An end-to-end Django project that utilizes web scraping techniques to gather data from an e-commerce website and employs a recommendation system. Users can log in to discover personalized product recommendations based on their preferences. This project showcases the integration of Django with machine learning for an enhanced e-commerce experience
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
To run this software, you need to have Python installed on your computer.
1. Clone the repo
git clone https://github.com/miracyuzakli/ecommerce-scraper-recommendation-django.git
2. Go into the project
cd ecommerce-scraper-recommendation-django
3. Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # Linux or macOS
# venv\Scripts\activate # Windows
4. Install required packages
pip install -r requirements.txt
5. Apply database migrations and run the server
python manage.py migrate
python manage.py runserver
6. Load product data
python manage.py loaddata fixtures/products_data.json
7. Run the server again
python manage.py runserver
This project is open source and we welcome your contributions. If you'd like to contribute, feel free to fork the repository and submit pull requests.