Welcome
Administration
Learn about how to configure, manage, and maintain HCL Detect environments. It includes details on system setup, user management, and permissions, ensuring seamless operation and efficient deployment of your continuous delivery processes.
About derived attribute functions
Derived attribute functions enable you to offload complex calculations involving multiple tuple attributes to custom Python scripts.
Implement Python script and JSON configuration
Define your custom business logic in a Python script and expose it to the Detect UI using a JSON configuration file.

Getting Started
Welcome to the documentation for HCL Detect, where you can find information about how to install, maintain, and use this service.
Installation
Learn more about HCL Detect installation and deploying core components of the product.
Administration
Learn about how to configure, manage, and maintain HCL Detect environments. It includes details on system setup, user management, and permissions, ensuring seamless operation and efficient deployment of your continuous delivery processes.
- Introduction
  Use this guide to administer HCL Detect, including user and role access, CLI-based configuration and management tasks, DEL reference topics, and support resources.
- User & Role Management
  This page explains how to manage roles and permission in HCL Detect.
- Configuration Management
  Use CLI commands to query and validate the infrastructure settings required for Detect operations.
- Metadata Management
  Use CLI commands to discover data sources, search tables, and retrieve column metadata for Detect integrations.
- Profile Management
  Manage profile definitions and attributes through the HCL Detect UI or CLI.
- Feed Application
  Create and manage feed applications through the HCL Detect UI or CLI.
- About derived attribute functions
  Derived attribute functions enable you to offload complex calculations involving multiple tuple attributes to custom Python scripts.
  - Implement Python script and JSON configuration
    Define your custom business logic in a Python script and expose it to the Detect UI using a JSON configuration file.
  - Configure derived attribute functions in the feed application
    Apply custom Python logic to your data streams by configuring the derived attribute in the feed management UI.
  - Configure derived attribute functions in the pipeline
    Incorporate the configured derived attribute into your active pipeline for data processing.
- Feed Parser Mapping
  Use CLI commands to define and maintain feed parser mappings between incoming feed fields and Detect target attributes.
- Destination Management
  Use CLI commands to configure, validate, and manage destination endpoints for Detect event delivery.
- Crypto Management
  Use CLI crypto utilities to encrypt and decrypt sensitive values used in Detect configuration workflows.
- Troubleshooting & Common Errors
- Detect Expression Language
- Detect Expression Language Built-in Functions
Working with the System
The section provides comprehensive instructions for creating, configuring, and managing marketing events. It covers topics such as defining audience conditions, setting up triggers, deploying events, and tracking their performance. Additionally, this section includes explanations of key terminology and offers advanced options to optimize event management.
System Data Model
This section provides detailed information about the internal tables used within the Detect module. It includes descriptions of each table's structure, purpose, and relationships, aiding administrators and developers in understanding and managing the underlying database schema effectively.

Implement Python script and JSON configuration

Define your custom business logic in a Python script and expose it to the Detect UI using a JSON configuration file.

About this task

The system requires a defined Python script and an updated JSON file to register the new derived attribute function.

Procedure

Create or update the Python file to define your custom logic.

The function must accept the variables provided by the tuple (for example, the transaction amount) and the variables configured in the UI (for example, GST rate and surcharge amount).

The following example demonstrates a function that calculates a GST amount and adds a fixed surcharge:

def get_GST_on_transaction_amount_plus_some_fixed_surcharges(transaction_amount, gst_rate, surcharge_amount):
    # Calculate the GST value based on the rate (e.g., 18%)
    gst_value = transaction_amount * (gst_rate / 100)
    
    # Add the fixed surcharge amount (e.g., 5 rupees)
    total_value = gst_value + surcharge_amount
    
    # Return the computed value to the engine as a double
    return total_value

Add the JSON entry to the configuration file.

This entry maps the UI fields to the Python function, specifying the required tuple attributes (such as transaction amount) and the double values the user must configure (such as GST rate).

Note:
To retain a computed value for use by future tuples of the same entity, add a storeBackAttribute entry to the JSON. For more information, see the store back mechanism described in Store back mechanism
Restart the Tomcat server and the engine.

You must perform a restart because the engine fetches the available function definitions during startup. Without a restart, the newly added function won't appear in the derived directory section of the UI.