A clean, minimal, and lightning-fast daily productivity app built with Streamlit.
DaySnap helps you focus only on today — no clutter, no overwhelm, just simple task planning that actually gets used.
“What’s the simplest way to plan my day right now?”
DaySnap is designed for:
- Students
- Freelancers
- Anyone who hates complex productivity apps
- Add tasks instantly (press Enter or click)
- Mark tasks as complete
- Delete tasks easily
- No categories, no tags, no distractions
- Tasks reset automatically every new day
- No manual cleanup needed
- Removes guilt from unfinished tasks
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Predefined habits:
- 🌅 Wake up early
- 🏃 Exercise
- 📚 Study
- 💧 Drink water
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Track daily consistency
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Tracks consecutive productive days
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Displays:
🔥 X Day Streak
-
Resets if you skip a day
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Shows task completion:
X/Y tasks completed
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Visual progress bar
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Motivational messages:
- “Good start 🚀”
- “Almost done 🔥”
- Minimal and distraction-free
- Mobile-friendly design
- Light & Dark mode toggle
- Smooth animations and modern styling
❌ Most productivity apps fail because they are:
- Too complex
- Too feature-heavy
- Feel like work
✅ DaySnap focuses on:
- Speed
- Simplicity
- Daily usability
- Python
- Streamlit
- JSON (for local data storage)
DaySnap/
│── app.py # Main application
│── daysnap_data.json # Local data storage
│── requirements.txt # Dependencies
│── .gitignore
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Uses local JSON file (
daysnap_data.json) -
Stores:
- Tasks
- Routine checklist
- Streak count
- Last active date
- Theme preference
- ⚡ Instant task creation
- 🔄 Automatic daily reset
- 🔥 Habit-forming streak system
- 📱 Mobile + Desktop friendly
- 🎨 Beautiful, modern UI
- ⏰ Time blocking
- 📅 Weekly view
- ☁️ Cloud sync (e.g., Firebase)
- 🔔 Notifications
- 🤖 AI-powered planning
Feel free to fork this project and improve it.
Ideas, suggestions, and improvements are welcome!
This project is open-source and available under the MIT License.
Built to solve a simple problem:
“Why are most productivity apps so complicated?”
DaySnap proves that simple tools get used more.
Built with ⚡ using Streamlit.
If you like this project, consider giving it a ⭐ on GitHub!