Integration with Airtable expands its spreadsheet-like functionality for more advanced data management and analysis. For example, you can leverage SQL and Python to automatically aggregate Airtable records, then visualize project statuses, inventory levels, or customer data through MDX-powered dashboards. Additionally, consolidating data from form entries or external services streamlines operational workflows, enabling faster, more informed decisions across the team. With Morph, these data-driven processes become simpler and more efficient, supporting improved collaboration and productivity.

Set up connection information

Please refer to the DB/SaaS Connection to register the integration.

Once the integration is created, you can retrieve an AccessToken using the integration name from get_auth_token. With this token, you can proceed with data processing using the API.

import pandas as pd

import morph
from morph import MorphGlobalContext
from morph_lib.api import get_auth_token

@morph.func
def get_salesforce_opportunities(context: MorphGlobalContext) -> pd.DataFrame:
    access_token = get_auth_token("salesforce-connection-name")

    # ↓↓↓ call API with access_token ↓↓↓

Links

• Airtable API Docs