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sientia-dataops-model-manager/e2e/test_train_model_workflow.py
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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"""
End-to-end tests for TrainModel workflow – main workflow scenarios.
Covers:
1.1.x – Happy-path training (various scenarios from docs/test-scenarios/)
1.2.x – Error paths (MinIO failure, missing DB row)
"""
import pytest
import pytest_asyncio
from temporalio.testing import WorkflowEnvironment
from temporalio.worker import Worker
from e2e.helpers import (
assert_experiment_error,
assert_experiment_run_name_set,
assert_experiment_status,
insert_experiment_run,
load_scenario,
make_workflow_id,
start_and_await_workflow,
)
from model_manager.workflows.train_model import TrainModel
# ---------------------------------------------------------------------------
# 1.1 – Happy paths
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_1_linear_regression_basic(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.1 – Linear Regression Basic (cenário 01).
Validates the complete training pipeline end-to-end:
load_model_metadata → validate_train_params → train_model →
update_experiment_run (TRAINING_SUCCESS).
"""
scenario = load_scenario('01-linear-regression-basic.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-1'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
assert_experiment_run_name_set(postgres_engine, experiment_run_id)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_2_polynomial_regression_degree2_with_scaler(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.2 – Polynomial Regression Degree 2 with Standard Scaler (cenário 03)."""
scenario = load_scenario('03-polynomial-regression-degree2.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-2'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
assert_experiment_run_name_set(postgres_engine, experiment_run_id)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_3_linear_regression_with_lags(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.3 – Linear Regression with lag_train/lag_val per variable (cenário 05)."""
scenario = load_scenario('05-linear-regression-with-lags.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-3'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
assert_experiment_run_name_set(postgres_engine, experiment_run_id)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_4_linear_regression_nan_interpolation(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.4 – nan_treatment='linear interpolation' (cenário 06)."""
scenario = load_scenario('06-linear-regression-nan-interpolation.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-4'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_5_linear_regression_with_limits(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.5 – support_filters with min/max limits per variable (cenário 08)."""
scenario = load_scenario('08-linear-regression-with-limits.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-5'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_6_polynomial_degree2_scaler_and_lags(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.6 – Polynomial degree 2, Standard Scaler and lags (cenário 09)."""
scenario = load_scenario('09-polynomial-degree2-with-scaler-and-lags.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-6'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
assert_experiment_run_name_set(postgres_engine, experiment_run_id)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_7_static_window_removal(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.7 – rem_static_win=true with window and static_threshold (cenário 11)."""
scenario = load_scenario('11-linear-regression-static-threshold-custom.json')
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-7'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_1_8_polynomial_with_support_filters(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.1.8 – Polynomial degree 4, Standard Scaler, upper/lower support filters (cenário 14)."""
scenario = load_scenario('14-angular-test-polynomial-support-filters.json')
# Override date range to match rows in our test CSV
scenario['data_model_kwargs']['start_date'] = '2025-06-02 00:00:00'
scenario['data_model_kwargs']['end_date'] = '2025-06-06 23:59:59'
experiment_run_id = scenario['experiment_run_id']
insert_experiment_run(postgres_engine, experiment_run_id)
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-1-8'),
)
assert_experiment_status(postgres_engine, experiment_run_id, 'TRAINING_SUCCESS')
# ---------------------------------------------------------------------------
# 1.2 – Error paths
# ---------------------------------------------------------------------------
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_2_1_minio_file_not_found(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.2.1 – Training file does not exist in MinIO → TRAINING_ERROR."""
scenario = load_scenario('01-linear-regression-basic.json')
scenario = {**scenario, 'experiment_run_id': 2001, 'file_name': 'does_not_exist.csv'}
experiment_run_id = 2001
insert_experiment_run(postgres_engine, experiment_run_id)
with pytest.raises(Exception):
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-2-1'),
)
assert_experiment_error(
postgres_engine,
experiment_run_id,
expected_status='TRAINING_ERROR',
error_substr='does_not_exist',
)
@pytest.mark.asyncio
@pytest.mark.integration
async def test_scenario_1_2_2_experiment_run_id_not_in_db(
temporal_test_env: WorkflowEnvironment,
temporal_worker: Worker,
postgres_engine,
):
"""Scenario 1.2.2 – experiment_run_id row absent → update_experiment_run raises."""
scenario = load_scenario('01-linear-regression-basic.json')
scenario = {**scenario, 'experiment_run_id': 9999}
# Intentionally NOT inserting the row
with pytest.raises(Exception):
await start_and_await_workflow(
temporal_test_env.client,
TrainModel.run,
scenario,
make_workflow_id('test-s1-2-2'),
)
from e2e.helpers import assert_no_experiment_row
assert_no_experiment_row(postgres_engine, 9999)
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