Extending Observable to the backend with a custom serverless runtime.
Innovative live-coding workflows against production traffic.
// let’s fetch this rather large dataset from the https://covid19.who.int/ home page.
// note: we use fetchp, which acts as a CORS-enabled proxy when developing this notebook
// this cell works only if our notebook is published with a custom URL.
allData = fetchp(
"https://covid19.who.int/page-data/table/page-data.json"
).then((d) => d.json())
// extract this interesting subset about vaccination
data = allData.result.pageContext.rawDataSets.vaccineData.data
// deploy the subset as a csv
deploy("data.csv", async (req, res) => {
res.header("Cache-control", `public, max-age=${1 * 3600}`); // 1 hour cache on the CDN
res.header("Content-Type", "text/plain");
res.send(aq.from(data).toCSV());
})
// deploy the subset as an apache arrow file
deploy("data.arrow", async (req, res) => {
res.header("Cache-control", `public, max-age=${1 * 3600}`); // 1 hour cache on the CDN
res.header("Content-Type", "application/octet-stream");
res.header("Content-Disposition", `attachment; filename="data.arrow"`);
res.send(aq.from(data).toArrowBuffer());
})
import { deploy } from '@endpointservices/serverless-cells'
import { fetchp } from "@tomlarkworthy/fetchp"
aq = require('arquero')
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.