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error-handling-patterns

Comprehensive error handling patterns across Python, TypeScript, Rust, and Go with language-specific implementations.

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SKILL.md

Full skill instructions

Error Handling Patterns

Build resilient applications with robust error handling strategies that gracefully handle failures and provide excellent debugging experiences.

When to Use This Skill

  • Implementing error handling in new features
  • Designing error-resilient APIs
  • Debugging production issues
  • Improving application reliability
  • Creating better error messages for users and developers
  • Implementing retry and circuit breaker patterns
  • Handling async/concurrent errors
  • Building fault-tolerant distributed systems

Core Concepts

1. Error Handling Philosophies

Exceptions vs Result Types:

  • Exceptions: Traditional try-catch, disrupts control flow
  • Result Types: Explicit success/failure, functional approach
  • Error Codes: C-style, requires discipline
  • Option/Maybe Types: For nullable values

When to Use Each:

  • Exceptions: Unexpected errors, exceptional conditions
  • Result Types: Expected errors, validation failures
  • Panics/Crashes: Unrecoverable errors, programming bugs

2. Error Categories

Recoverable Errors:

  • Network timeouts
  • Missing files
  • Invalid user input
  • API rate limits

Unrecoverable Errors:

  • Out of memory
  • Stack overflow
  • Programming bugs (null pointer, etc.)

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Best Practices

  1. Fail Fast: Validate input early, fail quickly
  2. Preserve Context: Include stack traces, metadata, timestamps
  3. Meaningful Messages: Explain what happened and how to fix it
  4. Log Appropriately: Error = log, expected failure = don't spam logs
  5. Handle at Right Level: Catch where you can meaningfully handle
  6. Clean Up Resources: Use try-finally, context managers, defer
  7. Don't Swallow Errors: Log or re-throw, don't silently ignore
  8. Type-Safe Errors: Use typed errors when possible
# Good error handling example
def process_order(order_id: str) -> Order:
    """Process order with comprehensive error handling."""
    try:
        # Validate input
        if not order_id:
            raise ValidationError("Order ID is required")

        # Fetch order
        order = db.get_order(order_id)
        if not order:
            raise NotFoundError("Order", order_id)

        # Process payment
        try:
            payment_result = payment_service.charge(order.total)
        except PaymentServiceError as e:
            # Log and wrap external service error
            logger.error(f"Payment failed for order {order_id}: {e}")
            raise ExternalServiceError(
                f"Payment processing failed",
                service="payment_service",
                details={"order_id": order_id, "amount": order.total}
            ) from e

        # Update order
        order.status = "completed"
        order.payment_id = payment_result.id
        db.save(order)

        return order

    except ApplicationError:
        # Re-raise known application errors
        raise
    except Exception as e:
        # Log unexpected errors
        logger.exception(f"Unexpected error processing order {order_id}")
        raise ApplicationError(
            "Order processing failed",
            code="INTERNAL_ERROR"
        ) from e

Common Pitfalls

  • Catching Too Broadly: except Exception hides bugs
  • Empty Catch Blocks: Silently swallowing errors
  • Logging and Re-throwing: Creates duplicate log entries
  • Not Cleaning Up: Forgetting to close files, connections
  • Poor Error Messages: "Error occurred" is not helpful
  • Returning Error Codes: Use exceptions or Result types
  • Ignoring Async Errors: Unhandled promise rejections