This module contains all the core data weave functionality. It is automatically imported into any DataWeave script.

Functions

++

++(Array<S>, Array<T>): Array<S | T>

Concatenates the elements of two arrays into a new array.

If the two arrays contain different types of elements, the resulting array is all of S type elements of Array<S> followed by all the T type elements of Array<T>. Either of the arrays can also have mixed-type elements.

The example concatenates an Array<Number> with an Array<String>.

Transform
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%dw 2.0
output application/json
---
{
  result: [0, 1, 2] ++ ["a", "b", "c"]
}
Output
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{
  "result": [0, 1, 2, "a", "b", "c"]
}

Note that the arrays can contain any supported data type, for example:

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%dw 2.0
output application/json
---
{
  a: [0, 1, true, "my string"] ++ [2, [3,4,5], {"a": 6}]
}
Output
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{
  "a": [0, 1, true, "my string", 2, [3, 4, 5], { "a": 6}]
}

++(String, String): String

Concatenates the characters of two strings.

Strings are treated as arrays of characters, so the ++ operator concatenates the characters of each String as if they were arrays of single character String. In the example, the String 'Mule' is treated as Array<String> ['M', 'u', 'l', 'e'].

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%dw 2.0
output application/json
---
{
  name: 'Mule' ++ 'Soft'
}
Output
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{
  'name': MuleSoft
}

++(Object, Object): Object

Concatenates two input objects and returns one flattened object.

The ++ operator extracts all the key-values pairs from each object, then combines them together into one result object.

Transform
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%dw 2.0
output application/xml
---
concat: {aa: 'a', bb: 'b'} ++ {cc: 'c'}
Output
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<?xml version='1.0' encoding='UTF-8'?>
<concat>
  <aa>a</aa>
  <bb>b</bb>
  <cc>c</cc>
</concat>

If you leave the output as application/dw, the example above concatenates each key-value pair from the two objects {aa: 'a', bb: 'b'} ++ {cc: 'c'} and returns a single object {aa: 'a' , bb: 'b', cc: 'c'}.

++(Date, LocalTime): LocalDateTime

Appends a LocalTime with a Date object and returns a more precise LocalDateTime value.

Date and LocalTime instances are written in standard Java notation, surrounded by pipe (|) symbols. The result is a LocalDateTime object in the standard Java format.

Transform
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%dw 2.0
output application/json
---
{
  a: |2003-10-01| ++ |23:57:59|,
  b: |2003-10-01| ++ |23:57:59Z|
}
Output
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{
    'a': '2003-10-01T23:57:59',
    'b': '2003-10-01T23:57:59Z'
}

Note that the order in which the two objects are concatenated is irrelevant, so logically, Date + LocalTime produces the same result as LocalTime + Date.

++(LocalTime, Date): LocalDateTime

Appends a LocalTime with a Date object and returns a more precise LocalDateTime value.

Transform
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%dw 2.0
output application/json
---
{
  a: |23:57:59| ++ |2003-10-01|,
  b: |23:57:59Z| ++ |2003-10-01|
}
Output
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{
    'a': '2003-10-01T23:57:59',
    'b': '2003-10-01T23:57:59Z'
}

Note that the order in which the two objects are concatenated is irrelevant, so logically, LocalTime + Date produces the same result as Date + LocalTime.

++(Date, Time): DateTime

Appends a Date to a Time object and returns a more precise DateTime value.

Transform
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%dw 2.0
output application/json
---
{
  a: |2003-10-01| ++ |23:57:59|,
  b: |2003-10-01| ++ |23:57:59Z|
}
Output
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{
    'a': '2003-10-01T23:57:59',
    'b': '2003-10-01T23:57:59Z'
}

Note that the order in which the two objects are concatenated is irrelevant, so logically, Date + Time produces the same result as Time + Date.

++(Time, Date): DateTime

Appends a Date to a Time object to return a more precise DateTime value.

Transform
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%dw 2.0
output application/json
---
{
  a: |23:57:59| ++ |2003-10-01|,
  b: |23:57:59Z| ++ |2003-10-01|
}
Output
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{
    'a': '2003-10-01T23:57:59',
    'b': '2003-10-01T23:57:59Z'
}

Note that the order in which the two objects are concatenated is irrelevant, so logically, Date + Time produces the same result as a Time + Date.

++(Date, TimeZone): DateTime

Appends a TimeZone to a Date type value and returns a DateTime result.

Transform
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%dw 2.0
output application/json
---
a: |2003-10-01T23:57:59| ++ |-03:00|
Output
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{
  'a': '2003-10-01T23:57:59-03:00'
}

++(TimeZone, Date): DateTime

Appends a Date to a TimeZone type value and returns a DateTime result.

Transform
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%dw 2.0
output application/json
---
a: |-03:00| ++ |2003-10-01T23:57:59|
Output
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{
  'a': '2003-10-01T23:57:59-03:00'
}

++(LocalDateTime, TimeZone): DateTime

Appends a TimeZone to a LocalDateTime type value and returns a DateTime result.

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%dw 2.0
output application/json
---
a: |2003-10-01T23:57:59| ++ |-03:00|
Output
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{
  'a': '2003-10-01T23:57:59-03:00'
}

++(TimeZone, LocalDateTime): DateTime

Appends a LocalDateTime to a TimeZone type value and returns a DateTime result.

Transform
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%dw 2.0
output application/json
---
a: |-03:00| ++ |2003-10-01T23:57:59|
Output
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{
  'a': '2003-10-01T23:57:59-03:00'
}

++(LocalTime, TimeZone): Time

Appends a TimeZone to a LocalTime type value and returns a Time result.

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%dw 2.0
output application/json
---
a: |2003-10-01T23:57:59| ++ |-03:00|
Output
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{
  'a': '2003-10-01T23:57:59-03:00'
}

++(TimeZone, LocalTime): Time

Appends a LocalTime to a TimeZone type value and returns a Time result.

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%dw 2.0
output application/json
---
a: |-03:00| ++ |2003-10-01T23:57:59|
Output
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{
  'a': '2003-10-01T23:57:59-03:00'
}

 — 

--(Array<S>, Array<Any>): Array<S>

Removes all the entries from the source Array that are present on the toRemove Array parameter.

When an element in the lhs array matches one of the values in the rhs array, it is removed. If multiple elements in the lhs array match a value, all matching values are removed from the lhs.

Transform
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%dw 2.0
output application/json
---
a: [0, 1, 1, 2] -- [1,2]
Output
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{
  "a": [0],
}

--({ (K)?: V }, Object): { (K)?: V }

Removes all the entries from the source Object that are present on the toRemove Object parameter.

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%dw 2.0
output application/json
---
{
   hello: 'world',
   name: "DW"
 } -- {hello: 'world'}
Output
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{
   "name": "DW"
}

--(Object, Array<String>)

Removes the properties from the source Object that are present the given list of keys.

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%dw 2.0
output application/json
---
{
   hello: 'world',
   name: "DW"
 } -- ['hello']
Output
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{
   "name": "DW"
}

--(Object, Array<Key>)

Removes the properties from the source Object that are present the given list of keys.

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%dw 2.0
output application/json
---
{
   hello: 'world',
   name: "DW"
 } -- ['hello' as Key]
Output
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{
   "name": "DW"
}

abs

abs(Number): Number

Returns the absolute value of a number.

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%dw 2.0
output application/json
---
{
  a: abs(-2),
  b: abs(2.5),
  c: abs(-3.4),
  d: abs(3)
}
Output
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{
  "a": 2,
  "b": 2.5,
  "c": 3.4,
  "d": 3
}

avg

avg(Array<Number>): Number

Creates an average of all the values in an array and outputs a single number. The array must of course contain only numerical value in it.

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%dw 2.0
output application/json
---
{
  a: avg([1, 1000]),
  b: avg([1, 2, 3])
}
Output
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{
  "a": 500.5,
  "b": 2.0
}

ceil

ceil(Number): Number

Rounds a number upwards, returning the first full number above than the one provided.

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%dw 2.0
output application/json
---

{
  a: ceil(1.5),
  b: ceil(2.2),
  c: ceil(3)
}
Output
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{
  "a": 2,
  "b": 3,
  "c": 3
}

contains

contains(Array<T>, Any): Boolean

Indicates whether an array contains a given value. Returns true or false.

Transform
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%dw 2.0
output application/json
---
ContainsRequestedItem: payload.root.*order.*items contains "3"
Input
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<?xml version="1.0" encoding="UTF-8"?>
<root>
    <order>
      <items>155</items>
    </order>
    <order>
      <items>30</items>
    </order>
    <order>
      <items>15</items>
    </order>
    <order>
      <items>5</items>
    </order>
    <order>
      <items>4</items>
      <items>7</items>
    </order>
    <order>
      <items>1</items>
      <items>3</items>
    </order>
    <order>
        null
    </order>
</root>
Output
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{
  "ContainsRequestedItem": true
}

contains(String, String): Boolean

Indicates whether a string contains a given substring. Returns true or false.

Transform
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%dw 2.0
output application/json
---
ContainsString: payload.root.mystring contains "me"
Input
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<?xml version="1.0" encoding="UTF-8"?>
<root>
  <mystring>some string</mystring>
</root>
Output
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{
  "ContainsString": true
}

contains(String, Regex): Boolean

Indicates whether a string contains a match to a given regular expression. Returns true or false.

Transform
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%dw 2.0
output application/json
---
ContainsString: payload.root.mystring contains /s[t|p]rin/
Input
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<?xml version="1.0" encoding="UTF-8"?>
<root>
  <mystring>A very long string</mystring>
</root>
Output
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{
  "ContainsString": true
}

daysBetween

daysBetween(Date, Date): Number

Returns the number of days between two dates.

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%dw 2.0
output application/json
---
{
  "days": daysBetween("2016-10-01T23:57:59-03:00", "2017-10-01T23:57:59-03:00")
}
Output
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 {
   "days": 365
 }

distinctBy

distinctBy(Array<T>, (item: T, index: Number) → Any): Array<T>

Returns only unique values from an array that may have duplicates. The lambda is invoked with two parameters: value and index. If these parameters are not defined, the index is defined by default as $$ and the value as $.

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%dw 2.0
output application/json
---
{

    book : {
      title : payload.title,
      year: payload.year,
      authors: payload.author distinctBy $
    }
}
Input
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{
  "title": "XQuery Kick Start",
  "author": [
    "James McGovern",
    "Per Bothner",
    "Kurt Cagle",
    "James Linn",
    "Kurt Cagle",
    "Kurt Cagle",
    "Kurt Cagle",
    "Vaidyanathan Nagarajan"
  ],
  "year":"2000"
}
Output
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{
  "book": {
    "title": "XQuery Kick Start",
    "year": "2000",
    "authors": [
      "James McGovern",
      "Per Bothner",
      "Kurt Cagle",
      "James Linn",
      "Vaidyanathan Nagarajan"
    ]
  }
}

distinctBy(Null, (item: Nothing, index: Nothing) → Any): Null

Helper function that allows distinctBy to work with null values.

distinctBy({ (K)?: V }, (value: V, key: K) → Any): Object

Returns an object with unlike key value pairs.

The function (a lambda) is invoked with two parameters: value and key. If these parameters are not defined, the index is defined by default as $$ and the value as $`.

Transform
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%dw 2.0
output application/xml
---
{

     book : {
        title : payload.book.title,
        authors: payload.book.&author distinctBy $
     }
}
Input
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<book>
  <title> "XQuery Kick Start"</title>
  <author>
    James Linn
  </author>
  <author>
    Per Bothner
  </author>
  <author>
    James McGovern
  </author>
  <author>
    James McGovern
  </author>
  <author>
    James McGovern
  </author>
</book>
Output
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<book>
  <title> "XQuery Kick Start"</title>
  <authors>
      <author>
        James Linn
      </author>
      <author>
        Per Bothner
      </author>
      <author>
        James McGovern
      </author>
  </authors>
</book>

endsWith

endsWith(String, String): Boolean

Returns true or false depending on if a string ends with a provided substring.

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%dw 2.0
output application/json
---
{
  a: "Mariano" endsWith "no",
  b: "Mariano" endsWith "to"
}
Output
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{
  "a": true,
  "b": false
}

filter

filter(Array<T>, (item: T, index: Number) → Boolean): Array<T>

Returns an array that containing elements that meet the criteria specified by a function (a lambda). The function is invoked with two parameters: value and index.

If the parameters are not named, the index is defined by default as $$, and the value is $. In the next example, the value ($) in the returned array must be greater than 2.

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%dw 2.0
output application/json
---
{
  biggerThanTwo: [1, 2, 3, 4, 5] filter($ > 2)
}
Output
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{
  'biggerThanTwo': [3,4,5]
}

In the next example, the index ($$) of the returned array must be greater than 2.

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%dw 2.0
output application/json
---
{
  indexBiggerThanTwo: [1, 2, 3, 4, 5] filter($$ > 2)
}
Output
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{
  'indexBiggerThanTwo': [4,5]
}

The next example passes named key and value parameters.

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%dw 2.0
output application/json
---
{
 example3: [0, 1, 2, 3, 4, 5] filter ((key1, value1) -> key1 > 3 and value1 < 5 )
}
Output
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{
  'example3': [4]
}

filter(Null, (item: Nothing, index: Nothing) → Boolean): Null

Helper function that allows filter to work with null values.

filterObject

filterObject({ (K)?: V }, (value: V, key: K, index: Number) → Boolean): { (K)?: V }

Returns an object that filters an input object based on a matching condition.

The function (a lambda) is invoked with three parameters: value, key, and index. If these parameters are not named, the value is defined by default as $, the key $$ and the index $$$.

This example filters an object by its value.

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%dw 2.0
output application/json
---
{'letter1': 'a', 'letter2': 'b'} filterObject ((value1) -> value1 == 'a')
Output
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{
  'letter1': 'a'
}

You can produce the same results with this input:

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%dw 2.0
output application/json
---
{'letter1': 'a', 'letter2': 'b'} filter ($ == 'a')

filterObject(Null, (value: Nothing, key: Nothing, index: Nothing) → Boolean): Null

Helper function that allows filterObject to work with null values.

find

find(Array<T>, Any): Array<Number>

Returns the array of all index where the elementToFind where present.

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%dw 2.0
output application/json
---
["name", "lastName"] find "name"
Output
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[
   0
]

find(String, Regex): Array<Array<Number>>

Returns the array of index where the regex matched in the text.

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%dw 2.0
output application/json
---
"DataWeave" find /a/
Output
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[
   [1], [3], [6]
]

find(String, String): Array<Number>

Returns the array of all index where the textToFind where present.

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%dw 2.0
output application/json
---
"aabccdbce" find "a"
Output
1
[0,1]

flatMap

flatMap(Array<T>, (item: T, index: Number) → Array<R>): Array<R>

Maps an array of items using the specified callback and applies flatten to the resulting array.

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%dw 2.0
output application/json
---
users: ['john', 'peter', 'matt'] flatMap([$$ as String, $])
Output
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{
   'users': [
     '0',
     'john',
     '1',
     'peter',
     '2',
     'matt'
   ]
 }

flatMap(Null, (item: Nothing, index: Nothing) → Any): Null

Helper function that allows flatMap to work with null values.

flatten

flatten(Array<Array<T> | Q>): Array<T | Q>

If you have an array of arrays, this operator can flatten it into a single simple array.

Transform
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%dw 2.0
output application/json
---
flatten(payload)
Input
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[
   [3,5],
   [9,5],
   [154,0.3]
]
Output
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[
  3,
  5,
  9,
  5,
  154,
  0.3
]

flatten(Null): Null

Helper function that allows flatten to work with null values.

floor

floor(Number): Number

Rounds a number downwards, returning the first full number below the one provided.

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%dw 2.0
output application/json
---
{
  a: floor(1.5),
  b: floor(2.2),
  c: floor(3)
}
Output
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{
  "a": 1,
  "b": 2,
  "c": 3
}

groupBy

groupBy(Array<T>, (item: T, index: Number) → R): { ®: Array<T> }

Partitions an Array into a Object that contains Arrays, according to the discriminator function (a lambda) that you define.

The lambda is invoked with three parameters: value, key, and index. If these parameters are not named, the value is defined by default as $, the key $$ and the index $$$.

Transform
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%dw 2.0
output application/json
---
"language": payload.langs groupBy $.language
Input
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{
  "langs": [
    {
      "name": "Foo",
      "language": "Java"
    },
    {
      "name": "Bar",
      "language": "Scala"
    },
    {
      "name": "FooBar",
      "language": "Java"
    }
  ]
}
Output
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{
  "language": {
    "Scala": [
        {"name":"Bar", "language":"Scala"}
      ],
    "Java": [
        {"name":"Foo", "language":"Java"},
        {"name":"FooBar", "language":"Java"}
      ]
  }
}

groupBy({ (K)?: V }, (value: V, key: K) → R): { ®: Array<T> }

Partitions an Object into a Object that contains Arrays, according to the discriminator lambda you define.

The lambda is invoked with two parameters: value and the key.

groupBy(Null, (Nothing, Nothing) → Any): Null

Helper function that allows groupBy to work with null values.

isBlank

isBlank(String | Null): Boolean

Returns true if it receives a string composed of only whitespace characters.

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%dw 2.0
output  application/json
---
{
  empty: isBlank(""),
  withSpaces: isBlank("      "),
  withText: isBlank(" 1223")
}
Output
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  {
    "empty": true,
    "withSpaces": true,
    "withText": false
  }

isDecimal

isDecimal(Number): Boolean

Returns true if it receives a number that has any decimals in it.

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%dw 2.0
output application/json
---
{
  decimal: isDecimal(1.1),
  integer: isDecimal(1)
}
Output
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  {
    "decimal": true,
    "integer": false
  }

isEmpty

isEmpty(Array<Any>): Boolean

Returns true or false depending on whether an array is empty.

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%dw 2.0
output application/json
---
{
  empty: isEmpty([]),
  nonEmpty: isEmpty([1])
}
Output
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  {
    "empty": true,
    "nonEmpty": false
  }

isEmpty(String): Boolean

Returns true or false depending on whether a string is empty.

Transform
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%dw 2.0
output application/json
---
{
  empty: isEmpty(""),
  nonEmpty: isEmpty("DataWeave")
}
Output
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  {
    "empty": true,
    "nonEmpty": false
  }

isEmpty(Null): Boolean

Returns true if it is a Null value

isEmpty(Object): Boolean

Returns true or false depending on whether an object is empty.

Transform
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2
3
4
5
6
7
%dw 2.0
output application/json
---
{
  empty: isEmpty({}),
  nonEmpty: isEmpty({name: "DataWeave"})
}
Output
1
2
3
4
  {
    "empty": true,
    "nonEmpty": false
  }

isEven

isEven(Number): Boolean

Returns true if the specified number is Even.

isInteger

isInteger(Number): Boolean

Returns true is the number doesn’t have any decimals.

Transform
1
2
3
4
5
6
7
%dw 2.0
output application/json
---
{
  decimal: isInteger(1.1),
  integer: isInteger(1)
}
Output
1
2
3
4
  {
    "decimal": false,
    "integer": true
  }

isLeapYear

isLeapYear(DateTime): Boolean

Returns true if it receives a DateTime for a leap year.

isLeapYear(Date): Boolean

Returns true if it receives a Date for a leap year.

isLeapYear(LocalDateTime): Boolean

Returns true if it receives a LocalDateTime for a leap year.

isOdd

isOdd(Number): Boolean

Returns true if the specified number is Odd.

joinBy

joinBy(Array<Any>, String): String

Merges an array into a single string value, using the provided string as a separator between elements.

Transform
1
2
3
4
%dw 2.0
output application/json
---
aa: ["a","b","c"] joinBy "-"
Output
1
2
3
{
  "aa": "a-b-c"
}

log

log(String, T): T

Logs the specified value with a given prefix. Then it returns the value unchanged.

Transform
1
2
3
4
%dw 2.0
payload application/json
---
{ age: log("My Age", payload.age) }
Input:
1
{ "age" : 33 }

This will print this output: My Age - 33.

Output
1
<age>33</age>

Note that besides producing the expected output, it also logs it.

lower

lower(String): String

Returns the provided string in lowercase characters.

Transform
1
2
3
4
5
6
%dw 2.0
output application/json
---
{
  name: lower("MULESOFT")
}
Output
1
2
3
{
  "name": "mulesoft"
}

lower(Null): Null

Helper function that allows lower to work with null values.

map

map(Array<T>, (item: T, index: Number) → R): Array<R>

Iterates over each item in an array and returns the array of items that results from applying a transformation function to the elements.

The function (a lambda) is invoked with the value and the index parameters. In the following example, custom names are defined for these parameters. Then both are used to construct the returned value. In this case, value is defined as firstName, and its index is defined as position.

Transform
1
2
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%dw 2.0
output application/json
---
users: ['john', 'peter', 'matt'] map ((firstName, position) -> position ++ ':' ++ upper(firstName))
Output
1
2
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5
6
7
{
  'users': [
    '0:JOHN',
    '1:PETER',
    '2:MATT'
  ]
}

If the parameters to map are not named, the index is defined by default as $$, and the value is $. The next example produces the same output as the script above. Note that the selector for the key in the next example must be surrounded by parentheses (for example, ($$)).

Transform
%dw 2.0
output application/json
---
users: ['john', 'peter', 'matt'] map (($$) ++ ':' ++ upper($))

This next transformation script produces an array of objects from an input array.

Transform
1
2
3
4
%dw 2.0
output application/json
---
payload.users map { ($$) : upper($) }
Input
{ 'users' : ['fer', 'steven', 'lorraine', 'george'] }
Output
1
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9
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12
13
14
[
  {
    '0': 'FER'
  },
  {
    '1': 'STEVEN'
  },
  {
    '2': 'LORRAINE'
  },
  {
    '3': 'GEORGE'
  }
]

map(Null, (item: Nothing, index: Nothing) → Any): Null

Helper function that allows map to work with null values.

mapObject

mapObject({ (K)?: V }, (value: V, key: K, index: Number) → Object): Object

Iterates through key-value pairs within an object and returns an object. You can retrieve the key, value, or index of any key-value pair in the object.

This function is similar to map. However, instead of processing only values of an object, mapObject processes both keys and values as a tuple. Also, instead of returning an array with the results of processing these values through the function, it returns an object, which consists of a list of the key-value pairs that result from processing both key and value of the object through the function (a lambda).

The function is invoked with three parameters: value, key and the index. The third parameter, index, is optional.

Transform
1
2
3
4
5
6
7
8
9
10
11
%dw 2.0
output application/json
var conversionRate=13
---
priceList: payload.prices mapObject(value, key, index) -> {
  (key) : {
       dollars: value,
       localCurrency: value * conversionRate,
       index_plus_1: index + 1
   }
}
Input
1
2
3
4
5
<prices>
    <basic>9.99</basic>
    <premium>53</premium>
    <vip>398.99</vip>
</prices>
Output
1
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5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
{
  'priceList': {
    'basic': {
      'dollars': '9.99',
      'localCurrency': 129.87,
      'index_plus_1': 1
    },
    'premium': {
      'dollars': '53',
      'localCurrency': 689,
      'index_plus_1': 2
    },
    'vip': {
      'dollars': '398.99',
      'localCurrency': 5186.87,
      'index_plus_1': 3
    }
  }
}

For each key-value pair in the input in the example, the key is preserved, and the value becomes an object with two properties: the original value and the result of multiplying the original value by a constant, a var that is defined as a directive in the header of the DataWeave script.

Important: When you use a parameter to populate one of the keys of your output, you must either enclose the parameter in parentheses (for example, (key)), or you need to prepend it with a $ and enclose it in quotation marks (for example, '$key', as shown above). Otherwise, the name of the property is treated as a literal string.

If you do not name the parameters, you need to reference them through placeholders: $ for the value, $$ for the key, and $$$ for the index, for example:

Transform
%dw 2.0
output application/xml
---
{ 'price' : 9 } mapObject('$$' : $)
Output
<?xml version='1.0' encoding='UTF-8'?>
<price>9</price>

The next example incorporates each index of the price input above, as well as the input keys and values.

Transform
%dw 2.0
output application/json
---
priceList: payload.prices mapObject(
 ($$) : { '$$$' : $ }
)

Notice that the index is surrounded in quotes ('$$$') because this Numeric key must be coerced to a String and cannot be a Number. Alternatively, you could write '$$$' as ($$$ as String).

When the preceding script receives the price input above, it produces the following output:

Output
{
  'priceList': {
    'basic': {
      '0': '9.99'
    },
    'premium': {
      '1': '53'
    },
    'vip': {
      '2': '398.99'
    }
  }
}

The next example returns the same output as the first mapObject example above, which explicitly invokes the named parameters (value, key, index).

Transform
%dw 2.0
output application/json
var conversionRate=13
---
priceList: payload.prices mapObject(
 ($$): {
   dollars: $,
   localCurrency: $ * conversionRate,
   index_plus_1: $$$ + 1
 }
)

When you use a parameter to populate one of the keys of your output, as with the case of $$, you must either enclose it in quote marks (for example, '$$') or parentheses (for example, ($$)). Both are equally valid.

mapObject(Null, (value: Nothing, key: Nothing, index: Number) → Nothing): Null

Helper function that allows mapObject to work with null values.

match

match(String, Regex): Array<String>

Matches a string against a regular expression and returns an array that contains the entire matching expression, followed by all of the capture groups that match the provided regex.

It can be applied to the result of any evaluated expression and can return any evaluated expression. See Pattern Matching in DataWeave.

Transform
1
2
3
4
%dw 2.0
output application/json
---
hello: "anniepoint@mulesoft.com" match(/([a-z]*)@([a-z]*).com/)
Output
1
2
3
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5
6
7
{
  "hello": [
    "anniepoint@mulesoft.com",
    "anniepoint",
    "mulesoft"
  ]
}

In the example above, the regular expression describes an email address. It contains two capture groups, what is before and what is after the @. The result is an array of three elements: the first is the whole email address, the second matches one of the capture groups, the third matches the other one.

matches

matches(String, Regex): Boolean

Matches a string against a regular expression and returns true or false.

Transform
1
2
3
4
%dw 2.0
output application/json
---
b: "admin123" matches /(\d+)/
Output
1
2
3
{
  "b": false
}

For use cases where you need to output or conditionally process the matched value, see Pattern Matching in DataWeave.

max

max(Array<T>): T | Null

Returns the highest element in an array. Returns null when the array is empty

Transform
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3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: max([1, 1000]),
  b: max([1, 2, 3]),
  d: max([1.5, 2.5, 3.5])
}
Output
1
2
3
4
5
{
  "a": 1000,
  "b": 3,
  "d": 3.5
}

maxBy

maxBy(Array<T>, (item: T) → Comparable): T | Null

Returns the element used to get the maximum result using a function. Return null when array is empty.

Transform
1
2
3
4
%dw 2.0
output  application/json
---
[ { a: "1" }, { a: "2" }, { a: "3" } ] maxBy ((item) -> item.a as Number)
Output
1
{ "a": "3" }

min

min(Array<T>): T | Null

Returns the lowest element in an array. Returns null when the array is empty

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: min([1, 1000]),
  b: min([1, 2, 3]),
  d: min([1.5, 2.5, 3.5])
}
Output
1
2
3
4
5
{
  "a": 1,
  "b": 1,
  "d": 1.5
}

minBy

minBy(Array<T>, (item: T) → Comparable): T | Null

Returns the element used to get the minimum result using a function. Return null when array is empty

Transform
1
2
3
4
%dw 2.0
output  application/json
---
[ { a: 1 }, { a: 2 }, { a: 3 } ] minBy (item) -> item.a
Output
1
{ "a": 1 }

mod

mod(Number, Number): Number

Returns the remainder after performing a division of the first number by the second one.

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: 3 mod 2,
  b: 4 mod 2,
  c: 2.2 mod 2
}
Output
1
2
3
4
5
{
  "a": 1,
  "b": 0,
  "c": 0.2
}

native

native(String): Nothing

Internal method it is used to marc that a function implementation is not written in DataWeave but in Scala

now

now(): DateTime

Returns a DateTime object with the current date and time.

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: now(),
  b: now().day,
  c: now().minutes
}
Output
1
2
3
4
5
{
  "a": "2015-12-04T18:15:04.091Z",
  "b": 4,
  "c": 15
}

See DataWeave Selectors for a list of possible selectors to use here.

orderBy

orderBy(O, (value: V, key: K) → R): O

Reorders the content of an array or object using a value returned by a function. The function (a lambda) can be invoked with these parameters: value and index.

If the parameters are not named, the index is defined by default as $$ and the value as $.

Transform
1
2
3
4
%dw 2.0
output application/json
---
orderByLetter: [{ letter: "d" }, { letter: "e" }, { letter: "c" }, { letter: "a" }, { letter: "b" }] orderBy($.letter)
Output
1
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5
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7
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9
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12
13
14
15
16
17
18
19
{
  "orderByLetter": [
    {
      "letter": "a"
    },
    {
      "letter": "b"
    },
    {
      "letter": "c"
    },
    {
      "letter": "d"
    },
    {
      "letter": "e"
    }
  ]
}

Note that orderBy($.letter) above produces the same result as orderBy($[0]).

The orderBy function does not have an option to order in descending order instead of ascending. In these cases, you can simply invert the order of the resulting array using -, for example:

Transform
1
2
3
4
%dw 2.0
output application/json
---
orderDescending: ([3,8,1] orderBy -$)
Output
1
{ "orderDescending": [8,3,1] }

orderBy(Array<T>, (item: T, index: Number) → R): Array<T>

Sorts an array using the specified criteria.

Transform
1
2
3
4
%dw 2.0
output application/json
---
[3,2,3] orderBy $
Output
1
2
3
4
5
[
  2,
  3,
  3
]

orderBy(Null, (item: Nothing, index: Nothing) → Null): Null

Helper function that allows orderBy to work with null values.

pluck

pluck({ (K)?: V }, (value: V, key: K, index: Number) → R): Array<R>

Useful for mapping an object into an array, pluck iterates over an input object and returns an array consisting of keys, values, or indices of that object. It is an alternative to mapObject, which is similar but returns an object, instead of an array.

The function can be invoked with any of these parameters: value, key, index. In the next example, 'pluck' iterates over each object within 'prices' and returns arrays of their keys, values, and indices.

If the parameters are not named, the value is defined by default as $, the key as $$, and the index as $$$.

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
result: {
  keys: payload.prices pluck($$),
  values: payload.prices pluck($),
  indices: payload.prices pluck($$$)
}
Input
1
2
3
4
5
<prices>
    <basic>9.99</basic>
    <premium>53.00</premium>
    <vip>398.99</vip>
</prices>
Output
1
2
3
4
5
6
7
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9
10
11
12
13
14
15
16
17
18
19
{
  'result': {
    'keys': [
      'basic',
      'premium',
      'vip'
    ],
    'values': [
      '9.99',
      '53',
      '398.99'
    ],
    'indices': [
      0,
      1,
      2
    ]
  }
}

You can also use named keys and values as parameters. For example, the next transformation example iterates over the prices input above and outputs an array with a single element.

Transform
1
2
3
4
%dw 2.0
output application/json
---
payload pluck(payload.prices)
Output
1
2
3
4
5
6
7
[
  {
    'basic': '9.99',
    'premium': '53.00',
    'vip': '398.99'
  }
]

Note that payload pluck(payload.prices) produces the same result as payload pluck(payload[0]).

pluck(Null, (value: Nothing, key: Nothing, index: Nothing) → Any): Null

Helper function that allows pluck to work with null values.

pow

pow(Number, Number): Number

Returns the result of the first number a to the power of the number following the pow operator.

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: 2 pow 3,
  b: 3 pow 2,
  c: 7 pow 3
}
Output
1
2
3
4
5
{
  "a": 8,
  "b": 9,
  "c": 343
}

random

random(): Number

Returns a pseudo-random number greater than or equal to 0.0 and less than 1.0.

Transform
1
2
3
4
5
6
%dw 2.0
output application/json
---
{
  price: random() * 1000
}

randomInt

randomInt(Number): Number

Returns a pseudo-random integer number between 0 and the specified number (exclusive).

Transform
1
2
3
4
5
6
%dw 2.0
output application/json
---
{
  price: randomInt(1000) //Returns an integer from 0 to 1000
}

read

read(String | Binary, String, Object)

Reads the input content (string or binary) with a mimeType reader for the data format of the input and returns the result of parsing that content.

The first argument provides the content to read. The second is its format (or content type). The default content type is application/dw. A third, optional argument sets reader configuration properties.

For other formats and reader configuration properties, see Data Formats Supported by DataWeave.

Transform
1
2
3
4
%dw 2.0
output application/xml
---
 read('{"name":"DataWeave"}', "application/json")
Output
1
<name>DataWeave</name>

readUrl

readUrl(String, String, Object)

Same as the read operator, but readURL uses a URL as input. Otherwise, it accepts the same arguments as read.

The default input content type is application/dw.

For other formats and reader configuration properties, see Data Formats Supported by DataWeave.

Transform
1
2
3
4
%dw 2.0
output application/xml
---
read('{"url":"https://www.mulesoft.com/"}')
Output
1
2
<?xml version='1.0' encoding='UTF-8'?>
<url>https://www.mulesoft.com/</url>

reduce

reduce(Array<T>, (item: T, accumulator: T) → T): T | Null

Apply a reduction to the array using just two parameters: the accumulator ($$), and the value ($). By default, the accumulator starts at the first value of the array. If the array is empty and no default value was set to the accumulator then null value is returned.

Transform
1
2
3
4
%dw 2.0
output application/json
---
sum: [0, 1, 2, 3, 4, 5] reduce ($$ + $)
Output
1
2
3
{
  "sum": 15
}
Transform
1
2
3
4
%dw 2.0
output application/json
---
concat: ["a", "b", "c", "d"] reduce ($$ ++ $)
Output
1
2
3
{
  "concat": "abcd"
}

In some cases, you may not want to use the first element of the array as an accumulator. To set the accumulator to something else, you must define this in a lambda.

Transform
1
2
3
4
%dw 2.0
output application/json
---
concat: ["a", "b", "c", "d"] reduce ((val, acc = "z") -> acc ++ val)
Output
1
2
3
{
  "concat": "zabcd"
}

In other cases, you may want to turn an array into a string keeping the commas in between. The example below defines a lambda that also adds commas when concatenating.

Transform
1
2
3
4
%dw 2.0
output application/json
---
concat: ["a", "b", "c", "d"] reduce ((val, acc) -> acc ++ "," ++ val)
Output
1
2
3
{
  "concat":  "a,b,c,d"
}

reduce(Array<T>, (item: T, accumulator: A) → A): A

replace

replace(String, Regex): ((Array<String>, Number) → String) → String

Replaces a section of a string for another, in accordance to a regular expression, and returns a modified string.

Transform
1
2
3
4
%dw 2.0
output application/json
---
b: 'admin123' replace /(\d+)/ with 'ID'
Output
1
2
3
{
  'b': 'adminID'
}

replace(String, String): ((Array<String>, Number) → String) → String

Replaces the occurrence of a given string inside other string with the specified value.

Transform
1
2
3
4
%dw 2.0
output application/json
---
b: "admin123" replace "123" with "ID"
Output
1
2
3
{
  "b": "adminID"
}

round

round(Number): Number

Rounds the value of a number to the nearest integer.

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: round(1.2),
  b: round(4.6),
  c: round(3.5)
}
Output
1
2
3
4
5
{
  "a": 1,
  "b": 5,
  "c": 4
}

scan

scan(String, Regex): Array<Array<String>>

Returns an array with all of the matches in the given string. Each match is returned as an array that contains the complete match, as well as any capture groups there may be in your regular expression.

Transform
1
2
3
4
%dw 2.0
output application/json
---
hello: "anniepoint@mulesoft.com,max@mulesoft.com" scan /([a-z]*)@([a-z]*).com/
Output
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9
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11
12
13
14
{
  "hello": [
    [
      "anniepoint@mulesoft.com",
      "anniepoint",
      "mulesoft"
    ],
    [
      "max@mulesoft.com",
      "max",
      "mulesoft"
    ]
  ]
}

In the example above, we see that the search regular expression describes an email address. It contains two capture groups, what’s before and what’s after the @. The result is an array with two matches, as there are two email addresses in the input string. Each of these matches is an array of three elements, the first is the whole email address, the second matches one of the capture groups, the third matches the other one.

sizeOf

sizeOf(Array<Any>): Number

Returns the number of elements in an array (or anything that can be converted to an array, such as a string).

Transform
1
2
3
4
5
6
%dw 2.0
output application/json
---
{
  arraySize: sizeOf([1,2,3])
}
Output
1
2
3
{
  "arraySize": 3
}

sizeOf(Object): Number

Returns the number of elements in an object.

Transform
1
2
3
4
5
6
%dw 2.0
output application/json
---
{
  objectSize: sizeOf({a:1,b:2})
}
Output
1
2
3
{
  "objectSize": 2
}

sizeOf(Binary): Number

Returns the byte length of a binary value.

sizeOf(String): Number

Returns the number of characters in an string.

Transform
1
2
3
4
5
6
%dw 2.0
output application/json
---
{
  textSize: sizeOf("MuleSoft")
}
Output
1
2
3
{
  "textSize": 8
}

splitBy

splitBy(String, Regex): Array<String>

Splits a string into an array of separate elements. The function takes a regular expression to identify some portion of that string, and if it finds a match, uses the match as separator. splitBy performs the opposite operation of joinBy.

Using the regular expression \^$.|?*+()-, the following example finds the the hyphen (-) in the input string (a-b-c), so it uses the hyphen as a seperator.

Transform
1
2
3
4
%dw 2.0
output application/json
---
split: "a-b-c" splitBy(/\^$.|?*+()-/)
Output
1
2
3
{
  "split": ["a","b","c"]
}

splitBy(String, String): Array<String>

Splits a string into an array of separate elements. The function takes a another string to look for some portion of the input string, and if it finds a match, uses the match as separator. splitBy performs the opposite operation of joinBy.

The following example uses the hyphen (-) as the separator, but the separator could be any other character in the input, such as splitBy("b").

Transform
1
2
3
4
%dw 2.0
output application/json
---
split: "a-b-c" splitBy("-")
Output
1
2
3
{
  "split": ["a", "b", "c"]
}

sqrt

sqrt(Number): Number

Returns the square root of the provided number.

Transform
1
2
3
4
5
6
7
8
%dw 2.0
output application/json
---
{
  a: sqrt(4),
  b: sqrt(25),
  c: sqrt(100)
}
Output
1
2
3
4
5
{
  "a": 2.0,
  "b": 5.0,
  "c": 10.0
}

startsWith

startsWith(String, String): Boolean

Returns true or false depending on whether a string starts with a provided substring.

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%dw 2.0
output application/json
---
{
  a: "Mariano" startsWith "Mar",
  b: "Mariano" startsWith "Em"
}
Output
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{
  "a": true,
  "b": false
}

sum

sum(Array<Number>): Number

Given an array of numbers, it returns the result of adding of all of them.

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%dw 2.0
output application/json
---
sum([1, 2, 3])
Output
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6

to

to(Number, Number): Range

Returns a range within the specified boundaries. The upper boundary is inclusive.

Transform
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%dw 2.0
output application/json
---
{
    "myRange": 1 to 10
}
Output
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{
    "myRange": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
}

trim

trim(String): String

Removes any excess spaces at the start and end of a string.

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%dw 2.0
output application/json
---
{
  "a": trim("   my long text     ")
}
Output
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{
  "a": "my long text"
}

trim(Null): Null

Helper function that allows trim to work with null values.

typeOf

typeOf(T): Type<T>

Returns the type of a value.

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%dw 2.0
output application/json
---
typeOf("A Text")
Output
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"String"

unzip

unzip(Array<Array<T>>): Array<Array<T>>

Performs the opposite function of [zip arrays]. That is, given a single array where each index contains an array with two elements, it outputs two separate arrays, each with the corresponding elements of each pair.

This can also be scaled up: If the indexes in the provided array contain arrays with more than two elements, the output will contain as many arrays as there are elements for each index.

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%dw 2.0
output application/json
---
{
  a: unzip([[0,"a"],[1,"b"],[2,"c"],[3,"d"]]),
  b: unzip([ [0,"a"], [1,"a"], [2,"a"], [3,"a"]]),
  c: unzip([ [0,"a"], [1,"a","foo"], [2], [3,"a"]])
}
Output
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{
   "a":[
      [0, 1, 2, 3],
      ["a", "b", "c", "d"]
    ],
  "b": [
      [0,1,2,3],
      ["a","a","a","a"]
    ],
  "c": [
      [0,1,2,3]
    ]
}

Note that even though example b can be considered the inverse function of example b in [zip array], the result is not analogous because it returns an array of repeated elements instead of a single element. Also note that in example c, the number of elements in each component of the original array is not consistent. So the output only creates as many full arrays as it can, in this case just one.

upper

upper(String): String

Returns the provided string in uppercase characters.

Transform
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%dw 2.0
output application/json
---
{
  name: upper("mulesoft")
}
Output
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{
  "name": "MULESOFT"
}

upper(Null): Null

Helper function that allows trim to work with null values.

uuid

uuid(): String

Returns a v4 UUID using random numbers as the source.

Transform
%dw 2.0
output application/json
---
uuid()
Output Example
"4a185c3b-05b3-4554-b72e-d5c07524cf91"

with

with(((V, U) → R) → X, (V, U) → R): X

When used with replace, with applies the specified function.

Transform
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%dw 2.0
output application/json
---
ssn: "987-65-4321" replace /[0-9]/ with("x")
Output
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{ ssn: "xxx-xx-xxxx" }

write

write(Any, String, Object): String | Binary

Writes the value to a specific format. Returns a String or Binary with the serialized representation of the value in the specified mimeType (format).

The first argument points to the input to write. The second is the format in which to write it. The default is application/dw. A third, optional argument lists writer configuration properties.

See Data Formats Supported by DataWeave for a full list of configuration properties for each format-specific writer.

Transform
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%dw 2.0
output application/xml
---
{
  "output" : write(payload, "application/csv", {"separator" : "|"})
}
Input
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[
  {
    "Name": "Mr White",
    "Email": "white@mulesoft.com",
    "Id": "1234",
    "Title": "Chief Java Prophet"
  },
  {
    "Name": "Mr Orange",
    "Email": "orange@mulesoft.com",
    "Id": "4567",
    "Title": "Integration Ninja"
  }
]
Output
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<?xml version='1.0' encoding='US-ASCII'?>
<output>Name|Email|Id|Title
Mr White|white@mulesoft.com|1234|Chief Java Prophet
Mr Orange|orange@mulesoft.com|4567|Integration Ninja
</output>

zip

zip(Array<T>, Array<R>): Array<Array<T | R>>

Given two or more separate lists, the zip function can be used to merge them together into a single list of consecutive n-tuples. Imagine two input lists each being one side of a zipper: similar to the interlocking teeth of a zipper, the zip function interdigitates each element from each input list, one element at a time.

Transform
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%dw 2.0
output application/json
---
{
  a: [0, 1, 2, 3] zip ['a', 'b', 'c', 'd'],
  b: [0, 1, 2, 3] zip ['a'],
  c: [0, 1, 2, 3] zip ['a', 'b']
}
Output
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{
  'a': [
    [0,'a'],
    [1,'b'],
    [2,'c'],
    [3,'d']
    ],
  'b': [
    [0,'a']
  ],
  'c': [
    [0,'a'],
    [1,'b']
  ]
}

Here is another example of the zip function with more than two input lists.

Transform
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%dw 2.0
output application/json
---
payload.list1 zip payload.list2 zip payload.list3
Input
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{
  'list1': ['a', 'b', 'c', 'd'],
  'list2': [1, 2, 3],
  'list3': ['aa', 'bb', 'cc', 'dd'],
  'list4': [['a', 'b', 'c'], [1, 2, 3, 4], ['aa', 'bb', 'cc', 'dd']]
}
Output
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[
  [
    'a',
    1,
    'aa'
  ],
  [
    'b',
    2,
    'bb'
  ],
  [
    'c',
    3,
    'cc'
  ]
]

Types

Any

Any type, is the top level type. Any extends all of the system types. That means anything can be assigned to a Any typed variable.

Definition
1
Any

Array

Array type, requires a Type(T) to represent the elements of the list. Example: Array<Number> represents an array of numbers.

Definition
1
Array

Binary

A Blob

Definition
1
Binary

Boolean

A Boolean type true of false

Definition
1
Boolean

CData

XML defines a custom type named CData that extends from String and is used to identify a CDATA XML block.

It can be used to tell the writer to wrap the content inside CDATA or to check if the input string arrives inside a CDATA block. :cdata inherits from the type :string.

Transform
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%dw 2.0
output application/xml
---
{
  users:
  {
    user : "Mariano" as CData,
    age : 31 as CData
  }
}
Output
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<?xml version="1.0" encoding="UTF-8"?>
<users>
  <user><![CDATA[Mariano]]></user>
  <age><![CDATA[31]]></age>
</users>
Definition
1
String {cdata: true}

Comparable

A union type that represents all the types that can be compared to each other.

Definition
1
String | Number | Boolean | DateTime | LocalDateTime | Date | LocalTime | Time | TimeZone

Date

A Date represented by Year Month Day

Definition
1
Date

DateTime

A Date Time with in a TimeZone

Definition
1
DateTime

Dictionary

Generic Dictionary interface

Definition
1
{ _?: T }

Enum

This type is based in the Enum Java class.

It must always be used with the class property, specifying the full Java class name of the class, as shown in the example below.

Transform
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%dw 2.0
output application/java
---
"Male" as Enum {class: "com.acme.GenderEnum"}
Definition
1
String {enumeration: true}

Iterator

This type is based in the iterator Java class. The iterator contains a collection, and includes methods to iterate through and filter it.

Note
Just like the Java class, the iterator is designed to be consumed only once. For example, if you then pass this value to a Logger component would result in consuming it and it would no longer be readable to further elements in the flow.
Definition
1
Array {iterator: true}

Key

A Key of an Object

Definition
1
Key

LocalDateTime

A DateTime in the current TimeZone

Definition
1
LocalDateTime

LocalTime

A Time in the current TimeZone

Definition
1
LocalTime

NaN

java.lang.Float and java.lang.Double have speciall cases for NaN and Infinit. DataWeave doesn’t have this concepts for its number multi precision nature. So when it is mapped to DataWeave values it is being wrapped in a Null with a Schema marker.

Transform
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%dw 2.0
output application/java
---
payload.double is NaN

This scripts shows how to determine if a number came from a NaN

Definition
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Null {NaN: true}

Namespace

A namespace type represented by an URI and a Prefix

Definition
1
Namespace

Nothing

Bottom type. This type is can be assigned to all the types

Definition
1
Nothing

Null

A null type

Definition
1
Null

Number

A number any number decimals and integers are represented by Number type

Definition
1
Number

Object

Object type. Represents any object, collection of Key Value Pairs

Definition
1
Object

Period

A Period

Definition
1
Period

Range

A Range type represents a sequence of numbers

Definition
1
Range

Regex

Regex Type

Definition
1
Regex

SimpleType

A union type that represents all the simple types.

Definition
1
String | Boolean | Number | DateTime | LocalDateTime | Date | LocalTime | Time | TimeZone | Period

String

These are the native types of DataWeave.

They are the only types that allow the ??? definition.

Definition
1
String

Time

A Time in a specific TimeZone

Definition
1
Time

TimeZone

A TimeZone

Definition
1
TimeZone

Type

Represents a Type in the DataWeave Type System

Definition
1
Type

Uri

An Uri

Definition
1
Uri