pyautogui — Cross-platform GUI automation for Python
Overview
PyAutoGUI is a user-friendly, cross-platform GUI automation Python module that allows for programmatic control of the mouse and keyboard. It is designed to be accessible for human beings, making it easy to automate repetitive tasks without the need for complex setup or configuration.
Key Features
- Cross-platform compatibility (Windows, macOS, Linux)
 - Mouse and keyboard control functions
 - Screenshot and image-related features using Pillow
 - Display message boxes for user interaction
 
Use Cases
- Automating repetitive tasks on the computer
 - Creating custom scripts for testing or demonstration purposes
 - Automating administrative tasks in software applications
 - Developing interactive tutorials or demonstrations
 
Advantages
- Easy to install and use, with no external dependencies on Windows
 - Supports both Python 2 and 3
 - Comprehensive documentation and community support
 
Limitations / Considerations
- Limited to the primary monitor in multi-monitor setups
 - All keyboard presses are sent to the currently focused window
 - May require additional libraries for full functionality on Linux and macOS
 
Similar / Related Projects
- AutoIt: A Windows-specific scripting language for automating the Windows GUI, differing in that it is not cross-platform.
 - SikuliX: An open-source automation tool that uses image recognition to automate GUI interactions, differing in its approach to automation.
 - Robot Framework: A generic automation framework that can be used for acceptance testing and process automation, differing in its broader scope and support for various libraries.
 
Basic Information
- GitHub: https://github.com/asweigart/pyautogui
 - Stars: 11,861
 - License: Unknown
 - Last Commit: 2025-09-12
 
📊 Project Information
- Project Name: pyautogui
 - GitHub URL: https://github.com/asweigart/pyautogui
 - Programming Language: Python
 - ⭐ Stars: 11,861
 - 🍴 Forks: 1,365
 - 📅 Created: 2014-07-17
 - 🔄 Last Updated: 2025-09-12
 
🏷️ Project Topics
Topics: [, ]
This article is automatically generated by AI based on GitHub project information and README content analysis