Airtable

Join the Beta

For early access to the Airtable private beta, enter your email to join the waitlist

In the meantime, the Superblocks REST API integration can be used to connect to the Airtable REST API.

Overview

Connect Superblocks to Airtable to build internal tools that create, fetch, update, and delete records in your Airtable bases.

Setting up Airtable

Before getting started in Superblocks, first generate an Airtable personal access token following the instructions here.

1. Add integration

In Superblocks, select REST API from the integrations page.

2. Configure settings

Fill out the form with the following settings:

Setting	Required	Description
Name	TRUE	Name that will be displayed to users when selecting this integration in Superblocks
Base URL	TRUE	Airtable API URL, https://api.airtable.com/v0
Authentication	TRUE	Select Bearer Token in the dropdown and add your Airtable personal access token next to Token
Headers	FALSE	Additional headers
Params	FALSE	Additional query parameters

3. Save

Click Create to save the integration.

info

If using Superblocks Cloud, add these Superblocks IPs to your allowlist (not necessary for On-Premise-Agent)

4. Set profiles

Optionally, configure different profiles for separate development environments.

success

Airtable Connected You can now query Airtable in any Application, Workflow, or Scheduled Job.

Creating Airtable steps

Connect to your Airtable integration from Superblocks by creating steps in Application APIs, Workflows, and Scheduled Jobs.

Follow the Airtable REST API documentation to call specific URL paths. For example, to list records in a table.

Note, to visualize the data in a Superblocks table, a follow up code step is needed to flatten the JSON response so it is a list of objects. There are different ways to accomplish this, but here are a couple examples using Python and JavaScript. Adjust as needed for your data set.

Python

import pandas as pd
import json
flattened_json = pd.json_normalize(getAirtableRecords.output.records)
df = pd.DataFrame.from_dict(flattened_json)
return json.loads(df.to_json(orient='records'))

JavaScript

return getAirtableRecords.output.records.map((item) => {
    return {
      id: item.id, 
      status: item.fields.Status, 
      notes: item.fields.Notes, 
      project: item.fields.Projects, 
      project_doc: item.fields['Project docs'][0]['thumbnails']['large']['url']
    };
});

Use cases

Applications

With the Airtable project tracking data properly formatted, we can now visualize it in a table alongside other information and components like dropdowns, charts, and slideouts.