[Answers](https://scrapfly.io/blog)   /  [beautifulsoup](https://scrapfly.io/blog/tag/beautifulsoup)   /  [How to scrape tables with BeautifulSoup?](https://scrapfly.io/blog/answers/how-to-scrape-tables-with-beautifulsoup)   # How to scrape tables with BeautifulSoup?

 by [Bernardas Alisauskas](https://scrapfly.io/blog/author/bernardas) Apr 18, 2026 2 min read [\#beautifulsoup](https://scrapfly.io/blog/tag/beautifulsoup) [\#data-parsing](https://scrapfly.io/blog/tag/data-parsing) 

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HTML tables are commonly found across different web pages. They exist as a data frame on the web page. In this guide, we'll explain how to scrape an HTML table with BeautifulSoup as the parsing library through a real-life example. Let's get started!



## Setup

Before we start, let's ensure the required libraries are installed.First, let's install the BeautifulSoup package using the `pip` terminal command:

shell```shell
pip install beautifulsoup4
```



As for the HTTP client, we'll be using the built-in `requests` Python library. However, it can be replaced with any other client, such as [httpx](https://scrapfly.io/blog/posts/web-scraping-with-python-httpx/).



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[Try Free →](https://scrapfly.io/register)## Retrieve Table Data

o start, let's have a look at our target table. We'll be using the target table classes [web-scraping.dev/product/1](https://web-scraping.dev/product/1):



We'll request the above page to retrieve the tables data available in the HTML:

python```python
from bs4 import BeautifulSoup
import requests 

response = requests.get("https://web-scraping.dev/product/1")
html = response.text

# Create the soup object
soup = BeautifulSoup(html, "lxml")
```



Above, we start by requesting the target webpage to retive the HTML tables. Then, we use BeautifulSoup to create a parser object.



## Parse HTML Tables

The BeautifulSoup package uses [CSS](https://scrapfly.io/blog/posts/parsing-html-with-css/) selectors to select HTML elements. Hence, we'll target the table class, and then iterate over its rows:

python```python
from bs4 import BeautifulSoup
import requests 

response = requests.get("https://web-scraping.dev/product/1")
html = response.text

soup = BeautifulSoup(html, "lxml")

# First, select the desried table element (the 2nd one on the page)
table = soup.find_all('table', {'class': 'table-product'})[1]

headers = []
rows = []
for i, row in enumerate(table.find_all('tr')):
    if i == 0:
        headers = [el.text.strip() for el in row.find_all('th')]
    else:
        rows.append([el.text.strip() for el in row.find_all('td')])
```



Above, we first use the `find_all` method to find all table elements and select the second table on the page. Then, we find each table row and iterate through them extracting their text contents. As for the `i == 0` condition, we use it to extract the table header rows, as it's first row in our BeautifulSoup table.

Here are what the results we got should look like:

python```python
print(headers)
['Version', 'Package Weight', 'Package Dimension', 'Variants', 'Delivery Type']
for row in rows:
    print(row)
    ['Pack 1', '1,00 kg', '100x230 cm', '6 available', '1 Day shipping']
    ['Pack 2', '2,11 kg', '200x460 cm', '6 available', '1 Day shipping']
    ['Pack 3', '3,22 kg', '300x690 cm', '6 available', '1 Day shipping']
    ['Pack 4', '4,33 kg', '400x920 cm', '6 available', '1 Day shipping']
    ['Pack 5', '5,44 kg', '500x1150 cm', '6 available', '1 Day shipping']
```



For more details on parsing with BeautifulSoup, refer to our dedicated guide.

[How to Parse Web Data with Python and BeautifulsoupBeautifulsoup is one the most popular libraries in web scraping. In this tutorial, we'll take a hand-on overview of how to use it, what is it good for and explore a real -life web scraping example.](https://scrapfly.io/blog/posts/web-scraping-with-python-beautifulsoup)



 

    Table of Contents- [Setup](#setup)
- [Retrieve Table Data](#retrieve-table-data)
- [Parse HTML Tables](#parse-html-tables)
 
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  ## Related Questions

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- [ Q How to scrape HTML table to Excel Spreadsheet (.xlsx)? ](https://scrapfly.io/blog/answers/html-table-to-xlsx-python-beautifulsoup)
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