pipelines/backend/api/python_http_client/docs/ApiRun.md

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# ApiRun
## Properties
Name | Type | Description | Notes
------------ | ------------- | ------------- | -------------
**id** | **str** | Output. Unique run ID. Generated by API server. | [optional]
**name** | **str** | Required input field. Name provided by user, or auto generated if run is created by scheduled job. Not unique. | [optional]
**storage_state** | [**ApiRunStorageState**](ApiRunStorageState.md) | | [optional]
**description** | **str** | | [optional]
**pipeline_spec** | [**ApiPipelineSpec**](ApiPipelineSpec.md) | | [optional]
**resource_references** | [**list[ApiResourceReference]**](ApiResourceReference.md) | Optional input field. Specify which resource this run belongs to. When creating a run from a particular pipeline version, the pipeline version can be specified here. | [optional]
**service_account** | **str** | Optional input field. Specify which Kubernetes service account this run uses. | [optional]
**created_at** | **datetime** | Output. The time that the run created. | [optional]
**scheduled_at** | **datetime** | Output. When this run is scheduled to run. This could be different from created_at. For example, if a run is from a backfilling job that was supposed to run 2 month ago, the scheduled_at is 2 month ago, v.s. created_at is the current time. | [optional]
**finished_at** | **datetime** | Output. The time this run is finished. | [optional]
**status** | **str** | | [optional]
**error** | **str** | In case any error happens retrieving a run field, only run ID and the error message is returned. Client has the flexibility of choosing how to handle error. This is especially useful during listing call. | [optional]
**metrics** | [**list[ApiRunMetric]**](ApiRunMetric.md) | Output. The metrics of the run. The metrics are reported by ReportMetrics API. | [optional]
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