Module markov.api.data.data_family

Classes

class AllDataFamilyResponse (data_families: List[DataFamily], count: int, return_code: str, message: str)

AllDataFamilyResponse(data_families: 'List[DataFamily]', count: 'int', return_code: 'str', message: 'str')

Class variables

var count : int

var data_families : List[DataFamily]

var message : str

var return_code : str

Static methods

def from_dict(kvs: Union[dict, list, str, int, float, bool, ForwardRef(None)], *, infer_missing=False) ‑> ~A

def from_json(s: Union[str, bytes, bytearray], *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) ‑> ~A

def schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) ‑> dataclasses_json.mm.SchemaF[~A]

Methods

def get_dict(self) ‑> Dict

def get_json(self) ‑> str

def to_dict(self, encode_json=False) ‑> Dict[str, Union[dict, list, str, int, float, bool, ForwardRef(None)]]

def to_json(self, *, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: Union[int, str, ForwardRef(None)] = None, separators: Optional[Tuple[str, str]] = None, default: Optional[Callable] = None, sort_keys: bool = False, **kw) ‑> str

class DSForDataFamilyResponse (ds_info: List[DSNameIdTuple], return_code: str, message: str)

DSForDataFamilyResponse(ds_info: 'List[DSNameIdTuple]', return_code: 'str', message: 'str')

Class variables

var ds_info : List[DSNameIdTuple]

var message : str

var return_code : str

Static methods

def from_dict(kvs: Union[dict, list, str, int, float, bool, ForwardRef(None)], *, infer_missing=False) ‑> ~A

def from_json(s: Union[str, bytes, bytearray], *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) ‑> ~A

def schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) ‑> dataclasses_json.mm.SchemaF[~A]

Methods

def to_dict(self, encode_json=False) ‑> Dict[str, Union[dict, list, str, int, float, bool, ForwardRef(None)]]

def to_json(self, *, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: Union[int, str, ForwardRef(None)] = None, separators: Optional[Tuple[str, str]] = None, default: Optional[Callable] = None, sort_keys: bool = False, **kw) ‑> str

class DSNameIdTuple (name: str, ds_id: str)

DSNameIdTuple(name: 'str', ds_id: 'str')

Class variables

var ds_id : str

var name : str

Static methods

def from_dict(kvs: Union[dict, list, str, int, float, bool, ForwardRef(None)], *, infer_missing=False) ‑> ~A

def from_json(s: Union[str, bytes, bytearray], *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) ‑> ~A

def schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) ‑> dataclasses_json.mm.SchemaF[~A]

Methods

def to_dict(self, encode_json=False) ‑> Dict[str, Union[dict, list, str, int, float, bool, ForwardRef(None)]]

def to_json(self, *, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: Union[int, str, ForwardRef(None)] = None, separators: Optional[Tuple[str, str]] = None, default: Optional[Callable] = None, sort_keys: bool = False, **kw) ‑> str

class DataFamily (name: str, notes: str, create_date: str = '', user_id: Optional[str] = '', team_id: Optional[str] = '', norm_name: Optional[str] = '', record_id: Optional[str] = '', workspace_id: Optional[str] = '', df_id: Optional[str] = '', misc: Optional[dict] = <factory>)

Represents a high level collection of DataSets that solve similar purpose and have similar expected behavior. This object is returned after a DataFamily is registered with Markov

Ex

CreditCardFraudFamily en-US would contain all the english US datasets for CreditCardFraud in the US.

Class variables

var create_date : str

var df_id : Optional[str]

variable key value args ({key:value} that you want to store alongside datafamily)

var misc : Optional[dict]

var name : str

Short description of what this datafamily is all about. This would help your fellow team mates to understand the purpose of this datafamily.

var norm_name : Optional[str]

var notes : str

var record_id : Optional[str]

var team_id : Optional[str]

var user_id : Optional[str]

var workspace_id : Optional[str]

Uniquely identify the DataFamily with Markov

Static methods

def create_from_dict(json_dict: Dict) ‑> DataFamily

Create the DataFamily from a serialized dictionary of this object.

Args

json_dict: Returns:

def create_from_json(json_str: str)

Create the DataFamily from Serialized JSON String.

Args

json_str : str

Serialized JSON String to fetch the dataFamily.

Returns

DataFamily instance

def from_dict(kvs: Union[dict, list, str, int, float, bool, ForwardRef(None)], *, infer_missing=False) ‑> ~A

def from_json(s: Union[str, bytes, bytearray], *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) ‑> ~A

def get_by_id(df_id: str)

Given the datafamily_id, get the datafamily if it exists

Args

df_id : str

datafamily_id to get DataFamily from if it exists. This should be a valid id

Returns

DataFamily instance

def get_by_name(name)

Given the name, get the datafamily if it exists

Args

name : str

name of the datafamily

Returns

DataFamily instance

def schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) ‑> dataclasses_json.mm.SchemaF[~A]

Instance variables

prop default_schema

Returns

Return the default (active) schema of this datafamily

Methods

def add_details(self, details: dict)

Flexible user specific key value pair of information to be stored with DataFamily with MarkovML

Args

details : dict

key-value pair to store custom key-value field with MarkovML

Returns

None

def clone(self) ‑> DataFamily

Clone into a separate DataFamily Object without unique identifier

def dataset_summary(self) ‑> List[DSNameIdTuple]

For the given DataFamily Return the list of Dataset NameID tuple which contains dataset name and ds_id

Returns

DSNameIdTuple tuple with name and ds_id

def get_dict(self) ‑> Dict

def get_json(self) ‑> str

def register(self) ‑> DataFamilyRegistrationResponse

def to_dict(self, encode_json=False) ‑> Dict[str, Union[dict, list, str, int, float, bool, ForwardRef(None)]]

def to_json(self, *, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: Union[int, str, ForwardRef(None)] = None, separators: Optional[Tuple[str, str]] = None, default: Optional[Callable] = None, sort_keys: bool = False, **kw) ‑> str

def update_default_data_schema(self, data_schema: DataSchema)

Get the default DataSchema of this data_set Family. Each DataFamily has an active schema and prior schemas. Schema is computed automatically from the DataSets registered and if there is a schema change, user is prompted to verify with an option to activate the new schema.

Args

data_schema : DataSchema

Add a new active schema to this DataFamily.

class DataFamilyRegistrationResponse (df_id: str, return_code: str, message: str, create_date: Optional[str])

DataFamilyRegistrationResponse(df_id: 'str', return_code: 'str', message: 'str', create_date: 'Optional[str]')

Class variables

var create_date : Optional[str]

var df_id : str

var message : str

var return_code : str

Static methods

def create_from_dict(value: Dict) ‑> DataFamilyRegistrationResponse

def create_from_json(value: str) ‑> DataFamilyRegistrationResponse

def from_dict(kvs: Union[dict, list, str, int, float, bool, ForwardRef(None)], *, infer_missing=False) ‑> ~A

def from_json(s: Union[str, bytes, bytearray], *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) ‑> ~A

def schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) ‑> dataclasses_json.mm.SchemaF[~A]

Methods

def get_dict(self) ‑> Dict

def get_json(self) ‑> str

def to_dict(self, encode_json=False) ‑> Dict[str, Union[dict, list, str, int, float, bool, ForwardRef(None)]]

def to_json(self, *, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: Union[int, str, ForwardRef(None)] = None, separators: Optional[Tuple[str, str]] = None, default: Optional[Callable] = None, sort_keys: bool = False, **kw) ‑> str

class DataFamilyResponse (record: DataFamily, return_code: str = 'COMMAND_FAILED', message: Optional[str] = '')

DataFamilyResponse(record: 'DataFamily', return_code: 'str' = 'COMMAND_FAILED', message: 'Optional[str]' = '')

Class variables

var message : Optional[str]

var record : DataFamily

var return_code : str

Static methods

def from_dict(kvs: Union[dict, list, str, int, float, bool, ForwardRef(None)], *, infer_missing=False) ‑> ~A

def from_json(s: Union[str, bytes, bytearray], *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw) ‑> ~A

def schema(*, infer_missing: bool = False, only=None, exclude=(), many: bool = False, context=None, load_only=(), dump_only=(), partial: bool = False, unknown=None) ‑> dataclasses_json.mm.SchemaF[~A]

Methods

def get_dict(self) ‑> Dict

def get_json(self) ‑> str

def to_dict(self, encode_json=False) ‑> Dict[str, Union[dict, list, str, int, float, bool, ForwardRef(None)]]

def to_json(self, *, skipkeys: bool = False, ensure_ascii: bool = True, check_circular: bool = True, allow_nan: bool = True, indent: Union[int, str, ForwardRef(None)] = None, separators: Optional[Tuple[str, str]] = None, default: Optional[Callable] = None, sort_keys: bool = False, **kw) ‑> str