https://github.com/justin-pyne/pomo-collab

A collaborative Pomodoro Timer web application, designed to facilitate focused work sessions with synchronized breaks. Built with HTML, CSS, and a blend of Python (Flask) & JavaScript.
https://github.com/justin-pyne/pomo-collab

bootstrap css docker flask html javascript python3 socketio

Last synced: 6 days ago
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A collaborative Pomodoro Timer web application, designed to facilitate focused work sessions with synchronized breaks. Built with HTML, CSS, and a blend of Python (Flask) & JavaScript.

• Host: GitHub
• URL: https://github.com/justin-pyne/pomo-collab
• Owner: justin-pyne
• Created: 2023-09-04T18:30:59.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-20T22:41:57.000Z (over 1 year ago)
• Last Synced: 2023-09-21T11:40:27.799Z (over 1 year ago)
• Topics: bootstrap, css, docker, flask, html, javascript, python3, socketio
• Language: Python
• Homepage:
• Size: 328 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# pomo-collab

A web-based Pomodoro timer designed to help users maintain productivity by using the Pomodoro technique. It employs the concept of 25-minute focused work sessions, followed by 5-minute breaks. After four such intervals, a longer break is taken. The application offers the potential for synchronized timer sessions, allowing friends or colleagues to work together in harmony.

## Features:

- Synchronized Timer: Invite friends to the same timer session to keep everyone on the same schedule.

- Pause & Reset: Any party can pause the timer or reset it to start afresh.

- Session Tracker: Keep track of completed work sessions to monitor productivity.

- Alerts: Notifications to inform the user when a session ends and a break begins.

## Technologies Used:

- Frontend: HTML, CSS, and JavaScript.

- Backend: Python (Flask)

## How to Run:

1. Clone the repository:

   - git clone pomo-collab

2. Navigate to the project directory:

   - cd pomo-collab

3. Install required packages:

   - pip install -r requirements.txt

4. Launch the docker containers:

   - docker-compose build

   - docker-compose up

5. Run the application:

   - python app.py

6. Open a web browser and navigate to http://127.0.0.1:5000/ to view the application.