pydantic

Installation
Summary

High-performance Python data validation with type hints, Rust-powered core, and seamless FastAPI/Django integration.

  • Validates data at runtime using Python type hints with automatic type coercion; strict mode available per-field or model-wide
  • Supports nested models, recursive types, generics, and custom validators (field-level and model-level) for complex validation logic
  • Includes built-in types for emails, URLs, file paths, secrets, and constrained integers/strings; extensible via custom Pydantic core schemas
  • Serializes to dict, JSON, or custom formats with field-level control; integrates directly with FastAPI request/response models and SQLAlchemy ORM
  • Settings management via BaseSettings for environment variables and config files; computed fields for derived properties
SKILL.md

Pydantic Validation Skill

Summary

Python data validation using type hints and runtime type checking with Pydantic v2's Rust-powered core for high-performance validation.

When to Use

  • API request/response validation (FastAPI, Django)
  • Settings and configuration management (env variables, config files)
  • ORM model validation (SQLAlchemy integration)
  • Data parsing and serialization (JSON, dict, custom formats)
  • Type-safe data classes with automatic validation
  • CLI argument parsing with type safety

Quick Start

from pydantic import BaseModel, Field, EmailStr
from datetime import datetime
Related skills
Installs
2.2K
GitHub Stars
43
First Seen
Jan 23, 2026