Hi Rodrigo,

One simple approach I’ve used is calling the REST API directly from a Databricks notebook using standard Python libraries—no extra setup or tools required.

The idea is to keep it minimal: generate the API signature, call the endpoint, and load the response. Here’s a very simplified example:

import time
import hashlib
import requests

# Generate API signature
def generate_signature(api_key, secret):
raw = api_key + secret + str(int(time.time()))
return hashlib.md5(raw.encode()).hexdigest()

# Call API
def fetch_data():
api_key = "<YOUR_API_KEY>"
secret = "<YOUR_SECRET>"
endpoint = "your-endpoint"

sig = generate_signature(api_key, secret)
url = f"https://api.example.com/v3/{endpoint}?apiKey={api_key}&sig={sig}"

response = requests.get(url)
return response.json()

# Run
data = fetch_data()

That’s really all you need to get started. From there, you can store the data in DBFS or a table.

If you need more throughput, you can later add parallel calls or pagination—but for smaller payloads, this works well and is very easy to maintain.

Best regards,
Rohan