# Path: google/cloud/monitoring_dashboard_v1/types/metrics.py
# class SparkChartType(proto.Enum):
# class TimeSeriesQuery(proto.Message):
# class TimeSeriesFilter(proto.Message):
# class TimeSeriesFilterRatio(proto.Message):
#     class RatioPart(proto.Message):
# class Threshold(proto.Message):
#     class Color(proto.Enum):
#     class Direction(proto.Enum):
#     SPARK_CHART_TYPE_UNSPECIFIED = 0
#     SPARK_LINE = 1
#     SPARK_BAR = 2
#         COLOR_UNSPECIFIED = 0
#         YELLOW = 4
#         RED = 6
#         DIRECTION_UNSPECIFIED = 0
#         ABOVE = 1
#         BELOW = 2


import proto  # type: ignore
from google.cloud.monitoring_dashboard_v1.types import metrics
from google.protobuf import duration_pb2  # type: ignore
        upper_bound = proto.Field(proto.DOUBLE, number=2,)

    class SparkChartView(proto.Message):
        r"""A sparkChart is a small chart suitable for inclusion in a
        table-cell or inline in text. This message contains the
        configuration for a sparkChart to show up on a Scorecard,
        showing recent trends of the scorecard's timeseries.

        Attributes:
            spark_chart_type (google.cloud.monitoring_dashboard_v1.types.SparkChartType):
                Required. The type of sparkchart to show in
                this chartView.
            min_alignment_period (google.protobuf.duration_pb2.Duration):
                The lower bound on data point frequency in
                the chart implemented by specifying the minimum
                alignment period to use in a time series query.
                For example, if the data is published once every
                10 minutes it would not make sense to fetch and
                align data at one minute intervals. This field
                is optional and exists only as a hint.
        """

        spark_chart_type = proto.Field(
            proto.ENUM, number=1, enum=metrics.SparkChartType,
        )
        min_alignment_period = proto.Field(
            proto.MESSAGE, number=2, message=duration_pb2.Duration,
        )

    time_series_query = proto.Field(

# Path: google/cloud/monitoring_dashboard_v1/types/metrics.py
# class SparkChartType(proto.Enum):
# class TimeSeriesQuery(proto.Message):
# class TimeSeriesFilter(proto.Message):
# class TimeSeriesFilterRatio(proto.Message):
#     class RatioPart(proto.Message):
# class Threshold(proto.Message):
#     class Color(proto.Enum):
#     class Direction(proto.Enum):
#     SPARK_CHART_TYPE_UNSPECIFIED = 0
#     SPARK_LINE = 1
#     SPARK_BAR = 2
#         COLOR_UNSPECIFIED = 0
#         YELLOW = 4
#         RED = 6
#         DIRECTION_UNSPECIFIED = 0
#         ABOVE = 1
#         BELOW = 2


# Path: google/cloud/monitoring_dashboard_v1/types/scorecard.py
import proto  # type: ignore
from google.cloud.monitoring_dashboard_v1.types import metrics
from google.protobuf import duration_pb2  # type: ignore

        upper_bound = proto.Field(proto.DOUBLE, number=2,)

    class SparkChartView(proto.Message):
        r"""A sparkChart is a small chart suitable for inclusion in a
        table-cell or inline in text. This message contains the
        configuration for a sparkChart to show up on a Scorecard,
        showing recent trends of the scorecard's timeseries.

        Attributes:
            spark_chart_type (google.cloud.monitoring_dashboard_v1.types.SparkChartType):
                Required. The type of sparkchart to show in
                this chartView.
            min_alignment_period (google.protobuf.duration_pb2.Duration):
                The lower bound on data point frequency in
                the chart implemented by specifying the minimum
                alignment period to use in a time series query.
                For example, if the data is published once every
                10 minutes it would not make sense to fetch and
                align data at one minute intervals. This field
                is optional and exists only as a hint.
        """

        spark_chart_type = proto.Field(
            proto.ENUM, number=1, enum=metrics.SparkChartType,
        )
        min_alignment_period = proto.Field(
            proto.MESSAGE, number=2, message=duration_pb2.Duration,
        )

    time_series_query = proto.Field(

        proto.MESSAGE, number=1, message=metrics.TimeSeriesQuery,