9 Best Python Web Scraping Libraries of 2026

1. 1

   Scrapy

   Open source crawling framework that schedules requests, parses responses and exports structured data from one asynchronous engine.

   9.7overall

   Open source crawling framework that schedules requests, parses responses and exports structured data from one asynchronous engine.

   Best forPython developers building crawlers that follow links across many pages and run on a schedule.

   Adoption data

   65.3k GitHub starsScrapy's main repository on GitHub had 65.3k stars in November 2026, the second highest count among the libraries on this list.

   GitHub, scrapy/scrapy repository on GitHub (2026): “Stars 65.3k stars”

   Scrapy is the most complete answer for a Python developer who needs to crawl, not just fetch one page. Its home page describes six parts around one asynchronous engine: a scheduler that queues and prioritizes requests, a concurrent downloader, the spiders you write, items, pipelines that validate and store records, and feed exports to JSON, CSV or S3. You test CSS and XPath selectors in the interactive shell before writing a spider, then scale the same project from a laptop to large crawls. The project lists 500+ contributors and fifteen years of releases, with version 2.20.0 out in November 2026, and the repository has 65.3k GitHub stars. The core does not render JavaScript, so dynamic sites need the scrapy-playwright extension, and anti-ban features come through the scrapy-zyte-api plugin, which connects to a paid Zyte service. For a one-off page grab it is more framework than you need.

   Strengths

   • +Covers the whole crawl, from request queue to exported file, in one project
   • +Over fifteen years of releases with 500+ contributors listed by the project
   • +Large extension catalog maintained by the community and Zyte

   Limitations

   • −No JavaScript rendering in the core; that needs an extension such as scrapy-playwright
   • −More structure to learn than a single requests plus parser script
   • −Hosted scheduling through Scrapy Cloud is a separate Zyte product

   SummaryScrapy is the strongest default for crawlers that span many pages and need pipelines and exports. Add scrapy-playwright when a site depends on JavaScript.

2. 2

   Playwright for Python

   Microsoft's browser automation library that drives Chromium, Firefox and WebKit from sync or async Python.

   9.6overall

   Microsoft's browser automation library that drives Chromium, Firefox and WebKit from sync or async Python.

   Best forDevelopers scraping JavaScript-heavy sites, logged-in pages and flows that need clicks and form input.

   Adoption data

   24.9%In the 2026 Stack Overflow Developer Survey, 24.9% of 10,604 respondents to the testing and code tools question had used Playwright in any language, the highest share of any browser automation tool listed.

   Stack Overflow, Code documentation and collaboration tools, Technology data 2026, Stack Overflow Developer Survey (2026): “Playwright 2,642 24.9%”

   Playwright for Python is the pick when the data you need only appears after JavaScript runs. The library drives Chromium, Firefox and WebKit through one API, and the docs describe it as a general purpose browser automation tool for both sync and async Python. Auto-waiting means actions wait until elements are actionable, which removes much of the sleep-and-retry code that browser scrapers used to need, and each browser context starts as a clean profile, so you can save a login once and reuse it. Playwright was the most used browser automation tool in the 2026 Stack Overflow survey at 24.9% of respondents to that question, though the figure covers every language, not Python alone. It is a browser driver, not a crawler: you write your own link queue, retries and storage, or pair it with Scrapy through scrapy-playwright or with Crawlee. Running real browsers also costs much more memory than plain HTTP requests.

   Strengths

   • +Renders pages the way a real browser does, including JavaScript content
   • +Most used browser automation tool in the 2026 Stack Overflow survey
   • +Async API fits large asyncio scraping jobs

   Limitations

   • −Each browser page uses far more memory and CPU than an HTTP request
   • −Built mainly for testing, so crawling, queues and exports are up to you
   • −Browsers must be installed and kept updated alongside the package

   SummaryPlaywright is the best Python choice for pages that need a real browser. Pair it with a crawler framework when you need queues and exports.

3. 3

   Beautiful Soup

   HTML and XML parsing library with simple methods for searching and modifying a parse tree.

   9.4overall

   HTML and XML parsing library with simple methods for searching and modifying a parse tree.

   Best forBeginners and quick scripts that fetch a page with Requests and pull a few fields out of messy HTML.

   Adoption data

   289,647,647 monthly downloadsThe beautifulsoup4 package was downloaded 289,647,647 times from PyPI in the month to November 11, 2026, according to PyPI Stats.

   PyPI Stats, beautifulsoup4 download stats (2026): “Downloads last month: 289,647,647”

   Beautiful Soup has been the starting point for Python scraping since 2004, and its download numbers show it still is: PyPI Stats counted almost 290 million downloads of beautifulsoup4 in the month to November 11, 2026. The library does one job, which is turning HTML or XML into a tree you can search with plain methods such as finding every link with a given class. It sits on top of parsers like lxml and html5lib, so you can pick speed or leniency, and it converts documents to Unicode for you. That makes it the gentlest way to learn scraping and a good fit for short scripts paired with Requests. It does not fetch pages, run JavaScript or manage a crawl, and on very large documents calling lxml directly is faster. Most developers outgrow it into Scrapy or Scrapling for bigger jobs, often keeping its parsing habits.

   Strengths

   • +Easiest parsing API to learn on this list
   • +Huge install base, so examples and answers are everywhere
   • +Tolerates broken markup that strict parsers reject

   Limitations

   • −Parses only; you need Requests, HTTPX or a browser to fetch pages
   • −Slower than using lxml directly on large documents
   • −No crawling, concurrency or JavaScript rendering

   SummaryBeautiful Soup is the easiest way to parse HTML in Python and the most downloaded library here. Use it with Requests for small jobs and move to a framework for crawls.

4. 4

   Scrapling

   Python scraping framework that combines HTTP requests, stealth browsers, adaptive parsing and Scrapy-like spiders in one library.

   9.3overall

   Python scraping framework that combines HTTP requests, stealth browsers, adaptive parsing and Scrapy-like spiders in one library.

   Best forDevelopers who want fetching, anti-bot handling, parsing and crawling in one package with an AI agent interface.

   Adoption data

   101.5k GitHub starsScrapling's repository on GitHub had 101.5k stars in November 2026, the highest count among the libraries on this list.

   GitHub, D4Vinci/Scrapling repository on GitHub (2026): “Stars 101.5k stars”

   Scrapling tries to replace a stack of separate tools with one library. Its documentation lists fast HTTP requests, stealth browsers that handle Cloudflare Turnstile and interstitial pages, CSS and XPath parsing, and concurrent spiders with proxy rotation, retries, AutoThrottle, pause and resume, and exports to JSON, JSONL, CSV and XML. The spider API is modeled on Scrapy, so the learning curve is short for anyone who has written a Scrapy spider. A distinctive feature is adaptive element tracking, which tries to find the same element after a site changes its markup. It also ships an MCP server and an Agent Skill for AI agents. The repository passed 101.5k GitHub stars in November 2026, more than any other library here, but it is younger than Scrapy and has fewer extensions and tutorials. Developers should also review site terms before using its stealth features.

   Strengths

   • +Covers static pages, JavaScript pages and full crawls in one library
   • +Adaptive selectors reduce breakage when page layouts change
   • +Highest GitHub star count on this list

   Limitations

   • −Younger project than Scrapy, Requests or Beautiful Soup, with a shorter release history
   • −Stealth and anti-bot features raise questions you must check against each site's terms
   • −Fewer third-party tutorials and extensions than Scrapy

   SummaryScrapling is the most feature-packed newer option, with fetching, browsers and spiders in one install. Choose Scrapy instead when you want the longer track record and extension catalog.

5. 5

   Requests

   Python's best known HTTP library for sending requests with sessions, cookies, proxies and timeouts.

   9.1overall

   Python's best known HTTP library for sending requests with sessions, cookies, proxies and timeouts.

   Best forScripts that fetch static pages or JSON endpoints and hand the HTML to a parser.

   Adoption data

   54.8k GitHub starsThe Requests repository on GitHub had 54.8k stars in November 2026.

   GitHub, psf/requests repository on GitHub (2026): “Stars 54.8k stars”

   Requests is the fetching half of the classic Python scraping pair. Its documentation lists the features a scraper relies on: sessions that keep cookies, keep-alive and connection pooling handled by urllib3, proxy support, connection timeouts, automatic decompression and streaming downloads. A request is one line, and the response text goes straight into Beautiful Soup or lxml. The repository has 54.8k GitHub stars and the library officially supports Python 3.10 and later. The limits matter for bigger jobs. Requests is synchronous, so fetching thousands of pages means threads, a different client such as HTTPX, or a framework like Scrapy. It has no HTTP/2 support and cannot see content that JavaScript adds after load. For small and medium scripts against static pages or JSON APIs, it remains the least effort option.

   Strengths

   • +Simplest way to fetch a page in Python
   • +Pairs naturally with Beautiful Soup or lxml
   • +Mature and widely documented

   Limitations

   • −Synchronous only, so large jobs need threads or another client
   • −No HTTP/2 support
   • −Does not run JavaScript or parse HTML

   SummaryRequests is the simplest way to fetch pages for a scraper. Switch to HTTPX for async or HTTP/2, and to Scrapy for large crawls.

6. 6

   lxml

   Fast XML and HTML processing library that binds the libxml2 and libxslt C libraries to a Python API.

   9.0overall

   Fast XML and HTML processing library that binds the libxml2 and libxslt C libraries to a Python API.

   Best forDevelopers parsing large volumes of HTML or XML who want XPath and speed over a friendlier API.

   Adoption data

   316,098,951 monthly downloadsThe lxml package was downloaded 316,098,951 times from PyPI in the month to November 11, 2026, according to PyPI Stats.

   PyPI Stats, lxml download stats (2026): “Downloads last month: 316,098,951”

   lxml is the speed option for parsing. It is a Python binding for the libxml2 and libxslt C libraries, and its site describes it as combining their speed and XML completeness with an API close to Python's ElementTree. For scrapers, the lxml.html module parses pages, links and forms, XPath gives precise selection, and lxml.cssselect adds CSS selectors. Many developers already use it without knowing it: Beautiful Soup can run on top of lxml, and PyPI Stats counted about 316 million lxml downloads in the month to November 11, 2026, a figure that includes it being pulled in as a dependency. The trade-off is ergonomics. The API is lower level than Beautiful Soup and it has no networking or crawl features, so it pairs with Requests, HTTPX or Scrapy. Choose it when you parse a lot of documents or rely heavily on XPath.

   Strengths

   • +Fast parsing thanks to its C libraries
   • +Full XPath support for precise extraction
   • +Used as a parser backend by Beautiful Soup

   Limitations

   • −Lower-level API than Beautiful Soup
   • −Strict XML habits can surprise newcomers working with broken HTML
   • −Parses only, with no fetching or crawling

   Summarylxml is the fastest way to parse HTML and XML with XPath in Python. Use it directly for heavy parsing and through Beautiful Soup when readability matters more.

7. 7

   Selenium

   W3C WebDriver browser automation project with official Python bindings for Chrome, Firefox, Edge and Safari.

   9.0overall

   W3C WebDriver browser automation project with official Python bindings for Chrome, Firefox, Edge and Safari.

   Best forTeams that already use Selenium for testing or need Safari, Edge or a distributed browser grid.

   Adoption data

   12.0%In the 2026 Stack Overflow Developer Survey, 12.0% of 10,604 respondents to the testing and code tools question had used Selenium in any language.

   Stack Overflow, Code documentation and collaboration tools, Technology data 2026, Stack Overflow Developer Survey (2026): “Selenium 1,272 12.0%”

   Selenium is the older browser automation standard and still a practical scraping tool when a page needs a real browser. It drives Chrome, Firefox, Edge and Safari through the W3C WebDriver standard, and Selenium Manager now downloads the matching driver automatically, which removes the old setup step. Selenium Grid spreads sessions across several machines, useful when one server cannot run enough browsers. In the 2026 Stack Overflow survey 12.0% of respondents to the testing tools question had used Selenium, about half Playwright's share, and those figures cover all languages. For new Python scrapers Playwright usually needs less code, thanks to auto-waiting, but Selenium makes sense if your team already maintains Selenium tests, needs Safari, or runs a Grid. As with any browser tool, you supply your own crawl logic and storage.

   Strengths

   • +Works with the widest set of real browsers, including Safari
   • +Long history, so most browser problems have documented answers
   • +Grid spreads browser work across machines

   Limitations

   • −More verbose than Playwright for waits and element handling
   • −Browser sessions are heavy compared with HTTP requests
   • −No built-in crawling, storage or export

   SummarySelenium is a sound choice for teams already invested in WebDriver or Grid. New browser scrapers usually start faster with Playwright.

8. 8

   Crawlee for Python

   Apify's open source crawling library with HTTP and browser crawlers, proxy rotation, fingerprints and a persistent queue.

   8.8overall

   Apify's open source crawling library with HTTP and browser crawlers, proxy rotation, fingerprints and a persistent queue.

   Best forDevelopers who want a modern async crawler with built-in blocking defenses and an easy path to cloud deployment.

   Adoption data

   9.7k GitHub starsThe Crawlee for Python repository on GitHub had 9.7k stars in November 2026.

   GitHub, apify/crawlee-python repository on GitHub (2026): “Stars 9.7k stars”

   Crawlee for Python is the most direct modern alternative to Scrapy. Apify built it to handle blocking, crawling, proxies and browsers, and it shows: crawlers based on Beautiful Soup, Parsel and Playwright share one API, and an adaptive crawler can decide per page whether JavaScript rendering is needed. Browser fingerprints, proxy rotation that drops blocked proxies, automatic concurrency scaling and a persistent queue for pause and resume are built in and switched on by default. Exporting results to CSV is a single call. The project has 9.7k GitHub stars, far fewer than Scrapy, so expect a smaller pool of tutorials and plugins. The library is free and runs anywhere, but its cloud story is the Apify platform, which is a paid service. It suits developers starting a new async crawler who want anti-blocking defaults without assembling extensions.

   Strengths

   • +Switch between HTTP and browser crawling without rewriting handlers
   • +Blocking defenses are on by default
   • +Deploys to Apify as an Actor with a few steps

   Limitations

   • −Smaller community and fewer extensions than Scrapy
   • −Async-only style may be new to some Python developers
   • −The smoothest cloud path runs through Apify's paid platform

   SummaryCrawlee is a strong choice for new async crawlers that mix HTTP and browser pages. Scrapy still has the bigger ecosystem.

9. 9

   HTTPX

   Next-generation Python HTTP client with a Requests-style API, async support and HTTP/2.

   8.7overall

   Next-generation Python HTTP client with a Requests-style API, async support and HTTP/2.

   Best forDevelopers who need async fetching or HTTP/2 in a lightweight scraper without a full framework.

   Adoption data

   15.8k GitHub starsThe HTTPX repository on GitHub had 15.8k stars in November 2026.

   GitHub, encode/httpx repository on GitHub (2026): “Stars 15.8k stars”

   HTTPX is what many developers reach for once Requests becomes the bottleneck. Its documentation describes a broadly Requests-compatible API with both synchronous and async clients and support for HTTP/1.1 and HTTP/2, plus strict timeouts, full type annotations and 100% test coverage. For scraping, the async client is the main draw: you can fetch hundreds of pages concurrently with asyncio while keeping familiar code, and HTTP/2 helps with sites that favor it. It also keeps the Requests feature set, including sessions with cookies, proxies, connection pooling and streaming downloads. The repository has 15.8k GitHub stars. Like Requests, it only fetches, so you pair it with Beautiful Soup, lxml or Parsel, and it cannot run JavaScript. If you need queues, retries and exports, a framework such as Scrapy or Crawlee will save time.

   Strengths

   • +Easy move from Requests with async added
   • +HTTP/2 support that Requests lacks
   • +Fully type annotated with 100% test coverage, per the docs

   Limitations

   • −Fetches only; you still need a parser
   • −No JavaScript rendering
   • −No crawl queue, retries policy or exports built in

   SummaryHTTPX is the best plain HTTP client for async scrapers in Python. Pair it with a parser and add a framework when the crawl grows.

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