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4c6d184ef5
* Fixes #10480 Glossary rename results in rename of Classification with the same name * Rename TagSource Tag to Classification
284 lines
9.8 KiB
Python
284 lines
9.8 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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Test Dagster 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 (
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Pipeline,
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PipelineStatus,
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StatusType,
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Task,
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TaskStatus,
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)
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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.basic import FullyQualifiedEntityName
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from metadata.generated.schema.type.entityReference import EntityReference
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from metadata.generated.schema.type.tagLabel import TagLabel
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from metadata.ingestion.models.pipeline_status import OMetaPipelineStatus
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from metadata.ingestion.source.pipeline.dagster.metadata import DagsterSource
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mock_file_path = (
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Path(__file__).parent.parent.parent / "resources/datasets/dagster_dataset.json"
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)
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with open(mock_file_path, encoding="UTF-8") as file:
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mock_data: dict = json.load(file)
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mock_dagster_config = {
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"source": {
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"type": "dagster",
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"serviceName": "dagster_source",
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"serviceConnection": {
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"config": {"type": "Dagster", "host": "http://lolhost:3000"}
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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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"authProvider": "openmetadata",
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"securityConfig": {"jwtToken": "jnsdjonfonsodifnoisdnfoinsdonfonsd"},
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}
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},
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}
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EXPECTED_DAGSTER_DETAILS = mock_data["data"]["graphOrError"]
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EXPECTED_CREATED_PIPELINES = [
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CreatePipelineRequest(
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name="graph5164c131c3524a271e7ecce49766d50a479b5ff4",
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displayName="story_recommender_job",
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description=None,
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pipelineUrl=None,
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concurrency=None,
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pipelineLocation=None,
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startDate=None,
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tasks=[
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Task(
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name="s3__recommender__recommender_model",
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displayName="s3__recommender__recommender_model",
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fullyQualifiedName=None,
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description=None,
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taskUrl=None,
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downstreamTasks=["s3__recommender__user_story_matrix"],
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taskType=None,
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taskSQL=None,
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startDate=None,
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endDate=None,
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tags=None,
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),
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Task(
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name="s3__recommender__user_story_matrix",
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displayName="s3__recommender__user_story_matrix",
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fullyQualifiedName=None,
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description=None,
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taskUrl=None,
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downstreamTasks=["snowflake__recommender__comment_stories"],
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taskType=None,
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taskSQL=None,
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startDate=None,
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endDate=None,
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tags=None,
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),
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Task(
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name="snowflake__recommender__comment_stories",
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displayName="snowflake__recommender__comment_stories",
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fullyQualifiedName=None,
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description=None,
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taskUrl=None,
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downstreamTasks=[],
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taskType=None,
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taskSQL=None,
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startDate=None,
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endDate=None,
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tags=None,
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),
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Task(
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name="snowflake__recommender__component_top_stories",
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displayName="snowflake__recommender__component_top_stories",
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fullyQualifiedName=None,
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description=None,
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taskUrl=None,
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downstreamTasks=[
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"s3__recommender__recommender_model",
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"s3__recommender__user_story_matrix",
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],
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taskType=None,
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taskSQL=None,
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startDate=None,
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endDate=None,
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tags=None,
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),
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Task(
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name="snowflake__recommender__user_top_recommended_stories",
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displayName="snowflake__recommender__user_top_recommended_stories",
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fullyQualifiedName=None,
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description=None,
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taskUrl=None,
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downstreamTasks=[
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"s3__recommender__recommender_model",
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"s3__recommender__user_story_matrix",
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],
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taskType=None,
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taskSQL=None,
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startDate=None,
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endDate=None,
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tags=None,
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),
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],
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tags=[
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TagLabel(
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tagFQN="DagsterTags.hacker_new_repository",
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description=None,
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source="Classification",
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labelType="Automated",
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state="Suggested",
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href=None,
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)
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],
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owner=None,
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service="dagster_source_test",
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extension=None,
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),
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]
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MOCK_CONNECTION_URI_PATH = (
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"/workspace/__repository__do_it_all_with_default_config"
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"@cereal.py/jobs/do_it_all_with_default_config/"
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)
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MOCK_LOG_URL = (
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"http://localhost:8080/instance/runs/a6ebb16c-505f-446d-8642-171c3320ccef"
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)
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EXPTECTED_PIPELINE_NAME = ["story_recommender_job"]
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EXPECTED_PIPELINE_STATUS = [
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OMetaPipelineStatus(
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pipeline_fqn="dagster_source.a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
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pipeline_status=PipelineStatus(
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executionStatus=StatusType.Pending.value,
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taskStatus=[
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TaskStatus(
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name="a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
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executionStatus=StatusType.Pending.value,
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startTime=1659616627124,
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endTime=1659616635858,
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logLink=f"{MOCK_LOG_URL}/status",
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)
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],
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timestamp=1659616635858,
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),
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),
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OMetaPipelineStatus(
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pipeline_fqn="dagster_source.a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
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pipeline_status=PipelineStatus(
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executionStatus=StatusType.Successful.value,
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taskStatus=[
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TaskStatus(
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name="a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
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executionStatus=StatusType.Successful.value,
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startTime=1655393914,
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endTime=1655394054,
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logLink=f"{MOCK_LOG_URL}/status",
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)
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],
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timestamp=1655393914,
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),
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),
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]
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MOCK_PIPELINE_SERVICE = PipelineService(
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id="86ff3c40-7c51-4ff5-9727-738cead28d9a",
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name="dagster_source_test",
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fullyQualifiedName=FullyQualifiedEntityName(__root__="dagster_source_test"),
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connection=PipelineConnection(),
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serviceType=PipelineServiceType.Dagster,
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)
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MOCK_PIPELINE = Pipeline(
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id="a58b1856-729c-493b-bc87-6d2269b43ec0",
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name="do_it_all_with_default_config",
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fullyQualifiedName="dagster_source.do_it_all_with_default_config",
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displayName="do_it_all_with_default_config",
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description="",
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pipelineUrl=MOCK_CONNECTION_URI_PATH,
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tasks=[
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Task(
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name="a58b1856-729c-493b-bc87-6d2269b43ec0",
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displayName="do_it_all_with_default_config",
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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 DagsterUnitTest(TestCase):
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"""
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Implements the necessary methods to extract
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Dagster Pipeline Unit Test
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"""
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@patch(
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"metadata.ingestion.source.pipeline.pipeline_service.PipelineServiceSource.test_connection"
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)
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@patch("dagster_graphql.DagsterGraphQLClient")
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# @patch("metadata.ingestion.source.pipeline.dagster.get_tag_labels")
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def __init__(self, methodName, graphql_client, test_connection) -> None:
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super().__init__(methodName)
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test_connection.return_value = False
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graphql_client.return_value = False
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config = OpenMetadataWorkflowConfig.parse_obj(mock_dagster_config)
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self.dagster = DagsterSource.create(
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mock_dagster_config["source"],
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config.workflowConfig.openMetadataServerConfig,
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)
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self.dagster.context.__dict__["pipeline"] = MOCK_PIPELINE
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self.dagster.context.__dict__["pipeline_service"] = MOCK_PIPELINE_SERVICE
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self.dagster.context.__dict__["repository_name"] = "hacker_new_repository"
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self.dagster.context.__dict__["repository_location"] = "project_fully_featured"
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def test_pipeline_name(self):
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assert (
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self.dagster.get_pipeline_name(EXPECTED_DAGSTER_DETAILS)
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in EXPTECTED_PIPELINE_NAME
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)
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@patch("metadata.ingestion.source.pipeline.dagster.metadata.DagsterSource.get_jobs")
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def test_yield_pipeline(self, get_jobs):
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results = self.dagster.yield_pipeline(EXPECTED_DAGSTER_DETAILS)
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get_jobs.return_value = EXPECTED_DAGSTER_DETAILS
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pipelines_list = []
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for result in results:
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pipelines_list.append(result)
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for _, (expected, original) in enumerate(
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zip(EXPECTED_CREATED_PIPELINES, pipelines_list)
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):
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self.assertEqual(expected, original)
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