# QuipNetwork/xq-py

A python implementation of the Quip Network's quantum virtual machine

Repository: https://github.com/QuipNetwork/xq-py
Canonical: https://ross.abutalabs.com/products/xq-py
License Family: other
Last push: 2026-06-03T18:22:38+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 85, release rhythm 35, longevity 10
- inputs: {"age_days": 153, "days_push": 91, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5514, forks 14 (observed 2026-08-28T04:09:21.836840+00:00)

## What it is
A Python implementation of the Quip Network's quantum virtual machine, allowing users to simulate quantum programs locally. It serves as a software emulator of quantum hardware for the Quip Network ecosystem.

## Use cases
- simulate quantum circuits in python
- run quantum programs without quantum hardware
- test quantum algorithms locally
- emulate a quantum virtual machine
- develop quantum software for the quip network

## When to choose
- you want to simulate quantum workloads in Python without access to real quantum hardware
- you are developing or testing software targeting the Quip Network
- you need a lightweight local quantum VM emulator

## When to avoid
- you need actual quantum hardware execution
- you need a high-performance compiled quantum simulator outside the Python ecosystem
- you require a license-guaranteed usage model, as no license is specified

## Facets
- artifact type: library
- maturity: active
- function: simulation, sdk, developer-tools
- domain: quantum-computing, simulation, developer-tools
- platform: python, cross-platform
- tags: quantum-computing, quantum-virtual-machine, simulator, python

## Member repositories
- QuipNetwork/xq-py (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:21.836840+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 2026-08-29T17:56:14.311823+00:00, confidence not recorded.
  - readme: https://github.com/QuipNetwork/xq-py (fetched 2026-08-28T04:09:21.836840+00:00, sha fc2272324b31)
- Data as of 2026-08-30T08:39:29.467469+00:00.