Python Error Handling

This covers the error handling patterns you actually need in production Python code. It shows you how to validate inputs early with clear error messages, use Pydantic for complex validation, chain exceptions to preserve debug context, and handle partial failures in batch operations without aborting everything. The custom exception hierarchy examples are solid, and the batch processing pattern that tracks successes and failures separately will save you headaches when processing large datasets. Good practical coverage of turning messy failure scenarios into manageable, debuggable code.