Anypoint Platform Development: DataWeave

2 days
Instructor-led
Level 1

Registration for the instructor-led course

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Summary

This course is for developers interested in advancing their DataWeave skills beyond those taught in the Anypoint Platform Development: Fundamentals course.

Get a datasheet for the course here.

Note: For the Mule 3 / DataWeave 1 version of the course, go here.

Objectives

At the end of this course, students should be able to:

Write generalized and reusable transformations using variables, functions, DataWeave modules.
Use the DataWeave Playground to test and author DataWeave code.
Build complex transformations from smaller testable steps.
Build more robust and testable functions and expressions using strong typing, match operators, error handling, and logging.
Create, transform, filter, combine, shuffle, select from, and reduce complex data structures that include nested arrays, objects, and arrays of objects.
Recursively replace or format every element or a list of elements in a nested schema.
Reduce arrays to other data structures or data types and calculate key performance indicators.

Audience

Mule 4 developers or architects who want to advance their DataWeave skills so that they can build complex transformations

Prerequisites

Experience developing Mule 4 applications as demonstrated by one of the following:
- Passing the MuleSoft Certified Developer - Level 1 (Mule 4) exam
- Completion of the Anypoint Platform Development: Fundamentals (Mule 4) course
- Completion of the Anypoint Platform Development: Mule 4 for Mule 3 Users course
A basic knowledge of functional programming
Note: If you are new to functional programming, read An introduction to functional programming in JavaScript.

Setup requirements

A computer with at least 8-16 GB available RAM (16 highly recommended), 2GHz CPU, and 10GB available storage
Internet access to port 80 (with > 5Mbps download and > 2Mbps upload)
Anypoint Studio 7.12.0 or later with embedded Mule runtime
Advanced REST Client (or any other REST client application)

Get a detailed setup document here.

Module 1: Applying DataWeave fundamentals	Review and apply DataWeave fundamentals as learned in the Anypoint Platform Development: Fundamentals course Set example input to preview DataWeave results in Anypoint Studio Chain together two argument functions by using infix notation Filter, order, and group elements of an object or array Retype DataWeave expressions in the middle of code execution
Module 2: Organizing and reusing DataWeave code	Organize DataWeave code into variables and functions Enclose variables and functions in do statement scopes Pass functions and lambda expressions as arguments to other DataWeave functions Create and use reusable DataWeave modules
Module 3: Writing defensive and robust DataWeave	Write more defensive DataWeave expressions that filter and route data based upon conditions Write more robust functions using a match operator to test for data types Handle and raise errors Log from within DataWeave expressions
Module 4: Constructing arrays and objects	Add components to and remove elements from arrays and objects Construct objects from lists of DataWeave expressions using object constructor curly braces { } Troubleshoot common issues when using object constructor curly braces { }
Module 5: Iteratively mapping and joining arrays and objects	Combine objects and arrays into nested data structures by using map and mapObject functions Extract an array of keys and/or values from an object by using the pluck function Conditionally join two nested schemas together by using the join function
Module 6: Updating inside nested data structures	Conditionally update and mask parts of nested data structures Format and update nested data structures by using recursive functions
Module 7: Reducing data from arrays	Conditionally test, count, and sum up elements of an array by using the DataWeave core Arrays module Reduce and accumulate array elements to other output types using the reduce function Calculate key performance indicators from input collections by using the reduce function

Anypoint Platform Development: DataWeave

Registration for the instructor-led course

Summary

Objectives

Audience

Prerequisites

Setup requirements

Private training

Training resources

Community

Developer resources