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OLX Price Search

Description

This project is a web scraper that searches and compares product prices on OLX, presenting the results in a user-friendly web interface.

Features

• Product search by name
• Display of maximum, minimum, and average price
• List of ads with direct links
• Interactive web interface using Gradio

Running with Docker Compose

You can also run the project using Docker Compose. Follow the steps below:

1. Make sure you have Docker and Docker Compose installed on your machine.
2. Navigate to the project directory:

   cd OLX-Price-Search

3. Build and start the containers:

   docker-compose up --build

4. After the build completes, run:

   docker-compose up -d

5. Access the address http://localhost:7878/

Technologies Used

• Python
• Selenium
• Gradio
• Docker
• Chrome Webdriver

How to Use

1. Clone the repository:

   git clone https://github.com/alex-des-santos/OLX-Price-Search.git

2. Navigate to the project directory:

   cd OLX-Price-Search

3. Install the dependencies:

   pip install -r requirements.txt

4. Run the main script:

   python main.py

5. Access the address http://localhost:7878/

Contributing

1. Fork the project
2. Create a branch for your feature:

   git checkout -b my-feature

3. Commit your changes:

   git commit -m 'My new feature'

4. Push to the remote repository:

   git push origin my-feature

5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Limitations and Future Improvements

• Error Handling: The scraper could be improved with more robust error handling to gracefully manage situations like network issues or changes in OLX's website structure.
• Scalability: Currently, the scraper might not be optimized for handling a very large number of searches concurrently. Future improvements could focus on improving scalability and performance.
• Data Persistence: Consider adding a mechanism to persist scraped data for offline access or analysis.
• Advanced Search Options: Expanding search capabilities to include filters (e.g., price range, location) would enhance the user experience.