⚡ Quick start

pip install facebook-page-info-scraper

from facebook_page_info_scraper import scrape_page

scrape_page("https://www.facebook.com/examplepage")

That is everything — both engines install and are ready to use.

🚀 Two engines, one result

Pick whichever suits the job. Both take the same URLs, return the same fields, and run the same extraction. They differ only in how the page is requested.

from facebook_page_info_scraper import scrape_pages       # 🌐 HTTP
from facebook_page_info_scraper.spider import run         # 🎭 Browser

scrape_pages(urls, threads=16)
run(urls, threads=8)

The browser engine downloads Chromium (~150 MB) the first time it runs — pip cannot fetch browser binaries, so it happens on first use. One time only.

📖 What it does

Give it a Facebook page URL, get back the page's public details: name, category, email, phone, website, address, likes, ratings, opening status.

🎯 What it solves

Facebook page data used to require driving a real browser — slow, heavy, and it broke every time Facebook changed its CSS. Both engines here read Facebook's own page payload instead, so neither depends on how the page looks.

🌐 Usage — HTTP

from facebook_page_info_scraper import scrape_page, scrape_pages

page  = scrape_page("https://www.facebook.com/examplepage")
pages = scrape_pages(urls, threads=16)

print(page["email"])        # hello@example.com
print(page["page_likes"])   # 12,480

python scrape.py urls.txt                  # -> pages.json
python scrape.py urls.txt --threads 24
python scrape.py urls.txt --out output.json

scrape_page(url,   want_about=True, timeout=25)
scrape_pages(urls, threads=16, want_about=True, timeout=25)

want_about=False reads only the page header — faster, but no email or phone.

🎭 Usage — Browser

from facebook_page_info_scraper.spider import run

run(urls, threads=8)                    # -> pages_browser.jsonl
run(urls, threads=8, headless=False)    # watch it work

python -m facebook_page_info_scraper.spider urls.txt --threads 8
python -m facebook_page_info_scraper.spider urls.txt --headed
python -m facebook_page_info_scraper.spider https://www.facebook.com/examplepage

run(urls,
    threads=8,                  # pages rendered at once, no cap
    out="pages_browser.jsonl",
    settle_ms=2000,             # pause after load before reading
    headless=True)

This engine works in batches — pass a list of URLs rather than one at a time.

📥 Input

Any Facebook page URL. These all work with either engine:

https://www.facebook.com/examplepage
https://facebook.com/examplepage                        (no www)
https://www.facebook.com/examplepage/                   (trailing slash)
https://www.facebook.com/pages/Example-Page/100000000000000
https://www.facebook.com/profile.php?id=100000000000000
http://sv-se.facebook.com/pages/Example-Page/100000000000000   (locale subdomain)

📤 Output

Identical from either engine.

{
  "page_name": "Example Store",
  "page_id": "100000000000000",
  "page_category": "Bakery",
  "email": "hello@example.com",
  "phone_number": "+33 1 23 45 67 89",
  "page_website": "https://example.com",
  "address": "1 Example Street\n12345 Sampletown",
  "page_likes": "12,480",
  "talking_about": "215",
  "were_here": "33",
  "recommend_percent": "94",
  "page_review_number": "18",
  "open_status": "Closed now",
  "price_range": "Price Range - $",
  "bio": "Example Store. 12,480 likes ...",
  "image": "https://scontent.xx.fbcdn.net/...",
  "canonical": "https://www.facebook.com/examplepage",
  "locale": "en_US",
  "ok": True
}

Fields

Always check ok:

page = scrape_page(url)
print(page.get("page_name")if page.get("ok") else page.get("error"))

One thing to know. email, phone_number and page_website are a string when the page lists one, and a list when it lists several.

"email": "hello@example.com"                          # one
"email": ["sales@example.com", "press@example.com"]   # several
"email": None                                         # none

def as_list(v):
    return [] if v is None else (v if isinstance(v, list) else [v])

🩺 Check your run

One call tells you how a batch went. Works on records from either engine.

from facebook_page_info_scraper import scrape_pages, summarise

records = scrape_pages(urls, threads=16)
summarise(records)

{
  "total": 213,          # records in
  "ok": 211,             # scraped successfully
  "failed": 2,
  "with_about": 164,     # found the About panel
  "with_email": 150,
  "with_phone": 115,
  "with_website": 161,
  "wrong_locale": 0,     # pages Facebook served in another language
  "avg_seconds": 1.44,
  "avg_kb": 533          # bytes actually read, not page size
}

Field counts are measured against ok, not total — dead URLs never drag your extraction numbers down. That makes the two problems easy to tell apart:

Handy as a guard in scheduled jobs:

stats = summarise(records)
if stats["with_email"] / stats["ok"] < 0.60:
    raise SystemExit("email extraction dropped — check for changes")

📊 Speed

Measured on the same 183-page list, same machine.

Both engines beat the old Selenium version by a wide margin — HTTP by roughly 50×, the browser engine by about 6× while still running JavaScript.

🔮 Roadmap

An AI extraction layer is planned for the tail that deterministic rules cannot reach — unlabelled free-text rows in languages whose formatting conventions vary, plus self-healing selectors that repair themselves when Facebook changes shape. It will sit behind the current parsers, not in front of them: rules first, model only where rules come up empty.

⬆️ Upgrading from 1.x

The old Selenium class still works:

pip install facebook-page-info-scraper[selenium]

from facebook_page_info_scraper import FacebookPageInfoScraper
FacebookPageInfoScraper(url).get_page_info()

Either new engine is a recommended replacement — same idea, much faster.

Two output differences:

• page_rate and page_review_number used to be swapped. They are correct now.
• location was a country name; the new address is the full street address.

🤝 Contributing

Contributions are welcome. If you find an issue or have a suggestion, please open an issue or submit a pull request on GitHub.

📝 Notes

• Only public pages. Nothing behind a login.
• Be reasonable with threads — this hits Facebook from your IP.
• Scraping Facebook is against their Terms of Service. Use accordingly.

License

MIT — see LICENSE.txt.