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SIENTIAPDE-1712

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SIENTIAPDE-1712 Enhance logging across various classes by adding logger parameters and improving debug statements. This update includes adjustments in Gates, MLFlow, ModelMetrics, and MLFlowRepository classes for better traceability and observability during operations.
This commit is contained in:
vitor-aignosi
2026-04-01 13:53:23 -03:00
parent b9fe4604f7
commit 381856f5ca
9 changed files with 74 additions and 31 deletions
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2
laborious/activities/gates.py
View File

@@ -522,7 +522,7 @@ class Gates(MinioManager):
operation='transform',
workflow_metadata=metadata,
last_timestamp=payload.last_timestamp,
logger=self.logger
logger=self.logger,
)
@activity.defn(name='format_prediction')

3
laborious/activities/mlflow.py
View File

@@ -19,8 +19,8 @@ with workflow.unsafe.imports_passed_through():
)
from sientia_do.utils.formatters import create_sample_dict
from laborious.utils.models.minio_dataframe_payload import MinioDataFramePayload
from laborious.utils.dataframe_debug import build_dataframe_debug_message
from laborious.utils.models.minio_dataframe_payload import MinioDataFramePayload
from laborious.utils.repository.minio_manager import MinioManager
from laborious.utils.repository.model_repository import MLFlowRepository
@@ -43,6 +43,7 @@ class MLFlow(MinioManager):
mlflow_password (str): MLFlow authentication password
model_monitoring_repository (MLFlowRepository): Repository for MLFlow operations
"""
_MAX_DEBUG_DATAFRAME_ROWS = 100
def __init__(

8
laborious/activities/model_metrics.py
View File

@@ -27,13 +27,13 @@ warnings.filterwarnings(
class ModelMetrics(SientiaMonitoring):
"""
_MAX_DEBUG_DATAFRAME_ROWS = 100
Metrics activities for the Laborious system.
This class provides activities for writing metrics to the Prometheus monitoring system.
"""
_MAX_DEBUG_DATAFRAME_ROWS = 100
def __init__(
self,
logger: Logger,
@@ -99,7 +99,9 @@ class ModelMetrics(SientiaMonitoring):
model_analysis = ModelAnalysis(config=config)
self._debug_dataframe(f'Reference data: Size {reference_data.shape}', reference_data, metadata)
self._debug_dataframe(
f'Reference data: Size {reference_data.shape}', reference_data, metadata
)
self._debug_dataframe(f'Target data: Size {target_data.shape}', target_data, metadata)

8
laborious/utils/repository/model_repository.py
View File

@@ -474,7 +474,9 @@ class MLFlowRepository(SientiaMonitoring):
raw_model = mlflow.pyfunc.load_model(artifact_path)
model = raw_model._model_impl.python_model
self.debug(f"Model wrapper loaded: {model.__class__.__name__}:{model.__dict__}", metadata)
self.debug(
f'Model wrapper loaded: {model.__class__.__name__}:{model.__dict__}', metadata
)
else:
if model_type == 'predict':
model = await self.load_predict_model(model_name, metadata, flavor)
@@ -1293,7 +1295,9 @@ class MLFlowRepository(SientiaMonitoring):
end_time = datetime.now()
if isinstance(predict_data, pd.DataFrame):
self._debug_dataframe('Data received from model prediction:', predict_data, metadata)
self._debug_dataframe(
'Data received from model prediction:', predict_data, metadata
)
# predict_data.to_csv(
# f"tmp/predicted_data_{model_name}.csv", index=True)

4
tests/laborious/activities/test_gates.py
View File

@@ -541,6 +541,7 @@ async def test_format_prediction_no_timestamp(gates_activity):
'model_id': 'test_model',
'prediction_confidence': 0.9,
'prediction_store_policy': 'lts:1',
'timestamp': '2023-05-26 11:12:27',
}
# Act
@@ -580,6 +581,7 @@ async def test_format_prediction_with_timestamp_erl(gates_activity):
'model_id': 'test_model',
'prediction_confidence': 0.9,
'prediction_store_policy': 'erl:2',
'timestamp': '2023-05-26 11:12:27',
}
# Act
@@ -619,6 +621,7 @@ async def test_format_prediction_with_timestamp_lts(gates_activity):
'model_id': 'test_model',
'prediction_confidence': 0.9,
'prediction_store_policy': 'lts:2',
'timestamp': '2023-05-26 11:12:27',
}
# Act
@@ -655,6 +658,7 @@ async def test_format_prediction_with_timestamp_invalid_policy(gates_activity):
'model_id': 'test_model',
'prediction_confidence': 0.9,
'prediction_store_policy': 'lts:2',
'timestamp': '2023-05-26 11:12:27',
}
gates_activity.get_prediction_store_policy = MagicMock(return_value=('invalid', 1))

2
tests/laborious/activities/test_mlflow.py
View File

@@ -181,6 +181,7 @@ async def test_request_transform_failure(mock_from_dataframe, mlflow):
status=transform_response,
workflow_metadata=metadata['metadata'],
last_timestamp=payload.last_timestamp,
logger=mlflow.logger,
)
assert response_data == mock_from_dataframe.return_value
@@ -252,6 +253,7 @@ async def test_request_predict_failure(mock_to_datetime, mock_from_dataframe, ml
status=predict_response,
workflow_metadata=metadata['metadata'],
last_timestamp=payload.last_timestamp,
logger=mlflow.logger,
)
assert response_data == mock_from_dataframe.return_value

24
tests/laborious/workflows/subworkflows/test_format_and_export_prediction.py
View File

@@ -93,6 +93,7 @@ async def test_run_none_path_flag(workflow_mock, format_and_export_prediction):
call(
Activities.export_data_to_postgres,
{
**metadata,
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'data': prediction_data,
@@ -100,7 +101,8 @@ async def test_run_none_path_flag(workflow_mock, format_and_export_prediction):
'column': 'timestamp',
'format': DATETIME_FORMAT_WITH_TZ,
},
**metadata,
'on_conflict': 'error',
'unique_columns': ['model_id', 'timestamp'],
},
retry_policy=ANY,
start_to_close_timeout=ANY,
@@ -243,6 +245,7 @@ async def test_run_none_path_flag_with_transformed_data(
call(
Activities.export_data_to_postgres,
{
**metadata,
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'data': prediction_data,
@@ -250,7 +253,8 @@ async def test_run_none_path_flag_with_transformed_data(
'column': 'timestamp',
'format': DATETIME_FORMAT_WITH_TZ,
},
**metadata,
'on_conflict': 'error',
'unique_columns': ['model_id', 'timestamp'],
},
retry_policy=ANY,
start_to_close_timeout=ANY,
@@ -349,14 +353,16 @@ async def test_run_default_path_flag(workflow_mock, format_and_export_prediction
call(
Activities.export_data_to_postgres,
{
**metadata,
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'data': prediction_data,
**metadata,
'timestamp_conversion': {
'column': 'timestamp',
'format': DATETIME_FORMAT_WITH_TZ,
},
'on_conflict': 'error',
'unique_columns': ['model_id', 'timestamp'],
},
retry_policy=ANY,
start_to_close_timeout=ANY,
@@ -456,6 +462,7 @@ async def test_run_none_path_flag_with_pi_web_api(workflow_mock, format_and_expo
call(
Activities.export_data_to_postgres,
{
**metadata,
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'data': pi_web_api_data,
@@ -463,7 +470,8 @@ async def test_run_none_path_flag_with_pi_web_api(workflow_mock, format_and_expo
'column': 'timestamp',
'format': DATETIME_FORMAT_WITH_TZ,
},
**metadata,
'on_conflict': 'error',
'unique_columns': ['model_id', 'timestamp'],
},
retry_policy=ANY,
start_to_close_timeout=ANY,
@@ -560,6 +568,7 @@ async def test_run_none_path_flag_with_pi_web_api_and_opc(
call(
Activities.export_data_to_postgres,
{
**metadata,
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'data': prediction_data,
@@ -567,7 +576,8 @@ async def test_run_none_path_flag_with_pi_web_api_and_opc(
'column': 'timestamp',
'format': DATETIME_FORMAT_WITH_TZ,
},
**metadata,
'on_conflict': 'error',
'unique_columns': ['model_id', 'timestamp'],
},
retry_policy=ANY,
start_to_close_timeout=ANY,
@@ -648,6 +658,7 @@ async def test_run_default_path_flag_with_pi_web_api(workflow_mock, format_and_e
call(
Activities.export_data_to_postgres,
{
**metadata,
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'data': pi_web_api_data,
@@ -655,7 +666,8 @@ async def test_run_default_path_flag_with_pi_web_api(workflow_mock, format_and_e
'column': 'timestamp',
'format': DATETIME_FORMAT_WITH_TZ,
},
**metadata,
'on_conflict': 'error',
'unique_columns': ['model_id', 'timestamp'],
},
retry_policy=ANY,
start_to_close_timeout=ANY,

53
tests/laborious/workflows/subworkflows/test_prediction_process.py
View File

@@ -51,14 +51,17 @@ async def test_run(workflow_mock, prediction_process):
}
# Mock the activity responses
workflow_mock.execute_activity_method.side_effect = [
{'content': 'transformed_data', 'timestamp': '2024-01-01'},
{'content': 'predicted_data', 'timestamp': '2024-01-01'},
MagicMock(),
]
workflow_mock.execute_local_activity_method.side_effect = [
('continue', 0.95, 'Input data with bad quality'), # input_gate
{'content': 'transformed_data', 'timestamp': '2024-01-01'}, # transform_data
# mlflow_response_gate (transform)
('continue', 0.95, 'Error'),
# mlflow_content_gate (transform)
('continue', 0.95, 'Transformed data not passed the content filter'),
{'content': 'predicted_data', 'timestamp': '2024-01-01'}, # request_predict
# mlflow_response_gate (predict)
('continue', 0.95, 'Error'),
]
@@ -67,7 +70,7 @@ async def test_run(workflow_mock, prediction_process):
await prediction_process.run(input_data)
# Assert
assert workflow_mock.execute_local_activity_method.call_count == 6
assert workflow_mock.execute_local_activity_method.call_count == 4
workflow_mock.execute_local_activity_method.assert_has_calls(
[
call(
@@ -83,7 +86,7 @@ async def test_run(workflow_mock, prediction_process):
)
]
)
workflow_mock.execute_local_activity_method.assert_has_calls(
workflow_mock.execute_activity_method.assert_has_calls(
[
call(
Activities.request_transform,
@@ -130,7 +133,7 @@ async def test_run(workflow_mock, prediction_process):
)
]
)
workflow_mock.execute_local_activity_method.assert_has_calls(
workflow_mock.execute_activity_method.assert_has_calls(
[
call(
Activities.request_predict,
@@ -166,6 +169,7 @@ async def test_run(workflow_mock, prediction_process):
'subworkflow.format_and_export_prediction',
{
'metadata': metadata,
'on_conflict': 'error',
'path_flag': 'continue',
'data': {'content': 'predicted_data', 'timestamp': '2024-01-01'},
'transformed_data': {'content': 'transformed_data', 'timestamp': '2024-01-01'},
@@ -266,9 +270,12 @@ async def test_run_stop_at_first_mlflow_response_gate(workflow_mock, prediction_
}
# Mock the activity responses
workflow_mock.execute_activity_method.side_effect = [
{'content': 'transformed_data', 'timestamp': '2024-01-01'},
MagicMock(),
]
workflow_mock.execute_local_activity_method.side_effect = [
('repeat', 0.95, 'Input data with bad quality'), # input_gate
{'content': 'transformed_data', 'timestamp': '2024-01-01'}, # transform_data
('continue', 0.95, 'Error'), # mlflow_response_gate (transform)
]
@@ -276,7 +283,7 @@ async def test_run_stop_at_first_mlflow_response_gate(workflow_mock, prediction_
await prediction_process.run(input_data)
# Assert
assert workflow_mock.execute_local_activity_method.call_count == 3
assert workflow_mock.execute_local_activity_method.call_count == 2
workflow_mock.execute_local_activity_method.assert_has_calls(
[
call(
@@ -292,7 +299,7 @@ async def test_run_stop_at_first_mlflow_response_gate(workflow_mock, prediction_
)
]
)
workflow_mock.execute_local_activity_method.assert_has_calls(
workflow_mock.execute_activity_method.assert_has_calls(
[
call(
Activities.request_transform,
@@ -353,9 +360,12 @@ async def test_run_stop_at_mlflow_content_gate(workflow_mock, prediction_process
}
# Mock the activity responses
workflow_mock.execute_activity_method.side_effect = [
{'content': 'transformed_data', 'timestamp': '2024-01-01'},
MagicMock(),
]
workflow_mock.execute_local_activity_method.side_effect = [
('continue', 0.95, 'Input data with bad quality'), # input_gate
{'content': 'transformed_data', 'timestamp': '2024-01-01'}, # transform_data
# mlflow_response_gate (transform)
('continue', 0.95, 'Error'),
# mlflow_content_gate (transform)
@@ -366,7 +376,7 @@ async def test_run_stop_at_mlflow_content_gate(workflow_mock, prediction_process
await prediction_process.run(input_data)
# Assert
assert workflow_mock.execute_local_activity_method.call_count == 4
assert workflow_mock.execute_local_activity_method.call_count == 3
workflow_mock.execute_local_activity_method.assert_has_calls(
[
@@ -383,7 +393,7 @@ async def test_run_stop_at_mlflow_content_gate(workflow_mock, prediction_process
)
]
)
workflow_mock.execute_local_activity_method.assert_has_calls(
workflow_mock.execute_activity_method.assert_has_calls(
[
call(
Activities.request_transform,
@@ -460,14 +470,17 @@ async def test_run_stop_at_mlflow_last_response_gate(workflow_mock, prediction_p
}
# Mock the activity responses
workflow_mock.execute_activity_method.side_effect = [
{'content': 'transformed_data', 'timestamp': '2024-01-01'},
{'content': 'predicted_data', 'timestamp': '2024-01-01'},
MagicMock(),
]
workflow_mock.execute_local_activity_method.side_effect = [
('continue', 0.95, 'Input data with bad quality'), # input_gate
{'content': 'transformed_data', 'timestamp': '2024-01-01'}, # transform_data
# mlflow_response_gate (transform)
('continue', 0.95, 'Error'),
# mlflow_content_gate (transform)
('continue', 0.95, 'Transformed data not passed the content filter'),
{'content': 'predicted_data', 'timestamp': '2024-01-01'}, # request_predict
('continue', 0.95, 'Error'), # mlflow_response_gate (predict)
]
@@ -475,7 +488,7 @@ async def test_run_stop_at_mlflow_last_response_gate(workflow_mock, prediction_p
await prediction_process.run(input_data)
# Assert
assert workflow_mock.execute_local_activity_method.call_count == 6
assert workflow_mock.execute_local_activity_method.call_count == 4
workflow_mock.execute_local_activity_method.assert_has_calls(
[
call(
@@ -491,7 +504,7 @@ async def test_run_stop_at_mlflow_last_response_gate(workflow_mock, prediction_p
)
]
)
workflow_mock.execute_local_activity_method.assert_has_calls(
workflow_mock.execute_activity_method.assert_has_calls(
[
call(
Activities.request_transform,
@@ -538,7 +551,7 @@ async def test_run_stop_at_mlflow_last_response_gate(workflow_mock, prediction_p
)
]
)
workflow_mock.execute_local_activity_method.assert_has_calls(
workflow_mock.execute_activity_method.assert_has_calls(
[
call(
Activities.request_predict,
@@ -727,6 +740,7 @@ async def test_path_flag_handler_continue(workflow_mock, prediction_process):
'confidence_tags': {},
},
'prediction_store_policy': prediction_store_policy,
'on_conflict': 'error',
},
)
@@ -806,12 +820,15 @@ async def test_run_with_cleanup_prefixes(workflow_mock, prediction_process):
'prediction_store_policy': 'lts:1',
}
workflow_mock.execute_activity_method.side_effect = [
{'content': 'transformed_data', 'timestamp': '2024-01-01'},
{'content': 'predicted_data', 'timestamp': '2024-01-01'},
MagicMock(),
]
workflow_mock.execute_local_activity_method.side_effect = [
('continue', 0.95, 'ok'),
{'content': 'transformed_data', 'timestamp': '2024-01-01'},
('continue', 0.95, ''),
('continue', 0.95, ''),
{'content': 'predicted_data', 'timestamp': '2024-01-01'},
('continue', 0.95, ''),
]

1
tests/laborious/workflows/test_predictions_batch.py
View File

@@ -95,6 +95,7 @@ async def test_run(workflow_mock: AsyncMock, predictions_batch: PredictionsBatch
'model_config': input_data.get('model_config', {}),
'path_priority': input_data.get('path_priority', ['STOP', 'CONTINUE', 'REPEAT']),
'opc_output_config': input_data.get('opc_output_config', {}),
'on_conflict': input_data.get('on_conflict', 'error'),
'pi_web_api_output_config': input_data.get('pi_web_api_output_config', {}),
'prediction_store_policy': input_data.get('prediction_store_policy', 'lts:1'),
'save_transform': input_data.get('save_transform', True),