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SerpApi profile image Artur Chukhrai
Artur Chukhrai for SerpApi

Posted on • Edited on • Originally published at serpapi.com

Scrape Google Product Online Sellers with Python

#webscraping #tutorial #python #programming

What will be scraped

wwbs-google-online-sellers

📌Note: In this image, I demonstrate that the data will be received with pagination. Therefore, I only show 5 sellers, and not all, as the image could take up a lot of space.

Full Code

If you don't need explanation, have a look at full code example in the online IDE.

import requests, json
from parsel import Selector


def get_online_sellers_results(url, headers):
    data = []

    while True:
        html = requests.get(url, headers=headers)
        selector = Selector(html.text)

        for result in selector.css('.sh-osd__offer-row'):
            name = result.css('.kjM2Bf::text, .b5ycib::text').get() 
            link = 'https://www.google.com' + result.css('.b5ycib::attr(href)').get() if result.css('.b5ycib') else None
            base_price = result.css('.fObmGc::text').get()
            shipping = result.css('.SuutWb tr:nth-child(2) td:nth-child(2)::text').get() 
            tax = result.css('.SuutWb tr:nth-child(3) td:nth-child(2)::text').get()
            total_price = result.css('.drzWO::text').get()

            data.append({
                'name': name,
                'link': link,
                'base_price': base_price,
                'additional_price': {
                    'shipping': shipping,
                    'tax': tax
                },
                'total_price': total_price
            })

        if 'Next' in selector.css('.R9e18b .internal-link::text').get():
            url = 'https://www.google.com' + selector.css('.R9e18b .internal-link::attr(data-url)').get()
        else:
            break

    return data


def main():
    # https://docs.python-requests.org/en/master/user/quickstart/#custom-headers
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36'
    }

    URL = 'https://www.google.com/shopping/product/14019378181107046593/offers?hl=en&gl=us'

    online_sellers = get_online_sellers_results(URL, headers)

    print(json.dumps(online_sellers, indent=2, ensure_ascii=False))


if __name__ == "__main__":
    main()
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Preparation

Install libraries:

pip install requests parsel
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Reduce the chance of being blocked

Make sure you're using request headers user-agent to act as a "real" user visit. Because default requests user-agent is python-requests and websites understand that it's most likely a script that sends a request. Check what's your user-agent.

There's a how to reduce the chance of being blocked while web scraping blog post that can get you familiar with basic and more advanced approaches.

Code Explanation

Import libraries:

import requests, json
from parsel import Selector
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Library Purpose
requests to make a request to the website.
json to convert extracted data to a JSON object.
Selector XML/HTML parser that have full XPath and CSS selectors support.

At the beginning of the main() function, the headers and URL are defined. This data is then passed to the get_online_sellers_results(URL, headers) function to form a request and extract information.

The online_sellers list contains the received data that this function returns. At the end of the function, the data is output in JSON format:

def main():
    # https://docs.python-requests.org/en/master/user/quickstart/#custom-headers
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36'
    }

    URL = 'https://www.google.com/shopping/product/14019378181107046593/offers?hl=en&gl=us'

    online_sellers = get_online_sellers_results(URL, headers)

    print(json.dumps(online_sellers, indent=2, ensure_ascii=False))
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This code uses the generally accepted rule of using the __name__ == "__main__" construct:

if __name__ == "__main__":
    main()
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This check will only be performed if the user has run this file. If the user imports this file into another, then the check will not work. You can watch the video Python Tutorial: if name == 'main' for more details.

Let's take a look at the get_online_sellers_results(url, headers) function mentioned earlier. This function takes url and headers parameters to create a request. At the beginning of the function, the data list in which the data will be stored is defined:

def get_online_sellers_results(url, headers):
    data = []
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Now we need to parse the HTML from the Parsel package, into which we pass the HTML structure that was received after the request.

Up to 20 sellers fit on one page. If there are more than 20 of them, then a page with the remaining sellers is added. To scrape a Google Product Online Sellers with pagination, you need to check for the presence of the Next button. While the Next button exists, you need to fetch the url for the next page in order to access it. If the Next button is not present, then you need to break the while loop:

while True:
    html = requests.get(url, headers=headers)
    selector = Selector(html.text)

    # data extraction from current page will be here

    if 'Next' in selector.css('.R9e18b .internal-link::text').get():
        url = 'https://www.google.com' + selector.css('.R9e18b .internal-link::attr(data-url)').get()
    else:
        break
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To retrieve data, you first need to find the .sh-osd__offer-row selector that is responsible for each seller and iterate over it:

for result in selector.css('.sh-osd__offer-row'):
    # data extraction from each seller will be here
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Data such as name, base_price, shipping, tax and total_price are retrieved for each seller. I want to draw your attention to the fact that not every seller has a link, so a ternary expression is used when extracting:

name = result.css('.kjM2Bf::text, .b5ycib::text').get() 
link = 'https://www.google.com' + result.css('.b5ycib::attr(href)').get() if result.css('.b5ycib') else None
base_price = result.css('.fObmGc::text').get()
shipping = result.css('.SuutWb tr:nth-child(2) td:nth-child(2)::text').get() 
tax = result.css('.SuutWb tr:nth-child(3) td:nth-child(2)::text').get()
total_price = result.css('.drzWO::text').get()
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Code Explanation
css() to access elements by the passed selector.
::text or ::attr(<attribute>) to extract textual or attribute data from the node.
get() to actually extract the textual data.

After extracting all data about the seller, a dictionary with this data is appended to the data list:

data.append({
    'name': name,
    'link': link,
    'base_price': base_price,
    'additional_price': {
        'shipping': shipping,
        'tax': tax
    },
    'total_price': total_price
})
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At the end of the function, the data list is returned.

return data
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Output:

[
  {
    "name": "Best Buy",
    "link": "https://www.google.com/url?q=https://www.bestbuy.com/site/steelseries-aerox-3-2022-edition-lightweight-wired-optical-gaming-mouse-onyx/6485231.p%3FskuId%3D6485231%26ref%3DNS%26loc%3D101&sa=U&ved=0ahUKEwiSuKKm1r_7AhWESDABHQvhDGwQ2ykIJA&usg=AOvVaw37TQlxlXfUf7Aow3-oj3Wr",
    "base_price": "$34.99",
    "additional_price": {
      "shipping": "$0.00",
      "tax": "$3.11"
    },
    "total_price": "$38.10"
  },
  ... other sellers
  {
    "name": "Network Hardwares",
    "link": "https://www.google.com/url?q=https://www.networkhardwares.com/products/aerox-3-wireless-2022-edition-62611%3Fcurrency%3DUSD%26variant%3D41025510441165%26utm_medium%3Dcpc%26utm_source%3Dgoogle%26utm_campaign%3DGoogle%2520Shopping%26srsltid%3DAYJSbAeM3Wi-nx6CPNXcQIZqlFcEv3uyBEgwTXa36ijEua1hx_LNmAm5EiM&sa=U&ved=0ahUKEwiSuKKm1r_7AhWESDABHQvhDGwQ2ykImgE&usg=AOvVaw1rOVOsiroUgnyyTT2JBN61",
    "base_price": "$64.51",
    "additional_price": {
      "shipping": "$0.00",
      "tax": "$5.73"
    },
    "total_price": "$70.24"
  }
]
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Using Google Online Sellers API from SerpApi

This section is to show the comparison between the DIY solution and our solution.

The main difference is that it's a quicker approach. Google Online Sellers API will bypass blocks from search engines and you don't have to create the parser from scratch and maintain it.

First, we need to install google-search-results:

pip install google-search-results
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Import the necessary libraries for work:

from serpapi import GoogleSearch
import os, json
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Next, we write the necessary parameters for making a request:

params = {
    # https://docs.python.org/3/library/os.html#os.getenv
    'api_key': os.getenv('API_KEY'),        # your serpapi api
    'engine': 'google_product',             # SerpApi search engine 
    'product_id': '14019378181107046593',   # product id
    'offers': True,                         # more offers, could be also set as '1` which is the same as True
    'hl': 'en',                             # language
    'gl': 'us'                              # country of the search, US -> USA
}
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We then create a search object where the data is retrieved from the SerpApi backend. In the results dictionary we get data from JSON:

search = GoogleSearch(params)   # where data extraction happens on the SerpApi backend
results = search.get_dict()     # JSON -> Python dict
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Retrieving the data is quite simple, we just need to access the 'sellers_results' key and then the 'online_sellers' key:

online_sellers = results['sellers_results']['online_sellers']
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After reviewing the playground, you will be able to understand which keys you can turn to into this JSON structure.

Example code to integrate:

from serpapi import GoogleSearch
import os, json

params = {
    # https://docs.python.org/3/library/os.html#os.getenv
    'api_key': os.getenv('API_KEY'),        # your serpapi api
    'engine': 'google_product',             # SerpApi search engine 
    'product_id': '14019378181107046593',   # product id
    'offers': True,                         # more offers, could be also set as '1` which is the same as True
    'hl': 'en',                             # language
    'gl': 'us'                              # country of the search, US -> USA
}

search = GoogleSearch(params)               # where data extraction happens on the backend
results = search.get_dict()                 # JSON -> Python dict

online_sellers = results['sellers_results']['online_sellers']

print(json.dumps(online_sellers, indent=2, ensure_ascii=False))
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Output:

[
  {
    "position": 1,
    "name": "Best Buy",
    "link": "https://www.google.com/url?q=https://www.bestbuy.com/site/steelseries-aerox-3-2022-edition-lightweight-wired-optical-gaming-mouse-onyx/6485231.p%3FskuId%3D6485231%26ref%3DNS%26loc%3D101&sa=U&ved=0ahUKEwiYt4fxyb_7AhXGFlkFHQZoCLMQ2ykIJA&usg=AOvVaw198AdAmbpUT5YEupYrp_iH",
    "base_price": "$34.99",
    "additional_price": {
      "shipping": "$0.00",
      "tax": "$3.02"
    },
    "total_price": "$38.01"
  },
  ... other sellers
  {
    "position": 38,
    "name": "Network Hardwares",
    "link": "https://www.google.com/url?q=https://www.networkhardwares.com/products/aerox-3-wireless-2022-edition-62611%3Fcurrency%3DUSD%26variant%3D41025510441165%26utm_medium%3Dcpc%26utm_source%3Dgoogle%26utm_campaign%3DGoogle%2520Shopping%26srsltid%3DAYJSbAdn6Cgm7HKsOdgiZ1_T8TK8NyOtSJpq2EC5meylVz982o4QDNcuTfA&sa=U&ved=0ahUKEwiYt4fxyb_7AhXGFlkFHQZoCLMQ2ykI5wE&usg=AOvVaw18MAXohnYThkG5Ip4Igqx-",
    "base_price": "$64.51",
    "additional_price": {
      "shipping": "$0.00",
      "tax": "$5.56"
    },
    "total_price": "$70.07"
  }
]
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