class documentation
class JoinDataSource(CodableBatchDataSource): (source)
Undocumented
Method | all |
Undocumented |
Method | all |
Undocumented |
Method | all |
Undocumented |
Method | depends |
Undocumented |
Async Method | freshness |
.table("my_table") .freshness() |
Method | job |
A key defining which sources can be grouped together in one request. |
Method | join |
Undocumented |
Async Method | schema |
Returns the schema for the data source |
Class Variable | left |
Undocumented |
Class Variable | left |
Undocumented |
Class Variable | method |
Undocumented |
Class Variable | right |
Undocumented |
Class Variable | right |
Undocumented |
Class Variable | right |
Undocumented |
Class Variable | source |
Undocumented |
Class Variable | type |
Undocumented |
Inherited from CodableBatchDataSource
:
Class Method | _deserialize |
Undocumented |
Method | _serialize |
Undocumented |
Inherited from BatchDataSource
(via CodableBatchDataSource
):
Class Method | multi |
Undocumented |
Method | __hash__ |
Undocumented |
Method | all |
Undocumented |
Method | all |
Undocumented |
Async Method | feature |
Setup the code needed to represent the data source as a feature view |
Method | features |
Undocumented |
Method | filter |
Undocumented |
Method | location |
Undocumented |
Method | source |
An id that identifies a source from others. |
Method | tags |
Undocumented |
Method | transform |
Undocumented |
Method | with |
Undocumented |
Method | with |
Undocumented |
def all_between_dates(self, request:
RetrivalRequest
, start_date: datetime
, end_date: datetime
) -> RetrivalJob
:
(source)
¶
Undocumented
def join(self, view:
Any
, on: str | FeatureFactory | list[ str] | list[ FeatureFactory] | None
= None, on_left: str | FeatureFactory | list[ str] | list[ FeatureFactory] | None
= None, on_right: str | FeatureFactory | list[ str] | list[ FeatureFactory] | None
= None, how: str
= 'inner') -> JoinDataSource
:
(source)
¶
Undocumented
Returns the schema for the data source
`python source = FileSource.parquet_at('test_data/titanic.parquet') schema = await source.schema() >>> {'passenger_id': FeatureType(name='int64'), ...} `
- Returns:
- dict[str, FeatureType]: A dictionary containing the column name and the feature type