This project generates a personalized study plan using your university timetable. You can fetch schedules from Everytime or upload XML files, analyze free periods, and use a neural network model to suggest weekly study priorities. A web interface lets you visualize and adjust the plan.
- Timetable import:
everytime.pyfetches an XML timetable from an Everytime share URL or loads a local file. - Timetable → Calendar:
every2cal.pylists free time slots and exports an.icscalendar. - Study plan generation:
models/study_plan_nn.pyassigns priorities based on subject importance, major relevance, and free time. - Web interface:
app.pyis a Flask server to input timetable data, view schedules, and retrain the model if needed.
- Install Python 3.8+ and required packages:
pip install flask torch requests icalendar python-dateutil
- Launch the web server:
python app.py
- Visit
http://localhost:5001in your browser to load a timetable and generate a study plan.
Convert a timetable directly to an .ics file:
python every2cal.py --id <EVERYTIME_ID> --begin 2024-03-02 --end 2024-06-20app.py– Flask application entry pointevery2cal.py– Converts timetable XML to.icsconvert.py– Parses XML and performs iCalendar conversionmodels/– Neural network (study_plan_nn.py) and saved model filestemplates/,static/– Web page templates and static resourcessubject_datas/– User-provided subject data storage