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HardPick

HardPick is a web application designed to help you find the best computer within your budget. By leveraging the power of Python, Node.js, and Flask, HardPick ensures a seamless and efficient experience for users looking to make informed purchasing decisions.

Table of Contents

Features

  • User-Friendly Interface: Easy-to-navigate interface to input budget and preferences.
  • Real-Time Data: Fetches the latest computer hardware data.
  • Budget Optimization: Recommends the best computer configuration within your specified budget.
  • Multi-Platform: Accessible via desktop and mobile devices.

How it works:

The front-end web application is built using JavaScript. Users input their desired PC specifications and budget, which are then sent as a request to an API built with Flask. This API scrapes various sites in Tunisia that sell PCs, benchmarks the components by scraping other websites, and assigns a score to each component. Based on these scores, the application renders a final result, recommending the best computer configuration within the user's budget.

Installation

Prerequisites

  • Python 3.x
  • Node.js and npm
  • Flask
  • beautifulSoup

Steps

  1. Clone the repository:

    git clone https://github.com/Amine-Zitoun/hardpick.git
    cd hardpick
  2. Set up the backend:

    cd backend
    python3 -m venv venv
    source venv/bin/activate
    pip install -r requirements.txt
  3. Set up the frontend:

    cd ../frontend
    npm install
  4. Run the application:

    cd ../backend
    flask run
    cd ../frontend
    npm start

Usage

  1. Open your web browser and navigate to http://localhost:3000.
  2. Enter your budget and preferences.
  3. Get recommendations for the best computer configuration within your budget.

Technologies Used

  • Python: Backend processing and data handling.
  • Flask: Web framework for the backend.
  • Node.js: JavaScript runtime for the frontend development.
  • React: (or your chosen front-end framework) for building user interfaces.
  • APIs: For fetching real-time data on computer hardware.

Contributing

Contributions are welcome! Please fork this repository and submit a pull request for review.

  1. Fork the repository.
  2. Create a new branch:
    git checkout -b feature-branch
  3. Make your changes and commit them:
    git commit -m "Description of your changes"
  4. Push to the branch:
    git push origin feature-branch
  5. Submit a pull request.

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Web app designed to help you find the best computer within your budget.

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