python-resilience

A circuit breaker in Python prevents cascading failures by temporarily stopping calls to an unhealthy service. This Skill provides code patterns to implement this mechanism, ensuring your distributed system degrades gracefully during outages.

Handling transient errors and network timeouts in Python requires retry mechanisms with exponential backoff and strict time limits. This Skill implements these strategies to prevent operations from hanging indefinitely during flaky network conditions.

Adding exponential backoff and jitter to Python retry logic involves increasing delays between subsequent attempts with randomized variation. This Skill provides specific code patterns using the tenacity library to automate this fault tolerance strategy.

Yes, this Python fault tolerance approach supports asynchronous operations. It leverages the asyncio library to implement retry strategies, timeout handling, and circuit breaker patterns for non-blocking network requests.

Graceful degradation when an external API is unresponsive is implemented by falling back to cached data or default values. This Skill provides fallback mechanisms to ensure your application continues to function despite primary service failures.

You should avoid using a circuit breaker pattern in Python for non-idempotent operations where retries are unsafe, or when external service failures require immediate hard crashes rather than graceful degradation. It is best suited for transient network errors.