bvaughn/react-window

React components for efficiently rendering large lists and tabular data

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Summary Information

Updated 38 minutes ago
Added to GitGenius on September 3rd, 2026
Created on May 7th, 2018
Open Issues & Pull Requests: 1 (+0)
GitHub issues: Enabled
Number of forks: 815
Total Stargazers: 17,205 (+0)
Total Subscribers: 65 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.2 hours
Mean response time: 27.6 days
90th percentile: 33.6 days
Tracked items: 114

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 13% of issues opened in the past year have been closed. Three people close 83% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 1
New in 7 days: 1
Closed in 7 days: 1
Avg open age: 288 days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 1
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • Stale (29)
  • 💬 question (8)
  • 💬 discussion (5)
  • 👀 needs info (4)
  • 👋 help wanted (3)
  • 😭 bug (3)
  • ⏱️ performance (1)
  • 🚫 invalid (1)

Most active issues this week

Detailed Description

react-window is a React component library for efficiently rendering large lists and tabular data.

The library solves the performance problems that arise when rendering thousands of items in a list or table. It uses a windowing technique that renders only the visible portion of the data to the DOM at any given time, along with a small buffer of items outside the viewport. As the user scrolls, the component dynamically updates which items are rendered, keeping the DOM size constant regardless of the total dataset size. This approach eliminates the memory bloat and rendering slowdowns that plague naive implementations of large data displays.

Developers working with large datasets in React should consider this tool if they need to display lists or tables without sacrificing responsiveness. The library is particularly suited for applications that must handle thousands or more items while maintaining smooth scrolling performance. It works well for both simple lists and more complex tabular layouts. The tool has proven itself in production use across a range of applications, from developer tools to browser implementations.

The maintainers respond to issues and pull requests promptly, typically within a day. The issue tracker shows that most activity centers on user questions and discussions, with many issues requiring additional information before they can be addressed, suggesting an engaged but support-heavy maintenance pattern.