How can I make Databricks API calls from notebook?

[User16752245312]

Access to Databricks APIs require the user to authenticate. This usually means creating a PAT (Personal Access Token) token. Conveniently, a token is readily available to you when you are using a Databricks notebook.

databricksURL = dbutils.notebook.entry_point.getDbutils().notebook().getContext().apiUrl().getOrElse(None)
myToken = dbutils.notebook.entry_point.getDbutils().notebook().getContext().apiToken().getOrElse(None)

Thus you don't need to generate and manage a token yourself.

import requests
 
header = {'Authorization': 'Bearer {}'.format(myToken)}
endpoint = '/api/2.0/jobs/runs/list'
payload = """{"limit": "5", "offset": "0"}"""
 
resp = requests.get(
  databricksURL + endpoint,
  data=payload,
  headers=header
)

[519320]

hmmm.... no resolution yet? 

[StephanieAlba]

This was a question and answer in one

[Panda]

@User16752245312  You can use Databricks Secret Scope to manage sensitive data such as personal access tokens (PATs) securely. Storing your token in a secret scope ensures you don’t hard-code credentials in your notebook, making it more secure.
For more details how to use Databricks REST API