Pydantic Has a Free Data Validation Library — Python Models with Automatic Type Checking

A Python developer parsed JSON from an API. Nested dicts, missing keys, wrong types - debugging data issues consumed hours every week. Pydantic validates data using Python type hints. Define a model, pass data, get validated objects or clear error messages. Used by FastAPI, LangChain, and thousands of projects. What Pydantic Offers for Free Type Validation - Validate data against Python type hints Serialization - Convert to/from JSON, dict Settings - Environment variable management Custom Validators - Field and model validators JSON Schema - Auto-generate JSON Schema from models Performance - Core written in Rust (Pydantic V2) IDE Support - Full autocomplete and type checking Quick Start from pydantic import BaseModel , EmailStr , field_validator class User ( BaseModel ): name : str email : EmailStr age : int @field_validator ( ' age ' ) def check_age ( cls , v ): if v < 0 or v > 150 : raise ValueError ( ' Invalid age ' ) return v user = User ( name = ' John ' , email = ' john@example.