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# Copyright 2022 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
,
Optional
from
typeguard
import
typechecked
from
feast
.
feature
import
Feature
from
feast
.
protos
.
feast
.
core
.
Feature_pb2
import
FeatureSpecV2
as
FieldProto
from
feast
.
types
import
FeastType
,
from_value_type
from
feast
.
value_type
import
ValueType
@
typechecked
class
Field
:
"""
A Field represents a set of values with the same structure.
Attributes:
name: The name of the field.
dtype: The type of the field, such as string or float.
description: A human-readable description.
tags: User-defined metadata in dictionary form.
vector_index: If set to True the field will be indexed for vector similarity search.
vector_length: The length of the vector if the vector index is set to True.
vector_search_metric: The metric used for vector similarity search.
"""
name
:
str
dtype
:
FeastType
description
:
str
tags
:
Dict
[
str
,
str
]
vector_index
:
bool
vector_length
:
int
vector_search_metric
:
Optional
[
str
]
def
__init__
(
self
,
*
,
name
:
str
,
dtype
:
FeastType
,
description
:
str
=
""
,
tags
:
Optional
[
Dict
[
str
,
str
]]
=
None
,
vector_index
:
bool
=
False
,
vector_length
:
int
=
0
,
vector_search_metric
:
Optional
[
str
]
=
None
,
):
"""
Creates a Field object.
Args:
name: The name of the field.
dtype: The type of the field, such as string or float.
description (optional): A human-readable description.
tags (optional): User-defined metadata in dictionary form.
vector_index (optional): If set to True the field will be indexed for vector similarity search.
vector_search_metric (optional): The metric used for vector similarity search.
"""
self
.
name
=
name
self
.
dtype
=
dtype
self
.
description
=
description
self
.
tags
=
tags
or
{}
self
.
vector_index
=
vector_index
self
.
vector_length
=
vector_length
self
.
vector_search_metric
=
vector_search_metric
def
__eq__
(
self
,
other
):
if
type
(
self
)
!=
type
(
other
):
return
False
if
(
self
.
name
!=
other
.
name
or
self
.
dtype
!=
other
.
dtype
or
self
.
description
!=
other
.
description
or
self
.
tags
!=
other
.
tags
or
self
.
vector_length
!=
other
.
vector_length
# or self.vector_index != other.vector_index
# or self.vector_search_metric != other.vector_search_metric
):
return
False
return
True
def
__hash__
(
self
):
return
hash
((
self
.
name
,
hash
(
self
.
dtype
)))
def
__lt__
(
self
,
other
):
return
self
.
name
<
other
.
name
def
__repr__
(
self
):
return
(
f"Field(
\n
"
f" name=
{
self
.
name
!r
}
,
\n
"
f" dtype=
{
self
.
dtype
!r
}
,
\n
"
f" description=
{
self
.
description
!r
}
,
\n
"
f" tags=
{
self
.
tags
!r
}
\n
"
f" vector_index=
{
self
.
vector_index
!r
}
\n
"
f" vector_length=
{
self
.
vector_length
!r
}
\n
"
f" vector_search_metric=
{
self
.
vector_search_metric
!r
}
\n
"
f")"
)
def
__str__
(
self
):
return
f"Field(name=
{
self
.
name
}
, dtype=
{
self
.
dtype
}
, tags=
{
self
.
tags
}
)"
def
to_proto
(
self
)
->
FieldProto
:
"""Converts a Field object to its protobuf representation."""
value_type
=
self
.
dtype
.
to_value_type
()
vector_search_metric
=
self
.
vector_search_metric
or
""
return
FieldProto
(
name
=
self
.
name
,
value_type
=
value_type
.
value
,
description
=
self
.
description
,
tags
=
self
.
tags
,
vector_index
=
self
.
vector_index
,
vector_length
=
self
.
vector_length
,
vector_search_metric
=
vector_search_metric
,
)
@
classmethod
def
from_proto
(
cls
,
field_proto
:
FieldProto
):
"""
Creates a Field object from a protobuf representation.
Args:
field_proto: FieldProto protobuf object
"""
value_type
=
ValueType
(
field_proto
.
value_type
)
vector_search_metric
=
getattr
(
field_proto
,
"vector_search_metric"
,
""
)
vector_index
=
getattr
(
field_proto
,
"vector_index"
,
False
)
vector_length
=
getattr
(
field_proto
,
"vector_length"
,
0
)
return
cls
(
name
=
field_proto
.
name
,
dtype
=
from_value_type
(
value_type
=
value_type
),
tags
=
dict
(
field_proto
.
tags
),
description
=
field_proto
.
description
,
vector_index
=
vector_index
,
vector_length
=
vector_length
,
vector_search_metric
=
vector_search_metric
,
)
@
classmethod
def
from_feature
(
cls
,
feature
:
Feature
):
"""
Creates a Field object from a Feature object.
Args:
feature: Feature object to convert.
"""
return
cls
(
name
=
feature
.
name
,
dtype
=
from_value_type
(
feature
.
dtype
),
description
=
feature
.
description
,
tags
=
feature
.
labels
,
)
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