What problem does it solve? Python applications often fail silently or crash with unhelpful messages when inputs are invalid or batch operations partially fail. This Skill provides concrete patterns for validating inputs early, raising meaningful exceptions, and handling failures gracefully so systems are easier to debug and maintain. ## Core Features & Use Cases - Input Validation Patterns: Fail-fast validation at API boundaries, range checks, and conversion of strings to typed domain objects like enums. - Exception Design: Custom exception hierarchies with structured context, exception chaining with raise ... from, and mapping failures to standard Python exception types. - Batch Failure Handling: Track per-item successes and failures in batch processing with progress callbacks, plus Pydantic models for complex structured validation. - Use Case: When building an API endpoint that processes a batch of user records, apply these patterns to validate each record, collect individual failures without aborting the batch, and return detailed error context to callers. ## Quick Start Ask the AI to add input validation and proper exception handling to your Python function that processes user data or batch operations.
