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test(ingest/mcp_diff): Fallback to overwriting file on more complicated diffs (#11407)
Co-authored-by: Harshal Sheth <hsheth2@gmail.com>
This commit is contained in:
Andrew Sikowitz
GitHub
parent
de40d251e2
commit
3e3a05f09c
@ -19,7 +19,8 @@
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},
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"externalUrl": "http://airflow.example.com/tree?dag_id=datahub_emitter_operator_jinja_template_dag",
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"name": "datahub_emitter_operator_jinja_template_dag",
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"description": "An example dag with jinja template"
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"description": "An example dag with jinja template",
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"env": "PROD"
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}
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}
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},
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@ -140,13 +141,14 @@
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"downstream_task_ids": "[]",
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"inlets": "[]",
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"outlets": "[]",
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"openlineage_run_facet_unknownSourceAttribute": "{\"_producer\": \"https://github.com/OpenLineage/OpenLineage/tree/1.18.0/integration/airflow\", \"_schemaURL\": \"https://openlineage.io/spec/2-0-2/OpenLineage.json#/$defs/BaseFacet\", \"unknownItems\": [{\"name\": \"DatahubEmitterOperator\", \"properties\": {\"depends_on_past\": false, \"downstream_task_ids\": \"[]\", \"execution_timeout\": \"<<non-serializable: timedelta>>\", \"executor_config\": {}, \"ignore_first_depends_on_past\": true, \"is_setup\": false, \"is_teardown\": false, \"mapped\": false, \"operator_class\": \"datahub_airflow_plugin.operators.datahub.DatahubEmitterOperator\", \"owner\": \"airflow\", \"priority_weight\": 1, \"queue\": \"default\", \"retries\": 0, \"retry_exponential_backoff\": false, \"task_id\": \"datahub_emitter_operator_jinja_template_dag_task\", \"trigger_rule\": \"all_success\", \"upstream_task_ids\": \"[]\", \"wait_for_downstream\": false, \"wait_for_past_depends_before_skipping\": false, \"weight_rule\": \"downstream\"}, \"type\": \"operator\"}]}"
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"openlineage_run_facet_unknownSourceAttribute": "{\"_producer\": \"https://github.com/OpenLineage/OpenLineage/tree/1.18.0/integration/airflow\", \"_schemaURL\": \"https://openlineage.io/spec/2-0-2/OpenLineage.json#/$defs/BaseFacet\", \"unknownItems\": [{\"name\": \"DatahubEmitterOperator\", \"properties\": {\"depends_on_past\": false, \"downstream_task_ids\": \"[]\", \"execution_timeout\": \"<<non-serializable: timedelta>>\", \"executor_config\": {}, \"ignore_first_depends_on_past\": true, \"is_setup\": false, \"is_teardown\": false, \"mapped\": false, \"multiple_outputs\": false, \"operator_class\": \"datahub_airflow_plugin.operators.datahub.DatahubEmitterOperator\", \"owner\": \"airflow\", \"priority_weight\": 1, \"queue\": \"default\", \"retries\": 0, \"retry_exponential_backoff\": false, \"task_id\": \"datahub_emitter_operator_jinja_template_dag_task\", \"trigger_rule\": \"all_success\", \"upstream_task_ids\": \"[]\", \"wait_for_downstream\": false, \"wait_for_past_depends_before_skipping\": false, \"weight_rule\": \"<<non-serializable: _DownstreamPriorityWeightStrategy>>\"}, \"type\": \"operator\"}]}"
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},
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"externalUrl": "http://airflow.example.com/taskinstance/list/?flt1_dag_id_equals=datahub_emitter_operator_jinja_template_dag&_flt_3_task_id=datahub_emitter_operator_jinja_template_dag_task",
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"name": "datahub_emitter_operator_jinja_template_dag_task",
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"type": {
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"string": "COMMAND"
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}
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},
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"env": "PROD"
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}
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}
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},
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@ -233,16 +235,16 @@
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"state": "running",
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"operator": "DatahubEmitterOperator",
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"priority_weight": "1",
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"log_url": "http://airflow.example.com/log?execution_date=2023-09-27T21%3A34%3A38%2B00%3A00&task_id=datahub_emitter_operator_jinja_template_dag_task&dag_id=datahub_emitter_operator_jinja_template_dag&map_index=-1",
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"log_url": "http://airflow.example.com/dags/datahub_emitter_operator_jinja_template_dag/grid?dag_run_id=manual_run_test&task_id=datahub_emitter_operator_jinja_template_dag_task&map_index=-1&tab=logs",
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"orchestrator": "airflow",
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"dag_id": "datahub_emitter_operator_jinja_template_dag",
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"task_id": "datahub_emitter_operator_jinja_template_dag_task"
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},
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"externalUrl": "http://airflow.example.com/log?execution_date=2023-09-27T21%3A34%3A38%2B00%3A00&task_id=datahub_emitter_operator_jinja_template_dag_task&dag_id=datahub_emitter_operator_jinja_template_dag&map_index=-1",
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"externalUrl": "http://airflow.example.com/dags/datahub_emitter_operator_jinja_template_dag/grid?dag_run_id=manual_run_test&task_id=datahub_emitter_operator_jinja_template_dag_task&map_index=-1&tab=logs",
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"name": "datahub_emitter_operator_jinja_template_dag_datahub_emitter_operator_jinja_template_dag_task_manual_run_test",
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"type": "BATCH_AD_HOC",
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"created": {
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"time": 1726570937652,
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"time": 1726699852909,
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"actor": "urn:li:corpuser:datahub"
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}
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}
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@ -267,7 +269,7 @@
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"aspectName": "dataProcessInstanceRunEvent",
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"aspect": {
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"json": {
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"timestampMillis": 1726570937652,
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"timestampMillis": 1726699852909,
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"partitionSpec": {
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"partition": "FULL_TABLE_SNAPSHOT",
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"type": "FULL_TABLE"
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@ -360,13 +362,14 @@
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"downstream_task_ids": "[]",
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"inlets": "[]",
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"outlets": "[]",
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"openlineage_run_facet_unknownSourceAttribute": "{\"_producer\": \"https://github.com/OpenLineage/OpenLineage/tree/1.18.0/integration/airflow\", \"_schemaURL\": \"https://openlineage.io/spec/2-0-2/OpenLineage.json#/$defs/BaseFacet\", \"unknownItems\": [{\"name\": \"DatahubEmitterOperator\", \"properties\": {\"depends_on_past\": false, \"downstream_task_ids\": \"[]\", \"execution_timeout\": \"<<non-serializable: timedelta>>\", \"executor_config\": {}, \"ignore_first_depends_on_past\": true, \"is_setup\": false, \"is_teardown\": false, \"mapped\": false, \"operator_class\": \"datahub_airflow_plugin.operators.datahub.DatahubEmitterOperator\", \"owner\": \"airflow\", \"priority_weight\": 1, \"queue\": \"default\", \"retries\": 0, \"retry_exponential_backoff\": false, \"task_id\": \"datahub_emitter_operator_jinja_template_dag_task\", \"trigger_rule\": \"all_success\", \"upstream_task_ids\": \"[]\", \"wait_for_downstream\": false, \"wait_for_past_depends_before_skipping\": false, \"weight_rule\": \"downstream\"}, \"type\": \"operator\"}]}"
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"openlineage_run_facet_unknownSourceAttribute": "{\"_producer\": \"https://github.com/OpenLineage/OpenLineage/tree/1.18.0/integration/airflow\", \"_schemaURL\": \"https://openlineage.io/spec/2-0-2/OpenLineage.json#/$defs/BaseFacet\", \"unknownItems\": [{\"name\": \"DatahubEmitterOperator\", \"properties\": {\"depends_on_past\": false, \"downstream_task_ids\": \"[]\", \"execution_timeout\": \"<<non-serializable: timedelta>>\", \"executor_config\": {}, \"ignore_first_depends_on_past\": true, \"is_setup\": false, \"is_teardown\": false, \"mapped\": false, \"multiple_outputs\": false, \"operator_class\": \"datahub_airflow_plugin.operators.datahub.DatahubEmitterOperator\", \"owner\": \"airflow\", \"priority_weight\": 1, \"queue\": \"default\", \"retries\": 0, \"retry_exponential_backoff\": false, \"task_id\": \"datahub_emitter_operator_jinja_template_dag_task\", \"trigger_rule\": \"all_success\", \"upstream_task_ids\": \"[]\", \"wait_for_downstream\": false, \"wait_for_past_depends_before_skipping\": false, \"weight_rule\": \"<<non-serializable: _DownstreamPriorityWeightStrategy>>\"}, \"type\": \"operator\"}]}"
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},
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"externalUrl": "http://airflow.example.com/taskinstance/list/?flt1_dag_id_equals=datahub_emitter_operator_jinja_template_dag&_flt_3_task_id=datahub_emitter_operator_jinja_template_dag_task",
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"name": "datahub_emitter_operator_jinja_template_dag_task",
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"type": {
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"string": "COMMAND"
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}
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},
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"env": "PROD"
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}
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}
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},
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@ -441,7 +444,7 @@
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"aspectName": "dataProcessInstanceRunEvent",
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"aspect": {
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"json": {
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"timestampMillis": 1726570937811,
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"timestampMillis": 1726699853392,
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"partitionSpec": {
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"partition": "FULL_TABLE_SNAPSHOT",
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"type": "FULL_TABLE"
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@ -19,7 +19,8 @@
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},
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"externalUrl": "http://airflow.example.com/tree?dag_id=datahub_emitter_operator_jinja_template_dag",
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"name": "datahub_emitter_operator_jinja_template_dag",
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"description": "An example dag with jinja template"
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"description": "An example dag with jinja template",
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"env": "PROD"
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}
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}
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},
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@ -146,7 +147,8 @@
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"name": "datahub_emitter_operator_jinja_template_dag_task",
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"type": {
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"string": "COMMAND"
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}
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},
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"env": "PROD"
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}
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}
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},
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@ -242,7 +244,7 @@
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"name": "datahub_emitter_operator_jinja_template_dag_datahub_emitter_operator_jinja_template_dag_task_manual_run_test",
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"type": "BATCH_AD_HOC",
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"created": {
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"time": 1726570903946,
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"time": 1726621020280,
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"actor": "urn:li:corpuser:datahub"
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}
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}
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@ -267,7 +269,7 @@
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"aspectName": "dataProcessInstanceRunEvent",
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"aspect": {
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"json": {
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"timestampMillis": 1726570903946,
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"timestampMillis": 1726621020280,
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"partitionSpec": {
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"partition": "FULL_TABLE_SNAPSHOT",
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"type": "FULL_TABLE"
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@ -366,7 +368,8 @@
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"name": "datahub_emitter_operator_jinja_template_dag_task",
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"type": {
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"string": "COMMAND"
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}
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},
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"env": "PROD"
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}
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}
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},
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@ -441,7 +444,7 @@
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"aspectName": "dataProcessInstanceRunEvent",
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"aspect": {
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"json": {
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"timestampMillis": 1726570904070,
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"timestampMillis": 1726621020427,
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"partitionSpec": {
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"partition": "FULL_TABLE_SNAPSHOT",
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"type": "FULL_TABLE"
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@ -84,10 +84,11 @@ def assert_metadata_files_equal(
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diff = diff_metadata_json(output, golden, ignore_paths, ignore_order=ignore_order)
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if diff and update_golden:
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if isinstance(diff, MCPDiff):
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if isinstance(diff, MCPDiff) and diff.is_delta_valid:
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diff.apply_delta(golden)
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write_metadata_file(pathlib.Path(golden_path), golden)
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else:
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# Fallback: just overwrite the golden file
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shutil.copyfile(str(output_path), str(golden_path))
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return
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@ -149,6 +149,7 @@ class MCPDiff:
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aspect_changes: Dict[str, Dict[str, MCPAspectDiff]] # urn -> aspect -> diff
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urns_added: Set[str]
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urns_removed: Set[str]
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is_delta_valid: bool
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def __bool__(self) -> bool:
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return bool(self.aspect_changes)
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@ -162,25 +163,31 @@ class MCPDiff:
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) -> "MCPDiff":
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ignore_paths = [cls.convert_path(path) for path in ignore_paths]
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is_delta_valid = True
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aspect_changes: Dict[str, Dict[str, MCPAspectDiff]] = defaultdict(dict)
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for urn in golden.keys() | output.keys():
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golden_map = golden.get(urn, {})
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output_map = output.get(urn, {})
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for aspect_name in golden_map.keys() | output_map.keys():
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t1 = golden_map.get(aspect_name, [])
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t2 = output_map.get(aspect_name, [])
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diff = DeepDiff(
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t1=golden_map.get(aspect_name, []),
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t2=output_map.get(aspect_name, []),
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t1=t1,
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t2=t2,
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exclude_regex_paths=ignore_paths,
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ignore_order=True,
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custom_operators=[DeltaInfoOperator()],
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)
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if diff:
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aspect_changes[urn][aspect_name] = MCPAspectDiff.create(diff)
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if len(t1) > 1 or len(t2) > 1:
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is_delta_valid = False
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return cls(
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urns_added=output.keys() - golden.keys(),
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urns_removed=golden.keys() - output.keys(),
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aspect_changes=aspect_changes,
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is_delta_valid=is_delta_valid,
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)
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@staticmethod
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@ -193,9 +200,13 @@ class MCPDiff:
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)
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def apply_delta(self, golden: List[Dict[str, Any]]) -> None:
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"""Update a golden file to match an output file based on the diff.
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:param golden: Golden file represented as a list of MCPs, altered in-place.
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"""
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aspect_diffs = [v for d in self.aspect_changes.values() for v in d.values()]
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for aspect_diff in aspect_diffs:
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for (_, old, new), diffs in aspect_diff.aspects_changed.items():
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for (_, old, new) in aspect_diff.aspects_changed.keys():
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golden[old.delta_info.idx] = new.delta_info.original
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indices_to_remove = set()
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@ -268,7 +279,7 @@ class MCPDiff:
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suffix = "rd"
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else:
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suffix = "th"
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ordinal = f"{(idx+1)}{suffix} " if idx else ""
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ordinal = f"{(idx + 1)}{suffix} " if idx else ""
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return f"{ordinal}<{ga.aspect_name}> {msg}"
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@staticmethod
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