version: "1.0.1" name: error-handling-patterns description: Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.

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