Cerberus
Lightweight, extensible schema and data validation tool for Pythondictionaries.
Decision gist · record as of 2026-08-14
Yes. Cerberus is a mature, actively maintained library with no known vulnerabilities, permissive ISC licensing, and low install friction. It solves a common problem—validating structured data—with a straightforward API and minimal dependencies. Install it if you need schema validation without the complexity of heavier frameworks.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction: pure Python wheel with only importlib-metadata as a runtime dependency.
- Actively maintained with last commit 2026-07-01; supports Python 3.7 through 3.14 and PyPy.
License · maintenance · safety
permissive license (permissive) — ISC License (permissive): you can use, modify, and distribute Cerberus freely in proprietary and open-source projects with minimal restrictions—just retain the copyright notice.
last release 2025-11-06 (281 days) · last repo commit 2026-07-01 · 3,287 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 6,700,879 downloads/mo, #1,870 on PyPI
Alternatives
Verify before relying
pip install cerberus
from cerberus import Validator
v = Validator({'name': {'type': 'string'}})
result = v.validate({'name': 'john doe'})
print(result) # True- Whether custom validators can be extended without modifying the library itself
- Performance characteristics on large or deeply nested schemas
- Adoption metrics and community size beyond repository stars
What it is and what it does
Cerberus is a lightweight data validation library that checks Python dictionaries and documents against a schema you define. It performs type checking and constraint validation out of the box, and is designed to be easily extended with custom validation logic. The library has no required dependencies beyond importlib-metadata and is maintained to work across modern Python versions from 3.7 onward.
You define a schema as a dictionary specifying field names and their validation rules (type, allowed values, etc.), then create a Validator instance and call validate() on your data. It returns True if the data passes all rules or False if it fails; you can inspect the errors property to see what went wrong. The design prioritizes simplicity and extensibility, making it suitable for validating configuration files, API payloads, form submissions, and other structured data.
Use it for
- Validate incoming JSON or form data in a web API before processing
- Check configuration files conform to an expected schema before loading
- Enforce data structure constraints in data pipelines or ETL workflows
- Normalize and validate user input in CLI tools or interactive applications
- Define and enforce document schemas for database or document store operations
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Cerberus is a mature, actively maintained library with no known vulnerabilities, permissive ISC licensing, and low install friction. It solves a common problem—validating structured data—with a straightforward API and minimal dependencies. Install it if you need schema validation without the complexity of heavier frameworks.
Install
cerberus on PyPI
Before you install
Low friction: pure Python wheel with only importlib-metadata as a runtime dependency. Actively maintained with last commit 2026-07-01; supports Python 3.7 through 3.14 and PyPy.
License in practice
ISC License (permissive): you can use, modify, and distribute Cerberus freely in proprietary and open-source projects with minimal restrictions—just retain the copyright notice.
Quickstart
pip install cerberus
from cerberus import Validator
v = Validator({'name': {'type': 'string'}})
result = v.validate({'name': 'john doe'})
print(result) # TrueVerify before relying
- Whether custom validators can be extended without modifying the library itself
- Performance characteristics on large or deeply nested schemas
- Adoption metrics and community size beyond repository stars
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageimportlib-metadata |
| Maintenance | Actively maintained 281 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 6,700,879 / month, #1,870 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: ISC License (ISCL)Natural Language :: EnglishOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPy |
Evidence: cerberus-1.3.8-py3-none-any.whl
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See also pycsvschema · eido · swagger-spec-validator · cerberus-python-client · fastjsonschema · jsonschema-pydantic-converter · check-jsonschema · flex · protoc-gen-validate · yamale