2025-04-03 10:39:47 +05:30

90 lines
3.2 KiB
Python

# Copyright 2025 Collate
# Licensed under the Collate Community License, Version 1.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Deploy the DAG and scan it with the scheduler
"""
import traceback
from typing import Callable
from flask import Blueprint, Response, request
from openmetadata_managed_apis.api.response import ApiResponse
from openmetadata_managed_apis.operations.deploy import DagDeployer
from openmetadata_managed_apis.utils.logger import routes_logger
from pydantic import ValidationError
from metadata.ingestion.api.parser import parse_ingestion_pipeline_config_gracefully
logger = routes_logger()
def get_fn(blueprint: Blueprint) -> Callable:
"""
Return the function loaded to a route
:param blueprint: Flask Blueprint to assign route to
:return: routed function
"""
# Lazy import the requirements
# pylint: disable=import-outside-toplevel
from airflow.api_connexion import security
from airflow.security import permissions
from airflow.www.app import csrf
@blueprint.route("/deploy", methods=["POST"])
@csrf.exempt
@security.requires_access(
[(permissions.ACTION_CAN_CREATE, permissions.RESOURCE_DAG)]
)
def deploy_dag() -> Response:
"""
Custom Function for the deploy_dag API
Creates workflow dag based on workflow dag file and refreshes
the session
"""
json_request = request.get_json(cache=False)
try:
if json_request is None:
return ApiResponse.error(
status=ApiResponse.STATUS_BAD_REQUEST,
error="Did not receive any JSON request to deploy",
)
ingestion_pipeline = parse_ingestion_pipeline_config_gracefully(
json_request
)
deployer = DagDeployer(ingestion_pipeline)
response = deployer.deploy()
return response
except ValidationError as err:
logger.debug(traceback.format_exc())
logger.error(
f"Request Validation Error parsing payload [{json_request}]. IngestionPipeline expected: {err}"
)
return ApiResponse.error(
status=ApiResponse.STATUS_BAD_REQUEST,
error=f"Request Validation Error parsing payload. IngestionPipeline expected: {err}",
)
except Exception as exc:
logger.debug(traceback.format_exc())
logger.error(f"Internal error deploying [{json_request}] due to [{exc}] ")
return ApiResponse.error(
status=ApiResponse.STATUS_SERVER_ERROR,
error=f"Internal error while deploying due to [{exc}] ",
)
return deploy_dag