📚 Learning Sprint Manager

A FastAPI + Alpine.js single-page app for running learning tracks with sprint planning, review boards, deadlines, spaced repetition, and revision history.

✨ Features

• Full SPA dashboard for creating tracks, filtering lanes, completing reviews, and logging study sessions without page reloads.
• Learning tracks with sprint focus, difficulty, weekly target hours, deadlines, progress, mastery score, and streak tracking.
• Spaced repetition workflow powered by review intervals and auto-generated review board cards.
• Review board with due, overdue, and upcoming cards plus one-click completion paths (strong, solid, wobbly).
• Revision history feed with session type, duration, confidence score, result, and scheduled next review snapshot.
• Lane pulse map for grouped progress and mastery visibility across backend, frontend, platform, AI, career, and algorithms tracks.
• Background scheduler that keeps due review cards in sync for active tracks.
• Render-ready deployment via render.yaml with demo data seeded on start.

📱 Responsive Support

This dashboard is optimized for desktop screens.

• Desktop: full support
• Tablet (landscape): full support
• Tablet (portrait): partial support
• Mobile: limited support

Some wide data tables require horizontal scrolling on smaller screens. For the best experience, use desktop or tablet in landscape mode.

🔌 API Endpoints

Method	Endpoint	Description
GET	/api/snapshot	Full dashboard payload (stats, tracks, review board, revision history, lane map)
POST	/api/tracks	Create learning track
PATCH	/api/tracks/{track_id}/toggle-active	Pause or reactivate track
DELETE	/api/tracks/{track_id}	Delete track with related sessions and review cards
POST	/api/tracks/{track_id}/quick-review	Log a quick revision session for a track
POST	/api/reviews/sync-due	Generate due review cards for active tracks
POST	/api/reviews/{review_id}/complete	Complete a review board card and log revision data
GET	/health	Health check

⚙️ Local Run

cd python-fastapi-learning-sprint-manager
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload

Open:

• UI: http://127.0.0.1:8000
• API docs: http://127.0.0.1:8000/docs

🧪 Local Demo Data

Seed a realistic local dataset (tracks, revision history, review cards):

cd python-fastapi-learning-sprint-manager
.venv/bin/python scripts/seed_demo.py

Reset local demo data:

cd python-fastapi-learning-sprint-manager
.venv/bin/python scripts/reset_demo.py

☁️ Deploy on Render

render.yaml is included in the repository. You can deploy directly from this config.