How does Crawlee compare to Scrapy for web scraping?

When choosing a web scraping framework, developers often compare Crawlee and Scrapy—two powerful but fundamentally different tools. While Scrapy has been the go-to Python framework for over a decade, Crawlee represents a modern Node.js approach with built-in browser automation. Understanding their differences is crucial for selecting the right tool for your project.

Core Technology and Language

The most fundamental difference between these frameworks is their underlying technology stack.

Scrapy is a Python-based framework that has been battle-tested since 2008. It's built on Twisted, an event-driven networking engine, making it excellent for HTTP-based scraping at scale.

import scrapy

class ProductSpider(scrapy.Spider):
    name = 'products'
    start_urls = ['https://example.com/products']

    def parse(self, response):
        for product in response.css('div.product'):
            yield {
                'name': product.css('h2::text').get(),
                'price': product.css('span.price::text').get(),
            }

        next_page = response.css('a.next::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)

Crawlee is a modern Node.js/TypeScript framework developed by Apify. It's designed with JavaScript-rendered websites in mind and provides seamless integration with Puppeteer, Playwright, and Cheerio.

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
    async requestHandler({ request, page, enqueueLinks }) {
        const products = await page.$$eval('div.product', elements =>
            elements.map(el => ({
                name: el.querySelector('h2')?.textContent,
                price: el.querySelector('span.price')?.textContent,
            }))
        );

        await enqueueLinks({
            selector: 'a.next',
        });

        console.log(products);
    },
});

await crawler.run(['https://example.com/products']);

Browser Automation and JavaScript Rendering

One of the most significant differences lies in how each framework handles modern, JavaScript-heavy websites.

Scrapy's Approach

Scrapy is primarily designed for static HTML scraping. While it can handle JavaScript-rendered content through middleware like Scrapy-Splash or Scrapy-Playwright, these require additional setup and external services.

# Scrapy with Playwright middleware
from scrapy_playwright.page import PageMethod

class DynamicSpider(scrapy.Spider):
    name = 'dynamic'

    def start_requests(self):
        yield scrapy.Request(
            'https://example.com',
            meta={
                'playwright': True,
                'playwright_page_methods': [
                    PageMethod('wait_for_selector', 'div.loaded'),
                ],
            }
        )

Crawlee's Native Browser Support

Crawlee has first-class support for browser automation built directly into the framework. You can easily switch between different crawling modes depending on your needs:

import { CheerioCrawler, PlaywrightCrawler } from 'crawlee';

// For static HTML - fast and lightweight
const cheerioCrawler = new CheerioCrawler({
    async requestHandler({ request, $ }) {
        const title = $('title').text();
        console.log(title);
    },
});

// For JavaScript-heavy sites - full browser automation
const playwrightCrawler = new PlaywrightCrawler({
    async requestHandler({ request, page }) {
        await page.waitForSelector('.dynamic-content');
        const title = await page.title();
        console.log(title);
    },
});

This flexibility makes Crawlee particularly effective for handling AJAX requests and dynamic content without extensive configuration.

Performance and Scalability

Scrapy's Performance Profile

Scrapy excels at high-speed, large-scale HTTP scraping. Its asynchronous architecture built on Twisted can handle thousands of concurrent requests efficiently:

# Scrapy configuration for high-performance scraping
CONCURRENT_REQUESTS = 32
CONCURRENT_REQUESTS_PER_DOMAIN = 16
DOWNLOAD_DELAY = 0.25
AUTOTHROTTLE_ENABLED = True
AUTOTHROTTLE_START_DELAY = 0.5
AUTOTHROTTLE_MAX_DELAY = 3.0

For purely HTTP-based scraping, Scrapy typically outperforms browser-based solutions by 10-50x in terms of speed and resource usage.

Crawlee's Intelligent Resource Management

Crawlee prioritizes reliability and browser automation over raw HTTP speed. It includes sophisticated features like:

• AutoscaledPool: Automatically adjusts concurrency based on system resources
• RequestQueue: Persistent storage for request management
• SessionPool: Manages browser sessions and cookies intelligently
• Smart rate limiting: Adapts to target website performance

const crawler = new PlaywrightCrawler({
    maxRequestsPerCrawl: 1000,
    maxConcurrency: 10,
    autoscaledPoolOptions: {
        maxConcurrency: 20,
        desiredConcurrency: 10,
    },
    sessionPoolOptions: {
        maxPoolSize: 100,
        sessionOptions: {
            maxUsageCount: 50,
        },
    },
});

Data Storage and Export

Scrapy's Export Pipeline

Scrapy provides built-in item pipelines with support for various formats:

# settings.py
FEEDS = {
    'products.json': {
        'format': 'json',
        'encoding': 'utf8',
        'store_empty': False,
        'indent': 4,
    },
    'products.csv': {
        'format': 'csv',
    },
}

Crawlee's Dataset System

Crawlee includes a Dataset API that automatically handles data storage with both local and cloud options:

import { Dataset } from 'crawlee';

const crawler = new PlaywrightCrawler({
    async requestHandler({ request, page }) {
        const data = await page.evaluate(() => ({
            title: document.title,
            url: window.location.href,
        }));

        // Data is automatically stored and deduplicated
        await Dataset.pushData(data);
    },
});

// Export data after crawling
const dataset = await Dataset.open();
const data = await dataset.getData();
console.log(data.items);

Request Management and Queue Systems

Scrapy's Request Handling

Scrapy uses a priority queue system with support for distributed crawling through Redis (Scrapy-Redis):

def parse(self, response):
    # Set priority for important requests
    yield scrapy.Request(
        'https://example.com/important',
        callback=self.parse_important,
        priority=10,
    )

Crawlee's Persistent Queues

Crawlee provides automatic request deduplication and persistence, ensuring no requests are lost even if your crawler crashes:

const crawler = new PlaywrightCrawler({
    async requestHandler({ request, enqueueLinks }) {
        // Automatically deduplicates and persists requests
        await enqueueLinks({
            selector: 'a[href]',
            transformRequestFunction: (req) => {
                // Add custom logic before enqueuing
                req.userData.timestamp = Date.now();
                return req;
            },
        });
    },
});

Anti-Scraping and Stealth Features

Scrapy's Approach

Scrapy requires manual configuration and third-party middleware for anti-bot measures:

# settings.py
DOWNLOADER_MIDDLEWARES = {
    'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware': None,
    'scrapy_user_agents.middlewares.RandomUserAgentMiddleware': 400,
    'scrapy.downloadermiddlewares.retry.RetryMiddleware': 90,
    'scrapy_proxies.RandomProxy': 100,
}

USER_AGENT_LIST = [
    'Mozilla/5.0 (Windows NT 10.0; Win64; x64)...',
    'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7)...',
]

Crawlee's Built-in Stealth

Crawlee includes sophisticated anti-detection features out of the box, particularly when using browser automation with Puppeteer:

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
    // Automatically rotates user agents, handles cookies, etc.
    useSessionPool: true,
    persistCookiesPerSession: true,

    // Use headless browsers with stealth plugins
    launchContext: {
        launchOptions: {
            headless: true,
        },
    },

    preNavigationHooks: [
        async ({ page }) => {
            // Custom stealth techniques
            await page.setExtraHTTPHeaders({
                'Accept-Language': 'en-US,en;q=0.9',
            });
        },
    ],
});

Error Handling and Retry Logic

Scrapy's Retry Middleware

# settings.py
RETRY_TIMES = 3
RETRY_HTTP_CODES = [500, 502, 503, 504, 522, 524, 408, 429]

# Custom retry logic
class CustomRetryMiddleware:
    def process_response(self, request, response, spider):
        if response.status in [403, 429]:
            return self._retry(request, spider)
        return response

Crawlee's Automatic Retries

const crawler = new PlaywrightCrawler({
    maxRequestRetries: 5,
    requestHandlerTimeoutSecs: 60,

    // Custom error handling
    failedRequestHandler: async ({ request }) => {
        console.log(`Request ${request.url} failed after ${request.retryCount} retries`);
        // Save failed URLs for later processing
        await Dataset.pushData({
            url: request.url,
            errors: request.errorMessages,
        });
    },
});

Ecosystem and Extensions

Scrapy's Mature Ecosystem

Scrapy benefits from over 15 years of development with extensive third-party packages:

• scrapy-splash: JavaScript rendering
• scrapy-redis: Distributed crawling
• scrapy-mongodb: MongoDB pipeline
• scrapy-rotating-proxies: Proxy rotation
• scrapyd: Deployment and scheduling

Crawlee's Modern Integrations

Crawlee is tightly integrated with the Apify platform but works standalone. It includes:

• Native Playwright and Puppeteer support
• Built-in proxy rotation (including residential proxies)
• Automatic storage (local, cloud, S3, etc.)
• TypeScript support with excellent type definitions
• Integration with popular databases and APIs

Which Should You Choose?

Choose Scrapy if: - You prefer Python and have existing Python infrastructure - You're scraping primarily static HTML websites - You need maximum speed for large-scale HTTP scraping - You want a mature ecosystem with extensive documentation - You're comfortable with asynchronous Python (Twisted)

Choose Crawlee if: - You work in a Node.js/JavaScript environment - You're scraping modern JavaScript-heavy websites - You need built-in browser automation without complex setup - You want TypeScript support and modern async/await syntax - You value automatic resource management and anti-detection features - You're dealing with single-page applications

Using a Web Scraping API Alternative

Both frameworks require significant setup, maintenance, and infrastructure. For production use cases, consider using a web scraping API that handles browser rendering, proxy rotation, and anti-bot bypass automatically. This approach can save development time and reduce operational complexity while providing consistent results.

Conclusion

Crawlee and Scrapy represent different philosophies in web scraping. Scrapy offers Python-based, high-performance HTTP scraping with a mature ecosystem. Crawlee provides modern JavaScript/TypeScript development with native browser automation and intelligent resource management.

For static HTML at scale, Scrapy remains hard to beat. For modern web applications requiring JavaScript execution and sophisticated anti-detection, Crawlee's integrated approach offers significant advantages. Many teams use both tools strategically—Scrapy for fast HTTP scraping and Crawlee when browser automation is essential.

Ultimately, the choice depends on your tech stack, target websites, and specific requirements. Both frameworks are production-ready and backed by active communities, making either a solid choice for serious web scraping projects.