class_docstr: Metadata about a run.
class_docstr_tok: ["Metadata","about","a","run","."]
code: def __init__(
      self,
      run_uuid,
      experiment_id,
      user_id,
      status,
      start_time,
      end_time,
      lifecycle_stage,
      artifact_uri=None,
      run_id=None,
      run_name=None,
  ):
      if experiment_id is None:
          raise Exception("experiment_id cannot be None")
      if user_id is None:
          raise Exception("user_id cannot be None")
      if status is None:
          raise Exception("status cannot be None")
      if start_time is None:
          raise Exception("start_time cannot be None")
      actual_run_id = run_id or run_uuid
      if actual_run_id is None:
          raise Exception("run_id and run_uuid cannot both be None")
      self._run_uuid = actual_run_id
      self._run_id = actual_run_id
      self._experiment_id = experiment_id
      self._user_id = user_id
      self._status = status
      self._start_time = start_time
      self._end_time = end_time
      self._lifecycle_stage = lifecycle_stage
      self._artifact_uri = artifact_uri
      self._run_name = run_name
  
imports: from mlflow.entities._mlflow_object import _MLflowObject
  from mlflow.entities.lifecycle_stage import LifecycleStage
  from mlflow.entities.run_status import RunStatus
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.protos.service_pb2 import RunInfo
label_desc: Use image node_id 1 to create a new RunInfo object from inherited base classes: _MLflowObject with example: obj = RunInfo(run_uuid, experiment_id, user_id, status, start_time, end_time, lifecycle_stage, artifact_uri, run_id, run_name)