Inspiration
Our team started by discussing the various productivity apps and tricks we use to help us study and manage time, such as using a bullet journal or Notion. A common issue we found is that many of them are customizable to the user, but at the cost of becoming fussy and high maintenance. The simple act of deciding which assignments to prioritize becomes overwhelming, which is especially harmful and stressful to people who struggle with decision making. With this in mind, we created a time management app that requires as little user input as possible. We want Syllabyte to feel like an aid and never a chore!
What it does
Syllabyte is a web app that allows the user to upload their syllabi for the semester. It then creates a personalized timetable including all deadlines and reminders for suggested start dates. The start dates are calculated based on user preference, deadline proximity, and assignment difficulty/weight.
How we built it
We used React to build our website and Django to connect our front-end calendar with the back-end. On the back-end, we used Python to scan in the uploaded syllabus pdfs, parse and create a database of assignments, and use our decision-making algorithm to determine suggested start dates.
Challenges we ran into
We didn't realize that parsing pdfs is actually difficult! We tried various APIs and libraries, but ran into many errors. The format of each syllabus differs as well, so we realized later that spatial information matters almost as much as textual. We also were unable to implement some desired features, such as Cloud integration and email reminders, due to time. Overall, we had a lot of big ideas, but creating a full stack application from scratch in 24 hours was challenging for us!
Accomplishments that we're proud of
We were happy to discover that our decision-making algorithm did not require complex math for optimization and actually gave reasonable deadlines. We were also able to parse our pdfs using a Python library, which gave us decent results from a pool of syllabi we collected. Finally, we're really proud of our idea, and it's something that we hope to work on and continue improving in the future!
What we learned
We learned a lot about pdf and image parsing, especially about the Google Cloud Document AI API, which we unfortunately weren't able to use in time for this hackathon. This hackathon was also a crash course for some of us in React. We also discovered the GitHub Copilot extension on VSCode, which autocompletes your code and sometimes even improves it!
What's next for Syllabyte
In the future, we hope to improve our website, integrate users' timetables with Google Calendar, and start creating a mobile version. We also want to look into using image parsing rather than text for the syllabi pdfs and improve our optimization algorithm using ML.
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