Twitter/X Profile Scraper

A browser-based Twitter/X profile discovery and scraping tool.

> Part of ScrapeClaw — a suite of production-ready, agentic social media scrapers for Instagram, YouTube, X/Twitter, and Facebook built with Python & Playwright, no API keys required.

---
name: twitter-scraper
description: Discover and scrape Twitter/X public profiles from your browser.
emoji: 🐦
version: 1.0.2
author: influenza
tags:
  - twitter
  - x
  - scraping
  - social-media
  - profile-discovery
  - influencer-discovery
metadata:
  clawdbot:
    requires:
      bins:
        - python3
        - chromium

    config:
      stateDirs:
        - data/output
        - data/queue
        - thumbnails
      outputFormats:
        - json
        - csv
---

Overview

This skill provides a two-phase Twitter/X scraping system:

1. Profile Discovery — Find Twitter accounts via Google Custom Search API or DuckDuckGo
2. Browser Scraping — Scrape public profiles using Playwright with anti-detection (no login required)

Features

• 🔍 - Discover Twitter/X profiles by location and category
• 🌐 - Full browser simulation for accurate scraping
• 🛡️ - Browser fingerprinting, human behavior simulation, and stealth scripts
• 📊 - Profile info, followers, tweets, engagement data, and media
• 💾 - JSON/CSV export with downloaded thumbnails
• 🔄 - Resume interrupted scraping sessions
• ⚡ - Auto-skip private accounts, low-follower profiles, suspended users
• 🌍 - Built-in residential proxy support with 4 providers

Getting Google API Credentials (Optional)

1. Go to Google Cloud Console
2. Create a new project or select existing
3. Enable "Custom Search API"
4. Create API credentials → API Key
5. Go to Programmable Search Engine
6. Create a search engine with x.com and twitter.com as the sites to search
7. Copy the Search Engine ID

If not configured, discovery falls back to DuckDuckGo (no API key needed).

Usage

Agent Tool Interface

For OpenClaw agent integration, the skill provides JSON output:

# Discover Twitter profiles (returns JSON)
discover --location "Miami" --category "tech" --output json

# Discover profiles in a specific category (returns JSON)
discover --location "New York" --category "crypto" --output json

# Scrape single profile (returns JSON)
scrape --username elonmusk --output json

# Scrape from a queue file
scrape data/queue/Miami_tech_20260220_120000.json

Output Data

Profile Data Structure

{
  "username": "elonmusk",
  "display_name": "Elon Musk",
  "bio": "...",
  "followers": 180000000,
  "following": 800,
  "tweets_count": 45000,
  "is_verified": true,
  "profile_pic_url": "https://...",
  "profile_pic_local": "thumbnails/elonmusk/profile_abc123.jpg",
  "user_location": "Mars & Earth",
  "join_date": "June 2009",
  "website": "https://x.ai",
  "influencer_tier": "mega",
  "category": "tech",
  "scrape_location": "New York",
  "scraped_at": "2026-02-17T12:00:00",
  "recent_tweets": [
    {
      "id": "1234567890",
      "text": "Tweet content...",
      "timestamp": "2026-02-17T10:30:00.000Z",
      "likes": 50000,
      "retweets": 12000,
      "replies": 3000,
      "views": "5.2M",
      "media_urls": ["https://..."],
      "media_local": ["thumbnails/elonmusk/tweet_media_0_def456.jpg"],
      "is_retweet": false,
      "is_reply": false,
      "url": "https://x.com/elonmusk/status/1234567890"
    }
  ]
}

Queue File Structure

{
  "location": "New York",
  "category": "tech",
  "total": 15,
  "usernames": ["user1", "user2", "..."],
  "completed": ["user1"],
  "failed": {"user3": "not_found"},
  "current_index": 2,
  "created_at": "2026-02-17T12:00:00",
  "source": "google_api"
}

Influencer Tiers

File Outputs

• Queue files: data/queue/{location}_{category}_{timestamp}.json
• Scraped data: data/output/{username}.json
• Thumbnails: thumbnails/{username}/profile_.jpg, thumbnails/{username}/tweet_media_.jpg
• Export files: data/export_{timestamp}.json, data/export_{timestamp}.csv

Configuration

Edit config/scraper_config.json:

{
  "proxy": {
    "enabled": false,
    "provider": "brightdata",
    "country": "",
    "sticky": true,
    "sticky_ttl_minutes": 10
  },
  "google_search": {
    "enabled": true,
    "api_key": "",
    "search_engine_id": "",
    "queries_per_location": 3
  },
  "scraper": {
    "headless": false,
    "min_followers": 500,
    "max_tweets": 20,
    "download_thumbnails": true,
    "max_thumbnails": 6,
    "delay_between_profiles": [4, 8],
    "timeout": 60000
  },
  "cities": ["New York", "Los Angeles", "Miami", "Chicago"],
  "categories": ["tech", "politics", "sports", "entertainment", "news", "crypto"]
}

Filters Applied

The scraper automatically filters out:

• ❌ Suspended or deactivated accounts
• ❌ Protected (private) accounts
• ❌ Profiles with < 500 followers (configurable)
• ❌ Non-existent usernames
• ❌ Already scraped entries (deduplication)

Anti-Detection

The scraper uses multiple anti-detection techniques:

• Browser fingerprinting — 4 rotating fingerprint profiles (viewport, user agent, timezone, WebGL, etc.)
• Stealth JavaScript — Hides navigator.webdriver, spoofs plugins/languages/hardware, canvas noise, fake chrome object
• Human behavior simulation — Random delays, mouse movements, scrolling patterns
• Network randomization — Variable timing between requests
• Login wall handling — Automatically dismisses Twitter's login prompts and overlays

Troubleshooting

No Profiles Discovered

• Check Google API key and quota
• Verify Search Engine ID is configured for x.com and twitter.com
• Try different location/category combinations
• If Google fails, DuckDuckGo fallback is used automatically

Rate Limiting

• Reduce scraping speed (increase delays in config)
• Run during off-peak hours
• Use a residential proxy (see below)

Login Wall Issues

• The scraper automatically dismisses login prompts
• If content is blocked, try running with --headless disabled to debug visually

🌐 Residential Proxy Support

Why Use a Residential Proxy?

Running a scraper at scale without a residential proxy will get your IP blocked fast. Here's why proxies are essential for long-running scrapes:

Recommended Proxy Providers

We have affiliate partnerships with top residential proxy providers. Using these links supports continued development of this skill:

Setup Steps

1. Get Your Proxy Credentials

Sign up with any provider above, then grab:

• Username (from your provider dashboard)
• Password (from your provider dashboard)
• Host and Port are pre-configured per provider (or use custom)

2. Configure via Environment Variables

export PROXY_ENABLED=true
export PROXY_PROVIDER=brightdata    # brightdata | iproyal | stormproxies | netnut | custom
export PROXY_USERNAME=your_user
export PROXY_PASSWORD=your_pass
export PROXY_COUNTRY=us             # optional: two-letter country code
export PROXY_STICKY=true            # optional: keep same IP per session

3. Provider-Specific Host/Port Defaults

These are auto-configured when you set the provider name:

Override with PROXY_HOST / PROXY_PORT env vars if your plan uses a different gateway.

4. Custom Proxy Provider

For any other proxy service, set provider to custom and supply host/port manually:

{
  "proxy": {
    "enabled": true,
    "provider": "custom",
    "host": "your.proxy.host",
    "port": 8080,
    "username": "user",
    "password": "pass"
  }
}

Running the Scraper with Proxy

Once configured, the scraper picks up the proxy automatically — no extra flags needed:

# Discover and scrape as usual — proxy is applied automatically
python main.py discover --location "Miami" --category "tech"
python main.py scrape --username elonmusk

# The log will confirm proxy is active:
# INFO - Proxy enabled: <ProxyManager provider=brightdata enabled host=brd.superproxy.io:22225>
# INFO - Browser using proxy: brightdata → brd.superproxy.io:22225

Using the Proxy Manager Programmatically

from proxy_manager import ProxyManager

# From config (auto-reads config/scraper_config.json)
pm = ProxyManager.from_config()

# From environment variables
pm = ProxyManager.from_env()

# Manual construction
pm = ProxyManager(
    provider="brightdata",
    username="your_user",
    password="your_pass",
    country="us",
    sticky=True
)

# For Playwright browser context
proxy = pm.get_playwright_proxy()
# → {"server": "http://brd.superproxy.io:22225", "username": "user-country-us-session-abc123", "password": "pass"}

# For requests / aiohttp
proxies = pm.get_requests_proxy()
# → {"http": "http://user:pass@host:port", "https": "http://user:pass@host:port"}

# Force new IP (rotates session ID)
pm.rotate_session()

# Debug info
print(pm.info())

Best Practices for Long-Running Scrapes

1. Use sticky sessions — Twitter requires consistent IPs during a browsing session. Set "sticky": true.
2. Target the right country — Set "country": "us" (or your target region) so Twitter serves content in the expected locale.
3. Combine with existing anti-detection — This scraper already has fingerprinting, stealth scripts, and human behavior simulation. The proxy is the final layer.
4. Rotate sessions between batches — Call pm.rotate_session() between large batches of profiles to get a fresh IP.
5. Use delays — Even with proxies, respect delay_between_profiles in config (default 4-8s) to avoid aggressive patterns.
6. Monitor your proxy dashboard — All providers have dashboards showing bandwidth usage and success rates.

Notes

• No login required — Only scrapes publicly visible content
• Checkpoint/resume — Queue files track progress; interrupted scrapes can be resumed with --resume
• Rate limiting — Waits 60s on rate limit, stops on daily limit detection
• Twitter selectors — Uses data-testid attributes (stable across UI changes) with fallbacks to aria-label and structural selectors