Steps To Scrape Car Details From CARMAX

  • 16/12/2022

Steps To Scrape Car Details From CARMAX

The development of human civilization is based on the pillars of intelligence. The power of knowing things. Everything boils down to the wisest actions. And these actions result from omniscience, achieved by nothing else but information that translates into knowledge. In the modern world that breathes transactions, decisions are made every day. These decisions are based on ideas and data.

Be the decision of an ambitious purchase or a quality sale. Seeking omniscience is the way out for emerging as the most profitable. In the modern world, if high technology plays, information on various aspects is available on the internet. Available but only sometimes visible. Accessible but hard to find. In such an environment, web scraping comes into play. Data fragments from various sources are always available in an organized or unorganized format.

This data is bound together by the web scraping services USA to a more structured design and is technically overviewed for various commercial purposes. The best way to start exploring the world of web scraping is by accessing some of the most relevant APIs employed by webpages, which can be eventually converted into HTML structures. There are multiple advantages to the same, like:

  1. Reduced outlay: A lot of the data is unnecessary. Avoid the same to minimize the response time.
  2. Well organized: The API outlays ensure the scraped, in most instances, is well-organized JSON information.
  3. Intense Quantity: The API formats have a more extensive range and higher probability of conversion compared to what is received from the HTML

The Problem

As discussed, web scraping is a process that caters to the dimensions of a natural cycle of every action. To understand it simply, let's work with an example of scraping information for an automobile. Let's learn the steps to scrape car details from Carmax. Something we can learn through web scraping automotive industry data.

Purchasing a car is a big deal. And only some automobile enthusiasts have a deep understanding of all the intricate details that need to be considered while buying a car. One may need help finding the exact brief of information that they desire. Hence they look up an online portal that deals in second-hand cars, like CarMax. Here, the data points are the details on the mileage, prices, gear types, geographical availability, and more.

Let's divide this task to scrape car details from CARMAX. We begin with the conventional way, followed by the API that paves the way to a much simpler method.

The Conventional Method

Web scraping automotive industry data has multiple ways to be approached. To scrape car details from CARMAX and go ahead with the conventional set of procedures, one must look up and understand the Beautiful Soup parser and work up the browser through the dos of the given method. Now, proceed with inspecting the HTML from the CarMax search page with a particular code.


import requests

from bs4 import BeautifulSoup

def get_carmax_page_web():

    """Get data for a page of 20 vehicles from the CarMax website."""

    # request HTML content from search page

    headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36'}

    page_url = ''

    response = requests.get(page_url, headers=headers)


    # extract vehicle list from HTML

    html = response.content

    soup = BeautifulSoup(html)

    vehicles_raw ='div.vehicle-browse--result--info')


    # extract relevant data points from vehicles section of the HTML

    return [




            **{key: value for key, value in vehicle.attrs.items() if key != 'class'}


        for vehicle in vehicles_raw


Moving on to web scraping automotive industry data, there is a trinity of steps that need to be taken care of before proceeding. Please note that there will be a significant time required for the development of this system and execution.

  1. Request HTML: This task will consume around a couple of minutes.
  2. Outline the most necessary and relevant information from the given HTML: This task will consume around 0.8 seconds of execution.
  3. Parse the collected data: This task will consume the minimum time of execution however will consume a massive chunk of time for development.

The Better Way

There also exists a better way to scrape car details from CARMAX. Numerous programs will install code into the user session of your browser, and that code will send API calls to load data straight to your browser from another server. Fortunately for researchers, most contemporary browsers let you easily keep an eye on these requests.

By launching the web designer console in Firefox and tapping the network tab, you can keep track of XHR requests. Again when the website has loaded, we can view each request that was made and the responses that were provided. Not to mention the web scraping services USA have come up with quite advanced tools and methods, especially when the context is automobile website scrape.

To proceed, you can point to the request that will be visible here. When we examine the JSON response, we find a Results value, and the associated response is a list of automobile models that looks like:


  {'AverageRating': 4.833,

    'Cylinders': 6,

    'Description': '2015 Acura RDX AWD',

    'DriveTrain': '4WD',

    'EngineSize': '3.5L',

    'ExteriorColor': 'Black',

    'Highlights': '4WD/AWD, Leather Seats, ...',


  {'AverageRating': 4.833,

    'Cylinders': 6,

    'Description': '2015 Acura RDX AWD',

    'DriveTrain': '4WD',

    'EngineSize': '3.5L',

    'ExteriorColor': 'Brown',

    'Highlights': 'Technology Package, Power Liftgate, ...',





Everything we must do in order to retrieve this pre-parsed information programmatically is to mimic the request performed by our browser - here's how to accomplish that in Python

def get_carmax_page_api():

    """Get data for a page of 20 vehicles from the CarMax API."""

    # make a GET request to the vehicles endpoint

    page_url = ''

    response = requests.get(page_url)


    # get JSON from requests and return the results subsection

    return response.json()['Results']

Since the output is already formatted for us, this code is considerably more compact. We no longer have to locate individual information points from a vast chunk of unorganized text.

To summarize, while executing things intelligently, discovering standard yet concealed APIs via our browser to scrape data rather than parsing HTML - we are capable of reducing execution time by roughly 90%, considerable development time, and acquiring more data per car. Always look for the best web scraping services USA for web scraping automotive industry data.

If you need web scraping services to scrape car details from Carmax, feel free to contact Botscraper. Our intelligent web scraper provides 100% risk free, fast & accurate data extraction, from Carmax. So, what are you waiting for? Get in touch today!

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