For ordinary multi-page HTML crawling, start with Scrapy: it is a free, full crawler framework with request scheduling, link following, extraction, and data exports. Choose Crawlee for Python if you want a single asyncio-based interface for HTTP and browser crawling, retries, persistent queues, and flexible storage. If a site renders its content with JavaScript, add browser automation—Scrapy can use the official scrapy-playwright extension to render pages while keeping its crawler workflow.
What to choose in 2026
| Need | Starting choice | Why |
|---|---|---|
| Crawl many pages of ordinary HTML and organize extracted data | Scrapy | It combines request scheduling, spider callbacks, link following, selectors, item pipelines, and feed exports. |
| Use Python for both HTTP and browser crawling with a shared interface | Crawlee for Python | The project documents HTTP and Playwright crawlers, retries, persistent queues, session and proxy management, and pluggable storage. |
| Capture content that appears only after JavaScript or user interaction | Playwright, Selenium, or Puppeteer as browser automation; or integrate a browser with a crawler | A browser executes page JavaScript. Scrapy’s official scrapy-playwright extension integrates browser rendering into Scrapy’s request/response workflow. |
| Take a one-off website screenshot rather than crawl and extract data | ScreenshotNeo | It is a screenshot API and MCP server, not a general-purpose crawling framework; it returns an image or PDF from one request. |
“Free” here describes framework software, not every cost of running a crawl. Compute, browser binaries, proxies, hosted deployment, and managed request services may cost extra. A local learning project may need none of them; persistent production crawls may need operational infrastructure.
What makes a scraping framework the right fit?
Crawl workflow
A crawler framework handles more than retrieving a page. It can schedule requests, follow links, retry work, pass responses to extraction code, and structure or export results. Scrapy is the clearest fit in this comparison when you need that end-to-end workflow across many pages. Browser automation tools primarily control a browser; they can scrape, but they are not interchangeable with a crawler’s scheduling and data pipeline.
Rendering and interaction
A direct HTTP fetch receives the server’s response without executing page JavaScript. If the response is an almost-empty shell whose content is added in the browser, parsing that response will not recover the rendered content. Use a real browser when the target requires JavaScript execution or interaction, and account for the added browser setup and resource use.
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Language and operations
Choose a tool that fits the language and asynchronous model already used by your project. Also decide whether you need persistent queues, session handling, storage, deployment, and monitoring, or just a local script. Those operational needs can matter more than a claimed speed difference: no controlled 2026 cross-framework benchmark establishes a fastest option.
Scrapy: best starting point for conventional crawling
Scrapy is a Python application framework for crawling websites and extracting structured data. Its documented workflow uses spiders and an asynchronous scheduler to make requests, process responses, extract fields with CSS or XPath selectors, and send structured items through pipelines or feed exports. It also provides a shell for debugging selectors, supports JSON, CSV, and XML feeds, and documents storage backends, extensions, and robots.txt support.
Why it suits multi-page jobs
- Define a spider that starts from one or more URLs, extracts records, and follows relevant links.
- Use CSS or XPath selectors to extract fields from returned HTML.
- Use item pipelines or feed exports to validate, transform, and save results.
- Set request delays and per-domain concurrency limits; Scrapy also documents AutoThrottle to adjust crawling activity.
These controls help make a crawler more considerate of a site, but they do not grant permission to access it. Check the target site’s terms and robots guidance, and follow applicable law; requirements vary by site and jurisdiction.
Where plain Scrapy falls short
Scrapy’s normal HTTP requests do not run browser JavaScript. If important content is inserted after page load, a spider may see only an empty shell. The official scrapy-playwright documentation describes using a real browser to render the page and return loaded HTML while retaining Scrapy’s workflow. Browser rendering adds setup and resource use, so use it for pages that need it rather than assuming every URL requires a browser.
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The Scrapy project page describes the framework and its stewardship; release details change over time, so check the project’s current release information before pinning a version. The comparison here does not treat a release number as evidence of speed or superiority.
Crawlee for Python: one interface for HTTP and browser crawling
Crawlee for Python is an open-source library documented by its project as supporting both HTTP parsing and browser-driven crawling. Its repository describes automatic parallel crawling, retries, request routing, a persistent request queue, session management and proxy rotation, and pluggable data and file storage. It offers BeautifulSoup-based HTTP crawling and a Playwright crawler. The repository states an Apache License 2.0 license and says the library can run anywhere; deployment to Apify is an available option, not a requirement.
When to choose it
- You want to write an asyncio-based Python crawler without switching to a separate interface for HTTP and browser crawls.
- You need a persistent queue or built-in retry and session-management facilities.
- You expect to store output through configurable storage or may later choose an optional hosted deployment.
These are project capabilities described by Crawlee’s own repository, not independently measured results. The available evidence does not establish that Crawlee is faster or more reliable than Scrapy for a given workload. Choose based on workflow and integration needs, then test with your own target and constraints.
Playwright, Selenium, and Puppeteer: browser automation, not the same job
Playwright, Selenium, and Puppeteer are commonly used to drive browsers for tasks such as rendering JavaScript-heavy pages or interacting with elements. They can be part of a scraping solution, but a browser script and a full crawler framework solve different parts of the problem. A browser script may be enough for a small, controlled task; crawling a large set of URLs also requires decisions about queues, retries, link discovery, output, and rate limits.
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Apify’s 2026 survey reports Selenium, Puppeteer, Playwright, and Scrapy among the most-used frameworks by its respondents. That is self-reported use, not a controlled comparison or a global census. The report says respondents mainly came from the Apify and The Web Scraping Club communities, which are composed largely of web-scraping experts. It does not establish a speed ranking.
What the 2026 usage numbers do—and do not—say
In Apify’s survey, 71.7% of respondents said they used Python for scraping, while 17% preferred JavaScript. These figures describe that survey’s audience, not all developers worldwide. They can inform language familiarity, but they do not prove which language or framework is best for a specific project.
The practical choice is therefore based on the job: Scrapy for a structured Python crawling workflow; Crawlee for Python when its combined HTTP/browser interface and queue or session features fit; and browser automation when rendering or interaction is necessary. There is no neutral, named benchmark in the cited material that supports declaring one framework the overall fastest.
Costs, deployment, and responsible crawling
The framework code can be free while operating it is not. A browser consumes compute and requires browser setup; persistent crawls need somewhere to run and store results; proxy or managed browser services may add separate charges. Scrapy’s extension material describes managed request infrastructure such as Zyte API, and Crawlee’s repository describes Apify deployment as an option. These are optional service categories, not prerequisites or a complete cost comparison.
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Start locally when the project is small. If you deploy, estimate costs from the actual workload—URL count, page weight, browser use, concurrency, storage, and retention—rather than assuming “free framework” means free production operation. Keep per-domain request rates reasonable, honor applicable access rules, and do not use browser automation or a managed service to bypass access controls.
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If your task is to capture a page as an image or PDF rather than crawl and extract records, ScreenshotNeo is an alternative to try first. It is a website screenshot API and MCP server: one GET request returns a PNG, JPEG, WebP, or PDF. Before capture it accepts consent banners like a visitor and removes more than 60 known consent platforms, newsletter popups, and chat widgets; each of those steps can be turned off. Bot checks, blank pages, timeouts, failed loads, and cache hits cost nothing, and response headers report the page verdict and billing status. Its MCP server offers take_screenshot, get_page_info, and capture_pdf for Claude, Cursor, and other MCP clients.
For a screenshot of Stripe, for example, the complete cURL request is:
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webp
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Common problems and fixes
The spider gets no useful text
Inspect the actual HTTP response before changing selectors. If it contains only a shell and the content appears after JavaScript runs, use browser rendering such as scrapy-playwright or a browser crawler. If the response contains the content, debug the CSS or XPath selector in Scrapy’s shell.
The crawl sends too many requests
Set appropriate request delays and per-domain concurrency limits, and consider Scrapy’s AutoThrottle. A successful crawl is not a reason to ignore a site’s rules or overload it; reduce activity if the target responds with errors or asks clients to slow down.
Browser-backed jobs consume too much time or compute
Do not render every URL by default. Fetch ordinary HTML directly and reserve browser rendering for pages whose content or interaction requires it. Browser execution is heavier than parsing a response, and the sources here provide no universal cost or speed ratio.
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Retries repeat failures without recovering
Retries help with transient failures, not an invalid URL, blocked access, a broken selector, or a page that requires browser execution. Inspect the failing request and response, distinguish transient network errors from repeatable page or policy errors, and correct the underlying cause before increasing retries.
Frequently asked questions
Is web scraping framework software free to use commercially?
Scrapy is open-source software, and Crawlee for Python’s repository states Apache License 2.0. Check the license and dependencies for the specific project and version you plan to use; this comparison does not establish current license terms for Playwright, Selenium, or Puppeteer.
Should I use Scrapy or Playwright?
They are not direct substitutes. Use Scrapy for crawler structure and data handling; use a browser such as Playwright when a page needs JavaScript execution or interaction. You can combine them through the documented scrapy-playwright extension.
Can I scrape a site just because a tool can load it?
No. Technical capability does not establish authorization. Check the site’s applicable terms and access guidance, and follow the law that applies to your use.
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