Connect to Turbot Pipes from Jupyter Notebook
Since your Turbot Pipes workspace is just a Postgres database, you can use the
standard psycopg2
adapter to query your workspace database from Python.
The Connect tab for your workspace provides the details you need to connect a Jupyter Notebook to Turbot Pipes.

It's the usual drill: import psycopg2, specify your connection string, create a connection, then run a query. (See also: Connect to Turbot Pipes from Python.)
In this example we connect from an instance of Jupyter Notebook running in VSCode, load the query results into a
pandas.DataFrame, then use itsdescribemethod to summarize the data.
Connect to Steampipe CLI from Jupyter Notebook
To connect Jupyter Notebook to Steampipe CLI,
run steampipe service start --show-password
and use the displayed connection
details.
Steampipe service is running:
Database:
Host(s): localhost, 127.0.0.1, 172.28.158.171 Port: 9193 Database: steampipe User: steampipe Password: 9a**-****-**7e Connection string: postgres://steampipe:9a49-42e2-a57e@localhost:9193/steampipe
Call the Turbot Pipes API from Jupyter Notebook
You can also use the
Turbot Pipes query API.
Grab your token, put it an
environment variable like PIPES_TOKEN
, and use this pattern.
import json, os, requestsurl = 'https://pipes.turbot.com/api/latest/org/acme/workspace/jon/query'data = {'sql':'select name, region from aws_s3_bucket limit 2'}token = os.environ['PIPES_TOKEN']headers = {"Authorization": "Bearer " + token}r = requests.post(url, headers=headers, data=data)print(json.dumps(r.json(),indent=4))
{ "items": [ { "name": "10k-with-bucket-kms", "region": "us-east-2" }, { "name": "10k-with-standard-kms", "region": "us-east-2" } ]}