diff --git a/examples/README.md b/examples/README.md index 633978c87..531a24bd3 100644 --- a/examples/README.md +++ b/examples/README.md @@ -52,6 +52,7 @@ ### Data loaders +- [`loader-airtable`](https://observablehq.observablehq.cloud/framework-example-loader-airtable/) - Loading data from Airtable - [`loader-arrow`](https://observablehq.observablehq.cloud/framework-example-loader-arrow/) - Generating Apache Arrow IPC files - [`loader-databricks`](https://observablehq.observablehq.cloud/framework-example-loader-databricks/) - Loading data from Databricks - [`loader-duckdb`](https://observablehq.observablehq.cloud/framework-example-loader-duckdb/) - Processing data with DuckDB diff --git a/examples/loader-airtable/README.md b/examples/loader-airtable/README.md new file mode 100644 index 000000000..27af460c8 --- /dev/null +++ b/examples/loader-airtable/README.md @@ -0,0 +1,7 @@ +[Framework examples →](../) + +# Airtable data loader + +View live: + +This Observable Framework example demonstrates how to write a JavaScript data loader that uses [Airtable](https://airtable.com/) as a backend. The data loader lives in [`src/data/penguins.csv.ts`](./src/data/penguins.csv.ts). diff --git a/examples/loader-airtable/observablehq.config.js b/examples/loader-airtable/observablehq.config.js new file mode 100644 index 000000000..fb0f92431 --- /dev/null +++ b/examples/loader-airtable/observablehq.config.js @@ -0,0 +1,3 @@ +export default { + root: "src" +}; diff --git a/examples/loader-airtable/package.json b/examples/loader-airtable/package.json new file mode 100644 index 000000000..ef86e357e --- /dev/null +++ b/examples/loader-airtable/package.json @@ -0,0 +1,22 @@ +{ + "type": "module", + "private": true, + "scripts": { + "clean": "rimraf src/.observablehq/cache", + "build": "rimraf dist && observable build", + "dev": "observable preview", + "deploy": "observable deploy", + "observable": "observable" + }, + "dependencies": { + "@observablehq/framework": "^1.7.0", + "airtable": "^0.12.2", + "dotenv": "^16.4.5" + }, + "devDependencies": { + "rimraf": "^5.0.5" + }, + "engines": { + "node": ">=18" + } +} diff --git a/examples/loader-airtable/src/.gitignore b/examples/loader-airtable/src/.gitignore new file mode 100644 index 000000000..1235d15eb --- /dev/null +++ b/examples/loader-airtable/src/.gitignore @@ -0,0 +1 @@ +/.observablehq/cache/ diff --git a/examples/loader-airtable/src/data/penguins.csv b/examples/loader-airtable/src/data/penguins.csv new file mode 100644 index 000000000..a1c6de8d4 --- /dev/null +++ b/examples/loader-airtable/src/data/penguins.csv @@ -0,0 +1,345 @@ +sex,body_mass_g,culmen_length_mm,culmen_depth_mm,id,flipper_length_mm,island,species +MALE,3750,39.1,18.7,1,181,Torgersen,Adelie +FEMALE,3800,39.5,17.4,2,186,Torgersen,Adelie +FEMALE,3250,40.3,18,3,195,Torgersen,Adelie +,,,,4,,Torgersen,Adelie +FEMALE,3450,36.7,19.3,5,193,Torgersen,Adelie +MALE,3650,39.3,20.6,6,190,Torgersen,Adelie +FEMALE,3625,38.9,17.8,7,181,Torgersen,Adelie +MALE,4675,39.2,19.6,8,195,Torgersen,Adelie +,3475,34.1,18.1,9,193,Torgersen,Adelie 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/dev/null +++ b/examples/loader-airtable/src/data/penguins.csv.ts @@ -0,0 +1,24 @@ +import "dotenv/config"; +import Airtable from "airtable"; +import {csvFormat} from "d3-dsv"; + +const {AIRTABLE_PAT, AIRTABLE_DB} = process.env; + +Airtable.configure({apiKey: AIRTABLE_PAT}); + +const base = Airtable.base(AIRTABLE_DB as string); + +const data: any[] = []; + +base("penguins") + .select({view: "Grid view"}) + .eachPage( + (records, fetchNextPage) => { + records.forEach((record) => data.push(record.fields)); + fetchNextPage(); + }, + (err) => { + if (err) throw err; + process.stdout.write(csvFormat(data)); + } + ); diff --git a/examples/loader-airtable/src/index.md b/examples/loader-airtable/src/index.md new file mode 100644 index 000000000..9dceda4e7 --- /dev/null +++ b/examples/loader-airtable/src/index.md @@ -0,0 +1,63 @@ +# Airtable data loader + +Here’s a TypeScript data loader that reads values from a database hosted on [Airtable](https://airtable.com/). + +It uses the [airtable.js](https://github.com/Airtable/airtable.js) development kit. See [the official API documentation](https://airtable.com/developers/web/api/introduction), which allows you to select your database for “live documentation” running on your own data; make sure to select the “JavaScript” tab. + +To run this data loader, you’ll need to create a personal access token at [/create/tokens](https://airtable.com/create/tokens) and save its value in the `.env` file at the root of the project. (Mine is scoped to only _read_ values from the _penguins_ database.) In that same `.env` file, you will also specify the database id: + +```txt +AIRTABLE_PAT="patXXXXX.XXXXXXXXXXXXXXXXXXXXXXXXXX" +AIRTABLE_DB="appWXXXXXXXXX" +``` + +
+ +To run this data loader, you’ll need to install `airtable` and `dotenv` using your preferred package manager such as npm or Yarn. + +
+ +The data loader’s code: + +```js run=false +import "dotenv/config"; +import Airtable from "airtable"; +import {csvFormat} from "d3-dsv"; + +const {AIRTABLE_PAT, AIRTABLE_DB} = process.env; + +Airtable.configure({apiKey: AIRTABLE_PAT}); + +const base = Airtable.base(AIRTABLE_DB as string); + +const data: any[] = []; + +base("penguins") + .select({view: "Grid view"}) + .eachPage( + (records, fetchNextPage) => { + records.forEach((record) => data.push(record.fields)); + fetchNextPage(); + }, + (err) => { + if (err) throw err; + process.stdout.write(csvFormat(data)); + } + ); +``` + +It lives in `data/penguins.csv.ts`, so we can load the data using `data/penguins.csv`. + +```js +Inputs.table(penguins) +``` + +```js echo +const penguins = FileAttachment("./data/penguins.csv").csv({typed: true}); +``` + +
+ +Using the Airtable API you can do more than just read the whole database: it’s also possible to load comments, or make specific queries to get a subset of the values. + +