def test_documentation(): platform = "urn:li:dataPlatform:kafka" dataset_name = ("test-timeline-sample-kafka") env = "PROD" dataset_urn = f"urn:li:dataset:({platform},{dataset_name},{env})" put(dataset_urn, "institutionalMemory", "test_resources/timeline/newdocumentation.json") put(dataset_urn, "institutionalMemory", "test_resources/timeline/newdocumentationv2.json") put(dataset_urn, "institutionalMemory", "test_resources/timeline/newdocumentationv3.json") res_data = timeline_cli.get_timeline(dataset_urn, ["DOCUMENTATION"], None, None, False) delete_cli.delete_one_urn_cmd(dataset_urn, False, False, "dataset", None, None) assert res_data assert len(res_data) == 3 assert res_data[0]["semVerChange"] == "MINOR" assert len(res_data[0]["changeEvents"]) == 1 assert res_data[1]["semVerChange"] == "MINOR" assert len(res_data[1]["changeEvents"]) == 1 assert res_data[2]["semVerChange"] == "MINOR" assert len(res_data[2]["changeEvents"]) == 3 assert res_data[2]["semVer"] == "0.2.0-computed"
def test_glossary(): platform = "urn:li:dataPlatform:kafka" dataset_name = ("test-timeline-sample-kafka") env = "PROD" dataset_urn = f"urn:li:dataset:({platform},{dataset_name},{env})" put(dataset_urn, "glossaryTerms", "test_resources/timeline/newglossary.json") put(dataset_urn, "glossaryTerms", "test_resources/timeline/newglossaryv2.json") put(dataset_urn, "glossaryTerms", "test_resources/timeline/newglossaryv3.json") res_data = timeline_cli.get_timeline(dataset_urn, ["GLOSSARY_TERM"], None, None, False) delete_cli.delete_one_urn_cmd(dataset_urn, False, False, "dataset", None, None) assert res_data assert len(res_data) == 3 assert res_data[0]["semVerChange"] == "MINOR" assert len(res_data[0]["changeEvents"]) == 1 assert res_data[1]["semVerChange"] == "MINOR" assert len(res_data[1]["changeEvents"]) == 1 assert res_data[2]["semVerChange"] == "MINOR" assert len(res_data[2]["changeEvents"]) == 2 assert res_data[2]["semVer"] == "0.2.0-computed"
def test_all(): platform = "urn:li:dataPlatform:kafka" dataset_name = ("test-timeline-sample-kafka") env = "PROD" dataset_urn = f"urn:li:dataset:({platform},{dataset_name},{env})" ingest_file_via_rest("tests/timeline/timeline_test_data.json") ingest_file_via_rest("tests/timeline/timeline_test_datav2.json") ingest_file_via_rest("tests/timeline/timeline_test_datav3.json") res_data = timeline_cli.get_timeline(dataset_urn, [ "TAG", "DOCUMENTATION", "TECHNICAL_SCHEMA", "GLOSSARY_TERM", "OWNERSHIP" ], None, None, False) delete_cli.delete_one_urn_cmd(dataset_urn, False, False, "dataset", None, None) assert res_data assert len(res_data) == 3 assert res_data[0]["semVerChange"] == "MINOR" assert len(res_data[0]["changeEvents"]) == 10 assert res_data[1]["semVerChange"] == "MAJOR" assert len(res_data[1]["changeEvents"]) == 9 assert res_data[2]["semVerChange"] == "MAJOR" assert len(res_data[2]["changeEvents"]) == 7 assert res_data[2]["semVer"] == "2.0.0-computed"
def test_schema(): platform = "urn:li:dataPlatform:kafka" dataset_name = ("test-timeline-sample-kafka") env = "PROD" dataset_urn = f"urn:li:dataset:({platform},{dataset_name},{env})" put(dataset_urn, "schemaMetadata", "test_resources/timeline/newschema.json") put(dataset_urn, "schemaMetadata", "test_resources/timeline/newschemav2.json") put(dataset_urn, "schemaMetadata", "test_resources/timeline/newschemav3.json") res_data = timeline_cli.get_timeline(dataset_urn, ["TECHNICAL_SCHEMA"], None, None, False) delete_cli.delete_one_urn_cmd(dataset_urn, False, False, "dataset", None, None) assert res_data assert len(res_data) == 3 assert res_data[0]["semVerChange"] == "MINOR" assert len(res_data[0]["changeEvents"]) == 6 assert res_data[1]["semVerChange"] == "MAJOR" assert len(res_data[1]["changeEvents"]) == 2 assert res_data[2]["semVerChange"] == "MAJOR" assert len(res_data[2]["changeEvents"]) == 2 assert res_data[2]["semVer"] == "2.0.0-computed"