Error Handling Expert

Build resilient applications with robust error handling strategies that gracefully handle failures and provide excellent debugging experiences. This skill consolidates best practices for designing error architectures.

When to Use This Skill

• Designing error handling for new features or APIs
• Deciding between Exceptions vs Result types
• Implementing retry/circuit breaker patterns
• Improving error messages and debugging context
• Handling async/concurrent errors in distributed systems

Core Concepts

1. Error Handling Philosophies

Exceptions vs Result Types:

• Exceptions: Traditional try-catch, disrupts control flow. Use for unexpected errors, exceptional conditions (e.g., Network Down, Disk Full).
• Result Types: Explicit success/failure, functional approach. Use for expected errors, validation failures (e.g., User Not Found, Invalid Email).
• Panic/Crash: Unrecoverable errors, programming bugs (e.g., Index Out of Bounds).

2. Universal Resilience Patterns

Circuit Breaker: Stop calling a failing service to prevent cascading failure. Open -> Half-Open -> Closed states.

Error Aggregation: Validate all fields and return all errors at once, rather than failing on the first one.

Graceful Degradation: Primary fails? -> Try Secondary -> Try Cache -> Return Default.

Exponential Backoff: Retry... wait 1s... retry... wait 2s... retry... wait 4s... stop.

Language-Specific Patterns

Python

Custom Exception Hierarchy:

class ApplicationError(Exception):
    """Base exception for all application errors."""
    def __init__(self, message: str, code: str = None, details: dict = None):
        super().__init__(message)
        self.code = code
        self.details = details or {}

class ValidationError(ApplicationError):
    """Raised when validation fails."""
    pass

Context Managers: Use for cleanup (transactions, streams).

@contextmanager
def database_transaction(session):
    try:
        yield session
        session.commit()
    except Exception:
        session.rollback()
        raise
    finally:
        session.close()

TypeScript/JavaScript

Result Type Pattern (Functional):

type Result<T, E = Error> = { ok: true; value: T } | { ok: false; error: E };

function parseJSON<T>(json: string): Result<T, SyntaxError> {
  try {
    return { ok: true, value: JSON.parse(json) };
  } catch (error) {
    return { ok: false, error: error as SyntaxError };
  }
}

Async Error Handling: ALWAYS use try/catch with async/await.

async function extractUser(id: string) {
  try {
    const user = await db.find(id);
    if (!user) throw new NotFoundError("User", id);
    return user;
  } catch (err) {
    // Re-throw if critical, or handle gracefully
    if (err instanceof NotFoundError) return null;
    throw err;
  }
}

Rust

Result and Option Types:

fn get_user_age(id: &str) -> Result<u32, AppError> {
    find_user(id)
        .ok_or_else(|| AppError::NotFound(id.to_string()))
        .map(|user| user.age)
}

Go

Explicit Error Returns:

func getUser(id string) (*User, error) {
    user, err := db.QueryUser(id)
    if err != nil {
        return nil, fmt.Errorf("failed to query user: %w", err)
    }
    return user, nil
}

Best Practices

• Fail Fast: Validate input early.
• Preserve Context: Include stack traces and metadata in custom errors.
• Meaningful Messages: Explain how to fix it, not just what went wrong.
• Don't Swallow Errors: Log or re-throw, don't silently ignore.

Resources

• Circuit Breaker Pattern
• Railway Oriented Programming