Use when reviewing dashboards, admin tables, search results, or feeds with many repeated items. Confirm the bottleneck is DOM or rendering cost before introduci
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-list-virtualization-0a70e3894db5 ,按照其中的说明把「list-virtualization」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Rendering hundreds or thousands of rows at once wastes memory and makes style calculation, layout, and painting more expensive. Virtualization keeps large collections responsive by limiting the number of mounted nodes.
Inspect long lists, tables, grids, and feeds for places where the UI renders every item at once. Flag views where the number of mounted rows or cards is large enough to create DOM, memory, or scroll-performance issues.
Introduce list or table virtualization so only the visible rows plus overscan render, while preserving sizing, keyboard navigation, and any required sticky headers or selection behavior.
Explain list virtualization, why it improves performance for large collections, and the tradeoffs engineers need to watch for around measurement and accessibility.
Inspect collection components, data tables, infinite feeds, and dashboards. Flag places where rendering the full dataset creates excessive DOM nodes or scroll jank, and verify the virtualization strategy still preserves item identity, semantics, and expected interactions.
For full implementation details, code examples, and framework-specific guidance,
see references/rule.md.
Rule page: https://frontendchecklist.io/en/rules/performance/list-virtualization