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SDKs

This guide covers User-Agent configuration for Databricks SDKs. Each SDK provides functions to register partner and product identifiers that are applied globally to all SDK requests.

Databricks SDK for Python​

With the Python SDK, partners must use the useragent.with_partner() and useragent.with_product() functions to register their product and ISV identifiers:

import os
from databricks.sdk import WorkspaceClient, useragent
from databricks.sdk.core import Config

# Set partner and product identifiers
useragent.with_partner("<isv-name>")
useragent.with_product("<product-name>", "<product-version>")

# Auth from env
cfg = Config(
    host=os.getenv("DATABRICKS_HOST"),
    client_id=os.getenv("DATABRICKS_CLIENT_ID"),
    client_secret=os.getenv("DATABRICKS_CLIENT_SECRET"),
    auth_type="oauth-m2m",
)

# Workspace client
w = WorkspaceClient(config=cfg)

# Quick test
for s in w.schemas.list(catalog_name="samples"):
    print("-", s.name)
note
  • with_partner() identifies the ISV or integration owner
  • with_product() specifies the product name and version (version must follow SemVer)

Databricks SDK for Go​

With the Go SDK, partners must use the WithPartner() and WithProduct() functions:

package main

import (
    "github.com/databricks/databricks-sdk-go"
    "github.com/databricks/databricks-sdk-go/useragent"
)

func main() {
    useragent.WithPartner("<isv-name>")
    useragent.WithProduct("<product-name>", "<product-version>")

    w := databricks.NewWorkspaceClient()
    // Example API call...
}
note
  • WithPartner() identifies the ISV or integration owner
  • WithProduct() sets the product name and version (must be a valid SemVer version)

Databricks SDK for Java​

For the Databricks SDK for Java, use the UserAgent.withProduct() and UserAgent.withPartner() methods:

package com.example;

import com.databricks.sdk.core.DatabricksConfig;
import com.databricks.sdk.WorkspaceClient;
import com.databricks.sdk.service.catalog.CatalogInfo;
import com.databricks.sdk.service.catalog.ListCatalogsRequest;
import com.databricks.sdk.core.UserAgent;

public class ListCatalogsExample {
  public static void main(String[] args) {
    // Load configuration from environment
    String host = System.getenv("DATABRICKS_HOST");
    String clientId = System.getenv("DATABRICKS_CLIENT_ID");
    String clientSecret = System.getenv("DATABRICKS_CLIENT_SECRET");

    // Set partner and product identifiers
    UserAgent.withProduct("<product-name>", "<product-version>");
    UserAgent.withPartner("<isv-name>");

    // Build configuration
    DatabricksConfig config = new DatabricksConfig()
        .setHost(host)
        .setClientId(clientId)
        .setClientSecret(clientSecret);

    // Create workspace client
    WorkspaceClient client = new WorkspaceClient(config);

    // Example: List catalogs starting with 's'
    for (CatalogInfo catalog : client.catalogs().list(new ListCatalogsRequest())) {
      String name = catalog.getName();
      if (name != null && name.toLowerCase().startsWith("s")) {
        System.out.println("Catalog: " + name);
      }
    }
  }
}
note
  • withPartner() identifies the ISV or integration owner
  • withProduct() sets the product name and version (must be a valid SemVer version)

What's next​

  • Configure REST APIs: Set up User-Agent headers for direct API calls. See REST APIs.
  • Configure Databricks Connect: Implement telemetry for Spark sessions. See Databricks Connect.
  • Review User-Agent format: Understand the required format and guidelines. See Telemetry & Attribution.