# schematics/schematics

Python Data Structures for Humans™.

Repository: https://github.com/schematics/schematics
Canonical: https://ross.abutalabs.com/products/schematics
Homepage: http://schematics.readthedocs.org/
Language: Python
License: NOASSERTION
License Family: other
Topics: python, validation, datastructures, types, schema, serialization, deserialization
Last push: 2023-07-12T06:21:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 5729, "days_push": 1148, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2587, forks 294 (observed 2026-08-28T04:07:02.740260+00:00)

## What it is
Schematics is a Python library for defining typed data structures, validating them, and converting data between formats like JSON or MsgPack. It provides ORM-like type systems without any database layer, making it suitable for API input validation and message format definitions.

## Use cases
- validate api request payloads in python
- serialize and deserialize data to  or msgpack
- define typed data structures for rpc message formats
- convert raw dicts into validated model objects
- strip fields from data based on user access rights
- document and enforce data schemas without a database

## When to avoid
- you need an ORM with actual database integration
- you prefer actively developed alternatives like pydantic or marshmallow
- you need cutting-edge Python version support, as the project sees limited maintenance

## Facets
- artifact type: library
- maturity: maintenance
- function: serialization, form-handling, type-system
- domain: data-science, developer-tools, apis
- platform: python
- tags: data-structures, schema, deserialization, data-validation

## Member repositories
- schematics/schematics (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:02.740260+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 2026-08-30T02:22:25.413040+00:00, confidence not recorded.
  - readme: https://github.com/schematics/schematics (fetched 2026-08-28T04:07:02.740260+00:00, sha c8acc9f266de)
  - registry_pypi: https://pypi.org/pypi/schematics/json (fetched 2026-08-29T10:05:19.007276+00:00, sha 1a93299e2ad6)
- Data as of 2026-08-30T08:39:29.467469+00:00.