17.2

The dynamic Python library import feature is available for all custom integration and utility commands.

For built-in integrations, it becomes available when users extend functionality by adding custom commands. Support for this feature within integration commands is steadily expanding, and integrations that currently support it will display a Libraries tab.

Integrations supporting the dynamic python library feature also include a For Built-in Commands sub-tab. This read-only view shows the libraries used by built-in commands, allowing users to leverage them and avoid duplicate import statements when creating custom commands.

To demonstrate the use of this feature, follow the steps below to create a translator that accepts an input string and translates it into Spanish using the Google Translator library for use within a playbook.

1. Navigate to the Configuration module, then select the Utility Commands sub-module.

   

2. Add a new custom command.

   

   1. Click the button.

   2. Enter the display name for the command (i.e., Translate to Spanish).

   3. Ensure that the Python option is selected as the implementation method.

   4. Click the + Add button.

3. Paste the code below into the code editor, replacing any existing content.

   

   PY

   from deep_translator import GoogleTranslator  # Imports the translation tool used to convert text into another language
   import uuid  # Imports a tool to generate a unique ID for tracking each translation
   
   def TranslateToSpanish(*args):
       """
       Translates user input into Spanish using GoogleTranslator from deep-translator.
       args[0]: input text to translate
       """
       errors = []  # Will store any errors that occur during the process
       returnData = "Successful"  # Default result status
       context = []  # Optional metadata (unused here)
       keyFields = {}  # Optional key field storage (unused here)
       resultData = {}  # Will hold the final output data
       raw = {
           "Results": [],  # Will show the input and translated text
           "D3Errors": []  # Placeholder for any system-specific errors
       }
   
       trace_id = str(uuid.uuid4())  # Creates a unique ID for tracking this translation request
   
       try:
           # Checks if the user provided text and if it is not just empty spaces
           if not args or not args[0].strip():
               errors.append("An input phrase is required as the first argument.")  # Adds an error message
               return pb.returnOutputModel({}, "Failed", {}, [], {}, errors)  # Returns a failure result
   
           original_text = args[0].strip()  # Cleans up the user's input by removing unnecessary spaces
   
           # Translates the input text into Spanish, automatically detecting the source language
           translated_text = GoogleTranslator(source='auto', target='es').translate(original_text)
   
           # Prepares the main output data
           resultData = {
               "trace_id": trace_id,  # Unique ID for the request
               "original": original_text,  # Original text provided by the user
               "translated": translated_text  # Translated Spanish version
           }
   
           # Stores the input/output pair in the results
           raw["Results"].append({
               "Input": original_text,
               "Output": translated_text
           })
   
       except Exception as err:
           # If something goes wrong, record the error and update the status
           errors.extend(err.args)
           returnData = "Failed"
   
       # Returns all results, including the translated text, tracking ID, and any errors
       return pb.returnOutputModel(
           resultData,
           returnData,
           keyFields,
           context,
           raw,
           errors
       )

4. Define the external dependencies used in the code.

   

   1. Navigate to the Libraries tab.

   2. Paste the code below into the mini code editor to define any external dependencies used in the command.

      PY

      deep-translator==1.11.4

      The format for each entry is: <library name>==<version number> (e.g., deep-translator==1.11.4).

   3. Click the Save button to apply the changes.

5. Add a field that allows users to input the original text to be translated into Spanish.

   

   1. Navigate to the Inputs tab.

   2. Click the + New Input Parameter button.

   3. Name the parameter original_text.

   4. (Optional) Add a display name to improve clarity for users interacting with the command.

   5. (Optional) Provide a description to clarify the purpose of the input parameter.

   6. (Optional) Add sample data to illustrate expected input.

   7. Click the + Add button.

6. Enable the command for use in a playbook.

   

   1. Navigate to the Settings tab.

   2. Select the Command Task checkbox.

   3. Click the Submit button.

   4. Click the Submit button on the pop-up window.

RESULT

Users will be able to find and use this custom utility command as a command task in a playbook. If the command executed successfully, users can click the button to view the translated text.