Luffy,screenlock pmodoro.

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  This is how our project looks when started

1. Why I Built Luffy Screen Pomodoro

While working on B.Tech assignments and practicing LeetCode, I frequently lost focus by switching to YouTube, games, or other distracting applications. Traditional Pomodoro and focus tools were easy to ignore and did not provide strong enforcement.

Luffy Screen Pomodoro was built to enforce focus sessions by physically blocking distractions at the system level, making it impossible to bypass a session once it begins.

1. What I Built

Luffy Screen Pomodoro is a Windows-based focus enforcement tool with a web interface. I started from an existing distraction blocker and redesigned both the architecture and user interface.

A Flask backend to manage focus sessions

System-level application and website locking using Windows administrator privileges

Mouse and keyboard control using PyAutoGUI and Pynput

Fullscreen lock mode to prevent task switching

A modern glassmorphism UI built with Tailwind CSS and animated effects

The setup process is intentionally simple:

cd Luffy python webapp.py

1. Challenges Faced

Mouse and keyboard locking required elevated permissions and extensive path debugging

Executable paths for applications such as Chrome and Notepad failed due to spacing and quotation issues

Dependency conflicts caused missing audio modules after package upgrades

Debugging a hybrid Flask and desktop automation system required significant trial and error

1. Key Accomplishments

Reliable full-screen locking with no Alt+Tab or task-switch escape

Successful trapping of applications such as Chrome, Notepad, and CodeChef

A polished and modern UI with glassmorphism and particle effects

A stable two-step setup suitable for public release and portfolio use

1. What I Learned

Low-level Windows automation using PyAutoGUI and Pynput

Advanced Tailwind CSS techniques and animated interface design

PowerShell scripting for bulk file and path fixes

Debugging and maintaining hybrid web–desktop applications

1. Future Improvements

Machine learning–based focus prediction using user activity patterns

Cross-platform support for Linux and macOS

Cloud synchronization and productivity leaderboards

A companion mobile application

Built With

• api
• css
• flask
• html
• javascript
• powershell
• pyautogui
• pygame
• pynput
• python
• tailwind