# Copyright 2021 Collate # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # 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. """ Test fivetran using the topology """ import json from pathlib import Path from unittest import TestCase from unittest.mock import patch from metadata.generated.schema.api.data.createPipeline import CreatePipelineRequest from metadata.generated.schema.entity.data.pipeline import Pipeline, Task from metadata.generated.schema.entity.services.pipelineService import ( PipelineConnection, PipelineService, PipelineServiceType, ) from metadata.generated.schema.metadataIngestion.workflow import ( OpenMetadataWorkflowConfig, ) from metadata.generated.schema.type.basic import FullyQualifiedEntityName from metadata.generated.schema.type.entityReference import EntityReference from metadata.ingestion.source.pipeline.fivetran.metadata import ( FivetranPipelineDetails, FivetranSource, ) mock_file_path = ( Path(__file__).parent.parent.parent / "resources/datasets/fivetran_dataset.json" ) with open(mock_file_path) as file: mock_data: dict = json.load(file) mock_fivetran_config = { "source": { "type": "fivetran", "serviceName": "fivetran_source", "serviceConnection": { "config": { "type": "Fivetran", "apiKey": "sample_api_key", "apiSecret": "sample_api_secret", } }, "sourceConfig": {"config": {"type": "PipelineMetadata"}}, }, "sink": {"type": "metadata-rest", "config": {}}, "workflowConfig": { "openMetadataServerConfig": { "hostPort": "http://localhost:8585/api", "authProvider": "openmetadata", "securityConfig": { "jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg" }, } }, } EXPECTED_FIVETRAN_DETAILS = FivetranPipelineDetails( source=mock_data.get("source"), destination=mock_data.get("destination"), group=mock_data.get("group"), ) EXPECTED_CREATED_PIPELINES = CreatePipelineRequest( name="wackiness_remote_aiding_pointless", displayName="test <> postgres_rds", description="", pipelineUrl="", tasks=[ Task( name="wackiness_remote_aiding_pointless", displayName="test <> postgres_rds", description="", ) ], service=FullyQualifiedEntityName(__root__="fivetran_source"), ) MOCK_PIPELINE_SERVICE = PipelineService( id="85811038-099a-11ed-861d-0242ac120002", name="fivetran_source", fullyQualifiedName=FullyQualifiedEntityName(__root__="fivetran_source"), connection=PipelineConnection(), serviceType=PipelineServiceType.Fivetran, ) MOCK_PIPELINE = Pipeline( id="2aaa012e-099a-11ed-861d-0242ac120002", name="wackiness_remote_aiding_pointless", fullyQualifiedName="fivetran_source.wackiness_remote_aiding_pointless", displayName="test <> postgres_rds", description="", pipelineUrl="", tasks=[ Task( name="wackiness_remote_aiding_pointless", displayName="test <> postgres_rds", description="", taskUrl="", ) ], service=EntityReference( id="85811038-099a-11ed-861d-0242ac120002", type="pipelineService" ), ) class FivetranUnitTest(TestCase): @patch( "metadata.ingestion.source.pipeline.pipeline_service.PipelineServiceSource.test_connection" ) @patch("metadata.ingestion.source.pipeline.fivetran.connection.get_connection") def __init__(self, methodName, fivetran_client, test_connection) -> None: super().__init__(methodName) test_connection.return_value = False config = OpenMetadataWorkflowConfig.parse_obj(mock_fivetran_config) self.fivetran = FivetranSource.create( mock_fivetran_config["source"], config.workflowConfig.openMetadataServerConfig, ) self.fivetran.context.__dict__["pipeline"] = MOCK_PIPELINE self.fivetran.context.__dict__["pipeline_service"] = MOCK_PIPELINE_SERVICE self.client = fivetran_client.return_value self.client.list_groups.return_value = [mock_data.get("group")] self.client.list_group_connectors.return_value = [mock_data.get("source")] self.client.get_destination_details.return_value = mock_data.get("destination") self.client.get_connector_details.return_value = mock_data.get("source") def test_pipeline_list(self): assert list(self.fivetran.get_pipelines_list())[0] == EXPECTED_FIVETRAN_DETAILS def test_pipeline_name(self): assert ( self.fivetran.get_pipeline_name(EXPECTED_FIVETRAN_DETAILS) == f'{mock_data.get("group").get("id")}_{mock_data.get("source").get("id")}' ) def test_pipelines(self): pipline = list(self.fivetran.yield_pipeline(EXPECTED_FIVETRAN_DETAILS))[0] assert pipline == EXPECTED_CREATED_PIPELINES