_valid_int_param(id_network): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') url = 'ip/id_network_ipv6/' + str(id_network) + "/" code, xml = self.submit(None, 'GET', url) key = "ips" return get_list_map(self.response(code, xml, [key]), key)
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List IPv6 from network. :param id_network: Network ipv6 identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ip': {'id': < id >, 'id_vlan': < id_vlan >, 'block1': <block1>, 'block2': <block2>, 'block3': <block3>, 'block4': <block4>, 'block5': <block5>, 'block6': <block6>, 'block7': <block7>, 'block8': <block8>, 'descricao': < description > 'equipamento': [ { all name equipamentos related } ], }} :raise IpNaoExisteError: Network does not have any ips. :raise InvalidParameterError: Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database.
[ "List", "IPv6", "from", "network", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L743-L779
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.search_ipv6_environment
def search_ipv6_environment(self, ipv6, id_environment): """Get IPv6 with an associated environment. :param ipv6: IPv6 address in the format x1:x2:x3:x4:x5:x6:x7:x8. :param id_environment: Environment identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ipv6': {'id': < id >, 'id_vlan': < id_vlan >, 'bloco1': < bloco1 >, 'bloco2': < bloco2 >, 'bloco3': < bloco3 >, 'bloco4': < bloco4 >, 'bloco5': < bloco5 >, 'bloco6': < bloco6 >, 'bloco7': < bloco7 >, 'bloco8': < bloco8 >, 'descricao': < descricao > }} :raise IpNaoExisteError: IPv6 is not registered or is not associated to the environment. :raise AmbienteNaoExisteError: Environment not found. :raise InvalidParameterError: Environment identifier and/or IPv6 string is/are none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_environment): raise InvalidParameterError( u'Environment identifier is invalid or was not informed.') ipv6_map = dict() ipv6_map['ipv6'] = ipv6 ipv6_map['id_environment'] = id_environment code, xml = self.submit( {'ipv6_map': ipv6_map}, 'POST', 'ipv6/environment/') return self.response(code, xml)
python
def search_ipv6_environment(self, ipv6, id_environment): """Get IPv6 with an associated environment. :param ipv6: IPv6 address in the format x1:x2:x3:x4:x5:x6:x7:x8. :param id_environment: Environment identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ipv6': {'id': < id >, 'id_vlan': < id_vlan >, 'bloco1': < bloco1 >, 'bloco2': < bloco2 >, 'bloco3': < bloco3 >, 'bloco4': < bloco4 >, 'bloco5': < bloco5 >, 'bloco6': < bloco6 >, 'bloco7': < bloco7 >, 'bloco8': < bloco8 >, 'descricao': < descricao > }} :raise IpNaoExisteError: IPv6 is not registered or is not associated to the environment. :raise AmbienteNaoExisteError: Environment not found. :raise InvalidParameterError: Environment identifier and/or IPv6 string is/are none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_environment): raise InvalidParameterError( u'Environment identifier is invalid or was not informed.') ipv6_map = dict() ipv6_map['ipv6'] = ipv6 ipv6_map['id_environment'] = id_environment code, xml = self.submit( {'ipv6_map': ipv6_map}, 'POST', 'ipv6/environment/') return self.response(code, xml)
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Get IPv6 with an associated environment. :param ipv6: IPv6 address in the format x1:x2:x3:x4:x5:x6:x7:x8. :param id_environment: Environment identifier. Integer value and greater than zero. :return: Dictionary with the following structure: :: {'ipv6': {'id': < id >, 'id_vlan': < id_vlan >, 'bloco1': < bloco1 >, 'bloco2': < bloco2 >, 'bloco3': < bloco3 >, 'bloco4': < bloco4 >, 'bloco5': < bloco5 >, 'bloco6': < bloco6 >, 'bloco7': < bloco7 >, 'bloco8': < bloco8 >, 'descricao': < descricao > }} :raise IpNaoExisteError: IPv6 is not registered or is not associated to the environment. :raise AmbienteNaoExisteError: Environment not found. :raise InvalidParameterError: Environment identifier and/or IPv6 string is/are none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "Get", "IPv6", "with", "an", "associated", "environment", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L781-L822
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.assoc_ipv4
def assoc_ipv4(self, id_ip, id_equip, id_net): """ Associate an IP4 with equipment. :param id_ip: IPv4 identifier. :param id_equip: Equipment identifier. Integer value and greater than zero. :param id_net: Network identifier. Integer value and greater than zero. :return: None :raise InvalidParameterError: IPv4, Equipment or Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_ip): raise InvalidParameterError( u'Ip identifier is invalid or was not informed.') if not is_valid_int_param(id_net): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') if not is_valid_int_param(id_equip): raise InvalidParameterError( u'Equipment identifier is invalid or was not informed.') ip_map = dict() ip_map['id_ip'] = id_ip ip_map['id_net'] = id_net ip_map['id_equip'] = id_equip url = "ipv4/assoc/" code, xml = self.submit({'ip_map': ip_map}, 'POST', url) return self.response(code, xml)
python
def assoc_ipv4(self, id_ip, id_equip, id_net): """ Associate an IP4 with equipment. :param id_ip: IPv4 identifier. :param id_equip: Equipment identifier. Integer value and greater than zero. :param id_net: Network identifier. Integer value and greater than zero. :return: None :raise InvalidParameterError: IPv4, Equipment or Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_ip): raise InvalidParameterError( u'Ip identifier is invalid or was not informed.') if not is_valid_int_param(id_net): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') if not is_valid_int_param(id_equip): raise InvalidParameterError( u'Equipment identifier is invalid or was not informed.') ip_map = dict() ip_map['id_ip'] = id_ip ip_map['id_net'] = id_net ip_map['id_equip'] = id_equip url = "ipv4/assoc/" code, xml = self.submit({'ip_map': ip_map}, 'POST', url) return self.response(code, xml)
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Associate an IP4 with equipment. :param id_ip: IPv4 identifier. :param id_equip: Equipment identifier. Integer value and greater than zero. :param id_net: Network identifier. Integer value and greater than zero. :return: None :raise InvalidParameterError: IPv4, Equipment or Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "Associate", "an", "IP4", "with", "equipment", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L824-L860
globocom/GloboNetworkAPI-client-python
networkapiclient/Ip.py
Ip.assoc_ipv6
def assoc_ipv6(self, id_ip, id_equip, id_net): """ Associate an IP6 with equipment. :param id_ip: IPv6 identifier. :param id_equip: Equipment identifier. Integer value and greater than zero. :param id_net: Network identifier. Integer value and greater than zero. :return: None :raise InvalidParameterError: IPv6, Equipment or Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_ip): raise InvalidParameterError( u'Ipv6 identifier is invalid or was not informed.') if not is_valid_int_param(id_net): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') if not is_valid_int_param(id_equip): raise InvalidParameterError( u'Equipment identifier is invalid or was not informed.') ip_map = dict() ip_map['id_ip'] = id_ip ip_map['id_net'] = id_net ip_map['id_equip'] = id_equip url = "ipv6/assoc/" code, xml = self.submit({'ip_map': ip_map}, 'POST', url) return self.response(code, xml)
python
def assoc_ipv6(self, id_ip, id_equip, id_net): """ Associate an IP6 with equipment. :param id_ip: IPv6 identifier. :param id_equip: Equipment identifier. Integer value and greater than zero. :param id_net: Network identifier. Integer value and greater than zero. :return: None :raise InvalidParameterError: IPv6, Equipment or Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_ip): raise InvalidParameterError( u'Ipv6 identifier is invalid or was not informed.') if not is_valid_int_param(id_net): raise InvalidParameterError( u'Network identifier is invalid or was not informed.') if not is_valid_int_param(id_equip): raise InvalidParameterError( u'Equipment identifier is invalid or was not informed.') ip_map = dict() ip_map['id_ip'] = id_ip ip_map['id_net'] = id_net ip_map['id_equip'] = id_equip url = "ipv6/assoc/" code, xml = self.submit({'ip_map': ip_map}, 'POST', url) return self.response(code, xml)
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Associate an IP6 with equipment. :param id_ip: IPv6 identifier. :param id_equip: Equipment identifier. Integer value and greater than zero. :param id_net: Network identifier. Integer value and greater than zero. :return: None :raise InvalidParameterError: IPv6, Equipment or Network identifier is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "Associate", "an", "IP6", "with", "equipment", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/Ip.py#L862-L898
globocom/GloboNetworkAPI-client-python
networkapiclient/TipoRede.py
TipoRede.listar
def listar(self): """List all network types. :return: Following dictionary: :: {'net_type': [{'id': < id_tipo_rede >, 'name': < nome_tipo_rede >}, ... other network types ...]} :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ code, xml = self.submit(None, 'GET', 'net_type/') key = 'net_type' return get_list_map(self.response(code, xml, [key]), key)
python
def listar(self): """List all network types. :return: Following dictionary: :: {'net_type': [{'id': < id_tipo_rede >, 'name': < nome_tipo_rede >}, ... other network types ...]} :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ code, xml = self.submit(None, 'GET', 'net_type/') key = 'net_type' return get_list_map(self.response(code, xml, [key]), key)
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List all network types. :return: Following dictionary: :: {'net_type': [{'id': < id_tipo_rede >, 'name': < nome_tipo_rede >}, ... other network types ...]} :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "List", "all", "network", "types", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/TipoRede.py#L38-L55
globocom/GloboNetworkAPI-client-python
networkapiclient/TipoRede.py
TipoRede.inserir
def inserir(self, name): """Insert new network type and return its identifier. :param name: Network type name. :return: Following dictionary: {'net_type': {'id': < id >}} :raise InvalidParameterError: Network type is none or invalid. :raise NomeTipoRedeDuplicadoError: A network type with this name already exists. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ net_type_map = dict() net_type_map['name'] = name code, xml = self.submit( {'net_type': net_type_map}, 'POST', 'net_type/') return self.response(code, xml)
python
def inserir(self, name): """Insert new network type and return its identifier. :param name: Network type name. :return: Following dictionary: {'net_type': {'id': < id >}} :raise InvalidParameterError: Network type is none or invalid. :raise NomeTipoRedeDuplicadoError: A network type with this name already exists. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ net_type_map = dict() net_type_map['name'] = name code, xml = self.submit( {'net_type': net_type_map}, 'POST', 'net_type/') return self.response(code, xml)
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Insert new network type and return its identifier. :param name: Network type name. :return: Following dictionary: {'net_type': {'id': < id >}} :raise InvalidParameterError: Network type is none or invalid. :raise NomeTipoRedeDuplicadoError: A network type with this name already exists. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "Insert", "new", "network", "type", "and", "return", "its", "identifier", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/TipoRede.py#L57-L76
globocom/GloboNetworkAPI-client-python
networkapiclient/TipoRede.py
TipoRede.alterar
def alterar(self, id_net_type, name): """Edit network type by its identifier. :param id_net_type: Network type identifier. :param name: Network type name. :return: None :raise InvalidParameterError: Network type identifier and/or name is(are) none or invalid. :raise TipoRedeNaoExisteError: Network type does not exist. :raise NomeTipoRedeDuplicadoError: Network type name already exists. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_net_type): raise InvalidParameterError( u'Network type is invalid or was not informed.') url = 'net_type/' + str(id_net_type) + '/' net_type_map = dict() net_type_map['name'] = name code, xml = self.submit({'net_type': net_type_map}, 'PUT', url) return self.response(code, xml)
python
def alterar(self, id_net_type, name): """Edit network type by its identifier. :param id_net_type: Network type identifier. :param name: Network type name. :return: None :raise InvalidParameterError: Network type identifier and/or name is(are) none or invalid. :raise TipoRedeNaoExisteError: Network type does not exist. :raise NomeTipoRedeDuplicadoError: Network type name already exists. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_net_type): raise InvalidParameterError( u'Network type is invalid or was not informed.') url = 'net_type/' + str(id_net_type) + '/' net_type_map = dict() net_type_map['name'] = name code, xml = self.submit({'net_type': net_type_map}, 'PUT', url) return self.response(code, xml)
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Edit network type by its identifier. :param id_net_type: Network type identifier. :param name: Network type name. :return: None :raise InvalidParameterError: Network type identifier and/or name is(are) none or invalid. :raise TipoRedeNaoExisteError: Network type does not exist. :raise NomeTipoRedeDuplicadoError: Network type name already exists. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "Edit", "network", "type", "by", "its", "identifier", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/TipoRede.py#L78-L104
globocom/GloboNetworkAPI-client-python
networkapiclient/TipoRede.py
TipoRede.remover
def remover(self, id_net_type): """Remove network type by its identifier. :param id_net_type: Network type identifier. :return: None :raise TipoRedeNaoExisteError: Network type does not exist. :raise TipoRedeError: Network type is associated with network. :raise InvalidParameterError: Network type is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_net_type): raise InvalidParameterError( u'Network type is invalid or was not informed.') url = 'net_type/' + str(id_net_type) + '/' code, xml = self.submit(None, 'DELETE', url) return self.response(code, xml)
python
def remover(self, id_net_type): """Remove network type by its identifier. :param id_net_type: Network type identifier. :return: None :raise TipoRedeNaoExisteError: Network type does not exist. :raise TipoRedeError: Network type is associated with network. :raise InvalidParameterError: Network type is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response. """ if not is_valid_int_param(id_net_type): raise InvalidParameterError( u'Network type is invalid or was not informed.') url = 'net_type/' + str(id_net_type) + '/' code, xml = self.submit(None, 'DELETE', url) return self.response(code, xml)
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Remove network type by its identifier. :param id_net_type: Network type identifier. :return: None :raise TipoRedeNaoExisteError: Network type does not exist. :raise TipoRedeError: Network type is associated with network. :raise InvalidParameterError: Network type is none or invalid. :raise DataBaseError: Networkapi failed to access the database. :raise XMLError: Networkapi failed to generate the XML response.
[ "Remove", "network", "type", "by", "its", "identifier", "." ]
train
https://github.com/globocom/GloboNetworkAPI-client-python/blob/cf34f913da48d9abbf750114f5d2ac4b2dde137d/networkapiclient/TipoRede.py#L106-L127
thautwarm/RBNF
rbnf/cli.py
cc
def cc(filename: 'input source file', output: 'output file name. default to be replacing input file\'s suffix with ".py"' = None, name: 'name of language' = 'unname'): """ rbnf source code compiler. """ lang = Language(name) with Path(filename).open('r') as fr: build_language(fr.read(), lang, filename) if not output: base, _ = os.path.splitext(filename) output = base + '.py' lang.dump(output)
python
def cc(filename: 'input source file', output: 'output file name. default to be replacing input file\'s suffix with ".py"' = None, name: 'name of language' = 'unname'): """ rbnf source code compiler. """ lang = Language(name) with Path(filename).open('r') as fr: build_language(fr.read(), lang, filename) if not output: base, _ = os.path.splitext(filename) output = base + '.py' lang.dump(output)
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rbnf source code compiler.
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/cli.py#L11-L28
thautwarm/RBNF
rbnf/cli.py
run
def run(filename: 'python file generated by `rbnf` command, or rbnf sour file', opt: 'optimize switch' = False): """ You can apply immediate tests on your parser. P.S: use `--opt` option takes longer starting time. """ from rbnf.easy import build_parser import importlib.util import traceback full_path = Path(filename) base, ext = os.path.splitext(str(full_path)) full_path_str = str(full_path) if not ext: if full_path.into('.py').exists(): full_path_str = base + '.py' elif Path(base).into('.rbnf'): full_path_str = base + '.rbnf' if full_path_str[-3:].lower() != '.py': with Path(full_path_str).open('r') as fr: ze_exp = ze.compile(fr.read(), filename=full_path_str) lang = ze_exp.lang else: spec = importlib.util.spec_from_file_location("runbnf", full_path_str) mod = importlib.util.module_from_spec(spec) spec.loader.exec_module(mod) try: lang = next(each for each in mod.__dict__.values() if isinstance(each, Language)) except StopIteration: raise NameError("Found no language in {}".format(full_path_str)) parse = build_parser(lang, opt=bool(opt)) namespace = {} print(Purple('type `:i` to switch between python mode and parsing mode.')) print(Purple('The last result of parsing is stored as symbol `res`.')) while True: inp = input('runbnf> ') if not inp.strip(): continue elif inp.strip() == 'exit': break if inp.strip() == ':i': while True: inp = input('python> ') if inp.strip() == ':i': break try: try: res = eval(inp, namespace) if res is not None: print(res) namespace['_'] = res except SyntaxError: exec(inp, namespace) except Exception: traceback.print_exc() else: res = namespace['res'] = parse(inp) print( LightBlue( 'parsed result = res: ResultDescription{result, tokens, state}' )) print(res.result)
python
def run(filename: 'python file generated by `rbnf` command, or rbnf sour file', opt: 'optimize switch' = False): """ You can apply immediate tests on your parser. P.S: use `--opt` option takes longer starting time. """ from rbnf.easy import build_parser import importlib.util import traceback full_path = Path(filename) base, ext = os.path.splitext(str(full_path)) full_path_str = str(full_path) if not ext: if full_path.into('.py').exists(): full_path_str = base + '.py' elif Path(base).into('.rbnf'): full_path_str = base + '.rbnf' if full_path_str[-3:].lower() != '.py': with Path(full_path_str).open('r') as fr: ze_exp = ze.compile(fr.read(), filename=full_path_str) lang = ze_exp.lang else: spec = importlib.util.spec_from_file_location("runbnf", full_path_str) mod = importlib.util.module_from_spec(spec) spec.loader.exec_module(mod) try: lang = next(each for each in mod.__dict__.values() if isinstance(each, Language)) except StopIteration: raise NameError("Found no language in {}".format(full_path_str)) parse = build_parser(lang, opt=bool(opt)) namespace = {} print(Purple('type `:i` to switch between python mode and parsing mode.')) print(Purple('The last result of parsing is stored as symbol `res`.')) while True: inp = input('runbnf> ') if not inp.strip(): continue elif inp.strip() == 'exit': break if inp.strip() == ':i': while True: inp = input('python> ') if inp.strip() == ':i': break try: try: res = eval(inp, namespace) if res is not None: print(res) namespace['_'] = res except SyntaxError: exec(inp, namespace) except Exception: traceback.print_exc() else: res = namespace['res'] = parse(inp) print( LightBlue( 'parsed result = res: ResultDescription{result, tokens, state}' )) print(res.result)
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You can apply immediate tests on your parser. P.S: use `--opt` option takes longer starting time.
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/cli.py#L32-L103
thautwarm/RBNF
rbnf/auto_lexer/rbnf_lexer.py
rbnf_lexing
def rbnf_lexing(text: str): """Read loudly for documentation.""" cast_map: const = _cast_map lexer_table: const = _lexer_table keyword: const = _keyword drop_table: const = _DropTable end: const = _END unknown: const = _UNKNOWN text_length = len(text) colno = 0 lineno = 0 position = 0 cast_const = ConstStrPool.cast_to_const while True: if text_length <= position: break for case_name, text_match_case in lexer_table: matched_text = text_match_case(text, position) if not matched_text: continue case_mem_addr = id(case_name) # memory address of case_name if case_mem_addr not in drop_table: if matched_text in cast_map: yield Tokenizer(keyword, cast_const(matched_text), lineno, colno) else: yield Tokenizer(cast_const(case_name), matched_text, lineno, colno) n = len(matched_text) line_inc = matched_text.count('\n') if line_inc: latest_newline_idx = matched_text.rindex('\n') colno = n - latest_newline_idx lineno += line_inc if case_name is _Space and matched_text[-1] == '\n': yield Tokenizer(end, '', lineno, colno) else: colno += n position += n break else: char = text[position] yield Tokenizer(unknown, char, lineno, colno) position += 1 if char == '\n': lineno += 1 colno = 0 else: colno += 1
python
def rbnf_lexing(text: str): """Read loudly for documentation.""" cast_map: const = _cast_map lexer_table: const = _lexer_table keyword: const = _keyword drop_table: const = _DropTable end: const = _END unknown: const = _UNKNOWN text_length = len(text) colno = 0 lineno = 0 position = 0 cast_const = ConstStrPool.cast_to_const while True: if text_length <= position: break for case_name, text_match_case in lexer_table: matched_text = text_match_case(text, position) if not matched_text: continue case_mem_addr = id(case_name) # memory address of case_name if case_mem_addr not in drop_table: if matched_text in cast_map: yield Tokenizer(keyword, cast_const(matched_text), lineno, colno) else: yield Tokenizer(cast_const(case_name), matched_text, lineno, colno) n = len(matched_text) line_inc = matched_text.count('\n') if line_inc: latest_newline_idx = matched_text.rindex('\n') colno = n - latest_newline_idx lineno += line_inc if case_name is _Space and matched_text[-1] == '\n': yield Tokenizer(end, '', lineno, colno) else: colno += n position += n break else: char = text[position] yield Tokenizer(unknown, char, lineno, colno) position += 1 if char == '\n': lineno += 1 colno = 0 else: colno += 1
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Read loudly for documentation.
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/auto_lexer/rbnf_lexer.py#L30-L96
thautwarm/RBNF
rbnf/std/common.py
recover_codes
def recover_codes(tokens: Iterator[Tokenizer]) -> str: """ from a series of tokenizers to code string. (preserve the indentation) """ tokens = iter(tokens) s = [] try: head = next(tokens) except StopIteration: return s append = s.append lineno = head.lineno start_indent = colno = head.colno append(head.value) colno += len(s[-1]) for each in tokens: n = each.lineno - lineno if n: append('\n' * n) lineno = each.lineno colno = each.colno if colno - start_indent > 0: append(' ' * colno) else: c = each.colno - colno if c: colno = each.colno if c > 0: append(' ' * c) append(each.value) colno += len(s[-1]) return s
python
def recover_codes(tokens: Iterator[Tokenizer]) -> str: """ from a series of tokenizers to code string. (preserve the indentation) """ tokens = iter(tokens) s = [] try: head = next(tokens) except StopIteration: return s append = s.append lineno = head.lineno start_indent = colno = head.colno append(head.value) colno += len(s[-1]) for each in tokens: n = each.lineno - lineno if n: append('\n' * n) lineno = each.lineno colno = each.colno if colno - start_indent > 0: append(' ' * colno) else: c = each.colno - colno if c: colno = each.colno if c > 0: append(' ' * c) append(each.value) colno += len(s[-1]) return s
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from a series of tokenizers to code string. (preserve the indentation)
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/std/common.py#L14-L60
thautwarm/RBNF
rbnf/auto_lexer/__init__.py
str_lexer
def str_lexer(mode): """ generate token strings' cache """ cast_to_const = ConstStrPool.cast_to_const def f_raw(inp_str, pos): return cast_to_const(mode) if inp_str.startswith(mode, pos) else None def f_collection(inp_str, pos): for each in mode: if inp_str.startswith(each, pos): return cast_to_const(each) return None if isinstance(mode, str): return f_raw if len(mode) is 1: mode = mode[0] return f_raw return f_collection
python
def str_lexer(mode): """ generate token strings' cache """ cast_to_const = ConstStrPool.cast_to_const def f_raw(inp_str, pos): return cast_to_const(mode) if inp_str.startswith(mode, pos) else None def f_collection(inp_str, pos): for each in mode: if inp_str.startswith(each, pos): return cast_to_const(each) return None if isinstance(mode, str): return f_raw if len(mode) is 1: mode = mode[0] return f_raw return f_collection
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generate token strings' cache
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/auto_lexer/__init__.py#L221-L243
thautwarm/RBNF
rbnf/auto_lexer/__init__.py
regex_lexer
def regex_lexer(regex_pat): """ generate token names' cache """ if isinstance(regex_pat, str): regex_pat = re.compile(regex_pat) def f(inp_str, pos): m = regex_pat.match(inp_str, pos) return m.group() if m else None elif hasattr(regex_pat, 'match'): def f(inp_str, pos): m = regex_pat.match(inp_str, pos) return m.group() if m else None else: regex_pats = tuple(re.compile(e) for e in regex_pat) def f(inp_str, pos): for each_pat in regex_pats: m = each_pat.match(inp_str, pos) if m: return m.group() return f
python
def regex_lexer(regex_pat): """ generate token names' cache """ if isinstance(regex_pat, str): regex_pat = re.compile(regex_pat) def f(inp_str, pos): m = regex_pat.match(inp_str, pos) return m.group() if m else None elif hasattr(regex_pat, 'match'): def f(inp_str, pos): m = regex_pat.match(inp_str, pos) return m.group() if m else None else: regex_pats = tuple(re.compile(e) for e in regex_pat) def f(inp_str, pos): for each_pat in regex_pats: m = each_pat.match(inp_str, pos) if m: return m.group() return f
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generate token names' cache
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/auto_lexer/__init__.py#L246-L270
thautwarm/RBNF
rbnf/py_tools/unparse.py
Unparser.dispatch
def dispatch(self, tree): "Dispatcher function, dispatching tree type T to method _T." if isinstance(tree, list): for t in tree: self.dispatch(t) return meth = getattr(self, "_" + tree.__class__.__name__) meth(tree)
python
def dispatch(self, tree): "Dispatcher function, dispatching tree type T to method _T." if isinstance(tree, list): for t in tree: self.dispatch(t) return meth = getattr(self, "_" + tree.__class__.__name__) meth(tree)
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Dispatcher function, dispatching tree type T to method _T.
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/py_tools/unparse.py#L101-L108
thautwarm/RBNF
rbnf/edsl/core.py
process
def process(fn, bound_names): """ process automatic context variable capturing. return the transformed function and its ast. """ if isinstance(fn, _AutoContext): fn = fn.fn # noinspection PyArgumentList,PyArgumentList if isinstance(fn, _FnCodeStr): if bound_names: assign_code_str = '{syms} = map(state.ctx.get, {names})'.format( syms=', '.join(bound_names) + ',', names=repr(bound_names)) else: assign_code_str = '' code = "def {0}({1}):\n{2}".format( fn.fn_name, ", ".join(fn.fn_args), textwrap.indent(assign_code_str + '\n' + fn.code, " ")) module_ast = ast.parse(code, fn.filename) bound_name_line_inc = int(bool(bound_names)) + 1 module_ast: ast.Module = ast.increment_lineno( module_ast, fn.lineno - bound_name_line_inc) fn_ast = module_ast.body[0] if isinstance(fn_ast.body[-1], ast.Expr): # auto addition of tail expr return # in rbnf you don't need to write return if the last statement in the end is an expression. it: ast.Expr = fn_ast.body[-1] fn_ast.body[-1] = ast.Return( lineno=it.lineno, col_offset=it.col_offset, value=it.value) filename = fn.filename name = fn.fn_name code_object = compile(module_ast, filename, "exec") local = {} # TODO: using types.MethodType here to create the function object leads to various problems. # Actually I don't really known why util now. exec(code_object, fn.namespace, local) ret = local[name] else: if not bound_names: return fn, get_ast(fn) code = fn.__code__ assigns = ast.parse("ctx = state.ctx\n" + "\n".join( "{0} = ctx.get({0!r})".format(name) for name in bound_names)) module_ast = get_ast(fn) fn_ast: ast.FunctionDef = module_ast.body[0] fn_ast.body = assigns.body + fn_ast.body module_ast = ast.Module([fn_ast]) filename = code.co_filename name = code.co_name __defaults__ = fn.__defaults__ __closure__ = fn.__closure__ __globals__ = fn.__globals__ code_object = compile(module_ast, filename, "exec") code_object = next( each for each in code_object.co_consts if isinstance(each, types.CodeType) and each.co_name == name) # noinspection PyArgumentList,PyUnboundLocalVariable ret = types.FunctionType(code_object, __globals__, name, __defaults__, __closure__) return ret, module_ast
python
def process(fn, bound_names): """ process automatic context variable capturing. return the transformed function and its ast. """ if isinstance(fn, _AutoContext): fn = fn.fn # noinspection PyArgumentList,PyArgumentList if isinstance(fn, _FnCodeStr): if bound_names: assign_code_str = '{syms} = map(state.ctx.get, {names})'.format( syms=', '.join(bound_names) + ',', names=repr(bound_names)) else: assign_code_str = '' code = "def {0}({1}):\n{2}".format( fn.fn_name, ", ".join(fn.fn_args), textwrap.indent(assign_code_str + '\n' + fn.code, " ")) module_ast = ast.parse(code, fn.filename) bound_name_line_inc = int(bool(bound_names)) + 1 module_ast: ast.Module = ast.increment_lineno( module_ast, fn.lineno - bound_name_line_inc) fn_ast = module_ast.body[0] if isinstance(fn_ast.body[-1], ast.Expr): # auto addition of tail expr return # in rbnf you don't need to write return if the last statement in the end is an expression. it: ast.Expr = fn_ast.body[-1] fn_ast.body[-1] = ast.Return( lineno=it.lineno, col_offset=it.col_offset, value=it.value) filename = fn.filename name = fn.fn_name code_object = compile(module_ast, filename, "exec") local = {} # TODO: using types.MethodType here to create the function object leads to various problems. # Actually I don't really known why util now. exec(code_object, fn.namespace, local) ret = local[name] else: if not bound_names: return fn, get_ast(fn) code = fn.__code__ assigns = ast.parse("ctx = state.ctx\n" + "\n".join( "{0} = ctx.get({0!r})".format(name) for name in bound_names)) module_ast = get_ast(fn) fn_ast: ast.FunctionDef = module_ast.body[0] fn_ast.body = assigns.body + fn_ast.body module_ast = ast.Module([fn_ast]) filename = code.co_filename name = code.co_name __defaults__ = fn.__defaults__ __closure__ = fn.__closure__ __globals__ = fn.__globals__ code_object = compile(module_ast, filename, "exec") code_object = next( each for each in code_object.co_consts if isinstance(each, types.CodeType) and each.co_name == name) # noinspection PyArgumentList,PyUnboundLocalVariable ret = types.FunctionType(code_object, __globals__, name, __defaults__, __closure__) return ret, module_ast
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process automatic context variable capturing. return the transformed function and its ast.
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/edsl/core.py#L107-L184
thautwarm/RBNF
rbnf/edsl/core.py
Language.ignore
def ignore(self, *ignore_lst: str): """ ignore a set of tokens with specific names """ def stream(): for each in ignore_lst: each = ConstStrPool.cast_to_const(each) yield id(each), each self.ignore_lst.update(stream())
python
def ignore(self, *ignore_lst: str): """ ignore a set of tokens with specific names """ def stream(): for each in ignore_lst: each = ConstStrPool.cast_to_const(each) yield id(each), each self.ignore_lst.update(stream())
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ignore a set of tokens with specific names
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/edsl/core.py#L324-L334
thautwarm/RBNF
rbnf/bootstrap/rbnf.py
build_language
def build_language(source_code: str, lang: Language, filename: str): """ lang: language object represents your language. """ state = MetaState(rbnf.implementation, requires=_Wild(), filename=filename) state.data = lang _build_language(source_code, state) lang.build()
python
def build_language(source_code: str, lang: Language, filename: str): """ lang: language object represents your language. """ state = MetaState(rbnf.implementation, requires=_Wild(), filename=filename) state.data = lang _build_language(source_code, state) lang.build()
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lang: language object represents your language.
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train
https://github.com/thautwarm/RBNF/blob/cceec88c90f7ec95c160cfda01bfc532610985e0/rbnf/bootstrap/rbnf.py#L536-L543
yunojuno-archive/django-inbound-email
inbound_email/backends/sendgrid.py
_decode_POST_value
def _decode_POST_value(request, field_name, default=None): """Helper to decode a request field into unicode based on charsets encoding. Args: request: the HttpRequest object. field_name: the field expected in the request.POST Kwargs: default: if passed in then field is optional and default is used if not found; if None, then assume field exists, which will raise an error if it does not. Returns: the contents of the string encoded using the related charset from the requests.POST['charsets'] dictionary (or 'utf-8' if none specified). """ if default is None: value = request.POST[field_name] else: value = request.POST.get(field_name, default) # it's inefficient to load this each time it gets called, but we're # not anticipating incoming email being a performance bottleneck right now! charsets = json.loads(request.POST.get('charsets', "{}")) charset = charsets.get(field_name, 'utf-8') if charset.lower() != 'utf-8': logger.debug("Incoming email field '%s' has %s encoding.", field_name, charset) return smart_text(value, encoding=charset)
python
def _decode_POST_value(request, field_name, default=None): """Helper to decode a request field into unicode based on charsets encoding. Args: request: the HttpRequest object. field_name: the field expected in the request.POST Kwargs: default: if passed in then field is optional and default is used if not found; if None, then assume field exists, which will raise an error if it does not. Returns: the contents of the string encoded using the related charset from the requests.POST['charsets'] dictionary (or 'utf-8' if none specified). """ if default is None: value = request.POST[field_name] else: value = request.POST.get(field_name, default) # it's inefficient to load this each time it gets called, but we're # not anticipating incoming email being a performance bottleneck right now! charsets = json.loads(request.POST.get('charsets', "{}")) charset = charsets.get(field_name, 'utf-8') if charset.lower() != 'utf-8': logger.debug("Incoming email field '%s' has %s encoding.", field_name, charset) return smart_text(value, encoding=charset)
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/sendgrid.py#L17-L45
yunojuno-archive/django-inbound-email
inbound_email/backends/sendgrid.py
SendGridRequestParser._get_addresses
def _get_addresses(self, address_data, retain_name=False): """ Takes RFC-compliant email addresses in both terse (email only) and verbose (name + email) forms and returns a list of email address strings (TODO: breaking change that returns a tuple of (name, email) per string) """ if retain_name: raise NotImplementedError( "Not yet implemented, but will need client-code changes too" ) # We trust than an email address contains an "@" after # email.utils.getaddresses has done the hard work. If we wanted # to we could use a regex to check for greater email validity # NB: getaddresses expects a list, so ensure we feed it appropriately if isinstance(address_data, str): if "[" not in address_data: # Definitely turn these into a list # NB: this is pretty assumptive, but still prob OK address_data = [address_data] output = [x[1] for x in getaddresses(address_data) if "@" in x[1]] return output
python
def _get_addresses(self, address_data, retain_name=False): """ Takes RFC-compliant email addresses in both terse (email only) and verbose (name + email) forms and returns a list of email address strings (TODO: breaking change that returns a tuple of (name, email) per string) """ if retain_name: raise NotImplementedError( "Not yet implemented, but will need client-code changes too" ) # We trust than an email address contains an "@" after # email.utils.getaddresses has done the hard work. If we wanted # to we could use a regex to check for greater email validity # NB: getaddresses expects a list, so ensure we feed it appropriately if isinstance(address_data, str): if "[" not in address_data: # Definitely turn these into a list # NB: this is pretty assumptive, but still prob OK address_data = [address_data] output = [x[1] for x in getaddresses(address_data) if "@" in x[1]] return output
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/sendgrid.py#L51-L76
yunojuno-archive/django-inbound-email
inbound_email/backends/sendgrid.py
SendGridRequestParser.parse
def parse(self, request): """Parse incoming request and return an email instance. Args: request: an HttpRequest object, containing the forwarded email, as per the SendGrid specification for inbound emails. Returns: an EmailMultiAlternatives instance, containing the parsed contents of the inbound email. TODO: non-UTF8 charset handling. TODO: handler headers. """ assert isinstance(request, HttpRequest), "Invalid request type: %s" % type(request) try: # from_email should never be a list (unless we change our API) from_email = self._get_addresses([_decode_POST_value(request, 'from')])[0] # ...but all these can and will be a list to_email = self._get_addresses([_decode_POST_value(request, 'to')]) cc = self._get_addresses([_decode_POST_value(request, 'cc', default='')]) bcc = self._get_addresses([_decode_POST_value(request, 'bcc', default='')]) subject = _decode_POST_value(request, 'subject') text = _decode_POST_value(request, 'text', default='') html = _decode_POST_value(request, 'html', default='') except IndexError as ex: raise RequestParseError( "Inbound request lacks a valid from address: %s." % request.get('from') ) except MultiValueDictKeyError as ex: raise RequestParseError("Inbound request is missing required value: %s." % ex) if "@" not in from_email: # Light sanity check for potential issues related to taking just the # first element of the 'from' address list raise RequestParseError("Could not get a valid from address out of: %s." % request) email = EmailMultiAlternatives( subject=subject, body=text, from_email=from_email, to=to_email, cc=cc, bcc=bcc, ) if html is not None and len(html) > 0: email.attach_alternative(html, "text/html") # TODO: this won't cope with big files - should really read in in chunks for n, f in list(request.FILES.items()): if f.size > self.max_file_size: logger.debug( "File attachment %s is too large to process (%sB)", f.name, f.size ) raise AttachmentTooLargeError( email=email, filename=f.name, size=f.size ) else: email.attach(f.name, f.read(), f.content_type) return email
python
def parse(self, request): """Parse incoming request and return an email instance. Args: request: an HttpRequest object, containing the forwarded email, as per the SendGrid specification for inbound emails. Returns: an EmailMultiAlternatives instance, containing the parsed contents of the inbound email. TODO: non-UTF8 charset handling. TODO: handler headers. """ assert isinstance(request, HttpRequest), "Invalid request type: %s" % type(request) try: # from_email should never be a list (unless we change our API) from_email = self._get_addresses([_decode_POST_value(request, 'from')])[0] # ...but all these can and will be a list to_email = self._get_addresses([_decode_POST_value(request, 'to')]) cc = self._get_addresses([_decode_POST_value(request, 'cc', default='')]) bcc = self._get_addresses([_decode_POST_value(request, 'bcc', default='')]) subject = _decode_POST_value(request, 'subject') text = _decode_POST_value(request, 'text', default='') html = _decode_POST_value(request, 'html', default='') except IndexError as ex: raise RequestParseError( "Inbound request lacks a valid from address: %s." % request.get('from') ) except MultiValueDictKeyError as ex: raise RequestParseError("Inbound request is missing required value: %s." % ex) if "@" not in from_email: # Light sanity check for potential issues related to taking just the # first element of the 'from' address list raise RequestParseError("Could not get a valid from address out of: %s." % request) email = EmailMultiAlternatives( subject=subject, body=text, from_email=from_email, to=to_email, cc=cc, bcc=bcc, ) if html is not None and len(html) > 0: email.attach_alternative(html, "text/html") # TODO: this won't cope with big files - should really read in in chunks for n, f in list(request.FILES.items()): if f.size > self.max_file_size: logger.debug( "File attachment %s is too large to process (%sB)", f.name, f.size ) raise AttachmentTooLargeError( email=email, filename=f.name, size=f.size ) else: email.attach(f.name, f.read(), f.content_type) return email
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/sendgrid.py#L78-L146
yunojuno-archive/django-inbound-email
inbound_email/backends/mailgun.py
MailgunRequestParser.parse
def parse(self, request): """Parse incoming request and return an email instance. Mailgun does a lot of the heavy lifting at their end - requests come in from them UTF-8 encoded, and with the message reply and signature stripped out for you. Args: request: an HttpRequest object, containing the forwarded email, as per the SendGrid specification for inbound emails. Returns: an EmailMultiAlternatives instance, containing the parsed contents of the inbound email. """ assert isinstance(request, HttpRequest), "Invalid request type: %s" % type(request) try: subject = request.POST.get('subject', '') text = "%s\n\n%s" % ( request.POST.get('stripped-text', ''), request.POST.get('stripped-signature', '') ) html = request.POST.get('stripped-html') from_email = request.POST.get('sender') to_email = request.POST.get('recipient').split(',') cc = request.POST.get('cc', '').split(',') bcc = request.POST.get('bcc', '').split(',') except MultiValueDictKeyError as ex: raise RequestParseError( "Inbound request is missing required value: %s." % ex ) except AttributeError as ex: raise RequestParseError( "Inbound request is missing required value: %s." % ex ) email = EmailMultiAlternatives( subject=subject, body=text, from_email=from_email, to=to_email, cc=cc, bcc=bcc, ) if html is not None and len(html) > 0: email.attach_alternative(html, "text/html") # TODO: this won't cope with big files - should really read in in chunks for n, f in list(request.FILES.items()): if f.size > self.max_file_size: logger.debug( "File attachment %s is too large to process (%sB)", f.name, f.size ) raise AttachmentTooLargeError( email=email, filename=f.name, size=f.size ) else: email.attach(n, f.read(), f.content_type) return email
python
def parse(self, request): """Parse incoming request and return an email instance. Mailgun does a lot of the heavy lifting at their end - requests come in from them UTF-8 encoded, and with the message reply and signature stripped out for you. Args: request: an HttpRequest object, containing the forwarded email, as per the SendGrid specification for inbound emails. Returns: an EmailMultiAlternatives instance, containing the parsed contents of the inbound email. """ assert isinstance(request, HttpRequest), "Invalid request type: %s" % type(request) try: subject = request.POST.get('subject', '') text = "%s\n\n%s" % ( request.POST.get('stripped-text', ''), request.POST.get('stripped-signature', '') ) html = request.POST.get('stripped-html') from_email = request.POST.get('sender') to_email = request.POST.get('recipient').split(',') cc = request.POST.get('cc', '').split(',') bcc = request.POST.get('bcc', '').split(',') except MultiValueDictKeyError as ex: raise RequestParseError( "Inbound request is missing required value: %s." % ex ) except AttributeError as ex: raise RequestParseError( "Inbound request is missing required value: %s." % ex ) email = EmailMultiAlternatives( subject=subject, body=text, from_email=from_email, to=to_email, cc=cc, bcc=bcc, ) if html is not None and len(html) > 0: email.attach_alternative(html, "text/html") # TODO: this won't cope with big files - should really read in in chunks for n, f in list(request.FILES.items()): if f.size > self.max_file_size: logger.debug( "File attachment %s is too large to process (%sB)", f.name, f.size ) raise AttachmentTooLargeError( email=email, filename=f.name, size=f.size ) else: email.attach(n, f.read(), f.content_type) return email
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/mailgun.py#L16-L82
yunojuno-archive/django-inbound-email
inbound_email/backends/mandrill.py
MandrillRequestParser._get_recipients
def _get_recipients(self, array): """Returns an iterator of objects in the form ["Name <[email protected]", ...] from the array [["[email protected]", "Name"]] """ for address, name in array: if not name: yield address else: yield "\"%s\" <%s>" % (name, address)
python
def _get_recipients(self, array): """Returns an iterator of objects in the form ["Name <[email protected]", ...] from the array [["[email protected]", "Name"]] """ for address, name in array: if not name: yield address else: yield "\"%s\" <%s>" % (name, address)
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Returns an iterator of objects in the form ["Name <[email protected]", ...] from the array [["[email protected]", "Name"]]
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/mandrill.py#L90-L99
yunojuno-archive/django-inbound-email
inbound_email/backends/mandrill.py
MandrillRequestParser.parse
def parse(self, request): """Parse incoming request and return an email instance. Args: request: an HttpRequest object, containing a list of forwarded emails, as per Mandrill specification for inbound emails. Returns: a list of EmailMultiAlternatives instances """ assert isinstance(request, HttpRequest), "Invalid request type: %s" % type(request) if settings.INBOUND_MANDRILL_AUTHENTICATION_KEY: _check_mandrill_signature( request=request, key=settings.INBOUND_MANDRILL_AUTHENTICATION_KEY, ) try: messages = json.loads(request.POST['mandrill_events']) except (ValueError, KeyError) as ex: raise RequestParseError("Request is not a valid json: %s" % ex) if not messages: logger.debug("No messages found in mandrill request: %s", request.body) return [] emails = [] for message in messages: if message.get('event') != 'inbound': logger.debug("Discarding non-inbound message") continue msg = message.get('msg') try: from_email = msg['from_email'] to = list(self._get_recipients(msg['to'])) cc = list(self._get_recipients(msg['cc'])) if 'cc' in msg else [] bcc = list(self._get_recipients(msg['bcc'])) if 'bcc' in msg else [] subject = msg.get('subject', "") attachments = msg.get('attachments', {}) attachments.update(msg.get('images', {})) text = msg.get('text', "") html = msg.get('html', "") except (KeyError, ValueError) as ex: raise RequestParseError( "Inbound request is missing or got an invalid value.: %s." % ex ) email = EmailMultiAlternatives( subject=subject, body=text, from_email=self._get_sender( from_email=from_email, from_name=msg.get('from_name'), ), to=to, cc=cc, bcc=bcc, ) if html is not None and len(html) > 0: email.attach_alternative(html, "text/html") email = self._process_attachments(email, attachments) emails.append(email) return emails
python
def parse(self, request): """Parse incoming request and return an email instance. Args: request: an HttpRequest object, containing a list of forwarded emails, as per Mandrill specification for inbound emails. Returns: a list of EmailMultiAlternatives instances """ assert isinstance(request, HttpRequest), "Invalid request type: %s" % type(request) if settings.INBOUND_MANDRILL_AUTHENTICATION_KEY: _check_mandrill_signature( request=request, key=settings.INBOUND_MANDRILL_AUTHENTICATION_KEY, ) try: messages = json.loads(request.POST['mandrill_events']) except (ValueError, KeyError) as ex: raise RequestParseError("Request is not a valid json: %s" % ex) if not messages: logger.debug("No messages found in mandrill request: %s", request.body) return [] emails = [] for message in messages: if message.get('event') != 'inbound': logger.debug("Discarding non-inbound message") continue msg = message.get('msg') try: from_email = msg['from_email'] to = list(self._get_recipients(msg['to'])) cc = list(self._get_recipients(msg['cc'])) if 'cc' in msg else [] bcc = list(self._get_recipients(msg['bcc'])) if 'bcc' in msg else [] subject = msg.get('subject', "") attachments = msg.get('attachments', {}) attachments.update(msg.get('images', {})) text = msg.get('text', "") html = msg.get('html', "") except (KeyError, ValueError) as ex: raise RequestParseError( "Inbound request is missing or got an invalid value.: %s." % ex ) email = EmailMultiAlternatives( subject=subject, body=text, from_email=self._get_sender( from_email=from_email, from_name=msg.get('from_name'), ), to=to, cc=cc, bcc=bcc, ) if html is not None and len(html) > 0: email.attach_alternative(html, "text/html") email = self._process_attachments(email, attachments) emails.append(email) return emails
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/mandrill.py#L107-L176
yunojuno-archive/django-inbound-email
inbound_email/views.py
_log_request
def _log_request(request): """Helper function to dump out debug info.""" logger.debug("Inbound email received") for k, v in list(request.POST.items()): logger.debug("- POST['%s']='%s'" % (k, v)) for n, f in list(request.FILES.items()): logger.debug("- FILES['%s']: '%s', %sB", n, f.content_type, f.size)
python
def _log_request(request): """Helper function to dump out debug info.""" logger.debug("Inbound email received") for k, v in list(request.POST.items()): logger.debug("- POST['%s']='%s'" % (k, v)) for n, f in list(request.FILES.items()): logger.debug("- FILES['%s']: '%s', %sB", n, f.content_type, f.size)
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Helper function to dump out debug info.
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/views.py#L23-L31
yunojuno-archive/django-inbound-email
inbound_email/views.py
receive_inbound_email
def receive_inbound_email(request): """Receives inbound email from SendGrid. This view receives the email from SendGrid, parses the contents, logs the message and the fires the inbound_email signal. """ # log the request.POST and request.FILES contents if log_requests is True: _log_request(request) # HEAD requests are used by some backends to validate the route if request.method == 'HEAD': return HttpResponse('OK') try: # clean up encodings and extract relevant fields from request.POST backend = get_backend_instance() emails = backend.parse(request) # backend.parse can return either an EmailMultiAlternatives # or a list of those if emails: if isinstance(emails, EmailMultiAlternatives): emails = [emails] for email in emails: # fire the signal for each email email_received.send(sender=backend.__class__, email=email, request=request) except AttachmentTooLargeError as ex: logger.exception(ex) email_received_unacceptable.send( sender=backend.__class__, email=ex.email, request=request, exception=ex ) except AuthenticationError as ex: logger.exception(ex) email_received_unacceptable.send( sender=backend.__class__, email=None, request=request, exception=ex ) except RequestParseError as ex: logger.exception(ex) if getattr(settings, 'INBOUND_EMAIL_RESPONSE_200', True): # NB even if we have a problem, always use HTTP_STATUS=200, as # otherwise the email service will continue polling us with the email. # This is the default behaviour. status_code = 200 else: status_code = 400 return HttpResponse( "Unable to parse inbound email: %s" % ex, status=status_code ) return HttpResponse("Successfully parsed inbound email.", status=200)
python
def receive_inbound_email(request): """Receives inbound email from SendGrid. This view receives the email from SendGrid, parses the contents, logs the message and the fires the inbound_email signal. """ # log the request.POST and request.FILES contents if log_requests is True: _log_request(request) # HEAD requests are used by some backends to validate the route if request.method == 'HEAD': return HttpResponse('OK') try: # clean up encodings and extract relevant fields from request.POST backend = get_backend_instance() emails = backend.parse(request) # backend.parse can return either an EmailMultiAlternatives # or a list of those if emails: if isinstance(emails, EmailMultiAlternatives): emails = [emails] for email in emails: # fire the signal for each email email_received.send(sender=backend.__class__, email=email, request=request) except AttachmentTooLargeError as ex: logger.exception(ex) email_received_unacceptable.send( sender=backend.__class__, email=ex.email, request=request, exception=ex ) except AuthenticationError as ex: logger.exception(ex) email_received_unacceptable.send( sender=backend.__class__, email=None, request=request, exception=ex ) except RequestParseError as ex: logger.exception(ex) if getattr(settings, 'INBOUND_EMAIL_RESPONSE_200', True): # NB even if we have a problem, always use HTTP_STATUS=200, as # otherwise the email service will continue polling us with the email. # This is the default behaviour. status_code = 200 else: status_code = 400 return HttpResponse( "Unable to parse inbound email: %s" % ex, status=status_code ) return HttpResponse("Successfully parsed inbound email.", status=200)
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Receives inbound email from SendGrid. This view receives the email from SendGrid, parses the contents, logs the message and the fires the inbound_email signal.
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train
https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/views.py#L36-L97
yunojuno-archive/django-inbound-email
inbound_email/backends/__init__.py
get_backend_class
def get_backend_class(): """Return reference to the configured backed class.""" # this will (intentionally) blow up if the setting does not exist assert hasattr(settings, 'INBOUND_EMAIL_PARSER') assert getattr(settings, 'INBOUND_EMAIL_PARSER') is not None package, klass = settings.INBOUND_EMAIL_PARSER.rsplit('.', 1) module = import_module(package) return getattr(module, klass)
python
def get_backend_class(): """Return reference to the configured backed class.""" # this will (intentionally) blow up if the setting does not exist assert hasattr(settings, 'INBOUND_EMAIL_PARSER') assert getattr(settings, 'INBOUND_EMAIL_PARSER') is not None package, klass = settings.INBOUND_EMAIL_PARSER.rsplit('.', 1) module = import_module(package) return getattr(module, klass)
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Return reference to the configured backed class.
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https://github.com/yunojuno-archive/django-inbound-email/blob/c0c1186fc2ced56b43d6b223e73cd5e8700dfc48/inbound_email/backends/__init__.py#L6-L14
rsheftel/raccoon
raccoon/sort_utils.py
sorted_exists
def sorted_exists(values, x): """ For list, values, returns the insert position for item x and whether the item already exists in the list. This allows one function call to return either the index to overwrite an existing value in the list, or the index to insert a new item in the list and keep the list in sorted order. :param values: list :param x: item :return: (exists, index) tuple """ i = bisect_left(values, x) j = bisect_right(values, x) exists = x in values[i:j] return exists, i
python
def sorted_exists(values, x): """ For list, values, returns the insert position for item x and whether the item already exists in the list. This allows one function call to return either the index to overwrite an existing value in the list, or the index to insert a new item in the list and keep the list in sorted order. :param values: list :param x: item :return: (exists, index) tuple """ i = bisect_left(values, x) j = bisect_right(values, x) exists = x in values[i:j] return exists, i
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For list, values, returns the insert position for item x and whether the item already exists in the list. This allows one function call to return either the index to overwrite an existing value in the list, or the index to insert a new item in the list and keep the list in sorted order. :param values: list :param x: item :return: (exists, index) tuple
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/sort_utils.py#L8-L21
rsheftel/raccoon
raccoon/sort_utils.py
sorted_index
def sorted_index(values, x): """ For list, values, returns the index location of element x. If x does not exist will raise an error. :param values: list :param x: item :return: integer index """ i = bisect_left(values, x) j = bisect_right(values, x) return values[i:j].index(x) + i
python
def sorted_index(values, x): """ For list, values, returns the index location of element x. If x does not exist will raise an error. :param values: list :param x: item :return: integer index """ i = bisect_left(values, x) j = bisect_right(values, x) return values[i:j].index(x) + i
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For list, values, returns the index location of element x. If x does not exist will raise an error. :param values: list :param x: item :return: integer index
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/sort_utils.py#L24-L34
rsheftel/raccoon
raccoon/sort_utils.py
sorted_list_indexes
def sorted_list_indexes(list_to_sort, key=None, reverse=False): """ Sorts a list but returns the order of the index values of the list for the sort and not the values themselves. For example is the list provided is ['b', 'a', 'c'] then the result will be [2, 1, 3] :param list_to_sort: list to sort :param key: if not None then a function of one argument that is used to extract a comparison key from each list element :param reverse: if True then the list elements are sorted as if each comparison were reversed. :return: list of sorted index values """ if key is not None: def key_func(i): return key(list_to_sort.__getitem__(i)) else: key_func = list_to_sort.__getitem__ return sorted(range(len(list_to_sort)), key=key_func, reverse=reverse)
python
def sorted_list_indexes(list_to_sort, key=None, reverse=False): """ Sorts a list but returns the order of the index values of the list for the sort and not the values themselves. For example is the list provided is ['b', 'a', 'c'] then the result will be [2, 1, 3] :param list_to_sort: list to sort :param key: if not None then a function of one argument that is used to extract a comparison key from each list element :param reverse: if True then the list elements are sorted as if each comparison were reversed. :return: list of sorted index values """ if key is not None: def key_func(i): return key(list_to_sort.__getitem__(i)) else: key_func = list_to_sort.__getitem__ return sorted(range(len(list_to_sort)), key=key_func, reverse=reverse)
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Sorts a list but returns the order of the index values of the list for the sort and not the values themselves. For example is the list provided is ['b', 'a', 'c'] then the result will be [2, 1, 3] :param list_to_sort: list to sort :param key: if not None then a function of one argument that is used to extract a comparison key from each list element :param reverse: if True then the list elements are sorted as if each comparison were reversed. :return: list of sorted index values
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/sort_utils.py#L37-L53
vmlaker/mpipe
doc/create.py
runDia
def runDia(diagram): """Generate the diagrams using Dia.""" ifname = '{}.dia'.format(diagram) ofname = '{}.png'.format(diagram) cmd = 'dia -t png-libart -e {} {}'.format(ofname, ifname) print(' {}'.format(cmd)) subprocess.call(cmd, shell=True) return True
python
def runDia(diagram): """Generate the diagrams using Dia.""" ifname = '{}.dia'.format(diagram) ofname = '{}.png'.format(diagram) cmd = 'dia -t png-libart -e {} {}'.format(ofname, ifname) print(' {}'.format(cmd)) subprocess.call(cmd, shell=True) return True
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Generate the diagrams using Dia.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/doc/create.py#L37-L44
vmlaker/mpipe
src/OrderedWorker.py
OrderedWorker.init2
def init2( self, input_tube, # Read task from the input tube. output_tubes, # Send result on all the output tubes. num_workers, # Total number of workers in the stage. disable_result, # Whether to override any result with None. do_stop_task, # Whether to call doTask() on "stop" request. ): """Create *num_workers* worker objects with *input_tube* and an iterable of *output_tubes*. The worker reads a task from *input_tube* and writes the result to *output_tubes*.""" super(OrderedWorker, self).__init__() self._tube_task_input = input_tube self._tubes_result_output = output_tubes self._num_workers = num_workers # Serializes reading from input tube. self._lock_prev_input = None self._lock_next_input = None # Serializes writing to output tube. self._lock_prev_output = None self._lock_next_output = None self._disable_result = disable_result self._do_stop_task = do_stop_task
python
def init2( self, input_tube, # Read task from the input tube. output_tubes, # Send result on all the output tubes. num_workers, # Total number of workers in the stage. disable_result, # Whether to override any result with None. do_stop_task, # Whether to call doTask() on "stop" request. ): """Create *num_workers* worker objects with *input_tube* and an iterable of *output_tubes*. The worker reads a task from *input_tube* and writes the result to *output_tubes*.""" super(OrderedWorker, self).__init__() self._tube_task_input = input_tube self._tubes_result_output = output_tubes self._num_workers = num_workers # Serializes reading from input tube. self._lock_prev_input = None self._lock_next_input = None # Serializes writing to output tube. self._lock_prev_output = None self._lock_next_output = None self._disable_result = disable_result self._do_stop_task = do_stop_task
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Create *num_workers* worker objects with *input_tube* and an iterable of *output_tubes*. The worker reads a task from *input_tube* and writes the result to *output_tubes*.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/OrderedWorker.py#L19-L45
vmlaker/mpipe
src/OrderedWorker.py
OrderedWorker.assemble
def assemble( cls, args, input_tube, output_tubes, size, disable_result=False, do_stop_task=False, ): """Create, assemble and start workers. Workers are created of class *cls*, initialized with *args*, and given task/result communication channels *input_tube* and *output_tubes*. The number of workers created is according to *size* parameter. *do_stop_task* indicates whether doTask() will be called for "stop" request. """ # Create the workers. workers = [] for ii in range(size): worker = cls(**args) worker.init2( input_tube, output_tubes, size, disable_result, do_stop_task, ) workers.append(worker) # Connect the workers. for ii in range(size): worker_this = workers[ii] worker_prev = workers[ii-1] worker_prev._link( worker_this, next_is_first=(ii==0), # Designate 0th worker as the first. ) # Start the workers. for worker in workers: worker.start()
python
def assemble( cls, args, input_tube, output_tubes, size, disable_result=False, do_stop_task=False, ): """Create, assemble and start workers. Workers are created of class *cls*, initialized with *args*, and given task/result communication channels *input_tube* and *output_tubes*. The number of workers created is according to *size* parameter. *do_stop_task* indicates whether doTask() will be called for "stop" request. """ # Create the workers. workers = [] for ii in range(size): worker = cls(**args) worker.init2( input_tube, output_tubes, size, disable_result, do_stop_task, ) workers.append(worker) # Connect the workers. for ii in range(size): worker_this = workers[ii] worker_prev = workers[ii-1] worker_prev._link( worker_this, next_is_first=(ii==0), # Designate 0th worker as the first. ) # Start the workers. for worker in workers: worker.start()
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/OrderedWorker.py#L53-L93
vmlaker/mpipe
src/OrderedWorker.py
OrderedWorker._link
def _link(self, next_worker, next_is_first=False): """Link the worker to the given next worker object, connecting the two workers with communication tubes.""" lock = multiprocessing.Lock() next_worker._lock_prev_input = lock self._lock_next_input = lock lock.acquire() lock = multiprocessing.Lock() next_worker._lock_prev_output = lock self._lock_next_output = lock lock.acquire() # If the next worker is the first one, trigger it now. if next_is_first: self._lock_next_input.release() self._lock_next_output.release()
python
def _link(self, next_worker, next_is_first=False): """Link the worker to the given next worker object, connecting the two workers with communication tubes.""" lock = multiprocessing.Lock() next_worker._lock_prev_input = lock self._lock_next_input = lock lock.acquire() lock = multiprocessing.Lock() next_worker._lock_prev_output = lock self._lock_next_output = lock lock.acquire() # If the next worker is the first one, trigger it now. if next_is_first: self._lock_next_input.release() self._lock_next_output.release()
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Link the worker to the given next worker object, connecting the two workers with communication tubes.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/OrderedWorker.py#L95-L112
vmlaker/mpipe
src/OrderedWorker.py
OrderedWorker.putResult
def putResult(self, result): """Register the *result* by putting it on all the output tubes.""" self._lock_prev_output.acquire() for tube in self._tubes_result_output: tube.put((result, 0)) self._lock_next_output.release()
python
def putResult(self, result): """Register the *result* by putting it on all the output tubes.""" self._lock_prev_output.acquire() for tube in self._tubes_result_output: tube.put((result, 0)) self._lock_next_output.release()
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/OrderedWorker.py#L114-L119
vmlaker/mpipe
src/UnorderedWorker.py
UnorderedWorker.init2
def init2( self, input_tube, # Read task from the input tube. output_tubes, # Send result on all the output tubes. num_workers, # Total number of workers in the stage. disable_result, # Whether to override any result with None. do_stop_task, # Whether to call doTask() on "stop" request. ): """Create *num_workers* worker objects with *input_tube* and an iterable of *output_tubes*. The worker reads a task from *input_tube* and writes the result to *output_tubes*.""" super(UnorderedWorker, self).__init__() self._tube_task_input = input_tube self._tubes_result_output = output_tubes self._num_workers = num_workers self._disable_result = disable_result self._do_stop_task = do_stop_task
python
def init2( self, input_tube, # Read task from the input tube. output_tubes, # Send result on all the output tubes. num_workers, # Total number of workers in the stage. disable_result, # Whether to override any result with None. do_stop_task, # Whether to call doTask() on "stop" request. ): """Create *num_workers* worker objects with *input_tube* and an iterable of *output_tubes*. The worker reads a task from *input_tube* and writes the result to *output_tubes*.""" super(UnorderedWorker, self).__init__() self._tube_task_input = input_tube self._tubes_result_output = output_tubes self._num_workers = num_workers self._disable_result = disable_result self._do_stop_task = do_stop_task
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/UnorderedWorker.py#L17-L34
vmlaker/mpipe
src/UnorderedWorker.py
UnorderedWorker.assemble
def assemble( cls, args, input_tube, output_tubes, size, disable_result, do_stop_task, ): """Create, assemble and start workers. Workers are created of class *cls*, initialized with *args*, and given task/result communication channels *input_tube* and *output_tubes*. The number of workers created is according to *size* parameter. *do_stop_task* indicates whether doTask() will be called for "stop" request. """ # Create the workers. workers = [] for ii in range(size): worker = cls(**args) worker.init2( input_tube, output_tubes, size, disable_result, do_stop_task, ) workers.append(worker) # Start the workers. for worker in workers: worker.start()
python
def assemble( cls, args, input_tube, output_tubes, size, disable_result, do_stop_task, ): """Create, assemble and start workers. Workers are created of class *cls*, initialized with *args*, and given task/result communication channels *input_tube* and *output_tubes*. The number of workers created is according to *size* parameter. *do_stop_task* indicates whether doTask() will be called for "stop" request. """ # Create the workers. workers = [] for ii in range(size): worker = cls(**args) worker.init2( input_tube, output_tubes, size, disable_result, do_stop_task, ) workers.append(worker) # Start the workers. for worker in workers: worker.start()
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Create, assemble and start workers. Workers are created of class *cls*, initialized with *args*, and given task/result communication channels *input_tube* and *output_tubes*. The number of workers created is according to *size* parameter. *do_stop_task* indicates whether doTask() will be called for "stop" request.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/UnorderedWorker.py#L42-L73
rsheftel/raccoon
raccoon/series.py
SeriesBase.show
def show(self, index=True, **kwargs): """ Print the contents of the Series. This method uses the tabulate function from the tabulate package. Use the kwargs to pass along any arguments to the tabulate function. :param index: If True then include the indexes as a column in the output, if False ignore the index :param kwargs: Parameters to pass along to the tabulate function :return: output of the tabulate function """ print(self._make_table(index=index, **kwargs))
python
def show(self, index=True, **kwargs): """ Print the contents of the Series. This method uses the tabulate function from the tabulate package. Use the kwargs to pass along any arguments to the tabulate function. :param index: If True then include the indexes as a column in the output, if False ignore the index :param kwargs: Parameters to pass along to the tabulate function :return: output of the tabulate function """ print(self._make_table(index=index, **kwargs))
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Print the contents of the Series. This method uses the tabulate function from the tabulate package. Use the kwargs to pass along any arguments to the tabulate function. :param index: If True then include the indexes as a column in the output, if False ignore the index :param kwargs: Parameters to pass along to the tabulate function :return: output of the tabulate function
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L50-L59
rsheftel/raccoon
raccoon/series.py
SeriesBase.get
def get(self, indexes, as_list=False): """ Given indexes will return a sub-set of the Series. This method will direct to the specific methods based on what types are passed in for the indexes. The type of the return is determined by the types of the parameters. :param indexes: index value, list of index values, or a list of booleans. :param as_list: if True then return the values as a list, if False return a Series. :return: either Series, list, or single value. The return is a shallow copy """ if isinstance(indexes, (list, blist)): return self.get_rows(indexes, as_list) else: return self.get_cell(indexes)
python
def get(self, indexes, as_list=False): """ Given indexes will return a sub-set of the Series. This method will direct to the specific methods based on what types are passed in for the indexes. The type of the return is determined by the types of the parameters. :param indexes: index value, list of index values, or a list of booleans. :param as_list: if True then return the values as a list, if False return a Series. :return: either Series, list, or single value. The return is a shallow copy """ if isinstance(indexes, (list, blist)): return self.get_rows(indexes, as_list) else: return self.get_cell(indexes)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L97-L110
rsheftel/raccoon
raccoon/series.py
SeriesBase.get_cell
def get_cell(self, index): """ For a single index and return the value :param index: index value :return: value """ i = sorted_index(self._index, index) if self._sort else self._index.index(index) return self._data[i]
python
def get_cell(self, index): """ For a single index and return the value :param index: index value :return: value """ i = sorted_index(self._index, index) if self._sort else self._index.index(index) return self._data[i]
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For a single index and return the value :param index: index value :return: value
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L112-L120
rsheftel/raccoon
raccoon/series.py
SeriesBase.get_rows
def get_rows(self, indexes, as_list=False): """ For a list of indexes return the values of the indexes in that column. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param as_list: if True return a list, if False return Series :return: Series if as_list if False, a list if as_list is True """ if all([isinstance(i, bool) for i in indexes]): # boolean list if len(indexes) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if all(indexes): # the entire column data = self._data index = self._index else: data = list(compress(self._data, indexes)) index = list(compress(self._index, indexes)) else: # index values list locations = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] data = [self._data[i] for i in locations] index = [self._index[i] for i in locations] return data if as_list else Series(data=data, index=index, data_name=self._data_name, index_name=self._index_name, sort=self._sort)
python
def get_rows(self, indexes, as_list=False): """ For a list of indexes return the values of the indexes in that column. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param as_list: if True return a list, if False return Series :return: Series if as_list if False, a list if as_list is True """ if all([isinstance(i, bool) for i in indexes]): # boolean list if len(indexes) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if all(indexes): # the entire column data = self._data index = self._index else: data = list(compress(self._data, indexes)) index = list(compress(self._index, indexes)) else: # index values list locations = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] data = [self._data[i] for i in locations] index = [self._index[i] for i in locations] return data if as_list else Series(data=data, index=index, data_name=self._data_name, index_name=self._index_name, sort=self._sort)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L122-L145
rsheftel/raccoon
raccoon/series.py
SeriesBase.get_location
def get_location(self, location): """ For an index location return a dict of the index and value. This is optimized for speed because it does not need to lookup the index location with a search. Also can accept relative indexing from the end of the SEries in standard python notation [-3, -2, -1] :param location: index location in standard python form of positive or negative number :return: dictionary """ return {self.index_name: self._index[location], self.data_name: self._data[location]}
python
def get_location(self, location): """ For an index location return a dict of the index and value. This is optimized for speed because it does not need to lookup the index location with a search. Also can accept relative indexing from the end of the SEries in standard python notation [-3, -2, -1] :param location: index location in standard python form of positive or negative number :return: dictionary """ return {self.index_name: self._index[location], self.data_name: self._data[location]}
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For an index location return a dict of the index and value. This is optimized for speed because it does not need to lookup the index location with a search. Also can accept relative indexing from the end of the SEries in standard python notation [-3, -2, -1] :param location: index location in standard python form of positive or negative number :return: dictionary
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L147-L156
rsheftel/raccoon
raccoon/series.py
SeriesBase.get_locations
def get_locations(self, locations, as_list=False): """ For list of locations return a Series or list of the values. :param locations: list of index locations :param as_list: True to return a list of values :return: Series or list """ indexes = [self._index[x] for x in locations] return self.get(indexes, as_list)
python
def get_locations(self, locations, as_list=False): """ For list of locations return a Series or list of the values. :param locations: list of index locations :param as_list: True to return a list of values :return: Series or list """ indexes = [self._index[x] for x in locations] return self.get(indexes, as_list)
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For list of locations return a Series or list of the values. :param locations: list of index locations :param as_list: True to return a list of values :return: Series or list
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L158-L168
rsheftel/raccoon
raccoon/series.py
SeriesBase.get_slice
def get_slice(self, start_index=None, stop_index=None, as_list=False): """ For sorted Series will return either a Series or list of all of the rows where the index is greater than or equal to the start_index if provided and less than or equal to the stop_index if provided. If either the start or stop index is None then will include from the first or last element, similar to standard python slide of [:5] or [:5]. Both end points are considered inclusive. :param start_index: lowest index value to include, or None to start from the first row :param stop_index: highest index value to include, or None to end at the last row :param as_list: if True then return a list of the indexes and values :return: Series or tuple of (index list, values list) """ if not self._sort: raise RuntimeError('Can only use get_slice on sorted Series') start_location = bisect_left(self._index, start_index) if start_index is not None else None stop_location = bisect_right(self._index, stop_index) if stop_index is not None else None index = self._index[start_location:stop_location] data = self._data[start_location:stop_location] if as_list: return index, data else: return Series(data=data, index=index, data_name=self._data_name, index_name=self._index_name, sort=self._sort)
python
def get_slice(self, start_index=None, stop_index=None, as_list=False): """ For sorted Series will return either a Series or list of all of the rows where the index is greater than or equal to the start_index if provided and less than or equal to the stop_index if provided. If either the start or stop index is None then will include from the first or last element, similar to standard python slide of [:5] or [:5]. Both end points are considered inclusive. :param start_index: lowest index value to include, or None to start from the first row :param stop_index: highest index value to include, or None to end at the last row :param as_list: if True then return a list of the indexes and values :return: Series or tuple of (index list, values list) """ if not self._sort: raise RuntimeError('Can only use get_slice on sorted Series') start_location = bisect_left(self._index, start_index) if start_index is not None else None stop_location = bisect_right(self._index, stop_index) if stop_index is not None else None index = self._index[start_location:stop_location] data = self._data[start_location:stop_location] if as_list: return index, data else: return Series(data=data, index=index, data_name=self._data_name, index_name=self._index_name, sort=self._sort)
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For sorted Series will return either a Series or list of all of the rows where the index is greater than or equal to the start_index if provided and less than or equal to the stop_index if provided. If either the start or stop index is None then will include from the first or last element, similar to standard python slide of [:5] or [:5]. Both end points are considered inclusive. :param start_index: lowest index value to include, or None to start from the first row :param stop_index: highest index value to include, or None to end at the last row :param as_list: if True then return a list of the indexes and values :return: Series or tuple of (index list, values list)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L170-L195
rsheftel/raccoon
raccoon/series.py
SeriesBase.to_dict
def to_dict(self, index=True, ordered=False): """ Returns a dict where the keys are the data and index names and the values are list of the data and index. :param index: If True then include the index in the dict with the index_name as the key :param ordered: If True then return an OrderedDict() to preserve the order of the columns in the Series :return: dict or OrderedDict() """ result = OrderedDict() if ordered else dict() if index: result.update({self._index_name: self._index}) if ordered: data_dict = [(self._data_name, self._data)] else: data_dict = {self._data_name: self._data} result.update(data_dict) return result
python
def to_dict(self, index=True, ordered=False): """ Returns a dict where the keys are the data and index names and the values are list of the data and index. :param index: If True then include the index in the dict with the index_name as the key :param ordered: If True then return an OrderedDict() to preserve the order of the columns in the Series :return: dict or OrderedDict() """ result = OrderedDict() if ordered else dict() if index: result.update({self._index_name: self._index}) if ordered: data_dict = [(self._data_name, self._data)] else: data_dict = {self._data_name: self._data} result.update(data_dict) return result
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Returns a dict where the keys are the data and index names and the values are list of the data and index. :param index: If True then include the index in the dict with the index_name as the key :param ordered: If True then return an OrderedDict() to preserve the order of the columns in the Series :return: dict or OrderedDict()
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L235-L251
rsheftel/raccoon
raccoon/series.py
SeriesBase.head
def head(self, rows): """ Return a Series of the first N rows :param rows: number of rows :return: Series """ rows_bool = [True] * min(rows, len(self._index)) rows_bool.extend([False] * max(0, len(self._index) - rows)) return self.get(indexes=rows_bool)
python
def head(self, rows): """ Return a Series of the first N rows :param rows: number of rows :return: Series """ rows_bool = [True] * min(rows, len(self._index)) rows_bool.extend([False] * max(0, len(self._index) - rows)) return self.get(indexes=rows_bool)
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Return a Series of the first N rows :param rows: number of rows :return: Series
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L253-L262
rsheftel/raccoon
raccoon/series.py
SeriesBase.select_index
def select_index(self, compare, result='boolean'): """ Finds the elements in the index that match the compare parameter and returns either a list of the values that match, of a boolean list the length of the index with True to each index that matches. If the indexes are tuples then the compare is a tuple where None in any field of the tuple will be treated as "*" and match all values. :param compare: value to compare as a singleton or tuple :param result: 'boolean' = returns a list of booleans, 'value' = returns a list of index values that match :return: list of booleans or values """ if isinstance(compare, tuple): # this crazy list comprehension will match all the tuples in the list with None being an * wildcard booleans = [all([(compare[i] == w if compare[i] is not None else True) for i, w in enumerate(v)]) for x, v in enumerate(self._index)] else: booleans = [False] * len(self._index) if self._sort: booleans[sorted_index(self._index, compare)] = True else: booleans[self._index.index(compare)] = True if result == 'boolean': return booleans elif result == 'value': return list(compress(self._index, booleans)) else: raise ValueError('only valid values for result parameter are: boolean or value.')
python
def select_index(self, compare, result='boolean'): """ Finds the elements in the index that match the compare parameter and returns either a list of the values that match, of a boolean list the length of the index with True to each index that matches. If the indexes are tuples then the compare is a tuple where None in any field of the tuple will be treated as "*" and match all values. :param compare: value to compare as a singleton or tuple :param result: 'boolean' = returns a list of booleans, 'value' = returns a list of index values that match :return: list of booleans or values """ if isinstance(compare, tuple): # this crazy list comprehension will match all the tuples in the list with None being an * wildcard booleans = [all([(compare[i] == w if compare[i] is not None else True) for i, w in enumerate(v)]) for x, v in enumerate(self._index)] else: booleans = [False] * len(self._index) if self._sort: booleans[sorted_index(self._index, compare)] = True else: booleans[self._index.index(compare)] = True if result == 'boolean': return booleans elif result == 'value': return list(compress(self._index, booleans)) else: raise ValueError('only valid values for result parameter are: boolean or value.')
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L275-L301
rsheftel/raccoon
raccoon/series.py
SeriesBase.equality
def equality(self, indexes=None, value=None): """ Math helper method. Given a column and optional indexes will return a list of booleans on the equality of the value for that index in the DataFrame to the value parameter. :param indexes: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the DataFrame :param value: value to compare :return: list of booleans """ indexes = [True] * len(self._index) if indexes is None else indexes compare_list = self.get_rows(indexes, as_list=True) return [x == value for x in compare_list]
python
def equality(self, indexes=None, value=None): """ Math helper method. Given a column and optional indexes will return a list of booleans on the equality of the value for that index in the DataFrame to the value parameter. :param indexes: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the DataFrame :param value: value to compare :return: list of booleans """ indexes = [True] * len(self._index) if indexes is None else indexes compare_list = self.get_rows(indexes, as_list=True) return [x == value for x in compare_list]
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Math helper method. Given a column and optional indexes will return a list of booleans on the equality of the value for that index in the DataFrame to the value parameter. :param indexes: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the DataFrame :param value: value to compare :return: list of booleans
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L312-L324
rsheftel/raccoon
raccoon/series.py
Series._pad_data
def _pad_data(self, index_len): """ Pad the data in Series with [None] to ensure that data is the same length as index :param index_len: length of index to extend data to :return: nothing """ self._data.extend([None] * (index_len - len(self._data)))
python
def _pad_data(self, index_len): """ Pad the data in Series with [None] to ensure that data is the same length as index :param index_len: length of index to extend data to :return: nothing """ self._data.extend([None] * (index_len - len(self._data)))
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Pad the data in Series with [None] to ensure that data is the same length as index :param index_len: length of index to extend data to :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L382-L389
rsheftel/raccoon
raccoon/series.py
Series.sort_index
def sort_index(self): """ Sort the Series by the index. The sort modifies the Series inplace :return: nothing """ sort = sorted_list_indexes(self._index) # sort index self._index = blist([self._index[x] for x in sort]) if self._blist else [self._index[x] for x in sort] # sort data self._data = blist([self._data[x] for x in sort]) if self._blist else [self._data[x] for x in sort]
python
def sort_index(self): """ Sort the Series by the index. The sort modifies the Series inplace :return: nothing """ sort = sorted_list_indexes(self._index) # sort index self._index = blist([self._index[x] for x in sort]) if self._blist else [self._index[x] for x in sort] # sort data self._data = blist([self._data[x] for x in sort]) if self._blist else [self._data[x] for x in sort]
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Sort the Series by the index. The sort modifies the Series inplace :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L418-L428
rsheftel/raccoon
raccoon/series.py
Series.set
def set(self, indexes, values=None): """ Given indexes will set a sub-set of the Series to the values provided. This method will direct to the below methods based on what types are passed in for the indexes. If the indexes contains values not in the Series then new rows or columns will be added. :param indexes: indexes value, list of indexes values, or a list of booleans. :param values: value or list of values to set. If a list then must be the same length as the indexes parameter. :return: nothing """ if isinstance(indexes, (list, blist)): self.set_rows(indexes, values) else: self.set_cell(indexes, values)
python
def set(self, indexes, values=None): """ Given indexes will set a sub-set of the Series to the values provided. This method will direct to the below methods based on what types are passed in for the indexes. If the indexes contains values not in the Series then new rows or columns will be added. :param indexes: indexes value, list of indexes values, or a list of booleans. :param values: value or list of values to set. If a list then must be the same length as the indexes parameter. :return: nothing """ if isinstance(indexes, (list, blist)): self.set_rows(indexes, values) else: self.set_cell(indexes, values)
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Given indexes will set a sub-set of the Series to the values provided. This method will direct to the below methods based on what types are passed in for the indexes. If the indexes contains values not in the Series then new rows or columns will be added. :param indexes: indexes value, list of indexes values, or a list of booleans. :param values: value or list of values to set. If a list then must be the same length as the indexes parameter. :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L430-L443
rsheftel/raccoon
raccoon/series.py
Series._add_row
def _add_row(self, index): """ Add a new row to the Series :param index: index of the new row :return: nothing """ self._index.append(index) self._data.append(None)
python
def _add_row(self, index): """ Add a new row to the Series :param index: index of the new row :return: nothing """ self._index.append(index) self._data.append(None)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L445-L453
rsheftel/raccoon
raccoon/series.py
Series._insert_row
def _insert_row(self, i, index): """ Insert a new row in the Series. :param i: index location to insert :param index: index value to insert into the index list :return: nothing """ if i == len(self._index): self._add_row(index) else: self._index.insert(i, index) self._data.insert(i, None)
python
def _insert_row(self, i, index): """ Insert a new row in the Series. :param i: index location to insert :param index: index value to insert into the index list :return: nothing """ if i == len(self._index): self._add_row(index) else: self._index.insert(i, index) self._data.insert(i, None)
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Insert a new row in the Series. :param i: index location to insert :param index: index value to insert into the index list :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L455-L467
rsheftel/raccoon
raccoon/series.py
Series._add_missing_rows
def _add_missing_rows(self, indexes): """ Given a list of indexes, find all the indexes that are not currently in the Series and make a new row for that index by appending to the Series. This does not maintain sorted order for the index. :param indexes: list of indexes :return: nothing """ new_indexes = [x for x in indexes if x not in self._index] for x in new_indexes: self._add_row(x)
python
def _add_missing_rows(self, indexes): """ Given a list of indexes, find all the indexes that are not currently in the Series and make a new row for that index by appending to the Series. This does not maintain sorted order for the index. :param indexes: list of indexes :return: nothing """ new_indexes = [x for x in indexes if x not in self._index] for x in new_indexes: self._add_row(x)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L469-L479
rsheftel/raccoon
raccoon/series.py
Series._insert_missing_rows
def _insert_missing_rows(self, indexes): """ Given a list of indexes, find all the indexes that are not currently in the Series and make a new row for that index, inserting into the index. This requires the Series to be sorted=True :param indexes: list of indexes :return: nothing """ new_indexes = [x for x in indexes if x not in self._index] for x in new_indexes: self._insert_row(bisect_left(self._index, x), x)
python
def _insert_missing_rows(self, indexes): """ Given a list of indexes, find all the indexes that are not currently in the Series and make a new row for that index, inserting into the index. This requires the Series to be sorted=True :param indexes: list of indexes :return: nothing """ new_indexes = [x for x in indexes if x not in self._index] for x in new_indexes: self._insert_row(bisect_left(self._index, x), x)
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Given a list of indexes, find all the indexes that are not currently in the Series and make a new row for that index, inserting into the index. This requires the Series to be sorted=True :param indexes: list of indexes :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L481-L491
rsheftel/raccoon
raccoon/series.py
Series.set_cell
def set_cell(self, index, value): """ Sets the value of a single cell. If the index is not in the current index then a new index will be created. :param index: index value :param value: value to set :return: nothing """ if self._sort: exists, i = sorted_exists(self._index, index) if not exists: self._insert_row(i, index) else: try: i = self._index.index(index) except ValueError: i = len(self._index) self._add_row(index) self._data[i] = value
python
def set_cell(self, index, value): """ Sets the value of a single cell. If the index is not in the current index then a new index will be created. :param index: index value :param value: value to set :return: nothing """ if self._sort: exists, i = sorted_exists(self._index, index) if not exists: self._insert_row(i, index) else: try: i = self._index.index(index) except ValueError: i = len(self._index) self._add_row(index) self._data[i] = value
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Sets the value of a single cell. If the index is not in the current index then a new index will be created. :param index: index value :param value: value to set :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L493-L511
rsheftel/raccoon
raccoon/series.py
Series.set_rows
def set_rows(self, index, values=None): """ Set rows to a single value or list of values. If any of the index values are not in the current indexes then a new row will be created. :param index: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the Series :param values: either a single value or a list. The list must be the same length as the index list if the index\ list is values, or the length of the True values in the index list if the index list is booleans :return: nothing """ if all([isinstance(i, bool) for i in index]): # boolean list if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for x in index if x] if len(index) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if len(values) != index.count(True): raise ValueError('length of values list must equal number of True entries in index list') indexes = [i for i, x in enumerate(index) if x] for x, i in enumerate(indexes): self._data[i] = values[x] else: # list of index if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for _ in index] if len(values) != len(index): raise ValueError('length of values and index must be the same.') # insert or append indexes as needed if self._sort: exists_tuples = list(zip(*[sorted_exists(self._index, x) for x in index])) exists = exists_tuples[0] indexes = exists_tuples[1] if not all(exists): self._insert_missing_rows(index) indexes = [sorted_index(self._index, x) for x in index] else: try: # all index in current index indexes = [self._index.index(x) for x in index] except ValueError: # new rows need to be added self._add_missing_rows(index) indexes = [self._index.index(x) for x in index] for x, i in enumerate(indexes): self._data[i] = values[x]
python
def set_rows(self, index, values=None): """ Set rows to a single value or list of values. If any of the index values are not in the current indexes then a new row will be created. :param index: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the Series :param values: either a single value or a list. The list must be the same length as the index list if the index\ list is values, or the length of the True values in the index list if the index list is booleans :return: nothing """ if all([isinstance(i, bool) for i in index]): # boolean list if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for x in index if x] if len(index) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if len(values) != index.count(True): raise ValueError('length of values list must equal number of True entries in index list') indexes = [i for i, x in enumerate(index) if x] for x, i in enumerate(indexes): self._data[i] = values[x] else: # list of index if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for _ in index] if len(values) != len(index): raise ValueError('length of values and index must be the same.') # insert or append indexes as needed if self._sort: exists_tuples = list(zip(*[sorted_exists(self._index, x) for x in index])) exists = exists_tuples[0] indexes = exists_tuples[1] if not all(exists): self._insert_missing_rows(index) indexes = [sorted_index(self._index, x) for x in index] else: try: # all index in current index indexes = [self._index.index(x) for x in index] except ValueError: # new rows need to be added self._add_missing_rows(index) indexes = [self._index.index(x) for x in index] for x, i in enumerate(indexes): self._data[i] = values[x]
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L513-L554
rsheftel/raccoon
raccoon/series.py
Series.set_locations
def set_locations(self, locations, values): """ For a list of locations set the values. :param locations: list of index locations :param values: list of values or a single value :return: nothing """ indexes = [self._index[x] for x in locations] self.set(indexes, values)
python
def set_locations(self, locations, values): """ For a list of locations set the values. :param locations: list of index locations :param values: list of values or a single value :return: nothing """ indexes = [self._index[x] for x in locations] self.set(indexes, values)
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For a list of locations set the values. :param locations: list of index locations :param values: list of values or a single value :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L566-L576
rsheftel/raccoon
raccoon/series.py
Series.append_row
def append_row(self, index, value): """ Appends a row of value to the end of the data. Be very careful with this function as for sorted Series it will not enforce sort order. Use this only for speed when needed, be careful. :param index: index :param value: value :return: nothing """ if index in self._index: raise IndexError('index already in Series') self._index.append(index) self._data.append(value)
python
def append_row(self, index, value): """ Appends a row of value to the end of the data. Be very careful with this function as for sorted Series it will not enforce sort order. Use this only for speed when needed, be careful. :param index: index :param value: value :return: nothing """ if index in self._index: raise IndexError('index already in Series') self._index.append(index) self._data.append(value)
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Appends a row of value to the end of the data. Be very careful with this function as for sorted Series it will not enforce sort order. Use this only for speed when needed, be careful. :param index: index :param value: value :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L614-L627
rsheftel/raccoon
raccoon/series.py
Series.append_rows
def append_rows(self, indexes, values): """ Appends values to the end of the data. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param indexes: list of indexes to append :param values: list of values to append :return: nothing """ # check that the values data is less than or equal to the length of the indexes if len(values) != len(indexes): raise ValueError('length of values is not equal to length of indexes') # check the indexes are not duplicates combined_index = self._index + indexes if len(set(combined_index)) != len(combined_index): raise IndexError('duplicate indexes in Series') # append index value self._index.extend(indexes) self._data.extend(values)
python
def append_rows(self, indexes, values): """ Appends values to the end of the data. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param indexes: list of indexes to append :param values: list of values to append :return: nothing """ # check that the values data is less than or equal to the length of the indexes if len(values) != len(indexes): raise ValueError('length of values is not equal to length of indexes') # check the indexes are not duplicates combined_index = self._index + indexes if len(set(combined_index)) != len(combined_index): raise IndexError('duplicate indexes in Series') # append index value self._index.extend(indexes) self._data.extend(values)
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Appends values to the end of the data. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param indexes: list of indexes to append :param values: list of values to append :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L629-L650
rsheftel/raccoon
raccoon/series.py
Series.delete
def delete(self, indexes): """ Delete rows from the DataFrame :param indexes: either a list of values or list of booleans for the rows to delete :return: nothing """ indexes = [indexes] if not isinstance(indexes, (list, blist)) else indexes if all([isinstance(i, bool) for i in indexes]): # boolean list if len(indexes) != len(self._index): raise ValueError('boolean indexes list must be same size of existing indexes') indexes = [i for i, x in enumerate(indexes) if x] else: indexes = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] indexes = sorted(indexes, reverse=True) # need to sort and reverse list so deleting works for i in indexes: del self._data[i] # now remove from index for i in indexes: del self._index[i]
python
def delete(self, indexes): """ Delete rows from the DataFrame :param indexes: either a list of values or list of booleans for the rows to delete :return: nothing """ indexes = [indexes] if not isinstance(indexes, (list, blist)) else indexes if all([isinstance(i, bool) for i in indexes]): # boolean list if len(indexes) != len(self._index): raise ValueError('boolean indexes list must be same size of existing indexes') indexes = [i for i, x in enumerate(indexes) if x] else: indexes = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] indexes = sorted(indexes, reverse=True) # need to sort and reverse list so deleting works for i in indexes: del self._data[i] # now remove from index for i in indexes: del self._index[i]
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L652-L672
rsheftel/raccoon
raccoon/series.py
Series.reset_index
def reset_index(self): """ Resets the index of the Series to simple integer list and the index name to 'index'. :return: nothing """ self.index = list(range(self.__len__())) self.index_name = 'index'
python
def reset_index(self): """ Resets the index of the Series to simple integer list and the index name to 'index'. :return: nothing """ self.index = list(range(self.__len__())) self.index_name = 'index'
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Resets the index of the Series to simple integer list and the index name to 'index'. :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L674-L681
rsheftel/raccoon
raccoon/series.py
ViewSeries.value
def value(self, indexes, int_as_index=False): """ Wrapper function for get. It will return a list, no index. If the indexes are integers it will be assumed that they are locations unless int_as_index = True. If the indexes are locations then they will be rotated to the left by offset number of locations. :param indexes: integer location, single index, list of indexes or list of boolean :param int_as_index: if True then will treat int index values as indexes and not locations :return: value or list of values """ # single integer value if isinstance(indexes, int): if int_as_index: return self.get(indexes, as_list=True) else: indexes = indexes - self._offset return self._data[indexes] # slice elif isinstance(indexes, slice): if isinstance(indexes.start, int) and not int_as_index: # treat as location start = indexes.start - self._offset stop = indexes.stop - self._offset + 1 # to capture the last value # check locations are valid and will not return empty if start > stop: raise IndexError('end of slice is before start of slice') if (start > 0 > stop) or (start < 0 < stop): raise IndexError('slide indexes invalid with given offset:%f' % self._offset) # where end is the last element if (start < 0) and stop == 0: return self._data[start:] return self._data[start:stop] else: # treat as index indexes = self._slice_index(indexes) return self.get(indexes, as_list=True) # list of booleans elif all([isinstance(x, bool) for x in indexes]): return self.get(indexes, as_list=True) # list of values elif isinstance(indexes, list): if int_as_index or not isinstance(indexes[0], int): return self.get(indexes, as_list=True) else: indexes = [x - self._offset for x in indexes] return self.get_locations(indexes, as_list=True) # just a single value else: return self.get(indexes)
python
def value(self, indexes, int_as_index=False): """ Wrapper function for get. It will return a list, no index. If the indexes are integers it will be assumed that they are locations unless int_as_index = True. If the indexes are locations then they will be rotated to the left by offset number of locations. :param indexes: integer location, single index, list of indexes or list of boolean :param int_as_index: if True then will treat int index values as indexes and not locations :return: value or list of values """ # single integer value if isinstance(indexes, int): if int_as_index: return self.get(indexes, as_list=True) else: indexes = indexes - self._offset return self._data[indexes] # slice elif isinstance(indexes, slice): if isinstance(indexes.start, int) and not int_as_index: # treat as location start = indexes.start - self._offset stop = indexes.stop - self._offset + 1 # to capture the last value # check locations are valid and will not return empty if start > stop: raise IndexError('end of slice is before start of slice') if (start > 0 > stop) or (start < 0 < stop): raise IndexError('slide indexes invalid with given offset:%f' % self._offset) # where end is the last element if (start < 0) and stop == 0: return self._data[start:] return self._data[start:stop] else: # treat as index indexes = self._slice_index(indexes) return self.get(indexes, as_list=True) # list of booleans elif all([isinstance(x, bool) for x in indexes]): return self.get(indexes, as_list=True) # list of values elif isinstance(indexes, list): if int_as_index or not isinstance(indexes[0], int): return self.get(indexes, as_list=True) else: indexes = [x - self._offset for x in indexes] return self.get_locations(indexes, as_list=True) # just a single value else: return self.get(indexes)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L738-L788
rsheftel/raccoon
raccoon/series.py
ViewSeries.from_dataframe
def from_dataframe(cls, dataframe, column, offset=0): """ Creates and return a Series from a DataFrame and specific column :param dataframe: raccoon DataFrame :param column: column name :param offset: offset value must be provided as there is no equivalent for a DataFrame :return: Series """ return cls(data=dataframe.get_entire_column(column, as_list=True), index=dataframe.index, data_name=column, index_name=dataframe.index_name, sort=dataframe.sort, offset=offset)
python
def from_dataframe(cls, dataframe, column, offset=0): """ Creates and return a Series from a DataFrame and specific column :param dataframe: raccoon DataFrame :param column: column name :param offset: offset value must be provided as there is no equivalent for a DataFrame :return: Series """ return cls(data=dataframe.get_entire_column(column, as_list=True), index=dataframe.index, data_name=column, index_name=dataframe.index_name, sort=dataframe.sort, offset=offset)
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Creates and return a Series from a DataFrame and specific column :param dataframe: raccoon DataFrame :param column: column name :param offset: offset value must be provided as there is no equivalent for a DataFrame :return: Series
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L807-L817
rsheftel/raccoon
raccoon/series.py
ViewSeries.from_series
def from_series(cls, series, offset=0): """ Creates and return a Series from a Series :param series: raccoon Series :param offset: offset value must be provided as there is no equivalent for a DataFrame :return: Series """ return cls(data=series.data, index=series.index, data_name=series.data_name, index_name=series.index_name, sort=series.sort, offset=offset)
python
def from_series(cls, series, offset=0): """ Creates and return a Series from a Series :param series: raccoon Series :param offset: offset value must be provided as there is no equivalent for a DataFrame :return: Series """ return cls(data=series.data, index=series.index, data_name=series.data_name, index_name=series.index_name, sort=series.sort, offset=offset)
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Creates and return a Series from a Series :param series: raccoon Series :param offset: offset value must be provided as there is no equivalent for a DataFrame :return: Series
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/series.py#L820-L829
vmlaker/mpipe
src/TubeQ.py
TubeQ.get
def get(self, timeout=None): """Return the next available item from the tube. Blocks if tube is empty, until a producer for the tube puts an item on it.""" if timeout: try: result = self._queue.get(True, timeout) except multiprocessing.Queue.Empty: return(False, None) return(True, result) return self._queue.get()
python
def get(self, timeout=None): """Return the next available item from the tube. Blocks if tube is empty, until a producer for the tube puts an item on it.""" if timeout: try: result = self._queue.get(True, timeout) except multiprocessing.Queue.Empty: return(False, None) return(True, result) return self._queue.get()
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Return the next available item from the tube. Blocks if tube is empty, until a producer for the tube puts an item on it.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/TubeQ.py#L16-L26
vmlaker/mpipe
src/Stage.py
Stage.get
def get(self, timeout=None): """Retrieve results from all the output tubes.""" valid = False result = None for tube in self._output_tubes: if timeout: valid, result = tube.get(timeout) if valid: result = result[0] else: result = tube.get()[0] if timeout: return valid, result return result
python
def get(self, timeout=None): """Retrieve results from all the output tubes.""" valid = False result = None for tube in self._output_tubes: if timeout: valid, result = tube.get(timeout) if valid: result = result[0] else: result = tube.get()[0] if timeout: return valid, result return result
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Retrieve results from all the output tubes.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/Stage.py#L42-L55
vmlaker/mpipe
src/Stage.py
Stage.link
def link(self, next_stage): """Link to the given downstream stage *next_stage* by adding its input tube to the list of this stage's output tubes. Return this stage.""" if next_stage is self: raise ValueError('cannot link stage to itself') self._output_tubes.append(next_stage._input_tube) self._next_stages.append(next_stage) return self
python
def link(self, next_stage): """Link to the given downstream stage *next_stage* by adding its input tube to the list of this stage's output tubes. Return this stage.""" if next_stage is self: raise ValueError('cannot link stage to itself') self._output_tubes.append(next_stage._input_tube) self._next_stages.append(next_stage) return self
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Link to the given downstream stage *next_stage* by adding its input tube to the list of this stage's output tubes. Return this stage.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/Stage.py#L64-L71
vmlaker/mpipe
src/Stage.py
Stage.getLeaves
def getLeaves(self): """Return the downstream leaf stages of this stage.""" result = list() if not self._next_stages: result.append(self) else: for stage in self._next_stages: leaves = stage.getLeaves() result += leaves return result
python
def getLeaves(self): """Return the downstream leaf stages of this stage.""" result = list() if not self._next_stages: result.append(self) else: for stage in self._next_stages: leaves = stage.getLeaves() result += leaves return result
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Return the downstream leaf stages of this stage.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/Stage.py#L73-L82
vmlaker/mpipe
src/Stage.py
Stage.build
def build(self): """Create and start up the internal workers.""" # If there's no output tube, it means that this stage # is at the end of a fork (hasn't been linked to any stage downstream). # Therefore, create one output tube. if not self._output_tubes: self._output_tubes.append(self._worker_class.getTubeClass()()) self._worker_class.assemble( self._worker_args, self._input_tube, self._output_tubes, self._size, self._disable_result, self._do_stop_task, ) # Build all downstream stages. for stage in self._next_stages: stage.build()
python
def build(self): """Create and start up the internal workers.""" # If there's no output tube, it means that this stage # is at the end of a fork (hasn't been linked to any stage downstream). # Therefore, create one output tube. if not self._output_tubes: self._output_tubes.append(self._worker_class.getTubeClass()()) self._worker_class.assemble( self._worker_args, self._input_tube, self._output_tubes, self._size, self._disable_result, self._do_stop_task, ) # Build all downstream stages. for stage in self._next_stages: stage.build()
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/Stage.py#L84-L104
vmlaker/mpipe
src/TubeP.py
TubeP.get
def get(self, timeout=None): """Return the next available item from the tube. Blocks if tube is empty, until a producer for the tube puts an item on it.""" if timeout: # Todo: Consider locking the poll/recv block. # Otherwise, this method is not thread safe. if self._conn1.poll(timeout): return (True, self._conn1.recv()) else: return (False, None) return self._conn1.recv()
python
def get(self, timeout=None): """Return the next available item from the tube. Blocks if tube is empty, until a producer for the tube puts an item on it.""" if timeout: # Todo: Consider locking the poll/recv block. # Otherwise, this method is not thread safe. if self._conn1.poll(timeout): return (True, self._conn1.recv()) else: return (False, None) return self._conn1.recv()
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Return the next available item from the tube. Blocks if tube is empty, until a producer for the tube puts an item on it.
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train
https://github.com/vmlaker/mpipe/blob/5a1804cf64271931f0cd3e4fff3e2b38291212dd/src/TubeP.py#L17-L28
rsheftel/raccoon
raccoon/dataframe.py
DataFrame._sort_columns
def _sort_columns(self, columns_list): """ Given a list of column names will sort the DataFrame columns to match the given order :param columns_list: list of column names. Must include all column names :return: nothing """ if not (all([x in columns_list for x in self._columns]) and all([x in self._columns for x in columns_list])): raise ValueError( 'columns_list must be all in current columns, and all current columns must be in columns_list') new_sort = [self._columns.index(x) for x in columns_list] self._data = blist([self._data[x] for x in new_sort]) if self._blist else [self._data[x] for x in new_sort] self._columns = blist([self._columns[x] for x in new_sort]) if self._blist \ else [self._columns[x] for x in new_sort]
python
def _sort_columns(self, columns_list): """ Given a list of column names will sort the DataFrame columns to match the given order :param columns_list: list of column names. Must include all column names :return: nothing """ if not (all([x in columns_list for x in self._columns]) and all([x in self._columns for x in columns_list])): raise ValueError( 'columns_list must be all in current columns, and all current columns must be in columns_list') new_sort = [self._columns.index(x) for x in columns_list] self._data = blist([self._data[x] for x in new_sort]) if self._blist else [self._data[x] for x in new_sort] self._columns = blist([self._columns[x] for x in new_sort]) if self._blist \ else [self._columns[x] for x in new_sort]
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Given a list of column names will sort the DataFrame columns to match the given order :param columns_list: list of column names. Must include all column names :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L126-L139
rsheftel/raccoon
raccoon/dataframe.py
DataFrame._pad_data
def _pad_data(self, max_len=None): """ Pad the data in DataFrame with [None} to ensure that all columns have the same length. :param max_len: If provided will extend all columns to this length, if not then will use the longest column :return: nothing """ if not max_len: max_len = max([len(x) for x in self._data]) for _, col in enumerate(self._data): col.extend([None] * (max_len - len(col)))
python
def _pad_data(self, max_len=None): """ Pad the data in DataFrame with [None} to ensure that all columns have the same length. :param max_len: If provided will extend all columns to this length, if not then will use the longest column :return: nothing """ if not max_len: max_len = max([len(x) for x in self._data]) for _, col in enumerate(self._data): col.extend([None] * (max_len - len(col)))
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Pad the data in DataFrame with [None} to ensure that all columns have the same length. :param max_len: If provided will extend all columns to this length, if not then will use the longest column :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L141-L151
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get
def get(self, indexes=None, columns=None, as_list=False, as_dict=False): """ Given indexes and columns will return a sub-set of the DataFrame. This method will direct to the below methods based on what types are passed in for the indexes and columns. The type of the return is determined by the types of the parameters. :param indexes: index value, list of index values, or a list of booleans. If None then all indexes are used :param columns: column name or list of column names. If None then all columns are used :param as_list: if True then return the values as a list, if False return a DataFrame. This is only used if the get is for a single column :param as_dict: if True then return the values as a dictionary, if False return a DataFrame. This is only used if the get is for a single row :return: either DataFrame, list, dict or single value. The return is a shallow copy """ if (indexes is None) and (columns is not None) and (not isinstance(columns, (list, blist))): return self.get_entire_column(columns, as_list) if indexes is None: indexes = [True] * len(self._index) if columns is None: columns = [True] * len(self._columns) if isinstance(indexes, (list, blist)) and isinstance(columns, (list, blist)): return self.get_matrix(indexes, columns) elif isinstance(indexes, (list, blist)) and (not isinstance(columns, (list, blist))): return self.get_rows(indexes, columns, as_list) elif (not isinstance(indexes, (list, blist))) and isinstance(columns, (list, blist)): return self.get_columns(indexes, columns, as_dict) else: return self.get_cell(indexes, columns)
python
def get(self, indexes=None, columns=None, as_list=False, as_dict=False): """ Given indexes and columns will return a sub-set of the DataFrame. This method will direct to the below methods based on what types are passed in for the indexes and columns. The type of the return is determined by the types of the parameters. :param indexes: index value, list of index values, or a list of booleans. If None then all indexes are used :param columns: column name or list of column names. If None then all columns are used :param as_list: if True then return the values as a list, if False return a DataFrame. This is only used if the get is for a single column :param as_dict: if True then return the values as a dictionary, if False return a DataFrame. This is only used if the get is for a single row :return: either DataFrame, list, dict or single value. The return is a shallow copy """ if (indexes is None) and (columns is not None) and (not isinstance(columns, (list, blist))): return self.get_entire_column(columns, as_list) if indexes is None: indexes = [True] * len(self._index) if columns is None: columns = [True] * len(self._columns) if isinstance(indexes, (list, blist)) and isinstance(columns, (list, blist)): return self.get_matrix(indexes, columns) elif isinstance(indexes, (list, blist)) and (not isinstance(columns, (list, blist))): return self.get_rows(indexes, columns, as_list) elif (not isinstance(indexes, (list, blist))) and isinstance(columns, (list, blist)): return self.get_columns(indexes, columns, as_dict) else: return self.get_cell(indexes, columns)
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Given indexes and columns will return a sub-set of the DataFrame. This method will direct to the below methods based on what types are passed in for the indexes and columns. The type of the return is determined by the types of the parameters. :param indexes: index value, list of index values, or a list of booleans. If None then all indexes are used :param columns: column name or list of column names. If None then all columns are used :param as_list: if True then return the values as a list, if False return a DataFrame. This is only used if the get is for a single column :param as_dict: if True then return the values as a dictionary, if False return a DataFrame. This is only used if the get is for a single row :return: either DataFrame, list, dict or single value. The return is a shallow copy
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L240-L269
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_cell
def get_cell(self, index, column): """ For a single index and column value return the value of the cell :param index: index value :param column: column name :return: value """ i = sorted_index(self._index, index) if self._sort else self._index.index(index) c = self._columns.index(column) return self._data[c][i]
python
def get_cell(self, index, column): """ For a single index and column value return the value of the cell :param index: index value :param column: column name :return: value """ i = sorted_index(self._index, index) if self._sort else self._index.index(index) c = self._columns.index(column) return self._data[c][i]
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For a single index and column value return the value of the cell :param index: index value :param column: column name :return: value
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L271-L281
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_rows
def get_rows(self, indexes, column, as_list=False): """ For a list of indexes and a single column name return the values of the indexes in that column. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param column: single column name :param as_list: if True return a list, if False return DataFrame :return: DataFrame is as_list if False, a list if as_list is True """ c = self._columns.index(column) if all([isinstance(i, bool) for i in indexes]): # boolean list if len(indexes) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if all(indexes): # the entire column data = self._data[c] index = self._index else: data = list(compress(self._data[c], indexes)) index = list(compress(self._index, indexes)) else: # index values list locations = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] data = [self._data[c][i] for i in locations] index = [self._index[i] for i in locations] return data if as_list else DataFrame(data={column: data}, index=index, index_name=self._index_name, sort=self._sort)
python
def get_rows(self, indexes, column, as_list=False): """ For a list of indexes and a single column name return the values of the indexes in that column. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param column: single column name :param as_list: if True return a list, if False return DataFrame :return: DataFrame is as_list if False, a list if as_list is True """ c = self._columns.index(column) if all([isinstance(i, bool) for i in indexes]): # boolean list if len(indexes) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if all(indexes): # the entire column data = self._data[c] index = self._index else: data = list(compress(self._data[c], indexes)) index = list(compress(self._index, indexes)) else: # index values list locations = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] data = [self._data[c][i] for i in locations] index = [self._index[i] for i in locations] return data if as_list else DataFrame(data={column: data}, index=index, index_name=self._index_name, sort=self._sort)
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For a list of indexes and a single column name return the values of the indexes in that column. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param column: single column name :param as_list: if True return a list, if False return DataFrame :return: DataFrame is as_list if False, a list if as_list is True
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L283-L308
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_columns
def get_columns(self, index, columns=None, as_dict=False): """ For a single index and list of column names return a DataFrame of the values in that index as either a dict or a DataFrame :param index: single index value :param columns: list of column names :param as_dict: if True then return the result as a dictionary :return: DataFrame or dictionary """ i = sorted_index(self._index, index) if self._sort else self._index.index(index) return self.get_location(i, columns, as_dict)
python
def get_columns(self, index, columns=None, as_dict=False): """ For a single index and list of column names return a DataFrame of the values in that index as either a dict or a DataFrame :param index: single index value :param columns: list of column names :param as_dict: if True then return the result as a dictionary :return: DataFrame or dictionary """ i = sorted_index(self._index, index) if self._sort else self._index.index(index) return self.get_location(i, columns, as_dict)
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For a single index and list of column names return a DataFrame of the values in that index as either a dict or a DataFrame :param index: single index value :param columns: list of column names :param as_dict: if True then return the result as a dictionary :return: DataFrame or dictionary
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L310-L321
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_entire_column
def get_entire_column(self, column, as_list=False): """ Shortcut method to retrieve a single column all rows. Since this is a common use case this method will be faster than the more general method. :param column: single column name :param as_list: if True return a list, if False return DataFrame :return: DataFrame is as_list if False, a list if as_list is True """ c = self._columns.index(column) data = self._data[c] return data if as_list else DataFrame(data={column: data}, index=self._index, index_name=self._index_name, sort=self._sort)
python
def get_entire_column(self, column, as_list=False): """ Shortcut method to retrieve a single column all rows. Since this is a common use case this method will be faster than the more general method. :param column: single column name :param as_list: if True return a list, if False return DataFrame :return: DataFrame is as_list if False, a list if as_list is True """ c = self._columns.index(column) data = self._data[c] return data if as_list else DataFrame(data={column: data}, index=self._index, index_name=self._index_name, sort=self._sort)
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Shortcut method to retrieve a single column all rows. Since this is a common use case this method will be faster than the more general method. :param column: single column name :param as_list: if True return a list, if False return DataFrame :return: DataFrame is as_list if False, a list if as_list is True
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L323-L335
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_matrix
def get_matrix(self, indexes, columns): """ For a list of indexes and list of columns return a DataFrame of the values. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param columns: list of column names :return: DataFrame """ if all([isinstance(i, bool) for i in indexes]): # boolean list is_bool_indexes = True if len(indexes) != len(self._index): raise ValueError('boolean index list must be same size of existing index') bool_indexes = indexes indexes = list(compress(self._index, indexes)) else: is_bool_indexes = False locations = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] if all([isinstance(i, bool) for i in columns]): # boolean list if len(columns) != len(self._columns): raise ValueError('boolean column list must be same size of existing columns') columns = list(compress(self._columns, columns)) col_locations = [self._columns.index(x) for x in columns] data_dict = dict() for c in col_locations: data_dict[self._columns[c]] = list(compress(self._data[c], bool_indexes)) if is_bool_indexes \ else [self._data[c][i] for i in locations] return DataFrame(data=data_dict, index=indexes, columns=columns, index_name=self._index_name, sort=self._sort)
python
def get_matrix(self, indexes, columns): """ For a list of indexes and list of columns return a DataFrame of the values. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param columns: list of column names :return: DataFrame """ if all([isinstance(i, bool) for i in indexes]): # boolean list is_bool_indexes = True if len(indexes) != len(self._index): raise ValueError('boolean index list must be same size of existing index') bool_indexes = indexes indexes = list(compress(self._index, indexes)) else: is_bool_indexes = False locations = [sorted_index(self._index, x) for x in indexes] if self._sort \ else [self._index.index(x) for x in indexes] if all([isinstance(i, bool) for i in columns]): # boolean list if len(columns) != len(self._columns): raise ValueError('boolean column list must be same size of existing columns') columns = list(compress(self._columns, columns)) col_locations = [self._columns.index(x) for x in columns] data_dict = dict() for c in col_locations: data_dict[self._columns[c]] = list(compress(self._data[c], bool_indexes)) if is_bool_indexes \ else [self._data[c][i] for i in locations] return DataFrame(data=data_dict, index=indexes, columns=columns, index_name=self._index_name, sort=self._sort)
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For a list of indexes and list of columns return a DataFrame of the values. :param indexes: either a list of index values or a list of booleans with same length as all indexes :param columns: list of column names :return: DataFrame
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L337-L369
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_location
def get_location(self, location, columns=None, as_dict=False, index=True): """ For an index location and either (1) list of columns return a DataFrame or dictionary of the values or (2) single column name and return the value of that cell. This is optimized for speed because it does not need to lookup the index location with a search. Also can accept relative indexing from the end of the DataFrame in standard python notation [-3, -2, -1] :param location: index location in standard python form of positive or negative number :param columns: list of columns, single column name, or None to include all columns :param as_dict: if True then return a dictionary :param index: if True then include the index in the dictionary if as_dict=True :return: DataFrame or dictionary if columns is a list or value if columns is a single column name """ if columns is None: columns = self._columns elif not isinstance(columns, list): # single value for columns c = self._columns.index(columns) return self._data[c][location] elif all([isinstance(i, bool) for i in columns]): if len(columns) != len(self._columns): raise ValueError('boolean column list must be same size of existing columns') columns = list(compress(self._columns, columns)) data = dict() for column in columns: c = self._columns.index(column) data[column] = self._data[c][location] index_value = self._index[location] if as_dict: if index: data[self._index_name] = index_value return data else: data = {k: [data[k]] for k in data} # this makes the dict items lists return DataFrame(data=data, index=[index_value], columns=columns, index_name=self._index_name, sort=self._sort)
python
def get_location(self, location, columns=None, as_dict=False, index=True): """ For an index location and either (1) list of columns return a DataFrame or dictionary of the values or (2) single column name and return the value of that cell. This is optimized for speed because it does not need to lookup the index location with a search. Also can accept relative indexing from the end of the DataFrame in standard python notation [-3, -2, -1] :param location: index location in standard python form of positive or negative number :param columns: list of columns, single column name, or None to include all columns :param as_dict: if True then return a dictionary :param index: if True then include the index in the dictionary if as_dict=True :return: DataFrame or dictionary if columns is a list or value if columns is a single column name """ if columns is None: columns = self._columns elif not isinstance(columns, list): # single value for columns c = self._columns.index(columns) return self._data[c][location] elif all([isinstance(i, bool) for i in columns]): if len(columns) != len(self._columns): raise ValueError('boolean column list must be same size of existing columns') columns = list(compress(self._columns, columns)) data = dict() for column in columns: c = self._columns.index(column) data[column] = self._data[c][location] index_value = self._index[location] if as_dict: if index: data[self._index_name] = index_value return data else: data = {k: [data[k]] for k in data} # this makes the dict items lists return DataFrame(data=data, index=[index_value], columns=columns, index_name=self._index_name, sort=self._sort)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L371-L405
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_locations
def get_locations(self, locations, columns=None, **kwargs): """ For list of locations and list of columns return a DataFrame of the values. :param locations: list of index locations :param columns: list of column names :param kwargs: will pass along these parameters to the get() method :return: DataFrame """ indexes = [self._index[x] for x in locations] return self.get(indexes, columns, **kwargs)
python
def get_locations(self, locations, columns=None, **kwargs): """ For list of locations and list of columns return a DataFrame of the values. :param locations: list of index locations :param columns: list of column names :param kwargs: will pass along these parameters to the get() method :return: DataFrame """ indexes = [self._index[x] for x in locations] return self.get(indexes, columns, **kwargs)
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For list of locations and list of columns return a DataFrame of the values. :param locations: list of index locations :param columns: list of column names :param kwargs: will pass along these parameters to the get() method :return: DataFrame
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L407-L418
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.get_slice
def get_slice(self, start_index=None, stop_index=None, columns=None, as_dict=False): """ For sorted DataFrames will return either a DataFrame or dict of all of the rows where the index is greater than or equal to the start_index if provided and less than or equal to the stop_index if provided. If either the start or stop index is None then will include from the first or last element, similar to standard python slide of [:5] or [:5]. Both end points are considered inclusive. :param start_index: lowest index value to include, or None to start from the first row :param stop_index: highest index value to include, or None to end at the last row :param columns: list of column names to include, or None for all columns :param as_dict: if True then return a tuple of (list of index, dict of column names: list data values) :return: DataFrame or tuple """ if not self._sort: raise RuntimeError('Can only use get_slice on sorted DataFrames') if columns is None: columns = self._columns elif all([isinstance(i, bool) for i in columns]): if len(columns) != len(self._columns): raise ValueError('boolean column list must be same size of existing columns') columns = list(compress(self._columns, columns)) start_location = bisect_left(self._index, start_index) if start_index is not None else None stop_location = bisect_right(self._index, stop_index) if stop_index is not None else None index = self._index[start_location:stop_location] data = dict() for column in columns: c = self._columns.index(column) data[column] = self._data[c][start_location:stop_location] if as_dict: return index, data else: data = data if data else None # if the dict is empty, convert to None return DataFrame(data=data, index=index, columns=columns, index_name=self._index_name, sort=self._sort, use_blist=self._blist)
python
def get_slice(self, start_index=None, stop_index=None, columns=None, as_dict=False): """ For sorted DataFrames will return either a DataFrame or dict of all of the rows where the index is greater than or equal to the start_index if provided and less than or equal to the stop_index if provided. If either the start or stop index is None then will include from the first or last element, similar to standard python slide of [:5] or [:5]. Both end points are considered inclusive. :param start_index: lowest index value to include, or None to start from the first row :param stop_index: highest index value to include, or None to end at the last row :param columns: list of column names to include, or None for all columns :param as_dict: if True then return a tuple of (list of index, dict of column names: list data values) :return: DataFrame or tuple """ if not self._sort: raise RuntimeError('Can only use get_slice on sorted DataFrames') if columns is None: columns = self._columns elif all([isinstance(i, bool) for i in columns]): if len(columns) != len(self._columns): raise ValueError('boolean column list must be same size of existing columns') columns = list(compress(self._columns, columns)) start_location = bisect_left(self._index, start_index) if start_index is not None else None stop_location = bisect_right(self._index, stop_index) if stop_index is not None else None index = self._index[start_location:stop_location] data = dict() for column in columns: c = self._columns.index(column) data[column] = self._data[c][start_location:stop_location] if as_dict: return index, data else: data = data if data else None # if the dict is empty, convert to None return DataFrame(data=data, index=index, columns=columns, index_name=self._index_name, sort=self._sort, use_blist=self._blist)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L420-L457
rsheftel/raccoon
raccoon/dataframe.py
DataFrame._insert_row
def _insert_row(self, i, index): """ Insert a new row in the DataFrame. :param i: index location to insert :param index: index value to insert into the index list :return: nothing """ if i == len(self._index): self._add_row(index) else: self._index.insert(i, index) for c in range(len(self._columns)): self._data[c].insert(i, None)
python
def _insert_row(self, i, index): """ Insert a new row in the DataFrame. :param i: index location to insert :param index: index value to insert into the index list :return: nothing """ if i == len(self._index): self._add_row(index) else: self._index.insert(i, index) for c in range(len(self._columns)): self._data[c].insert(i, None)
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Insert a new row in the DataFrame. :param i: index location to insert :param index: index value to insert into the index list :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L459-L472
rsheftel/raccoon
raccoon/dataframe.py
DataFrame._add_row
def _add_row(self, index): """ Add a new row to the DataFrame :param index: index of the new row :return: nothing """ self._index.append(index) for c, _ in enumerate(self._columns): self._data[c].append(None)
python
def _add_row(self, index): """ Add a new row to the DataFrame :param index: index of the new row :return: nothing """ self._index.append(index) for c, _ in enumerate(self._columns): self._data[c].append(None)
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Add a new row to the DataFrame :param index: index of the new row :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L486-L495
rsheftel/raccoon
raccoon/dataframe.py
DataFrame._add_column
def _add_column(self, column): """ Add a new column to the DataFrame :param column: column name :return: nothing """ self._columns.append(column) if self._blist: self._data.append(blist([None] * len(self._index))) else: self._data.append([None] * len(self._index))
python
def _add_column(self, column): """ Add a new column to the DataFrame :param column: column name :return: nothing """ self._columns.append(column) if self._blist: self._data.append(blist([None] * len(self._index))) else: self._data.append([None] * len(self._index))
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Add a new column to the DataFrame :param column: column name :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L509-L520
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.set
def set(self, indexes=None, columns=None, values=None): """ Given indexes and columns will set a sub-set of the DataFrame to the values provided. This method will direct to the below methods based on what types are passed in for the indexes and columns. If the indexes or columns contains values not in the DataFrame then new rows or columns will be added. :param indexes: indexes value, list of indexes values, or a list of booleans. If None then all indexes are used :param columns: columns name, if None then all columns are used. Currently can only handle a single column or\ all columns :param values: value or list of values to set (index, column) to. If setting just a single row, then must be a\ dict where the keys are the column names. If a list then must be the same length as the indexes parameter, if\ indexes=None, then must be the same and length of DataFrame :return: nothing """ if (indexes is not None) and (columns is not None): if isinstance(indexes, (list, blist)): self.set_column(indexes, columns, values) else: self.set_cell(indexes, columns, values) elif (indexes is not None) and (columns is None): self.set_row(indexes, values) elif (indexes is None) and (columns is not None): self.set_column(indexes, columns, values) else: raise ValueError('either or both of indexes or columns must be provided')
python
def set(self, indexes=None, columns=None, values=None): """ Given indexes and columns will set a sub-set of the DataFrame to the values provided. This method will direct to the below methods based on what types are passed in for the indexes and columns. If the indexes or columns contains values not in the DataFrame then new rows or columns will be added. :param indexes: indexes value, list of indexes values, or a list of booleans. If None then all indexes are used :param columns: columns name, if None then all columns are used. Currently can only handle a single column or\ all columns :param values: value or list of values to set (index, column) to. If setting just a single row, then must be a\ dict where the keys are the column names. If a list then must be the same length as the indexes parameter, if\ indexes=None, then must be the same and length of DataFrame :return: nothing """ if (indexes is not None) and (columns is not None): if isinstance(indexes, (list, blist)): self.set_column(indexes, columns, values) else: self.set_cell(indexes, columns, values) elif (indexes is not None) and (columns is None): self.set_row(indexes, values) elif (indexes is None) and (columns is not None): self.set_column(indexes, columns, values) else: raise ValueError('either or both of indexes or columns must be provided')
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Given indexes and columns will set a sub-set of the DataFrame to the values provided. This method will direct to the below methods based on what types are passed in for the indexes and columns. If the indexes or columns contains values not in the DataFrame then new rows or columns will be added. :param indexes: indexes value, list of indexes values, or a list of booleans. If None then all indexes are used :param columns: columns name, if None then all columns are used. Currently can only handle a single column or\ all columns :param values: value or list of values to set (index, column) to. If setting just a single row, then must be a\ dict where the keys are the column names. If a list then must be the same length as the indexes parameter, if\ indexes=None, then must be the same and length of DataFrame :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L522-L546
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.set_cell
def set_cell(self, index, column, value): """ Sets the value of a single cell. If the index and/or column is not in the current index/columns then a new index and/or column will be created. :param index: index value :param column: column name :param value: value to set :return: nothing """ if self._sort: exists, i = sorted_exists(self._index, index) if not exists: self._insert_row(i, index) else: try: i = self._index.index(index) except ValueError: i = len(self._index) self._add_row(index) try: c = self._columns.index(column) except ValueError: c = len(self._columns) self._add_column(column) self._data[c][i] = value
python
def set_cell(self, index, column, value): """ Sets the value of a single cell. If the index and/or column is not in the current index/columns then a new index and/or column will be created. :param index: index value :param column: column name :param value: value to set :return: nothing """ if self._sort: exists, i = sorted_exists(self._index, index) if not exists: self._insert_row(i, index) else: try: i = self._index.index(index) except ValueError: i = len(self._index) self._add_row(index) try: c = self._columns.index(column) except ValueError: c = len(self._columns) self._add_column(column) self._data[c][i] = value
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Sets the value of a single cell. If the index and/or column is not in the current index/columns then a new index and/or column will be created. :param index: index value :param column: column name :param value: value to set :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L548-L573
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.set_row
def set_row(self, index, values): """ Sets the values of the columns in a single row. :param index: index value :param values: dict with the keys as the column names and the values what to set that column to :return: nothing """ if self._sort: exists, i = sorted_exists(self._index, index) if not exists: self._insert_row(i, index) else: try: i = self._index.index(index) except ValueError: # new row i = len(self._index) self._add_row(index) if isinstance(values, dict): if not (set(values.keys()).issubset(self._columns)): raise ValueError('keys of values are not all in existing columns') for c, column in enumerate(self._columns): self._data[c][i] = values.get(column, self._data[c][i]) else: raise TypeError('cannot handle values of this type.')
python
def set_row(self, index, values): """ Sets the values of the columns in a single row. :param index: index value :param values: dict with the keys as the column names and the values what to set that column to :return: nothing """ if self._sort: exists, i = sorted_exists(self._index, index) if not exists: self._insert_row(i, index) else: try: i = self._index.index(index) except ValueError: # new row i = len(self._index) self._add_row(index) if isinstance(values, dict): if not (set(values.keys()).issubset(self._columns)): raise ValueError('keys of values are not all in existing columns') for c, column in enumerate(self._columns): self._data[c][i] = values.get(column, self._data[c][i]) else: raise TypeError('cannot handle values of this type.')
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Sets the values of the columns in a single row. :param index: index value :param values: dict with the keys as the column names and the values what to set that column to :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L575-L599
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.set_column
def set_column(self, index=None, column=None, values=None): """ Set a column to a single value or list of values. If any of the index values are not in the current indexes then a new row will be created. :param index: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the DataFrame :param column: column name :param values: either a single value or a list. The list must be the same length as the index list if the index\ list is values, or the length of the True values in the index list if the index list is booleans :return: nothing """ try: c = self._columns.index(column) except ValueError: # new column c = len(self._columns) self._add_column(column) if index: # index was provided if all([isinstance(i, bool) for i in index]): # boolean list if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for x in index if x] if len(index) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if len(values) != index.count(True): raise ValueError('length of values list must equal number of True entries in index list') indexes = [i for i, x in enumerate(index) if x] for x, i in enumerate(indexes): self._data[c][i] = values[x] else: # list of index if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for _ in index] if len(values) != len(index): raise ValueError('length of values and index must be the same.') # insert or append indexes as needed if self._sort: exists_tuples = list(zip(*[sorted_exists(self._index, x) for x in index])) exists = exists_tuples[0] indexes = exists_tuples[1] if not all(exists): self._insert_missing_rows(index) indexes = [sorted_index(self._index, x) for x in index] else: try: # all index in current index indexes = [self._index.index(x) for x in index] except ValueError: # new rows need to be added self._add_missing_rows(index) indexes = [self._index.index(x) for x in index] for x, i in enumerate(indexes): self._data[c][i] = values[x] else: # no index, only values if not isinstance(values, (list, blist)): # values not a list, turn into one of length same as index values = [values for _ in self._index] if len(values) != len(self._index): raise ValueError('values list must be at same length as current index length.') else: self._data[c] = blist(values) if self._blist else values
python
def set_column(self, index=None, column=None, values=None): """ Set a column to a single value or list of values. If any of the index values are not in the current indexes then a new row will be created. :param index: list of index values or list of booleans. If a list of booleans then the list must be the same\ length as the DataFrame :param column: column name :param values: either a single value or a list. The list must be the same length as the index list if the index\ list is values, or the length of the True values in the index list if the index list is booleans :return: nothing """ try: c = self._columns.index(column) except ValueError: # new column c = len(self._columns) self._add_column(column) if index: # index was provided if all([isinstance(i, bool) for i in index]): # boolean list if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for x in index if x] if len(index) != len(self._index): raise ValueError('boolean index list must be same size of existing index') if len(values) != index.count(True): raise ValueError('length of values list must equal number of True entries in index list') indexes = [i for i, x in enumerate(index) if x] for x, i in enumerate(indexes): self._data[c][i] = values[x] else: # list of index if not isinstance(values, (list, blist)): # single value provided, not a list, so turn values into list values = [values for _ in index] if len(values) != len(index): raise ValueError('length of values and index must be the same.') # insert or append indexes as needed if self._sort: exists_tuples = list(zip(*[sorted_exists(self._index, x) for x in index])) exists = exists_tuples[0] indexes = exists_tuples[1] if not all(exists): self._insert_missing_rows(index) indexes = [sorted_index(self._index, x) for x in index] else: try: # all index in current index indexes = [self._index.index(x) for x in index] except ValueError: # new rows need to be added self._add_missing_rows(index) indexes = [self._index.index(x) for x in index] for x, i in enumerate(indexes): self._data[c][i] = values[x] else: # no index, only values if not isinstance(values, (list, blist)): # values not a list, turn into one of length same as index values = [values for _ in self._index] if len(values) != len(self._index): raise ValueError('values list must be at same length as current index length.') else: self._data[c] = blist(values) if self._blist else values
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L601-L656
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.set_location
def set_location(self, location, values, missing_to_none=False): """ Sets the column values, as given by the keys of the values dict, for the row at location to the values of the values dict. If missing_to_none is False then columns not in the values dict will be left unchanged, if it is True then they are set to None. This method does not add new columns and raises an error. :param location: location :param values: dict of column names as keys and the value as the value to set the row for that column to :param missing_to_none: if True set any column missing in the values to None, otherwise leave unchanged :return: nothing """ if missing_to_none: # populate the dict with None in any column missing for column in self._columns: if column not in values: values[column] = None for column in values: i = self._columns.index(column) self._data[i][location] = values[column]
python
def set_location(self, location, values, missing_to_none=False): """ Sets the column values, as given by the keys of the values dict, for the row at location to the values of the values dict. If missing_to_none is False then columns not in the values dict will be left unchanged, if it is True then they are set to None. This method does not add new columns and raises an error. :param location: location :param values: dict of column names as keys and the value as the value to set the row for that column to :param missing_to_none: if True set any column missing in the values to None, otherwise leave unchanged :return: nothing """ if missing_to_none: # populate the dict with None in any column missing for column in self._columns: if column not in values: values[column] = None for column in values: i = self._columns.index(column) self._data[i][location] = values[column]
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Sets the column values, as given by the keys of the values dict, for the row at location to the values of the values dict. If missing_to_none is False then columns not in the values dict will be left unchanged, if it is True then they are set to None. This method does not add new columns and raises an error. :param location: location :param values: dict of column names as keys and the value as the value to set the row for that column to :param missing_to_none: if True set any column missing in the values to None, otherwise leave unchanged :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L658-L677
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.append_row
def append_row(self, index, values, new_cols=True): """ Appends a row of values to the end of the data. If there are new columns in the values and new_cols is True they will be added. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param index: value of the index :param values: dictionary of values :param new_cols: if True add new columns in values, if False ignore :return: nothing """ if index in self._index: raise IndexError('index already in DataFrame') if new_cols: for col in values: if col not in self._columns: self._add_column(col) # append index value self._index.append(index) # add data values, if not in values then use None for c, col in enumerate(self._columns): self._data[c].append(values.get(col, None))
python
def append_row(self, index, values, new_cols=True): """ Appends a row of values to the end of the data. If there are new columns in the values and new_cols is True they will be added. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param index: value of the index :param values: dictionary of values :param new_cols: if True add new columns in values, if False ignore :return: nothing """ if index in self._index: raise IndexError('index already in DataFrame') if new_cols: for col in values: if col not in self._columns: self._add_column(col) # append index value self._index.append(index) # add data values, if not in values then use None for c, col in enumerate(self._columns): self._data[c].append(values.get(col, None))
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L691-L716
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.append_rows
def append_rows(self, indexes, values, new_cols=True): """ Appends rows of values to the end of the data. If there are new columns in the values and new_cols is True they will be added. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param indexes: list of indexes :param values: dictionary of values where the key is the column name and the value is a list :param new_cols: if True add new columns in values, if False ignore :return: nothing """ # check that the values data is less than or equal to the length of the indexes for column in values: if len(values[column]) > len(indexes): raise ValueError('length of %s column in values is longer than indexes' % column) # check the indexes are not duplicates combined_index = self._index + indexes if len(set(combined_index)) != len(combined_index): raise IndexError('duplicate indexes in DataFrames') if new_cols: for col in values: if col not in self._columns: self._add_column(col) # append index value self._index.extend(indexes) # add data values, if not in values then use None for c, col in enumerate(self._columns): self._data[c].extend(values.get(col, [None] * len(indexes))) self._pad_data()
python
def append_rows(self, indexes, values, new_cols=True): """ Appends rows of values to the end of the data. If there are new columns in the values and new_cols is True they will be added. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param indexes: list of indexes :param values: dictionary of values where the key is the column name and the value is a list :param new_cols: if True add new columns in values, if False ignore :return: nothing """ # check that the values data is less than or equal to the length of the indexes for column in values: if len(values[column]) > len(indexes): raise ValueError('length of %s column in values is longer than indexes' % column) # check the indexes are not duplicates combined_index = self._index + indexes if len(set(combined_index)) != len(combined_index): raise IndexError('duplicate indexes in DataFrames') if new_cols: for col in values: if col not in self._columns: self._add_column(col) # append index value self._index.extend(indexes) # add data values, if not in values then use None for c, col in enumerate(self._columns): self._data[c].extend(values.get(col, [None] * len(indexes))) self._pad_data()
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Appends rows of values to the end of the data. If there are new columns in the values and new_cols is True they will be added. Be very careful with this function as for sort DataFrames it will not enforce sort order. Use this only for speed when needed, be careful. :param indexes: list of indexes :param values: dictionary of values where the key is the column name and the value is a list :param new_cols: if True add new columns in values, if False ignore :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L718-L751
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.to_dict
def to_dict(self, index=True, ordered=False): """ Returns a dict where the keys are the column names and the values are lists of the values for that column. :param index: If True then include the index in the dict with the index_name as the key :param ordered: If True then return an OrderedDict() to preserve the order of the columns in the DataFrame :return: dict or OrderedDict() """ result = OrderedDict() if ordered else dict() if index: result.update({self._index_name: self._index}) if ordered: data_dict = [(column, self._data[i]) for i, column in enumerate(self._columns)] else: data_dict = {column: self._data[i] for i, column in enumerate(self._columns)} result.update(data_dict) return result
python
def to_dict(self, index=True, ordered=False): """ Returns a dict where the keys are the column names and the values are lists of the values for that column. :param index: If True then include the index in the dict with the index_name as the key :param ordered: If True then return an OrderedDict() to preserve the order of the columns in the DataFrame :return: dict or OrderedDict() """ result = OrderedDict() if ordered else dict() if index: result.update({self._index_name: self._index}) if ordered: data_dict = [(column, self._data[i]) for i, column in enumerate(self._columns)] else: data_dict = {column: self._data[i] for i, column in enumerate(self._columns)} result.update(data_dict) return result
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Returns a dict where the keys are the column names and the values are lists of the values for that column. :param index: If True then include the index in the dict with the index_name as the key :param ordered: If True then return an OrderedDict() to preserve the order of the columns in the DataFrame :return: dict or OrderedDict()
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L833-L849
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.to_json
def to_json(self): """ Returns a JSON of the entire DataFrame that can be reconstructed back with raccoon.from_json(input). Any object that cannot be serialized will be replaced with the representation of the object using repr(). In that instance the DataFrame will have a string representation in place of the object and will not reconstruct exactly. :return: json string """ input_dict = {'data': self.to_dict(index=False), 'index': list(self._index)} # if blist, turn into lists if self.blist: input_dict['index'] = list(input_dict['index']) for key in input_dict['data']: input_dict['data'][key] = list(input_dict['data'][key]) meta_data = dict() for key in self.__slots__: if key not in ['_data', '_index']: value = self.__getattribute__(key) meta_data[key.lstrip('_')] = value if not isinstance(value, blist) else list(value) meta_data['use_blist'] = meta_data.pop('blist') input_dict['meta_data'] = meta_data return json.dumps(input_dict, default=repr)
python
def to_json(self): """ Returns a JSON of the entire DataFrame that can be reconstructed back with raccoon.from_json(input). Any object that cannot be serialized will be replaced with the representation of the object using repr(). In that instance the DataFrame will have a string representation in place of the object and will not reconstruct exactly. :return: json string """ input_dict = {'data': self.to_dict(index=False), 'index': list(self._index)} # if blist, turn into lists if self.blist: input_dict['index'] = list(input_dict['index']) for key in input_dict['data']: input_dict['data'][key] = list(input_dict['data'][key]) meta_data = dict() for key in self.__slots__: if key not in ['_data', '_index']: value = self.__getattribute__(key) meta_data[key.lstrip('_')] = value if not isinstance(value, blist) else list(value) meta_data['use_blist'] = meta_data.pop('blist') input_dict['meta_data'] = meta_data return json.dumps(input_dict, default=repr)
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L851-L874
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.rename_columns
def rename_columns(self, rename_dict): """ Renames the columns :param rename_dict: dict where the keys are the current column names and the values are the new names :return: nothing """ if not all([x in self._columns for x in rename_dict.keys()]): raise ValueError('all dictionary keys must be in current columns') for current in rename_dict.keys(): self._columns[self._columns.index(current)] = rename_dict[current]
python
def rename_columns(self, rename_dict): """ Renames the columns :param rename_dict: dict where the keys are the current column names and the values are the new names :return: nothing """ if not all([x in self._columns for x in rename_dict.keys()]): raise ValueError('all dictionary keys must be in current columns') for current in rename_dict.keys(): self._columns[self._columns.index(current)] = rename_dict[current]
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Renames the columns :param rename_dict: dict where the keys are the current column names and the values are the new names :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L876-L886
rsheftel/raccoon
raccoon/dataframe.py
DataFrame.delete_all_rows
def delete_all_rows(self): """ Deletes the contents of all rows in the DataFrame. This function is faster than delete_rows() to remove all information, and at the same time it keeps the container lists for the columns and index so if there is another object that references this DataFrame, like a ViewSeries, the reference remains in tact. :return: nothing """ del self._index[:] for c in range(len(self._columns)): del self._data[c][:]
python
def delete_all_rows(self): """ Deletes the contents of all rows in the DataFrame. This function is faster than delete_rows() to remove all information, and at the same time it keeps the container lists for the columns and index so if there is another object that references this DataFrame, like a ViewSeries, the reference remains in tact. :return: nothing """ del self._index[:] for c in range(len(self._columns)): del self._data[c][:]
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Deletes the contents of all rows in the DataFrame. This function is faster than delete_rows() to remove all information, and at the same time it keeps the container lists for the columns and index so if there is another object that references this DataFrame, like a ViewSeries, the reference remains in tact. :return: nothing
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train
https://github.com/rsheftel/raccoon/blob/e5c4b5fb933b51f33aff11e8168c39790e9a7c75/raccoon/dataframe.py#L933-L943