In this blog post, I will show you how to generate XML output from a JSON data source while avoiding some of the most common pitfalls and explain how to use encoding, namespaces, fields, and attributes.
In Mule 4, DataWeave is everywhere: every listener and processor can be configured with it. Because most Mule users already know Java well, this article will help Java developers to easily use DataWeave by rewriting their lambdas expressions.
MuleSoft recently released runtime version 4.2.0, and along with it, DataWeave 2.2! DataWeave 2.2 has a ton of new features that I won’t be able to cover in a single blog post, so I’ll be covering them over the course of a few blog posts.
I have been asked so many times about DataWeave Performance during my time in the field. This is because developers try to find arguments to not use it when they realize that a new and proprietary programming language is introduced. Most of the time they have the same “natural response” of resolving the problem by going to the known and comfortable zone called “Java.”
When building DataWeave transformations for your Mule application, you will run into situations in which you will need to invoke external logic that may be encapsulated in a Java POJO, Groovy, Python, Ruby script, or really any lookup that uses a CSV file or database table as part of the transformation.
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