Announcing a new DataWeave tutorial series
Have you ever used DataWeave? In this three-part tutorial series, you will be guided through different DataWeave operators that you can use directly in your Anypoint Studio projects.
How to use DataWeave to read XML
At some point while developing a Mule application, it’s almost inevitable that you’ll need to manipulate XML.
In this article, I will teach you how to read XML using DataWeave scripts and how to modify its encoding, namespaces, fields, and attributes with the goal to generate a JSON document output.
DataWeave function chaining for Java programmers
In this article, you will learn how to use method chaining in DataWeave with reference to Java 8 lambda expressions and how to convert from Java Streams into DataWeave chaining.
Java 8 introduced the Stream API, which is used to process a stream of objects. Various methods can be chained together such as filter, limit, map, and reduce,
DataWeave: Generating XML
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.
DataWeave lambdas for Java programmers
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.
DataWeave 2.2 – additions to the Arrays module, part 2
This post will examine the remaining additions to the DataWeave Arrays module that weren’t covered in part 1: the join functions.
DataWeave 2.2 – additions to the Arrays module, part 1
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.
Mule programming style guide: DataWeave code
In this post, I will discuss how I format my DataWeave code to improve its readability.
DataWeave performance demystified
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.”
How NVIDIA integrated 12 different systems for GDPR compliance
Here’s how NVIDIA leveraged an API-led approach to build system APIs for backend applications and stitch data together using a process API that leverages MuleSoft’s Message Processors.