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api-clients-generation-pipeline[bot]ci.datadog-api-spec
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Dashboards - Add semantic_mode support to FormulaAndFunctionMetricQueryDefinition (#2993)
Co-authored-by: ci.datadog-api-spec <packages@datadoghq.com>
1 parent 7096e39 commit c68aa36

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‎.generator/schemas/v1/openapi.yaml‎

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@@ -2952,11 +2952,24 @@ components:
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description: Metrics query definition.
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example: avg:system.cpu.user{*}
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type: string
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semantic_mode:
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$ref: '#/components/schemas/FormulaAndFunctionMetricSemanticMode'
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required:
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- data_source
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- query
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- name
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type: object
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FormulaAndFunctionMetricSemanticMode:
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description: Semantic mode for metrics queries. This determines how metrics
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from different sources are combined or displayed.
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enum:
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- combined
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- native
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example: combined
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type: string
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x-enum-varnames:
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- COMBINED
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- NATIVE
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FormulaAndFunctionProcessQueryDataSource:
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description: Data sources that rely on the process backend.
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enum:

‎docs/datadog_api_client.v1.model.rst‎

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:members:
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:show-inheritance:
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datadog\_api\_client.v1.model.formula\_and\_function\_metric\_semantic\_mode module
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-----------------------------------------------------------------------------------
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.. automodule:: datadog_api_client.v1.model.formula_and_function_metric_semantic_mode
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:members:
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:show-inheritance:
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datadog\_api\_client.v1.model.formula\_and\_function\_process\_query\_data\_source module
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-----------------------------------------------------------------------------------------
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‎examples/v1/dashboards/CreateDashboard_3685886950.py‎

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"""
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Create a new dashboard with a timeseries widget using formulas and functions metrics query with native semantic_mode
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"""
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from datadog_api_client import ApiClient, Configuration
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from datadog_api_client.v1.api.dashboards_api import DashboardsApi
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from datadog_api_client.v1.model.dashboard import Dashboard
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from datadog_api_client.v1.model.dashboard_layout_type import DashboardLayoutType
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from datadog_api_client.v1.model.formula_and_function_metric_data_source import FormulaAndFunctionMetricDataSource
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from datadog_api_client.v1.model.formula_and_function_metric_query_definition import (
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FormulaAndFunctionMetricQueryDefinition,
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)
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from datadog_api_client.v1.model.formula_and_function_metric_semantic_mode import FormulaAndFunctionMetricSemanticMode
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from datadog_api_client.v1.model.formula_and_function_response_format import FormulaAndFunctionResponseFormat
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from datadog_api_client.v1.model.timeseries_widget_definition import TimeseriesWidgetDefinition
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from datadog_api_client.v1.model.timeseries_widget_definition_type import TimeseriesWidgetDefinitionType
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from datadog_api_client.v1.model.timeseries_widget_request import TimeseriesWidgetRequest
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from datadog_api_client.v1.model.widget import Widget
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from datadog_api_client.v1.model.widget_display_type import WidgetDisplayType
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from datadog_api_client.v1.model.widget_formula import WidgetFormula
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body = Dashboard(
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layout_type=DashboardLayoutType.ORDERED,
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title="Example-Dashboard with native semantic_mode",
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widgets=[
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Widget(
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definition=TimeseriesWidgetDefinition(
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type=TimeseriesWidgetDefinitionType.TIMESERIES,
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requests=[
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TimeseriesWidgetRequest(
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queries=[
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FormulaAndFunctionMetricQueryDefinition(
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data_source=FormulaAndFunctionMetricDataSource.METRICS,
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name="query1",
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query="avg:system.cpu.user{*}",
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semantic_mode=FormulaAndFunctionMetricSemanticMode.NATIVE,
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),
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],
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response_format=FormulaAndFunctionResponseFormat.TIMESERIES,
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formulas=[
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WidgetFormula(
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formula="query1",
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),
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],
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display_type=WidgetDisplayType.LINE,
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),
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],
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),
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),
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],
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)
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configuration = Configuration()
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with ApiClient(configuration) as api_client:
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api_instance = DashboardsApi(api_client)
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response = api_instance.create_dashboard(body=body)
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print(response)

‎examples/v1/dashboards/CreateDashboard_865807520.py‎

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"""
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Create a new dashboard with a timeseries widget using formulas and functions metrics query with combined semantic_mode
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"""
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from datadog_api_client import ApiClient, Configuration
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from datadog_api_client.v1.api.dashboards_api import DashboardsApi
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from datadog_api_client.v1.model.dashboard import Dashboard
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from datadog_api_client.v1.model.dashboard_layout_type import DashboardLayoutType
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from datadog_api_client.v1.model.formula_and_function_metric_data_source import FormulaAndFunctionMetricDataSource
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from datadog_api_client.v1.model.formula_and_function_metric_query_definition import (
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FormulaAndFunctionMetricQueryDefinition,
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)
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from datadog_api_client.v1.model.formula_and_function_metric_semantic_mode import FormulaAndFunctionMetricSemanticMode
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from datadog_api_client.v1.model.formula_and_function_response_format import FormulaAndFunctionResponseFormat
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from datadog_api_client.v1.model.timeseries_widget_definition import TimeseriesWidgetDefinition
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from datadog_api_client.v1.model.timeseries_widget_definition_type import TimeseriesWidgetDefinitionType
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from datadog_api_client.v1.model.timeseries_widget_request import TimeseriesWidgetRequest
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from datadog_api_client.v1.model.widget import Widget
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from datadog_api_client.v1.model.widget_display_type import WidgetDisplayType
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from datadog_api_client.v1.model.widget_formula import WidgetFormula
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body = Dashboard(
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layout_type=DashboardLayoutType.ORDERED,
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title="Example-Dashboard with combined semantic_mode",
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widgets=[
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Widget(
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definition=TimeseriesWidgetDefinition(
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type=TimeseriesWidgetDefinitionType.TIMESERIES,
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requests=[
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TimeseriesWidgetRequest(
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queries=[
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FormulaAndFunctionMetricQueryDefinition(
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data_source=FormulaAndFunctionMetricDataSource.METRICS,
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name="query1",
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query="avg:system.cpu.user{*}",
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semantic_mode=FormulaAndFunctionMetricSemanticMode.COMBINED,
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),
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],
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response_format=FormulaAndFunctionResponseFormat.TIMESERIES,
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formulas=[
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WidgetFormula(
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formula="query1",
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),
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],
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display_type=WidgetDisplayType.LINE,
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),
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],
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),
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),
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],
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)
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configuration = Configuration()
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with ApiClient(configuration) as api_client:
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api_instance = DashboardsApi(api_client)
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response = api_instance.create_dashboard(body=body)
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print(response)

‎src/datadog_api_client/v1/model/distribution_widget_histogram_request_query.py‎

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@@ -30,6 +30,9 @@ def __init__(self, **kwargs):
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:param query: Metrics query definition.
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:type query: str
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:param semantic_mode: Semantic mode for metrics queries. This determines how metrics from different sources are combined or displayed.
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:type semantic_mode: FormulaAndFunctionMetricSemanticMode, optional
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:param compute: Compute options.
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:type compute: FormulaAndFunctionEventQueryDefinitionCompute
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‎src/datadog_api_client/v1/model/formula_and_function_metric_query_definition.py‎

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if TYPE_CHECKING:
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from datadog_api_client.v1.model.formula_and_function_metric_aggregation import FormulaAndFunctionMetricAggregation
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from datadog_api_client.v1.model.formula_and_function_metric_data_source import FormulaAndFunctionMetricDataSource
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from datadog_api_client.v1.model.formula_and_function_metric_semantic_mode import (
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FormulaAndFunctionMetricSemanticMode,
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)
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class FormulaAndFunctionMetricQueryDefinition(ModelNormal):
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from datadog_api_client.v1.model.formula_and_function_metric_data_source import (
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FormulaAndFunctionMetricDataSource,
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)
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from datadog_api_client.v1.model.formula_and_function_metric_semantic_mode import (
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FormulaAndFunctionMetricSemanticMode,
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)
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return {
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"aggregator": (FormulaAndFunctionMetricAggregation,),
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"cross_org_uuids": ([str],),
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"data_source": (FormulaAndFunctionMetricDataSource,),
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"name": (str,),
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"query": (str,),
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"semantic_mode": (FormulaAndFunctionMetricSemanticMode,),
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}
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attribute_map = {
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"data_source": "data_source",
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"name": "name",
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"query": "query",
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"semantic_mode": "semantic_mode",
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}
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def __init__(
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query: str,
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aggregator: Union[FormulaAndFunctionMetricAggregation, UnsetType] = unset,
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cross_org_uuids: Union[List[str], UnsetType] = unset,
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semantic_mode: Union[FormulaAndFunctionMetricSemanticMode, UnsetType] = unset,
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**kwargs,
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):
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"""
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:param query: Metrics query definition.
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:type query: str
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:param semantic_mode: Semantic mode for metrics queries. This determines how metrics from different sources are combined or displayed.
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:type semantic_mode: FormulaAndFunctionMetricSemanticMode, optional
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"""
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if aggregator is not unset:
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kwargs["aggregator"] = aggregator
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if cross_org_uuids is not unset:
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kwargs["cross_org_uuids"] = cross_org_uuids
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if semantic_mode is not unset:
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kwargs["semantic_mode"] = semantic_mode
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super().__init__(kwargs)
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self_.data_source = data_source

‎src/datadog_api_client/v1/model/formula_and_function_metric_semantic_mode.py‎

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# Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License.
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# This product includes software developed at Datadog (https://www.datadoghq.com/).
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# Copyright 2019-Present Datadog, Inc.
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from __future__ import annotations
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from datadog_api_client.model_utils import (
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ModelSimple,
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cached_property,
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)
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from typing import ClassVar
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class FormulaAndFunctionMetricSemanticMode(ModelSimple):
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"""
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Semantic mode for metrics queries. This determines how metrics from different sources are combined or displayed.
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:param value: Must be one of ["combined", "native"].
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:type value: str
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"""
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allowed_values = {
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"combined",
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"native",
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}
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COMBINED: ClassVar["FormulaAndFunctionMetricSemanticMode"]
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NATIVE: ClassVar["FormulaAndFunctionMetricSemanticMode"]
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@cached_property
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def openapi_types(_):
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return {
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"value": (str,),
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}
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FormulaAndFunctionMetricSemanticMode.COMBINED = FormulaAndFunctionMetricSemanticMode("combined")
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FormulaAndFunctionMetricSemanticMode.NATIVE = FormulaAndFunctionMetricSemanticMode("native")

‎src/datadog_api_client/v1/model/formula_and_function_query_definition.py‎

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:param query: Metrics query definition.
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:type query: str
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:param semantic_mode: Semantic mode for metrics queries. This determines how metrics from different sources are combined or displayed.
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:type semantic_mode: FormulaAndFunctionMetricSemanticMode, optional
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:param compute: Compute options.
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:type compute: FormulaAndFunctionEventQueryDefinitionCompute
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‎src/datadog_api_client/v1/model/slo_data_source_query_definition.py‎

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:param query: Metrics query definition.
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:type query: str
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:param semantic_mode: Semantic mode for metrics queries. This determines how metrics from different sources are combined or displayed.
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:type semantic_mode: FormulaAndFunctionMetricSemanticMode, optional
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"""
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super().__init__(kwargs)
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‎src/datadog_api_client/v1/models/__init__.py‎

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from datadog_api_client.v1.model.formula_and_function_metric_query_definition import (
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FormulaAndFunctionMetricQueryDefinition,
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)
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from datadog_api_client.v1.model.formula_and_function_metric_semantic_mode import FormulaAndFunctionMetricSemanticMode
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from datadog_api_client.v1.model.formula_and_function_process_query_data_source import (
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FormulaAndFunctionProcessQueryDataSource,
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)
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"FormulaAndFunctionMetricAggregation",
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"FormulaAndFunctionMetricDataSource",
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"FormulaAndFunctionMetricQueryDefinition",
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"FormulaAndFunctionMetricSemanticMode",
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"FormulaAndFunctionProcessQueryDataSource",
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"FormulaAndFunctionProcessQueryDefinition",
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"FormulaAndFunctionQueryDefinition",

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