QQ Music Playlist Analysis & Review Report
Successfully exported 710 songs from a public QQ Music playlist and built a 'data → analysis → audiovisual' pipeline: structured tagging, music-critic-style analysis, and a single-file visual review report.
A complete data engineering exercise on a public QQ Music playlist: from bulk export to multi-dimensional analysis and a visual review report.
Data Collection
The QQ Music playlist page is an SPA whose DOM only renders the first 10 songs. By using opencli to control the browser and fetching the official API from within the loaded page context, the request naturally carried cookies — sidestepping CORS — and pulled all 710 songs with full fields (title / artist / album / duration / songmid) in one go. The result was packaged into a reusable one-command export script.
Music Analysis
Each song received 6-dimension tagging (genre / style / year / language / artist nationality / audience profile), aggregated statistics, and a music-critic-style analysis report (snapshot / slice / commentary / profile / recommendations).
Visualization
Built an HTML → single-file visualization report (self-contained data + ECharts, KPI overview + 10 charts + critic commentary) and rendered it as a full-page long screenshot for easy sharing. Reusable music-critic sub-Agent and playlist-review Skill were also distilled from the process.
Highlights
- Used opencli to control a browser and fetch the official API from within the page context
- bypassing SPA first-render and CORS limitations
- 6-dimension tagging per song + aggregate stats + music-critic insights
- producing a human-readable analysis report
- Single-file visualization report (KPIs + 10 charts + commentary) + full-page long screenshot
- shareable with others
