# -*- coding: utf-8 -*-
# Copyright 2024 Google LLC
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# 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
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#     http://www.apache.org/licenses/LICENSE-2.0
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# 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.
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# limitations under the License.
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from __future__ import annotations

from typing import MutableMapping, MutableSequence

import proto  # type: ignore

from google.cloud.aiplatform_v1.types import feature_monitoring_stats
from google.protobuf import timestamp_pb2  # type: ignore


__protobuf__ = proto.module(
    package="google.cloud.aiplatform.v1",
    manifest={
        "Feature",
    },
)


class Feature(proto.Message):
    r"""Feature Metadata information.
    For example, color is a feature that describes an apple.

    Attributes:
        name (str):
            Immutable. Name of the Feature. Format:
            ``projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}``
            ``projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}``

            The last part feature is assigned by the client. The feature
            can be up to 64 characters long and can consist only of
            ASCII Latin letters A-Z and a-z, underscore(_), and ASCII
            digits 0-9 starting with a letter. The value will be unique
            given an entity type.
        description (str):
            Description of the Feature.
        value_type (google.cloud.aiplatform_v1.types.Feature.ValueType):
            Immutable. Only applicable for Vertex AI
            Feature Store (Legacy). Type of Feature value.
        create_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Only applicable for Vertex AI
            Feature Store (Legacy). Timestamp when this
            EntityType was created.
        update_time (google.protobuf.timestamp_pb2.Timestamp):
            Output only. Only applicable for Vertex AI
            Feature Store (Legacy). Timestamp when this
            EntityType was most recently updated.
        labels (MutableMapping[str, str]):
            Optional. The labels with user-defined
            metadata to organize your Features.
            Label keys and values can be no longer than 64
            characters (Unicode codepoints), can only
            contain lowercase letters, numeric characters,
            underscores and dashes. International characters
            are allowed.

            See https://goo.gl/xmQnxf for more information
            on and examples of labels. No more than 64 user
            labels can be associated with one Feature
            (System labels are excluded)."
            System reserved label keys are prefixed with
            "aiplatform.googleapis.com/" and are immutable.
        etag (str):
            Used to perform a consistent
            read-modify-write updates. If not set, a blind
            "overwrite" update happens.
        disable_monitoring (bool):
            Optional. Only applicable for Vertex AI Feature Store
            (Legacy). If not set, use the monitoring_config defined for
            the EntityType this Feature belongs to. Only Features with
            type
            ([Feature.ValueType][google.cloud.aiplatform.v1.Feature.ValueType])
            BOOL, STRING, DOUBLE or INT64 can enable monitoring.

            If set to true, all types of data monitoring are disabled
            despite the config on EntityType.
        monitoring_stats_anomalies (MutableSequence[google.cloud.aiplatform_v1.types.Feature.MonitoringStatsAnomaly]):
            Output only. Only applicable for Vertex AI
            Feature Store (Legacy). The list of historical
            stats and anomalies with specified objectives.
        version_column_name (str):
            Only applicable for Vertex AI Feature Store. The name of the
            BigQuery Table/View column hosting data for this version. If
            no value is provided, will use feature_id.
        point_of_contact (str):
            Entity responsible for maintaining this
            feature. Can be comma separated list of email
            addresses or URIs.
    """

    class ValueType(proto.Enum):
        r"""Only applicable for Vertex AI Legacy Feature Store.
        An enum representing the value type of a feature.

        Values:
            VALUE_TYPE_UNSPECIFIED (0):
                The value type is unspecified.
            BOOL (1):
                Used for Feature that is a boolean.
            BOOL_ARRAY (2):
                Used for Feature that is a list of boolean.
            DOUBLE (3):
                Used for Feature that is double.
            DOUBLE_ARRAY (4):
                Used for Feature that is a list of double.
            INT64 (9):
                Used for Feature that is INT64.
            INT64_ARRAY (10):
                Used for Feature that is a list of INT64.
            STRING (11):
                Used for Feature that is string.
            STRING_ARRAY (12):
                Used for Feature that is a list of String.
            BYTES (13):
                Used for Feature that is bytes.
            STRUCT (14):
                Used for Feature that is struct.
        """
        VALUE_TYPE_UNSPECIFIED = 0
        BOOL = 1
        BOOL_ARRAY = 2
        DOUBLE = 3
        DOUBLE_ARRAY = 4
        INT64 = 9
        INT64_ARRAY = 10
        STRING = 11
        STRING_ARRAY = 12
        BYTES = 13
        STRUCT = 14

    class MonitoringStatsAnomaly(proto.Message):
        r"""A list of historical
        [SnapshotAnalysis][google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.SnapshotAnalysis]
        or
        [ImportFeaturesAnalysis][google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.ImportFeaturesAnalysis]
        stats requested by user, sorted by
        [FeatureStatsAnomaly.start_time][google.cloud.aiplatform.v1.FeatureStatsAnomaly.start_time]
        descending.

        Attributes:
            objective (google.cloud.aiplatform_v1.types.Feature.MonitoringStatsAnomaly.Objective):
                Output only. The objective for each stats.
            feature_stats_anomaly (google.cloud.aiplatform_v1.types.FeatureStatsAnomaly):
                Output only. The stats and anomalies
                generated at specific timestamp.
        """

        class Objective(proto.Enum):
            r"""If the objective in the request is both
            Import Feature Analysis and Snapshot Analysis, this objective
            could be one of them. Otherwise, this objective should be the
            same as the objective in the request.

            Values:
                OBJECTIVE_UNSPECIFIED (0):
                    If it's OBJECTIVE_UNSPECIFIED, monitoring_stats will be
                    empty.
                IMPORT_FEATURE_ANALYSIS (1):
                    Stats are generated by Import Feature
                    Analysis.
                SNAPSHOT_ANALYSIS (2):
                    Stats are generated by Snapshot Analysis.
            """
            OBJECTIVE_UNSPECIFIED = 0
            IMPORT_FEATURE_ANALYSIS = 1
            SNAPSHOT_ANALYSIS = 2

        objective: "Feature.MonitoringStatsAnomaly.Objective" = proto.Field(
            proto.ENUM,
            number=1,
            enum="Feature.MonitoringStatsAnomaly.Objective",
        )
        feature_stats_anomaly: feature_monitoring_stats.FeatureStatsAnomaly = (
            proto.Field(
                proto.MESSAGE,
                number=2,
                message=feature_monitoring_stats.FeatureStatsAnomaly,
            )
        )

    name: str = proto.Field(
        proto.STRING,
        number=1,
    )
    description: str = proto.Field(
        proto.STRING,
        number=2,
    )
    value_type: ValueType = proto.Field(
        proto.ENUM,
        number=3,
        enum=ValueType,
    )
    create_time: timestamp_pb2.Timestamp = proto.Field(
        proto.MESSAGE,
        number=4,
        message=timestamp_pb2.Timestamp,
    )
    update_time: timestamp_pb2.Timestamp = proto.Field(
        proto.MESSAGE,
        number=5,
        message=timestamp_pb2.Timestamp,
    )
    labels: MutableMapping[str, str] = proto.MapField(
        proto.STRING,
        proto.STRING,
        number=6,
    )
    etag: str = proto.Field(
        proto.STRING,
        number=7,
    )
    disable_monitoring: bool = proto.Field(
        proto.BOOL,
        number=12,
    )
    monitoring_stats_anomalies: MutableSequence[
        MonitoringStatsAnomaly
    ] = proto.RepeatedField(
        proto.MESSAGE,
        number=11,
        message=MonitoringStatsAnomaly,
    )
    version_column_name: str = proto.Field(
        proto.STRING,
        number=106,
    )
    point_of_contact: str = proto.Field(
        proto.STRING,
        number=107,
    )


__all__ = tuple(sorted(__protobuf__.manifest))
