gitea_admin/sientia-dataops-model-manager

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vitor-aignosi 6bd30e3328 feat: enhance test scenarios and configuration for regression models

- Updated `pyproject.toml` to include new linting rules for end-to-end tests.
- Modified `requirements-dev.txt` to add dependencies for E2E testing with `testcontainers` and `requests`.
- Refactored multiple JSON test scenario files to standardize structure, including new fields for `experiment_run_id`, `bucket_name`, and `file_name`.
- Improved model training parameters in `train_model_params.py` to use `experiment_name` directly.
- Adjusted `data_manager_repository.py` to utilize the updated `experiment_name` for logging.

These changes improve the organization and clarity of regression model tests and enhance the overall testing framework.

2026-05-04 11:11:16 -03:00

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E2E Test Scenarios

This document maps the workflow scenarios tested in the E2E suite to their corresponding JSON input files and expected behaviors.

1. TrainModel Workflow (`test_train_model_workflow.py`)

1.1 Happy Paths (Successful execution)

Test Function	Input JSON	Expected Status	Description
`test_scenario_1_1_1_linear_regression_basic`	`01-linear-regression-basic.json`	`TRAINING_SUCCESS`	Basic linear regression without scaler. Verifies end-to-end pipeline.
`test_scenario_1_1_2_polynomial_regression_degree2_with_scaler`	`03-polynomial-regression-degree2.json`	`TRAINING_SUCCESS`	Polynomial regression (degree 2) with Standard Scaler.
`test_scenario_1_1_3_linear_regression_with_lags`	`05-linear-regression-with-lags.json`	`TRAINING_SUCCESS`	Linear regression with `lag_train`/`lag_val` per variable.
`test_scenario_1_1_4_linear_regression_nan_interpolation`	`06-linear-regression-nan-interpolation.json`	`TRAINING_SUCCESS`	Linear regression with `nan_treatment='linear interpolation'`.
`test_scenario_1_1_5_linear_regression_with_limits`	`08-linear-regression-with-limits.json`	`TRAINING_SUCCESS`	Linear regression with `support_filters` (min/max limits per variable).
`test_scenario_1_1_6_polynomial_degree2_scaler_and_lags`	`09-polynomial-degree2-with-scaler-and-lags.json`	`TRAINING_SUCCESS`	Polynomial regression (degree 2), Standard Scaler, and lags.
`test_scenario_1_1_7_static_window_removal`	`11-linear-regression-static-threshold-custom.json`	`TRAINING_SUCCESS`	Linear regression with `rem_static_win=true`, `window`, and `static_threshold`.
`test_scenario_1_1_8_polynomial_with_support_filters`	`14-angular-test-polynomial-support-filters.json`	`TRAINING_SUCCESS`	Polynomial regression (degree 4), Standard Scaler, and support filters.

1.2 Error Paths

Test Function	Input JSON	Expected Status	Description
`test_scenario_1_2_1_minio_file_not_found`	`01-linear-regression-basic.json`	`TRAINING_ERROR`	MinIO file does not exist. Workflow fails during file download.
`test_scenario_1_2_2_experiment_run_id_not_in_db`	`01-linear-regression-basic.json`	N/A (raises Exception)	`experiment_run_id` does not exist in DB. Workflow fails immediately on status update attempt.

2. Parameter Validation (`test_train_model_validation.py`)

These scenarios test the business rule validations inside validate_train_params. All are expected to terminate with ORCHESTRATOR_VALIDATION_ERROR.

Test Function	Modification	Expected Error Substring
`test_scenario_2_1_1_train_size_out_of_range`	`train_size = 5`	`'train_size'`
`test_scenario_2_1_2_empty_variable_columns`	`variable_columns = []`	`'variable_columns'`
`test_scenario_2_1_3_invalid_date_format`	`date_format = 'INVALID'`	`'date_format'`
`test_scenario_2_1_4_whitespace_only_model_name`	`model_name = ' '`	`'model_name'`
`test_scenario_2_1_5_unknown_model_type`	`model_type = 'totally_unknown_model'`	`'totally_unknown_model'`
`test_scenario_2_1_6_missing_target_variable`	`target_variable = ''`	`'target_variable'`
`test_scenario_2_1_7_missing_experiment_run_id`	Missing `experiment_run_id`	N/A (raises ValueError immediately)

3. CleanupFiles Workflow (`test_cleanup_files_workflow.py`)

Test Function	Description
`test_scenario_3_1_1_cleanup_with_no_temp_dirs`	Temp directory is empty. Activity completes without error.
`test_scenario_3_1_2_cleanup_removes_old_temp_dirs`	Two stale timestamped directories are removed.
`test_scenario_3_1_3_cleanup_nonexistent_temp_path`	Target path does not exist. Handled gracefully without error.

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