error-handling-patterns

在实现错误处理、设计API，或提升应用可靠性时使用此功能。掌握跨语言的通用模式，包括异常处理、Result类型、错误传播与优雅降级。

SKILL.md

--- frontmatter

name: error-handling-patterns
description: Use when implementing error handling, designing APIs, or improving application reliability. Master patterns across languages including exceptions, Result types, error propagation, and graceful degradation.

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

Exceptions vs Result Types:

•Exceptions: Traditional try-catch, disrupts control flow. Use for unexpected errors, exceptional conditions.
•Result Types: Explicit success/failure, functional approach. Use for expected errors, validation failures.
•Error Codes: C-style, requires discipline.
•Option/Maybe Types: For nullable values.
•Panics/Crashes: Unrecoverable errors, programming bugs.

2. Error Categories

Recoverable Errors:

•Network timeouts
•Missing files
•Invalid user input
•API rate limits

Unrecoverable Errors:

•Out of memory
•Stack overflow
•Programming bugs (null pointer, etc.)

Universal Patterns

Pattern 1: Circuit Breaker

Prevent cascading failures in distributed systems. See language specific implementations for details, but logically:

•Closed: Normal operation.
•Open: Failing beyond threshold, reject requests immediately.
•Half-Open: Allow limited requests to test recovery.

Pattern 2: Error Aggregation

Collect multiple errors instead of failing on first error (e.g. form validation).

Pattern 3: Graceful Degradation

Provide fallback functionality when errors occur (e.g. cache vs live data).

Language-Specific Patterns

For detailed implementation examples, consult the specific resource file:

•Python: resources/python.md (Custom exceptions, context managers, decorators)
•TypeScript/JavaScript: resources/typescript.md (Custom error classes, Result types, Async handling)
•Rust: resources/rust.md (Result/Option types, ? operator)
•Go: resources/go.md (Explicit error returns, sentinel errors, wrapping)

Best Practices

•Fail Fast: Validate input early, fail quickly.
•Preserve Context: Include stack traces, metadata, timestamps.
•Meaningful Messages: Explain what happened and how to fix it.
•Log Appropriately: Error = log, expected failure = don't spam logs.
•Handle at Right Level: Catch where you can meaningfully handle.
•Clean Up Resources: Use try-finally, context managers, defer.
•Don't Swallow Errors: Log or re-throw, don't silently ignore.
•Type-Safe Errors: Use typed errors when possible.

Common Pitfalls

•Catching Too Broadly: except Exception hides bugs.
•Empty Catch Blocks: Silently swallowing errors.
•Logging and Re-throwing: Creates duplicate log entries.
•Not Cleaning Up: Forgetting to close files, connections.
•Poor Error Messages: "Error occurred" is not helpful.
•Returning Error Codes: Use exceptions or Result types instead.
•Ignoring Async Errors: Unhandled promise rejections.