Overview
The codebase currently lacks comprehensive error handling, logging standards, and debugging capabilities. Many functions use basic print statements or generic exception handling.
Current Issues
- Inconsistent error handling patterns across modules
- Basic print statements instead of structured logging
- No standardized debugging framework
- Missing graceful error recovery mechanisms
- Limited error context and traceability
Proposed Improvements
1. Structured Logging
import logging
import structlog
# Configure structured logging
logging.basicConfig(
format=\"%(message)s\",
stream=sys.stdout,
level=logging.INFO,
)
logger = structlog.get_logger()
2. Error Handling Standards
- Create custom exception classes for different error types
- Implement retry mechanisms with exponential backoff
- Add proper error context and user-friendly messages
- Use context managers for resource management
3. Debug Infrastructure
- Add debug modes with varying verbosity levels
- Implement performance profiling hooks
- Create diagnostic information collection
- Add health check endpoints
Implementation Plan
- Create
logging_config.py with standardized logging setup
- Define custom exception hierarchy in
exceptions.py
- Add error handling decorators for common patterns
- Implement debug utilities and performance monitoring
- Update all modules to use new standards
Benefits
- Better debugging and troubleshooting capabilities
- Improved user experience with meaningful error messages
- Enhanced monitoring and observability
- Easier maintenance and issue resolution
Overview
The codebase currently lacks comprehensive error handling, logging standards, and debugging capabilities. Many functions use basic print statements or generic exception handling.
Current Issues
Proposed Improvements
1. Structured Logging
2. Error Handling Standards
3. Debug Infrastructure
Implementation Plan
logging_config.pywith standardized logging setupexceptions.pyBenefits