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	* Fixed airflow APIs caching * FIxed linting * fixed py format Co-authored-by: Onkar Ravgan <onkarravgan@Onkars-MacBook-Pro.local>
		
			
				
	
	
		
			91 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			91 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
#  Copyright 2021 Collate
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#  Licensed under the Apache License, Version 2.0 (the "License");
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#  you may not use this file except in compliance with the License.
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#  You may obtain a copy of the License at
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#  http://www.apache.org/licenses/LICENSE-2.0
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#  Unless required by applicable law or agreed to in writing, software
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#  distributed under the License is distributed on an "AS IS" BASIS,
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#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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#  See the License for the specific language governing permissions and
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#  limitations under the License.
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"""
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Deploy the DAG and scan it with the scheduler
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"""
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import traceback
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from typing import Callable
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from flask import Blueprint, Response, request
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from openmetadata_managed_apis.api.response import ApiResponse
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from openmetadata_managed_apis.operations.deploy import DagDeployer
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from openmetadata_managed_apis.utils.logger import routes_logger
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from pydantic import ValidationError
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from metadata.generated.schema.entity.services.ingestionPipelines.ingestionPipeline import (
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    IngestionPipeline,
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)
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logger = routes_logger()
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def get_fn(blueprint: Blueprint) -> Callable:
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    """
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    Return the function loaded to a route
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    :param blueprint: Flask Blueprint to assign route to
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    :return: routed function
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    """
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    # Lazy import the requirements
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    # pylint: disable=import-outside-toplevel
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    from airflow.api_connexion import security
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    from airflow.security import permissions
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    from airflow.www.app import csrf
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    @blueprint.route("/deploy", methods=["POST"])
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    @csrf.exempt
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    @security.requires_access(
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        [(permissions.ACTION_CAN_CREATE, permissions.RESOURCE_DAG)]
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    )
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    def deploy_dag() -> Response:
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        """
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        Custom Function for the deploy_dag API
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        Creates workflow dag based on workflow dag file and refreshes
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        the session
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        """
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        json_request = request.get_json(cache=False)
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        try:
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            if json_request is None:
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                return ApiResponse.error(
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                    status=ApiResponse.STATUS_BAD_REQUEST,
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                    error=f"Did not receive any JSON request to deploy",
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                )
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            ingestion_pipeline = IngestionPipeline(**json_request)
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            deployer = DagDeployer(ingestion_pipeline)
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            response = deployer.deploy()
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            return response
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        except ValidationError as err:
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            logger.debug(traceback.format_exc())
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            logger.error(
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                f"Request Validation Error parsing payload [{json_request}]. IngestionPipeline expected: {err}"
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            )
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            return ApiResponse.error(
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                status=ApiResponse.STATUS_BAD_REQUEST,
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                error=f"Request Validation Error parsing payload. IngestionPipeline expected: {err}",
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            )
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        except Exception as exc:
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            logger.debug(traceback.format_exc())
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            logger.error(f"Internal error deploying [{json_request}] due to [{exc}] ")
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            return ApiResponse.error(
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                status=ApiResponse.STATUS_SERVER_ERROR,
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                error=f"Internal error while deploying due to [{exc}] ",
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            )
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    return deploy_dag
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