wshobson/agents/python-resilience
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Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.
Install
npx vskill@latest install wshobson/agents/python-resilienceSKILL.md
Python Resilience Patterns
Build fault-tolerant Python applications that gracefully handle transient failures, network issues, and service outages. Resilience patterns keep systems running when dependencies are unreliable.
When to Use This Skill
- Adding retry logic to external service calls
- Implementing timeouts for network operations
- Building fault-tolerant microservices
- Handling rate limiting and backpressure
- Creating infrastructure decorators
- Designing circuit breakers
Core Concepts
1. Transient vs Permanent Failures
Retry transient errors (network timeouts, temporary service issues). Don't retry permanent errors (invalid credentials, bad requests).
2. Exponential Backoff
Increase wait time between retries to avoid overwhelming recovering services.
3. Jitter
Add randomness to backoff to prevent thundering herd when many clients retry simultaneously.
4. Bounded Retries
Cap both attempt count and total duration to prevent infinite retry loops.
Quick Start
Fundamental Patterns
Pattern 1: Basic Retry with Tenacity
Use the tenacity library for production-grade retry logic. For simpler cases, consider built-in retry functionality or a lightweight custom implementation.
Pattern 2: Retry Only Appropriate Errors
Whitelist specific transient exceptions. Never retry:
ValueError,TypeError- These are bugs, not transient issuesAuthenticationError- Invalid credentials won't become valid- HTTP 4xx errors (except 429) - Client errors are permanent
Pattern 3: HTTP Status Code Retries
Retry specific HTTP status codes that indicate transient issues.
Pattern 4: Combined Exception and Status Retry
Handle both network exceptions and HTTP status codes.
Detailed worked examples and patterns
Detailed sections (starting with ## Advanced Patterns) live in references/details.md. Read that file when the navigation summary above is insufficient.
Best Practices Summary
- Retry only transient errors - Don't retry bugs or authentication failures
- Use exponential backoff - Give services time to recover
- Add jitter - Prevent thundering herd from synchronized retries
- Cap total duration -
stop_after_attempt(5) | stop_after_delay(60) - Log every retry - Silent retries hide systemic problems
- Use decorators - Keep retry logic separate from business logic
- Inject dependencies - Make infrastructure testable
- Set timeouts everywhere - Every network call needs a timeout
- Fail gracefully - Return cached/default values for non-critical paths
- Monitor retry rates - High retry rates indicate underlying issues
Security
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Source
- SKILL.md in the repositoryCheckingplugins/python-development/skills/python-resilience/SKILL.md
Popularity
- Repository stars
- 39,975
- Repository forks
- 4,262
- 7-day trend score
- 53
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 22 Mar 2026, 7 months ago.
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