caniscrape 0.1.7

Analyze website anti-bot protections before you scrape

caniscrape 🔍

Know before you scrape. Analyze any website's anti-bot protections in seconds.

Stop wasting hours building scrapers only to discover the site has Cloudflare + JavaScript rendering + CAPTCHA + rate limiting. caniscrape does reconnaissance upfront so you know exactly what you're dealing with before writing a single line of code.

🎯 What It Does

caniscrape analyzes a URL and tells you:

• What protections are active (WAF, CAPTCHA, rate limits, TLS fingerprinting, honeypots)
• Difficulty score (0-10 scale: Easy → Very Hard)
• Specific recommendations on what tools/proxies you'll need
• Estimated complexity so you can decide: build it yourself or use a service

🚀 Quick Start

Installation

pip install caniscrape

Required dependency:

# Install wafw00f (WAF detection)
pipx install wafw00f

# Install Playwright browsers (for JS detection)
playwright install chromium

Basic Usage

caniscrape https://example.com

Example Output

🔬 What It Analyzes

1. WAF Detection

Identifies Web Application Firewalls (Cloudflare, Akamai, Imperva, DataDome, PerimeterX, etc.)

2. Rate Limiting

• Tests with burst and sustained traffic patterns
• Detects HTTP 429s, timeouts, throttling, soft bans
• Determines blocking threshold (requests/min)

3. JavaScript Rendering

• Compares content with/without JS execution
• Detects SPAs (React, Vue, Angular)
• Calculates percentage of content missing without JS

4. CAPTCHA Detection

• Scans for reCAPTCHA, hCaptcha, Cloudflare Turnstile
• Tests if CAPTCHA appears on load or after rate limiting
• Monitors network traffic for challenge endpoints

5. TLS Fingerprinting

• Compares standard Python clients vs browser-like clients
• Detects if site blocks based on TLS handshake signatures

6. Behavioral Analysis

• Scans for invisible "honeypot" links (bot traps)
• Detects if site is monitoring mouse/scroll behavior

7. robots.txt

• Checks scraping permissions
• Extracts recommended crawl-delay

🛠️ Advanced Usage

Aggressive WAF Detection

# Find ALL WAFs (slower, may trigger rate limits)
caniscrape https://example.com --find-all

Browser Impersonation

# Use curl_cffi for better stealth (slower but more likely to succeed)
caniscrape https://example.com --impersonate

Deep Honeypot Scanning

# Check 2/3 of links (more accurate, slower)
caniscrape https://example.com --thorough

# Check ALL links (most accurate, very slow on large sites)
caniscrape https://example.com --deep

Combine Options

caniscrape https://example.com --impersonate --find-all --thorough

📊 Difficulty Scoring

The tool calculates a 0-10 difficulty score based on:

Factor	Impact
CAPTCHA on page load	+5 points
CAPTCHA after rate limit	+4 points
DataDome/PerimeterX WAF	+4 points
Akamai/Imperva WAF	+3 points
Aggressive rate limiting	+3 points
Cloudflare WAF	+2 points
Honeypot traps detected	+2 points
TLS fingerprinting active	+1 point

Score interpretation:

• 0-2: Easy (basic scraping will work)
• 3-4: Medium (need some precautions)
• 5-7: Hard (requires advanced techniques)
• 8-10: Very Hard (consider using a service)

🔧 Installation Details

System Requirements

• Python 3.9+
• pip or pipx

Full Installation

# 1. Install caniscrape
pip install caniscrape

# 2. Install wafw00f (WAF detection)
# Option A: Using pipx (recommended)
python -m pip install --user pipx
pipx install wafw00f

# Option B: Using pip
pip install wafw00f

# 3. Install Playwright browsers (for JS/CAPTCHA/behavioral detection)
playwright install chromium

Dependencies

Core dependencies (installed automatically):

• click - CLI framework
• rich - Terminal formatting
• aiohttp - Async HTTP requests
• beautifulsoup4 - HTML parsing
• playwright - Headless browser automation
• curl_cffi - Browser impersonation

External tools (install separately):

• wafw00f - WAF detection

🎓 Use Cases

For Developers

• Before building a scraper: Check if it's even feasible
• Debugging scraper issues: Identify what protection broke your scraper
• Client estimates: Give accurate time/cost estimates for scraping projects

For Data Engineers

• Pipeline planning: Know what infrastructure you'll need (proxies, CAPTCHA solvers)
• Cost estimation: Calculate proxy/CAPTCHA costs before committing to a data source

For Researchers

• Site selection: Find the easiest data sources for your research
• Compliance: Check robots.txt before scraping

⚠️ Limitations & Disclaimers

What It Can't Detect

• Dynamic protections: Some sites only trigger defenses under specific conditions
• Behavioral AI: Advanced ML-based bot detection that adapts in real-time
• Account-based restrictions: Protections that only activate for logged-in users

Legal & Ethical Notes

• This tool is for reconnaissance only - it does not bypass protections
• Always respect robots.txt and terms of service
• Some sites may consider aggressive scanning hostile - use --find-all and --deep sparingly
• You are responsible for how you use this tool and any scrapers you build

Technical Notes

• Analysis takes 30-60 seconds per URL
• Some checks require making multiple requests (may trigger rate limits)
• Results are a snapshot - protections can change over time

🤝 Contributing

Found a bug? Have a feature request? Contributions are welcome!

1. Fork the repo
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

MIT License - see LICENSE file for details

🙏 Acknowledgments

Built on top of:

• wafw00f - WAF detection
• Playwright - Browser automation
• curl_cffi - Browser impersonation

📬 Contact

Questions? Feedback? Open an issue on GitHub.

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Remember: This tool tells you HOW HARD it will be to scrape. It doesn't do the scraping for you. Use it to make informed decisions before you start building.