Comparison of WeChat Mini‑Program Frameworks: WePY, Mpvue, Taro, Uni‑app, and Chameleon

Since the launch of WeChat Mini‑Program beta in 2016, demand for complex business development has grown, but native tools are limited (no CSS preprocessors, ES7+, project engineering, unified request or cache handling).

The article introduces five open‑source frameworks—WePY, Mpvue, Taro, Uni‑app and Chameleon—detailing their core features, CLI commands and sample code.

$ npm install @wepy/cli -g

$ wepy init standard myproj

# install vue-cli globally

$ npm install -g @vue/cli

# create uni‑app project

$ vue create -p dcloudio/uni-preset-vue my-project

# install Taro CLI

$ npm install -g @tarojs/cli

It then evaluates the frameworks on four criteria: business‑function coverage, integration cost (code migration and learning), project performance (package size, memory usage, page‑switch time, startup time, first‑render and subsequent‑render times), and maintainability (GitHub stars, community activity, open‑source degree).

Performance tables show native code has the smallest package, while Taro and Uni‑app achieve the best runtime metrics because they automatically diff data before calling setData , transmitting only changed fields.

Maintainability analysis reveals that although WePY and Mpvue have high star counts, their communities are inactive; Taro, Uni‑app and Chameleon have active forums and chat groups, but Uni‑app is only partially open‑source.

In conclusion, the article advises against using unmaintained frameworks (WePY, Mpvue) and recommends React‑oriented teams choose Taro, while Vue‑oriented teams can adopt Uni‑app or Chameleon based on their specific needs.