def description_to_entityset(description, **kwargs):
'''Deserialize entityset from data description.
Args:
description (dict) : Description of an :class:`.EntitySet`. Likely generated using :meth:`.serialize.entityset_to_description`
kwargs (keywords): Additional keyword arguments to pass as keywords arguments to the underlying deserialization method.
Returns:
entityset (EntitySet) : Instance of :class:`.EntitySet`.
'''
check_schema_version(description, 'entityset')
from featuretools.entityset import EntitySet
# If data description was not read from disk, path is None.
path = description.get('path')
entityset = EntitySet(description['id'])
last_time_index = []
for entity in description['entities'].values():
entity['loading_info']['params'].update(kwargs)
# If path is None, an empty dataframe will be created for entity.
description_to_entity(entity, entityset, path=path)
if entity['properties']['last_time_index']:
last_time_index.append(entity['id'])
for relationship in description['relationships']:
relationship = Relationship.from_dictionary(relationship, entityset)
entityset.add_relationship(relationship)
if len(last_time_index):
entityset.add_last_time_indexes(updated_entities=last_time_index)
return entityset
def description_to_entityset(description, **kwargs):
'''Deserialize entityset from data description.
Args:
description (dict) : Description of an :class:`.EntitySet`. Likely generated using :meth:`.serialize.entityset_to_description`
kwargs (keywords): Additional keyword arguments to pass as keywords arguments to the underlying deserialization method.
Returns:
entityset (EntitySet) : Instance of :class:`.EntitySet`.
'''
check_schema_version(description, 'entityset')
from featuretools.entityset import EntitySet
# If data description was not read from disk, path is None.
path = description.get('path')
entityset = EntitySet(description['id'])
for df in description['dataframes'].values():
if path is not None:
data_path = os.path.join(path, 'data', df['name'])
dataframe = read_woodwork_table(data_path,
validate=False,
**kwargs)
else:
dataframe = empty_dataframe(df)
entityset.add_dataframe(dataframe)
for relationship in description['relationships']:
rel = Relationship.from_dictionary(relationship, entityset)
entityset.add_relationship(relationship=rel)
return entityset
def from_dictionary(cls, arguments, entityset, dependencies, primitive):
base_features = [dependencies[name] for name in arguments["base_features"]]
relationship_path = [
Relationship.from_dictionary(r, entityset)
for r in arguments["relationship_path"]
]
parent_dataframe_name = relationship_path[0].parent_dataframe.ww.name
relationship_path = RelationshipPath([(False, r) for r in relationship_path])
use_previous_data = arguments["use_previous"]
use_previous = use_previous_data and Timedelta.from_dictionary(
use_previous_data
)
where_name = arguments["where"]
where = where_name and dependencies[where_name]
feat = cls(
base_features=base_features,
parent_dataframe_name=parent_dataframe_name,
primitive=primitive,
relationship_path=relationship_path,
use_previous=use_previous,
where=where,
name=arguments["name"],
)
feat._names = arguments.get("feature_names")
return feat
def from_dictionary(cls, arguments, entityset, dependencies,
primitives_deserializer):
base_features = [
dependencies[name] for name in arguments['base_features']
]
relationship_path = [
Relationship.from_dictionary(r, entityset)
for r in arguments['relationship_path']
]
parent_dataframe_name = relationship_path[0].parent_dataframe.ww.name
relationship_path = RelationshipPath([(False, r)
for r in relationship_path])
primitive = primitives_deserializer.deserialize_primitive(
arguments['primitive'])
use_previous_data = arguments['use_previous']
use_previous = use_previous_data and Timedelta.from_dictionary(
use_previous_data)
where_name = arguments['where']
where = where_name and dependencies[where_name]
return cls(base_features=base_features,
parent_dataframe_name=parent_dataframe_name,
primitive=primitive,
relationship_path=relationship_path,
use_previous=use_previous,
where=where,
name=arguments['name'])
def from_dictionary(cls, arguments, entityset, dependencies,
primitives_deserializer):
base_feature = dependencies[arguments['base_feature']]
relationship = Relationship.from_dictionary(arguments['relationship'],
entityset)
child_dataframe_name = relationship.child_dataframe.ww.name
return cls(base_feature=base_feature,
child_dataframe_name=child_dataframe_name,
relationship=relationship,
name=arguments['name'])
def test_relationship_serialization(es):
relationship = Relationship(es, 'sessions', 'id', 'log', 'session_id')
dictionary = {
'parent_dataframe_name': 'sessions',
'parent_column_name': 'id',
'child_dataframe_name': 'log',
'child_column_name': 'session_id',
}
assert relationship.to_dictionary() == dictionary
assert Relationship.from_dictionary(dictionary, es) == relationship
def test_relationship_serialization(es):
relationship = Relationship(es['sessions']['id'], es['log']['session_id'])
dictionary = {
'parent_entity_id': 'sessions',
'parent_variable_id': 'id',
'child_entity_id': 'log',
'child_variable_id': 'session_id',
}
assert relationship.to_dictionary() == dictionary
assert Relationship.from_dictionary(dictionary, es) == relationship
def test_relationship_serialization(es):
relationship = Relationship(es, "sessions", "id", "log", "session_id")
dictionary = {
"parent_dataframe_name": "sessions",
"parent_column_name": "id",
"child_dataframe_name": "log",
"child_column_name": "session_id",
}
assert relationship.to_dictionary() == dictionary
assert Relationship.from_dictionary(dictionary, es) == relationship
def from_dictionary(cls, arguments, entityset, dependencies, primitive):
base_feature = dependencies[arguments["base_feature"]]
relationship = Relationship.from_dictionary(
arguments["relationship"], entityset
)
child_dataframe_name = relationship.child_dataframe.ww.name
return cls(
base_feature=base_feature,
child_dataframe_name=child_dataframe_name,
relationship=relationship,
name=arguments["name"],
)
def description_to_entityset(description, **kwargs):
"""Deserialize entityset from data description.
Args:
description (dict) : Description of an :class:`.EntitySet`. Likely generated using :meth:`.serialize.entityset_to_description`
kwargs (keywords): Additional keyword arguments to pass as keywords arguments to the underlying deserialization method.
Returns:
entityset (EntitySet) : Instance of :class:`.EntitySet`.
"""
check_schema_version(description, "entityset")
from featuretools.entityset import EntitySet
# If data description was not read from disk, path is None.
path = description.get("path")
entityset = EntitySet(description["id"])
for df in description["dataframes"].values():
if path is not None:
data_path = os.path.join(path, "data", df["name"])
format = description.get("format")
if format is not None:
kwargs["format"] = format
if format == "parquet" and df["loading_info"][
"table_type"] == "pandas":
kwargs["filename"] = df["name"] + ".parquet"
dataframe = read_woodwork_table(data_path,
validate=False,
**kwargs)
else:
dataframe = empty_dataframe(df)
entityset.add_dataframe(dataframe)
for relationship in description["relationships"]:
rel = Relationship.from_dictionary(relationship, entityset)
entityset.add_relationship(relationship=rel)
return entityset
