Dataweave Series for Practice & Interview Part-2

Practice Dataweave here :- Dataweave Playground

Important Note:- First Copy Input, Output, DW Code & Use Json Online Validator, to format the JSON, since medium changes the JSON.

1. Array to Object

Input:-

["a:b","c:d"]

Output:-

[
 {
 "a": "b"
 },
 {
 "c": "d"
 }
]

Dataweave Code:-

payload map{
 (($ splitBy ":")[0]):($ splitBy ":")[1]
}

2. Search a field in the same payload using other field values

Input:-

[{
"ID": "A",
"name": "123",
"bossID": "C"
},
{
"ID": "B",
"name": "345",
"bossID": "D"
},
{
"ID": "C",
"name": "456",
"bossID": "B"
},
{
"ID": "D",
"name": "789",
"bossID": "C"
}]

Output:-

[{
"EmpName": "123",
"BossName": "456"
},
{
"EmpName": "345",
"BossName": "789"
},
{
"EmpName": "456",
"BossName": "345"
},
{
"EmpName": "789",
"BossName": "456"
}]

Dataweave Code:-

payload map(item, index)->{
"EmpName": item.name,
"BossName": (payload filter $.ID == item.bossID).name[0]
}

3. Group By Year present inside a String

Input:-

{
 "AU": ["PROD-202100BG12",
 "PROD-202100BG12",
 "PROD-202000BG12",
 "PROD-201900BG12"]
}

Output:-

{
 "2021": [
 "PROD-202100BG12",
 "PROD-202100BG12"
 ],
 "2020": [
 "PROD-202000BG12"
 ],
 "2019": [
 "PROD-201900BG12"
 ]
}

Dataweave Code:-

import * from dw::core::Strings
 - -
payload.AU groupBy ((item, index) -> substringAfter(item,"-")[0 to 3])

4. Output the Following Pattern

Input:-

{
 "number": "1034101910291333"
}

Output:-

[
 "1034",
 "10341019",
 "103410191029",
 "1034101910291333"
]

Dataweave Code:-

var a=abs(sizeOf(payload.number)/4)
 - -
0 to a-1 map payload.number[0 to 4*($+1)-1]

5. Filter based on field value and form a String

Input:-

[
 {
 "name": "abc",
 "city" : "hyd"
 },
 {
 "name": "xyz",
 "city" : "delhi"
 },
 {
 "name": "abc1",
 "city" : "hyd"
 }
]

Output:-

"abc,abc1"

Dataweave Code:-

((payload filter $.city=="hyd").name) joinBy(',')

6. Round down Value to Nearest Whole Number

Input:-

"14.99"

Output:-

14

Dataweave Code:-

floor("14.99")

7. Print ASCII/UniCode value of Character & Vice-Versa

Input:-

{
 "ASCII Value":"A",
 "Char at ASCII":"65"
}

Output:-

{
 "ASCII Value": 65,
 "Char at ASCII": "A"
}

Dataweave Code:-

import * from dw::core::Strings
 - -
{
 "ASCII Value":charCode(payload."ASCII Value"),
 "Char at ASCII":fromCharCode(payload."Char at ASCII" as Number)
}

8. Filter Key & Values of Objects in Separate Array

Input:-

{
 "firstName": "EmpFirstName",
 "lastName": "EmpLastName",
 "address": "EmpAddress"
}

Output:-

{
 "Keys": [
 "firstName",
 "lastName",
 "address"
 ],
 "Values": [
 "EmpFirstName",
 "EmpLastName",
 "EmpAddress"
 ]
}

Dataweave Code:-

{
 "Keys":keysOf(payload),
 "Values":valuesOf(payload)
}

9. Filter files based on File extension

Input:-

["a.csv","b.csv","c.xlsx","d.docx","e.docx"]

Output:-

["a.csv","b.csv","c.xlsx"]

Dataweave Code:-

import * from dw::core::Strings
 - -
payload filter ( $ endsWith ("csv")) or ( $ endsWith ("xlsx"))

10. Filter Values present in both array

Input:-

{
 "a" : ["12", "15", "17"] ,
 "b":["15", "18", "20", "12" , "89"]
}

Output:-

["12","15"]

Dataweave Code:-

payload.a filter (payload.b contains $)

📢 Check the other Articles in the Dataweave Series:- Dataweave Series for Practice & Interview Part 1–10

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