Pydantic Multi-Model Architect
Standardizes the creation of Pydantic models using a multi-model architecture to ensure consistent API contracts and database schemas.
This skill provides a structured approach to Python data validation by implementing the multi-model pattern, which separates concerns between resource creation, updates, and API responses. It automates the generation of Pydantic models with built-in support for camelCase aliases, optional PATCH request fields, and database-specific attributes like doc_types for Cosmos DB. By following this pattern, developers can maintain clean, type-safe API contracts that seamlessly integrate with frontend TypeScript types and backend database logic.
Key Features
01Streamlines the synchronization between Python models and TypeScript interfaces
02Generates PATCH-compatible update models with intelligent optional fields
03Implements the robust multi-model pattern (Base, Create, Update, Response, InDB)
04Automates camelCase alias mapping for seamless frontend JSON compatibility
05Provides templates for database document structures with doc_type identifiers
0675 GitHub stars
Use Cases
01Synchronizing backend snake_case models with frontend camelCase requirements
02Designing NoSQL database schemas for systems like Cosmos DB or MongoDB
03Building RESTful APIs with FastAPI that require strict contract validation