error-handling-patterns
Comprehensive error handling patterns across Python, TypeScript, Rust, and Go with language-specific implementations.
- Covers error philosophies (exceptions vs Result types), error categories (recoverable vs unrecoverable), and language-specific patterns including custom exception hierarchies, Result types, and async error handling
- Includes three universal patterns: circuit breaker for preventing cascading failures, error aggregation for collecting multiple errors, and graceful degradation with fallback functions
- Provides best practices for fail-fast validation, meaningful error messages, resource cleanup, and type-safe error handling with concrete code examples
- Highlights common pitfalls like overly broad exception catching, empty catch blocks, poor error messages, and unhandled async errors
Error Handling Patterns
Build resilient applications with robust error handling strategies that gracefully handle failures and provide excellent debugging experiences.
When to Use This Skill
- Implementing error handling in new features
- Designing error-resilient APIs
- Debugging production issues
- Improving application reliability
- Creating better error messages for users and developers
- Implementing retry and circuit breaker patterns
- Handling async/concurrent errors
- Building fault-tolerant distributed systems
Core Concepts
1. Error Handling Philosophies
More from wshobson/agents
tailwind-design-system
Build scalable design systems with Tailwind CSS v4, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.
41.0Ktypescript-advanced-types
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.
40.4Knodejs-backend-patterns
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
31.8Kpython-performance-optimization
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
22.1Kapi-design-principles
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
20.3Kpython-testing-patterns
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
19.7K