EverydayWechat — Automate WeChat Interactions with Custom Messages and Smart Replies
Overview
EverydayWechat is an open-source Python project that utilizes Itchat to automate WeChat interactions. It enables users to send custom messages to friends or groups on a schedule and provides smart auto-reply capabilities. The project also includes a group assistant feature that can perform various tasks like querying weather, movie box office, and more.
Key Features
- Automated daily message sending to friends or groups
- Smart auto-reply to WeChat messages
- Group assistant functionality for various queries
Use Cases
- Individuals who want to automate daily greetings or reminders to loved ones
- Groups that require a bot for automated responses and information retrieval
- Developers looking to integrate WeChat automation into their applications
Advantages
- Easy setup and operation, suitable for non-technical users
- Supports multiple functionalities like weather updates and movie box office queries
- Open-source, allowing for community contributions and customizations
Limitations / Considerations
- Relies on the web version of WeChat, which may have limitations or require specific login conditions
- May not be suitable for commercial use due to potential legal issues
- Requires Python 3.5+ and Itchat library
Similar / Related Projects
- Wechaty: A conversational SDK for WeChat, offering more extensive bot capabilities but with a steeper learning curve.
- Itchat: The underlying library used by EverydayWechat, providing basic functionalities for WeChat automation.
- WechatAddGroupHelper: A related project by the same author, focusing on adding groups in WeChat.
Basic Information
- GitHub: https://github.com/sfyc23/EverydayWechat
- Stars: 10,221
- License: MIT
- Last Commit: 2025-09-21
📊 Project Information
- Project Name: EverydayWechat
- GitHub URL: https://github.com/sfyc23/EverydayWechat
- Programming Language: Python
- ⭐ Stars: 10,221
- 🍴 Forks: 2,311
- 📅 Created: 2019-03-11
- 🔄 Last Updated: 2025-09-21
🏷️ Project Topics
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🔗 Related Resource Links
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This article is automatically generated by AI based on GitHub project information and README content analysis