forked from feast-dev/feast
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathfeature.py
More file actions
196 lines (158 loc) · 5.8 KB
/
Copy pathfeature.py
File metadata and controls
196 lines (158 loc) · 5.8 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
# 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 Dict, List, Optional
from feast.protos.feast.core.Feature_pb2 import FeatureSpecV2 as FeatureSpecProto
from feast.protos.feast.serving.ServingService_pb2 import (
FeatureReferenceV2 as FeatureRefProto,
)
from feast.protos.feast.types import Value_pb2 as ValueTypeProto
from feast.value_type import ValueType
class Feature:
"""
A Feature represents a class of serveable feature.
Args:
name: Name of the feature.
dtype: The type of the feature, such as string or float.
labels (optional): User-defined metadata in dictionary form.
"""
def __init__(
self, name: str, dtype: ValueType, labels: Optional[Dict[str, str]] = None,
):
"""Creates a Feature object."""
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()
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
def __repr__(self):
# return string representation of the reference
return self.name
def __str__(self):
# readable string of the reference
return f"Feature<{self.__repr__()}>"
@property
def name(self):
"""
Gets the name of this feature.
"""
return self._name
@property
def dtype(self) -> ValueType:
"""
Gets the data type of this feature.
"""
return self._dtype
@property
def labels(self) -> Dict[str, str]:
"""
Gets the labels of this feature.
"""
return self._labels
def to_proto(self) -> FeatureSpecProto:
"""
Converts Feature object to its Protocol Buffer representation.
Returns:
A FeatureSpecProto protobuf.
"""
value_type = ValueTypeProto.ValueType.Enum.Value(self.dtype.name)
return FeatureSpecProto(
name=self.name, value_type=value_type, labels=self.labels,
)
@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=dict(feature_proto.labels),
)
return feature
class FeatureRef:
""" Feature Reference represents a reference to a specific feature. """
def __init__(self, name: str, feature_table: str):
self.proto = FeatureRefProto(name=name, feature_table=feature_table)
@classmethod
def from_proto(cls, proto: FeatureRefProto):
"""
Construct a feature reference from the given FeatureReference proto
Args:
proto: Protobuf FeatureReference to construct from
Returns:
FeatureRef that refers to the given feature
"""
return cls(name=proto.name, feature_table=proto.feature_table)
@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)
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