Published
Edited
Apr 19, 2022
Importers
34 stars
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async function importCell(
cell, // e.g., "chart"
notebook, // e.g., "@d3/bar-chart" or "8d5ef3030dfd3bad"
injections = {} // e.g., {data: [{name, value}, …]}
) {

// Instantiate a new runtime, but reuse the existing runtime’s require.
// (This is ensures that any requires in imports still work.)
const library = Object.assign(new Library(), {require: () => require});
const runtime = new Runtime(library);

// Create the main module, including any injected values.
const main = runtime.module();
for (const name in injections) {
main.define(name, [], () => injections[name]);
}

// Load the requested notebook’s definition as an ES module.
const origin = `https://api.observablehq.com`;
const {default: define} = await import(
/^@[0-9a-z_-]+\/[0-9a-z_-]+(\/\d+)?([@~]|$)/.test(notebook += "") ? `${origin}/${notebook}.js?v=3`
: /^[0-9a-f]{16}([@~]|$)/.test(notebook) ? `${origin}/d/${notebook}.js?v=3`
: notebook);

// Create the imported notebook’s module, and then derive a module
// from it to inject the desired values. (If there are none, then
// this is basically a noop.)
const imported = runtime.module(define);
const derived = imported.derive([...Object.keys(injections)], main);

// In many cases the imported cell will only have a single value, but
// we must use the most generic representation (an async generator) as
// the imported cell may be an async generator, or may reference one.
return Generators.observe((notify) => {

// Create the primary variable with an observer that will report the
// desired cell’s fulfilled or rejected values.
main.variable({
fulfilled(value) { notify(value); },
rejected(value) { notify(Promise.reject(value)); }
}).import(cell, derived);

// Lastly, when this generator is disposed, dispose the runtime to
// ensure that any imported generators terminate.
return () => runtime.dispose();
});
}
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importCell("chart", "@d3/bar-chart@268")
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importCell("chart", "@d3/bar-chart@268", {height: 200, color: "brown"})
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importCell(
"chart",
"@d3/horizontal-bar-chart@254",
{
margin: {
top: 20,
right: 20,
bottom: 0,
left: 40
},
data: (await FileAttachment("us-population-by-age.csv").csv())
.map(({years, population}) => ({name: years, value: +population}))
}
)
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histogram = (data, options) => importCell("chart", "@d3/histogram@261", {...options, data})
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histogram(Array.from({length: 1000}, Math.random))
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observablehq = require("@observablehq/runtime@4")
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Runtime = observablehq.Runtime
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Library = observablehq.Library
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One platform to build and deploy the best data apps

Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.
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