tiktok-product-scraper

What problem does it solve?

This skill automates collecting TikTok Shop product data from multiple sources, producing structured JSON and a human-friendly MD report, and optionally downloading reference videos for deeper analysis.

Core Features & Use Cases

• Multi-source scraping with auto-fallback: Primary source tabcut.com and a fallback to fastmoss.com when data is incomplete.
• Output formats: Generates tabcut_data.json (or fastmoss_data.json) and a corresponding tabcut_data.md for review, plus optional video assets in ref_video/.
• n8n integration: Designed to run as an n8n workflow node with Bash commands to orchestrate steps.
• Batch and automation: Supports batch processing via CSV and automates JSON-to-MD conversion for review.

Quick Start

1. Install Python and create a virtual environment, then install dependencies from requirements.txt.
2. Configure credentials in scripts/config/.env (Tabcut and FastMoss).
3. Run the scraper for a single product (with optional video downloads):
   • python run_scraper.py --product-id <PRODUCT_ID> --download-videos --output-dir "../product_list/YYYYMMDD"
   • or without --download-videos if only metadata is needed.
4. Convert the JSON to Markdown for review using the provided helper script:
   • python convert_json_to_md.py <PRODUCT_ID> --date YYYYMMDD