# Copyright 2020 The Feast Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import List, MutableMapping, Optional
from feast.core.Feature_pb2 import FeatureSpecV2 as FeatureSpecProto
from feast.serving.ServingService_pb2 import FeatureReferenceV2 as FeatureRefProto
from feast.types import Value_pb2 as ValueTypeProto
from feast.value_type import ValueType
[docs]class Feature:
"""Feature field type"""
def __init__(
self,
name: str,
dtype: ValueType,
labels: Optional[MutableMapping[str, str]] = None,
):
self._name = name
if not isinstance(dtype, ValueType):
raise ValueError("dtype is not a valid ValueType")
self._dtype = dtype
if labels is None:
self._labels = dict() # type: MutableMapping
else:
self._labels = labels
def __eq__(self, other):
if (
self.name != other.name
or self.dtype != other.dtype
or self.labels != other.labels
):
return False
return True
def __lt__(self, other):
return self.name < other.name
@property
def name(self):
"""
Getter for name of this field
"""
return self._name
@property
def dtype(self) -> ValueType:
"""
Getter for data type of this field
"""
return self._dtype
@property
def labels(self) -> MutableMapping[str, str]:
"""
Getter for labels of this field
"""
return self._labels
[docs] def to_proto(self) -> FeatureSpecProto:
"""Converts Feature object to its Protocol Buffer representation"""
value_type = ValueTypeProto.ValueType.Enum.Value(self.dtype.name)
return FeatureSpecProto(
name=self.name, value_type=value_type, labels=self.labels,
)
[docs] @classmethod
def from_proto(cls, feature_proto: FeatureSpecProto):
"""
Args:
feature_proto: FeatureSpecV2 protobuf object
Returns:
Feature object
"""
feature = cls(
name=feature_proto.name,
dtype=ValueType(feature_proto.value_type),
labels=feature_proto.labels,
)
return feature
[docs]class FeatureRef:
""" Feature Reference represents a reference to a specific feature. """
def __init__(self, name: str, feature_table: str = None):
self.proto = FeatureRefProto(name=name, feature_table=feature_table)
[docs] @classmethod
def from_proto(cls, proto: FeatureRefProto):
"""
Construct a feature reference from the given FeatureReference proto
Arg:
proto: Protobuf FeatureReference to construct from
Returns:
FeatureRef that refers to the given feature
"""
return cls(name=proto.name, feature_table=proto.feature_table)
[docs] @classmethod
def from_str(cls, feature_ref_str: str):
"""
Parse the given string feature reference into FeatureRef model
String feature reference should be in the format feature_table:feature.
Where "feature_table" and "name" are the feature_table name and feature name
respectively.
Args:
feature_ref_str: String representation of the feature reference
Returns:
FeatureRef that refers to the given feature
"""
proto = FeatureRefProto()
# parse feature table name if specified
if ":" in feature_ref_str:
proto.feature_table, proto.name = feature_ref_str.split(":")
else:
raise ValueError(
f"Unsupported feature reference: {feature_ref_str} - Feature reference string should be in the form [featuretable_name:featurename]"
)
return cls.from_proto(proto)
[docs] def to_proto(self) -> FeatureRefProto:
"""
Convert and return this feature table reference to protobuf.
Returns:
Protobuf respresentation of this feature table reference.
"""
return self.proto
def __repr__(self):
# return string representation of the reference
ref_str = self.proto.feature_table + ":" + self.proto.name
return ref_str
def __str__(self):
# readable string of the reference
return f"FeatureRef<{self.__repr__()}>"
def _build_feature_references(feature_ref_strs: List[str]) -> List[FeatureRefProto]:
"""
Builds a list of FeatureReference protos from a list of FeatureReference strings
Args:
feature_ref_strs: List of string feature references
Returns:
A list of FeatureReference protos parsed from args.
"""
feature_refs = [FeatureRef.from_str(ref_str) for ref_str in feature_ref_strs]
feature_ref_protos = [ref.to_proto() for ref in feature_refs]
return feature_ref_protos