Add product analytics to FormulaAndFunctionEventsDataSource

.generator/schemas/v1/openapi.yaml

@@ -2875,6 +2875,7 @@ components:
       - ci_tests
       - ci_pipelines
       - incident_analytics
+      - product_analytics
       example: logs
       type: string
       x-enum-varnames:
@@ -2889,6 +2890,7 @@ components:
       - CI_TESTS
       - CI_PIPELINES
       - INCIDENT_ANALYTICS
+      - PRODUCT_ANALYTICS
     FormulaAndFunctionMetricAggregation:
       description: The aggregation methods available for metrics queries.
       enum:

examples/v1/dashboards/CreateDashboard_607525069.py

@@ -0,0 +1,96 @@
+"""
+Create a new timeseries widget with product_analytics data source
+"""
+
+from datadog_api_client import ApiClient, Configuration
+from datadog_api_client.v1.api.dashboards_api import DashboardsApi
+from datadog_api_client.v1.model.dashboard import Dashboard
+from datadog_api_client.v1.model.dashboard_layout_type import DashboardLayoutType
+from datadog_api_client.v1.model.dashboard_reflow_type import DashboardReflowType
+from datadog_api_client.v1.model.formula_and_function_event_aggregation import FormulaAndFunctionEventAggregation
+from datadog_api_client.v1.model.formula_and_function_event_query_definition import (
+    FormulaAndFunctionEventQueryDefinition,
+)
+from datadog_api_client.v1.model.formula_and_function_event_query_definition_compute import (
+    FormulaAndFunctionEventQueryDefinitionCompute,
+)
+from datadog_api_client.v1.model.formula_and_function_event_query_definition_search import (
+    FormulaAndFunctionEventQueryDefinitionSearch,
+)
+from datadog_api_client.v1.model.formula_and_function_events_data_source import FormulaAndFunctionEventsDataSource
+from datadog_api_client.v1.model.formula_and_function_response_format import FormulaAndFunctionResponseFormat
+from datadog_api_client.v1.model.timeseries_widget_definition import TimeseriesWidgetDefinition
+from datadog_api_client.v1.model.timeseries_widget_definition_type import TimeseriesWidgetDefinitionType
+from datadog_api_client.v1.model.timeseries_widget_legend_column import TimeseriesWidgetLegendColumn
+from datadog_api_client.v1.model.timeseries_widget_legend_layout import TimeseriesWidgetLegendLayout
+from datadog_api_client.v1.model.timeseries_widget_request import TimeseriesWidgetRequest
+from datadog_api_client.v1.model.widget import Widget
+from datadog_api_client.v1.model.widget_display_type import WidgetDisplayType
+from datadog_api_client.v1.model.widget_formula import WidgetFormula
+from datadog_api_client.v1.model.widget_legacy_live_span import WidgetLegacyLiveSpan
+from datadog_api_client.v1.model.widget_line_type import WidgetLineType
+from datadog_api_client.v1.model.widget_line_width import WidgetLineWidth
+from datadog_api_client.v1.model.widget_request_style import WidgetRequestStyle
+
+body = Dashboard(
+    title="Example-Dashboard with product_analytics datasource",
+    widgets=[
+        Widget(
+            definition=TimeseriesWidgetDefinition(
+                title="",
+                show_legend=True,
+                legend_layout=TimeseriesWidgetLegendLayout.AUTO,
+                legend_columns=[
+                    TimeseriesWidgetLegendColumn.AVG,
+                    TimeseriesWidgetLegendColumn.MIN,
+                    TimeseriesWidgetLegendColumn.MAX,
+                    TimeseriesWidgetLegendColumn.VALUE,
+                    TimeseriesWidgetLegendColumn.SUM,
+                ],
+                time=WidgetLegacyLiveSpan(),
+                type=TimeseriesWidgetDefinitionType.TIMESERIES,
+                requests=[
+                    TimeseriesWidgetRequest(
+                        formulas=[
+                            WidgetFormula(
+                                formula="query1",
+                            ),
+                        ],
+                        queries=[
+                            FormulaAndFunctionEventQueryDefinition(
+                                data_source=FormulaAndFunctionEventsDataSource.PRODUCT_ANALYTICS,
+                                name="query1",
+                                search=FormulaAndFunctionEventQueryDefinitionSearch(
+                                    query="test_level:test",
+                                ),
+                                indexes=[
+                                    "*",
+                                ],
+                                compute=FormulaAndFunctionEventQueryDefinitionCompute(
+                                    aggregation=FormulaAndFunctionEventAggregation.COUNT,
+                                ),
+                                group_by=[],
+                            ),
+                        ],
+                        response_format=FormulaAndFunctionResponseFormat.TIMESERIES,
+                        style=WidgetRequestStyle(
+                            palette="dog_classic",
+                            line_type=WidgetLineType.SOLID,
+                            line_width=WidgetLineWidth.NORMAL,
+                        ),
+                        display_type=WidgetDisplayType.LINE,
+                    ),
+                ],
+            ),
+        ),
+    ],
+    layout_type=DashboardLayoutType.ORDERED,
+    reflow_type=DashboardReflowType.AUTO,
+)
+
+configuration = Configuration()
+with ApiClient(configuration) as api_client:
+    api_instance = DashboardsApi(api_client)
+    response = api_instance.create_dashboard(body=body)
+
+    print(response)

src/datadog_api_client/v1/model/formula_and_function_events_data_source.py

@@ -16,7 +16,7 @@ class FormulaAndFunctionEventsDataSource(ModelSimple):
     """
     Data source for event platform-based queries.
 
-    :param value: Must be one of ["logs", "spans", "network", "rum", "security_signals", "profiles", "audit", "events", "ci_tests", "ci_pipelines", "incident_analytics"].
+    :param value: Must be one of ["logs", "spans", "network", "rum", "security_signals", "profiles", "audit", "events", "ci_tests", "ci_pipelines", "incident_analytics", "product_analytics"].
     :type value: str
     """
 
@@ -32,6 +32,7 @@ class FormulaAndFunctionEventsDataSource(ModelSimple):
         "ci_tests",
         "ci_pipelines",
         "incident_analytics",
+        "product_analytics",
     }
     LOGS: ClassVar["FormulaAndFunctionEventsDataSource"]
     SPANS: ClassVar["FormulaAndFunctionEventsDataSource"]
@@ -44,6 +45,7 @@ class FormulaAndFunctionEventsDataSource(ModelSimple):
     CI_TESTS: ClassVar["FormulaAndFunctionEventsDataSource"]
     CI_PIPELINES: ClassVar["FormulaAndFunctionEventsDataSource"]
     INCIDENT_ANALYTICS: ClassVar["FormulaAndFunctionEventsDataSource"]
+    PRODUCT_ANALYTICS: ClassVar["FormulaAndFunctionEventsDataSource"]
 
     @cached_property
     def openapi_types(_):
@@ -63,3 +65,4 @@ def openapi_types(_):
 FormulaAndFunctionEventsDataSource.CI_TESTS = FormulaAndFunctionEventsDataSource("ci_tests")
 FormulaAndFunctionEventsDataSource.CI_PIPELINES = FormulaAndFunctionEventsDataSource("ci_pipelines")
 FormulaAndFunctionEventsDataSource.INCIDENT_ANALYTICS = FormulaAndFunctionEventsDataSource("incident_analytics")
+FormulaAndFunctionEventsDataSource.PRODUCT_ANALYTICS = FormulaAndFunctionEventsDataSource("product_analytics")

tests/v1/cassettes/test_scenarios/test_create_a_new_timeseries_widget_with_product_analytics_data_source.frozen

@@ -0,0 +1 @@
+2025-09-18T18:51:17.951Z

tests/v1/cassettes/test_scenarios/test_create_a_new_timeseries_widget_with_product_analytics_data_source.yaml

@@ -0,0 +1,41 @@
+interactions:
+- request:
+    body: '{"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"}}]}'
+    headers:
+      accept:
+      - application/json
+      content-type:
+      - application/json
+    method: POST
+    uri: https://api.datadoghq.com/api/v1/dashboard
+  response:
+    body:
+      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":[]}'
+    headers:
+      content-type:
+      - application/json
+    status:
+      code: 200
+      message: OK
+- request:
+    body: null
+    headers:
+      accept:
+      - application/json
+    method: DELETE
+    uri: https://api.datadoghq.com/api/v1/dashboard/zvr-td5-ppm
+  response:
+    body:
+      string: '{"deleted_dashboard_id":"zvr-td5-ppm"}
+
+        '
+    headers:
+      content-type:
+      - application/json
+    status:
+      code: 200
+      message: OK
+version: 1

tests/v1/features/dashboards.feature

@@ -950,6 +950,15 @@ Feature: Dashboards
     And the response "widgets[0].definition.time.value" is equal to 8
     And the response "widgets[0].definition.time.hide_incomplete_cost_data" is equal to true
 
+  @team:DataDog/dashboards-backend
+  Scenario: Create a new timeseries widget with product_analytics data source
+    Given new "CreateDashboard" request
+    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"}
+    When the request is sent
+    Then the response status is 200 OK
+    And the response "widgets[0].definition.requests[0].queries[0].data_source" is equal to "product_analytics"
+    And the response "widgets[0].definition.requests[0].queries[0].search.query" is equal to "test_level:test"
+
   @generated @skip @team:DataDog/reporting-and-sharing
   Scenario: Create a shared dashboard returns "Bad Request" response
     Given new "CreatePublicDashboard" request