Pydantic

Name: Pydantic
Author: Pydantic Services Inc.

by Pydantic Services Inc. · Library · also known as pydantic-core, Pydantic Validation

Python data-validation library using type hints to parse, validate and serialize models, with a Rust core; the schema layer behind FastAPI and many LLM SDKs

MIT licenseOpen sourceFreeLocalSelf-hostable

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Link verified Nov 2, 2026

Overview

Pydantic is an MIT-licensed Python library that uses standard type hints to define data models and then validates, coerces and serializes data against them, with a Rust implementation (pydantic-core) performing the work. BaseModel classes, dataclass support, TypeAdapter for arbitrary types, field and model validators, strict and lax modes, JSON Schema generation and settings management (pydantic-settings) make it the common schema layer of modern Python: FastAPI derives request validation and OpenAPI documents from Pydantic models, the OpenAI and Anthropic SDKs and frameworks such as Pydantic AI, LangChain and Instructor use models to define structured outputs and tool arguments, and configuration files, API payloads and dataset records are routinely parsed through it.

The company Pydantic Services develops the library and sells Logfire, an observability platform, alongside the open-source Pydantic AI agent framework. Version 2 rewrote the core and changed some APIs from version 1, which still affects older code. Pydantic validates individual records rather than whole DataFrames, so tabular validation belongs to Pandera or Great Expectations, and heavy validation of very large collections can dominate runtime despite the Rust core.

Capabilities

Type-hint driven models with validation and coercion
Strict and lax modes, custom validators and serializers
JSON Schema generation and JSON serialization
TypeAdapter for validating arbitrary types
pydantic-settings for environment-based configuration
Rust core (pydantic-core) for performance

Typical workflows

Request and response models for a FastAPI service
Structured outputs and tool schemas for LLM applications
Typed configuration loaded from environment variables

Strengths

Idiomatic Python using standard typing
Ubiquitous in the API and LLM ecosystems
MIT license

Limitations

Record-level, not DataFrame-level validation
v1 to v2 migration changes still encountered in older code
Validation cost on very large collections

Prerequisites

Python 3.9 or later

Who it is for

Python backend developers
Developers of LLM applications and agents
Data engineers validating records

Alternatives & comparison

FastAPI
Python web framework for building HTTP APIs from type-annotated functions, with automatic validation through Pydantic and generated OpenAPI documentation
Open sourceOpen source
Great Expectations (GX Core)
Python data-quality framework that declares Expectations about datasets, validates them against pandas, Spark or SQL sources and produces Data Docs
Open sourceOpen source
Instructor
Python library for extracting validated structured data from LLM responses using Pydantic models, with automatic retries, streaming partials and support for many providers
Open sourceOpen source
Pandera
Lightweight Python library for declaring and validating DataFrame schemas for pandas, Polars, PySpark and other backends, with type-hint style models
Open sourceOpen source
Pydantic AI
Type-safe Python agent framework from the Pydantic team with validated structured outputs, dependency injection, swappable model providers, MCP, durable execution and evals
Open sourceOpen source

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Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

License
Pydantic LICENSE (MIT)
https://github.com/pydantic/pydantic/blob/main/LICENSE
Supports: license_spdx, source_model
checked Nov 1, 2026
Official documentation
Pydantic Validation documentation
https://docs.pydantic.dev/latest
Supports: capabilities, integrations
Redirects to pydantic.dev/docs/validation/latest/
checked Nov 1, 2026
Official site
Pydantic
https://pydantic.dev/
Supports: name, summary, vendor
checked Nov 1, 2026
Repository
pydantic/pydantic
https://github.com/pydantic/pydantic
Supports: repo_url
checked Nov 1, 2026

Confidence: High
Reviewed: Nov 1, 2026
Links: Broken · Nov 2, 2026