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ci.datadog-api-spec
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Regenerate client from commit 442428b of spec repo
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‎.generator/schemas/v1/openapi.yaml‎

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@@ -2875,6 +2875,7 @@ components:
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- ci_tests
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- ci_pipelines
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- incident_analytics
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- product_analytics
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example: logs
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type: string
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x-enum-varnames:
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- CI_TESTS
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- CI_PIPELINES
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- INCIDENT_ANALYTICS
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- PRODUCT_ANALYTICS
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FormulaAndFunctionMetricAggregation:
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description: The aggregation methods available for metrics queries.
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enum:

‎examples/v1_dashboards_CreateDashboard_607525069.rs‎

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// Create a new timeseries widget with product_analytics data source
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use datadog_api_client::datadog;
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use datadog_api_client::datadogV1::api_dashboards::DashboardsAPI;
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use datadog_api_client::datadogV1::model::Dashboard;
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use datadog_api_client::datadogV1::model::DashboardLayoutType;
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use datadog_api_client::datadogV1::model::DashboardReflowType;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionEventAggregation;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionEventQueryDefinition;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionEventQueryDefinitionCompute;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionEventQueryDefinitionSearch;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionEventsDataSource;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionQueryDefinition;
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use datadog_api_client::datadogV1::model::FormulaAndFunctionResponseFormat;
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use datadog_api_client::datadogV1::model::TimeseriesWidgetDefinition;
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use datadog_api_client::datadogV1::model::TimeseriesWidgetDefinitionType;
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use datadog_api_client::datadogV1::model::TimeseriesWidgetLegendColumn;
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use datadog_api_client::datadogV1::model::TimeseriesWidgetLegendLayout;
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use datadog_api_client::datadogV1::model::TimeseriesWidgetRequest;
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use datadog_api_client::datadogV1::model::Widget;
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use datadog_api_client::datadogV1::model::WidgetDefinition;
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use datadog_api_client::datadogV1::model::WidgetDisplayType;
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use datadog_api_client::datadogV1::model::WidgetFormula;
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use datadog_api_client::datadogV1::model::WidgetLegacyLiveSpan;
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use datadog_api_client::datadogV1::model::WidgetLineType;
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use datadog_api_client::datadogV1::model::WidgetLineWidth;
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use datadog_api_client::datadogV1::model::WidgetRequestStyle;
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use datadog_api_client::datadogV1::model::WidgetTime;
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#[tokio::main]
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async fn main() {
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let body =
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Dashboard::new(
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DashboardLayoutType::ORDERED,
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"Example-Dashboard with product_analytics datasource".to_string(),
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vec![
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Widget::new(
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WidgetDefinition::TimeseriesWidgetDefinition(
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Box::new(
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TimeseriesWidgetDefinition::new(
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vec![
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TimeseriesWidgetRequest::new()
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.display_type(WidgetDisplayType::LINE)
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.formulas(vec![WidgetFormula::new("query1".to_string())])
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.queries(
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vec![
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FormulaAndFunctionQueryDefinition
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::FormulaAndFunctionEventQueryDefinition(
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Box::new(
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FormulaAndFunctionEventQueryDefinition::new(
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FormulaAndFunctionEventQueryDefinitionCompute::new(
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FormulaAndFunctionEventAggregation::COUNT,
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),
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FormulaAndFunctionEventsDataSource::PRODUCT_ANALYTICS,
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"query1".to_string(),
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)
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.group_by(vec![])
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.indexes(vec!["*".to_string()])
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.search(
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FormulaAndFunctionEventQueryDefinitionSearch::new(
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"test_level:test".to_string(),
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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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.response_format(FormulaAndFunctionResponseFormat::TIMESERIES)
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.style(
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WidgetRequestStyle::new()
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.line_type(WidgetLineType::SOLID)
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.line_width(WidgetLineWidth::NORMAL)
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.palette("dog_classic".to_string()),
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)
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],
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TimeseriesWidgetDefinitionType::TIMESERIES,
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)
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.legend_columns(
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vec![
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TimeseriesWidgetLegendColumn::AVG,
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TimeseriesWidgetLegendColumn::MIN,
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TimeseriesWidgetLegendColumn::MAX,
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TimeseriesWidgetLegendColumn::VALUE,
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TimeseriesWidgetLegendColumn::SUM
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],
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)
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.legend_layout(TimeseriesWidgetLegendLayout::AUTO)
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.show_legend(true)
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.time(WidgetTime::WidgetLegacyLiveSpan(Box::new(WidgetLegacyLiveSpan::new())))
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.title("".to_string()),
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),
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),
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)
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],
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).reflow_type(DashboardReflowType::AUTO);
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let configuration = datadog::Configuration::new();
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let api = DashboardsAPI::with_config(configuration);
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let resp = api.create_dashboard(body).await;
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if let Ok(value) = resp {
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println!("{:#?}", value);
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} else {
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println!("{:#?}", resp.unwrap_err());
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}
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}

‎src/datadogV1/model/model_formula_and_function_events_data_source.rs‎

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@@ -18,6 +18,7 @@ pub enum FormulaAndFunctionEventsDataSource {
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CI_TESTS,
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CI_PIPELINES,
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INCIDENT_ANALYTICS,
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PRODUCT_ANALYTICS,
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UnparsedObject(crate::datadog::UnparsedObject),
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}
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Self::CI_TESTS => String::from("ci_tests"),
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Self::CI_PIPELINES => String::from("ci_pipelines"),
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Self::INCIDENT_ANALYTICS => String::from("incident_analytics"),
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Self::PRODUCT_ANALYTICS => String::from("product_analytics"),
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Self::UnparsedObject(v) => v.value.to_string(),
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}
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}
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"ci_tests" => Self::CI_TESTS,
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"ci_pipelines" => Self::CI_PIPELINES,
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"incident_analytics" => Self::INCIDENT_ANALYTICS,
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"product_analytics" => Self::PRODUCT_ANALYTICS,
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_ => Self::UnparsedObject(crate::datadog::UnparsedObject {
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value: serde_json::Value::String(s.into()),
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}),

‎tests/scenarios/cassettes/v1/dashboards/Create-a-new-timeseries-widget-with-product-analytics-data-source.frozen‎

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2025-09-18T18:51:17.951Z

‎tests/scenarios/cassettes/v1/dashboards/Create-a-new-timeseries-widget-with-product-analytics-data-source.json‎

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{
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"http_interactions": [
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{
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"request": {
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"body": {
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"string": "{\"layout_type\":\"ordered\",\"reflow_type\":\"auto\",\"title\":\"Test-Create_a_new_timeseries_widget_with_product_analytics_data_source-1758221477 with product_analytics datasource\",\"widgets\":[{\"definition\":{\"legend_columns\":[\"avg\",\"min\",\"max\",\"value\",\"sum\"],\"legend_layout\":\"auto\",\"requests\":[{\"display_type\":\"line\",\"formulas\":[{\"formula\":\"query1\"}],\"queries\":[{\"compute\":{\"aggregation\":\"count\"},\"data_source\":\"product_analytics\",\"group_by\":[],\"indexes\":[\"*\"],\"name\":\"query1\",\"search\":{\"query\":\"test_level:test\"}}],\"response_format\":\"timeseries\",\"style\":{\"line_type\":\"solid\",\"line_width\":\"normal\",\"palette\":\"dog_classic\"}}],\"show_legend\":true,\"time\":{},\"title\":\"\",\"type\":\"timeseries\"}}]}",
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"encoding": null
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},
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"headers": {
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"Accept": [
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"application/json"
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],
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"Content-Type": [
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"application/json"
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]
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},
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"method": "post",
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"uri": "https://api.datadoghq.com/api/v1/dashboard"
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},
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"response": {
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"body": {
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"string": "{\"id\":\"zvr-td5-ppm\",\"title\":\"Test-Create_a_new_timeseries_widget_with_product_analytics_data_source-1758221477 with product_analytics datasource\",\"description\":null,\"author_handle\":\"9919ec9b-ebc7-49ee-8dc8-03626e717cca\",\"author_name\":\"CI Account\",\"layout_type\":\"ordered\",\"url\":\"/dashboard/zvr-td5-ppm/test-createanewtimeserieswidgetwithproductanalyticsdatasource-1758221477-with-pr\",\"template_variables\":null,\"widgets\":[{\"definition\":{\"legend_columns\":[\"avg\",\"min\",\"max\",\"value\",\"sum\"],\"legend_layout\":\"auto\",\"requests\":[{\"display_type\":\"line\",\"formulas\":[{\"formula\":\"query1\"}],\"queries\":[{\"compute\":{\"aggregation\":\"count\"},\"data_source\":\"product_analytics\",\"group_by\":[],\"indexes\":[\"*\"],\"name\":\"query1\",\"search\":{\"query\":\"test_level:test\"}}],\"response_format\":\"timeseries\",\"style\":{\"line_type\":\"solid\",\"line_width\":\"normal\",\"palette\":\"dog_classic\"}}],\"show_legend\":true,\"time\":{},\"title\":\"\",\"type\":\"timeseries\"},\"id\":6058978575853641}],\"notify_list\":null,\"created_at\":\"2025-09-18T18:51:18.107135+00:00\",\"modified_at\":\"2025-09-18T18:51:18.107135+00:00\",\"reflow_type\":\"auto\",\"restricted_roles\":[]}",
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"encoding": null
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},
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"headers": {
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"Content-Type": [
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"application/json"
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]
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},
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"status": {
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"code": 200,
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"message": "OK"
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}
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},
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"recorded_at": "Thu, 18 Sep 2025 18:51:17 GMT"
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},
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{
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"request": {
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"body": "",
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"headers": {
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"Accept": [
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"application/json"
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]
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},
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"method": "delete",
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"uri": "https://api.datadoghq.com/api/v1/dashboard/zvr-td5-ppm"
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},
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"response": {
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"body": {
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"string": "{\"deleted_dashboard_id\":\"zvr-td5-ppm\"}\n",
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"encoding": null
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},
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"headers": {
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"Content-Type": [
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"application/json"
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]
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},
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"status": {
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"code": 200,
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"message": "OK"
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}
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},
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"recorded_at": "Thu, 18 Sep 2025 18:51:17 GMT"
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}
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],
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"recorded_with": "VCR 6.0.0"
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}

‎tests/scenarios/features/v1/dashboards.feature‎

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And the response "widgets[0].definition.time.value" is equal to 8
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And the response "widgets[0].definition.time.hide_incomplete_cost_data" is equal to true
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@team:DataDog/dashboards-backend
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Scenario: Create a new timeseries widget with product_analytics data source
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Given new "CreateDashboard" request
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And body with value {"title":"{{ unique }} with product_analytics datasource","widgets":[{"definition":{"title":"","show_legend":true,"legend_layout":"auto","legend_columns":["avg","min","max","value","sum"],"time":{},"type":"timeseries","requests":[{"formulas":[{"formula":"query1"}],"queries":[{"data_source":"product_analytics","name":"query1","search":{"query":"test_level:test"},"indexes":["*"],"compute":{"aggregation":"count"},"group_by":[]}],"response_format":"timeseries","style":{"palette":"dog_classic","line_type":"solid","line_width":"normal"},"display_type":"line"}]}}],"layout_type":"ordered","reflow_type":"auto"}
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When the request is sent
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Then the response status is 200 OK
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And the response "widgets[0].definition.requests[0].queries[0].data_source" is equal to "product_analytics"
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And the response "widgets[0].definition.requests[0].queries[0].search.query" is equal to "test_level:test"
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@generated @skip @team:DataDog/reporting-and-sharing
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Scenario: Create a shared dashboard returns "Bad Request" response
955964
Given new "CreatePublicDashboard" request

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