error-handling-patternslisted

# 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,