crawl4ai（crawl4ai 命令行）

Crawl4AI

Overview

Crawl4AI provides comprehensive web crawling and data extraction capabilities. This skill supports both CLI (recommended for quick tasks) and Python SDK (for programmatic control).

Choose your interface:

• CLI (crwl) - Quick, scriptable commands: CLI Guide
• Python SDK - Full programmatic control: SDK Guide

Quick Start

Installation

pip install crawl4ai
crawl4ai-setup

# Verify installation
crawl4ai-doctor

CLI (Recommended)

# Basic crawling - returns markdown
crwl https://example.com

# Get markdown output
crwl https://example.com -o markdown

# JSON output with cache bypass
crwl https://example.com -o json -v --bypass-cache

# See more examples
crwl --example

Python SDK

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])

asyncio.run(main())

For SDK configuration details: SDK Guide - Configuration (lines 61-150)

Core Concepts

Configuration Layers

Both CLI and SDK use the same underlying configuration:

Key Parameters

Browser Configuration:

• headless: Run with/without GUI
• viewport_width/height: Browser dimensions
• user_agent: Custom user agent
• proxy_config: Proxy settings

Crawler Configuration:

• page_timeout: Max page load time (ms)
• wait_for: CSS selector or JS condition to wait for
• cache_mode: bypass, enabled, disabled
• js_code: JavaScript to execute
• css_selector: Focus on specific element

For complete parameters: CLI Config | SDK Config

Output Content

Every crawl returns:

• markdown - Clean, formatted markdown
• html - Raw HTML
• links - Internal and external links discovered
• media - Images, videos, audio found
• extracted_content - Structured data (if extraction configured)

Markdown Generation (Primary Use Case)

Crawl4AI excels at generating clean, well-formatted markdown:

CLI

# Basic markdown
crwl https://docs.example.com -o markdown

# Filtered markdown (removes noise)
crwl https://docs.example.com -o markdown-fit

# With content filter
crwl https://docs.example.com -f filter_bm25.yml -o markdown-fit

Filter configuration:

# filter_bm25.yml (relevance-based)
type: "bm25"
query: "machine learning tutorials"
threshold: 1.0

Python SDK

from crawl4ai.content_filter_strategy import BM25ContentFilter
from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator

bm25_filter = BM25ContentFilter(user_query="machine learning", bm25_threshold=1.0)
md_generator = DefaultMarkdownGenerator(content_filter=bm25_filter)

config = CrawlerRunConfig(markdown_generator=md_generator)
result = await crawler.arun(url, config=config)

print(result.markdown.fit_markdown)  # Filtered
print(result.markdown.raw_markdown)  # Original

For content filters: Content Processing (lines 2481-3101)

Data Extraction

1. Schema-Based CSS Extraction (Most Efficient)

No LLM required - fast, deterministic, cost-free.

CLI:

# Generate schema once (uses LLM)
python scripts/extraction_pipeline.py --generate-schema https://shop.com "extract products"

# Use schema for extraction (no LLM)
crwl https://shop.com -e extract_css.yml -s product_schema.json -o json

Schema format:

{
  "name": "products",
  "baseSelector": ".product-card",
  "fields": [
    {"name": "title", "selector": "h2", "type": "text"},
    {"name": "price", "selector": ".price", "type": "text"},
    {"name": "link", "selector": "a", "type": "attribute", "attribute": "href"}
  ]
}

2. LLM-Based Extraction

For complex or irregular content:

CLI:

# extract_llm.yml
type: "llm"
provider: "openai/gpt-4o-mini"
instruction: "Extract product names and prices"
api_token: "your-token"

crwl https://shop.com -e extract_llm.yml -o json

For extraction details: Extraction Strategies (lines 4522-5429)

Advanced Patterns

Dynamic Content (JavaScript-Heavy Sites)

CLI:

crwl https://example.com -c "wait_for=css:.ajax-content,scan_full_page=true,page_timeout=60000"

Crawler config:

# crawler.yml
wait_for: "css:.ajax-content"
scan_full_page: true
page_timeout: 60000
delay_before_return_html: 2.0

Multi-URL Processing

CLI (sequential):

for url in url1 url2 url3; do crwl "$url" -o markdown; done

Python SDK (concurrent):

urls = ["https://site1.com", "https://site2.com", "https://site3.com"]
results = await crawler.arun_many(urls, config=config)

For batch processing: arun_many() Reference (lines 1057-1224)

Session & Authentication

CLI:

# login_crawler.yml
session_id: "user_session"
js_code: |
  document.querySelector('#username').value = 'user';
  document.querySelector('#password').value = 'pass';
  document.querySelector('#submit').click();
wait_for: "css:.dashboard"

# Login
crwl https://site.com/login -C login_crawler.yml

# Access protected content (session reused)
crwl https://site.com/protected -c "session_id=user_session"

For session management: Advanced Features (lines 5429-5940)

Anti-Detection & Proxies

CLI:

# browser.yml
headless: true
proxy_config:
  server: "http://proxy:8080"
  username: "user"
  password: "pass"
user_agent_mode: "random"

crwl https://example.com -B browser.yml

Common Use Cases

Google Search Scraping

# Search Google and get results as JSON
python scripts/google_search.py "your search query" 20

# Example
python scripts/google_search.py "2026年Go语言展望" 20

The script extracts:

• Search result titles
• URLs (cleaned, removes Google redirects)
• Descriptions/snippets
• Site names

Output is saved to google_search_results.json and printed to stdout.

Documentation to Markdown

crwl https://docs.example.com -o markdown > docs.md

E-commerce Product Monitoring

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

# Monitor (no LLM costs)
crwl https://shop.com -e extract_css.yml -s schema.json -o json

News Aggregation

# Multiple sources with filtering
for url in news1.com news2.com news3.com; do
  crwl "https://$url" -f filter_bm25.yml -o markdown-fit
done

Interactive Q&A

# First view content
crwl https://example.com -o markdown

# Then ask questions
crwl https://example.com -q "What are the main conclusions?"
crwl https://example.com -q "Summarize the key points"

Resources

Provided Scripts

• scripts/google_search.py - Google search scraper with JSON output
• scripts/extraction_pipeline.py - Schema generation and extraction
• scripts/basic_crawler.py - Simple markdown extraction
• scripts/batch_crawler.py - Multi-URL processing

Reference Documentation

Best Practices

1. Start with CLI for quick tasks, SDK for automation
2. Use schema-based extraction - 10-100x more efficient than LLM
3. Enable caching during development - --bypass-cache only when needed
4. Set appropriate timeouts - 30s normal, 60s+ for JS-heavy sites
5. Use content filters for cleaner, focused markdown
6. Respect rate limits - Add delays between requests

Troubleshooting

JavaScript Not Loading

crwl https://example.com -c "wait_for=css:.dynamic-content,page_timeout=60000"

Bot Detection Issues

crwl https://example.com -B browser.yml

# browser.yml
headless: false
viewport_width: 1920
viewport_height: 1080
user_agent: "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"

Content Not Extracted

# Debug: see full output
crwl https://example.com -o all -v

# Try different wait strategy
crwl https://example.com -c "wait_for=js:document.querySelector('.content')!==null"

Session Issues

# Verify session
crwl https://site.com -c "session_id=test" -o all | grep -i session

For comprehensive API documentation, see Complete SDK Reference.