Here's a compilation of some of the (fairly complex) DW scripts I've done.
Check out the Table of Contents to find all the functions listed here.
In each function's section, you'll find a brief description of what it does, the input/script/output to run the function, and a button to open the example in the DataWeave Playground directly -- without having to copy and paste each example yourself.
Note
To learn more about this functionality, check out this video: How to generate examples from GitHub to open in the DataWeave Playground.
To learn more about DataWeave, please go to DataWeave's official landing page: dataweave.mulesoft.com. There you will find aditional resources like the link to join the official DataWeave Slack workspace, the DataWeave Playground, the Visual Studio Code extension, the documentation, and so on.
If you want to open an example in Visual Studio Code, you can use the Export button located at the top of the DataWeave Playground, extract the .zip file, and open the extracted folder in VSCode. Make sure you already installed Java 8, Maven, and the DataWeave extension for VSCode. For more information, please see the resources below.
- Video: How to export a script from the DataWeave Playground to Visual Studio Code | Short Tutorial
- Article: How to move your code from the DataWeave Playground to Visual Studio Code
- Tutorial: Getting started with the DataWeave extension for Visual Studio Code
Recursive Functions
- getChildren (v1-2021)
- getChildren (v2-2024)
- removeDynamodbKeys
Tail Recursive Functions
- addIndexTailRecursive
- getDaysBetween
- extractPath
- filterValueByConditions
- extractPathWithFilters
- getDatesArray
- flattenObject
Head and Tail Constructor
Other Functions
Other Transformations
Array<String>toArray<Object>- Clean XML for WordPress publishing
- Clean HTML (text) for WordPress publishing
- YAML Objects to OpenAPI Schema
- JSON example to AsyncAPI YAML Schema
I don't personally recommend using recursive functions because they can reach the Stack Overflow error and mess with your code's performance. But there are some cases where it is needed.
To understand recursive functions better, take a look at this video: What are recursive functions and how to use them in DataWeave | #Codetober 2022 Day 22
Creates a tree from a flat array with parent/child relationship. Please note there are two versions of this same functionality.
Video: DataWeave Scripts Repo: getChildren recursive function | #Codetober 2021 Day 9
Input
[
{
"parent": "111",
"child": "222",
"name": "node1",
"level": "1"
},
{
"parent": "222",
"child": "333",
"name": "node2",
"level": "2"
},
{
"parent": "333",
"child": "444",
"name": "node3",
"level": "3"
},
{
"parent": "222",
"child": "555",
"name": "node4",
"level": "2"
},
{
"parent": "333",
"child": "666",
"name": "node5",
"level": "3"
}
]Script
%dw 2.0
output application/json skipNullOn="everywhere"
fun getChildren(items, parentItem) = do {
var parentLevel = parentItem.level as Number
var thisLevelItemsFiltered = items filter (
($.level ~= (parentLevel + 1))
and ($.parent == parentItem.child)
)
---
if (isEmpty(thisLevelItemsFiltered)) null
else (
thisLevelItemsFiltered match {
case [] -> null
else -> thisLevelItemsFiltered map {
name: $.name,
children: getChildren(items, $)
}
}
)
}
var items = payload orderBy $.level
var parentItem = items[0]
---
{
parent: parentItem.parent,
name: parentItem.name,
children: getChildren(items, parentItem)
}Output
{
"parent": "111",
"name": "node1",
"children": [
{
"name": "node2",
"children": [
{
"name": "node3"
},
{
"name": "node5"
}
]
},
{
"name": "node4"
}
]
}
Input
[
{
"parent": "111",
"child": "222",
"name": "node1",
"level": "1"
},
{
"parent": "222",
"child": "333",
"name": "node2",
"level": "2"
},
{
"parent": "333",
"child": "444",
"name": "node3",
"level": "3"
},
{
"parent": "222",
"child": "555",
"name": "node4",
"level": "2"
},
{
"parent": "333",
"child": "666",
"name": "node5",
"level": "3"
}
]Script
%dw 2.0
output application/json skipNullOn="everywhere"
var grouped = payload groupBy $.level
var parent = grouped["1"][0]
fun getChildren(data, level:Number, child:String) = do {
var c = data[level as String] filter ($.parent ~= child) map {
name: $.name,
children: getChildren(data, level+1, $.child)
}
---
c match {
case ch if isEmpty(ch) -> null
else -> c
}
}
---
{
parent: parent.parent,
name: parent.name,
children: getChildren(grouped, 2, parent.child)
}Output
{
"parent": "111",
"name": "node1",
"children": [
{
"name": "node2",
"children": [
{
"name": "node3"
},
{
"name": "node5"
}
]
},
{
"name": "node4"
}
]
}Removes the keys created by Amazon DynamoDB after performing a scan operation to retrieve the items from a table.
You can set up which keys you want to remove using the dynamodbKeys variable. In this example, I added the keys l, m, n, s, bool.
In the dynamodbKeyUpdate variable, I added the string "unrepeatableKey" because it will be used to replace the unwanted keys with this and then extract the value from it. If you have this key in your actual input, make sure to change it to something that doesn't exist within your payload.
Input
{
"scannedCount": 1,
"lastEvaluatedKey": null,
"count": 1,
"consumedCapacity": null,
"items": [
{
"addresses": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": [
{
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": {
"geo": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": {
"lng": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": "-122.39521",
"bs": null,
"s": null
},
"lat": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": "37.78916",
"bs": null,
"s": null
}
},
"n": null,
"bs": null,
"s": null
},
"country": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "United States"
},
"city": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "San Francisco"
},
"street": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "415 Mission Street"
},
"postalCode": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "94105"
},
"main": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": true,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": null
},
"state": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "California"
}
},
"n": null,
"bs": null,
"s": null
},
{
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": {
"geo": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": {
"lng": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": "-79.37756",
"bs": null,
"s": null
},
"lat": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": "43.64184",
"bs": null,
"s": null
}
},
"n": null,
"bs": null,
"s": null
},
"country": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "Canada"
},
"city": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "Toronto"
},
"street": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "10 Bay St."
},
"postalCode": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "M5J 2R8"
},
"main": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": false,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": null
},
"state": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "Ontario"
}
},
"n": null,
"bs": null,
"s": null
}
],
"m": null,
"n": null,
"bs": null,
"s": null
},
"name": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": {
"firstName": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "Alex"
},
"lastName": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "Martinez"
}
},
"n": null,
"bs": null,
"s": null
},
"id": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "1"
},
"email": {
"nullvalue": null,
"ss": null,
"b": null,
"bool": null,
"ns": null,
"l": null,
"m": null,
"n": null,
"bs": null,
"s": "alex@sf.com"
}
}
]
}Script
%dw 2.0
output application/json
import filterTree from dw::util::Tree
fun removeDynamodbKeys(data) = do {
var dynamodbKeys = ["l", "m", "n", "s", "bool"] // add the keys you want to remove
var dynamodbKeyUpdate = "unrepeatableKey" // change this name if this key is indeed repeated within your input
fun removeDynamodbKeysRec(value) = value match {
case obj is Object -> do {
var finalObj = obj mapObject ((value, key) ->
if (dynamodbKeys contains (key as String))
(dynamodbKeyUpdate): removeDynamodbKeysRec(value)
else
(key): removeDynamodbKeysRec(value)
)
---
finalObj[dynamodbKeyUpdate] default finalObj
}
case arr is Array -> arr map removeDynamodbKeysRec($)
else -> value
}
---
data filterTree ($ != null)
then removeDynamodbKeysRec($)
}
---
removeDynamodbKeys(payload.items)Output
[
{
"addresses": [
{
"geo": {
"lng": "-122.39521",
"lat": "37.78916"
},
"country": "United States",
"city": "San Francisco",
"street": "415 Mission Street",
"postalCode": "94105",
"main": true,
"state": "California"
},
{
"geo": {
"lng": "-79.37756",
"lat": "43.64184"
},
"country": "Canada",
"city": "Toronto",
"street": "10 Bay St.",
"postalCode": "M5J 2R8",
"main": false,
"state": "Ontario"
}
],
"name": {
"firstName": "Alex",
"lastName": "Martinez"
},
"id": "1",
"email": "alex@sf.com"
}
]If you really want to use recursion in DataWeave, I very much recommend using tail-recursive functions instead of the regular recursive functions. These are better performance-wise because they do not reach the Stack Overflow error.
To understand tail-recursive functions better, take a look at this video: What are TAIL-recursive functions and how to use them in DataWeave | #Codetober 2022 Day 23
Transforms a JSON payload into a different JSON structure and keeps a count of the indexes accross the whole output array. This function has its own repository that contains additional explanations and links to other resources such as slides and previous versions. To learn more about it please go to this repository: Reviewing a Complex DataWeave Transformation Use-case.
Video: DataWeave Scripts Repo: addIndexTailRecursive tail recursive function | #Codetober 2021 Day 10
Input
{
"FlightOptions": [
{
"Connections": [
{
"ReferenceID": 111,
"TaxCode": "ABC",
"EndOfConnection": false
},
{
"ReferenceID": 222,
"TaxCode": "DEF",
"EndOfConnection": true
}
]
},
{
"Connections": [
{
"ReferenceID": 333,
"TaxCode": "GHI",
"EndOfConnection": true
},
{
"ReferenceID": 444,
"TaxCode": "JKL",
"EndOfConnection": true
}
]
},
{
"Connections": [
{
"ReferenceID": 555,
"TaxCode": "MNO",
"EndOfConnection": false
},
{
"ReferenceID": 666,
"TaxCode": "PQR",
"EndOfConnection": false
},
{
"ReferenceID": 777,
"TaxCode": "STU",
"EndOfConnection": false
}
]
},
{
"Connections": [
{
"ReferenceID": 888,
"TaxCode": "VWX",
"EndOfConnection": false
}
]
},
{
"Connections": [
{
"ReferenceID": 999,
"TaxCode": "MNO",
"EndOfConnection": false
},
{
"ReferenceID": 101,
"TaxCode": "PQR",
"EndOfConnection": true
},
{
"ReferenceID": 102,
"TaxCode": "STU",
"EndOfConnection": false
}
]
}
]
}Script
%dw 2.0
output application/json
import update from dw::util::Values
fun addIndexTailRecursive(
connectionsArray: Array<Object>,
indexAccumulatorArray: Array = [],
index: Number = 1,
connectionsAccumulatorArray: Array = []
) = (
if (isEmpty(connectionsArray)) connectionsAccumulatorArray
else do {
var thisConnection: Object = connectionsArray[0]
var thisConnectionIsEndOfConnection: Boolean = thisConnection.EndOfConnection ~= true
var newIndexAccumulatorArray = if (thisConnectionIsEndOfConnection) [] else indexAccumulatorArray + index
---
addIndexTailRecursive(
connectionsArray[1 to -1] default [],
newIndexAccumulatorArray,
index + 1,
if (thisConnectionIsEndOfConnection) (
connectionsAccumulatorArray + {
AppliedTaxCode: thisConnection.TaxCode,
AppliedConnections: (indexAccumulatorArray + index) map {
Type: "Connection",
IndexValue: $
}
}
)
else connectionsAccumulatorArray
)
}
)
---
addIndexTailRecursive(
payload.FlightOptions.Connections
reduce ((flightOption, accumulator = []) -> do {
var lastConnection = {
(flightOption[-1] update "EndOfConnection" with true)
}
var updatedConnections = (flightOption[0 to -2] default []) + lastConnection
---
accumulator ++ updatedConnections
})
)Output
[
{
"AppliedTaxCode": "DEF",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 1
},
{
"Type": "Connection",
"IndexValue": 2
}
]
},
{
"AppliedTaxCode": "GHI",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 3
}
]
},
{
"AppliedTaxCode": "JKL",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 4
}
]
},
{
"AppliedTaxCode": "STU",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 5
},
{
"Type": "Connection",
"IndexValue": 6
},
{
"Type": "Connection",
"IndexValue": 7
}
]
},
{
"AppliedTaxCode": "VWX",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 8
}
]
},
{
"AppliedTaxCode": "PQR",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 9
},
{
"Type": "Connection",
"IndexValue": 10
}
]
},
{
"AppliedTaxCode": "STU",
"AppliedConnections": [
{
"Type": "Connection",
"IndexValue": 11
}
]
}
]Count the number of days between two dates using certain filters to either count some days or keep them out.
Filters:
includeEndDate- Boolean to include the endDate in count or not. Default value isfalse.includingDaysOfWeek- Array of Numbers to include just certain days of the week in count. Default is to count all days of the week (1-7).excludingDates- Array of Dates to include certain dates that should not be counted. Default is empty.
Video: DataWeave Scripts Repo: getDaysBetween tail recursive function | #Codetober 2021 Day 12
Script
%dw 2.0
output application/json
// example vars
var exampleStartDate = "2021-02-01" as Date
var exampleEndDate = "2021-02-22" as Date
// tail recursive function
fun getDaysBetween (
startDate: Date, // starting date
endDate: Date, // ending date
includeEndDate: Boolean = false, // boolean to include endDate in count
includingDaysOfWeek: Array<Number> = [1, 2, 3, 4, 5, 6, 7], // default value is all days of the week (Mon-Sun)
excludingDates: Array<Date> = [], // send array with holidays
count: Number = 0 // counter for tail recursive function
) = do {
var includesDayOfWeek = includingDaysOfWeek contains startDate.dayOfWeek
var isExcludedDate = excludingDates contains startDate
var isValidDate = includesDayOfWeek and not isExcludedDate
var newCount = if (isValidDate) count + 1 else count
---
if (startDate > endDate) count
else if (startDate == endDate) (
if (includeEndDate and isValidDate) count + 1
else count
)
else getDaysBetween (
startDate + |P1D|,
endDate,
includeEndDate,
includingDaysOfWeek,
excludingDates,
newCount
)
}
---
{
Start_Date: exampleStartDate,
End_Date: exampleEndDate,
Count_Working_Days_Including_EndDate: getDaysBetween(
exampleStartDate,
exampleEndDate,
true,
[1, 2, 3, 4, 5]
),
Count_Working_Days_Excluding_EndDate: getDaysBetween(
exampleStartDate,
exampleEndDate,
false,
[1, 2, 3, 4, 5]
),
If_Every_Weekend_Was_A_Long_Weekend: getDaysBetween(
exampleStartDate,
exampleEndDate,
true,
[1, 2, 3, 4]
),
Count_Working_Days_With_Exclusion_Dates: getDaysBetween(
exampleStartDate,
exampleEndDate,
true,
[1, 2, 3, 4, 5],
[
"2021-02-15" as Date,
"2021-02-16" as Date,
"2021-02-17" as Date,
"2021-02-18" as Date,
"2021-02-19" as Date
]
),
Count_All_Days_Including_EndDate: getDaysBetween(
exampleStartDate,
exampleEndDate,
true
),
Count_All_Days_Excluding_EndDate: getDaysBetween(
exampleStartDate,
exampleEndDate
)
}Output
{
"Start_Date": "2021-02-01",
"End_Date": "2021-02-22",
"Count_Working_Days_Including_EndDate": 16,
"Count_Working_Days_Excluding_EndDate": 15,
"If_Every_Weekend_Was_A_Long_Weekend": 13,
"Count_Working_Days_With_Exclusion_Dates": 11,
"Count_All_Days_Including_EndDate": 22,
"Count_All_Days_Excluding_EndDate": 21
}Extract values from a JSON input using a String representation of a path.
Video: DataWeave Scripts Repo: extractPath tail recursive function | #Codetober 2021 Day 13
Input
{
"object": {
"array": [
{
"test": "value1"
},
{
"test": "value2"
}
]
}
}Script
%dw 2.0
output application/json
import isNumeric, substringAfter from dw::core::Strings
fun extractPath(value, path: String) = do {
var nextItem = (path scan /\w+/)[0][0]
---
if (isEmpty(nextItem)) value
else do {
var isIndex = isNumeric(nextItem)
var extractor = isIndex match {
case true -> nextItem as Number
else -> nextItem
}
var restOfPath = substringAfter(path, nextItem)
---
extractPath(
value[extractor],
restOfPath
)
}
}
---
extractPath(payload, "object.array[0].test")Output
"value1"Returns the filtered given value using the conditions passed in an Array of Strings.
Video: DataWeave Scripts Repo: filterValueByConditions tail recursive function | #Codetober 2021 Day 17
Input
[
{
"id": 123,
"name": "abc",
"active": true
},
{
"id": 456,
"name": "def",
"active": true
},
{
"id": 789,
"name": "abc",
"active": false
}
]Script
%dw 2.0
output application/json
fun filterValueByConditions(value, conditions) = (
if (isEmpty(conditions[0])) value
else do {
var firstConditionArr = conditions[0] splitBy ":"
---
filterValueByConditions(
value filter ($[firstConditionArr[0]] ~= firstConditionArr[1]),
conditions[1 to -1]
)
}
)
---
payload filterValueByConditions [
"active:true",
"name:abc"
]Output
[
{
"id": 123,
"name": "abc",
"active": true
}
]Mixing the previous two functions (extractPath and filterValueByConditions) and adding a bit more code to them, this function extracts a specific path and filters the output depending on the given conditions. This also contains an additional function: isArrayOfArray to check if a given value is of the type Array<Array>.
Note
In order to apply the filters successfully, the given key must be from an Array.
Video: DataWeave Scripts Repo: extractPathWithFilters tail recursive function | #Codetober 2021 Day 21
Input
{
"site": "ProstDev",
"contributors": [
{
"active": true,
"id": 123,
"name": {
"firstName": "Alexandra",
"lastName": "Martinez"
},
"posts": [
{
"name": "blogpost1",
"duration": 3,
"comments": [
{
"name": "Jane Doe",
"text": "Good Job, Alex!"
}
]
},
{
"name": "blogpost2",
"duration": 5
},
{
"name": "blogpost3",
"duration": 2,
"comments": [
{
"name": "Pravallika",
"text": "Good Job, Alex!"
}
]
}
]
},
{
"active": true,
"id": 456,
"name": {
"firstName": "Pravallika",
"lastName": "Nagaraja"
},
"posts": [
{
"name": "blogpost4",
"duration": 2
},
{
"name": "blogpost5",
"duration": 3,
"comments": [
{
"name": "Jane Doe",
"text": "Good Job, Pravallika!"
}
]
},
{
"name": "blogpost6",
"duration": 7,
"comments": [
{
"name": "Alex",
"text": "Good Job, Pravallika!"
}
]
}
]
},
{
"active": false,
"id": 789,
"name": {
"firstName": "Jane",
"lastName": "Doe"
},
"posts": [
{
"name": "blogpost7",
"duration": 3,
"comments": [
{
"name": "Alex",
"text": "Good Job, Jane!"
}
]
}
]
}
]
}Script
%dw 2.0
output application/json
import isNumeric, substringAfter from dw::core::Strings
fun isArrayOfArray(value): Boolean = (
(typeOf(value) ~= "Array")
and (typeOf(value[0]) ~= "Array")
)
fun filterValueByConditions(value, conditions) = (
if (isEmpty(conditions[0])) value
else do {
var firstConditionArr = conditions[0] splitBy ":"
---
filterValueByConditions(
value filter ($[firstConditionArr[0]] ~= firstConditionArr[1]),
conditions[1 to -1]
)
}
)
fun extractPathWithFilters(value, path: String, filters: Array = []) = do {
var nextItem = (path scan /\w+/)[0][0]
---
if (isEmpty(nextItem)) value
else do {
var isIndex = isNumeric(nextItem)
var extractor = isIndex match {
case true -> nextItem as Number
else -> nextItem
}
var extractedValue = value[extractor]
var newValue = filterValueByConditions(
isArrayOfArray(extractedValue) match {
case true -> flatten(extractedValue) // flatten array of arrays
else ->extractedValue
},
(filters filter ($.key contains nextItem)).condition
)
---
extractPathWithFilters(
newValue,
substringAfter(path, nextItem),
filters
)
}
}
---
{
all_comments: extractPathWithFilters(
payload,
"contributors.posts.comments"
),
all_posts_duration_3: extractPathWithFilters(
payload,
"contributors.posts",
[
{
"key": "posts",
"condition": "duration:3"
}
]
),
all_posts_duration_3_and_active_contributor: extractPathWithFilters(
payload,
"contributors.posts",
[
{
"key": "posts",
"condition": "duration:3"
},
{
"key": "contributors",
"condition": "active:true"
}
]
)
}Output
{
"all_comments": [
{
"name": "Jane Doe",
"text": "Good Job, Alex!"
},
{
"name": "Pravallika",
"text": "Good Job, Alex!"
},
{
"name": "Jane Doe",
"text": "Good Job, Pravallika!"
},
{
"name": "Alex",
"text": "Good Job, Pravallika!"
},
{
"name": "Alex",
"text": "Good Job, Jane!"
}
],
"all_posts_duration_3": [
{
"name": "blogpost1",
"duration": 3,
"comments": [
{
"name": "Jane Doe",
"text": "Good Job, Alex!"
}
]
},
{
"name": "blogpost5",
"duration": 3,
"comments": [
{
"name": "Jane Doe",
"text": "Good Job, Pravallika!"
}
]
},
{
"name": "blogpost7",
"duration": 3,
"comments": [
{
"name": "Alex",
"text": "Good Job, Jane!"
}
]
}
],
"all_posts_duration_3_and_active_contributor": [
{
"name": "blogpost1",
"duration": 3,
"comments": [
{
"name": "Jane Doe",
"text": "Good Job, Alex!"
}
]
},
{
"name": "blogpost5",
"duration": 3,
"comments": [
{
"name": "Jane Doe",
"text": "Good Job, Pravallika!"
}
]
}
]
}Outputs an Array of Dates Array<Date> containing all the dates between two given dates. (See daysUntil for an alternate solution)
Video: DataWeave Scripts repo: getDatesArray tail recursive function | #Codetober 2022 Day 24
Script
%dw 2.0
output application/json
var date = "2022-10-16" as Date
var dateFinal = "2022-10-18" as Date
fun getDatesArray (
startDate: Date,
endDate: Date,
datesArray: Array = []
) = do {
var newArray = datesArray + startDate
---
if (startDate > endDate) []
else if (startDate == endDate) (
newArray
)
else getDatesArray (
startDate + |P1D|,
endDate,
newArray
)
}
---
getDatesArray(date, dateFinal)Output
[
"2022-10-16",
"2022-10-17",
"2022-10-18"
]Takes an input object with nested objects and transforms it to a two-level object. Can be used in conjuction with YAML Objects to OpenAPI Schema for your Data Cloud Ingestion API in Salesforce.
Input
{
"customer1": {
"id": 1,
"first_name": "Alex",
"last_name": "Martinez",
"email": "alex@sf.com",
"addresses": [
{
"street": "415 Mission Street",
"city": "San Francisco",
"state": "CA",
"postalCode": "94105",
"geo": {
"lat": 37.78916,
"lng": -122.39521
}
},
{
"street": "123",
"city": "San Francisco",
"state": "CA",
"postalCode": "94105",
"geo": {
"lat": 37.78916,
"lng": -122.39521
}
}
]
},
"customer2": {
"id": 1,
"first_name": "Alex",
"last_name": "Martinez",
"email": "alex@sf.com",
"addresses": [
{
"street": "415 Mission Street",
"city": "San Francisco",
"state": "CA",
"postalCode": "94105",
"geo": {
"lat": 37.78916,
"lng": -122.39521
}
},
{
"street": "123",
"city": "San Francisco",
"state": "CA",
"postalCode": "94105",
"geo": {
"lat": 37.78916,
"lng": -122.39521
}
}
]
}
}Script
%dw 2.0
output application/json
fun flattenObject(data:Any, result={}) = (
data match {
case is Object -> data mapObject ((value, key) ->
value match {
case is Object -> flattenObject(value, result)
else -> flattenObject(value, result ++ {(key):value})
}
)
case is Array -> flattenObject(data[0]) // only first item from array will be taken
else -> result
}
)
---
//payload must be an object
payload mapObject ((value, key, index) ->
(key): flattenObject(value)
)Output
{
"customer1": {
"id": 1,
"first_name": "Alex",
"last_name": "Martinez",
"email": "alex@sf.com",
"street": "415 Mission Street",
"city": "San Francisco",
"state": "CA",
"postalCode": "94105",
"lat": 37.78916,
"lng": -122.39521
},
"customer2": {
"id": 1,
"first_name": "Alex",
"last_name": "Martinez",
"email": "alex@sf.com",
"street": "415 Mission Street",
"city": "San Francisco",
"state": "CA",
"postalCode": "94105",
"lat": 37.78916,
"lng": -122.39521
}
}This syntax hasn't been documented so far, but in the following examples you can get a better feeling of how it works. It can be used with the Array and Object types.
The general idea is that you create a function that will essentially be recursive, but since this syntax is a lazy evaluation, you won't receive the Stack Overflow error. Inside the function, specify the head, then use ~ to specify the tail afterwards. Surround this in [] for Array or {} for Object.
This is said to be a better syntax than using recursive or tail-recursive functions. So, I recommend you get familiar with it to use it in your Array/Object transformations.
Outputs an Array of Dates Array<Date> containing all the dates between two given dates. (See getDatesArray for an alternate solution)
Video: DataWeave Scripts repo: daysUntil function (head and tail constructor) | #Codetober 2022 Day 25
Script
%dw 2.0
output application/json
var date = "2022-10-16" as Date
var dateFinal = "2022-10-18" as Date
fun daysUntil (
startDate: Date,
endDate: Date
): Array<Date> = (
if (startDate > endDate) []
else if (startDate == endDate) [startDate]
else [startDate ~ daysUntil(startDate + |P1D|, endDate)]
)
---
date daysUntil dateFinalOutput
[
"2022-10-16",
"2022-10-17",
"2022-10-18"
]Outputs an array of numbers Array<Number> containing all the numbers from 1 to the given input.
Video: DataWeave Scripts repo: daysUntil function (head and tail constructor) | #Codetober 2022 Day 25
Script
%dw 2.0
output application/json
fun countAll(count: Number): Array<Number> =
if (count <= 1) [count]
else [count ~ countAll(count-1)]
---
countAll(3)Output
[
3,
2,
1
]Creates an infinite array of numbers Array<Number> without reaching a stack overflow error, thanks to the head & tail constructor's lazy evaluation. The index/range selector is used to extract a portion of the infinite array to actually see the result.
Video: DataWeave Scripts repo: infiniteCountFrom func (head & tail constructor) | #Codetober 2022 Day 26
Script
%dw 2.0
output application/json
fun infiniteCountFrom(startingNumber: Number): Array<Number> =
[startingNumber ~ infiniteCountFrom(startingNumber + 1)]
---
// remove the [1 to 10] to make it really infinite
// warning: it will NEVER stop running
// watch the video for more information: https://youtu.be/WDi0g2VtFIg
infiniteCountFrom(0)[1 to 10]Output
[
1,
2,
3,
4,
5,
6,
7,
8,
9,
10
]I wasn't sure where to put these functions, so I just dropped them here 😄
Replaces the value with a masked String when the field or the field's attribute contains private information. This function can also be used for different data types, you just need to remove the first condition since it's no longer reading the XML attributes (fieldsToMask contains value.@name).
Video: DataWeave Scripts Repo: maskFields function | #Codetober 2021 Day 24
Input
<?xml version='1.0' encoding='UTF-8'?>
<a>
<Data name="ssn">123456789</Data>
<Data name="accountType">savings</Data>
<Data name="accountNo">111222333444</Data>
<ssn>123456789</ssn>
<accountNo>111222333444</accountNo>
<account>
<person>
<ssn>123456789</ssn>
<name>Jane Doe</name>
</person>
<accountDetails>
<accountNo>111222333444</accountNo>
<accountType>savings</accountType>
<Data name="accountNo">111222333444</Data>
</accountDetails>
</account>
</a>Script
%dw 2.0
output application/xml
import mapLeafValues from dw::util::Tree
var maskedValue = "****" // Replace the value with this String
var fieldsToMask = ["ssn", "accountNo"] // List of fields that need to be masked
fun maskFields(data) = (
data mapLeafValues ((value, path) ->
if (
(fieldsToMask contains value.@name) // If the name of the attribute matches
or (fieldsToMask contains path[-1].selector) // If the name of the field matches
) maskedValue // Replace value
else value // Leave value as-is
)
)
---
maskFields(payload) Output
<?xml version='1.0' encoding='UTF-8'?>
<a>
<Data name="ssn">****</Data>
<Data name="accountType">savings</Data>
<Data name="accountNo">****</Data>
<ssn>****</ssn>
<accountNo>****</accountNo>
<account>
<person>
<ssn>****</ssn>
<name>Jane Doe</name>
</person>
<accountDetails>
<accountNo>****</accountNo>
<accountType>savings</accountType>
<Data name="accountNo">****</Data>
</accountDetails>
</account>
</a>Evaluates if the values from an Array contain at least one empty value (null, [], "", {}). To read more about these 3 different approaches please check out this post: How to check for empty values in an array in DataWeave | Part 4: Arrays Module.
Video: DataWeave Scripts Repo: containsEmptyValues function | #Codetober 2021 Day 26
Script
%dw 2.0
output application/json
import some from dw::core::Arrays
// Arrays module
fun containsEmptyValues1(arr) = if (isEmpty(arr)) true
else arr some isEmpty($)
// Pattern Matching
fun containsEmptyValues2(arr) = arr match {
case [] -> true
case a is Array -> a some isEmpty($)
else -> isEmpty(arr)
}
// Function Overloading
fun containsEmptyValues3(value: Null) = true
fun containsEmptyValues3(arr: Array) = arr match {
case [] -> true
else -> arr some isEmpty($)
}
---
{
fun1: containsEmptyValues1(["1", null]),
fun2: containsEmptyValues2(["1", "2"]),
fun3: containsEmptyValues3(["1", ""])
}Output
{
"fun1": true,
"fun2": false,
"fun3": true
}Creates a simple text output with the concatenation of a text input.
Input
S
M
L
XL
2XL
3XL
4XL
Width, in
20.00
22.01
24.00
25.98
28.00
30.00
32.00
Length, in
27.00
28.00
29.00
30.00
31.00
32.00
32.99Script
%dw 2.0
output text/plain
var p = payload splitBy "\n\n" map (
$ splitBy "\n"
)
var units = (p[1][0] splitBy ", ")[-1]
var sizes = p[0]
var name1 = (p[1][0] splitBy ",")[0]
var column1 = p[1][1 to -1]
var name2 = (p[2][0] splitBy ",")[0]
var column2 = p[2][1 to -1]
---
sizes map (
"$($) - $(name1): $(column1[$$]) $(units), $(name2): $(column2[$$]) $(units)"
) joinBy "\n"Output
S - Width: 20.00 in, Length: 27.00 in
M - Width: 22.01 in, Length: 28.00 in
L - Width: 24.00 in, Length: 29.00 in
XL - Width: 25.98 in, Length: 30.00 in
2XL - Width: 28.00 in, Length: 31.00 in
3XL - Width: 30.00 in, Length: 32.00 in
4XL - Width: 32.00 in, Length: 32.99 inThese are not necessarily functions that I created, but I thought they still created some additional value to learn other kinds of transformations.
Transforms an Array of Strings containing key-value pair strings into an Array of Objects with the provided key-value pairs.
Note
The solution does not include the handling of other scenarios (i.e., invalid keys, not enough args, nulls, etc.)
Input
["key1","value1","key2","value2","key3","value3"]Script
%dw 2.0
output application/json
import divideBy from dw::core::Arrays
---
payload divideBy 2
map {
($[0]): $[1]
}Output
[
{
"key1": "value1"
},
{
"key2": "value2"
},
{
"key3": "value3"
}
]Transforms an input XML to a WordPress-friendly text that can be safely published in a blog post (as a script) to avoid issues with the HTML code.
| From | To |
|---|---|
< |
< |
> |
> |
Input
<plugin>
<groupid>org.mule.tools.maven</groupid>
<artifactid>mule-maven-plugin</artifactid>
<version>${mule.maven.plugin.version}</version>
<extensions>true</extensions>
<configuration>
<cloudhubdeployment>
<uri>https://anypoint.mulesoft.com</uri>
<muleversion>4.4.0</muleversion>
<applicationname>mulesoft-mfa-cicd</applicationname>
<environment>Sandbox</environment>
<workertype>MICRO</workertype>
<region>us-east-2</region>
<workers>1</workers>
<objectstorev2>true</objectstorev2>
<connectedappclientid>${client.id}</connectedappclientid>
<connectedappclientsecret>${client.secret}</connectedappclientsecret>
<connectedappgranttype>client_credentials</connectedappgranttype>
</cloudhubdeployment>
</configuration>
</plugin>Script
%dw 2.0
output text/plain
---
write(payload,"application/xml")
replace "<?xml version='1.0' encoding='UTF-8'?>\n" with ""
replace "<" with "<"
replace ">" with ">"Output
<plugin>
<groupid>org.mule.tools.maven</groupid>
<artifactid>mule-maven-plugin</artifactid>
<version>${mule.maven.plugin.version}</version>
<extensions>true</extensions>
<configuration>
<cloudhubdeployment>
<uri>https://anypoint.mulesoft.com</uri>
<muleversion>4.4.0</muleversion>
<applicationname>mulesoft-mfa-cicd</applicationname>
<environment>Sandbox</environment>
<workertype>MICRO</workertype>
<region>us-east-2</region>
<workers>1</workers>
<objectstorev2>true</objectstorev2>
<connectedappclientid>${client.id}</connectedappclientid>
<connectedappclientsecret>${client.secret}</connectedappclientsecret>
<connectedappgranttype>client_credentials</connectedappgranttype>
</cloudhubdeployment>
</configuration>
</plugin>
Transforms an input text (ideally, HTML or XML) to a WordPress-friendly text that can be safely published in a blog post (as a script) to avoid issues with the HTML code.
| From | To |
|---|---|
< |
< |
> |
> |
Input
<lightning-button-menu
alternative-text="Show menu"
menu-alignment="auto"
>
<template for:each={myMenuItems} for:item="menuItem">
<lightning-menu-item
key={menuItem.id}
value={menuItem.value}
label={menuItem.label}
></lightning-menu-item>
</template>
</lightning-button-menu>
Script
%dw 2.0
output text/plain
---
payload
replace "<" with "<"
replace ">" with ">"Output
<lightning-button-menu
alternative-text="Show menu"
menu-alignment="auto"
>
<template for:each={myMenuItems} for:item="menuItem">
<lightning-menu-item
key={menuItem.id}
value={menuItem.value}
label={menuItem.label}
></lightning-menu-item>
</template>
</lightning-button-menu>
Transforms input YAML Objects to an OpenAPI Schema definition. Especially useful for the Salesforce Ingestion API.
Input
runner_profiles:
maid: 4
first_name: Alex
last_name: Martinez
email: alex@sf.com
gender: NB
city: NF
state: ON
created: 2017-07-21
exercises:
runid: 1
datetime: 2017-07-21T17:32:28Z
km_run: 2
calories_burned: 5
duration_minutes: 6
maid: 8
type: abcScript
%dw 2.0
output application/yaml skipNullOn="objects"
import try from dw::Runtime
fun isDate(value: Any): Boolean = try(() -> value as Date).success
fun isDateTime(value: Any): Boolean = try(() -> value as DateTime).success
---
{
openapi: "3.0.3",
components: {
schemas: payload mapObject ((mainObj, mainObjKey) ->
(mainObjKey): {
"type": lower(typeOf(mainObj)),
properties: mainObj mapObject ((props, propsKey) ->
(propsKey): {
"type": lower(typeOf(props)),
format: (props match {
case is Number -> null
case d if isDateTime(d) -> "date-time"
case d if isDate(d) -> "date"
else -> null
})
}
)
}
)
}
}Output
%YAML 1.2
---
openapi: 3.0.3
components:
schemas:
runner_profiles:
type: object
properties:
maid:
type: number
first_name:
type: string
last_name:
type: string
email:
type: string
gender:
type: string
city:
type: string
state:
type: string
created:
type: string
format: date
exercises:
type: object
properties:
runid:
type: number
datetime:
type: string
format: date-time
km_run:
type: number
calories_burned:
type: number
duration_minutes:
type: number
maid:
type: number
type:
type: stringTransforms a JSON example into a YAML schema to be used in an AsyncAPI 2.6 specification.
Note
There are some limitations to this code: 1) it assumes the first value is always an object and 2) doesn't dive too deep into the arrays structures, only for the first level. Problems will arise if there are Array<Object>, Array<Array> and so on.
Input
{
"eventId": "8f736b-d58e-4c8-ab5b-2b0c5ea26",
"replayId": 14094,
"event": {
"ChangeEventHeader": {
"entityName": "AsyncAPI_User__c",
"recordIds": [
"a00aj00000Oa3mMAAR"
],
"changeType": "CREATE",
"changeOrigin": "com/salesforce/api/soap/62.0;client=SfdcInternalAPI/",
"transactionKey": "0015f80-b56-30d6-7b4c-3e26a683e",
"sequenceNumber": 1,
"commitTimestamp": 1.73038659E+12,
"commitNumber": 1.7303865909031895E+18,
"commitUser": "00aj0008VWLA4",
"nulledFields": [
],
"diffFields": [
],
"changedFields": [
]
},
"OwnerId": "00aj0008VWLA4",
"Name": "alex martinez",
"CreatedDate": 1.73038659E+12,
"CreatedById": "00aj0008VWLA4",
"LastModifiedDate": 1.73038659E+12,
"LastModifiedById": "00aj0008VWLA4",
"First_Name__c": "alex",
"Last_Name__c": "martinez",
"Email__c": "alex@sf.com",
"Created_At__c": 1.730386573E+12
}
}Script
%dw 2.0
output application/yaml skipNullOn="objects"
fun getTypeField(data):Object = {"type": lower(typeOf(data) as String)}
fun getValueStructure(data) = {
(getTypeField(data)),
examples: [data]
}
fun getArrayStructure(data:Array) = {
(getTypeField(data)),
items: (
if (!isEmpty(data[0])) getValueStructure(data[0])
else null
)
}
fun getObjectStructure(data:Object) = {
(getTypeField(data)),
properties: data mapObject ((value, key) -> {
(key): (value match {
case is Object -> getObjectStructure(value)
case is Array -> getArrayStructure(value)
else -> getValueStructure(value)
})
})
}
---
payload: getObjectStructure(payload)Output
%YAML 1.2
---
payload:
type: object
properties:
eventId:
type: string
examples:
- 8f736b-d58e-4c8-ab5b-2b0c5ea26
replayId:
type: number
examples:
- 14094
event:
type: object
properties:
ChangeEventHeader:
type: object
properties:
entityName:
type: string
examples:
- AsyncAPI_User__c
recordIds:
type: array
items:
type: string
examples:
- a00aj00000Oa3mMAAR
changeType:
type: string
examples:
- CREATE
changeOrigin:
type: string
examples:
- com/salesforce/api/soap/62.0;client=SfdcInternalAPI/
transactionKey:
type: string
examples:
- 0015f80-b56-30d6-7b4c-3e26a683e
sequenceNumber:
type: number
examples:
- 1
commitTimestamp:
type: number
examples:
- 1.73038659E+12
commitNumber:
type: number
examples:
- 1.7303865909031895E+18
commitUser:
type: string
examples:
- 00aj0008VWLA4
nulledFields:
type: array
diffFields:
type: array
changedFields:
type: array
OwnerId:
type: string
examples:
- 00aj0008VWLA4
Name:
type: string
examples:
- alex martinez
CreatedDate:
type: number
examples:
- 1.73038659E+12
CreatedById:
type: string
examples:
- 00aj0008VWLA4
LastModifiedDate:
type: number
examples:
- 1.73038659E+12
LastModifiedById:
type: string
examples:
- 00aj0008VWLA4
First_Name__c:
type: string
examples:
- alex
Last_Name__c:
type: string
examples:
- martinez
Email__c:
type: string
examples:
- alex@sf.com
Created_At__c:
type: number
examples:
- 1.730386573E+12