error-handling-patterns

A circuit breaker pattern prevents cascading failures by blocking requests to failing services. You implement it by wrapping external API calls in a state monitor that trips open after threshold failures, providing fallback mechanisms to maintain application stability.

Exceptions interrupt normal control flow for unexpected errors, while Result types force explicit error handling as return values. Result types make error propagation visible in function signatures, preventing unhandled failures and improving debugging experiences across your application.

Creating a custom exception hierarchy in Python involves defining base exception classes that inherit from Exception, then subclassing for specific domains. This structure improves debugging by categorizing failures and enabling targeted error handling strategies throughout your application.

Graceful degradation allows applications to maintain partial functionality during failures by providing fallback responses. You should use it when interacting with external APIs or non-critical services where returning reduced functionality is preferable to complete application crashes.

Yes, the guidance covers TypeScript, Rust, Python, and Go. It includes language-specific patterns like async error handling for TypeScript, Result and Option types for Rust, explicit error returns for Go, and custom exception hierarchies for Python.

Error aggregation collects multiple validation or processing failures into a single result instead of stopping at the first. This approach is useful for batch operations and user input validation, providing comprehensive feedback rather than requiring repeated retry cycles.