# pyeve/cerberus

Lightweight, extensible data validation library for Python

Repository: https://github.com/pyeve/cerberus
Canonical: https://ross.abutalabs.com/products/pyeve-cerberus
Homepage: http://python-cerberus.org
Language: Python
License: ISC
License Family: permissive
Topics: python, data-validation
Last push: 2026-07-01T04:53:50+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 90, release rhythm 35, longevity 100
- inputs: {"age_days": 5075, "days_push": 63, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3288, forks 245 (observed 2026-08-28T04:07:53.834960+00:00)

## What it is
Cerberus is a lightweight, extensible data validation library for Python that validates dictionaries against user-defined schemas. It provides type checking and normalization rules out of the box, has no dependencies, and supports custom validation rules.

## Use cases
- validate  payloads against a schema in python
- validate dictionaries with type checking
- normalize and sanitize incoming data
- define custom validation rules for documents
- validate config files before loading
- schema validation for python dicts without heavy dependencies

## When to choose
- you need dependency-free schema validation for python dictionaries
- you want simple, readable schema definitions with extensible custom rules
- you need data normalization alongside validation
- you're building APIs or processing untrusted dict-like input

## When to avoid
- you need pydantic-style typed models with IDE autocompletion and type hints
- you're validating complex nested objects rather than dictionaries
- you need async validation or high-performance bulk validation
- you want a library under very active development

## Facets
- artifact type: library
- maturity: maintenance
- function: serialization
- domain: data-science, developer-tools, apis
- platform: python, cross-platform
- tags: data-validation, schema-validation, dictionaries, normalization, no-dependencies

## Member repositories
- pyeve/cerberus (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:53.834960+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:22:50.716051+00:00, confidence not recorded.
  - readme: https://github.com/pyeve/cerberus (fetched 2026-08-28T04:07:53.834960+00:00, sha 426d167462fb)
  - homepage: http://python-cerberus.org (fetched 2026-08-29T09:37:27.679302+00:00, sha 838ecc3a69e9)
  - registry_pypi: https://pypi.org/pypi/cerberus/json (fetched 2026-08-29T09:37:27.689893+00:00, sha f4a90603c4a5)
- Data as of 2026-08-30T08:39:29.467469+00:00.