This project provides a modern, Vite-style development workflow for traditional mini-program development, enhancing developer experience (DX). It targets developers building WeChat and related mini-program projects, offering a unified monorepo structure and official scaffolding tools.

How It Works

weapp-vite adapts Vite's modern tooling, including its bundler and Hot Module Replacement (HMR), to mini-program environments. It employs a monorepo architecture managed by `pnpm` and `turbo` for efficient builds, CI, and validation. This approach replaces legacy workflows with a contemporary toolchain, enabling faster development cycles and improved developer productivity.

Quick Start & Requirements

• Primary install command: pnpm create weapp-vite (alternatively yarn create weapp-vite or npm create weapp-vite@latest).
• Local monorepo setup: pnpm install, pnpm build:pkgs, pnpm test.
• Prerequisites: pnpm is the primary package manager. No specific hardware or advanced software dependencies (like CUDA) are listed.
• Documentation: https://vite.icebreaker.top

Highlighted Details

• Official project scaffolder: create-weapp-vite.
• Monorepo structure includes core tooling (packages/, packages-runtime/), shared utilities (@weapp-core/), demo applications (apps/), starter templates (templates/), and CI/e2e fixtures (e2e-apps/).
• Extensive CI, HMR, IDE, and runtime validation powered by pnpm and turbo.
• Key packages include the main bundler (weapp-vite), MCP tooling (@weapp-vite/mcp), and WeChat DevTools CLI helpers (weapp-ide-cli).

Maintenance & Community

Contributions are welcomed via issues for bugs and feature requests, and pull requests for fixes, refactors, or new examples. Contribution details are available in `CONTRIBUTING.md`. No specific community channels like Discord or Slack are mentioned.

Licensing & Compatibility

Distributed under the MIT License. No explicit restrictions for commercial use or closed-source linking are noted.

Limitations & Caveats

The project focuses on "traditional mini-program development," which may imply limitations for highly non-standard or emerging platform features. Details on "AI-friendly tooling" and "MCP support" are sparse, warranting further investigation for adoption.