OpenMetadata/ingestion/tests/unit/topology/pipeline/test_dagster.py

#  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 Dagster 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,
    PipelineStatus,
    StatusType,
    Task,
    TaskStatus,
)
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, SourceUrl
from metadata.generated.schema.type.entityReference import EntityReference
from metadata.generated.schema.type.tagLabel import (
    LabelType,
    State,
    TagLabel,
    TagSource,
)
from metadata.ingestion.models.pipeline_status import OMetaPipelineStatus
from metadata.ingestion.source.pipeline.dagster.metadata import DagsterSource
from metadata.ingestion.source.pipeline.dagster.models import GraphOrError

mock_file_path = (
    Path(__file__).parent.parent.parent / "resources/datasets/dagster_dataset.json"
)
with open(mock_file_path, encoding="UTF-8") as file:
    mock_data: dict = json.load(file)

mock_dagster_config = {
    "source": {
        "type": "dagster",
        "serviceName": "dagster_source",
        "serviceConnection": {
            "config": {"type": "Dagster", "host": "http://lolhost:3000"}
        },
        "sourceConfig": {"config": {"type": "PipelineMetadata"}},
    },
    "sink": {"type": "metadata-rest", "config": {}},
    "workflowConfig": {
        "openMetadataServerConfig": {
            "hostPort": "http://localhost:8585/api",
            "authProvider": "openmetadata",
            "securityConfig": {"jwtToken": "jnsdjonfonsodifnoisdnfoinsdonfonsd"},
        }
    },
}


EXPECTED_DAGSTER_DETAILS = mock_data["data"]["graphOrError"]

EXPECTED_CREATED_PIPELINES = [
    CreatePipelineRequest(
        name="graph5164c131c3524a271e7ecce49766d50a479b5ff4",
        displayName="story_recommender_job",
        description=None,
        concurrency=None,
        pipelineLocation=None,
        startDate=None,
        tasks=[
            Task(
                name="s3__recommender__recommender_model",
                displayName="s3__recommender__recommender_model",
                fullyQualifiedName=None,
                description=None,
                downstreamTasks=["s3__recommender__user_story_matrix"],
                taskType=None,
                taskSQL=None,
                startDate=None,
                endDate=None,
                tags=[],
                sourceUrl=SourceUrl(
                    "http://lolhost:3000/locations/project_fully_featured/jobs/story_recommender_job/s3__recommender__recommender_model"
                ),
            ),
            Task(
                name="s3__recommender__user_story_matrix",
                displayName="s3__recommender__user_story_matrix",
                fullyQualifiedName=None,
                description=None,
                downstreamTasks=["snowflake__recommender__comment_stories"],
                taskType=None,
                taskSQL=None,
                startDate=None,
                endDate=None,
                tags=[],
                sourceUrl=SourceUrl(
                    "http://lolhost:3000/locations/project_fully_featured/jobs/story_recommender_job/s3__recommender__user_story_matrix"
                ),
            ),
            Task(
                name="snowflake__recommender__comment_stories",
                displayName="snowflake__recommender__comment_stories",
                fullyQualifiedName=None,
                description=None,
                downstreamTasks=None,
                taskType=None,
                taskSQL=None,
                startDate=None,
                endDate=None,
                tags=[],
                sourceUrl=SourceUrl(
                    "http://lolhost:3000/locations/project_fully_featured/jobs/story_recommender_job/snowflake__recommender__comment_stories"
                ),
            ),
            Task(
                name="snowflake__recommender__component_top_stories",
                displayName="snowflake__recommender__component_top_stories",
                fullyQualifiedName=None,
                description=None,
                downstreamTasks=[
                    "s3__recommender__recommender_model",
                    "s3__recommender__user_story_matrix",
                ],
                taskType=None,
                taskSQL=None,
                startDate=None,
                endDate=None,
                tags=[],
                sourceUrl=SourceUrl(
                    "http://lolhost:3000/locations/project_fully_featured/jobs/story_recommender_job/snowflake__recommender__component_top_stories"
                ),
            ),
            Task(
                name="snowflake__recommender__user_top_recommended_stories",
                displayName="snowflake__recommender__user_top_recommended_stories",
                fullyQualifiedName=None,
                description=None,
                downstreamTasks=[
                    "s3__recommender__recommender_model",
                    "s3__recommender__user_story_matrix",
                ],
                taskType=None,
                taskSQL=None,
                startDate=None,
                endDate=None,
                tags=[],
                sourceUrl=SourceUrl(
                    "http://lolhost:3000/locations/project_fully_featured/jobs/story_recommender_job/snowflake__recommender__user_top_recommended_stories"
                ),
            ),
        ],
        tags=[
            TagLabel(
                tagFQN="DagsterTags.hacker_new_repository",
                description=None,
                source="Classification",
                labelType="Automated",
                state="Suggested",
                href=None,
            )
        ],
        owners=None,
        service="dagster_source_test",
        extension=None,
        sourceUrl=SourceUrl(
            "http://lolhost:3000/locations/project_fully_featured/jobs/story_recommender_job/"
        ),
    ),
]
MOCK_CONNECTION_URI_PATH = (
    "/workspace/__repository__do_it_all_with_default_config"
    "@cereal.py/jobs/do_it_all_with_default_config/"
)
MOCK_LOG_URL = (
    "http://localhost:8080/instance/runs/a6ebb16c-505f-446d-8642-171c3320ccef"
)

EXPTECTED_PIPELINE_NAME = ["story_recommender_job"]

EXPECTED_PIPELINE_STATUS = [
    OMetaPipelineStatus(
        pipeline_fqn="dagster_source.a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
        pipeline_status=PipelineStatus(
            executionStatus=StatusType.Pending.value,
            taskStatus=[
                TaskStatus(
                    name="a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
                    executionStatus=StatusType.Pending.value,
                    startTime=1659616627124,
                    endTime=1659616635858,
                    logLink=f"{MOCK_LOG_URL}/status",
                )
            ],
            timestamp=1659616635858,
        ),
    ),
    OMetaPipelineStatus(
        pipeline_fqn="dagster_source.a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
        pipeline_status=PipelineStatus(
            executionStatus=StatusType.Successful.value,
            taskStatus=[
                TaskStatus(
                    name="a10f6d82-4fc6-4c90-ba04-bb773c8fbb0f",
                    executionStatus=StatusType.Successful.value,
                    startTime=1655393914000,
                    endTime=1655394054000,
                    logLink=f"{MOCK_LOG_URL}/status",
                )
            ],
            timestamp=1655393914000,
        ),
    ),
]

MOCK_PIPELINE_SERVICE = PipelineService(
    id="86ff3c40-7c51-4ff5-9727-738cead28d9a",
    name="dagster_source_test",
    fullyQualifiedName=FullyQualifiedEntityName("dagster_source_test"),
    connection=PipelineConnection(),
    serviceType=PipelineServiceType.Dagster,
)


MOCK_PIPELINE = Pipeline(
    id="a58b1856-729c-493b-bc87-6d2269b43ec0",
    name="do_it_all_with_default_config",
    fullyQualifiedName="dagster_source.do_it_all_with_default_config",
    displayName="do_it_all_with_default_config",
    description="",
    sourceUrl=MOCK_CONNECTION_URI_PATH,
    tasks=[
        Task(
            name="a58b1856-729c-493b-bc87-6d2269b43ec0",
            displayName="do_it_all_with_default_config",
        )
    ],
    service=EntityReference(
        id="85811038-099a-11ed-861d-0242ac120002", type="pipelineService"
    ),
)


class DagsterUnitTest(TestCase):
    """
    Implements the necessary methods to extract
    Dagster Pipeline Unit Test
    """

    @patch(
        "metadata.ingestion.source.pipeline.pipeline_service.PipelineServiceSource.test_connection"
    )
    @patch("dagster_graphql.DagsterGraphQLClient")
    # @patch("metadata.ingestion.source.pipeline.dagster.get_tag_labels")
    def __init__(self, methodName, graphql_client, test_connection) -> None:
        super().__init__(methodName)
        test_connection.return_value = False
        graphql_client.return_value = False
        config = OpenMetadataWorkflowConfig.model_validate(mock_dagster_config)
        self.dagster = DagsterSource.create(
            mock_dagster_config["source"],
            config.workflowConfig.openMetadataServerConfig,
        )
        self.dagster.context.get().__dict__["pipeline"] = MOCK_PIPELINE.name.root
        self.dagster.context.get().__dict__[
            "pipeline_service"
        ] = MOCK_PIPELINE_SERVICE.name.root
        self.dagster.context.get().__dict__["repository_name"] = "hacker_new_repository"
        self.dagster.context.get().__dict__[
            "repository_location"
        ] = "project_fully_featured"

    def test_pipeline_name(self):
        assert (
            self.dagster.get_pipeline_name(GraphOrError(**EXPECTED_DAGSTER_DETAILS))
            in EXPTECTED_PIPELINE_NAME
        )

    @patch("metadata.ingestion.source.pipeline.dagster.client.DagsterClient.get_jobs")
    @patch("metadata.utils.tag_utils.get_tag_label")
    def test_yield_pipeline(self, get_tag_label, get_jobs):
        results = self.dagster.yield_pipeline(GraphOrError(**EXPECTED_DAGSTER_DETAILS))
        get_jobs.return_value = GraphOrError(**EXPECTED_DAGSTER_DETAILS)
        get_tag_label.return_value = TagLabel(
            tagFQN="DagsterTags.hacker_new_repository",
            labelType=LabelType.Automated.value,
            state=State.Suggested.value,
            source=TagSource.Classification.value,
        )
        pipelines_list = []
        for result in results:
            pipelines_list.append(result.right)

        for _, (expected, original) in enumerate(
            zip(EXPECTED_CREATED_PIPELINES, pipelines_list)
        ):
            self.assertEqual(expected, original)