crawl4ai

Crawl4AI

Overview

This skill provides comprehensive support for web crawling and data extraction using the Crawl4AI library, including the complete SDK reference, ready-to-use scripts for common patterns, and optimized workflows for efficient data extraction.

Quick Start

Installation Check

# Verify installation
crawl4ai-doctor

# If issues, run setup
crawl4ai-setup

Basic First Crawl

import asyncio
from crawl4ai import AsyncWebCrawler

async def main():
    async with AsyncWebCrawler() as crawler:
        result = await crawler.arun("https://example.com")
        print(result.markdown[:500])  # First 500 chars

asyncio.run(main())

Using Provided Scripts

# Simple markdown extraction
python scripts/basic_crawler.py https://example.com

# Batch processing
python scripts/batch_crawler.py urls.txt

# Data extraction
python scripts/extraction_pipeline.py --generate-schema https://shop.com "extract products"

Core Crawling Fundamentals

1. Basic Crawling

Understanding the core components for any crawl:

from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig

# Browser configuration (controls browser behavior)
browser_config = BrowserConfig(
    headless=True,  # Run without GUI
    viewport_width=1920,
    viewport_height=1080,
    user_agent="custom-agent"  # Optional custom user agent
)

# Crawler configuration (controls crawl behavior)
crawler_config = CrawlerRunConfig(
    page_timeout=30000,  # 30 seconds timeout
    screenshot=True,  # Take screenshot
    remove_overlay_elements=True  # Remove popups/overlays
)

# Execute crawl with arun()
async with AsyncWebCrawler(config=browser_config) as crawler:
    result = await crawler.arun(
        url="https://example.com",
        config=crawler_config
    )

    # CrawlResult contains everything
    print(f"Success: {result.success}")
    print(f"HTML length: {len(result.html)}")
    print(f"Markdown length: {len(result.markdown)}")
    print(f"Links found: {len(result.links)}")