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api-clients-generation-pipeline[bot]ci.datadog-api-spec
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ci.datadog-api-spec
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Regenerate client from commit 267e916e of spec repo (#1137)
Co-authored-by: ci.datadog-api-spec <[email protected]>
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‎.apigentools-info

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@@ -4,13 +4,13 @@
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"spec_versions": {
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"v1": {
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"apigentools_version": "1.6.4",
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"regenerated": "2022-08-29 18:11:44.465510",
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"spec_repo_commit": "95e8a34f"
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"regenerated": "2022-08-30 09:41:16.697170",
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"spec_repo_commit": "267e916e"
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},
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"v2": {
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"apigentools_version": "1.6.4",
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"regenerated": "2022-08-29 18:11:44.477822",
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"spec_repo_commit": "95e8a34f"
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"regenerated": "2022-08-30 09:41:16.709766",
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"spec_repo_commit": "267e916e"
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}
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}
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}

‎.generator/schemas/v1/openapi.yaml

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@@ -2485,6 +2485,7 @@ components:
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- profiles
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- audit
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- events
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- ci_tests
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example: logs
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type: string
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x-enum-varnames:
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- PROFILES
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- AUDIT
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- EVENTS
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- CI_TESTS
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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_1307120899.py

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"""
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Create a new timeseries widget with ci_tests data source
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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.dashboard_reflow_type import DashboardReflowType
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from datadog_api_client.v1.model.formula_and_function_event_aggregation import FormulaAndFunctionEventAggregation
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from datadog_api_client.v1.model.formula_and_function_event_query_definition import (
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FormulaAndFunctionEventQueryDefinition,
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)
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from datadog_api_client.v1.model.formula_and_function_event_query_definition_compute import (
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FormulaAndFunctionEventQueryDefinitionCompute,
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)
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from datadog_api_client.v1.model.formula_and_function_event_query_definition_search import (
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FormulaAndFunctionEventQueryDefinitionSearch,
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)
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from datadog_api_client.v1.model.formula_and_function_events_data_source import FormulaAndFunctionEventsDataSource
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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_legend_column import TimeseriesWidgetLegendColumn
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from datadog_api_client.v1.model.timeseries_widget_legend_layout import TimeseriesWidgetLegendLayout
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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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from datadog_api_client.v1.model.widget_line_type import WidgetLineType
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from datadog_api_client.v1.model.widget_line_width import WidgetLineWidth
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from datadog_api_client.v1.model.widget_request_style import WidgetRequestStyle
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from datadog_api_client.v1.model.widget_time import WidgetTime
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body = Dashboard(
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title="Example-Create_a_new_timeseries_widget_with_ci_tests_data_source with ci_tests datasource",
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widgets=[
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Widget(
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definition=TimeseriesWidgetDefinition(
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title="",
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show_legend=True,
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legend_layout=TimeseriesWidgetLegendLayout("auto"),
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legend_columns=[
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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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time=WidgetTime(),
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type=TimeseriesWidgetDefinitionType("timeseries"),
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requests=[
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TimeseriesWidgetRequest(
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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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queries=[
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FormulaAndFunctionEventQueryDefinition(
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data_source=FormulaAndFunctionEventsDataSource("ci_tests"),
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name="query1",
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search=FormulaAndFunctionEventQueryDefinitionSearch(
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query="test_level:test",
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),
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indexes=[
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"*",
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],
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compute=FormulaAndFunctionEventQueryDefinitionCompute(
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aggregation=FormulaAndFunctionEventAggregation("count"),
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),
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group_by=[],
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),
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],
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response_format=FormulaAndFunctionResponseFormat("timeseries"),
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style=WidgetRequestStyle(
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palette="dog_classic",
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line_type=WidgetLineType("solid"),
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line_width=WidgetLineWidth("normal"),
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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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layout_type=DashboardLayoutType("ordered"),
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reflow_type=DashboardReflowType("auto"),
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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/formula_and_function_events_data_source.py

Lines changed: 2 additions & 1 deletion
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@@ -13,7 +13,7 @@ class FormulaAndFunctionEventsDataSource(ModelSimple):
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"""
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Data source for event platform-based queries.
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:param value: Must be one of ["logs", "spans", "network", "rum", "security_signals", "profiles", "audit", "events"].
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:param value: Must be one of ["logs", "spans", "network", "rum", "security_signals", "profiles", "audit", "events", "ci_tests"].
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:type value: str
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"""
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"PROFILES": "profiles",
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"AUDIT": "audit",
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"EVENTS": "events",
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"CI_TESTS": "ci_tests",
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},
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}
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‎tests/v1/cassettes/test_scenarios/test_create_a_new_timeseries_widget_with_ci_tests_data_source.frozen

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2022-08-22T19:31:16.232Z

‎tests/v1/cassettes/test_scenarios/test_create_a_new_timeseries_widget_with_ci_tests_data_source.yaml

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interactions:
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- request:
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body: '{"layout_type":"ordered","reflow_type":"auto","title":"Test-Create_a_new_timeseries_widget_with_ci_tests_data_source-1661196676
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with ci_tests 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":"ci_tests","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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headers:
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accept:
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- application/json
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content-type:
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- application/json
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method: POST
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uri: https://api.datadoghq.com/api/v1/dashboard
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response:
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body:
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string: '{"notify_list":null,"description":null,"restricted_roles":[],"author_name":null,"template_variables":null,"is_read_only":false,"id":"ykp-mnk-euu","title":"Test-Create_a_new_timeseries_widget_with_ci_tests_data_source-1661196676
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with ci_tests datasource","url":"/dashboard/ykp-mnk-euu/test-createanewtimeserieswidgetwithcitestsdatasource-1661196676-with-citests-dat","created_at":"2022-08-22T19:31:16.421905+00:00","modified_at":"2022-08-22T19:31:16.421905+00:00","reflow_type":"auto","author_handle":"[email protected]","widgets":[{"definition":{"legend_columns":["avg","min","max","value","sum"],"title":"","legend_layout":"auto","show_legend":true,"time":{},"requests":[{"formulas":[{"formula":"query1"}],"style":{"line_width":"normal","palette":"dog_classic","line_type":"solid"},"display_type":"line","response_format":"timeseries","queries":[{"search":{"query":"test_level:test"},"data_source":"ci_tests","compute":{"aggregation":"count"},"name":"query1","indexes":["*"],"group_by":[]}]}],"type":"timeseries"},"id":5710436152334347}],"layout_type":"ordered"}
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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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status:
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code: 200
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message: OK
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- request:
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body: null
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headers:
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accept:
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- application/json
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method: DELETE
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uri: https://api.datadoghq.com/api/v1/dashboard/ykp-mnk-euu
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response:
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body:
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string: '{"deleted_dashboard_id":"ykp-mnk-euu"}
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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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status:
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code: 200
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message: OK
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version: 1

‎tests/v1/features/dashboards.feature

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And the response "widgets[0].definition.type" is equal to "trace_service"
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And the response "widgets[0].definition.env" is equal to "none"
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@team:DataDog/dashboards
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Scenario: Create a new timeseries widget with ci_tests data source
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Given new "CreateDashboard" request
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And body with value {"title":"{{ unique }} with ci_tests 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":"ci_tests","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 "ci_tests"
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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/dashboards
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Scenario: Delete a dashboard returns "Dashboards Not Found" response
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Given new "DeleteDashboard" request

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