BRACU Gradesheet Analyzer is a privacy-focused academic dashboard for BRAC University students. Built with Streamlit, this tool enables advanced GPA analytics, course planning, simulation, and resource tracking — all in a sleek and intuitive interface.
🔗 Live App:
👉 https://bracu-gradesheet-analyzer.streamlit.app/
Designed with BRACU students in mind, the analyzer allows you to:
- 📥 Upload your official gradesheet (PDF)
- 📈 Track and simulate CGPA changes (add, retake, remove courses)
- 📊 View GPA and CGPA trends across semesters
- 🔓 See which core and COD (General Education) courses are unlocked
- 📚 Access course resources: PDFs, midterms, finals, links
- 🧠 Plan ahead using COD stream requirements and credit simulations
- 💡 Get course-specific visual insights and motivational quotes
| Category | Feature Description |
|---|---|
| 🧾 Gradesheet Upload | Securely upload and extract academic data from official BRACU transcripts |
| 🧮 GPA Calculator | Instant CGPA and credit calculation |
| 🔁 Course Simulation | Add, retake, and remove courses — see real-time CGPA impact |
| 🎯 CGPA Planner | Plan future semesters based on your CGPA goals |
| 📈 GPA Trends | Interactive line charts showing GPA & CGPA progression |
| 📘 Unlocked Courses | See all currently unlocked core and COD courses |
| 🧠 COD Stream Checker | Visualize COD stream coverage and get suggestions |
| 📚 Course Resources | Browse midterms, finals, links, folders for each course |
| ✅ Completed Breakdown | Categorized view of all completed courses by type |
| 🌟 Quote of the Hour | Random academic or nerd-themed motivational quote |
- Python 3.9+
- Streamlit — For the web UI
- Plotly — For interactive graphs
- PyMuPDF — For extracting data from transcripts
- Pandas — For processing and visualization
Follow these steps to set up and run the app on your local machine:
# Clone the repository
git clone https://github.com/xDhruboVai/BRACU-Gradesheet-Analyzer.git
cd BRACU-Gradesheet-Analyzer
# (Optional) Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install required dependencies
pip install -r requirements.txt
# Run the Streamlit app
streamlit run app.py
# The app will open at http://localhost:8501/
#At any point if it says x: command not found, use python -m rest of the command