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SIENTIAPDE-1579: Lint fixes and formatting

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This commit is contained in:
Kou Kinoshita
2026-02-18 17:31:58 -03:00
parent c6d6f94e05
commit 43cbc31e10
7 changed files with 151 additions and 124 deletions
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5
model_manager/activities/experiment_tracking.py
View File

@@ -6,6 +6,8 @@ in the PostgreSQL database, extending the base Postgres activity with specialize
methods for experiment management.
"""
import enum
from temporalio import activity, workflow
with workflow.unsafe.imports_passed_through():
@@ -13,7 +15,6 @@ with workflow.unsafe.imports_passed_through():
import traceback
from collections.abc import Mapping
from datetime import UTC, datetime
from enum import Enum
from typing import Any
from sientia_do.notifications.handlers import CoreNotificationHandler as NotificationHandler
@@ -24,7 +25,7 @@ with workflow.unsafe.imports_passed_through():
from sqlalchemy import text
class UpdateType(str, Enum):
class UpdateType(enum.StrEnum):
"""Types of experiment run updates."""
STATUS = 'status'

4
model_manager/sientia/models.py
View File

@@ -463,7 +463,9 @@ class DataPreprocessor(BaseEstimator, TransformerMixin):
if not date_str:
return None
try:
python_fmt = _frontend_date_format_to_strftime(self.date_format) if self.date_format else None
python_fmt = (
_frontend_date_format_to_strftime(self.date_format) if self.date_format else None
)
if python_fmt:
return pd.to_datetime(date_str, format=python_fmt)
return pd.to_datetime(date_str)

4
model_manager/utils/models/experiment_status.py
View File

@@ -1,7 +1,7 @@
from enum import Enum
from enum import StrEnum
class ExperimentStatus(str, Enum):
class ExperimentStatus(StrEnum):
"""
Status values for experiment run lifecycle.

6
model_manager/utils/repository/training_repository.py
View File

@@ -481,9 +481,9 @@ class TrainingRepository:
'datetime',
'DateTime',
]
timestamp_columns = (
[params.date_column] if params.date_column else []
) + [c for c in common_timestamp_columns if c != params.date_column]
timestamp_columns = ([params.date_column] if params.date_column else []) + [
c for c in common_timestamp_columns if c != params.date_column
]
for col in timestamp_columns:
if col in data.columns:

28
scripts/run_cleanup_test.py
View File

@@ -14,18 +14,18 @@ import asyncio
import os
import sys
from datetime import timedelta
from typing import Any
from dotenv import load_dotenv
from pathlib import Path
from typing import Any
from dotenv import load_dotenv
from temporalio.client import Client
# Ensure project root is on PYTHONPATH when running directly
# Ensure project root is on PYTHONPATH when running directly (must run before model_manager import)
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
if ROOT_DIR not in sys.path:
sys.path.insert(0, ROOT_DIR)
from model_manager.workflows.cleanup_files import CleanupFiles
from model_manager.workflows.cleanup_files import CleanupFiles # noqa: E402
# Carrega variáveis de ambiente do arquivo .env na raiz do projeto
PROJECT_ROOT = Path(__file__).resolve().parent.parent
@@ -53,7 +53,7 @@ async def main(argv: list[str]) -> None:
if argv:
bucket_name = argv[0]
print(f"Connecting to Temporal at {temporal_host} (namespace={temporal_namespace})...")
print(f'Connecting to Temporal at {temporal_host} (namespace={temporal_namespace})...')
client = await Client.connect(
target_host=temporal_host,
namespace=temporal_namespace,
@@ -64,12 +64,14 @@ async def main(argv: list[str]) -> None:
'bucket_name': bucket_name,
}
workflow_id = f"cleanup-files-manual-{int(asyncio.get_event_loop().time())}"
workflow_id = f'cleanup-files-manual-{int(asyncio.get_event_loop().time())}'
print(f"Starting cleanup_files workflow once...\n"
f" workflow_id = {workflow_id}\n"
f" task_queue = {task_queue}\n"
f" bucket_name = {bucket_name}")
print(
f'Starting cleanup_files workflow once...\n'
f' workflow_id = {workflow_id}\n'
f' task_queue = {task_queue}\n'
f' bucket_name = {bucket_name}'
)
handle = await client.start_workflow(
CleanupFiles.run,
@@ -79,9 +81,9 @@ async def main(argv: list[str]) -> None:
run_timeout=timedelta(minutes=10),
)
print("Workflow started, waiting for completion...")
print('Workflow started, waiting for completion...')
await handle.result()
print("cleanup_files workflow completed successfully.")
print('cleanup_files workflow completed successfully.')
if __name__ == '__main__': # pragma: no cover - manual utility script

92
scripts/run_training_test.py
View File

@@ -39,7 +39,6 @@ from dotenv import load_dotenv
from psycopg2.extras import Json
from temporalio import client
# Carrega variáveis de ambiente do arquivo .env na raiz do projeto
PROJECT_ROOT = Path(__file__).resolve().parent.parent
ENV_PATH = PROJECT_ROOT / '.env'
@@ -325,9 +324,7 @@ def run_local_pipeline(
try:
train_result = training_repository.train(file_content, train_params)
train_result = training_repository.after_train_calculation(
train_params, train_result
)
train_result = training_repository.after_train_calculation(train_params, train_result)
except Exception as e:
result['error'] = str(e)
raise # re-raise so caller gets full traceback for diagnosis
@@ -448,7 +445,7 @@ def run_single_scenario(scenario_name: str, csv_path: Path) -> dict:
# Load scenario
try:
experiment_request = load_scenario(scenario_name)
print(f" Loaded scenario: {scenario_name}")
print(f' Loaded scenario: {scenario_name}')
except FileNotFoundError as exc:
result['error'] = str(exc)
return result
@@ -459,7 +456,7 @@ def run_single_scenario(scenario_name: str, csv_path: Path) -> dict:
try:
uploaded_file_name = upload_to_minio(csv_path)
result['s3_object_name'] = uploaded_file_name
print(f" Uploaded CSV to MinIO: {uploaded_file_name}")
print(f' Uploaded CSV to MinIO: {uploaded_file_name}')
except subprocess.CalledProcessError as exc:
result['error'] = f'Failed to upload file to MinIO: {exc}'
return result
@@ -471,7 +468,7 @@ def run_single_scenario(scenario_name: str, csv_path: Path) -> dict:
try:
experiment_run_id = insert_experiment_run(uploaded_file_name, experiment_request)
result['experiment_run_id'] = experiment_run_id
print(f" Created experiment_run with ID: {experiment_run_id}")
print(f' Created experiment_run with ID: {experiment_run_id}')
except psycopg2.Error as exc:
result['error'] = f'Database error while inserting experiment_run: {exc}'
return result
@@ -487,7 +484,7 @@ def run_single_scenario(scenario_name: str, csv_path: Path) -> dict:
workflow_id = asyncio.run(trigger_temporal_workflow(workflow_payload))
result['workflow_id'] = workflow_id
result['success'] = True
print(f" Workflow started: {workflow_id}")
print(f' Workflow started: {workflow_id}')
except Exception as exc: # noqa: BLE001
result['error'] = f'Failed to start Temporal workflow: {exc}'
return result
@@ -507,29 +504,26 @@ def print_summary(results: list[dict]) -> None:
print('\n' + '=' * 60)
print('SUMMARY')
print('=' * 60)
print(f"Total: {len(results)} | Passed: {len(passed)} | Failed: {len(failed)}")
print(f'Total: {len(results)} | Passed: {len(passed)} | Failed: {len(failed)}')
print('=' * 60)
if passed:
print('\n✓ PASSED:')
for r in passed:
print(f" - {r['scenario']}")
print(f' - {r["scenario"]}')
if failed:
print('\n✗ FAILED:')
for r in failed:
print(f" - {r['scenario']}")
print(f' - {r["scenario"]}')
if r['error']:
print(f" Error: {r['error']}")
print(f' Error: {r["error"]}')
print()
def main() -> None:
args = parse_args()
# List scenarios and exit if requested
if args.list:
def _handle_list_scenarios() -> None:
"""Print available scenarios and exit."""
scenarios = list_available_scenarios()
if scenarios:
print('Available test scenarios:')
@@ -539,8 +533,9 @@ def main() -> None:
print(f'No scenarios found in {TEST_SCENARIOS_DIR}')
sys.exit(0)
# Run all scenarios if requested
if args.all:
def _handle_run_all(args: argparse.Namespace) -> None:
"""Run all scenarios and exit with appropriate code."""
scenarios = list_available_scenarios()
if not scenarios:
print(f'No scenarios found in {TEST_SCENARIOS_DIR}', file=sys.stderr)
@@ -548,7 +543,6 @@ def main() -> None:
print(f'Running {len(scenarios)} scenarios...\n')
results = []
for i, scenario in enumerate(scenarios, 1):
print(f'[{i}/{len(scenarios)}] Running scenario: {scenario}')
result = run_single_scenario(scenario, args.csv)
@@ -557,26 +551,26 @@ def main() -> None:
print(f'[{i}/{len(scenarios)}] {status} {scenario}\n')
print_summary(results)
# Exit with error code if any scenario failed
failed_count = sum(1 for r in results if not r['success'])
sys.exit(1 if failed_count > 0 else 0)
# Validate-only mode: no external services
if args.validate_only:
def _handle_validate_only(args: argparse.Namespace) -> None:
"""Validate scenario parameters only and exit."""
if not args.scenario:
print('Error: --scenario is required with --validate-only.', file=sys.stderr)
sys.exit(1)
result = run_validate_only(args.scenario)
if result['success']:
print(f"Validation OK: {result['scenario']}")
print(f'Validation OK: {result["scenario"]}')
else:
print(f"Validation failed: {result['error']}", file=sys.stderr)
print(f'Validation failed: {result["error"]}', file=sys.stderr)
sys.exit(1)
return
sys.exit(0)
# Local pipeline: same code path as worker, full traceback on error
if args.local:
def _handle_local(args: argparse.Namespace) -> None:
"""Run local pipeline and exit."""
if not args.scenario:
print('Error: --scenario is required with --local.', file=sys.stderr)
sys.exit(1)
@@ -587,7 +581,7 @@ def main() -> None:
save_mlflow=args.local_save_mlflow,
)
if not result['success']:
print(f"Error: {result['error']}", file=sys.stderr)
print(f'Error: {result["error"]}', file=sys.stderr)
sys.exit(1)
out = {'scenario': result['scenario'], 'success': True}
if result.get('run_name') is not None:
@@ -595,21 +589,15 @@ def main() -> None:
if result.get('run_dir') is not None:
out['run_dir'] = result['run_dir']
print(json.dumps(out, indent=2))
return
# Require scenario argument if not listing or running all
if not args.scenario:
print('Error: --scenario or --all is required. Use --list to see available scenarios.', file=sys.stderr)
sys.exit(1)
# Run single scenario (MinIO + Postgres + Temporal)
def _handle_single_scenario(args: argparse.Namespace) -> None:
"""Run one scenario (MinIO + Postgres + Temporal) and print result."""
print(f'Running scenario: {args.scenario}')
result = run_single_scenario(args.scenario, args.csv)
if not result['success']:
print(f"Error: {result['error']}", file=sys.stderr)
print(f'Error: {result["error"]}', file=sys.stderr)
sys.exit(1)
print(
json.dumps(
{
@@ -623,5 +611,31 @@ def main() -> None:
)
def main() -> None:
args = parse_args()
if args.list:
_handle_list_scenarios()
if args.all:
_handle_run_all(args)
if args.validate_only:
_handle_validate_only(args)
if args.local:
_handle_local(args)
return
if not args.scenario:
print(
'Error: --scenario or --all is required. Use --list to see available scenarios.',
file=sys.stderr,
)
sys.exit(1)
_handle_single_scenario(args)
if __name__ == '__main__':
main()

22
tests/utils/repository/test_training_repository.py
View File

@@ -991,7 +991,9 @@ class TestConfigureDatetimeIndex:
assert 'var2' in result.columns
@pytest.mark.filterwarnings('ignore::UserWarning')
def test_configure_datetime_index_invalid_timestamp_column(self, training_repo, datetime_params):
def test_configure_datetime_index_invalid_timestamp_column(
self, training_repo, datetime_params
):
"""Test _configure_datetime_index with invalid timestamp values."""
data = pd.DataFrame(
{
@@ -1151,10 +1153,12 @@ class TestApplySupportFilters:
def test_snake_case_upper_lower_line(self):
"""Support filters with upper_line/lower_line (snake_case) filter rows."""
data = pd.DataFrame({
data = pd.DataFrame(
{
'x': [1.0, 2.0, 3.0, 4.0],
'target': [2.0, 4.0, 6.0, 8.0],
})
}
)
support_filters = {
'x': {
'upper_line': {'intercept': 1.0, 'angle': 50},
@@ -1167,10 +1171,12 @@ class TestApplySupportFilters:
def test_camel_case_upper_lower_line(self):
"""Support filters with upperLine/lowerLine (camelCase) are accepted."""
data = pd.DataFrame({
data = pd.DataFrame(
{
'x': [1.0, 2.0, 3.0],
'target': [1.0, 2.0, 3.0],
})
}
)
support_filters = {
'x': {
'upperLine': {'intercept': 2, 'angle': 5},
@@ -1183,11 +1189,13 @@ class TestApplySupportFilters:
def test_two_variables_ands_masks(self):
"""Two variables apply AND of both masks."""
data = pd.DataFrame({
data = pd.DataFrame(
{
'a': [1.0, 2.0, 3.0],
'b': [1.0, 2.0, 3.0],
'target': [2.0, 2.0, 2.0],
})
}
)
support_filters = {
'a': {
'upper_line': {'intercept': 10, 'angle': 45},