error-handling-patterns

Error handling prevents crashes by catching exceptions, categorizing them as recoverable or unrecoverable, and executing appropriate recovery logic. Implement try-catch blocks, use result types to encapsulate success or failure, and apply retry strategies for transient failures to maintain application stability.

Centralized logging collects all error events in one location for analysis and debugging. Standardize error messages with context (timestamp, stack trace, user ID), route logs to a central system, and structure them consistently across your application to simplify root-cause analysis.

Graceful degradation handles API errors by catching them, logging details, and returning a user-friendly message instead of exposing technical errors. Use circuit-breaker patterns to stop retrying failed services, apply exponential backoff for transient failures, and degrade functionality rather than fail entirely.

Exceptions suit unexpected or unrecoverable errors; result types (return objects with success/failure states) suit expected outcomes like invalid input. Combine both: use exceptions for programming errors and system failures, result types for predictable validation and business logic failures.

Yes, error handling patterns are language-agnostic principles. This skill provides concrete code examples in both Python and TypeScript, demonstrating how to implement exceptions, retry strategies, and circuit-breaker patterns with each language's native syntax and libraries.

A circuit-breaker pattern prevents cascading failures by stopping requests to a failing service after repeated errors, then gradually retrying. It reduces load on struggling systems, improves user experience by failing fast, and protects dependent services from resource exhaustion.