Add Error Handling

Strengthen resilience by catching and recovering from predictable failures.

Steps

1. Error detection

   • Identify failure points (network calls, file I/O, external APIs)
   • Find unhandled exceptions, missing validations, and async errors
   • Ensure coroutine boundaries (async def) wrap awaited calls with exception handling

2. Handling strategy

   • Use specific exception types (ValueError, RuntimeError, custom errors) instead of bare except
   • Raise from lower-level exceptions (raise MyError(...) from exc) to preserve context
   • Validate inputs early (pydantic models, schema checks, assert statements for invariants)
   • Log structured errors with correlation IDs or context-specific metadata

3. Recovery mechanisms

   • Retry transient failures with exponential backoff (tenacity, async_retry)
   • Provide fallbacks (cached data, defaults) when external services fail
   • Use context managers (with statements) to guarantee cleanup
   • Propagate user-friendly errors to callers while logging detailed internals

4. User experience

   • Return clear API responses (HTTP 4xx/5xx) with actionable messages
   • Add loading states or retries for UI/integration components when backend requests fail
   • Suggest remediation steps in logs/docs if manual intervention is required

Checklist

• Identified every potential failure point in the changed code
• Added validation and sanitization for external inputs
• Logged meaningful error details without leaking secrets
• Wrapped async calls with appropriate try/except or asyncio.wait_for
• Added retries or fallbacks for transient dependencies
• Raised custom exceptions with from chains for traceability
• Provided clear user-facing messages or HTTP status codes