Inspiration
We recently got bikes, and since then we've been obsessed with finding the best routes and parks to bike in. We also suffered repairing many parts, so we wanted to make it easier for everyone.
What it does
route recommendations, show bikeracks, and other things, bike fixing giudance...
How we built it
We built URBike using:
Python (98.2%) as the primary language, supplemented with other tools like JavaScript (0.9%), C (0.5%), and Cython. Flask for the backend to handle routes and application logic. HTML/CSS for the front-end elements, ensuring a user-friendly experience. APIs and Maps Integration to provide geolocation for route recommendations and bike rack locations. Used virtual environments (Venv) for dependency management.
Challenges we ran into
nsuring accurate integration of geolocation APIs for bike routes and racks. Designing a seamless user experience across different devices. Handling database optimizations for performance under real-time queries.
Accomplishments that we're proud of
Deploying a functional Flask application. Integrating map services for location-based features. Creating a modular architecture to enable future scalability.
What we learned
Leveraging Flask to build robust web applications. Importance of modular programming for future enhancements. Best practices in managing dependencies and virtual environments.
What's next for URBike
Expand the bike rack database with more accurate location data. Enhance route recommendations with user feedback and machine learning. Add a bike repair scheduling feature for users. Deploy the project for mobile platforms.
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