The Python data source is one of the integration methods available on the Kuika platform that allows you to develop custom functions and business logic. Using Python, you can define custom operations within your application, create functions that accept parameters, and use these functions in application workflows.

With the Python data source, you can write custom code to address needs beyond the built-in actions, customize data processing workflows, and create reusable functions.

You may need to have an appropriate subscription plan to use the Python data source feature. You can upgrade your subscription to access more advanced development tools.

Add a Data Source Connection to Your App Using Python

1. Log in to the Kuika platform and open the project you’ll be working on from the Apps screen.
2. Open the Data Sources module.

• Here, you can view existing data sources and add a new one.

3. In the left panel, click the + icon next to the Sources heading.
4. Select the Python option.
5. Enter a name for your data source.
6. Click the CREATE button to complete the process.

Anatomy of the Python Action Modal

A. Top Menu

• Title (Python Action): The modal’s title indicates that the created data source is a Python-based action.
• CREATE Button: Used to save the Python data source you’ve created.
• Close Button (X): Used to close the screen and exit the process.

B. Top Settings Area

• Name: This field allows you to enter a description of what your function does. It helps other developers—or even you in the future—remember the purpose of the code.
• External Libraries (BETA): This field allows you to add external libraries to use in your Python code. It is currently labeled BETA.

• Python version: A drop-down menu that lets you specify which Python (CPython) version your code will run on. Supported versions:
  
  • CPython 3.14.6
  • CPython 3.13.14
  • CPython 3.12.13
  • CPython 3.11.15
  • CPython 3.10.20
• By default, the latest version (CPython 3.14.6) is selected; you can choose an older version as needed.
• Generate with AI: This option is used to automatically generate Python code with AI support. When enabled, you can receive code suggestions from the system.

C. Python Editor

• This is the code editing area.
• All custom functions are defined here.
• Default example structure.

def new_function(parameter1: str) -> str:    # Your code here    return parameter1

This structure demonstrates the following:

• Functions are defined using the `def` keyword.
• They can accept parameters.
• The parameter type can be specified using a type hint (: str).
• The return type can be defined as -> str.
• In the function body, the area where you will write your code is marked with a comment line (# Your code here).

D. TIDY UP Button

• Located in the upper-right corner of the code editor.
• It is used to format, indent, and make the written code more readable.

E. Test Console

• This area, located at the bottom of the screen, is used to test the functions you’ve written.
• In this section:
  
  • The function list is displayed.
  • Parameter input fields are provided.
  • The output results can be viewed.

Configuring Python Data Source Settings

Manual Code Writing

If “Generate with AI” is turned off, all code is written manually directly in the editor.

Example:

def to_upper_case(text: str) -> str:    return text.upper()

Code Generation with AI

If you enable the “Generate with AI” feature, you can create code automatically by writing a description.

Example command:

Create a function that converts the entered text to uppercase.

Python Version Selection

You can select the CPython version your code will run on from the Python version dropdown menu. Since language features or library compatibility may vary between different versions, it is recommended that you select the version that best suits your project’s needs.

Using External Libraries (BETA)

Through the External Libraries section, you can include additional packages in your project beyond the standard Python libraries. This feature is currently in the BETA phase.

Parameter Definition

You can add parameters to your functions.

Example:

def sum_numbers(value1: float, value2: float) -> float:    return value1 + value2

This function takes two numbers and returns their sum.

Specifying the Return Type

The data type to be returned must be specified in the function definition using the -> symbol.

Example types:

• str
• int
• float
• bool
• dict
• list
• Any

Testing Functions with the Test Console

After writing your code, you can use the Test Console section below.

1. Select the function you want to test.
2. Enter sample data into the parameter fields.
3. Run the function.
4. Check the returned result.

Example:

def hello(name: str) -> str:    return "Hello " + name

Parameter: Kuika Expected output: Hello Kuika

Saving the Data Source with CREATE

After completing and testing your code, you can save the Python data source by clicking the CREATE button. The saved data source becomes available for use within the application.

Expected Output / Result

Once these steps are completed:

• The Python data source is added to the Sources list.
• The defined functions become available for use in the system.
• Custom business rules can be managed via code.