Best Open-Source Web Scraping Framework for Python
4 open-source options compared for web scraping framework for Python, with live GitHub data on each.
Last updated Repo data refreshed 25 Oct 20264 options
Our pick · scrapy
Our pick is Scrapy, a fast high-level web crawling and scraping framework for Python, ideal for large-scale, high-performance data extraction from static or moderately dynamic websites. Its asynchronous architecture provides efficiency and reliability for complex projects, though tools like Playwright are needed for heavy JavaScript rendering. Playwright, the Python version of the testing and automation library, offers robust browser automation for highly dynamic pages despite a higher resource cost. While Requests-HTML was once suitable for quick, simple tasks, its dormant status and latest release in 2019 mean it is less suitable for current needs, unlike the active Apify SDK for Python which focuses on scalable cloud-integrated scraping solutions.
Scrapy vs Playwright for Python vs requests-html vs Apify SDK: side by side
A fast, high-level screen scraping and web crawling framework for Python that makes it easy to extract data from websites.
Best for: Large-scale, high-performance web crawling and data extraction from static or moderately dynamic websites where efficiency and scalability are paramount.
What's good
Highly scalable and performant for large-scale crawling, thanks to its asynchronous architecture (Twisted).
Comprehensive framework with built-in components for handling requests, responses, item pipelines, link extractors, and middleware.
Extensive documentation, large community, and mature ecosystem with many plugins and add-ons.
Robust request scheduling, retries, and handling of redirects and cookies out-of-the-box.
Watch out for
Steep learning curve for beginners due to its opinionated structure and asynchronous nature.
★ 15,066 starsLicence: Apache-2.0Last commit 24 Oct 2026Latest release 22 Oct 2026Python
Playwright is a Python library to automate Chromium, Firefox and WebKit with a single API, enabling robust and reliable web scraping of dynamic websites.
Best for: Scraping highly dynamic, JavaScript-rendered websites and single-page applications (SPAs) where full browser capabilities and interaction are essential.
What's good
Excellent for scraping modern, JavaScript-heavy websites as it automates real browser instances (Chromium, Firefox, WebKit).
Provides a powerful API for interacting with pages, handling events, waiting for elements, and bypassing common anti-bot measures.
Supports parallel execution, screenshotting, PDF generation, and network request interception, offering deep control over the browsing context.
Cross-browser compatibility and active development by Microsoft ensure a reliable and up-to-date tool.
Watch out for
Higher resource consumption (CPU, RAM) compared to requests-based scrapers due to running full browser instances.
Slower execution speed for static content compared to Scrapy or Requests, as it involves rendering the entire page.
Requires careful management of browser instances and contexts to avoid memory leaks or performance degradation in long-running tasks.
A user-friendly, all-in-one Python library for parsing HTML and executing JavaScript, built on Requests and Parsel.
Best for: Quick, simple web scraping tasks on static or moderately dynamic websites where ease of use and rapid prototyping are prioritized over scalability.
What's good
Extremely easy to get started with for simple scraping tasks, offering a very intuitive API for CSS/XPath selection.
Can render JavaScript using headless Chromium (via Pyppeteer), making it capable of handling some dynamic content.
Combines the simplicity of Requests with powerful parsing capabilities, providing a cohesive experience.
Offers an elegant way to interact with elements and forms using `render()` and `session`.
Watch out for
No commits pushed since Apr 2024; check whether it still fits your stack before adopting it.
JavaScript rendering via Pyppeteer can be unreliable, complex to set up, and is not as robust or actively maintained as Playwright.
Not designed for large-scale crawling; lacks features like request scheduling, retries, or item pipelines found in full frameworks like Scrapy.
Performance can degrade quickly for many concurrent requests or complex parsing, as it's primarily synchronous.
★ 180 starsLicence: Apache-2.0Last commit 23 Oct 2026Latest release 8 Oct 2026Python
The Apify SDK for Python provides tools and functionalities for building scalable web scrapers, crawlers, and data extraction agents.
Best for: Building robust and scalable web scraping solutions, especially for dynamic websites, with a focus on ease of deployment and cloud integration.
What's good
Provides a unified API for both Playwright and Puppeteer, allowing flexible browser automation for dynamic content.
Offers robust state management, request queueing, proxy rotation, and result storage out-of-the-box.
Designed for cloud execution on the Apify platform, simplifying deployment and scaling for complex projects.
Good for handling concurrency and retries, making it suitable for more involved scraping operations than simple scripts.
Watch out for
Can feel opinionated and might introduce unnecessary complexity if not leveraging its cloud features or advanced components.
The learning curve can be steeper than `requests-html` due to its broader feature set and concept of 'Actors' and 'storages'.
While usable standalone, its full potential and ease of use are realized when integrated with the Apify platform, which can lead to vendor lock-in concerns.
"Dormant" means no commit pushed to the default branch in the last 12 months. "Archived" means the maintainers have marked the repository read-only on GitHub. "Deprecated" means the project's README says it is deprecated or no longer maintained. Stars, licence, commit and release dates come from the GitHub API (GitLab for projects developed there) and are cached for up to 24 hours. The written analysis is AI-assisted and checked against that data.
Scrapy vs Playwright
Scrapy and Playwright for Python cover different halves of scraping: Scrapy crawls and extracts structured data, while Playwright drives a real browser for pages that need JavaScript. See Scrapy vs Playwright for when to use each, or both together.
Are Scrapy, Playwright for Python, requests-html and Apify SDK actively maintained?
Scrapy, Playwright for Python and Apify SDK are active: each has had a commit in the last 12 months (most recent: Scrapy on 22 Oct 2026, Playwright for Python on 24 Oct 2026, Apify SDK on 23 Oct 2026). requests-html is dormant: no commit since 16 Apr 2024. Status is checked against GitHub daily.
What licences do Scrapy, Playwright for Python, requests-html and Apify SDK use?
Scrapy: BSD-3-Clause; Playwright for Python: Apache-2.0; requests-html: MIT; Apify SDK: Apache-2.0. Check each project's licence file before use.
Which is easiest to learn: Scrapy, Playwright for Python, requests-html or Apify SDK?
By our estimate (1 = easiest, 5 = steepest): Scrapy 4/5, Playwright for Python 3/5, requests-html 2/5, Apify SDK 3/5. requests-html has the gentlest learning curve. This is ExploreGit's AI-assisted estimate, not a measured figure.
