How to Scrape Nested Tags using BeautifulSoup? Last Updated : 22 Jul, 2021 Comments Improve Suggest changes Like Article Like Report We can scrap the Nested tag in beautiful soup with help of. (dot) operator. After creating a soup of the page if we want to navigate nested tag then with the help of. we can do it. For scraping Nested Tag using Beautifulsoup follow the below-mentioned steps. Step-by-step Approach Step 1: The first step will be for scraping we need to import beautifulsoup module and get the request of the website we need to import the requests module. from bs4 import BeautifulSoup import requests Step 2: The second step will be to request the URL call get method. page=requests.get(sample_website) Step 3: The third step will be for creating soup use beautifulsoup method and for the HTML parse tree use an HTML parser. BeautifulSoup(page.content, 'html.parser') Step 4: The fourth step will be to perform .operator till when we want the tag for scrap nested tag, if we want to scrap tag inside body and table then we will use the below statement to scrape nested tags. soup.body.table.tagImplementations Below are various examples that depict how to scrape different nested tags from a particular URL Example 1: Python3 from bs4 import BeautifulSoup import requests # sample website sample_website = 'https://www.geeksforgeeks.org/different-ways-to-remove-all-the-digits-from-string-in-java/' # call get method to request the page page = requests.get(sample_website) # with the help of BeautifulSoup method and # html parser created soup soup = BeautifulSoup(page.content, 'html.parser') # With the help of . operator we will scrap a tag # under body->ui->i # here we will go a tag inside body then ul then # i.means under the body tag we will go to ul tag # and again inside the ul tag we will go i tag print(soup.body.ul.i) Output: <i class="gfg-icon gfg-icon_arrow-down gfg-icon_header"></i> Example 2: Python3 from bs4 import BeautifulSoup import requests # sample website sample_website = 'https://www.geeksforgeeks.org/different-ways-to-remove-all-the-digits-from-string-in-java/' # call get method to request the page page = requests.get(sample_website) # with the help of BeautifulSoup method and html # parser created soup soup = BeautifulSoup(page.content, 'html.parser') # With the help of . operator we will scrap a tag # under body->a # here we will go a tag inside body then a then # li.means under the body tag we will go to a tag print(soup.body.a) Output: <a class="gfg-stc" href="#main" style="top:0">Skip to content</a> Example 3: Python3 from bs4 import BeautifulSoup import requests # sample website sample_website = 'https://www.geeksforgeeks.org/different-ways-to-remove-all-the-digits-from-string-in-java/' # call get method to request the page page = requests.get(sample_website) # with the help of BeautifulSoup method and # html parser created soup soup = BeautifulSoup(page.content, 'html.parser') #With the help of . operator we will scrap a # tag under body->a # here we will go a tag inside body then a then # li.means under the body tag we will go to a tag print(soup.body.a) # With the help of . operator we will scrap a # tag under body->ui->li # here we will go a tag inside body then ul then # li.means under the body tag we will go to ul tag # and again inside the ul tag we will go li tag # and inside to li tag we will go to a tag print(soup.body.ul.li.a) Output: <a href="https://www.geeksforgeeks.org/analysis-of-algorithms-set-1-asymptotic-analysis/" target="_self">Asymptotic Analysis</a> Comment More infoAdvertise with us Next Article Extract all the URLs that are nested within <li> tags using BeautifulSoup vipinyadav15799 Follow Improve Article Tags : Python Python BeautifulSoup Python bs4-Exercises Practice Tags : python Similar Reads Python Web Scraping Tutorial In today’s digital world, data is the key to unlocking valuable insights, and much of this data is available on the web. 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