Is Crawlee Python as feature-complete as the JavaScript version?

Crawlee Python is rapidly maturing but is not yet as feature-complete as the JavaScript version. While both versions share the same core philosophy and architecture, the JavaScript version has a significant head start in development and offers a broader feature set. However, the Python version includes all essential features needed for production web scraping and is actively catching up.

Current Feature Parity Status

Features Available in Both Versions

Both Crawlee Python and JavaScript support the core functionality that makes Crawlee powerful:

Crawler Types: - BeautifulSoupCrawler (Python) / CheerioCrawler (JavaScript) - Fast HTML parsing - PlaywrightCrawler (both) - Browser automation for JavaScript-rendered pages - HttpCrawler (both) - Low-level HTTP requests with full control

Core Features: - Automatic request queue management - Smart request retry logic with exponential backoff - Session management and cookie handling - Proxy rotation support - Request storage and data persistence - Configurable concurrency controls - Request filtering and deduplication - Automatic rate limiting and politeness policies

Data Management: - Dataset storage (structured data export) - Key-value store (arbitrary data persistence) - Request queue (distributed crawling support)

JavaScript-Exclusive Features

The JavaScript version currently has several advanced features not yet available in Python:

Advanced Crawlers: - PuppeteerCrawler - While Python has PlaywrightCrawler, Puppeteer-specific implementation is JavaScript-only - JSDOMCrawler - Lightweight DOM simulation

Enhanced Features: - More mature adaptive crawling algorithms - Advanced browser pool management - Comprehensive cloud integration (Apify platform) - More extensive middleware system - Better TypeScript type definitions - More plugin ecosystem options

Development Tools: - More comprehensive CLI tools - Advanced debugging utilities - Browser snapshot features for development

Practical Comparison: Code Examples

Python Version Example

from crawlee.playwright_crawler import PlaywrightCrawler, PlaywrightCrawlingContext

async def main():
    crawler = PlaywrightCrawler(
        max_requests_per_crawl=100,
        headless=True,
    )

    @crawler.router.default_handler
    async def request_handler(context: PlaywrightCrawlingContext) -> None:
        # Extract data from the page
        data = await context.page.evaluate('''() => {
            return {
                title: document.querySelector('h1')?.textContent,
                items: Array.from(document.querySelectorAll('.item')).map(el => ({
                    name: el.querySelector('.name')?.textContent,
                    price: el.querySelector('.price')?.textContent
                }))
            }
        }''')

        # Push data to dataset
        await context.push_data(data)

        # Enqueue new requests
        await context.enqueue_links(selector='a.next-page')

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

if __name__ == '__main__':
    import asyncio
    asyncio.run(main())

JavaScript Version Example

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
    maxRequestsPerCrawl: 100,
    headless: true,

    async requestHandler({ page, request, enqueueLinks, pushData }) {
        // Extract data from the page
        const data = await page.evaluate(() => {
            return {
                title: document.querySelector('h1')?.textContent,
                items: Array.from(document.querySelectorAll('.item')).map(el => ({
                    name: el.querySelector('.name')?.textContent,
                    price: el.querySelector('.price')?.textContent
                }))
            };
        });

        // Push data to dataset
        await pushData(data);

        // Enqueue new requests
        await enqueueLinks({ selector: 'a.next-page' });
    },
});

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

As you can see, the API design is remarkably similar, making it easier to switch between versions if needed.

Performance Considerations

Python Version Performance

from crawlee.beautifulsoup_crawler import BeautifulSoupCrawler

async def main():
    # Python version excels with BeautifulSoup for static content
    crawler = BeautifulSoupCrawler(
        max_requests_per_crawl=1000,
        max_request_retries=3,
        # Concurrency control
        max_concurrency=50,
    )

    @crawler.router.default_handler
    async def handler(context):
        # Fast HTML parsing with BeautifulSoup
        title = context.soup.select_one('h1').get_text()
        await context.push_data({'title': title})

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

Performance Characteristics: - BeautifulSoup parsing is generally faster than Cheerio for simple tasks - Python's async/await implementation performs well for I/O-bound operations - Lower memory footprint for simple crawling tasks - Excellent integration with Python's data science ecosystem (pandas, numpy)

JavaScript Version Performance

import { CheerioCrawler } from 'crawlee';

const crawler = new CheerioCrawler({
    maxRequestsPerCrawl: 1000,
    maxRequestRetries: 3,
    maxConcurrency: 50,

    async requestHandler({ $, request, pushData }) {
        // Fast HTML parsing with Cheerio
        const title = $('h1').text();
        await pushData({ title });
    },
});

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

Performance Characteristics: - Cheerio (jQuery-like) is extremely fast for DOM manipulation - Node.js event loop excels at high-concurrency scenarios - Better performance with browser automation at scale - More mature optimization strategies

Browser Automation Comparison

Both versions support browser automation for modern web scraping, but with slight differences:

Python with Playwright

from crawlee.playwright_crawler import PlaywrightCrawler

async def main():
    crawler = PlaywrightCrawler(
        browser_type='chromium',
        headless=True,
        browser_pool_options={
            'max_pages_per_browser': 10,
        }
    )

    @crawler.router.default_handler
    async def handler(context):
        # Wait for dynamic content
        await context.page.wait_for_selector('.dynamic-content')

        # Handle authentication if needed
        await context.page.fill('#username', 'user')
        await context.page.fill('#password', 'pass')
        await context.page.click('button[type="submit"]')

        data = await context.page.inner_text('.result')
        await context.push_data({'result': data})

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

JavaScript with Playwright

import { PlaywrightCrawler } from 'crawlee';

const crawler = new PlaywrightCrawler({
    browserPoolOptions: {
        maxPagesPerBrowser: 10,
    },

    async requestHandler({ page, pushData }) {
        // Wait for dynamic content
        await page.waitForSelector('.dynamic-content');

        // Handle authentication
        await page.fill('#username', 'user');
        await page.fill('#password', 'pass');
        await page.click('button[type="submit"]');

        const data = await page.innerText('.result');
        await pushData({ result: data });
    },
});

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

Ecosystem and Community

Python Advantages

Rich Data Science Integration: Seamless integration with pandas, numpy, scikit-learn
Growing Community: Python's dominance in data science attracts more scraping developers
Familiar Syntax: Python's readability appeals to data scientists and analysts
Library Compatibility: Easy integration with popular Python libraries (requests, httpx, aiohttp)

JavaScript Advantages

Mature Ecosystem: Longer development time means more plugins and extensions
Apify Platform: Deep integration with Apify's cloud scraping platform
NPM Packages: Access to vast npm ecosystem
Browser Native: JavaScript naturally integrates with browser automation tools
Community Size: Larger user base means more examples and solutions

Installation and Setup

Python Installation

# Install from PyPI
pip install crawlee

# Install with Playwright support
pip install 'crawlee[playwright]'

# Install Playwright browsers
playwright install

# Verify installation
python -c "import crawlee; print(crawlee.__version__)"

JavaScript Installation

# Install from npm
npm install crawlee

# Install with Playwright
npm install crawlee playwright

# Verify installation
npx crawlee --version

Which Version Should You Choose?

Choose Python If:

You're working primarily in Python ecosystems
You need tight integration with data science libraries (pandas, numpy)
Your team is more comfortable with Python syntax
You're building data pipelines that connect to Python-based tools
You need the essential features but don't require cutting-edge capabilities

Choose JavaScript If:

You need the most advanced features and latest updates
You're deploying to Apify platform
You're comfortable with TypeScript/JavaScript
You need the most mature browser automation
You want access to the largest plugin ecosystem
You're building high-performance, high-concurrency crawlers

Migration Path

If you start with one version and need to switch, the similar API design makes migration straightforward:

# Python pattern
@crawler.router.default_handler
async def handler(context):
    data = await context.page.evaluate('() => ({ title: document.title })')
    await context.push_data(data)

// JavaScript equivalent
async requestHandler({ page, pushData }) {
    const data = await page.evaluate(() => ({ title: document.title }));
    await pushData(data);
}

Future Roadmap

The Crawlee team is actively working to achieve feature parity between Python and JavaScript versions. Expected improvements for Python include:

Enhanced browser pool management
More sophisticated adaptive crawling
Additional crawler types
Improved cloud platform integration
More comprehensive middleware system

Conclusion

While Crawlee Python isn't yet as feature-complete as the JavaScript version, it provides all the essential functionality needed for professional web scraping projects. The Python version is production-ready, well-maintained, and rapidly improving. For most use cases, the choice between versions should be based on your existing tech stack, team expertise, and specific feature requirements rather than feature completeness alone.

Both versions share the same excellent architecture, making Crawlee a solid choice for handling browser sessions regardless of which language you prefer.

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