[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-74824":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":9,"rankLanguage":9,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":24,"topics":25,"createdAt":9,"pushedAt":9,"updatedAt":42,"readmeContent":43,"aiSummary":44,"trendingCount":15,"starSnapshotCount":15,"syncStatus":45,"lastSyncTime":46,"discoverSource":47},74824,"ChartGPU","ChartGPU\u002FChartGPU","Beautiful, open source, WebGPU-based charting library","https:\u002F\u002Fchartgpu.github.io\u002FChartGPU\u002F",null,"TypeScript",3125,95,15,10,0,9,17,38,27,88.25,"MIT License",false,"main",true,[26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41],"awesome-list","candlestick-chart","chart-library","charting-library","charts","data-analysis","data-visualization","financial-charts","gpu","high-performance","open-source","scatter-plot","shaders","typescript","webgpu","wgsl","2026-06-12 04:01:16","\u003Cp align=\"center\" style=\"margin-bottom:0; margin-top:20px;\">\n  \u003Cimg src=\"docs\u002Fassets\u002Fchartgpu.png\" alt=\"ChartGPU\" width=\"400\">\n\u003C\u002Fp>\n\n\u003Cp align=\"center\" style=\"margin-top:-18px;\">\n  The fastest open-source charting library — 50M points at 60 FPS.\n\u003C\u002Fp>\n\n\u003Cdiv align=\"center\">\n\n\n[\u003Cimg src=\"docs\u002Fassets\u002Fpowered-by-webgpu.svg\" alt=\"Powered by WebGPU\" height=\"28\" \u002F>](https:\u002F\u002Fforthebadge.com)\n[![GitHub Stars](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fstars\u002FChartGPU\u002Fchartgpu?style=for-the-badge&color=yellow)](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu)\n[![CI Status](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Factions\u002Fworkflow\u002Fstatus\u002Fchartgpu\u002Fchartgpu\u002Ftests.yml?branch=main&style=for-the-badge&label=Tests)](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Factions\u002Fworkflows\u002Ftests.yml)\n[![npm version](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fv\u002Fchartgpu?style=for-the-badge&color=blue)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Fchartgpu)\n[![NPM Downloads](https:\u002F\u002Fimg.shields.io\u002Fnpm\u002Fdm\u002Fchartgpu?style=for-the-badge&color=%2368cc49)](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Fchartgpu)\n[![License: MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-MIT-yellow.svg?style=for-the-badge)](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002FLICENSE)\n[![Live Demo](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Fdemo-live-brightgreen?style=for-the-badge)](https:\u002F\u002Fchartgpu.github.io\u002FChartGPU\u002Fexamples\u002F)\n[![Examples](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FExamples-Code%20Samples-blue?style=for-the-badge)](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Ftree\u002Fmain\u002Fexamples)\n[![Documentation](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDocumentation-Getting%20Started-blue?style=for-the-badge)](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002Fdocs\u002FGETTING_STARTED.md)\n\n[\u003Cimg src=\"https:\u002F\u002Fhackerbadge.now.sh\u002Fapi?id=46706528\" alt=\"Featured on Hacker News\" height=\"30\" \u002F>](https:\u002F\u002Fnews.ycombinator.com\u002Fitem?id=46706528)\n\n[\u003Cimg src=\"https:\u002F\u002Fawesome.re\u002Fmentioned-badge.svg\" alt=\"Featured in Awesome WebGPU\" style=\"height: 30px;\" \u002F>](https:\u002F\u002Fgithub.com\u002Fmikbry\u002Fawesome-webgpu)\n\n\n\u003C\u002Fdiv>\n\nChartGPU is a TypeScript charting library built on WebGPU for smooth, interactive rendering—especially when you have lots of data.\n\n## Demo\n\n![ChartGPU demo](https:\u002F\u002Fraw.githubusercontent.com\u002Fchartgpu\u002Fchartgpu\u002Fmain\u002Fdocs\u002Fassets\u002Fchart-gpu-demo.gif)\n\n### Streaming Multi-Chart Dashboard\n\nFive live charts. Annotations ticking in real time. Latency percentiles, throughput, error rates, resource utilization — all streaming simultaneously at 60 FPS on a single shared `GPUDevice`. This is what ChartGPU was built for.\n\nWant to build your own? Check out the [Multi-Chart Dashboard Cookbook](docs\u002Fguides\u002Fmultichart-dashboard-cookbook.md) for hands-on recipes and tips to get started!\n\n![Streaming multi-chart dashboard example](docs\u002Fassets\u002Fstreaming-dashboard-example.png)\n\n### 35M points (benchmark)\n\n35,000,000 points rendered at ~72 FPS (benchmark mode).\n\n![35 million point benchmark at 72 FPS](docs\u002Fassets\u002F35-million-ultimate-benchmark-example.png)\n\n## Quick Start\n\n```ts\nimport { ChartGPU } from 'chartgpu';\nconst container = document.getElementById('chart')!;\nawait ChartGPU.create(container, {\n  series: [{ type: 'line', data: [[0, 1], [1, 3], [2, 2]] }],\n});\n```\n\n### Annotations\n\nAdd reference lines, point markers, and text overlays to highlight important data features:\n\n```ts\nawait ChartGPU.create(container, {\n  series: [{ type: 'line', data: [[0, 1], [1, 3], [2, 2]] }],\n  annotations: [\n    \u002F\u002F Horizontal reference line\n    {\n      id: 'ref-y',\n      type: 'lineY',\n      y: 2.5,\n      layer: 'belowSeries',\n      style: { color: '#ffd166', lineWidth: 2, lineDash: [8, 6], opacity: 0.95 },\n      label: { text: 'threshold' },\n    },\n    \u002F\u002F Point marker at peak\n    {\n      id: 'peak',\n      type: 'point',\n      x: 1,\n      y: 3,\n      layer: 'aboveSeries',\n      marker: { symbol: 'circle', size: 8, style: { color: '#ff4ab0' } },\n      label: { template: 'peak={y}', decimals: 2 },\n    },\n  ],\n});\n```\n\nSee [Annotations Documentation](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002Fdocs\u002Fapi\u002Foptions.md#annotations) and the [annotations example](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Ftree\u002Fmain\u002Fexamples\u002Fannotation-authoring).\n\n## Highlights\n\n- 🚀 WebGPU-accelerated rendering for high FPS with large datasets\n- 📈 Multiple series types: line, area, bar, scatter, pie, candlestick\n- 🌡️ Scatter density\u002Fheatmap mode (`mode: 'density'`) for large point clouds — see [`docs\u002Fapi\u002Foptions.md#scatterseriesconfig`](docs\u002Fapi\u002Foptions.md#scatterseriesconfig) and [`examples\u002Fscatter-density-1m\u002F`](examples\u002Fscatter-density-1m\u002F)\n- 📍 Annotation overlays: reference lines (horizontal\u002Fvertical), point markers, and text labels — see [`docs\u002Fapi\u002Foptions.md#annotations`](docs\u002Fapi\u002Foptions.md#annotations) and [`examples\u002Fannotations\u002F`](examples\u002Fannotations\u002F)\n- 🧭 Built-in interaction: hover highlight, tooltip, crosshair\n- 🔁 Streaming updates via `appendData(...)` with typed-array support (`XYArraysData`, `InterleavedXYData`, `DataPoint[]`) — see [`examples\u002Fcartesian-data-formats\u002F`](examples\u002Fcartesian-data-formats\u002F)\n- 🔌 Line\u002Farea segmentation via `null` data entries — gaps for exchange outages, maintenance windows, etc. `connectNulls` option bridges gaps — see [`examples\u002Fexchange-gaps\u002F`](examples\u002Fexchange-gaps\u002F)\n- 🔍 X-axis zoom (inside gestures + optional slider UI)\n- 🎛️ Theme presets (`'dark' | 'light'`) and custom theme support\n- 🔗 Shared GPUDevice support for multi-chart dashboards (efficient GPU resource management) — see [`docs\u002Fapi\u002Fchart.md#shared-gpudevice`](docs\u002Fapi\u002Fchart.md#shared-gpudevice)\n- 🧱 Shared pipeline cache for multi-chart dashboards (dedupe shader modules + render pipelines across charts) — see [`docs\u002Fapi\u002Fchart.md#pipeline-cache-cgpu-pipeline-cache`](docs\u002Fapi\u002Fchart.md#pipeline-cache-cgpu-pipeline-cache)\n\n\n### Candlestick Charts\n\nFinancial OHLC (open-high-low-close) candlestick rendering with classic\u002Fhollow style toggle and color customization. The live streaming demo renders **5 million candlesticks at over 100 FPS** with real-time updates.\n\n![Candlestick chart example](docs\u002Fassets\u002Fcandle-stick-example.png)\n\n### Scatter Density (1M points)\n\nGPU-binned density\u002Fheatmap mode for scatter plots (`mode: 'density'`) to reveal structure in overplotted point clouds. See [`docs\u002Fapi\u002Foptions.md#scatterseriesconfig`](docs\u002Fapi\u002Foptions.md#scatterseriesconfig) and the demo in [`examples\u002Fscatter-density-1m\u002F`](examples\u002Fscatter-density-1m\u002F).\n\n![Scatter density chart example (1M points)](docs\u002Fassets\u002Fscatter-plot-density-chart-1million-points-example.png)\n\n### Interactive Annotation Authoring\n\nFull-featured annotation authoring system with interactive editing capabilities. Create, edit, drag, and delete annotations with an intuitive UI. Supports all annotation types: reference lines (horizontal\u002Fvertical), point markers, text annotations (plot-space + data-space tracking), labels, and styling options.\n\n![Annotations comprehensive demo](docs\u002Fassets\u002Fannotations.png)\n\n**Key features:**\n- **Right-click empty space** → Add vertical\u002Fhorizontal line or text note with custom color, style & label\n- **Click & drag annotations** → Reposition them (lines constrained to their axis)\n- **Right-click on annotation** → Edit properties or delete\n- **Full styling control** → Color picker, line style (solid\u002Fdashed), line width, and label customization\n- **Undo\u002FRedo support** → All annotations are reversible\n- **Scroll to zoom, Drag to pan** → Standard chart interactions work seamlessly\n\n![Annotation configuration dialog](docs\u002Fassets\u002Fannontations-add-indicator.png)\n\nThe annotation authoring system is demonstrated in the [`examples\u002Fannotation-authoring\u002F`](examples\u002Fannotation-authoring\u002F) example.\n\n## Installation\n\n```bash\nnpm install chartgpu\n```\n\n**GitHub Packages:**\n\n```bash\nnpm install @chartgpu\u002Fchartgpu\n```\n\nFor GitHub Packages, configure your `.npmrc`:\n\n```\n@chartgpu:registry=https:\u002F\u002Fnpm.pkg.github.com\n```\n\n## React Integration\n\nReact bindings are available via [`chartgpu-react`](https:\u002F\u002Fgithub.com\u002FChartGPU\u002Fchartgpu-react):\n\n```bash\nnpm install chartgpu-react\n```\n\n```tsx\nimport { ChartGPUChart } from 'chartgpu-react';\n\nfunction MyChart() {\n  return (\n    \u003CChartGPUChart\n      options={{\n        series: [{ type: 'line', data: [[0, 1], [1, 3], [2, 2]] }],\n      }}\n    \u002F>\n  );\n}\n```\n\nSee the [chartgpu-react repository](https:\u002F\u002Fgithub.com\u002FChartGPU\u002Fchartgpu-react) for full documentation and examples.\n\n## Browser support (WebGPU required)\n\n- Chrome 113+ or Edge 113+ (WebGPU enabled by default)\n- Safari 18+ (WebGPU enabled by default)\n- Firefox: Windows 114+, Mac 145+, Linux nightly\n\nSee the [gpuweb repository](https:\u002F\u002Fgithub.com\u002Fgpuweb\u002Fgpuweb\u002Fwiki\u002FImplementation-Status) for full Implementation Status\n\n## Who's Using ChartGPU\n\nChartGPU is a young project and we'd love to hear how you're using it! If your team or project uses ChartGPU, [open a pull request](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fpulls) to add your name here.\n\n\u003C!-- Add your project\u002Fcompany below:\n- [Your Project](https:\u002F\u002Flink) — short description\n-->\n\n## Documentation\n\n- Full documentation: [Getting Started](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002Fdocs\u002FGETTING_STARTED.md)\n- API reference: [`docs\u002Fapi\u002FREADME.md`](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002Fdocs\u002Fapi\u002FREADME.md)\n\n## Examples\n\n- Browse examples: [`examples\u002F`](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Ftree\u002Fmain\u002Fexamples)\n- Run locally:\n  - `npm install`\n  - `npm run dev` (opens `http:\u002F\u002Flocalhost:5173\u002Fexamples\u002F`)\n\n## Contributing\n\nSee [`CONTRIBUTING.md`](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002FCONTRIBUTING.md).\n\n## License\n\nMIT — see [`LICENSE`](https:\u002F\u002Fgithub.com\u002Fchartgpu\u002Fchartgpu\u002Fblob\u002Fmain\u002FLICENSE).\n\n## Architecture\n\nChartGPU follows a functional-first architecture. `ChartGPU.create(...)` owns the canvas and WebGPU lifecycle, delegating render orchestration to a modular render coordinator with 11 specialized modules.\n\nFor the full architecture diagram, see [`docs\u002FARCHITECTURE.md`](docs\u002FARCHITECTURE.md). For deep internal notes, see [`docs\u002Fapi\u002FINTERNALS.md`](docs\u002Fapi\u002FINTERNALS.md).","ChartGPU 是一个基于 WebGPU 的开源图表库，专为高性能的数据可视化而设计。它利用 GPU 加速实现了流畅的交互式渲染，尤其适用于处理大规模数据集。核心功能包括支持多种图表类型（如蜡烛图、散点图等），能够实时处理和显示多达5000万数据点，并保持60帧每秒的刷新率。此外，该库还提供了丰富的自定义选项以及便捷的开发文档与示例代码。适合应用于需要高效展示大量数据的场景，例如金融分析、科学研究或任何要求高精度和响应速度的数据监控平台。",2,"2026-06-11 03:50:59","high_star"]