Web Scraping Developer Needed to Extract data from Realtor Site

Description

1. Job Description:
We are looking for an experienced web scraper to help us collect property listings from a real estate website. The task is to scrape all on-sale properties within California from the specified realtor site and export the listings into CSV format. This project must be completed by February 1st.
2. Requirements:- Develop a Python-based scraper that can extract property details such as: - Property name - Price - Location (City, ZIP code) - Square footage - Number of bedrooms and bathrooms - Other relevant property details (e.g., listing date, property type)
- Ensure the scraper can handle pagination and capture all available listings.- The scraped data should be exported to a CSV file for each property listing.- The scraper should be designed in a way that it can be rerun for future data extraction.
3. Budget: $400
4. Deadline: February 1st, 2025
5. Skills Required:- Web scraping (Python, BeautifulSoup, Selenium, or Scrapy)- Knowledge of handling realtor site and bypassing common scraping restrictions (if necessary)- Experience exporting data to CSV files- Ability to deliver the script and CSV files within the given timeline
6. Additional Information:- The property listings should only include on-sale properties located in California.- You will need to communicate any additional requirements (e.g., specific site restrictions or challenges) and provide regular updates on the progress.- If you have any specific experience scraping real estate websites, please mention it in your proposal.
7. To Apply:Please send a message outlining your experience with web scraping, your approach to this task, and examples of similar projects you’ve worked on. Feel free to ask any questions about the job or provide suggestions on how you can ensure the project’s success.