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221 lines
6.3 KiB
Python
221 lines
6.3 KiB
Python
import logging
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from typing import List
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import pytest
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import yaml
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from pydantic import ValidationError
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from datahub.ingestion.source.metadata.lineage import LineageConfig, _get_lineage_mcp
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from datahub.metadata.schema_classes import FineGrainedLineageClass, UpstreamClass
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logger = logging.getLogger(__name__)
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@pytest.fixture
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def basic_mcp():
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"""
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The below mcp should represent a lineage that looks like this
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topic1 -
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->topic3
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topic2 -
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:return:
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"""
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sample_lineage = """
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lineage:
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- entity:
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name: topic3
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type: dataset
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env: DEV
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platform: kafka
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upstream:
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- entity:
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name: topic1
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic2
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type: dataset
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env: DEV
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platform: kafka
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fineGrainedLineages:
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- upstreamType: FIELD_SET
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upstreams:
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- urn:li:schemaField:(urn:li:dataset:(urn:li:dataPlatform:kafka,topic1,PROD),user_id)
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downstreamType: FIELD_SET
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downstreams:
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- urn:li:schemaField:(urn:li:dataset:(urn:li:dataPlatform:kafka,topic3,PROD),user_id)
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confidenceScore: 0.9
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transformOperation: func1
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"""
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config = yaml.safe_load(sample_lineage)
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lineage_config: LineageConfig = LineageConfig.parse_obj(config)
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return _get_lineage_mcp(lineage_config.lineage[0], False)
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def unsupported_entity_type_mcp():
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sample_lineage = """
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lineage:
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- entity:
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name: topic3
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type: NotSupported!
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env: DEV
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platform: kafka
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upstream:
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- entity:
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name: topic1
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic2
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic6
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type: dataset
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env: DEV
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platform: kafka
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upstream:
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- entity:
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name: topic4
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic5
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type: dataset
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env: DEV
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platform: kafka
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"""
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config = yaml.safe_load(sample_lineage)
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return LineageConfig.parse_obj(config)
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def unsupported_upstream_entity_type_mcp():
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sample_lineage = """
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lineage:
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- entity:
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name: topic3
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type: dataset
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env: DEV
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platform: kafka
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upstream:
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- entity:
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name: topic1
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type: NotSupported
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env: DEV
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platform: kafka
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- entity:
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name: topic2
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type: dataset
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env: DEV
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platform: kafka
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"""
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config = yaml.safe_load(sample_lineage)
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return LineageConfig.parse_obj(config)
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def unsupported_entity_env_mcp():
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sample_lineage = """
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lineage:
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- entity:
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name: topic3
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type: dataset
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env: NotSupported!
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platform: kafka
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upstream:
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- entity:
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name: topic1
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic2
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic6
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type: dataset
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env: DEV
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platform: kafka
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upstream:
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- entity:
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name: topic4
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type: dataset
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env: DEV
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platform: kafka
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- entity:
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name: topic5
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type: dataset
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env: DEV
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platform: kafka
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"""
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config = yaml.safe_load(sample_lineage)
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return LineageConfig.parse_obj(config)
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def test_basic_lineage_entity_root_node_urn(basic_mcp):
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"""
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Checks to see if the entityUrn extracted is correct for the root entity node
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"""
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assert (
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basic_mcp.entityUrn == "urn:li:dataset:(urn:li:dataPlatform:kafka,topic3,DEV)"
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)
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def test_basic_lineage_upstream_urns(basic_mcp):
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"""
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Checks to see if the upstream urns are correct for a basic_mcp example
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"""
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basic_mcp_upstreams: List[UpstreamClass] = basic_mcp.aspect.upstreams
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assert (
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basic_mcp_upstreams[0].dataset
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== "urn:li:dataset:(urn:li:dataPlatform:kafka,topic1,DEV)"
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and basic_mcp_upstreams[1].dataset
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== "urn:li:dataset:(urn:li:dataPlatform:kafka,topic2,DEV)"
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)
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def test_basic_lineage_finegrained_upstream_urns(basic_mcp):
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"""
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Checks to see if the finegrained urns are correct for a basic_mcp example
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"""
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fine_grained_lineage: FineGrainedLineageClass = (
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basic_mcp.aspect.fineGrainedLineages[0]
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)
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assert fine_grained_lineage.upstreamType == "FIELD_SET"
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assert fine_grained_lineage.downstreamType == "FIELD_SET"
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assert fine_grained_lineage.confidenceScore == 0.9
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assert fine_grained_lineage.transformOperation == "func1"
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def test_unsupported_entity_type():
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"""
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Checks to see how we handle the case of unsupported entity types.
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If validation is working correctly, it should raise a ValidationError
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"""
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with pytest.raises(ValidationError):
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unsupported_entity_type_mcp()
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def test_unsupported_upstream_entity_type():
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"""
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Checks to see how invalid types work in the upstream node.
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If validation is working correctly, it should raise a ValidationError
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"""
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with pytest.raises(ValidationError):
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unsupported_upstream_entity_type_mcp()
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def test_unsupported_entity_env():
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"""
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Checks to see how invalid envs work.
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If validation is working correctly, it should raise a ValidationError
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"""
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with pytest.raises(ValidationError):
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unsupported_entity_env_mcp()
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