For instance, check out this code to get the h3 tag: soup.h3 Output: Products You can access individual tags as attributes of the soup object. Now that we have got the HTML parsed, let’s dive into accessing the tags and data within them. It is best to specify a particular parser for consistent results across platforms and virtual environments. “lxml”, “html.parser”) or the type of document (e.g. The “features” argument in BeautifulSoup lets you choose the type of parser to use (e.g. The first parameter used while calling the BeautifulSoup constructor is the sample HTML, and the second one is the features. sample_html = '' soup = BeautifulSoup(sample_html, 'html.parser') It uses other libraries such as lxml, html.parser, and html5lib to do this. BeautifulSoup will not parse the HTML content by itself. You can use the code lines mentioned below to parse the HTML page. Now, let’s parse the HTML code (mentioned above). Demo Page Products Name: Abra Price: 100.00 Buy Name: Absol Price: 80.00 Buy Name: Altaria Price: 120.00 Buy Name: Arctozolt Price: 110.00 Buy Name: Barbaracle Price: 100.00 Buy Parsing HTML content It’s a simple listing page with pokemon as products. We will be using the following HTML throughout this article. How to parse and extract data from an HTML page using BeautifulSoup? BeautifulSoup installation pip install beautifulsoup4 In this article, we’ll dive deeper into using BeautifulSoup for web scraping. BeautifulSoup web scraping is a popular choice in the Python community. It enables you to parse HTML and XML documents, making data extraction easy and efficient. BeautifulSoup is a Python library that helps you parse web pages and extract information from them. Data extracted from web pages in its raw HTML form may not be immediately usable, so it is essential to convert it into a structured format first. It helps in gathering data that helps in machine learning, data analysis, and artificial intelligence use cases. Web scraping is a technique used to extract data from websites automatically.
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