Viper Tracking is a local-first, privacy-focused desktop activity tracking tool designed for deep self-analysis, productivity evaluation, and time auditing. Built with performance-by-design and full user customizability in mind, it gives you full control over what is tracked, how it's labeled, and how it's analyzed - without compromising your data privacy.
- Why should I use ViperTracking instead of XYZ?
- Simple Explanation
- Roadmap
- Key Features
- Feature Showcase
- Design Philosophy
- Architecture & Technologies
- Use Cases
- Installation
- Privacy & Security
- License & Contribution
- Why I Built This
- Numbers
- Devlog
- Contact
Simple. You are in full control of everything that happens here.
I built this with intention and love. "Working" is never good enough for me.
I keep improving it, so we can better understand how we spend our time and learn from it.
Whether it's projects, tickets, or just your daily screen routine,
Viper Tracking helps you track it all in a way that works for you.
This README, the devlog, and the roadmap aren’t built for everyone to fully understand.
And that’s okay, even I can’t always grasp everything I’ve done here. I just kept going, step by step.
If you feel lost while reading, that’s completely fine.
I’m not the best explainer, but I’ve tried to be honest, open, and structured throughout these docs.
Please don’t think you’re worse or “not technical enough” if something seems confusing.
We just walked different paths. This was mine — one line of code after another,
often without knowing what the next step would be.
(And yes, sometimes I re-read my own docs to remember what I actually built 😄)
This tool is not yet available as a ready-to-run installer.
But don't worry everything is coming together quickly.
Check out the ViperTracking Roadmap
to see what's already built, what's being worked on right now,
and what's coming next.
- Track window focus and user input in 5-second intervals
- Fully offline and privacy-preserving - no external communication, no webinterface
- Dynamic labeling system (manual or conditional by AND/OR logic)
- Modular GUI built with ttkbootstrap and custom widgets
- Interactive GUI to create filters for timeframes with unlimited add/subtract logic
- Dynamic visualizations showing activity levels, app usage over time, extra app-based and label-based timelines.
All fully interactive and filterable - Auto-aggregation of low-percentage data in charts
- Multi-threaded architecture: input tracking, system tray, DB access and GUI
- System tray controls for quick label entry and GUI launch
- Keyboard-friendly UX with clean theming, custom style manager
- SQLite database with normalized structure and flexible query system
Curious what ViperTracking looks like in action?
Check out the current feature showcase → Showcase
It’s a visual tour with images and GIFs highlighting core features, UI flows, and work-in-progress elements.
This page will be updated continuously as new visual features and improvements roll out.
- Privacy by Design: No keystroke logging, only filtered activity tracking; no data leaves your machine.
- Performance by Design: Runs on low-end hardware, minimal resource usage, efficient data handling.
- Visibility by Choice: User can fully configure what’s tracked, labeled, or shown.
- Documentation for All: Code is fully documented, even for beginners. Tracking logic is transparent and explainable.
- Languages / Frameworks: Python 3.9+, tkinter, ttkbootstrap, Matplotlib, Pandas, Pystray
- Database: SQLite3 (normalized schema with selective JSON usage)
- Concurrency: Native
threading(input tracking, GUI, DB thread) - Logging: Extended
loggingmodule - Config system: Fully custom-made with distinction between static configs and editable settings
- Custom UI Toolkit: Features in-development components from Ouroboros UIX, an upcoming open-source UI framework.
The need for a better UIX architecture became clear through ViperTracking itself,
this project marks the starting point of its development, and selected elements will be extended
and extracted into the framework later on.
Platform: Windows-only (tested on Windows 11, likely compatible with Windows 10)
- Track your daily time spent on applications
- Analyze patterns in productivity and distraction
- Filter specific time ranges, app types, activities, or combinations
- Tag and analyze project work with custom labels (e.g., "Ticket #12345")
- Search what you watched or worked on weeks ago using keywords
- Set parental controls and restrict settings via PIN
- Optional: ignore sensitive categories (e.g., private browsing or specific keywords)
Note: Pre-Beta versions require manual setup.
It is recommended to run the project inside your IDE during development.
After the Open Beta, a user-friendly installer will be available for regular use.
- Clone the repository:
git clone https://github.com/sora7672/viper_tracking.git
- Install dependencies:
pip install -r requirements.txt
- Run the application:
python main.py
A one-click installer (with optional autostart service) and portable version will be provided in the Open Beta.
- 100% local execution — no server, no telemetry, no remote logging
- Keystrokes are not logged, only categorized (e.g., "gaming keys", "arrow keys")
- In short: your data will always remain your data. The only exception is if you choose to provide logs for error reporting.
- See tracking_logic.py for clear, beginner-friendly documentation of the tracking logic, even understandable for non-technical users.
- Open Source – non-commercial use only
- You may learn from and reference the code, but commercial reuse is prohibited
- Contributions may be accepted after Beta release
- A bug report form will be provided via GitHub Pages. Alternatively, feel free to open an issue directly in this repository.
Originally, ViperTracking began as a small exercise to learn MongoDB,
but it quickly evolved into a deeply personal project. As someone with ADHD,
I often struggled to measure time realistically and wanted a tool that helped me see clearly how I use my computer,
no assumptions, just data.
Over time, it became my portfolio foundation, my first real architecture,
and something I hope can motivate others to pursue their own ideas.
I’ve overcome thread deadlocks, architectural rewrites, and even phases of depression and self-doubt.
This project isn’t just about code — it’s about perseverance, learning through doing,
and building something that actually helps people understand themselves better.
Some geeky context for what went into this (as of 1st May 2025):
- 1100+ hours of code, testing, and architecture
- 250–350 hours of thinking through problems offline
- 270.000 characters of pure code
- That’s roughly 150 pages in a printed book
- 138.000 characters of internal documentation
- 7 months until presentation milestone
- 6 full weeks without a single line of code
- Regular weeks of 70+ hours of focused coding
- In just 8 days, I wrote 2 new systems to prevent deep TTK/Tkinter errors
- ~1500 lines, added to a project that had previously just hit 11.000 lines total
Want to follow the development journey in more depth?
The Devlog is not just about features and architecture.
It became something else along the way:
a personal log, a reflection space, and a voice for those who struggle while building,
learning, or just trying to keep going.
This started as a project and became my journey.
Built in chaos, shaped by pressure, and written to be honest.
It shows how I found my way in this world.
If you want to get in touch, ask questions, or suggest features:
Discord: sora_7672
Feel free to reach out!
Just one thing: if your first message is just "hi" or doesn't include a reason, I probably won't reply.
Be clear from the start. That helps me keep things efficient and spam-free 😊
Always take one step at a time.
Even if it is a step back, you still learn something from it.
Every line of code you write can help someone in the future if you give it your best today.
Thanks for reading!
Sora_7672