Introducing FlouState: A Revolutionary Way to Understand Your Coding Habits
Discover how I developed FlouState, a cutting-edge Visual Studio Code extension designed to provide deeper insights into your programming sessions—not just tracking how long you code, but revealing what you’re actually doing.
Explore FlouState Here: https://floustate.com
Download the Extension: FlouState on Visual Studio Marketplace
About FlouState
Traditional coding time trackers offer a mere sum of hours spent. However, they fall short in capturing the nature of the work—are you crafting new features, debugging issues, or familiarizing yourself with unfamiliar code? FlouState bridges this gap by categorizing your activities dynamically, providing actionable insights into your workflow.
Using advanced analysis techniques—including monitoring file change patterns, detecting debugging sessions, and applying language-specific heuristics—FlouState delivers a real-time breakdown of your coding types. Imagine combining the insights of WakaTime with intelligent work type detection, all without manual input.
Why It Matters
Understanding how you spend your coding hours is critical for productivity. A three-hour session might be entirely different depending on whether you’re actively building, debugging, or studying code. Conventional timers can’t distinguish these nuances, but FlouState aims to fill that void for developers seeking clarity.
Technological Foundations
- Frontend: Built with Next.js 14 and TypeScript, leveraging Supabase for authentication, real-time data, and database management, and styled with Tailwind CSS
- VS Code Extension: Developed using TypeScript and the VS Code Extension API
- Payment and Subscription: Managed via Stripe, ensuring a smooth user experience
- Privacy Considerations: Designed with user privacy at the forefront—your code content stays on your machine, with analytic processes occurring locally
Distinguishing Features
Unlike traditional trackers, FlouState’s intelligence comes from integrating multiple detection methods:
- Monitoring file edit patterns
- Identifying active debugging sessions
- Applying language-aware heuristics
- Analyzing activity streams in real time
These combined signals allow me to generate granular reports, like revealing that last week I dedicated approximately 45% of my time to feature development, 15% to refactoring, and a mere 2% to debugging—highlighting areas for potential productivity improvements.
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