SIENTIAPDE-1646
Update dependencies and refactor MLFlow activities - Replaced direct GitHub dependencies in `requirements.txt` with specific versioned packages for `sientia_do` and `sientia_model`. - Refactored imports in `activities.py` to streamline the code structure. - Enhanced the `MLFlow` class in `mlflow.py` by introducing a method to resolve model aliases, improving flexibility in model lookups. - Simplified shutdown logic in `worker.py` for better readability. - Added new tests for MLFlow activities and improved existing test coverage for data handling and model retraining processes.
This commit is contained in:
@@ -229,3 +229,74 @@ async def test_shutdown(
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mock_gates_init.close.assert_called_once()
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mock_model_metrics_init.close.assert_called_once()
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mock_api_init.close.assert_called_once()
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@patch('laborious.activities.activities.SientiaMLflowRepository')
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@patch('laborious.activities.activities.build_mlflow_config')
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@patch('laborious.activities.activities.Storage.__init__')
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@patch('laborious.activities.activities.MLFlow.__init__')
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@patch('laborious.activities.activities.OPC.__init__')
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@patch('laborious.activities.activities.Gates.__init__')
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@patch('laborious.activities.activities.ModelMetrics.__init__')
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@patch('laborious.activities.activities.API.__init__')
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@patch('laborious.activities.activities.MinioRepository')
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@patch('laborious.activities.activities.MetricsController')
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def test___init___builds_mlflow_repository_when_not_provided(
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mock_metrics_controller,
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mock_minio_repository,
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_mock_api_init,
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_mock_model_metrics_init,
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_mock_gates_init,
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_mock_opc_init,
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_mock_mlflow_init,
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_mock_storage_init,
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mock_build_mlflow_config,
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mock_mlflow_repository_cls,
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):
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postgres_config = {
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'host': 'localhost',
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'port': 5432,
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'user': 'postgres',
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'password': 'postgres',
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'dbname': 'postgres',
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'min_connections': 1,
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'max_connections': 10,
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}
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minio_config = {
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'endpoint_url': 'localhost:9000',
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'access_key': 'minio',
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'secret_key': 'minio123',
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'default_bucket': 'test',
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'retention_hours': 24,
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'secure': False,
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}
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opc_config = {'bootstrap_servers': 'localhost:9092', 'polling_time': 1000, 'group_id': 'test'}
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pi_web_api_config = {'base_url': 'https://pi', 'auth_type': 'bearer', 'auth_token': 'token'}
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logger = MagicMock()
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notification_handler = MagicMock()
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plugin_store = MagicMock()
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mock_build_mlflow_config.return_value = {
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'url': 'http://mlflow:80',
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'username': 'u',
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'password': 'p',
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}
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Activities(
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postgres_config=postgres_config,
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plugin_store=plugin_store,
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minio_config=minio_config,
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opc_config=opc_config,
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pi_web_api_config=pi_web_api_config,
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logger=logger,
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notification_handler=notification_handler,
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)
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mock_build_mlflow_config.assert_called_once()
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mock_mlflow_repository_cls.assert_called_once_with(
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host='http://mlflow:80',
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username='u',
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password='p',
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logger=logger,
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notification_handler=notification_handler,
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metrics_controller=mock_metrics_controller.return_value,
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)
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@@ -328,6 +328,27 @@ async def test_write_pi_web_api_data_empty_tags(mock_dataframe, api, base_input_
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}
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@mark.asyncio
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@patch('laborious.activities.api.DataFrame')
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async def test_write_pi_web_api_data_updates_confidence_and_comments(
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mock_dataframe, api, base_input_data
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):
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mock_dataframe.return_value = _create_mock_dataframe()
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api.pi_web_api_client.write_value.side_effect = [
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[{'WebId': 'web_id_1', 'Errors': []}],
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[{'WebId': 'web_id_2', 'Errors': []}],
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]
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with patch.object(
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api,
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'process_pi_web_api_response',
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new=AsyncMock(side_effect=[(0.33, 'PI warning'), (0, '')]),
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) as process_mock:
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result = await api.write_pi_web_api_data(base_input_data)
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assert process_mock.await_count == 2
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assert result is not None
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@mark.asyncio
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async def test_close(api):
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api.close()
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@@ -1,3 +1,4 @@
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from datetime import datetime
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from unittest.mock import ANY, AsyncMock, MagicMock, patch
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import numpy as np
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@@ -108,6 +109,47 @@ metadata = {
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}
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def test_detect_and_parse_datetime_index_empty(mlflow):
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df = pd.DataFrame()
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out = mlflow._detect_and_parse_datetime_index(df, metadata['metadata'])
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assert out.empty
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def test_detect_and_parse_datetime_index_mixed_types_error(mlflow):
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idx = pd.Index([pd.Timestamp('2020-01-01', tz='UTC'), 'x'])
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df = pd.DataFrame({'a': [1, 2]}, index=idx)
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with raises(ValueError):
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mlflow._detect_and_parse_datetime_index(df, metadata['metadata'])
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def test_detect_and_parse_datetime_index_invalid_string_error(mlflow):
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idx = pd.Index(['bad-format'])
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df = pd.DataFrame({'a': [1]}, index=idx)
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with raises(ValueError):
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mlflow._detect_and_parse_datetime_index(df, metadata['metadata'])
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def test_detect_and_parse_datetime_index_unsupported_type_error(mlflow):
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idx = pd.Index([pd.Period('2020-01', freq='M')])
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df = pd.DataFrame({'a': [1]}, index=idx)
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with raises(ValueError):
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mlflow._detect_and_parse_datetime_index(df, metadata['metadata'])
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def test_detect_and_parse_datetime_index_datetime_success(mlflow):
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idx = pd.Index([datetime(2020, 1, 1, 0, 0, 0)])
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df = pd.DataFrame({'a': [1]}, index=idx)
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out = mlflow._detect_and_parse_datetime_index(df, metadata['metadata'])
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assert out.index[0].endswith('+0000')
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def test_detect_and_parse_datetime_index_timestamp_with_tz_success(mlflow):
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idx = pd.DatetimeIndex([pd.Timestamp('2020-01-01 00:00:00', tz='UTC')])
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df = pd.DataFrame({'a': [1]}, index=idx)
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out = mlflow._detect_and_parse_datetime_index(df, metadata['metadata'])
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assert out.index[0].endswith('+0000')
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@mark.asyncio
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@patch(
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'laborious.activities.mlflow.MinioDataFramePayload.from_dataframe',
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@@ -160,6 +202,41 @@ async def test_request_transform_success(mock_from_dataframe, mlflow):
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assert response_data == mock_from_dataframe.return_value
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@mark.asyncio
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@patch(
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'laborious.activities.mlflow.MinioDataFramePayload.from_dataframe',
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new_callable=AsyncMock,
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)
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async def test_request_transform_success_without_transform_meta(mock_from_dataframe, mlflow):
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ts = pd.Timestamp('2020-01-01', tz='UTC')
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raw = pd.DataFrame(
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{
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'variable': ['v1'],
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'timestamp': [ts],
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'value': [1.0],
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'created_at': [ts],
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}
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)
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out_idx = pd.Index([ts.strftime(DATETIME_FORMAT_WITH_TZ)], name=None)
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out_df = pd.DataFrame({'v1': [1.0]}, index=out_idx)
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wrapper = MagicMock()
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wrapper.transform.return_value = (out_df, {})
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mlflow.mlflow_repository.get_cached_model.return_value = wrapper
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payload = AsyncMock()
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payload.retrieve = AsyncMock(return_value=raw)
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input_data = {
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**metadata,
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'data': payload,
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'model_name': 'test_model',
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'model_config': {},
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}
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await mlflow.request_transform(input_data)
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mock_from_dataframe.assert_called_once()
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@mark.asyncio
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@patch(
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'laborious.activities.mlflow.MinioDataFramePayload.from_dataframe',
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@@ -233,6 +310,39 @@ async def test_request_predict(mock_to_datetime, mock_from_dataframe, mlflow):
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assert response_data == mock_from_dataframe.return_value
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@mark.asyncio
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@patch(
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'laborious.activities.mlflow.MinioDataFramePayload.from_dataframe',
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new_callable=AsyncMock,
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)
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@patch('laborious.activities.mlflow.to_datetime')
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async def test_request_predict_success_dataframe_and_meta(
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mock_to_datetime, mock_from_dataframe, mlflow
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):
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wrapper = MagicMock()
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pred_df = pd.DataFrame({'raw': [0.3]})
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wrapper.predict.return_value = (pred_df, {'m': 1})
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mlflow.mlflow_repository.get_cached_model.return_value = wrapper
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data_mock = MagicMock()
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data_mock.index = pd.DatetimeIndex([pd.Timestamp('2020-01-01', tz='UTC')])
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payload = AsyncMock()
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payload.retrieve = AsyncMock(return_value=data_mock)
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input_data = {
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**metadata,
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'data': payload,
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'model_name': 'test_model',
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'model_config': {},
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}
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await mlflow.request_predict(input_data)
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assert list(pred_df.columns) == ['prediction', 'response_time']
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mlflow.info.assert_any_call("Wrapper predict metadata: {'m': 1}", metadata['metadata'])
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mock_from_dataframe.assert_called_once()
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@mark.asyncio
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@patch(
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'laborious.activities.mlflow.MinioDataFramePayload.from_dataframe',
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@@ -275,7 +385,7 @@ async def test_request_predict_failure(mock_to_datetime, mock_from_dataframe, ml
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async def test_retrain_model_success_data_success_retrain(
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mock_to_datetime, mock_rmtree, mock_mkdtemp, mock_log_artifact, mlflow
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):
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mock_mkdtemp.return_value = '/tmp/x'
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mock_mkdtemp.return_value = 'tmp'
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mv_alias = MagicMock()
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mv_alias.run_id = 'source-run'
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@@ -326,7 +436,7 @@ async def test_retrain_model_success_data_success_retrain(
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async def test_retrain_model_success_with_payload_data(
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mock_to_datetime, mock_rmtree, mock_mkdtemp, mock_log_artifact, mlflow
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):
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mock_mkdtemp.return_value = '/tmp/x'
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mock_mkdtemp.return_value = 'tmp'
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mv_alias = MagicMock(run_id='src')
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mlflow.mlflow_repository._client.get_model_version_by_alias.return_value = mv_alias
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wrapper = MagicMock()
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@@ -362,6 +472,48 @@ async def test_retrain_model_success_with_payload_data(
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assert response['success'] is True
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@mark.asyncio
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@patch('laborious.activities.mlflow.mlflow.log_artifact')
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@patch('laborious.activities.mlflow.tempfile.mkdtemp')
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@patch('laborious.activities.mlflow.rmtree')
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@patch('laborious.activities.mlflow.to_datetime')
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async def test_retrain_model_success_full_retrain_branch(
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mock_to_datetime, mock_rmtree, mock_mkdtemp, mock_log_artifact, mlflow
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):
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mock_mkdtemp.return_value = 'tmp'
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mv_alias = MagicMock(run_id='src')
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mlflow.mlflow_repository._client.get_model_version_by_alias.return_value = mv_alias
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wrapper = MagicMock()
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mlflow.mlflow_repository.get_cached_model.return_value = wrapper
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mock_cm = MagicMock()
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mock_cm.__enter__.return_value = MagicMock(run_id='r', experiment_id='e')
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mock_cm.__exit__.return_value = False
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mlflow.mlflow_repository.start_run.return_value = mock_cm
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ts = pd.Timestamp('2020-01-01', tz='UTC')
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raw_data = pd.DataFrame(
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{
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'variable': ['target', 'f1', 'target', 'f1'],
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'timestamp': [ts, ts, ts + pd.Timedelta(days=1), ts + pd.Timedelta(days=1)],
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'value': [1.0, 2.0, 3.0, 4.0],
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}
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)
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payload = AsyncMock()
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payload.retrieve = AsyncMock(return_value=raw_data)
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response = await mlflow.retrain_model(
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{
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**metadata,
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'data': payload,
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'model_name': 'test_model',
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'model_config': {'target': 'target', 'full_retrain': True, 'validation_fraction': 0.5},
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}
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)
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wrapper.train.assert_called_once()
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assert response['success'] is True
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|
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|
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@mark.asyncio
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@patch('laborious.activities.mlflow.to_datetime')
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async def test_retrain_model_success_data_fail_retrain(mock_to_datetime, mlflow):
|
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@@ -393,7 +545,6 @@ async def test_retrain_model_success_data_fail_retrain(mock_to_datetime, mlflow)
|
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)
|
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|
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assert response['success'] is False
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mlflow.send_notification_async.assert_called_once()
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assert 'retrain failed' in response['message']
|
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|
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|
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@@ -415,19 +566,17 @@ async def test_retrain_model_data_error(mlflow):
|
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|
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@mark.asyncio
|
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async def test_retrain_model_missing_target(mlflow):
|
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raw_data = MagicMock(columns=['variable', 'timestamp', 'value'])
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raw_data.__getitem__.return_value.max.return_value = 'ts'
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ts = pd.Timestamp('2020-01-01', tz='UTC')
|
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raw_data = pd.DataFrame(
|
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{
|
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'variable': ['f1', 'f2'],
|
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'timestamp': [ts, ts],
|
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'value': [1.0, 2.0],
|
||||
}
|
||||
)
|
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payload = AsyncMock()
|
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payload.retrieve = AsyncMock(return_value=raw_data)
|
||||
|
||||
pivoted = MagicMock()
|
||||
raw_data.drop_duplicates.return_value = raw_data
|
||||
raw_data.pivot.return_value = pivoted
|
||||
pivoted.fillna = MagicMock()
|
||||
pivoted.columns.name = None
|
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pivoted.index = MagicMock()
|
||||
pivoted.__setitem__ = MagicMock()
|
||||
|
||||
response = await mlflow.retrain_model(
|
||||
{
|
||||
**metadata,
|
||||
@@ -561,6 +710,24 @@ async def test_get_reference_data_not_found(mlflow):
|
||||
assert result is None
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
async def test_get_reference_data_missing_csv_file_returns_none(mlflow):
|
||||
input_data = {
|
||||
**metadata,
|
||||
'model_name': 'test_model',
|
||||
}
|
||||
mv = MagicMock(run_id='run1')
|
||||
mlflow.mlflow_repository._client.get_model_version_by_alias.return_value = mv
|
||||
|
||||
with patch('laborious.activities.mlflow.tempfile.mkdtemp', return_value='tmp'):
|
||||
with patch('laborious.activities.mlflow.rmtree'):
|
||||
with patch('laborious.activities.mlflow.Path') as mp:
|
||||
mp.return_value.rglob.return_value = []
|
||||
result = await mlflow.get_reference_data(input_data)
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
async def test_get_reference_data_exception(mlflow):
|
||||
input_data = {
|
||||
|
||||
@@ -190,6 +190,21 @@ async def test_from_dataframe_inline():
|
||||
assert result.last_timestamp == '2024-01-01'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('laborious.utils.models.minio_dataframe_payload.OFFLOAD_THRESHOLD_BYTES', 10**9)
|
||||
async def test_from_dataframe_inline_uses_provided_last_timestamp():
|
||||
minio = AsyncMock()
|
||||
df = _mock_dataframe({'timestamp': ['2024-01-01'], 'value': [42]})
|
||||
result = await MinioDataFramePayload.from_dataframe(
|
||||
dataframe=df,
|
||||
minio_repo=minio,
|
||||
model_name='m',
|
||||
operation='initial',
|
||||
last_timestamp='2024-01-02',
|
||||
)
|
||||
assert result.last_timestamp == '2024-01-02'
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@patch('laborious.utils.models.minio_dataframe_payload.now')
|
||||
@patch('laborious.utils.models.minio_dataframe_payload.OFFLOAD_THRESHOLD_BYTES', 0)
|
||||
@@ -264,3 +279,9 @@ def test_from_dict_passthrough_existing_instance():
|
||||
original = MinioDataFramePayload(last_timestamp='2024-01-01', data={'a': 1}, bucket='b')
|
||||
result = MinioDataFramePayload.from_dict(original)
|
||||
assert result is original
|
||||
|
||||
|
||||
def test_debug_with_logger_calls_custom_debug():
|
||||
logger = MagicMock()
|
||||
MinioDataFramePayload._debug(logger, 'msg', {'a': 1})
|
||||
logger.custom_debug.assert_called_once_with('msg', {'a': 1})
|
||||
|
||||
12
tests/laborious/utils/test_dataframe_debug.py
Normal file
12
tests/laborious/utils/test_dataframe_debug.py
Normal file
@@ -0,0 +1,12 @@
|
||||
from pandas import DataFrame
|
||||
|
||||
from laborious.utils.dataframe_debug import build_dataframe_debug_message
|
||||
|
||||
|
||||
def test_build_dataframe_debug_message_skips_large_dataframe():
|
||||
df = DataFrame({'a': [1, 2, 3]})
|
||||
|
||||
msg = build_dataframe_debug_message('payload', df, max_rows=1)
|
||||
|
||||
assert 'skipped because dataframe has 3 rows' in msg
|
||||
assert '(max: 1)' in msg
|
||||
243
tests/laborious/worker/test_worker.py
Normal file
243
tests/laborious/worker/test_worker.py
Normal file
@@ -0,0 +1,243 @@
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
from pytest import mark, raises
|
||||
|
||||
from laborious.worker import worker
|
||||
|
||||
|
||||
def _build_fake_activities():
|
||||
inst = MagicMock()
|
||||
inst.init_opc = AsyncMock()
|
||||
inst.shutdown = AsyncMock()
|
||||
inst.load_query_with_minio_offload = MagicMock()
|
||||
inst.retrain_model = MagicMock()
|
||||
inst.update_production_model = MagicMock()
|
||||
inst.format_retrain_report = MagicMock()
|
||||
inst.export_data_to_postgres = MagicMock()
|
||||
inst.load_custom_query = MagicMock()
|
||||
inst.calculate_simple_metrics = MagicMock()
|
||||
inst.get_reference_data = MagicMock()
|
||||
inst.calculate_drift = MagicMock()
|
||||
inst.request_predict = MagicMock()
|
||||
inst.request_transform = MagicMock()
|
||||
inst.input_gate = MagicMock()
|
||||
inst.mlflow_response_gate = MagicMock()
|
||||
inst.mlflow_content_gate = MagicMock()
|
||||
inst.format_transformed_data = MagicMock()
|
||||
inst.format_prediction = MagicMock()
|
||||
inst.format_default_prediction = MagicMock()
|
||||
inst.write_opc_data = MagicMock()
|
||||
inst.cleanup_minio_objects_expired = MagicMock()
|
||||
inst.repeat_last_prediction = MagicMock()
|
||||
inst.write_metrics = MagicMock()
|
||||
inst.write_pi_web_api_data = MagicMock()
|
||||
return inst
|
||||
|
||||
|
||||
def _build_fake_worker(async_result=None, async_error: Exception | None = None):
|
||||
w = MagicMock()
|
||||
|
||||
async def _run():
|
||||
if async_error is not None:
|
||||
raise async_error
|
||||
return async_result
|
||||
|
||||
w.run = MagicMock(side_effect=_run)
|
||||
return w
|
||||
|
||||
|
||||
@patch('laborious.worker.worker.start_http_server')
|
||||
def test_start_prometheus_server_success(mock_start_http):
|
||||
with patch.object(worker.metrics.APP_UP, 'labels') as labels:
|
||||
gauge = MagicMock()
|
||||
labels.return_value = gauge
|
||||
with patch('laborious.worker.worker.os.getenv', return_value='9090'):
|
||||
worker.start_prometheus_server()
|
||||
mock_start_http.assert_called_once_with(9090)
|
||||
gauge.set.assert_called_once_with(1)
|
||||
|
||||
|
||||
@patch('laborious.worker.worker.start_http_server', side_effect=RuntimeError('nope'))
|
||||
def test_start_prometheus_server_error_exits(_mock_start_http):
|
||||
with patch('laborious.worker.worker.os._exit', side_effect=SystemExit(1)) as m_exit:
|
||||
with raises(SystemExit):
|
||||
worker.start_prometheus_server()
|
||||
m_exit.assert_called_once_with(1)
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
async def test_main_missing_runtime_exits_fast(monkeypatch):
|
||||
monkeypatch.setenv('RUNTIME', '')
|
||||
with (
|
||||
patch('laborious.worker.worker.start_prometheus_server'),
|
||||
patch('laborious.worker.worker.get_logger') as m_logger,
|
||||
patch('laborious.worker.worker.NotificationHandler'),
|
||||
patch('laborious.worker.worker.MetricsController'),
|
||||
patch.object(worker.metrics.APP_UP, 'labels') as labels,
|
||||
patch('laborious.worker.worker.sys.exit', side_effect=SystemExit(1)),
|
||||
):
|
||||
labels.return_value = MagicMock()
|
||||
with raises(SystemExit):
|
||||
await worker.main()
|
||||
assert m_logger.return_value.custom_critical.called
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
async def test_main_plugin_install_failure(monkeypatch):
|
||||
monkeypatch.setenv('RUNTIME', 'single')
|
||||
fake_activities = _build_fake_activities()
|
||||
fake_plugin = MagicMock()
|
||||
fake_plugin.install_runtime = AsyncMock(side_effect=RuntimeError('install failed'))
|
||||
with (
|
||||
patch('laborious.worker.worker.start_prometheus_server'),
|
||||
patch('laborious.worker.worker.get_logger'),
|
||||
patch(
|
||||
'laborious.worker.worker.build_mongodb_config',
|
||||
return_value={'connection_string': 'cs', 'database_name': 'db'},
|
||||
),
|
||||
patch('laborious.worker.worker.NotificationHandler'),
|
||||
patch('laborious.worker.worker.MetricsController'),
|
||||
patch(
|
||||
'laborious.worker.worker.build_plugin_store_config',
|
||||
return_value={
|
||||
'base_url': '',
|
||||
'owner': '',
|
||||
'repo': '',
|
||||
'username': None,
|
||||
'password': None,
|
||||
'branch': None,
|
||||
'cache_ttl_seconds': None,
|
||||
'pypi_index_url': '',
|
||||
'pypi_username': None,
|
||||
'pypi_password': None,
|
||||
},
|
||||
),
|
||||
patch('laborious.worker.worker.PluginStore', return_value=fake_plugin),
|
||||
patch('laborious.worker.worker.Activities', return_value=fake_activities),
|
||||
patch.object(worker.metrics.APP_UP, 'labels') as labels,
|
||||
patch('laborious.worker.worker.sys.exit', side_effect=SystemExit(1)),
|
||||
):
|
||||
labels.return_value = MagicMock()
|
||||
with raises(SystemExit):
|
||||
await worker.main()
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
async def test_main_success_exit_zero(monkeypatch):
|
||||
monkeypatch.setenv('RUNTIME', 'single')
|
||||
fake_activities = _build_fake_activities()
|
||||
fake_plugin = MagicMock()
|
||||
fake_plugin.install_runtime = AsyncMock(return_value=None)
|
||||
fake_workers = [_build_fake_worker() for _ in range(4)]
|
||||
|
||||
with (
|
||||
patch('laborious.worker.worker.start_prometheus_server'),
|
||||
patch('laborious.worker.worker.get_logger'),
|
||||
patch(
|
||||
'laborious.worker.worker.build_mongodb_config',
|
||||
return_value={'connection_string': 'cs', 'database_name': 'db'},
|
||||
),
|
||||
patch('laborious.worker.worker.NotificationHandler') as m_notif_cls,
|
||||
patch('laborious.worker.worker.MetricsController'),
|
||||
patch(
|
||||
'laborious.worker.worker.build_plugin_store_config',
|
||||
return_value={
|
||||
'base_url': '',
|
||||
'owner': '',
|
||||
'repo': '',
|
||||
'username': None,
|
||||
'password': None,
|
||||
'branch': None,
|
||||
'cache_ttl_seconds': None,
|
||||
'pypi_index_url': '',
|
||||
'pypi_username': None,
|
||||
'pypi_password': None,
|
||||
},
|
||||
),
|
||||
patch('laborious.worker.worker.PluginStore', return_value=fake_plugin),
|
||||
patch('laborious.worker.worker.Activities', return_value=fake_activities),
|
||||
patch('laborious.worker.worker.build_postgres_config', return_value={}),
|
||||
patch('laborious.worker.worker.build_minio_config', return_value={}),
|
||||
patch('laborious.worker.worker.build_opc_config', return_value={}),
|
||||
patch('laborious.worker.worker.build_api_config', return_value={}),
|
||||
patch('laborious.worker.worker.PrometheusConfig', return_value=MagicMock()),
|
||||
patch('laborious.worker.worker.TelemetryConfig', return_value=MagicMock()),
|
||||
patch('laborious.worker.worker.Runtime', return_value=MagicMock()),
|
||||
patch(
|
||||
'laborious.worker.worker.client.Client.connect', new=AsyncMock(return_value=MagicMock())
|
||||
),
|
||||
patch('laborious.worker.worker.prepare_worker', side_effect=fake_workers) as m_prepare,
|
||||
patch.object(worker.metrics.APP_UP, 'labels') as labels,
|
||||
patch('laborious.worker.worker.sys.exit', side_effect=SystemExit(0)),
|
||||
):
|
||||
labels.return_value = MagicMock()
|
||||
with raises(SystemExit):
|
||||
await worker.main()
|
||||
|
||||
notif = m_notif_cls.return_value
|
||||
notif.shutdown.assert_called_once()
|
||||
fake_activities.shutdown.assert_awaited_once()
|
||||
assert m_prepare.call_count == 4
|
||||
prepare_calls = m_prepare.call_args_list
|
||||
assert prepare_calls[0].kwargs['runtime'] == 'single'
|
||||
assert prepare_calls[3].kwargs['runtime'] == 'single'
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
async def test_main_worker_gather_error_exits_one(monkeypatch):
|
||||
monkeypatch.setenv('RUNTIME', 'single')
|
||||
fake_activities = _build_fake_activities()
|
||||
fake_plugin = MagicMock()
|
||||
fake_plugin.install_runtime = AsyncMock(return_value=None)
|
||||
fake_workers = [
|
||||
_build_fake_worker(async_error=RuntimeError('boom')),
|
||||
_build_fake_worker(),
|
||||
_build_fake_worker(),
|
||||
_build_fake_worker(),
|
||||
]
|
||||
|
||||
with (
|
||||
patch('laborious.worker.worker.start_prometheus_server'),
|
||||
patch('laborious.worker.worker.get_logger') as m_logger,
|
||||
patch(
|
||||
'laborious.worker.worker.build_mongodb_config',
|
||||
return_value={'connection_string': 'cs', 'database_name': 'db'},
|
||||
),
|
||||
patch('laborious.worker.worker.NotificationHandler'),
|
||||
patch('laborious.worker.worker.MetricsController'),
|
||||
patch(
|
||||
'laborious.worker.worker.build_plugin_store_config',
|
||||
return_value={
|
||||
'base_url': '',
|
||||
'owner': '',
|
||||
'repo': '',
|
||||
'username': None,
|
||||
'password': None,
|
||||
'branch': None,
|
||||
'cache_ttl_seconds': None,
|
||||
'pypi_index_url': '',
|
||||
'pypi_username': None,
|
||||
'pypi_password': None,
|
||||
},
|
||||
),
|
||||
patch('laborious.worker.worker.PluginStore', return_value=fake_plugin),
|
||||
patch('laborious.worker.worker.Activities', return_value=fake_activities),
|
||||
patch('laborious.worker.worker.build_postgres_config', return_value={}),
|
||||
patch('laborious.worker.worker.build_minio_config', return_value={}),
|
||||
patch('laborious.worker.worker.build_opc_config', return_value={}),
|
||||
patch('laborious.worker.worker.build_api_config', return_value={}),
|
||||
patch('laborious.worker.worker.PrometheusConfig', return_value=MagicMock()),
|
||||
patch('laborious.worker.worker.TelemetryConfig', return_value=MagicMock()),
|
||||
patch('laborious.worker.worker.Runtime', return_value=MagicMock()),
|
||||
patch(
|
||||
'laborious.worker.worker.client.Client.connect', new=AsyncMock(return_value=MagicMock())
|
||||
),
|
||||
patch('laborious.worker.worker.prepare_worker', side_effect=fake_workers),
|
||||
patch.object(worker.metrics.APP_UP, 'labels') as labels,
|
||||
patch('laborious.worker.worker.sys.exit', side_effect=SystemExit(1)),
|
||||
):
|
||||
labels.return_value = MagicMock()
|
||||
with raises(SystemExit):
|
||||
await worker.main()
|
||||
|
||||
assert m_logger.return_value.custom_error.called
|
||||
@@ -1,6 +1,6 @@
|
||||
from unittest.mock import ANY, AsyncMock, MagicMock, call, patch
|
||||
|
||||
from pytest import fixture, mark
|
||||
from pytest import fixture, mark, raises
|
||||
|
||||
from laborious.activities.activities import Activities
|
||||
from laborious.workflows.sub_workflows.prediction_process import PredictionProcess
|
||||
@@ -840,3 +840,27 @@ async def test_run_with_cleanup_prefixes(workflow_mock, prediction_process):
|
||||
retry_policy=ANY,
|
||||
start_to_close_timeout=ANY,
|
||||
)
|
||||
|
||||
|
||||
@mark.asyncio
|
||||
@patch('laborious.workflows.sub_workflows.prediction_process.workflow', new_callable=AsyncMock)
|
||||
async def test_run_always_cleans_up_on_pipeline_exception(workflow_mock, prediction_process):
|
||||
input_data = {
|
||||
'metadata': metadata,
|
||||
'data': {'last_timestamp': '2024-01-01'},
|
||||
'model_id': 1,
|
||||
'model_name': 'm',
|
||||
'model_config': {},
|
||||
'save_transform': False,
|
||||
}
|
||||
prediction_process._run_prediction_pipeline = AsyncMock(side_effect=RuntimeError('boom'))
|
||||
|
||||
with raises(RuntimeError):
|
||||
await prediction_process.run(input_data)
|
||||
|
||||
workflow_mock.execute_activity_method.assert_called_once_with(
|
||||
Activities.cleanup_minio_objects_expired,
|
||||
{**metadata, 'data': input_data['data']},
|
||||
retry_policy=ANY,
|
||||
start_to_close_timeout=ANY,
|
||||
)
|
||||
|
||||
Reference in New Issue
Block a user