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  • What data can I scrape from Cars.com for car listings using Python?

    Posted by Alheri Mien on 12/19/2024 at 12:05 pm

    Scraping car listings from Cars.com using Python can help you extract important details like car models, prices, locations, and mileage. Python’s requests library allows you to fetch the page content, while BeautifulSoup can parse the HTML and extract the desired data. By targeting the structure of Cars.com pages, such as the divs or classes associated with car listings, you can efficiently retrieve the required information. This process involves sending a GET request to the website, loading the HTML content into BeautifulSoup, and using tags to find specific data points. Below is an example of how to scrape car data from Cars.com.

    import requests
    from bs4 import BeautifulSoup
    # Target URL for Cars.com listings
    url = "https://www.cars.com/shopping/results/"
    headers = {
        "User-Agent": "Mozilla/5.0"
    }
    # Fetch the page content
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        soup = BeautifulSoup(response.content, "html.parser")
        cars = soup.find_all("div", class_="vehicle-card")
        for car in cars:
            name = car.find("h2", class_="title").text.strip() if car.find("h2", class_="title") else "Name not available"
            price = car.find("span", class_="primary-price").text.strip() if car.find("span", class_="primary-price") else "Price not available"
            mileage = car.find("div", class_="mileage").text.strip() if car.find("div", class_="mileage") else "Mileage not available"
            print(f"Name: {name}, Price: {price}, Mileage: {mileage}")
    else:
        print("Failed to fetch the Cars.com page.")
    

    This Python script sends an HTTP request to Cars.com, retrieves the page’s content, and parses it to extract car details such as name, price, and mileage. For dynamic content, tools like Selenium can be used to handle JavaScript rendering. To ensure the scraper collects data from all pages, you can implement pagination logic to iterate through additional listings. Storing the scraped data in a structured format such as a CSV or database allows for further analysis.

    Agathi Toviyya replied 2 days, 16 hours ago 2 Members · 1 Reply
  • 1 Reply
  • Agathi Toviyya

    Member
    12/20/2024 at 7:40 am

    Adding pagination support would significantly improve the scraper’s functionality. Cars.com often displays a limited number of car listings per page, and navigating through multiple pages ensures a more comprehensive dataset. By identifying the “Next” button or pagination links, the scraper can loop through all available pages and collect more listings. Random delays between requests reduce the chances of being flagged by anti-scraping systems. Pagination handling is an essential feature for scraping larger datasets.

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