Skip to content

mikeperello-scopely/deck.gl

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

version build downloads Coverage Status

deck.gl | Website

WebGL2-powered, highly performant large-scale data visualization

docs

deck.gl is designed to simplify high-performance, WebGL-based visualization of large data sets. Users can quickly get impressive visual results with minimal effort by composing existing layers, or leverage deck.gl's extensible architecture to address custom needs.

deck.gl maps data (usually an array of JSON objects) into a stack of visual layers - e.g. icons, polygons, texts; and look at them with views: e.g. map, first-person, orthographic.

deck.gl handles a number of challenges out of the box:

  • Performant rendering and updating of large data sets
  • Interactive event handling such as picking, highlighting and filtering
  • Cartographic projections and integration with major basemap providers
  • A catalog of proven, well-tested layers

Deck.gl is designed to be highly customizable. All layers come with flexible APIs to allow programmatic control of each aspect of the rendering. All core classes such are easily extendable by the users to address custom use cases.

Flavors

Script Tag

<script src="https://unpkg.com/deck.gl@latest/dist.min.js"></script>

NPM Module

npm install deck.gl

Pure JS

React

Python

pip install pydeck

Third-Party Goodies

Learning Resources

Contributing

deck.gl is part of vis.gl, an OpenJS Foundation project. Read the contribution guidelines if you are interested in contributing.

Attributions

Data sources

Data sources are listed in each example.

The deck.gl project is supported by

BrowserStack

About

WebGL2 powered visualization framework

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • JavaScript 48.0%
  • TypeScript 42.4%
  • Python 4.6%
  • Jupyter Notebook 1.9%
  • HTML 1.9%
  • CSS 1.0%
  • Other 0.2%