Deploy a Custom Script to Data 360 Sandbox by Using UI

The deployment process packages your Python script, its dependencies, and Data 360 configuration, and then uploads them to Data 360.

• Enable Code Extension in Data Cloud Setup by using the Feature Manager. See Enable Data 360 Features in Feature Manager.
• Write custom scripts and validate them locally against a sandbox org. See Write and Validate Custom Scripts.

1. Go to your code extension script package directory.

   1cd </path/to/your/package>

2. Package your code and its dependencies into a .zip file.

   1sf data-code-extension script zip --package-dir ./payload

   The CLI automatically packages these files.

   • Source file: entrypoint.py
   • Dependencies: requirements.txt and equivalent dependency files
   • Configuration: config.json and other configuration files
   • Project files: Essential project structure files (for example, Dockerfile)

   To ensure a successful deployment, confirm that your zipped file size is less than 5 GB.

   Important

3. Go to Data Cloud Setup. Under Developer Tools, select Code Extension.

4. Click New.

5. Enter these details, and then click Next.

   Field	Description
   Deployment Name	A name for your deployment. This name helps you and your team identify the code extension in the Data 360 user interface.
   Deployment API Name	A unique identifier for your custom script deployment. The API name can contain only underscores and alphanumeric characters. It must be unique, begin with a letter, and be no more than 40 characters. The name can’t include spaces, end with an underscore, or contain two consecutive underscores.
   Description	A concise summary of what your code extension does and its intended business use case.

6. Specify these code details, and then click Next.

   

   Field	Description
   Programming Language	Select Python, the language used to write your custom script.
   Code Type	Select Script.
   Use in Feature	Select Batch Data Transform to use the deployed script in your batch data transform.
   Compute Size	Select the compute size based on your expected workload and resource requirements. Larger sizes provide more vCPUs and memory but consume more credits. The available compute sizes are: Standard - Large - 4 Compute Units per hour, Standard - X-Large - 8 Compute Units per hour, Standard - 2X-Large - 16 Compute Units per hour, and Standard - 4X-Large - 32 Compute Units per hour. With each size increase, the number of CPU cores and memory doubles.

7. To upload your code extension, click File Upload and select your zipped package. You can also drag your package into the upload window.

   Use the dropdown options to remove or replace the uploaded code extension as needed.

8. Click Submit Code to deploy your script.

   The deployment completes in a few minutes. Monitor the deployment status on the Code Extension page.

View Deployment Details

• Invoke Code Extension by Creating a Batch Data Transform
• Migrate Custom Script from Sandbox to Production

j

Code Extension in Data 360

Use Custom Script in Data 360

Quick Start

Set Up Salesforce CLI for Code Extension

Write and Validate Custom Script

Configure Data Model Object Schema for DMO-DMO Transforms

Deploy Custom Script to Sandbox

Deploy Custom Script to Data 360 Sandbox using UI

Deploy Custom Script to Data 360 Sandbox Using CLI

Invoke Code Extension by Creating a Batch Data Transform

Run Code Extension by Running a Batch Data Transform

Monitor Custom Script Deployments and Execution History

Migrate Custom Script to Production

Delete Deployment

Query Code Extension Logs by Using Query Editor

Query Code Extension Logs by Using the Query API

Query Code Extension Logs by Using Salesforce CLI

Execute the Code Extension Workflow by Using Agentforce Vibes

Execute the Code Extension Workflow by Using Agentic Tools and Salesforce Skills

Use Custom Functions in Data 360