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='[e-mail]', age=30)
print(user.model_dump_json())

GitHub: pydantic/pydantic - 22K+ stars

---

Need to monitor and scrape data from multiple web services automatically? I build custom scraping solutions. Check out my web scraping toolkit or email me at [e-mail] for a tailored solution.