def to_proto(self) -> FeatureViewProto:
"""
Converts an feature view object to its protobuf representation.
Returns:
FeatureViewProto protobuf
"""
meta = FeatureViewMetaProto(
created_timestamp=self.created_timestamp,
last_updated_timestamp=self.last_updated_timestamp,
)
if self.ttl is not None:
ttl_duration = Duration()
ttl_duration.FromTimedelta(self.ttl)
spec = FeatureViewSpecProto(
name=self.name,
entities=self.entities,
features=[feature.to_proto() for feature in self.features],
tags=self.tags,
ttl=(ttl_duration if ttl_duration is not None else None),
online=self.online,
input=self.input.to_proto(),
)
return FeatureViewProto(spec=spec, meta=meta)
def to_proto(self) -> FeatureViewProto:
"""
Converts an feature view object to its protobuf representation.
Returns:
FeatureViewProto protobuf
"""
meta = FeatureViewMetaProto(
created_timestamp=self.created_timestamp,
last_updated_timestamp=self.last_updated_timestamp,
materialization_intervals=[],
)
for interval in self.materialization_intervals:
interval_proto = MaterializationIntervalProto()
interval_proto.start_time.FromDatetime(interval[0])
interval_proto.end_time.FromDatetime(interval[1])
meta.materialization_intervals.append(interval_proto)
ttl_duration = None
if self.ttl is not None:
ttl_duration = Duration()
ttl_duration.FromTimedelta(self.ttl)
spec = FeatureViewSpecProto(
name=self.name,
entities=self.entities,
features=[feature.to_proto() for feature in self.features],
tags=self.tags,
ttl=(ttl_duration if ttl_duration is not None else None),
online=self.online,
input=self.input.to_proto(),
)
return FeatureViewProto(spec=spec, meta=meta)
def to_proto(self) -> FeatureViewProto:
"""
Converts a feature view object to its protobuf representation.
Returns:
A FeatureViewProto protobuf.
"""
meta = FeatureViewMetaProto(materialization_intervals=[])
if self.created_timestamp:
meta.created_timestamp.FromDatetime(self.created_timestamp)
if self.last_updated_timestamp:
meta.last_updated_timestamp.FromDatetime(
self.last_updated_timestamp)
for interval in self.materialization_intervals:
interval_proto = MaterializationIntervalProto()
interval_proto.start_time.FromDatetime(interval[0])
interval_proto.end_time.FromDatetime(interval[1])
meta.materialization_intervals.append(interval_proto)
ttl_duration = None
if self.ttl is not None:
ttl_duration = Duration()
ttl_duration.FromTimedelta(self.ttl)
batch_source_proto = self.batch_source.to_proto()
batch_source_proto.data_source_class_type = f"{self.batch_source.__class__.__module__}.{self.batch_source.__class__.__name__}"
stream_source_proto = None
if self.stream_source:
stream_source_proto = self.stream_source.to_proto()
stream_source_proto.data_source_class_type = f"{self.stream_source.__class__.__module__}.{self.stream_source.__class__.__name__}"
spec = FeatureViewSpecProto(
name=self.name,
entities=self.entities,
features=[field.to_proto() for field in self.schema],
description=self.description,
tags=self.tags,
owner=self.owner,
ttl=(ttl_duration if ttl_duration is not None else None),
online=self.online,
batch_source=batch_source_proto,
stream_source=stream_source_proto,
)
return FeatureViewProto(spec=spec, meta=meta)