error-handling-patterns

Exceptions interrupt control flow while Result types encode errors as return values. This skill explains both error handling patterns, comparing their use across Python, TypeScript, Rust, and Go to help you build fault-tolerant software.

To implement a circuit breaker for network failures, you wrap downstream service calls in a state machine that trips after repeated errors, preventing cascading crashes. This skill provides guidance on this and other graceful degradation techniques for microservices.

Creating a custom exception hierarchy in Python involves defining base exception classes and inheriting them for specific error categories. This skill provides the guidance to structure these hierarchies effectively, improving debugging and application maintainability.

Yes, this error handling guidance covers fault tolerance patterns across multiple languages including Python and Rust. It details language-specific mechanisms like Python exceptions and Rust Result types to help you prevent unexpected crashes.

The best way to handle invalid inputs and downstream service errors in API endpoints is applying error aggregation and graceful degradation patterns. This skill details how to provide informative user feedback and log issues effectively without crashing.

You should use error aggregation when your application needs to collect multiple validation failures or downstream issues simultaneously instead of failing on the first error. This skill covers this advanced pattern to improve debugging and software resilience.