{
  "id": 12322513,
  "title": "How to get Xiaohongshu (RedNote) data in Python",
  "url": "https://urgent.news/2026/10/06/how-to-get-xiaohongshu-rednote-data-in-python",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-06T06:51:13.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/silkline/how-to-get-xiaohongshu-rednote-data-in-python-11pg"
  },
  "original_language": "en",
  "account": "Xiaohongshu (RedNote) is a popular platform in China where consumers share reviews, hauls, travel guides, and café lists. Due to its value for brand and product research, obtaining data from Xiaohongshu can be challenging. This tutorial focuses on extracting data from Xiaohongshu using Python in just 20 lines of code.\n\nThe script begins by setting up the environment, requiring Python 3.10 or higher and an Apify account. Replace 'your-token-here' with your personal Apify API token. Install necessary libraries using pip install apify-client pandas and export the API token as APIFY_TOKEN.\n\nThe search function starts by querying Xiaohongshu for a specified keyword, like 咖啡 (coffee). Chinese keywords are essential for obtaining accurate results. After running the search, the script loads the results into a pandas DataFrame and ranks the notes based on the save count (collects) versus like count. This ratio helps identify useful content, such as guides or reviews.",
  "summary": "Disclosure: I built the Xiaohongshu Scraper used in this tutorial. It's a paid Actor on Apify (pay per result), and the pricing is listed at the end. Xiaohongshu (小红书), known abroad as RedNote, is where Chinese consumers go to decide what to buy. People post reviews, \"what I bought\" hauls, travel guides and café lists, and other people save those notes to come back to later. For brand research,…",
  "key_points": [
    "Use Python 3.10+ and Apify account for Xiaohongshu data extraction",
    "Replace your-token-here with personal Apify API token",
    "Rank notes by save count and like count to find valuable content"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}