Pydantic
Validates Python data using standard type hints, converting and checking inputs automatically.
- Stars
- 29.3k
- Forks
- 3.1k
- Licence
- MIT
- Language
- Python
- Last update
- 4 days ago
- Type
- Library
What it is
Pydantic is a Python library that checks that data has the shape you describe, using ordinary type hints on classes. You define a model, pass in raw data such as a dictionary from JSON, and it converts values to the right types (for example turning the string '123' into an integer) or raises an error if they do not fit. It is commonly used to make sure data entering a program is well-formed.
- Define a User model and convert raw input like a string ID and a date string into typed fields
- Validate a JSON payload before using it in your program
- Give a clear list of validation errors when data is malformed
- Load typed settings or configuration into a model object
Great for
- Python developers who already use type hints and want runtime checks on incoming data
- Teams parsing JSON or config files into typed objects
- Projects that need clear validation errors for user or API input
- Developers migrating from Pydantic V1 who want to upgrade incrementally
Not ideal for
- Projects not using Python, since the library is Python-only
- Anyone needing a no-code tool; this requires writing Python classes
- Code that must run on Python versions older than 3.10, which the README says is the minimum for its type-hint style
How to get it
- 1
Install with a package manager
You'll need: Python 3.10 or newer · pip or conda
Install with pip
pip install -U pydanticInstall with conda
conda install pydantic -c conda-forge - 2
Run it
- Install the package with pip install -U pydantic
- Create a class that inherits from BaseModel with typed fields
- Pass a dictionary of raw data into the class to create an instance
- Print the instance or its fields to see the converted values
- 3
Get the most out of it
- Read the documentation at pydantic.dev for the full set of field options and validators
- Use the V1 compatibility import from pydantic (v1 as pydantic_v1) to upgrade a project gradually
- Check the install section of the docs for the faster installation options the README mentions
- Pair with your IDE or linter, since the models use standard type hints
Downloads
Strengths
- Uses standard Python type hints, so it works with linters and IDEs
- Converts and validates data in one step, as shown in the README example
- Actively maintained, with a recent push and a large user base (about 29k stars)
Trade-offs
- Version 2 is a rewrite with breaking changes from V1, so older code may need updating
- Some advanced features and performance options are only described in the external documentation, not the README
- The README is truncated here, so details of the full feature set are not verified in this entry
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| pydantic (this) | 29.3k | Library | beginner | 4 days ago | Python developers who already use type hints and want runtime checks on incoming data |
| sqlmodel | 18.5k | Library | beginner | 4 days ago | Python developers building FastAPI applications that use a SQL database |
| validator.js | 23.7k | Library | beginner | 2 months ago | JavaScript developers validating form or API input on Node.js |
| validator | 20.2k | Library | intermediate | 7 days ago | Go developers validating request bodies or form data in web APIs |
| ajv | 14.9k | Library | intermediate | 2 months ago | Node.js developers validating API request or response bodies |
| class-validator | 11.9k | Library | beginner | 8 months ago | TypeScript developers validating request bodies or form data in Node.js or the browser |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.