Web scraping is an effective method for data retrieval and extraction, allowing users to access and gather information from websites using automation tools and scripts.
It is an essential tool for data analysts, researchers, business stakeholders, and developers to improve their workflows and facilitate growth.
There are different tools and technologies for web scraping, many of which are compatible with multiple programming languages. Python has become a widely-adopted programming language in the web scraping ecosystem. This is because of its powerful libraries, great syntax, and active developer community.
Libraries are a source of vast tools and functionalities, which developers and web scrapers can use to handle complex websites and challenges to web scraping activities. Knowing the suitable library to use can help you improve your workflow and save time and resources.
In this article, you will read about the top Python web scraping libraries, their peculiarities, pros, and cons.
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Table of Contents
ZenRows web scraping API stands out as the number one Python web scraping library. It is an all-in-one solution that can overcome the most threatening scraping challenges. It comes with powerful features out of the box, such as headless browsers, rotating proxies, and others that help to effectively bypass website anti-bot detection defenses.
It is easy to use and is compatible with other libraries. With well-detailed and clear documentation, it is easy to use and adapt to by newbies and experienced web scrapers.
BeautifulSoup is a popular Python library with excellent HTML and XML parsing capabilities. Using BeautifulSoup, you can easily traverse and collate specific information from the parsed HTML and XML. It is good for examining and parsing messy documents. BeautifulSoup also allows you to perform different actions and manipulate the data within the parsed documents.
You can combine BeautifulSoup with other tools to extend its capabilities. With BeautifulSoup, it is seamless to fetch web content and create data processing pipelines. Whether you need to scrape data from sites or analyze XML files, BeautifulSoup provides a reliable solution.
Selenium takes the mimicking of human actions on a website step further. It is highly compatible with dynamic websites with JavaScript rendering. Selenium can fill forms, scroll, wait for pages to load, and click buttons. All of these features will aid the scraper to bypass anti-bot defenses that websites have put in place, making it hard for them to tell your actions via Selenium apart from humans.
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Playwright, like Selenium, is well known as a scraping library that can simulate human actions accurately. Although it could pose a longer learning curve for beginners, its detailed documentation serves as a guide to help people learn and adapt to it.
Playwright’s compatibility with multiple browsers and operating systems gives developers the flexibility required for their scraping needs. You can write scripts to work across different platforms and lets you choose the one that best suits you.
urllib3 is an inbuilt lightweight Python library that offers a simple API for making HTTP requests, managing connections, handling cookies, etc. It is well known for its stability in scraping activities.
However, it is not suitable for scraping dynamic websites as it cannot handle JavaScript-rendered content as well as others. It also has less community support compared to others. Use Urllib3 for small-scale scraping tasks or websites that do not rely heavily on JavaScript.
The importance of libraries in web scraping cannot be overstated. You must understand the uniqueness of each library to enable you to choose the most suitable for your web scraping work.
Selenium and BeautifulSoup are Python libraries that provide unique functionalities for web scraping. ZenRows, however, provides these and more, emerging an all-encompassing reliable solution. With ZenRows, you can get data faster, as it handles all anti-bot detection bypass techniques and JavaScript rendering in one API call.
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