2022-07-27 20:50:56 +05:30
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# 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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Test fivetran using the topology
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"""
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import json
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from pathlib import Path
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from unittest import TestCase
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from unittest.mock import patch
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from metadata.generated.schema.api.data.createPipeline import CreatePipelineRequest
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from metadata.generated.schema.entity.data.pipeline import Pipeline, Task
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from metadata.generated.schema.entity.services.pipelineService import (
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PipelineConnection,
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PipelineService,
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PipelineServiceType,
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)
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from metadata.generated.schema.metadataIngestion.workflow import (
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OpenMetadataWorkflowConfig,
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)
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from metadata.generated.schema.type.entityReference import EntityReference
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from metadata.ingestion.source.pipeline.fivetran import (
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FivetranPipelineDetails,
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FivetranSource,
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)
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mock_file_path = (
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Path(__file__).parent.parent.parent / "resources/datasets/fivetran_dataset.json"
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)
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with open(mock_file_path) as file:
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mock_data: dict = json.load(file)
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mock_fivetran_config = {
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"source": {
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"type": "fivetran",
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"serviceName": "fivetran_source",
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"serviceConnection": {
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"config": {
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"type": "Fivetran",
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"apiKey": "sample_api_key",
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"apiSecret": "sample_api_secret",
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}
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},
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"sourceConfig": {"config": {"type": "PipelineMetadata"}},
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},
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"sink": {"type": "metadata-rest", "config": {}},
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"workflowConfig": {
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"openMetadataServerConfig": {
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"hostPort": "http://localhost:8585/api",
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2022-09-26 16:19:47 +05:30
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"authProvider": "openmetadata",
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"securityConfig": {
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"jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
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},
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2022-07-27 20:50:56 +05:30
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}
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},
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}
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EXPECTED_FIVETRAN_DETAILS = FivetranPipelineDetails(
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source=mock_data.get("source"),
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destination=mock_data.get("destination"),
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group=mock_data.get("group"),
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)
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EXPECTED_CREATED_PIPELINES = CreatePipelineRequest(
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name="wackiness_remote_aiding_pointless",
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displayName="test <> postgres_rds",
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description="",
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pipelineUrl="",
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tasks=[
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Task(
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name="wackiness_remote_aiding_pointless",
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displayName="test <> postgres_rds",
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description="",
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)
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],
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service=EntityReference(
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id="85811038-099a-11ed-861d-0242ac120002", type="pipelineService"
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),
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)
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MOCK_PIPELINE_SERVICE = PipelineService(
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id="85811038-099a-11ed-861d-0242ac120002",
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name="fivetran_source",
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connection=PipelineConnection(),
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serviceType=PipelineServiceType.Fivetran,
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)
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MOCK_PIPELINE = Pipeline(
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id="2aaa012e-099a-11ed-861d-0242ac120002",
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name="wackiness_remote_aiding_pointless",
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fullyQualifiedName="fivetran_source.wackiness_remote_aiding_pointless",
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displayName="test <> postgres_rds",
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description="",
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pipelineUrl="",
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tasks=[
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Task(
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name="wackiness_remote_aiding_pointless",
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displayName="test <> postgres_rds",
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description="",
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taskUrl="",
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)
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],
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service=EntityReference(
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id="85811038-099a-11ed-861d-0242ac120002", type="pipelineService"
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),
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)
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class FivetranUnitTest(TestCase):
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@patch("metadata.ingestion.source.pipeline.pipeline_service.test_connection")
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@patch("metadata.ingestion.source.pipeline.fivetran.FivetranClient")
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def __init__(self, methodName, fivetran_client, test_connection) -> None:
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super().__init__(methodName)
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test_connection.return_value = False
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config = OpenMetadataWorkflowConfig.parse_obj(mock_fivetran_config)
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self.fivetran = FivetranSource.create(
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mock_fivetran_config["source"],
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config.workflowConfig.openMetadataServerConfig,
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)
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self.fivetran.context.__dict__["pipeline"] = MOCK_PIPELINE
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self.fivetran.context.__dict__["pipeline_service"] = MOCK_PIPELINE_SERVICE
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self.client = fivetran_client.return_value
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self.client.list_groups.return_value = [mock_data.get("group")]
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self.client.list_group_connectors.return_value = [mock_data.get("source")]
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self.client.get_destination_details.return_value = mock_data.get("destination")
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self.client.get_connector_details.return_value = mock_data.get("source")
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def test_pipeline_list(self):
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assert list(self.fivetran.get_pipelines_list())[0] == EXPECTED_FIVETRAN_DETAILS
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def test_pipeline_name(self):
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assert (
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self.fivetran.get_pipeline_name(EXPECTED_FIVETRAN_DETAILS)
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== f'{mock_data.get("group").get("id")}_{mock_data.get("source").get("id")}'
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)
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def test_pipelines(self):
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pipline = list(self.fivetran.yield_pipeline(EXPECTED_FIVETRAN_DETAILS))[0]
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assert pipline == EXPECTED_CREATED_PIPELINES
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