SIENTIAPDE-1241: Refactor: Remove redundant logging and fix duplicate logs
This commit removes redundant logging statements from training and experiment tracking activities, preventing duplicate log entries. It also introduces a logger helper to disable log propagation, further addressing the duplicate logs issue. Additionally, the Makefile, run_coverage.sh, setup_port_forwards.sh, and simulator/Dockerfile files were removed as they are no longer needed.
This commit is contained in:
Bruno Domingues
7
Makefile
7
Makefile
@@ -1,7 +0,0 @@
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VERSION = 1.0.8
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name = sientia-model-manager
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# ENVIRONMENT = production
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docker-hub:
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@docker build --no-cache -t aignosi.azurecr.io/$(name):$(VERSION) .
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@docker push aignosi.azurecr.io/$(name):$(VERSION)
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@@ -89,9 +89,6 @@ class ExperimentTracking(Postgres):
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notification_handler=notification_handler,
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)
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self.logger = logger
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self.notification_handler = notification_handler
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def __del__(self):
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"""
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Destructor to safely handle cleanup during garbage collection.
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@@ -160,10 +157,6 @@ class ExperimentTracking(Postgres):
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run_name = input_data.get('run_name')
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try:
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self.info(
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f'Updating experiment run {experiment_run_id} with status: {status}', metadata
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)
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query_params: dict[str, Any]
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if update_type == UpdateType.STATUS:
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@@ -249,6 +242,4 @@ class ExperimentTracking(Postgres):
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level=NotificationLevel.ERROR,
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attachment_content=trace,
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)
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self.error(trace, metadata=metadata)
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raise RuntimeError(error_msg) from e
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@@ -80,7 +80,6 @@ class Training(BaseActivity):
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metadata = input_data.get('metadata', {})
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try:
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self.info('Validating training parameters', metadata)
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train_params = TrainModelParams.from_dict(input_data)
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train_params.validate_business_rules()
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@@ -104,8 +103,6 @@ class Training(BaseActivity):
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level=NotificationLevel.ERROR,
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attachment_content=trace,
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)
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self.error(trace, metadata=metadata)
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raise
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@activity.defn(name='train_model')
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@@ -177,8 +174,6 @@ class Training(BaseActivity):
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attachment_content=trace,
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)
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self.error(trace, metadata=metadata)
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raise ModelTrainingError(
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model_trained=model_trained,
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model_saved=model_saved,
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@@ -223,6 +218,4 @@ class Training(BaseActivity):
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level=NotificationLevel.ERROR,
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attachment_content=trace,
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)
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self.error(trace, metadata=metadata)
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raise
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27
model_manager/utils/logger_helper.py
Normal file
27
model_manager/utils/logger_helper.py
Normal file
@@ -0,0 +1,27 @@
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"""
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Logger helper to prevent duplicate logs caused by propagation.
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This module provides a wrapper around sientia_do Logger to disable
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log propagation and prevent duplicate log entries in the Model Manager.
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"""
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from sientia_do.observability.logger import Logger as SientiaLogger
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def get_logger(name: str) -> SientiaLogger:
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"""
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Create a Logger instance with propagation disabled.
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This prevents duplicate logs caused by hierarchical propagation
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in Python's logging system.
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Args:
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name: Logger name (typically __name__ of the calling module).
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Returns:
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Logger: Configured logger instance with propagation disabled.
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"""
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logger = SientiaLogger(name)
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# Disable propagation to prevent duplicate logs
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logger.base_logger.propagate = False
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return logger
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@@ -55,25 +55,14 @@ class ModelRepository:
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Exception: If model saving fails (after sending notification)
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"""
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experiment_name = train_result.params.experiment_name
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self.logger.info(f'Starting model save for experiment: {experiment_name}')
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# Step 1: Generate next run name
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self.logger.info('Generating run name')
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train_result.run_name = self._get_next_run_name(experiment_name)
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self.logger.info(f'Generated run name: {train_result.run_name}')
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# Step 2: Generate artifacts (reports, CSV files)
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self.logger.info('Generating artifacts')
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train_result = self._generate_artifacts(train_result)
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self.logger.info('Artifacts generated successfully')
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# Step 3: Save run to MLflow
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self.logger.info('Saving run to MLflow')
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self._save_run(train_result)
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self.logger.info(
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f'Model saved successfully - Run: {train_result.run_name}, '
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f'Experiment: {experiment_name}'
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f'Model saved successfully - experiment run id: {train_result.params.experiment_run_id}, '
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f'experiment name: {experiment_name}, '
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f'run name: {train_result.run_name}'
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)
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return train_result
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@@ -93,8 +82,6 @@ class ModelRepository:
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self.logger.info('No run directory specified, skipping cleanup')
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return
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self.logger.info(f'Cleaning up run directory: {run_dir}')
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if os.path.exists(run_dir):
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shutil.rmtree(run_dir)
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self.logger.info(f'Run directory deleted successfully: {run_dir}')
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@@ -102,7 +102,6 @@ class StorageRepository:
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Raises:
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OSError: If the download fails (network, permissions, missing key, etc.).
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"""
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self.logger.info(f'Fetching file from MinIO: {bucket_name}/{file_name}')
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response = self.minio_client.get_object(Bucket=bucket_name, Key=file_name)
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with response['Body'] as body:
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@@ -124,6 +123,5 @@ class StorageRepository:
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bucket_name: Bucket that contains the object.
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file_name: Object key to delete.
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"""
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self.logger.info(f'Deleting file from MinIO: {bucket_name}/{file_name}')
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self.minio_client.delete_object(Bucket=bucket_name, Key=file_name)
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self.logger.info(f'File deleted successfully: {bucket_name}/{file_name}')
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@@ -66,9 +66,7 @@ class TrainingRepository:
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ValueError: If transformed data is empty
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Exception: If data loading, preprocessing, or training fails
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"""
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self.logger.info('Loading data from BytesIO file')
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data = load_data(uploaded_file, params.line_separator, params.decimal_separator)
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self.logger.info('Initializing and fitting data preprocessor')
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process_data = self._init_data_preprocessor(params)
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process_data.fit(data)
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data_view = process_data.transform(data)
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@@ -76,7 +74,6 @@ class TrainingRepository:
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if len(data_view) <= 0:
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raise ValueError('Data view is empty after transformation')
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self.logger.info('Splitting data into train/test sets')
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x_train, x_test, y_train, y_test = split_train_test(
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data_view[params.variable_columns],
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data_view[params.target_variable],
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@@ -85,17 +82,18 @@ class TrainingRepository:
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random_state=42,
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)
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self.logger.info('Preparing training data')
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data_train = pd.concat([x_train, y_train], axis=1)
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scaler_dict = self._init_scaler_dict(process_data, params)
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self.logger.info('Training linear regression model')
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regr = LinearRegressionModel(
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target_variable=params.target_variable,
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variable_columns=params.variable_columns,
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)
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regr.fit(data_train)
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self.logger.info(
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f'Model trained successfully - experiment run id: {params.experiment_run_id}'
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)
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return TrainModelResult(
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params=params,
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@@ -128,12 +126,10 @@ class TrainingRepository:
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TrainModelResult: Updated result with predictions, denormalized data,
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and metrics (mse_val, mae_val, r2_val)
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"""
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self.logger.info('Making predictions on test set')
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y_pred_array = tmr.regr.predict(tmr.x_test)
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if params.use_scaler:
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scaler = tmr.process_data.get_scaler()
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self.logger.info('Denormalizing features')
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# If using custom scaler with denormalize_* helpers
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if hasattr(scaler, 'denormalize_single_input'):
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@@ -141,7 +137,6 @@ class TrainingRepository:
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tmr.x_train[col] = scaler.denormalize_single_input(tmr.x_train[col], col)
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tmr.x_test[col] = scaler.denormalize_single_input(tmr.x_test[col], col)
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self.logger.info('Denormalizing target variable')
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tmr.y_train = scaler.denormalize_single_input(tmr.y_train, params.target_variable)
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tmr.y_test = scaler.denormalize_single_input(tmr.y_test, params.target_variable)
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y_pred_array = scaler.denormalize_predictions(y_pred_array, params.target_variable)
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@@ -158,18 +153,15 @@ class TrainingRepository:
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tmr.x_test[feature_cols] = scaler.inverse_transform(x_test_features)
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# Target was not scaled with StandardScaler in preprocessing; leave y as-is
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self.logger.info('Adding index to predictions')
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tmr.y_pred = pd.Series(y_pred_array, index=tmr.y_test.index)
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tmr.y_pred.name = f'{params.target_variable}_pred'
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self.logger.info('Reordering all data by index')
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tmr.x_train = tmr.x_train.sort_index()
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tmr.x_test = tmr.x_test.sort_index()
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tmr.y_train = tmr.y_train.sort_index()
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tmr.y_test = tmr.y_test.sort_index()
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tmr.y_pred = tmr.y_pred.sort_index()
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self.logger.info('Calculating evaluation metrics')
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assert tmr.y_pred is not None, 'y_pred should be set at this point'
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tmr.mse_val = round(
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@@ -183,6 +175,9 @@ class TrainingRepository:
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)
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tmr.r2_val = round(r2(tmr.y_test.astype(np.float64), tmr.y_pred.astype(np.float64)), 2)
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self.logger.info(
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f'Model metrics calculated successfully - experiment run id: {params.experiment_run_id}'
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)
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return tmr
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def _init_scaler_dict(self, process_data: DataPreprocessor, params: TrainModelParams) -> dict:
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@@ -33,7 +33,6 @@ with workflow.unsafe.imports_passed_through():
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from prometheus_client import start_http_server
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from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
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from sientia_do.observability.logger import get_logger
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from model_manager import metrics
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from model_manager.activities.activities import Activities
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@@ -43,6 +42,7 @@ with workflow.unsafe.imports_passed_through():
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build_mongodb_config,
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build_postgres_config,
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)
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from model_manager.utils.logger_helper import get_logger
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from model_manager.workflows.train_model import TrainModel
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POD_ID = os.getenv('POD_ID')
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@@ -73,7 +73,7 @@ async def main():
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metadata = {
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'pod_id': POD_ID,
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'workflow_name': '-',
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'workflow_name': 'train_model',
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}
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logger.custom_info(f'Starting Worker with POD_ID: {POD_ID}', metadata)
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@@ -53,6 +53,8 @@ with workflow.unsafe.imports_passed_through():
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maximum_attempts=5,
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)
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POD_ID = os.getenv('POD_ID')
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@workflow.defn(name='train_model')
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class TrainModel:
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@@ -98,6 +100,7 @@ class TrainModel:
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metadata = {
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'metadata': {
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'pod_id': POD_ID,
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'experiment_run_id': experiment_run_id,
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'workflow_name': 'train_model',
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}
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@@ -1,11 +0,0 @@
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#!/bin/bash
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# Exit on any error
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set -e
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echo "Activating virtual environment..."
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source ./venv/bin/activate
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pytest --cov=model_manager --cov-report=html
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xdg-open htmlcov/index.html
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@@ -1,111 +0,0 @@
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#!/bin/bash
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# Exit on any error
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set -e
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# Color codes for output
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[1;33m'
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NC='\033[0m' # No Color
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echo -e "${GREEN}=== Port Forward Setup Script ===${NC}\n"
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# Define port forwards: LOCAL_PORT:NAMESPACE:SERVICE:REMOTE_PORT:DESCRIPTION
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PORT_FORWARDS=(
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"55432:paradedb:paradedb-rw:5432:PostgreSQL"
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"45249:sientia-tracker:sientia-tracker-mlflow-tracking:80:MLflow"
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"37463:temporal:temporal-frontend:7233:Temporal"
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"8080:temporal:temporal-web:8080:Temporal UI"
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"42297:mongodb:my-release-mongodb:27017:MongoDB"
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"36577:minio:minio:9000:MinIO"
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)
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# Step 1: Kill existing port-forward jobs for these services
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echo -e "${YELLOW}Step 1: Checking for existing port-forward jobs...${NC}"
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for pf in "${PORT_FORWARDS[@]}"; do
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IFS=':' read -r local_port namespace service remote_port description <<< "$pf"
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# Check if there's a job with this service name
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existing_jobs=$(jobs -l | grep "kubectl.*port-forward.*svc/$service" || true)
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if [ -n "$existing_jobs" ]; then
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echo -e "${YELLOW} Found existing port-forward for $description ($service)${NC}"
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# Extract PIDs and kill them
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pids=$(echo "$existing_jobs" | awk '{print $2}')
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for pid in $pids; do
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echo -e "${YELLOW} Killing job with PID $pid${NC}"
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kill "$pid" 2>/dev/null || true
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done
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fi
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done
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# Wait a moment for ports to be released
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sleep 1
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echo -e "${GREEN} Cleanup complete${NC}\n"
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# Step 2: Check if any of the ports are already in use
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echo -e "${YELLOW}Step 2: Checking if ports are available...${NC}"
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ports_in_use=()
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for pf in "${PORT_FORWARDS[@]}"; do
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IFS=':' read -r local_port namespace service remote_port description <<< "$pf"
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# Check if port is in use using lsof or netstat
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if command -v lsof &> /dev/null; then
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if lsof -Pi :$local_port -sTCP:LISTEN -t >/dev/null 2>&1; then
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ports_in_use+=("$local_port:$description")
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fi
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elif command -v netstat &> /dev/null; then
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if netstat -tuln | grep -q ":$local_port "; then
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ports_in_use+=("$local_port:$description")
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fi
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elif command -v ss &> /dev/null; then
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if ss -tuln | grep -q ":$local_port "; then
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ports_in_use+=("$local_port:$description")
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fi
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fi
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done
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# If any ports are in use, report and exit
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if [ ${#ports_in_use[@]} -gt 0 ]; then
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echo -e "${RED}ERROR: The following ports are already in use:${NC}"
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for port_info in "${ports_in_use[@]}"; do
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IFS=':' read -r port desc <<< "$port_info"
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echo -e "${RED} - Port $port (for $desc)${NC}"
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done
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echo -e "\n${RED}Please free these ports before running this script.${NC}"
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exit 1
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fi
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echo -e "${GREEN} All ports are available${NC}\n"
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# Step 3: Create all port forwards
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echo -e "${YELLOW}Step 3: Creating port forwards...${NC}"
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|
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for pf in "${PORT_FORWARDS[@]}"; do
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IFS=':' read -r local_port namespace service remote_port description <<< "$pf"
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echo -e "${GREEN} Starting port-forward: $description${NC}"
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echo -e " Local port: $local_port -> $namespace/$service:$remote_port"
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|
||||
kubectl -n "$namespace" port-forward "svc/$service" "$local_port:$remote_port" &
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||||
|
||||
# Give it a moment to start
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||||
sleep 0.5
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||||
done
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||||
|
||||
echo -e "\n${GREEN}=== All port forwards created successfully ===${NC}"
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||||
echo -e "\n${YELLOW}Active port forwards:${NC}"
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for pf in "${PORT_FORWARDS[@]}"; do
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||||
IFS=':' read -r local_port namespace service remote_port description <<< "$pf"
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echo -e " - ${GREEN}localhost:$local_port${NC} -> $description ($namespace/$service)"
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||||
done
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||||
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||||
echo -e "\n${YELLOW}To stop all port forwards, run:${NC}"
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||||
echo -e " jobs -p | xargs kill"
|
||||
echo -e "\n${YELLOW}To view active port forwards:${NC}"
|
||||
echo -e " jobs -l"
|
||||
@@ -1,30 +0,0 @@
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||||
# syntax=docker/dockerfile:1.4
|
||||
|
||||
FROM python:3.11-slim
|
||||
|
||||
# Enable use of SSH agent/socket
|
||||
# This line enables SSH during build
|
||||
# (don't forget the syntax header above)
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||||
RUN apt-get update && apt-get install -y git openssh-client && rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# Use build-time SSH mount for Git clone
|
||||
# The SSH key will NOT remain in the image
|
||||
# IMPORTANT: this block requires BuildKit
|
||||
# and the --ssh flag during docker build
|
||||
|
||||
# SSH config to skip host key check (safe in CI/local dev)
|
||||
RUN mkdir -p /root/.ssh && echo "StrictHostKeyChecking no" > /root/.ssh/config
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# Clone using SSH
|
||||
ARG GIT_REPO
|
||||
ARG GIT_BRANCH=main
|
||||
|
||||
# Mount SSH key just for this RUN
|
||||
RUN --mount=type=ssh git clone --branch ${GIT_BRANCH} ${GIT_REPO} .
|
||||
|
||||
# Install requirements if exists
|
||||
RUN if [ -f requirements.txt ]; then pip install --no-cache-dir -r requirements.txt; fi
|
||||
|
||||
CMD ["python", "server.py"]
|
||||
@@ -1,3 +1,2 @@
|
||||
- remover os testes das classes alteradas e refazer de novo depois
|
||||
- no final alterar o readme
|
||||
- verificar erro de logs duplicados
|
||||
|
||||
47
validate.sh
47
validate.sh
@@ -1,9 +1,39 @@
|
||||
#!/bin/bash
|
||||
# Model Manager Code Validation Script
|
||||
# This script runs all code quality checks before committing or deploying
|
||||
#
|
||||
# Usage:
|
||||
# ./validate.sh # Run all checks including tests (default)
|
||||
# ./validate.sh --no-tests # Skip unit tests
|
||||
# ./validate.sh --skip-tests # Skip unit tests (alias)
|
||||
|
||||
set -e # Exit on any error
|
||||
|
||||
# Parse command line arguments
|
||||
RUN_TESTS=true
|
||||
for arg in "$@"; do
|
||||
case $arg in
|
||||
--no-tests|--skip-tests)
|
||||
RUN_TESTS=false
|
||||
shift
|
||||
;;
|
||||
--help|-h)
|
||||
echo "Usage: $0 [OPTIONS]"
|
||||
echo ""
|
||||
echo "Options:"
|
||||
echo " --no-tests, --skip-tests Skip unit tests (default: run tests)"
|
||||
echo " --help, -h Show this help message"
|
||||
echo ""
|
||||
exit 0
|
||||
;;
|
||||
*)
|
||||
echo "Unknown option: $arg"
|
||||
echo "Use --help for usage information"
|
||||
exit 1
|
||||
;;
|
||||
esac
|
||||
done
|
||||
|
||||
# Colors for output
|
||||
RED='\033[0;31m'
|
||||
GREEN='\033[0;32m'
|
||||
@@ -16,6 +46,11 @@ echo -e "${BLUE}║ Model Manager - Code Validation Suite ║${N
|
||||
echo -e "${BLUE}╚════════════════════════════════════════════════════════╝${NC}"
|
||||
echo ""
|
||||
|
||||
if [ "$RUN_TESTS" = false ]; then
|
||||
echo -e "${YELLOW}ℹ️ Unit tests will be skipped${NC}"
|
||||
echo ""
|
||||
fi
|
||||
|
||||
# Check if virtual environment is activated
|
||||
if [[ -z "${VIRTUAL_ENV}" ]] && [[ -z "${CONDA_DEFAULT_ENV}" ]]; then
|
||||
echo -e "${YELLOW}⚠️ Warning: No virtual environment detected${NC}"
|
||||
@@ -67,8 +102,16 @@ if ! run_step "4. Security Analysis (Bandit)" "bandit -r model_manager/ -ll -q";
|
||||
fi
|
||||
|
||||
# Step 5: Unit Tests (pytest)
|
||||
if ! run_step "5. Unit Tests (pytest)" "pytest tests/ --cov=model_manager --cov-report=term-missing --cov-report=xml --cov-report=html --cov-fail-under=80 -q"; then
|
||||
FAILED_STEPS+=("Unit Tests")
|
||||
if [ "$RUN_TESTS" = true ]; then
|
||||
if ! run_step "5. Unit Tests (pytest)" "pytest tests/ --cov=model_manager --cov-report=term-missing --cov-report=xml --cov-report=html --cov-fail-under=80 -q"; then
|
||||
FAILED_STEPS+=("Unit Tests")
|
||||
fi
|
||||
else
|
||||
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
|
||||
echo -e "${BLUE}▶ 5. Unit Tests (pytest)${NC}"
|
||||
echo -e "${BLUE}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
|
||||
echo -e "${YELLOW}⏭️ Unit Tests - SKIPPED${NC}"
|
||||
echo ""
|
||||
fi
|
||||
|
||||
# Summary
|
||||
|
||||
Reference in New Issue
Block a user