Project Info

Peter Parking

Inspiration

Driving uphill through many different colleges to look for parking spots is tiring and time-consuming. Being late to class solely due to parking isn't rare. We thought we should solve this problem that students from all backgrounds are currently facing.

What it does

Peter Parking shows available parking lots throughout the UCSC campus based on user interactions. People can report how many parking spots were available at a certain parking lot, and that information gets saved into our data storage and becomes available to view on the website.

How we built it

We used html, css, and js to build our website, and we used Flask to transfer user reports from the website to Python where the data gets stored.

Challenges we ran into

As a team of beginner coders, our biggest challenge was connecting the website (frontend) to our data storage (backend). We watched countless tutorials on YouTube and finally found our way to navigate through this using Flask, a program that works as a bridge between python codes and html/css/js.

Accomplishments we're proud of

We're proud of ourselves for starting with 0 and ending with a 1; we learned so many new assets by problem-solving real challenges we faced during development of Peter Parking.

What we learned

We learned the importance of prior planning, teamwork, dedication and strong mentality during day 1 of CruzHacks, as we were still lost on what idea to materialize until the very start of day 2. However we were able to gather and push ourselves toward our goal and finally made it happen.

What's next

Our first step for improving Peter Parking is adding a server so people can check the parking status on campus from anywhere. Next is making Peter Parking show the status for every single parking lot on campus, and last is adding motorcycle and bicycle parking lot supports.

Parking Map Project

Introduction

This interactive parking map is a web application that helps users find and report available parking spots. It integrates a Python Flask backend with a frontend using HTML, CSS, and JavaScript.

Features

Interactive map interface with clickable buttons for parking lots.
Dropdown menus displaying parking lot names and available spots.
User-reporting feature for updating parking availability.

Technology Stack

Backend: Python, Flask
Frontend: HTML, CSS, JavaScript

Installation and Setup

To run this project locally, follow these steps:

Prerequisites

Python 3.6 or higher
Flask

Installation

Clone the repository:
```
git clone [repository URL]
```
Navigate to the project directory:
```
cd [project-directory]
```
Install Flask and other dependencies:
```
pip install -r requirements.txt
```

Run the Flask App

Open a terminal or command prompt.
Navigate to the directory containing dict.py.
Start the Flask server:
```
python dict.py
```

Run the Frontend

You can access the application through the provided website URL(https://akdbsdud6.github.io/).

Connect Frontend to Backend

Ensure your frontend JavaScript fetch requests are pointed to your Flask server (e.g., http://localhost:5000/get_parking_data/Stevenson).

Usage

Navigate the map to view different parking lots.
Click on parking lot buttons to see details and availability.
Use the 'Report' feature to update the availability of parking spots.

Analysis

Compare with all teams

View

Metric

akdbsdud6
9

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

CSSIn code
FlaskIn code
HTMLIn code
PythonIn code
JavaScriptClaimed

4 of 5 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

28 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.