Based on my over a decade of software development experience, including my role as CTO at AIMultiple, where I led data collection from ~80,000 web domains, I have selected the top Python web scraping libraries.
Best Python web scraping libraries
BeautifulSoup
BeautifulSoup is a Python library for parsing HTML and XML and extracting data from web pages. It sits on top of an HTML or XML parser and provides a simple, Pythonic way to search, navigate, and modify the parse tree.
BeautifulSoup remains actively maintained, with version 4.14.3 released on 2025. The current package requires Python 3.7 or newer.1
Pros of BeautifulSoup:
- It works with multiple parsers, including Python’s built-in HTML parser, html5lib, and lxml. This makes it easy to trade off speed, leniency, and installation complexity depending on your project.
Cons of BeautifulSoup:
- Beautiful Soup parses markup, but it does not download pages itself. In most scraping workflows, it is paired with an HTTP client such as Requests or urllib3.
Scrapy
Unlike the other tools we’ve discussed, Scrapy is not a single library but a complete framework. Scrapy continued to evolve in 2026. Version 2.14.0, released on January 5, 2026, introduced more coroutine-based replacements for older Deferred-based APIs, improved the API for custom download handlers, and dropped support for Python 3.9. 2
Pros of Scrapy:
- Scrapy is built on Twisted, an asynchronous networking framework, which allows it to handle many requests efficiently. Recent releases have also added more coroutine-based replacements for older Deferred-style APIs, pushing the framework further toward modern async-friendly development.
- Scrapy includes built-in extensions and middleware for handling common crawling tasks such as obeying robots.txt rules, managing cookies and sessions, and working with proxies. Recent releases also improved the API for custom download handlers.
Cons of Scrapy:
- Current Scrapy releases require Python 3.10+, so users on Python 3.9 or older will need to upgrade before adopting the latest version.
- As a full framework, Scrapy has a more complex architecture than parser-focused tools like Beautiful Soup.
Selenium
Selenium is useful for scraping dynamic websites that rely on JavaScript, because it can control a real browser and interact with pages much like a human user would, including clicking buttons, filling out forms, and scrolling. In 2026, Selenium’s Python bindings are on version 4.41.0 and support Python 3.10+.
Recent official release notes highlight major Grid updates, including native Kubernetes Dynamic Grid support, a Session Event API, and improvements to remote-browser infrastructure.
Pros of Selenium:
- Selenium can automate actions such as clicking buttons, filling out forms, scrolling, dragging and dropping, and navigating multi-step workflows.
- Selenium works across major browsers including Chrome, Firefox, Safari, and Edge.
Cons of Selenium:
- Because Selenium runs a real browser, it uses significantly more CPU and memory than parser- or HTTP-based tools, which makes it less efficient for very large-scale crawling.
Requests
Requests is an HTTP library that allows users to make HTTP calls to collect data from web sources.3 The current Requests package officially supports Python 3.9 and newer.
Pros of Requests:
- Requests is commonly paired with Beautiful Soup or lxml, with Requests handling the download step and the parser handling extraction.
Cons of Requests:
- Requests only retrieves the server response. It does not execute JavaScript or interact with a page like a browser automation tool such as Selenium or Playwright.
Playwright
Playwright is a Python library for browser automation that works across Chromium, Firefox, and WebKit through a single API.4 Compared with older browser automation stacks, Playwright emphasizes modern browser support, consistent cross-browser behavior, and a smoother installation workflow. In 2026, the Python package is at version 1.58.0 and supports Python 3.9+.
Playwright’s 1.58 release introduced several usability improvements, including Trace Viewer and UI Mode updates such as a system-theme option, search inside code editors, a reorganized network-details panel, and automatically formatted JSON responses.
Pros of Playwright:
- The current Playwright release bundles support around Chromium 145.0.7632.6, Firefox 146.0.1, and WebKit 26.0, reinforcing its appeal for teams that want evergreen browser automation without separately managing traditional WebDriver binaries.
- Playwright can render JavaScript-heavy websites and interact with content that does not appear in the initial HTML response, making it a strong choice for modern web apps.
Cons of Playwright:
- Like Selenium, Playwright runs real browser engines, so it uses more CPU and memory than parser- or HTTP-based tools such as Beautiful Soup or Requests.
lxml
lxml is a powerful Python library for parsing HTML and XML. It combines Python’s ElementTree-style API with the speed and feature depth of the underlying libxml2 and libxslt C libraries, which makes it a strong choice for fast parsing, XPath queries, and structured data extraction.
The current PyPI release is lxml 6.0.2, released in 2025. Current official installation guidance states that lxml 6.0 and later require Python 3.8 or newer.
Pros of lxml:
- lxml is especially useful for XPath-based extraction and structured parsing tasks that need more power than basic tag traversal.
Cons of lxml:
- lxml is more technical than Beautiful Soup and can feel less approachable for simple scraping tasks.
urllib3
urllib3 is a powerful Python HTTP client library that provides features such as thread-safe connection pooling, retries, redirects, proxy support, and SSL/TLS verification. It is more low-level than Requests, but that also makes it a strong option for developers who want more control over HTTP behavior in scraping and automation workflows.5
The current PyPI release is urllib3 2.6.3, released in 2026, and the package now requires Python 3.9 or newer.
Pros of Urllib3:
- urllib3 includes connection pooling, retry helpers, redirect handling, TLS verification, multipart uploads, and proxy support, which make it more capable than Python’s standard URL utilities for serious HTTP work.
- urllib3 exposes lower-level HTTP behavior more directly, which can be useful when fine-tuning retries, pooling, transport settings, or proxy behavior in scraping infrastructure.
Cons of Urllib3:
- urllib3 is powerful, but it is not as simple or ergonomic for newcomers as Requests. For many small scraping tasks, Requests is easier to learn and use.
MechanicalSoup
MechanicalSoup is a Python library for automating interaction with websites. It automatically stores and sends cookies, follows redirects, follows links, and submits forms, making it useful for login flows and other session-based interactions on static sites. It is built on top of Requests for HTTP sessions and Beautiful Soup for document parsing. It does not execute JavaScript 6
The current PyPI release is MechanicalSoup 1.4.0, released in 2025. Its 1.4 release added support for Python 3.12 and 3.13, removed support for Python 3.6, 3.7, and 3.8.
Pros of MechanicalSoup:
- MechanicalSoup is especially useful for tasks such as logging in, filling out forms, maintaining sessions, and navigating link-based workflows on sites that do not require JavaScript execution.
- MechanicalSoup sits between a plain HTTP client and a full browser automation tool, which makes it practical for certain scraping tasks that need form handling but not JavaScript rendering.
Cons of MechanicalSoup:
- MechanicalSoup does not render pages or execute JavaScript, so it is not a good fit for modern web apps that load critical content client-side.
What is a Python web scraping library?
A Python web scraping library is a Python tool that helps you collect data from websites. Different libraries focus on different parts of the process such as:
- Requests / urllib3 fetch web pages
- Beautiful Soup / lxml parse and extract data from HTML
- Scrapy provides a full scraping framework
- Selenium / Playwright automate real browsers for dynamic sites
- MechanicalSoup helps with forms and session-based workflows
How do you choose the best web scraping library?
How complex is the target website?
For sites with clean, straightforward HTML, the combination of the Requests library and BeautifulSoup is often the most efficient approach. Modern websites often utilize JavaScript, which means that the data you want to scrape may not be directly present in the initial HTML source.
You’ll need a browser automation tool that can render JavaScript (such as Selenium or Playwright) to simulate user actions, like clicks, and scroll to reveal the desired publicly available web data.
What is the scale of your project?
For single-use scraping tasks, the simplicity of BeautifulSoup can make it an ideal choice. If you need to build a scalable web crawler to scrape large volumes of data, Scrapy is a good choice, as it offers built-in support for asynchronous scraping and data processing pipelines.
Do you need to handle anti-scraping measures?
Many websites have measures in place to block scrapers, such as CAPTCHAs, IP blocking, and rate limiting. While some Python web scraping tools offer basic support for proxy servers, more advanced data collection projects might require rotating proxies and web unblockers to avoid detection.
FAQs about Python web scraping libraries
Beautiful Soup is a parsing library, ideal for beginners and smaller web scraping projects. It excels at navigating and searching through HTML and XML documents. However, it doesn’t fetch web pages.
Scrapy is a comprehensive framework designed for large-scale and complex web scraping projects, with built-in support for asynchronous requests. Scrapy is the go-to option when you need to crawl multiple pages.
Selenium and Playwright are browser automation tools that are essential for scraping dynamic websites that rely heavily on JavaScript to load content. If the data you need isn’t in the initial HTML source, these tools can interact with the page like a user. Playwright is considered a more modern alternative to Selenium.
Reference Links
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