Historical retrieval without an entity dataframe

Is your feature request related to a problem? Please describe. The current Feast get_historical_features() method requires that users provide an entity dataframe as follows

training_df = store.get_historical_features(
    entity_df=entity_df, 
    feature_refs = [
        'drivers_activity:trips_today'
        'drivers_profile:rating'
    ],
)

However, many users would like the feature store to provide entities to them for training, instead of having to query or provide entities as part of the entity dataframe.

Describe the solution you’d like Allow users to specify an existing feature view from which an entity dataframe will be queried.

training_df = store.get_historical_features(
    entity_df="drivers_activity", 
    feature_refs = [
        'drivers_activity:trips_today'
        'drivers_profile:rating'
    ],
)

With the addition of time range filtering.

training_df = store.get_historical_features(
    entity_df="drivers_activity", 
    feature_refs = [
        'drivers_activity:trips_today'
        'drivers_profile:rating'
    ],
    from_date=(today - timedelta(days = 7)),
    to_date=datetime.now(),
)

[lara-marinelli]

Any workaround for the problem of getting “training datasets” (with no passing entity ids)?

[fcas]

(2) Any workaround for the problem of getting “training datasets” (with no passing entity ids)?