syllabusCalendarExport

A full-stack web application that parses syllabus PDFs, extracts key academic events (assignments, exams, deadlines), and converts them into calendar-ready formats. Users can review and edit extracted events before exporting to .ics for seamless integration with Google Calendar or iOS.

📅 Syllabus Calendar Extractor

A full-stack web application that converts course syllabus PDFs into structured calendar events.

Upload a syllabus, automatically extract important dates (assignments, exams, deadlines), review and edit them, and export to an .ics file for seamless import into Google Calendar or Apple Calendar.

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🚀 Features

• 📄 Upload syllabus PDFs
• 🧠 Extract key academic events (assignments, exams, deadlines)
• ✏️ Editable review table before export
• 📆 Export events as .ics (compatible with Google Calendar, Apple Calendar, Outlook)
• 🔍 Confidence scoring + source snippets for transparency

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Tech Stack

Frontend

• Next.js (App Router)
• TypeScript
• Tailwind CSS

Backend

• FastAPI (Python)
• PyMuPDF (PDF text extraction)
• Regex-based parsing (initial version)
• iCalendar (.ics) generation

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📂 Project Structure

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syllabus-calendar-extractor/
├── frontend/          # Next.js app
│   ├── app/
│   ├── components/
│   └── lib/
├── parser-service/    # FastAPI backend
│   ├── main.py
│   ├── sample_parser.py
│   └── requirements.txt

Setup

1. Clone the repo

git clone https://github.com/yourusername/syllabus-calendar-extractor.git
cd syllabus-calendar-extractor 

2. Frontend Setup

cd frontend
npm install
npm run dev

Will Run At: http://localhost:3000 (Copy and paste in browser)

3. Backend Setup

cd parser-service

# Create virtual environment (recommended)
python3 -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run server
python -m uvicorn main:app --reload

Will Run At: http://127.0.0.1:8000

How It Works

1.	User uploads a syllabus PDF
2.	Backend extracts text using PyMuPDF
3.	Parser identifies relevant lines (deadlines, exams, events)
4.	Dates are normalized into structured event objects
5.	Frontend displays an editable table
6.	User exports events as .ics

Current Limitations

•	Rule-based parser (may miss complex syllabus formats)
•	Limited time extraction accuracy
•	Some duplicate or noisy text may appear
•	English-only support

Future Improvements

•	NLP / LLM-based extraction for higher accuracy
•	Automatic semester/year detection
•	Table-aware parsing for structured syllabi
•	Google Calendar API integration
•	Improved deduplication and filtering
•	Better UI (bulk edits, tagging, filters)

Motivation

Students often spend time manually transferring syllabus deadlines into their calendars. This project automates that workflow, making it faster and less error-prone to stay organized throughout the semester.

Author

Juan Rizo