mirror of
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90 lines
3.2 KiB
Python
90 lines
3.2 KiB
Python
# Copyright 2025 Collate
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# Licensed under the Collate Community License, Version 1.0 (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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# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
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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.ingestion.api.parser import parse_ingestion_pipeline_config_gracefully
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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="Did not receive any JSON request to deploy",
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)
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ingestion_pipeline = parse_ingestion_pipeline_config_gracefully(
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json_request
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)
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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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