Scraping_Intelligence_Logo
phone-header
Service +

Web Scraping Services

AI-Powered Web Scraping Custom Data Extraction Mobile App Scraping Web Scraping API Web Crawler Development Live Crawler Price Monitoring Brand Monitoring Product Matching Services Digital Shelf Analytics Machine Learning AI Training Dataset
Solution +
E-commerce Data Scraping Real Estate & Property Data Scraping Healthcare & Medical Data Scraping Food Delivery Data Scraping Travel & Hotel Data Scraping OTT Streaming Data Scraping Job Listings & Recruitment View All
Crawlers +
Amazon Data Scraper Lazada Data Scraper Zomato Data Scraper Netflix Data Scraper Linkedin Data Scraper Grubhub Data Scraper Yelp Data Scraper Zillow Data Scraper View All
Resources +
Blog Case Studies
Company +
About Us Contact Us Privacy Policy FAQs
Table Of Content
    Back to Blog

    How To Scrape Google Trends Without Using API?

    how-to-scrape-google-trends-data-without-an-api
    Category
    Google
    Publish Date
    July 16, 2021
    Author
    Scraping Intelligence

    Let us execute some code as we already have Python & an IDE/Selenium installed. Now, setup a web crawler and move ahead.

    #IMPORT THESE PACKAGES
import selenium
from selenium import webdriver
#OPTIONAL PACKAGE, BUY MAYBE NEEDED
from webdriver_manager.chrome import ChromeDriverManager

    Let’s use the following line of code to define our web browser in Selenium:

    #THIS INITIALIZES THE DRIVER (AKA THE WEB BROWSER)
                    driver = webdriver.Chrome(ChromeDriverManager().install())

    We’ll use the search phrase “cars” to acquire the URL of a specific Google Trends search page. Let’s head over to scraping of Google Trends and look for automobiles:

    As you’ll see, there is a lot of information on this page. Let’s imagine we wanted to use scraped Google Trends to get the most common relevant search term:

    Then, in your Python script, copy and paste the following code:

    POSTS = driver.find_element_by_xpath(‘DELETE THESE WORDS AND REPLACE WITH XPATH’).text

    Return to the Google Chrome browser now and save the XPath. To do so, right-click on the line in which the XPath appeared in the inspector tab, then right-click > copy > copy complete XPath.

    Return to your Python script and insert the following between the two quotes:

    POSTS = driver.find_element_by_xpath(‘/html/body/div[2]/div[2]/div/md-content/div/div/div[4]/trends-widget/ng-include/widget/div/div/ng-include/div/div[1]/div/ng-include/a/div/div[2]/span’).text
                    print(POSTS)

    That concludes our discussion. In our console, we’ll now be able to see the top related query for that search term:

    To accomplish this, return to your Python script and cut/paste the following code:

    #THIS PRETTY MUCH TELLS THE WEB BROWSER WHICH WEBSITE TO GO TO
                    driver.get('COPY AND PASTE YOUR URL HERE')

    This code should be replaced with the following URL from our Google Trends search page:

    #THIS PRETTY MUCH TELLS THE WEB BROWSER WHICH WEBSITE TO GO TO
                    driver.get('https://trends.google.com/trends/explore?q=cars&geo=US')

    Next, we’ll use the web browser to get the HTML property of the topmost related query. To begin, learn how and when to enable your development settings in your internet browser and turn them on. Next, right-click on the real top search engine (as shown below) and select inspect; you should see something similar to this:

    Here is the final execution of the project

    #IMPORT THESE PACKAGES
import selenium
from selenium import webdriver
#OPTIONAL PACKAGE, BUY MAYBE NEEDED
from webdriver_manager.chrome import ChromeDriverManager

#THIS INITIALIZES THE DRIVER (AKA THE WEB BROWSER)
driver = webdriver.Chrome(ChromeDriverManager().install())

#THIS PRETTY MUCH TELLS THE WEB BROWSER WHICH WEBSITE TO GO TO
driver.get('https://trends.google.com/trends/explore?q=cars&geo=US')

POSTS = driver.find_element_by_xpath('/html/body/div[2]/div[2]/div/md-content/div/div/div[4]/trends-widget/ng-include/widget/div/div/ng-include/div/div[1]/div/ng-include/a/div/div[2]/span').text
print(POSTS)

    Once the process gets completed, you have finally scraped some information from Google Trends without using an API. The above mentioned is a script used for scraping Google trends.

    About the author

    Zoltan Bettenbuk

    Zoltan Bettenbuk is the CTO of ScraperAPI - helping thousands of companies get access to the data they need. He’s a well-known expert in data processing and web scraping. With more than 15 years of experience in software development, product management, and leadership, Zoltan frequently publishes his insights on our blog as well as on Twitter and LinkedIn.

    Latest Blog

    Explore our latest content pieces for every industry and audience seeking information about data scraping and advanced tools.

    build-financial-data-pipeline
    Grocery
    30 Jan 2026
    How to Scrape Bulk Product Data from JioMart for Market Insights?

    Learn how to Extract bulk JioMart Data on prices, categories, and stock levels to track market trends and support retail teams at scale daily.

    web-scraping-lead-generation
    Business
    27 Jan 2026
    Web Scraping for Lead Generation 2026: Build Lead Lists at Scale

    Build targeted lead lists by using web scraping to automatically collect emails, phone numbers & profiles. Fill your CRM faster with quality prospects.

    how-to-scrape-glassdoor-job-data-using-lxml-and-python
    Recruitment
    22 Jan 2026
    How to Scrape Glassdoor Job Data in 2026: A Complete Python Guide?

    Learn how to scrape Glassdoor job listings using Python. Get accurate job data, company reviews, and salary details with a step-by-step tutorial.

    retail-data-scraping-use-cases
    E-commerce & Retail
    19 Jan 2026
    What Are the 5 Key Use Cases of Retail Data Scraping?

    Explore key use cases like competitor price monitoring, product assortment tracking, sentiment analysis, and trend forecasting with data scraping to Boost your retail strategy.

    Grocery
    30 Jan 2026
    Business
    27 Jan 2026
    Recruitment
    22 Jan 2026
    E-commerce & Retail
    19 Jan 2026