error-handling-patterns

# 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.)

## Language-Specific Patterns

### Python Error Handling

**Custom Exception Hierarchy:**
```python
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 {}
        self.timestamp = datetime.utcnow()

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

class NotFoundError(ApplicationError):
    """Raised when resource not found."""
    pass

class ExternalServiceError(ApplicationError):
    """Raised when external service fails."