FellowQ

A multi-user job queue manager for Python scripts, designed to run on a shared drive (e.g. D:) on Windows Server.

Features

• Add Python scripts (.py files) to a shared queue
• Live dashboard showing the currently running job, queued jobs, and completed jobs
• Move queued jobs up/down by setting a position number
• Kill the currently running job (with tracking of which user killed it)
• Start / resume queue processing
• Console output from each job is saved to a .msg file alongside the script
• No admin rights required to run

Requirements

• Python 3.8 or later
• Install Flask: pip install flask

Quick Start

1. Copy the FellowQ folder to your shared drive (e.g. D:\FellowQ).
2. Open a terminal (Command Prompt or PowerShell) and navigate to the folder:

   cd /d D:\FellowQ
   

3. Install Flask if you haven't already:

   pip install flask
   

4. Run FellowQ:

   python fellowq.py
   

5. Open the dashboard in your web browser:
   • On the same machine: http://localhost:5000
   • From another machine: http://<server-name>:5000

Usage

1. Set your username – Enter your name in the top-right field so the queue knows who added or killed each job.

2. Add jobs – Type the full path to a .py file and click Add. The script is added to the end of the queue.

3. Start the queue – Click Start Queue. FellowQ will begin executing queued jobs in order.

4. Monitor – The dashboard updates automatically every 2 seconds. The Currently Running section shows live console output from the active job.

5. Reorder jobs – Change the number next to any queued job and click Move to change its position.

6. Kill a job – Click Kill Current Job to stop the running job. The queue will not start the next job automatically (click Start Queue again when ready).

7. Completed jobs – Finished jobs appear in the Completed Jobs section with start/end times, exit status, and who added (and killed) them.

Files

File	Description
fellowq.py	Main application (Flask web server + job runner)
templates/index.html	Web dashboard
settings.json	Settings (e.g. port number and user badges)
queue.json	Persistent job queue (auto-created)
*.msg	Console output files, created next to each .py script

Notes

• FellowQ uses a single background thread to execute jobs one at a time.
• Console output is written to a .msg file in the same folder as the script (e.g. my_script.py → my_script.msg).
• The queue is persisted to queue.json, so it survives restarts.
• User badges in the header are loaded from settings.json (users list).
• Press Ctrl+C in the terminal to stop FellowQ.