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ci.datadog-api-spec
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Regenerate client from commit 2478f8a of spec repo
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‎.generator/schemas/v1/openapi.yaml‎

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‎examples/v1/dashboards/CreateDashboard_1322784076.py‎

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"""
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Create a heatgrid widget with custom discrete thresholds
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"""
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from os import environ
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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.heatgrid_color_bin import HeatgridColorBin
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from datadog_api_client.v1.model.heatgrid_custom_color_source import HeatgridCustomColorSource
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from datadog_api_client.v1.model.heatgrid_discrete_custom_color import HeatgridDiscreteCustomColor
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from datadog_api_client.v1.model.heatgrid_discrete_mode import HeatgridDiscreteMode
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from datadog_api_client.v1.model.heatgrid_label_column import HeatgridLabelColumn
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from datadog_api_client.v1.model.heatgrid_label_column_width import HeatgridLabelColumnWidth
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from datadog_api_client.v1.model.heatgrid_legend import HeatgridLegend
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from datadog_api_client.v1.model.heatgrid_nesting_display import HeatgridNestingDisplay
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from datadog_api_client.v1.model.heatgrid_sort import HeatgridSort
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from datadog_api_client.v1.model.heatgrid_sort_by_label import HeatgridSortByLabel
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from datadog_api_client.v1.model.heatgrid_sort_by_label_property import HeatgridSortByLabelProperty
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from datadog_api_client.v1.model.heatgrid_sort_order import HeatgridSortOrder
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from datadog_api_client.v1.model.heatgrid_widget_definition import HeatgridWidgetDefinition
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from datadog_api_client.v1.model.heatgrid_widget_definition_type import HeatgridWidgetDefinitionType
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from datadog_api_client.v1.model.heatgrid_widget_formula import HeatgridWidgetFormula
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from datadog_api_client.v1.model.heatgrid_widget_request import HeatgridWidgetRequest
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from datadog_api_client.v1.model.heatgrid_widget_response_format import HeatgridWidgetResponseFormat
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from datadog_api_client.v1.model.widget import Widget
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body = Dashboard(
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title="Example-Dashboard",
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layout_type=DashboardLayoutType.ORDERED,
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widgets=[
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Widget(
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definition=HeatgridWidgetDefinition(
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type=HeatgridWidgetDefinitionType.HEATGRID,
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requests=[
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HeatgridWidgetRequest(
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response_format=HeatgridWidgetResponseFormat.TIMESERIES,
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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{*} by {host}",
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),
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],
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formulas=[
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HeatgridWidgetFormula(
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formula="query1",
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),
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],
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),
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],
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sort=HeatgridSort(
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nesting_display=HeatgridNestingDisplay.FLAT,
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sort_by=HeatgridSortByLabel(
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_property=HeatgridSortByLabelProperty.LABEL,
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order=HeatgridSortOrder.ASC,
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),
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),
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color=HeatgridDiscreteCustomColor(
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mode=HeatgridDiscreteMode.DISCRETE,
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source=HeatgridCustomColorSource.CUSTOM,
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bins=[
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HeatgridColorBin(
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color="#00FF00",
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),
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HeatgridColorBin(
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color="#FF0000",
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lower_bound=80.0,
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),
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],
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),
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legend=HeatgridLegend(
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show_caption=True,
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),
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label_column=HeatgridLabelColumn(
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width=HeatgridLabelColumnWidth.M,
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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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configuration.access_token = environ["DD_BEARER_TOKEN"]
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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_1681529203.py‎

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"""
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Create a heatgrid widget with custom gradient colors for both themes
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"""
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from os import environ
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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.heatgrid_color_stop import HeatgridColorStop
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from datadog_api_client.v1.model.heatgrid_custom_color_source import HeatgridCustomColorSource
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from datadog_api_client.v1.model.heatgrid_gradient_custom_color import HeatgridGradientCustomColor
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from datadog_api_client.v1.model.heatgrid_gradient_mode import HeatgridGradientMode
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from datadog_api_client.v1.model.heatgrid_label_column import HeatgridLabelColumn
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from datadog_api_client.v1.model.heatgrid_label_column_width import HeatgridLabelColumnWidth
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from datadog_api_client.v1.model.heatgrid_legend import HeatgridLegend
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from datadog_api_client.v1.model.heatgrid_nesting_display import HeatgridNestingDisplay
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from datadog_api_client.v1.model.heatgrid_sort import HeatgridSort
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from datadog_api_client.v1.model.heatgrid_sort_aggregation import HeatgridSortAggregation
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from datadog_api_client.v1.model.heatgrid_sort_by_value import HeatgridSortByValue
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from datadog_api_client.v1.model.heatgrid_sort_by_value_property import HeatgridSortByValueProperty
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from datadog_api_client.v1.model.heatgrid_sort_order import HeatgridSortOrder
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from datadog_api_client.v1.model.heatgrid_widget_definition import HeatgridWidgetDefinition
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from datadog_api_client.v1.model.heatgrid_widget_definition_type import HeatgridWidgetDefinitionType
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from datadog_api_client.v1.model.heatgrid_widget_formula import HeatgridWidgetFormula
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from datadog_api_client.v1.model.heatgrid_widget_request import HeatgridWidgetRequest
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from datadog_api_client.v1.model.heatgrid_widget_response_format import HeatgridWidgetResponseFormat
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from datadog_api_client.v1.model.widget import Widget
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body = Dashboard(
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title="Example-Dashboard",
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layout_type=DashboardLayoutType.ORDERED,
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widgets=[
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Widget(
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definition=HeatgridWidgetDefinition(
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type=HeatgridWidgetDefinitionType.HEATGRID,
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requests=[
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HeatgridWidgetRequest(
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response_format=HeatgridWidgetResponseFormat.TIMESERIES,
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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{*} by {host}",
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),
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],
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formulas=[
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HeatgridWidgetFormula(
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formula="query1",
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),
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],
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),
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],
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sort=HeatgridSort(
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nesting_display=HeatgridNestingDisplay.FLAT,
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sort_by=HeatgridSortByValue(
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_property=HeatgridSortByValueProperty.VALUE,
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order=HeatgridSortOrder.DESC,
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aggregation=HeatgridSortAggregation.AVG,
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),
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),
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color=HeatgridGradientCustomColor(
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mode=HeatgridGradientMode.GRADIENT,
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source=HeatgridCustomColorSource.CUSTOM,
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stops=[
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HeatgridColorStop(
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position=0,
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color=["#FFFFFF", "#000000"],
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),
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HeatgridColorStop(
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position=100,
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color="#FF0000",
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),
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],
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),
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legend=HeatgridLegend(
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show_caption=True,
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),
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label_column=HeatgridLabelColumn(
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width=HeatgridLabelColumnWidth.M,
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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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configuration.access_token = environ["DD_BEARER_TOKEN"]
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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_2574782816.py‎

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"""
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Create a heatgrid widget with a preset gradient
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"""
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from os import environ
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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.heatgrid_gradient_mode import HeatgridGradientMode
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from datadog_api_client.v1.model.heatgrid_gradient_preset_color import HeatgridGradientPresetColor
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from datadog_api_client.v1.model.heatgrid_label_column import HeatgridLabelColumn
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from datadog_api_client.v1.model.heatgrid_label_column_width import HeatgridLabelColumnWidth
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from datadog_api_client.v1.model.heatgrid_legend import HeatgridLegend
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from datadog_api_client.v1.model.heatgrid_nesting_display import HeatgridNestingDisplay
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from datadog_api_client.v1.model.heatgrid_preset_color_source import HeatgridPresetColorSource
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from datadog_api_client.v1.model.heatgrid_sort import HeatgridSort
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from datadog_api_client.v1.model.heatgrid_sort_aggregation import HeatgridSortAggregation
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from datadog_api_client.v1.model.heatgrid_sort_by_value import HeatgridSortByValue
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from datadog_api_client.v1.model.heatgrid_sort_by_value_property import HeatgridSortByValueProperty
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from datadog_api_client.v1.model.heatgrid_sort_order import HeatgridSortOrder
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from datadog_api_client.v1.model.heatgrid_widget_definition import HeatgridWidgetDefinition
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from datadog_api_client.v1.model.heatgrid_widget_definition_type import HeatgridWidgetDefinitionType
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from datadog_api_client.v1.model.heatgrid_widget_formula import HeatgridWidgetFormula
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from datadog_api_client.v1.model.heatgrid_widget_request import HeatgridWidgetRequest
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from datadog_api_client.v1.model.heatgrid_widget_response_format import HeatgridWidgetResponseFormat
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from datadog_api_client.v1.model.widget import Widget
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body = Dashboard(
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title="Example-Dashboard",
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layout_type=DashboardLayoutType.ORDERED,
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widgets=[
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Widget(
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definition=HeatgridWidgetDefinition(
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type=HeatgridWidgetDefinitionType.HEATGRID,
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requests=[
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HeatgridWidgetRequest(
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response_format=HeatgridWidgetResponseFormat.TIMESERIES,
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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{*} by {host}",
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),
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],
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formulas=[
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HeatgridWidgetFormula(
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formula="query1",
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),
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],
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),
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],
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sort=HeatgridSort(
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nesting_display=HeatgridNestingDisplay.FLAT,
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sort_by=HeatgridSortByValue(
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_property=HeatgridSortByValueProperty.VALUE,
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order=HeatgridSortOrder.DESC,
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aggregation=HeatgridSortAggregation.AVG,
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),
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),
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color=HeatgridGradientPresetColor(
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mode=HeatgridGradientMode.GRADIENT,
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source=HeatgridPresetColorSource.PRESET,
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preset_name="classic",
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),
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legend=HeatgridLegend(
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show_caption=True,
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),
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label_column=HeatgridLabelColumn(
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width=HeatgridLabelColumnWidth.M,
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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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configuration.access_token = environ["DD_BEARER_TOKEN"]
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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/heatgrid_color.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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ModelComposed,
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cached_property,
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)
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class HeatgridColor(ModelComposed):
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def __init__(self, **kwargs):
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"""
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A color string, or two color strings for the light and dark themes, in that order.
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"""
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super().__init__(kwargs)
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@cached_property
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def _composed_schemas(_):
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# we need this here to make our import statements work
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# we must store _composed_schemas in here so the code is only run
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# when we invoke this method. If we kept this at the class
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# level we would get an error because the class level
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# code would be run when this module is imported, and these composed
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# classes don't exist yet because their module has not finished
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# loading
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return {
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"oneOf": [
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str,
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[str],
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],
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}

‎src/datadog_api_client/v1/model/heatgrid_color_bin.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 typing import List, Union, TYPE_CHECKING
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from datadog_api_client.model_utils import (
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ModelNormal,
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cached_property,
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unset,
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UnsetType,
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)
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if TYPE_CHECKING:
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from datadog_api_client.v1.model.heatgrid_color import HeatgridColor
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class HeatgridColorBin(ModelNormal):
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@cached_property
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def additional_properties_type(_):
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return None
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@cached_property
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def openapi_types(_):
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from datadog_api_client.v1.model.heatgrid_color import HeatgridColor
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return {
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"color": (HeatgridColor,),
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"lower_bound": (float,),
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}
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attribute_map = {
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"color": "color",
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"lower_bound": "lower_bound",
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}
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def __init__(
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self_, color: Union[HeatgridColor, str, List[str]], lower_bound: Union[float, UnsetType] = unset, **kwargs
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):
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"""
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A color and optional lower threshold for a discrete bin.
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:param color: A color string, or two color strings for the light and dark themes, in that order.
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:type color: HeatgridColor
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:param lower_bound: Inclusive lower bound. Omit for the first bin.
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:type lower_bound: float, optional
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"""
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if lower_bound is not unset:
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kwargs["lower_bound"] = lower_bound
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super().__init__(kwargs)
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self_.color = color

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