xiaohongshu-crawler

You can scrape Xiaohongshu posts by specifying target keywords to retrieve structured data including titles, authors, and engagement metrics. The skill filters results by date ranges and sorting options, returning structured tables ready for trend analysis.

Xiaohongshu notes extraction returns structured fields mapping titles, authors, favorites, shares, comments, likes, and publication dates. This structured output supports direct content discovery and competitive research without manual multi-step scraping.

Crawled Xiaohongshu data can be exported to CSV format compatible with Excel and HTML visualization reports. These export options facilitate offline data analysis and sharing for brand competitive analysis and MCN content planning scenarios.

This web scraping tool requires the Python requests dependency to perform API-based data retrieval from Xiaohongshu. It handles structured output generation and robust error handling using this HTTP library.

Automating Xiaohongshu content discovery involves using keyword-based crawling with date filters to batch retrieve post metrics. This approach delivers reliable, ready-to-analyze structured results, replacing manual scraping for competitive research workflows.

Filtering Xiaohongshu posts by date ranges relies on API-based data retrieval with structured output and explicit field mappings. Users should note that robust error handling manages retrieval failures, but large-scale historical scraping may encounter platform limitations.