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Learn how to effectively iterate and transform dynamic objects in `DataWeave`, handling scenarios where values are strings or arrays using `MuleSoft`.
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Mastering Dynamic Object Transformation in DataWeave with MuleSoft

When working with dynamic payloads in MuleSoft's DataWeave, one common challenge is transforming the structure of these objects, especially when key names and their respective types vary. For instance, you may find yourself needing to convert certain string values into arrays while leaving other keys untouched. In this guide, we will explore this problem and provide a solution using a clear and concise approach.

The Problem

You have a dynamic output object that may contain various data types, including strings, numbers, and nested objects. Specifically, you need to handle a case where one of the keys—let’s say 'bbb'—contains a list represented as a string (e.g., "221,222,223"), and you want this to be converted into an array.

For example, given the following input:

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You want the output to be structured as follows:

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The key here is that only the value associated with the key 'bbb' needs to be transformed into an array, while other keys and their values should remain unchanged.

The Solution

To tackle this problem, we can define a recursive function. This function will check the type of each value and apply the appropriate transformation, ensuring that we also handle nested data structures. Let's break down the key components of the solution.

Step 1: Defining the Functions

We need several helper functions to achieve our transformation:

filterKeys: This function will filter the keys of the object based on our criteria.

splitString: This function will split a string by commas and trim any extra whitespace from the resulting array.

orderMembers: This is the main function that recursively processes the input object and applies transformations based on the type of each value.

Here’s how these functions look in DataWeave:

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Step 2: Executing the Transformation

With these functions defined, you can now invoke orderMembers by passing in your input dynamic object along with an array of keys that need to be processed. In this case, we’ll specifically focus on 'bbb':

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Step 3: Understanding the Output

Using the functions defined above, the output for the given testData will be structured as follows:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

This guide has shown you how to effectively iterate through a dynamic payload object using DataWeave, allowing you to convert specific string representations of lists into arrays while keeping the rest of the structure intact. By using recursive functions and careful type matching, you can adapt your transformations for various scenarios efficiently.

By mastering these DataWeave techniques, you can streamline your data processing tasks in MuleSoft and handle intricate transformations with confidence.