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DataWeave With MuleSoft
Engineering Student MuleSoft
Meetup Group
July 16, 2022
16:30 IST (GMT+05:30)

2.
Safe Harbour Statement
● Both the speaker and the host are organizing this meet-up in individual capacity only. We are
not representing our companies here.
● This presentation is strictly for learning purposes only. Organizer/Presenter do not hold
any responsibility that same solution will work for your business requirements.
● This presentation is not meant for any promotional activities.
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Housekeeping
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4.
Organizers
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5.
About the Speaker
Nitish Raj, Lead Software Engineer – EPAM Systems
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• Started IT journey in 2014 as a Java developer
• Started working on Mule 3.8 in 2016
• Recent MuleSoft Certified Developer Level 2
• Co-Leader of Engineering Student Meetup and
Manchester Meetup group.
• MuleSoft Mentor

6.
Quick recap (Previous meetups)
1. What is MuleSoft and its core capabilities? Quick start with MuleSoft.
2. Start With API Design Using Restful API Modeling Language (RAML)
3. API Implementation using APIKIT router, Anypoint API Manager and API Policies
4. MuleSoft API testing
5. Error Handling With MuleSoft
6. DataWeave Basics
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What is DataWeave?
● Functional programming language designed for transforming data.
● Expression language used to configure components and connectors
● Can be used to access and evaluate the data in the payload, attributes, and variables of a
Mule event
● Case-sensitive
● Supports auto-complete
● It can be used to take one piece of data, and convert it into a different output format by
adding or removing values.
● It is also available in other contexts, like as a command-line tool.
● Current version: 2.4
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Sample Use Case
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• User fills out details and orders
an item
• In the Backend, Mule APIs kick
off to transform the data in
required formats.
• User details are sent to
Salesforce in JSON
• User Address details are the sent
to Database in JAVA format
• User items and billing details are
sent to SAP in XML format.

9.
Architecture of DataWeave Script
● A DataWeave script consists of a header and a body, separated by three dashes
● Header
○ Directives, e.g. Import, Input type, output type, Global vars, functions etc
● Body*
○ The body contains the expression that produces the resulting output, usually a data mapping
or a transformation.
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%dw 2.0
output application/json
---
payload.message
DataWeave
version (Major)
Header and Body
Separator
(Three dashes)
Body (Generates
the output)
Header contains
directives that apply to
the body expression

10.
Data Types
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Data Type Definition & Example
String Enclosed by double quotes
E.g. “mulesoft”
Boolean True or False, without any quotes
Number 12345
Date
DateTime
|2020-10-01|
|2020-10-01T23:57:59|
Array* Set of values enclosed in square brackets
E.g.
[1,2,3,4,5 ]
Object* Set of key value pairs enclosed in curly braces {}
E.g.
{“key”: “value”}
{“name”:”nitish”}

11.
Data Operators
● Data operators are symbols that enable you to perform operations on data to produce a
result.
● It is the same as most common programming languages.
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Operator Description
+ For addition
- For subtraction
* For multiplication
/ For division
Operator Description
< For less than.
> For greater than.
<= For less than or equal to.
>= For greater than or equal to.
== For equal to.
~= Equality operator that tries to
coerce one value to the type
of the other when the types
are different
Operator Description
not Negates the result of the
input.
! Negates the result of the
input.
and Returns true if the result of
all inputs is true, false if not.
or Returns true if the result of
any input is true, false if
not.
Mathematical Operators
Logical Operators
Equality & Relational
Operators

12.
Quiz
● Which one of the below is a valid JSON object
○ [{ "name": "nitish“ }]
○ { "name": "nitish“ }
○ { "name"}
● Which are the examples of a valid Array below
○ [{ "name": "nitish“ }]
○ [1,2,3,4,5]
○ { "name"}

13.
Mule 4 event structure revisit
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Accessing Mule objects
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15.
Quiz
● How a query param with a key name can be read using the DataWeave expression?
○ attributes.queryParams.name
○ payload.queryParams.name

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Writing expressions for JSON & Java
Input & Output
● The data model can consist of three different types of data: objects, arrays, simple literals
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17.
Hands On - Walkthrough
● Exploring DataWeave options
○ Transform Message Component
○ Metadata propagation from various connectors (HTTP Listener etc)
● Preview feature
○ Checking Tooling & Restarting
● Checking your DataWeave expression using review feature
● Creating multiple transformations
● Sample Quiz
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18.
Quiz
● Where does the DataWeave code go?
● Can you save the code externally and reuse it?

19.
DataWeave Selectors
● Traverse the structures of objects and arrays and return matching values.
● Can be used on Payload, variables and everywhere where DataWeave expression is
needed
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Selector Type Syntax Return Type
Single-value .keyName Any type of value that belongs to a matching key
Multi-value .*keyName Array of values of any matching keys
All repeated, Not in nested structure (Only root key if matched)
Descendants ..keyName Array of values of any matching descendant keys
Not repeated, Only first in each main and nested structure
Index [<index>] Value of any type at selected array index
Range [<index> to <index>] Array with values from selected indexes
Selector

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If Else and Else if
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Operator Description
if else An if operator evaluates a
conditional expression and returns
the value under the if only if the
conditional expression is true.
Otherwise, it returns the expression
under else. Every if expression must
have a matching else expression.
else if An else operator chains expressions
together within an if-else construct
by incorporating else if.
%dw 2.0
output application/json
var data = {"name": "nitish"}
---
if (data.name == "nitish") "Success"
else if (data.name[0] == "n") "Partial
Success"
else "Failure"
if (criteria_expression)
<return_if_true>
else if (criteria_expression)
<return_if_true>
else
<return if no other match>

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Map
● Use the map function to apply a transformation to each element in an array.
● The lambda is invoked with two parameters: index and the value. If these parameters are
not named, the index is defined by default as $$ and the value as $.
○ Input can be: JSON or Java Array
○ Returns Array
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payload map () { }
Payload should
be an array
Function, applied to each element
(Each data in array)
Lambda

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MapObject
● Iterates over an object using a mapper that acts on keys, values, or indices of that object.
Accepts Object Returns Object
● Parameters
○ Object: Input to the operator
○ Mapper: Expression that provides the key, value or index used for mapping the specified
object into an output object
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%dw 2.0
output application/json
var data = { "a":"b","c":"d"}
---
data mapObject {
($$$):
{($$): $}
}
{
"0": {
"a": "b"
},
"1": {
"c": "d"
}
}
Indices
Value
key

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Pluck
● Map an object into an array
● Iterates over an object and returns an array of keys, values, or indices from the object.
● Alternative to mapObject but returns Array instead of an array
● Parameters
○ Object: Input to operator
○ Mapper: Expression that provides the key, value or index used for mapping the specified
object into an output object
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%dw 2.0
output application/json
var data = { "a":"b","c":"d"}
---
data pluck {
($$$):
{($$): $}
}
[
{
"0": {
"a": "b"
}
},
{
"1": {
"c": "d"
}
}
]
Indices
Value
key

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Flatten
● Converts a set of sub-arrays into a single flattened array
○ Syntax: flatten(arrayOfArrays)
■ Input: [ [1,2,3], [4,5,[6]], [], [null] ]
■ Output: [ 1, 2, 3, 4, 5, [6], null ]
■ Input should always be an array, that can be array of multiple arrays or any supported data types.
● E.g. Useful in merging output result from Scatter Gather
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[1,2,3,4,5] [“A”,”B”,”C”,”D”,”E”]
[1,2,3,4,5, “A”,”B”,”C”,”D”,”E”]
Array 1 Array 2
Single Array

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Writing expressions for XML output
● XML documents must contain one root element that is the parent of all other elements:
● Speciying attributes for XML output
○ @(attributeName: attributeValue)
■ Attribute Name: Key name of the data
■ Attribute Value: mapped value/ required value
■ Attributes must always be “quoted”
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<root father=“Mr Muley”>
<child>
<subchild>.....</subchild>
</child>
</root>

26.
Calling a flow from a DataWeave expression
● Lookup function
○ Lookup(“flowToBeCalled”, payload)
■ 3rd argument: Timeout in ms (Optional)
○ Arguments
■ Flow name to be called
■ Payload (data) to be sent
● Limitation
○ Can not call sub-flows
○ Default timeout is 10 seconds, Can be modified
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Creating multiple transformations
● You can also create multiple transformations with one Transform Message component
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28.
Quiz
● Does the target of a transformation have to be the payload?
● Is DataWeave expression case sensitive?
● Difference between Map, Map Object and Pluck.
● Does Flatten remove null values?
● Where DWL files are stored in the project structure?
A. src/main/resources
B. src/test/resources
C. sr/main/mule
D. src/test/munit
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29.
Trivia Quiz
1. Can a DataWeave expression be stored in a variable?
A. True
B. False
2. Which DataWeave operator takes in Object(s) as input and outputs as Array
A. Map
B. Map Object
C. Pluck
D. Concat
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30.
Trivia Quiz
3. DataWeave lookup() operator can only call the below kind of flow
A. Sub-flow
B. Flow
4. How can an attribute be specified in XML data?
A. @(map: mapObject)
B. @(attributeValue: attributeName)
C. @(attributeName: attributeValue)
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31.
Introduce yourself to your neighbor
Networking time

32.
Thank you