Source code for ai_flow.ops.workflow_execution_ops

# Copyright 2022 The AI Flow Authors
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#   http://www.apache.org/licenses/LICENSE-2.0
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import logging
from typing import List, Optional

from ai_flow.common.exception.exceptions import AIFlowException
from ai_flow.metadata.workflow_execution import WorkflowExecutionMeta

from ai_flow.rpc.client.aiflow_client import get_scheduler_client

logger = logging.getLogger(__name__)


[docs]def start_workflow_execution(workflow_name: str, namespace: str = 'default') -> int: """ Start a new execution of the workflow. :param workflow_name: The workflow to be executed. :param namespace: The namespace which contains the workflow. :return: Id of the workflow execution just started. :raises: AIFlowException if failed to start workflow execution. """ client = get_scheduler_client() try: return client.start_workflow_execution(workflow_name, namespace) except AIFlowException as e: logger.exception("Failed to start execution for workflow %s with exception %s", f'{namespace}.{workflow_name}', str(e)) raise e
[docs]def stop_workflow_execution(workflow_execution_id: int): """ Asynchronously stop the execution of the workflow. :param workflow_execution_id: The id of workflow execution to be stopped. :raises: AIFlowException if failed to stop the workflow execution. """ client = get_scheduler_client() try: client.stop_workflow_execution(workflow_execution_id) except AIFlowException as e: logger.exception("Failed to stop workflow execution %s with exception %s", str(workflow_execution_id), str(e)) raise e
[docs]def stop_workflow_executions(workflow_name: str, namespace: str = 'default'): """ Asynchronously stop all executions of the workflow. :param workflow_name: The workflow to be stopped. :param namespace: The namespace which contains the workflow. :raises: AIFlowException if failed to stop workflow executions. """ client = get_scheduler_client() try: client.stop_workflow_executions(namespace=namespace, workflow_name=workflow_name) except AIFlowException as e: logger.exception("Failed to stop all executions of workflow %s with exception %s", f'{namespace}.{workflow_name}', str(e)) raise e
[docs]def get_workflow_execution(workflow_execution_id: int) -> Optional[WorkflowExecutionMeta]: """ Retrieves the workflow execution from metadata. :param workflow_execution_id: The id of the workflow execution. :return: The WorkflowExecutionMeta instance, return None if no execution found. """ client = get_scheduler_client() return client.get_workflow_execution(workflow_execution_id)
[docs]def list_workflow_executions(workflow_name: str, namespace: str = 'default', limit: int = None, offset: int = None) -> Optional[List[WorkflowExecutionMeta]]: """ Retrieves the list of executions of the workflow. :param workflow_name: The workflow to be listed. :param namespace: The namespace which contains the workflow. :param limit: The maximum records to be listed. :param offset: The offset to start to list. :return: The WorkflowExecutionMeta list, return None if no workflow execution found. """ client = get_scheduler_client() return client.list_workflow_executions(namespace=namespace, workflow_name=workflow_name, page_size=limit, offset=offset)
[docs]def delete_workflow_execution(workflow_execution_id: int): """ Deletes the workflow execution from metadata, note that the workflow execution to be deleted should be finished. :param workflow_execution_id: The id of the workflow execution. :raises: AIFlowException if failed to delete the workflow execution. """ client = get_scheduler_client() try: client.delete_workflow_execution(workflow_execution_id) except AIFlowException as e: logger.exception("Failed to delete workflow execution %s with exception %s", str(workflow_execution_id), str(e)) raise e