Beautifulsoup 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.
Scrapy and BeautifulSoup are two popular web scraping libraries though very different. Scrapy is a framework while beautifulsoup is a HTML parser
To find HTML elements that do NOT contains a specific attribute we can use regular expression matching or lambda functions. Here's how to do it.
To find sibling HTML element nodes using BeautifulSoup the find_next_sibling() method can be used or CSS selector ~. Here's how to do it in Python.
To find HTML elements by one of many different element names we can use list of tags in find() methods or CSS selectors. Here's how to do it.
To select HTML element located between two HTML elements using BeautifulSoup the find_next_sibling() method can be used. Here's how to do it.
To find HTML node by a specific attribute value in BeautifulSoup the attribute match parameter can be used in the find() methods. Here's how.
To find HTML node by class name using BeautifulSoup the class match parameter can be used using the find() methods. Here's how to do it.
To find all links in the HTML pages using BeautifulSoup and Python the find_all() method can be used. Here's how to do it.
BeautilfulSoup for Python doesn't support XPath selectors but there are popular alternatives to fill in this niche. Here are some.
To scrape HTML tables using BeautifulSoup and Python the find_all() method can be used with common table parsing algorithms. Here's how to do it.
BeautifulSoup is a popular HTML library for Python. It's most popular alternatives are lxml, parsel and html5lib. Here's how they differ from bs4.
To turn HTML data to text in Python we can use BeautifulSoup's get_text() method which strips away HTML data and leaves text as is. Here's how.
