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    Orca is an Electron app that generates images and reports of Plotly things like plotly.js graphs, dash apps, dashboards from the command line. Additionally, Orca is the backbone of Plotly's Image Server. Orca is also an acronym for Open-source Report Creator App.

    Visit to learn more or visit the Plotly forum.

    Follow @plotlygraphs on Twitter for Orca announcements.


    If you have Node.js installed (recommended v8.x), you can easily install Orca using npm as:

    $ npm install -g electron@1.8.4 orca

    which makes the orca executable available in your path.

    Alternatively, you can download the standalone Orca binaries corresponding to your operating system from the release page. Then, on

    Mac OS

    • Unzip from your Downloads/ folder
    • Double-click on orca-X.Y.Z.dmg file, that should open an installation window
    • Drag the orca icon into Applications
    • In finder, go to the Applications/ folder
    • Right-click on the orca icon and click on Open, this should open an Installation Succeeded window
    • Open the terminal and start using Orca!


    • Extract the file
    • In the release folder, double-click on orca Setup X.Y.Z, this will create an orca icon on your Desktop
    • Right-click on the orca icon, then click on Properties and copy the Starts in field
    • In the command prompt, run PATH %PATH%;<paste the "Starts in" field here>


    • Run $ chmod +x orca-X.Y.Z-x86_64.AppImage
    • Add it to your $PATH

    Quick start

    From the command line:

    $ orca graph '{ "data": [{"y": [1,2,1]}] }' -o fig.png

    generates a PNG from the inputted plotly.js JSON attributes. Or,

    $ orca graph --format svg

    generates an SVG from a plotly.js JSON hosted on

    To print info about the supported arguments, run:

    $ orca --help
    $ orca <command> --help

    To call orca from a Python script:

    from subprocess import call
    import json
    fig = {"data": [{"y": [1,2,1]}]}
    call(['orca', 'graph', json.dumps(fig)])

    To call orca from an R script:

    p <- plot_ly(x = 1:10, y = 1:10, color = 1:10)
    b <- plotly_build(p)$x[c("data", "layout")]
    json <- plotly:::to_JSON(b)
    cmd <- sprintf("orca graph '%s' -o r-export-test.png", json)

    API usage

    Using the orca npm module allows developers to build their own Plotly exporting tool. We export two Electron app creator methods run and serve. Both methods return an Electron app object (which is an event listener/emitter).

    To create a runner app:

    // main.js
    const orca = require('orca/src')
    const app ={
      component: 'plotly-graph',
      input: 'path-to-file' || 'glob*' || url || '{data: [], layout: {}}' || [/* array of those */],
      debug: true
    app.on('after-export', (info) => {
      fs.writeFile('output.png', info.body, (err) => console.warn(err))
    // other available events:
    app.on('after-export-all', () => {})
    app.on('export-error', () => {})
    app.on('renderer-error', () => {})

    then launch it with electron main.js

    Or, to create a server app:

    // main.js
    const orca = require('orca/src')
    const app = orca.serve({
      port: 9090,
      component: 'component name ' || [{
        name: 'plotly-graph',
        path: /* path to module if none given, tries to resolve ${name} */,
        route: /* default to same as ${name} */,
        // other options passed to component methods
        options: {
          plotlyJS: '',
          mathjax: '',
          topojson: '',
          mapboxAccessToken: ''
      }, {
        // other component
      }, {
        // other component ...
      debug: false || true
    app.on('after-export', (info) => {
    // other available events:
    app.on('after-connect', () => {})
    app.on('export-error', () => {})
    app.on('renderer-error', () => {})

    then launch it with electron main.js

    Plotly's image server

    Plotly's image server is dockerized and deployed here. See the deployment/ README for more info.

    System dependencies

    If you don't care about exporting EPS you can skip this section.

    The environment you're installing this into may require Poppler for EPS exports.

    Poppler installation via Aptitude (used by some *nix/BSD, e.g. Ubuntu)

    $ apt-get poppler-utils (requires `sudo` or root privileges)

    Poppler installation via Homebrew (third-party package manager for Mac OS X)

    $ brew install poppler


    See You can also contact us if you would like a specific feature added.

    Tests and Linux builds Mac OS build Windows build
    CircleCI Build Status AppVeyor


    Code released under the MIT © License.


    npm i orca

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