# 发现 Facebook 页面（返回 JSON）
discover --location "Miami" --category "restaurant" --type page --output json
# 发现 Facebook 群组（返回 JSON）
discover --location "New York" --category "fitness" --type group --output json
# 抓取单个页面（返回 JSON）
scrape --page-name examplebusiness --output json
# 抓取单个群组（返回 JSON）
scrape --page-name examplegroup --type group --output json

{
  "page_name": "example_business",
  "display_name": "Example Business",
  "entity_type": "page",
  "category": "Restaurant",
  "subcategory": "Italian Restaurant",
  "about": "Family-owned Italian restaurant since 1985",
  "followers": 45000,
  ...
}

# 克隆仓库
git clone https://github.com/influenza-0/facebook-scraper.git
cd facebook-scraper
# 安装依赖
pip install -r requirements.txt

# 可选：Google API 凭证（用于高级发现）
export GOOGLE_API_KEY="your_api_key"
export GOOGLE_CSE_ID="your_cse_id"
# 可选：代理
export HTTP_PROXY="http://proxy:port"
export HTTPS_PROXY="http://proxy:port"

# 按位置发现页面
python -m src.main discover --location "Los Angeles" --category "restaurant" --type page
# 按类别发现群组
python -m src.main discover --location "San Francisco" --category "technology" --type group

# 抓取页面
python -m src.main scrape --page-name examplebusiness --type page
# 抓取群组
python -m src.main scrape --page-name examplegroup --type group

python -m src.main scrape --page-name examplebusiness --output json

python -m src.main scrape --page-name examplebusiness --output csv

python -m src.main scrape --page-name examplebusiness --download-thumbnails

python -m src.main scrape --page-name examplebusiness --resume

# 跳过低赞页面
python -m src.main discover --location "Miami" --category "restaurant" --min-likes 1000
# 跳过私密群组
python -m src.main discover --location "New York" --category "fitness" --skip-private

playwright install chromium

# Facebook Page & Group Scraper

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.

A browser-based Facebook page and group discovery and scraping tool.

---
name: facebook-scraper
description: Discover and scrape Facebook pages and public groups from your browser.
emoji: 📘
version: 1.0.0
author: influenza
tags:
  - facebook
  - scraping
  - social-media
  - page-discovery
  - group-discovery
  - business-pages
metadata:
  clawdbot:
    requires:
      bins:
        - python3
        - chromium
    config:
      stateDirs:
        - data/output
        - data/queue
        - thumbnails
      outputFormats:
        - json
        - csv

Overview

This skill provides a two-phase Facebook scraping system:

• Page/Group Discovery
• Browser Scraping

Features

• 🔍 - Discover Facebook pages and groups by location and category
• 🌐 - Full browser simulation for accurate scraping
• 🛡️ - Browser fingerprinting, human behavior simulation, and stealth scripts
• 📊 - Page/group info, stats, images, and engagement data
• 💾 - JSON/CSV export with downloaded thumbnails
• 🔄 - Resume interrupted scraping sessions
• ⚡ - Auto-skip private groups, low-like pages, empty profiles
• 📂 - Supports pages, groups, and public profiles via --type flag

Getting Google API Credentials (Optional)

• Go to Google Cloud Console
• Create a new project or select existing
• Enable "Custom Search API"
• Create API credentials → API Key
• Go to Programmable Search Engine
• Create a search engine with facebook.com as the site to search
• Copy the Search Engine ID

Usage

Agent Tool Interface

For OpenClaw agent integration, the skill provides JSON output:

# Discover Facebook pages (returns JSON)
discover --location "Miami" --category "restaurant" --type page --output json
# Discover Facebook groups (returns JSON)
discover --location "New York" --category "fitness" --type group --output json
# Scrape single page (returns JSON)
scrape --page-name examplebusiness --output json
# Scrape single group (returns JSON)
scrape --page-name examplegroup --type group --output json

Output Data

Page/Group Data Structure

{
  "page_name": "example_business",
  "display_name": "Example Business",
  "entity_type": "page",
  "category": "Restaurant",
  "subcategory": "Italian Restaurant",
  "about": "Family-owned Italian restaurant since 1985",
  "followers": 45000,
  "page_likes": 42000,
  "location": "Miami, FL",
  "address": "123 Main St, Miami, FL 33101",
  "phone": "+1-555-0123",
  "email": "info@example.com",
  "website": "https://example.com",
  "hours": "Mon-Sat 11AM-10PM",
  "is_verified": false,
  "page_tier": "mid",
  "profile_pic_local": "thumbnails/example_business/profile_abc123.jpg",
  "cover_photo_local": "thumbnails/example_business/cover_def456.jpg",
  "recent_posts": [
    {"post_url": "https://facebook.com/example_business/posts/123", "reactions": 320, "comments": 45, "shares": 12}
  ],
  "scrape_timestamp": "2026-02-20T14:30:00"
}

Group Data Structure

{
  "page_name": "example_group",
  "display_name": "Miami Fitness Community",
  "entity_type": "group",
  "about": "A community for fitness enthusiasts in Miami",
  "members": 15000,
  "privacy": "Public",
  "posts_per_day": 25,
  "location": "Miami",
  "page_tier": "mid",
  "profile_pic_local": "thumbnails/example_group/profile_abc123.jpg",
  "cover_photo_local": "thumbnails/example_group/cover_def456.jpg",
  "scrape_timestamp": "2026-02-20T14:30:00"
}

Page Tiers

Tier	Likes/Members Range
nano	< 1,000
micro	1,000 - 10,000
mid	10,000 - 100,000
macro	100,000 - 1M
mega	> 1,000,000

File Outputs

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

Configuration

Edit config/scraper_config.json:

{
  "google_search": {
    "enabled": true,
    "api_key": "",
    "search_engine_id": "",
    "queries_per_location": 3
  },
  "scraper": {
    "headless": false,
    "min_likes": 1000,
    "download_thumbnails": true,
    "max_thumbnails": 6
  },
  "cities": ["New York", "Los Angeles", "Miami", "Chicago"],
  "categories": ["restaurant", "retail", "fitness", "real-estate", "healthcare", "beauty"]
}

Filters Applied

The scraper automatically filters out:

• ❌ Private groups
• ❌ Pages with < 1,000 likes (configurable)
• ❌ Deactivated or removed pages
• ❌ Non-existent pages/groups
• ❌ Already scraped entries (deduplication)

Troubleshooting

Login Issues

• Ensure credentials are correct
• Handle verification codes when prompted
• Wait if rate limited (the script will auto-retry)

No Pages Discovered

• Check Google API key and quota
• Verify Search Engine ID is configured for facebook.com
• Try different location/category combinations

Rate Limiting

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

---

🌐 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:

Advantage	Description
Avoid IP Bans	Residential IPs look like real household users, not data-center bots. Facebook is far less likely to flag them.
Automatic IP Rotation	Each request (or session) gets a fresh IP, so rate-limits never stack up on one address.
Geo-Targeting	Route traffic through a specific country/city so scraped content matches the target audience's locale.
Sticky Sessions	Keep the same IP for a configurable window (e.g. 10 min) — critical for maintaining a Facebook login session.
Higher Success Rate	Rotating residential IPs deliver 95%+ success rates compared to ~30% with data-center proxies on Facebook.
Long-Running Scrapes	Scrape thousands of pages/groups over hours or days without interruption.
Concurrent Scraping	Run multiple browser instances across different IPs simultaneously.

Recommended Proxy Providers

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

Provider	Best For	Sign Up
Bright Data	World's largest residential network, 72M+ IPs, enterprise-grade	👉 Sign Up for Bright Data
IProyal	Premium residential pool, pay-as-you-go, 195+ countries	👉 Sign Up for IProyal
Storm Proxies	Fast & reliable residential IPs, developer-friendly API	👉 Sign Up for Storm Proxies
NetNut	ISP-grade residential network, 52M+ IPs, direct connectivity	👉 Sign Up for NetNut

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 Entirely via Environment Variables

export PROXY_ENABLED=true
export PROXY_PROVIDER=netnut       # 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:

Provider	Host	Port
Bright Data	brd.superproxy.io	22225
IProyal	proxy.iproyal.com	12321
Storm Proxies	rotating.stormproxies.com	9999
NetNut	gw-resi.netnut.io	5959

Override with "host" and "port" in config or 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 "restaurant" --type page
python main.py scrape --page-name examplebusiness
# The log will confirm proxy is active:
# INFO - Proxy enabled: 
# INFO - Browser using proxy: netnut → gw-resi.netnut.io:5959

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="netnut",
    username="your_user",
    password="your_pass",
    country="us",
    sticky=True
)
# For Playwright browser context
proxy = pm.get_playwright_proxy()
# → {"server": "http://gw-resi.netnut.io:5959", "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

• Always use sticky sessions — Facebook requires consistent IPs during a login session. Set "sticky": true.
• Target the right country — Set "country": "us" (or your target region) so Facebook serves content in the expected locale.
• Combine with existing anti-detection — This scraper already has fingerprinting, stealth scripts, and human behavior simulation. The proxy is the final layer.
• Rotate sessions between accounts — Call pm.rotate_session() when switching Facebook accounts to get a fresh IP.
• Use delays — Even with proxies, respect delay_between_profiles in config (default 5-10s) to avoid aggressive patterns.
• Monitor your proxy dashboard — All providers (Bright Data, IProyal, Storm Proxies, NetNut) have dashboards showing bandwidth usage and success rates.