---
id: validators
version: "0.35.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# validators — Python Data Validation for Humans™

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install validators
uv add validators
poetry add validators

## Description

# validators - Python Data Validation for Humans™

[![PyCQA][pycqa-badge]][pycqa-link] [![SAST][sast-badge]][sast-link] [![Docs][docs-badge]][docs-link] [![Version][vs-badge]][vs-link] [![Downloads][dw-badge]][dw-link]

<!-- [![Package][package-badge]][package-link] -->

Python has all kinds of data validation tools, but every one of them seems to
require defining a schema or form. I wanted to create a simple validation
library where validating a simple value does not require defining a form or a
schema.

```shell
pip install validators
```

Then,

```python
>>> import validators
>>>
>>> validators.email('someone@example.com')
True
```

## Resources

<!-- Backup documentation URL :  https://yozachar.github.io/pyvalidators/ -->
<!-- Original documentation URL :  https://python-validators.github.io/validators/ -->

- [Documentation](https://yozachar.github.io/pyvalidators)
- [Bugtracker](https://github.com/python-validators/validators/issues)
- [Security](https://github.com/python-validators/validators/blob/master/SECURITY.md)
- [Code](https://github.com/python-validators/validators/)

<!-- Original docs URL will be restored, once properly versioned docs are ready. -->

---

>...

## AI interpretation — verify before relying

validators provides simple, schema-free validation functions for common data types like email addresses, URLs, and other formats, letting you validate individual values with direct function calls rather than defining schemas.

Verdict: validators is a lightweight, actively maintained validation library with no dependencies, permissive licensing, and no known vulnerabilities. It is well-suited for projects needing straightforward format validation without schema overhead. The recent release cadence and active repository indicate solid maintenance, though users on Python 3.9 should plan for migration as that version approaches end-of-life.

[View on SkillFed](https://skillfed.io/packages/validators) · [View on PyPI](https://pypi.org/project/validators/)