# x-hw/amazing-qr

💮 amazing QRCode generator in Python (supporting animated gif) - Python amazing 二维码生成器（支持 gif 动态图片二维码）

Repository: https://github.com/x-hw/amazing-qr
Canonical: https://ross.abutalabs.com/products/amazing-qr
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: qrcode, gif, amazing, picture, qr-code, qrcode-generator
Last push: 2026-08-25T14:11:47+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 100
- inputs: {"age_days": 3660, "days_push": 8, "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 10805, forks 1574 (observed 2026-08-28T04:10:44.362847+00:00)

## What it is
A Python library and CLI tool (amzqr) that generates QR codes, including artistic black-and-white or colorized QR codes merged with pictures and animated GIF QR codes. It supports version, error-correction level, contrast, and brightness options.

## Use cases
- generate a qr code in python
- create an animated gif qr code
- make a qr code with a background picture
- generate artistic colorized qr codes
- qr code generator command line tool

## When to choose
- you need QR codes embedded in static images or animated GIFs
- you want a simple pip-installable Python API or CLI for QR generation
- you need artistic or colorized QR codes

## When to avoid
- you need to decode or scan QR codes rather than generate them
- you need QR codes with logos placed precisely or advanced styling frameworks
- you need a non-Python environment

## Facets
- artifact type: library
- maturity: active
- function: image-processing, cli, data-generation
- domain: developer-tools, graphics, media
- platform: python, cli, cross-platform, windows
- tags: qrcode, gif, animated-qrcode, artistic-qrcode, image-embedding, linux, macos

## Member repositories
- x-hw/amazing-qr (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:44.362847+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 2026-08-29T17:17:41.703600+00:00, confidence not recorded.
  - readme: https://github.com/x-hw/amazing-qr (fetched 2026-08-28T04:10:44.362847+00:00, sha 552632590229)
- Data as of 2026-08-30T08:39:29.467469+00:00.