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2 个仓库

Awesome GitHub RepositoriesOptimized Option Lists

Large option lists with async loading, lazy mounting, virtualization, and empty states.

Distinct from Virtualized Lists: Distinct from Virtualized Lists: covers the full optimization pipeline including async loading and empty states, not just DOM virtualization.

Explore 2 awesome GitHub repositories matching software engineering & architecture · Optimized Option Lists. Refine with filters or upvote what's useful.

Awesome Optimized Option Lists GitHub Repositories

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  • chakra-ui/arkchakra-ui 的头像

    chakra-ui/ark

    5,004在 GitHub 上查看↗

    Ark is a headless UI component library that delivers accessible, cross-framework primitives with behavior governed by finite state machines. It provides unstyled components that encapsulate logic and accessibility — including full keyboard navigation, focus management, and WAI-ARIA support — while leaving visual styling entirely to the consumer. Components expose scoped data attributes for CSS targeting and use state machines to produce predictable, testable interactive behavior across every state transition. The library distinguishes itself through a state propagation model that distributes

    Optimizes large option lists with async loading, virtualization, and empty state handling.

    TypeScriptcomponentsdesign-systemheadless
    在 GitHub 上查看↗5,004
  • bvaughn/react-virtualized-selectbvaughn 的头像

    bvaughn/react-virtualized-select

    1,171在 GitHub 上查看↗

    该项目是一个高性能下拉组件,旨在处理用户界面中的海量数据集。通过集成窗口化和虚拟化技术,它仅渲染视口内当前可见的项目,确保包含数千个条目的列表保持响应且内存高效。 该库作为现有选择组件的扩展,利用高阶组件模式注入虚拟化逻辑,而无需修改底层源代码。它提供对选择体验的广泛控制,允许开发者覆盖默认渲染逻辑、管理选项状态并支持用户创建的输入。 除了核心虚拟化,该库还支持复杂的数据工作流,包括从远程 API 异步加载选项和以编程方式管理焦点。开发者可以通过属性驱动的组合自定义下拉菜单的外观和布局,从而实现动态选项高度以及针对单个项目或容器的专门渲染。

    Optimizes performance for large option lists through virtualization and asynchronous data loading.

    JavaScript
    在 GitHub 上查看↗1,171
  1. Home
  2. Software Engineering & Architecture
  3. Performance and Reliability
  4. Performance Optimization
  5. Data Handling and Throughput
  6. Large Dataset Optimizations
  7. Virtualized Lists
  8. Optimized Option Lists