Logging Patterns

Use this skill when implementing features that need logging or debugging.

Checklist

Setup Logger

• • Import LoggerService: from app.services import logger_service
• • Get logger with category: logger = logger_service.get_logger(__name__, category='[Category]')
• • Verify category matches feature domain (see categories below)

Select Appropriate Category

Choose the category that matches your feature domain:

• • [ModelLoad] - Model loading operations
• • [Download] - Download operations
• • [Generate] - Image generation
• • [API] - API endpoints
• • [Database] - Database operations
• • [Service] - Service layer operations
• • [Socket] - WebSocket events
• • [GPU] - GPU operations

Use Appropriate Log Level

• • .debug() - Detailed diagnostic information (only visible with LOG_LEVEL=DEBUG)
• • .info() - General informational messages (progress, status updates)
• • .warning() - Warning messages (degraded functionality, deprecated usage)
• • .error() - Error messages (failures that don't stop execution)
• • .exception() - Exceptions with full stack traces (use in except blocks)

Example Usage

from app.services import logger_service

logger = logger_service.get_logger(__name__, category='ModelLoad')

def load_model(model_path: str):
    logger.info(f'Loading model from {model_path}')
    try:
        # ... model loading logic
        logger.debug('Model loaded successfully')
    except FileNotFoundError as error:
        logger.error(f'Model file not found: {error}')
        raise

Configuration

• • Test with debug logging: LOG_LEVEL=DEBUG uv run python main.py
• • Verify logs appear with correct category prefix in output

Reference

See app/services/logger.py for LoggerService implementation.