Threads Post Scraper Pro

An Apify Actor for extracting user posts from Meta's Threads platform. It scrapes a user's thread history and outputs structured data for analysis or archiving.

Overview

This actor takes a Threads username or profile URL and scrapes their posted threads. It handles pagination automatically, fetching multiple pages of content based on your configuration. Output is organized into individual thread records and a summary, available in JSON, CSV, or Excel formats via Apify's dataset.

Key Features

• Simple Input: Accepts either a username (zuck) or a full profile URL.
• Smart Pagination: Automatically navigates through pages using cursor management. Scrapes approximately 19 threads per page.
• Configurable Depth: Control the scrape with max_pages (1-50 pages).
• Reliable Operation: Includes automatic retries and error handling.
• Structured Output: Each thread is saved as an individual record with full metadata (user info, caption, likes, comments, timestamp).

How to Use

1. Configure Input: In the Apify Console, provide the target username/URL and optional page limit.
2. Run the Actor: Click "Start" to execute the scrape.
3. Get Results: Download the data from the actor's dataset in your preferred format.

Input Configuration

The actor requires a JSON input object with the following parameters:

Example Input:

{
  "username": "zuck",
  "max_pages": 5
}

Output Format

The dataset contains two primary record types:

1. Individual Thread Records: One per scraped thread.
   json { "thread_id": "3759936745132642616", "username": "zuck", "page_number": 1, "thread_data": { "pk": "3759936745132642616", "user": { "username": "zuck", "full_name": "Mark Zuckerberg", "is_verified": true }, "caption": { "text": "Thread content here..." }, "taken_at": 1699123456, "like_count": 1234, "comment_count": 56 } }

2. Summary Record: A single record with scrape statistics.
   json { "summary": true, "success": true, "username": "zuck", "pages_requested": 5, "pages_fetched": 5, "total_threads": 95, "threads_per_page_avg": 19, "fetched_at": "2025-11-18T08:30:00.000Z" }

Usage Notes

• Scale: For a quick check, use 1-2 pages (~20-40 threads). For a comprehensive scrape, use up to 50 pages (~950 threads).
• Data Handling: The summary record indicates success, but the main data is in the individual thread records saved separately.