fbscrape

A Python library for scraping Facebook using Camoufox with account pooling, rotation, and concurrent scraping.

Built and maintained at the Media Ecosystem Observatory for social-media research. Sibling projects: igscrape for Instagram, pytok for TikTok and xscrape for X/Twitter.

Features

Eleven endpoints - UserTimeline, Search, GroupTimeline, CommentsList, PostDetail, PageTransparency, ProfileAuthenticity, ProfileInfo, ProfileAbout, GroupInfo, GroupAbout
High-level API - Simple FacebookScraper class handles all complexity
Concurrent scraping - WorkerPool manages multiple browser sessions
Account management - SQLite-backed pool with automatic rotation
Threshold rotation - Rotate accounts after N paginations to avoid detection
GraphQL interception - Replay-based pagination via captured request templates
Resumable - --continue picks a scrape back up from its last cursor
In-scrape media - Collect media during the scrape before fbcdn URLs expire
Post-processing - Flatten raw GraphQL into CSV/JSONL/Parquet and download media
CLI tools - Manage accounts and run scrapes from the command line

Installation

pip install -e .

Install Playwright browsers:

playwright install

Quick Start

High-Level API (Recommended)

from fbscrape import FacebookScraper, gather
import asyncio


async def main():
    async with FacebookScraper(db="accounts.db", max_browser_sessions=3) as scraper:
        result = await scraper.user_timeline(
            handle="zuck",
            start_date="2024-01-01",
            end_date="2025-01-01"
        )
        print(f"Scraped {len(result.data)} posts")


if __name__ == "__main__":
    asyncio.run(main())

Concurrent Scraping

from fbscrape import FacebookScraper, gather
import asyncio


async def main():
    async with FacebookScraper(db="accounts.db", max_browser_sessions=3) as scraper:
        handles = ["zuck", "meta", "facebook"]

        # Results arrive as they complete (not in submission order)
        async for result in gather(
            scraper.user_timeline(h, "2024-01-01", "2025-01-01")
            for h in handles
        ):
            handle = result.query.query["handle"]
            print(f"{handle}: {len(result.data)} posts")


if __name__ == "__main__":
    asyncio.run(main())

Low-Level API (BrowserSession)

For more control, use BrowserSession directly. The per-endpoint methods are user_timeline_hybrid / search_hybrid / group_timeline_hybrid / comments_list_hybrid / post_detail_hybrid / page_transparency_hybrid / profile_authenticity_hybrid / profile_info_hybrid / profile_about_hybrid / group_info_hybrid / group_about_hybrid:

from fbscrape.browser_session import BrowserSession
from fbscrape.accounts_pool import AccountsPool
import asyncio


async def main():
    pool = AccountsPool("accounts.db")
    account = await pool.get_available()

    async with BrowserSession(account, pool, headless=True) as session:
        outcome = await session.user_timeline_hybrid(
            handle="zuck",
            start_date="2024-01-01",
            end_date="2025-01-01"
        )
        print(f"Scraped {len(outcome.data)} posts")

    await pool.release_account(account.identifier)


if __name__ == "__main__":
    asyncio.run(main())

Returns ScrapeOutcome (no query field). To build a ScrapingResult, construct a Query yourself and call ScrapingResult.from_outcome(query, outcome).

Endpoints

fbscrape supports eleven endpoints, all registered in Query.ENDPOINT_REGISTRY, all running in hybrid mode (capture a real request template from the live page, then replay it). Four are paginated post/comment streams; the rest are single-shot record fetches.

Endpoint	Required `query`	Output shape
`UserTimeline`	`handle` (dates optional)	`data: list[dict]` — one per post
`Search`	`query_text` (filters optional)	`data: list[dict]` — one per search-result post
`GroupTimeline`	`handle` (dates optional)	`data: list[dict]` — one per group post
`CommentsList`	`handle`, `post_id`	`data: list[dict]` — one per top-level comment
`PostDetail`	`handle`, `post_id`	`data: [record]` — one post, timeline schema
`PageTransparency`	`page_id` (handle optional)	`data: [transparency_dict]`
`ProfileAuthenticity`	`user_id`	`data: [authenticity_dict]`
`ProfileInfo`	`handle`	`data: [profile_header_dict]`
`ProfileAbout`	`handle`	`data: [profile_about_dict]`
`GroupInfo`	`handle`	`data: [group_header_dict]`
`GroupAbout`	`handle`	`data: [group_about_dict]`

Each endpoint has a full guide under docs/endpoints/ — inputs, scrape strategy, every option, usage recipes, and gotchas (including the user_id vs page_id distinction, the user_id → page_id → transparency pipeline, and comments handling).

Output format

Each scrape is saved as a gzipped JSONL file — one record per line — named <handle>_<endpoint>_hybrid.jsonl.gz (no date segment; the actual scrape parameters live in each line's query field):

data/posts/zuck_UserTimeline_hybrid.jsonl.gz

Every line is {query, result, time_started, time_taken, last_cursor, data: <one record>}; result / time_taken are null mid-scrape and stamped on the final line. Records stream to disk as they're parsed (constant memory), and --continue appends a new gzip member without rewriting the file. Read it back with:

from fbscrape.jsonl_store import load_scrape_file
query, records = load_scrape_file("data/posts/zuck_UserTimeline_hybrid.jsonl.gz")

The flatten and download-media commands read both this format and legacy whole-file envelopes (.json / .json.gz).

Architecture

A quick note; the full walkthrough is in docs/architecture/overview.md.

┌──────────────────────────────────────────────────────────────────┐
│                     FacebookScraper                               │
│  user_timeline / search / group_timeline / comments_list /       │
│  post_detail / page_transparency / profile_* / group_* →         │
│  ScrapingResult                                                   │
└────────────────────────────┬─────────────────────────────────────┘
                             │
                             ▼
┌──────────────────────────────────────────────────────────────────┐
│                       WorkerPool                                  │
│  - Creates N workers (N = min(max_sessions, active_accounts))    │
│  - Shared task queue with Future-based results                   │
│  - Workers pull tasks and execute concurrently                   │
└────────────────────────────┬─────────────────────────────────────┘
                             │
                             ▼
┌──────────────────────────────────────────────────────────────────┐
│                         Worker                                    │
│  - Owns ONE account from AccountsPool                            │
│  - Tracks scroll count, rotates at threshold                     │
│  - Creates fresh BrowserSession per task                         │
│  - Handles errors: login failure, ban, rate limit → rotate       │
└────────────────────────────┬─────────────────────────────────────┘
                             │
                             ▼
┌──────────────────────────────────────────────────────────────────┐
│                      BrowserSession                               │
│  - Playwright browser with Camoufox                              │
│  - Login, cookie management                                       │
│  - GraphQL response interception + replay-based pagination       │
│  - Returns ScrapeOutcome with `data: list[dict]`                 │
└──────────────────────────────────────────────────────────────────┘

Layer Responsibilities

Layer	Responsibility
FacebookScraper	User-facing API, hides complexity
WorkerPool	Concurrency, task distribution via Futures
Worker	Account lifecycle, scroll tracking, error recovery
BrowserSession	Browser automation, GraphQL interception
AccountsPool	SQLite storage, locking, account selection

Command Line Interface

Global Options

fbscrape --db /path/to/accounts.db <command>
fbscrape --help

Scraping

# UserTimeline — paginated; --start-date / --end-date are both OPTIONAL.
# When omitted: start has no lower bound; end defaults to today (UTC) to
# mirror FB's UI fingerprint (which always sends `beforeTime`).
fbscrape scrape user-timeline zuck --start-date 2024-01-01 --end-date 2025-01-01
fbscrape scrape user-timeline zuck meta --start-date 2024-01-01 --headless --max-sessions 2

# Open-ended UserTimeline scrape — pull the most recent N posts with no date filter.
fbscrape scrape user-timeline zuck --max-posts 500

# Search — paginated, hybrid only. Filters optional; no filters = FB default ranking.
fbscrape scrape search 'mark carney'
fbscrape scrape search 'mark carney' --filter recent_posts \
    --filter creation_time.start=2025-01-01 --filter creation_time.end=2025-12-31
fbscrape scrape search 'mark carney' --filter posts_from.source=public
fbscrape scrape search --input-file queries.csv --filter recent_posts

# GroupTimeline — paginated, hybrid only. `handle` accepts vanity OR numeric
# group id. `--start-date` and `--end-date` are BOTH OPTIONAL (FB's UI sends
# no date filter on group feeds — when omitted there is no client-side
# bound either). Default sort is TOP_POSTS (matches FB UI; lowest-
# fingerprint and empirically safer for sustained scraping than
# CHRONOLOGICAL); under non-chronological sorts, termination is driven by
# --max-consecutive-out-of-range (default 20 = bail after N posts in a row
# outside the date window — no-op when no dates are provided), or
# --max-posts.
fbscrape scrape group-timeline 392585550772135 --start-date 2024-01-01 --end-date 2025-01-01
fbscrape scrape group-timeline 787909081545196 --start-date 2024-01-01
fbscrape scrape group-timeline --input-file groups.csv --headless
# Open-ended group scrape — pull the most recent N posts.
fbscrape scrape group-timeline 392585550772135 --max-posts 500
# Override sort / stop knobs:
fbscrape scrape group-timeline 392585550772135 --start-date 2024-01-01 \
    --sorting-setting CHRONOLOGICAL --max-consecutive-out-of-range 30

# CommentsList — top-level comments on a post. Identifier is `<handle>:<post_id>`;
# post_id accepts numeric form OR the pfbid form (both work in FB's permalink URL).
# Exhaustion-only by default; pass --max-results to cap. No date filter (comments
# are returned non-chronologically by FB's "Most Relevant" ranking). Replies
# (depth>0) are NOT collected here — each comment carries `replies_total_count`
# so callers can decide which comments warrant a separate reply-fetching pass.
fbscrape scrape comments-list MarkJCarney2025:pfbid02fqwzpi9P7cbpefNM1CUF1qzBGD5oPKR5PBwN62nQthxyiojY4uSJ6AYx85P2Nx4Gl
fbscrape scrape comments-list zuck:10115311901107991 --max-results 200 --headless
fbscrape scrape comments-list --input-file posts.csv

# PageTransparency — single-shot, takes a page_id (handle optional)
fbscrape scrape page-transparency 899800046546098
fbscrape scrape page-transparency habsfanhub:899800046546098
fbscrape scrape page-transparency --input-file pages.csv --headless

# ProfileAuthenticity — single-shot, takes a user_id
fbscrape scrape profile-authenticity 100044331674441
fbscrape scrape profile-authenticity --input-file users.csv --headless

# PostDetail — single-shot; fetch ONE post's content by its permalink.
# handle + post_id (numeric OR pfbid). Pass --group for group posts
# (/groups/<handle>/posts/<post_id>/); default is a page/user post
# (/<handle>/posts/<post_id>/). No GraphQL replay — the post's Story is read
# from the permalink's server-rendered document, then flattened to the same
# schema as a timeline post.
fbscrape scrape post-detail albertansunitedtostoptheucp:27209929835285847 --group
fbscrape scrape post-detail zuck:10115311901107991 --headless
fbscrape scrape post-detail --input-file posts.csv --group

# ProfileInfo / ProfileAbout — single-shot; a profile's header, and its About
# page (contact/basic-info/links sections). Take a vanity handle or numeric id.
fbscrape scrape profile-info zuck
fbscrape scrape profile-about 61582991935083 --headless

# GroupInfo / GroupAbout — single-shot; a group's header, and its About page
# (description, rules, activity stats, admin facepile). Vanity or numeric id.
fbscrape scrape group-info 392585550772135
fbscrape scrape group-about 392585550772135 --headless

# Post-processing — flatten raw GraphQL into csv/jsonl/parquet. Accepts the
# current `.jsonl.gz` output as well as legacy `.json` / `.json.gz` envelopes,
# a single file, or a whole directory.
fbscrape flatten data/posts/zuck_UserTimeline_hybrid.jsonl.gz --format all
fbscrape flatten data/posts/ --format parquet
fbscrape flatten data/posts/ --output data/merged.parquet --concat

# Download media (within ~3 days of scrape — fbcdn URLs expire ~4-5 days out)
fbscrape download-media data/posts/zuck_UserTimeline_hybrid.jsonl.gz --include-thumbnails

# ...or collect media DURING the scrape, so signatures are never stale.
# Immediately (pagination waits on each batch's downloads):
fbscrape scrape user-timeline zuck --download-media
# Handed off to another process (near-zero cost to the scrape):
fbscrape scrape user-timeline zuck --media-manifest data/media_queue.jsonl
fbscrape download-media data/media_queue.jsonl --from-manifest --out-dir data/media/

# Inspect a cURL copied from DevTools — prints a structured GraphQL summary
# (friendly_name, doc_id, decoded `variables` JSON, key headers). Cookie /
# fb_dtsg / lsd / jazoest are redacted by default; pass --raw to disable
# redaction, --full to include every header and telemetry body field.
fbscrape utils parse-curl "curl 'https://www.facebook.com/api/graphql/' -X POST ..."

--input-file accepts CSV / Parquet / YAML / JSON / JSONL. Recognized columns depend on the subcommand: handle + optional start_date / end_date for user-timeline and group-timeline; query_text for search (filters via --filter, not file columns); handle + post_id (both required) for comments-list and post-detail; page_id (required) + handle (optional) for page-transparency; user_id for profile-authenticity.

Media: during the scrape, or after it

fbcdn URLs are self-signed (oh= signature, oe= expiry) and go stale in about 4–5 days — after that they answer HTTP 403 Bad URL hash. So there are three ways to get the pixels, and the right one depends on how much you trust the gap between scraping and downloading:

Path	How	Cost	Use when
Post-hoc	`fbscrape download-media <file>`	none to the scrape	you'll download within a couple of days
Immediate	`--download-media` during the scrape	pagination waits on each batch's fetches	the scrape is long, or the media matters more than speed
Handoff	`--media-manifest <path.jsonl>` during the scrape	~nothing (one appended line per item)	you want fresh URLs and a fast scrape

The two in-scrape flags work on every post-bearing endpoint — user-timeline, group-timeline, search, comments-list, post-detail — and can be combined (download now, keep the manifest as a record of what was queued):

# Immediate: media lands in <output-dir>/media/<target>/ as each batch is parsed
fbscrape scrape group-timeline 392585550772135 --download-media
fbscrape scrape group-timeline 392585550772135 --media-dir /data/media   # implies --download-media

# Handoff: append one line per media item; drain it from any other process
fbscrape scrape user-timeline zuck meta --media-manifest data/media_queue.jsonl
fbscrape download-media data/media_queue.jsonl --from-manifest --out-dir data/media/

# Both, plus thumbnails and a tighter fetch pool
fbscrape scrape search 'mark carney' --download-media --media-manifest q.jsonl \
  --include-thumbnails --media-concurrency 4

Manifest lines are plain JSONL (.jsonl.gz also works — pass a .gz path), one per media item, and are safe to append to from several concurrent sessions:

{"post_id": "1234", "kind": "image", "idx": 0, "url": "https://scontent...", "ext": "jpg",
 "filename": "1234_img_00.jpg", "queued_at": "2026-08-13T18:20:04+00:00",
 "endpoint": "GroupTimeline", "label": "392585550772135"}

filename is the same name the immediate path writes (<post_id>_img_00.jpg, _vid_00.mp4, _thumb_00.jpg), so a drain into the same directory skips what's already there. queued_at tells a consumer how much signature runway is left. Comment attachments are named after the comment id.

From the Python API the same options are keyword arguments on every post-bearing scraper method, plus on_new_posts for your own sink:

async with FacebookScraper(db="db/accounts.db") as scraper:
    async def index_batch(posts):           # sync or async, both work
        await my_queue.put(posts)           # raw (unflattened) records

    result = await scraper.group_timeline(
        "392585550772135",
        start_date="2025-01-01",
        download_media=True,                # requires media_dir
        media_dir="data/media/392585550772135",
        media_manifest="data/media_queue.jsonl",
        include_thumbnails=True,
        on_new_posts=index_batch,
    )

A sink that raises is logged and skipped — a CDN hiccup or a bug in your callback can't kill the scrape. See docs/media_streaming.md for the mechanism.

Account Management

Account commands live under the account group: fbscrape account <cmd>.

# Add account with email
fbscrape account add --email user@example.com --password secret123

# Add account with phone
fbscrape account add --phone +1234567890 --password secret123

# Add with all options
fbscrape account add \
    --email user@example.com \
    --password secret123 \
    --username fbusername \
    --cookies /path/to/cookies.json \
    --proxy http://proxy:8080

# Bulk add from file
fbscrape account add-from-file accounts.txt --format "email:password"

# List accounts
fbscrape account list
fbscrape account list --active
fbscrape account list -v  # verbose

# Show account details
fbscrape account info user@example.com

# Delete accounts
fbscrape account delete user@example.com
fbscrape account delete --inactive
fbscrape account delete --all

Logging In

Accounts need a live Facebook session (cookies) before scraping. login authenticates one or more accounts and persists cookies to the DB. Scrapes also log in automatically on start when an account has stored credentials.

# Automatic form-fill login (account needs a stored password)
fbscrape login user@example.com --mode automatic

# Try stored cookies first, fall back to form-fill
fbscrape login user@example.com --mode automatic --cookies

# Manual: opens a non-headless browser and pauses for a human to log in by hand
fbscrape login user@example.com --mode manual --no-headless

Account Status

# Activate/deactivate
fbscrape account activate user@example.com
fbscrape account deactivate user@example.com --error "Account banned"

# Unlock (remove rate limit locks)
fbscrape account unlock user@example.com
fbscrape account unlock --all

# Release (set in_use=false)
fbscrape account release user@example.com
fbscrape account release --all

# Reset scroll counts
fbscrape account reset-scrolls user@example.com
fbscrape account reset-scrolls --all
fbscrape account reset-scrolls --all --endpoint UserTimeline

Statistics

fbscrape account stats

Output:

Account Pool Statistics
------------------------------
  Total:    10
  Active:   8
  Inactive: 2
  In Use:   3
  Locked:   1

Cookie Management

fbscrape account set-cookies user@example.com cookies.json
fbscrape account export-cookies user@example.com output.json

Field Management

# Update individual fields
fbscrape account set user@example.com username myusername
fbscrape account set user@example.com active true
fbscrape account set user@example.com proxy_server http://proxy:8080

# List updatable fields
fbscrape account fields

Configuration

FacebookScraper Options

FacebookScraper(
    db="accounts.db",           # Path to SQLite database
    max_browser_sessions=5,     # Max concurrent browsers
    scroll_threshold=500,       # Scrolls before rotating account
    headless=True,              # Run browsers headlessly
    mobile=False,               # Use mobile browser emulation
)

Environment Variables

FB_RAISE_WHEN_NO_ACCOUNT=false  # Raise error vs wait when no accounts
FB_LOG_LEVEL=INFO               # Logging level (TRACE, DEBUG, INFO, WARNING, ERROR, CRITICAL)

Debug Logging

Enable debug logging to see detailed execution flow:

from fbscrape.logger import set_log_level

set_log_level("DEBUG")

Or via environment variable:

FB_LOG_LEVEL=DEBUG python your_script.py

Account Fields

Field	Type	Description
`email`	str \| None	Account email (identifier)
`phone_number`	str \| None	Account phone (identifier)
`password`	str	Account password
`username`	str \| None	Facebook username
`cookies`	list[dict]	Playwright-format cookies
`proxy_server`	str \| None	Proxy URL
`active`	bool	Whether account is usable
`in_use`	bool	Whether currently in use
`locks`	dict	Rate limit locks (`{"locked_until": "..."}`)
`scroll_count_overall_24h`	int	Scrolls in last 24 hours
`scroll_count_per_endpoint_total`	dict	Scrolls per endpoint (e.g., `{"UserTimeline": 150}`)
`error_msg`	str \| None	Last error message

Error Handling

Scrape calls resolve to a ScrapingResult — check .result before trusting .data, since per-task conditions like "rate_limit", "account is private", or "parse_error" still resolve successfully. Tasks that exhaust their 3-retry budget or drain the pool instead raise in your gather() loop (RetryBudgetExhaustedError / NoAccountError). Behind the scenes the Worker rotates, locks, or deactivates accounts per exception type.

from fbscrape import FacebookScraper, gather
from fbscrape.exceptions import NoAccountError, RetryBudgetExhaustedError

async with FacebookScraper(db="db/accounts.db") as scraper:
    async for result in gather(
        scraper.user_timeline(h, "2024-01-01", "2025-01-01") for h in handles
    ):
        print(result.query.query["handle"], result.result, len(result.data))

Full reference — every result string, the exception → Worker-action table, and exactly what the gather() loop yields vs. raises — is in docs/results_and_errors.md.

Project Structure

fbscrape/
├── __init__.py          # Package exports
├── scraper.py           # FacebookScraper (high-level API)
├── worker_pool.py       # WorkerPool (concurrency)
├── worker.py            # Worker (account lifecycle + dispatch)
├── browser_session.py   # BrowserSession (browser automation, scrape methods)
├── login.py             # Login flows (cookies → automatic → manual)
├── accounts_pool.py     # AccountsPool (SQLite management)
├── account.py           # Account dataclass
├── response.py          # GraphQL interception + FacebookGraphQLParser
├── models.py            # Query, ScrapeOutcome, ScrapingResult, ENDPOINT_REGISTRY
├── stop_conditions.py   # Pagination stop-condition framework
├── jsonl_store.py       # JSONL I/O: writer, readers, resume tail, converter
├── downloaders.py       # Async media downloader
├── cli.py               # Command-line interface
├── db.py                # Database migrations
├── utils.py             # Helpers (gather, cookies, etc.)
├── exceptions.py        # Custom exceptions
└── logger.py            # Logging setup

Testing

Three-tier suite (unit / integration / e2e). pytest runs the fast unit tier only; integration and e2e drive a real browser against Facebook and are gated on an available account (e2e additionally requires FBSCRAPE_RUN_E2E=1). See tests/README.md for the layout and fixture capture.

pytest                              # unit tier (fast, no network)
pytest -m integration               # live headless scrapes (needs an account)
FBSCRAPE_RUN_E2E=1 pytest -m e2e     # full CLI scrape → flatten / download-media

Documentation

Deeper references live under docs/ (indexed in docs/README.md):

Doc	Contents
`docs/endpoints/`	Per-endpoint guides — inputs, strategy, options, recipes, gotchas
`docs/architecture/overview.md`	Full architecture walkthrough
`docs/architecture/account_management.md`	Account state machine + DB semantics
`docs/results_and_errors.md`	Result strings, exception → Worker-action, the `gather()` contract
`docs/search_filters.md`	Search filter usage + adding a filter
`docs/group_scraping_runbook.md`	Running a group collection: sort and termination choices, resuming / topping up, batch bookkeeping, recovery paths
`docs/media_streaming.md`	Collecting media during a scrape
`docs/adding_endpoints.md`	Playbook for adding a new endpoint

Contributing? See CONTRIBUTING.md. Working with an AI agent on this repo? CLAUDE.md is the agent-facing map.

License

PolyForm Noncommercial 1.0.0 — see LICENSE.

Free to use, modify, and redistribute for noncommercial purposes, including by educational institutions, public research organizations, charities, and government bodies regardless of funding source. Commercial use is not permitted under this license; contact the Media Ecosystem Observatory for other arrangements.

Name		Name	Last commit message	Last commit date
docker		docker
docs		docs
fbscrape		fbscrape
tests		tests
.dockerignore		.dockerignore
.gitignore		.gitignore
CLAUDE.md		CLAUDE.md
CONTRIBUTING.md		CONTRIBUTING.md
DOCKER.md		DOCKER.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
docker-compose.yml		docker-compose.yml
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
uv.lock		uv.lock

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fbscrape

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Quick Start

High-Level API (Recommended)

Concurrent Scraping

Low-Level API (BrowserSession)

Endpoints

Output format

Architecture

Layer Responsibilities

Command Line Interface

Global Options

Scraping

Media: during the scrape, or after it

Account Management

Logging In

Account Status

Statistics

Cookie Management

Field Management

Configuration

FacebookScraper Options

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Debug Logging

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Error Handling

Project Structure

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fbscrape

Features

Installation

Quick Start

High-Level API (Recommended)

Concurrent Scraping

Low-Level API (BrowserSession)

Endpoints

Output format

Architecture

Layer Responsibilities

Command Line Interface

Global Options

Scraping

Media: during the scrape, or after it

Account Management

Logging In

Account Status

Statistics

Cookie Management

Field Management

Configuration

FacebookScraper Options

Environment Variables

Debug Logging

Account Fields

Error Handling

Project Structure

Testing

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