schematics/schematics
Python Data Structures for Humans™. observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 5729
- days_rel: n/a
- days_push: 1148
- n_releases_24m: 0
Adoption not part of the score
2587 stars · 294 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
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
library · maturity maintenance
serialization form-handling type-system data-science developer-tools apis python data-structures schema deserialization data-validation
2 sources
- readme: https://github.com/schematics/schematics · fetched 2026-08-28 · c8acc9f266de
- registry_pypi: https://pypi.org/pypi/schematics/json · fetched 2026-08-29 · 1a93299e2ad6
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| schematics/schematics | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="schematics/schematics")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem