python-error-handling
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.
By wshobson · 12,376 installs
npx skills add wshobson/agents --skill python-error-handling
Source repository · Upstream listing
Python Error Handling
Build robust Python applications with proper input validation, meaningful exceptions, and graceful failure handling. Good error handling makes debugging easier and systems more reliable.
When to Use This Skill
Validating user input and API parameters
Designing exception hierarchies for applications
Handling partial failures in batch operations
Converting external data to domain types
Building user friendly error messages
Implementing fail fast validation patterns
Core Concepts
1. Fail Fast
Validate inputs early, before expensive operations. Report all validation errors at once when possible.
2. Meaningful Exceptions
Use appropriate exception types with context. Messages should explain what failed, why, and how to fix it.
3. Partial Failures
In batch operations, don't let one failure abort everything. Track successes and failures separately.
4. Preserve Context
Chain exceptions to maintain the full error trail for debugging.
Quick Start
Fundamental Patterns
Pattern 1: Early Input Validation
Validate all inputs at API boundaries before any processing begins.
Pattern 2: Convert to Domain Types Early
Parse strings and external data into typed domain objects at system boundaries.
Pattern 3: Pydantic for Complex Validation
Use Pydantic models for structured input validation with automatic error messages.
Pattern 4: Map Errors to Standard Exceptions
Use Python's built in exception types appropriately, adding context as needed.
Failure Type Exception Example
Invalid input ValueError Bad parameter values
Wrong type TypeError Expected string, got int
Missing item KeyError Dict key not found
Operational failure RuntimeError Service unavailable
Timeout TimeoutError Operation took too long
File not found FileNotFoundError Path doesn't exist
Permission denied PermissionError Access forbidden
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
1. Validate early Check inputs before expensive operations
2. Use specific exceptions ValueError , TypeError , not generic Exception
3. Include context Messages should explain what, why, and how to fix
4. Convert types at boundaries Parse strings to enums/domain types early
5. Chain exceptions Use raise ... from e to preserve debug info
6. Handle partial failures Don't abort batches on single item errors
7. Use Pydantic For complex input validation with structured errors
8. Document failure modes Docstrings should list possible exceptions
9. Log with context Include IDs, counts, and other debugging info
10. Test error paths Verify exceptions are raised correctly