Price Assist

Get the best price for your car

View Deployment · Report Bug

About the app

• Price Assist helps the users to get the best price for their used old cars in a matter of minutes.
• Our app makes use of the various specifications of your car like mileage, brand, kilometers driven, etc. to predict its most optimal selling price.
• If someone is interested to buy a second-hand vehicle, they will know whether the price offered by the seller is overpriced or not.

Design

• The app makes use of Material UI 5 for the beautiful UI components.
• All the icons are taken from Icons8 under its free-tier subscription and react-icons package.

About ReactJs

• React is a JavaScript-based UI development library.
• Facebook and an open-source developer community run it.
• Although React is a library rather than a language, it is widely used in web development.
• The library first appeared in May 2013 and is now one of the most commonly used frontend libraries for web development.
• React offers various extensions for entire application architectural support, such as Flux and React Native, beyond mere UI.

About Django

• Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design.
• Django was designed to help developers take applications from concept to completion as quickly as possible.
• Django takes security seriously and helps developers avoid many common security mistakes.
• Some of the busiest sites on the web leverage Django’s ability to quickly and flexibly scale.

About Sklearn

• Scikit-learn (Sklearn) is the most useful and robust library for machine learning in Python.
• It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction via a consistence interface in Python.
• This library is largely written in Python and is built upon NumPy, SciPy and Matplotlib.

Libraries and tools 🛠

React JS

JavaScript ES6

Firebase

Heroku

Material UI 5

Axios

Formik

Django

Python

Sklearn

Pandas

Numpy

Setup

• Fork and clone the repository locally.
• Navigate to the cloned folder

Frontend

1. Download the latest version of Node.js for your OS
2. Run npm install
3. Start the app npm run

Backend

1. Create Python Venv and download all the dependencies using requirements.txt (present in /backend)
2. Run python manage.py runserver on windows and python3 manage.py runserver

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement" or "feature". Don't forget to give the project a star!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This application is released under MIT License for fair use (see License).