Dataweave Series for Practice & Interview Part-5

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. Dynamic Value of Key in Key-Value Pair

Input:-

[
{
"Source": " customerName",
"destination": " customer "
},
{
"Source": " customerAddress",
"destination": " address"
}
]

Output:-

{
 " customerName": " customer ",
 " customerAddress": " address"
}

Dataweave Code:-

payload map ((item, index) -> 
 (item.Source):item.destination 
) reduce($$++$)

2. Filter department and count

Input:-

[
   {
       "firstName" : "John",
       "lastName" : "Doe",
       "jobTitle" : "Engineer",
       "department": "Technology"
   },
   {
       "firstName" : "Smith",
       "lastName" : "Doe",
       "jobTitle" : "Engineer",
       "department": "Technology"
   },
   {
       "firstName" : "Kelly",
       "lastName" : "Doe",
       "jobTitle" : "Analyst",
       "department": "Operations"
   },
   {
       "firstName" : "Keith",
       "lastName" : "Doe",
       "jobTitle" : "Analyst",
       "department": "Finance"
   }
]

Output:-

[
  {
    "department": "Technology",
    "count": 2
  },
  {
    "department": "Operations",
    "count": 1
  },
  {
    "department": "Finance",
    "count": 1
  }
]

Dataweave Code:-

%dw 2.0
import * from dw::core::Arrays
output application/json
---
payload distinctBy($.department)map(item,index)->{
    "department": item.department,
    "count":payload countBy ($.department==item.department )
}

3. Print the alphabets with their count of occurrence in the array

Input:-

["a","b","c","a","b","a"]

Output:-

["a3","b2","c1"]

Dataweave Code:-

%dw 2.0
import * from dw::core::Arrays
output application/json
---
payload distinctBy $ map ((item,index)-> item ++ (payload countBy($==item)))

4. Write If Condition without Else

Input:-

{
  "Name": "Shubham",
  "Age": "26"
}

Output:-

{
  "Name": "Shubham"
}

Dataweave Code:-

{
    "Name":[(payload.Name) if payload.Age>25][0]
}

Explanation:- This works only if you wrap the value inside the parenthesis and inside the array.

5. Trim Values inside nested JSON Structure

Input:-

{
  "Employee": [
    {
      "Code": "    501-AKASH",
      "Age": "26",
       "Salary": [{
          "Base":" 330000  "
      }],
      "Date": {
          "Joining":"  26/10/2020 "
      },
      "Billed": ["   NO  "]
    },
    {
      "Code": "    502-PRIYA",
      "Age": "30   ",
      "Salary": [{
          "Base":"200000  "
      }],
      "Date": {
          "Joining":"  26/10/2022 "
      },
      "Billed": ["   YES  "]
    }
  ]
}

Output:-

{
  "Employee": [
    {
      "Code": "501-AKASH",
      "Age": "26",
      "Salary": [
        {
          "Base": "330000"
        }
      ],
      "Date": {
        "Joining": "26/10/2020"
      },
      "Billed": [
        "NO"
      ]
    },
    {
      "Code": "502-PRIYA",
      "Age": "30",
      "Salary": [
        {
          "Base": "200000"
        }
      ],
      "Date": {
        "Joining": "26/10/2022"
      },
      "Billed": [
        "YES"
      ]
    }
  ]
}

Dataweave Code:-

%dw 2.0
output application/json
fun trimVal(value) = value match {
    case is String -> trim($)
    case is Array -> value map (trimVal($))
    case is Object -> value mapObject {
        ($$):trimVal($)
    }
    else -> $
}
---
trimVal(payload)

6. Separate Multiple Values with Single Key into Different Objects

Input:-

{
"NameList": "Shubh,Priya"
}

Output:-

%dw 2.0
output application/json
var valuesList=payload.NameList splitBy  ','
---
valuesList map ((item, index) -> 
    {
        (("Student ") ++(index)): item
    }
)

Dataweave Code:-

[
  {
    "Student 0": "Shubh"
  },
  {
    "Student 1": "Priya"
  }
]

7. Usage of FilterTree Function

Input:-

{
  "firstName": "",
  "lastName": "Shubham",
  "friends": [
    {
      "id": "",
      "test": {
          "val":""
      }
    },
    {
      "age": "123"
    },
    ""
  ]
}

Output:-

{
  "lastName": "Shubham",
  "friends": [
    {
      "test": {
        
      }
    },
    {
      "age": "123"
    }
  ]
}

Dataweave Code:-

%dw 2.0
import * from dw::util::Tree
output application/json
---
payload filterTree ((value, path) ->
            value match  {
                            case s is String -> !isEmpty(s)
                            else -> true
                          })

8. Capitalize the leaf values of nested object: Usage of mapLeafValues function

Input:-

{
     "user": [{
         "name": "Shubham",
         "lastName": {
             "Middle":"",
             "Last":"Chaurasia"
         }
     }],
     "group": "dataweave series"
 }

Output:-

{
  "user": [
    {
      "name": "SHUBHAM",
      "lastName": {
        "Middle": "",
        "Last": "CHAURASIA"
      }
    }
  ],
  "group": "DATAWEAVE SERIES"
}

Dataweave Code:-

%dw 2.0
import * from dw::util::Tree
output application/json
---
payload  mapLeafValues (value, path) -> upper(value)

9. Print Last Date of the Month given a date as input

Input:-

{
    "lastday": "10-02-2023"
}

Output:-

{
  "lastDay": 28
}

Dataweave Code:-

%dw 2.0
fun lastDay(date) =
  (((date as Date {format: "dd-MM-yyyy"} as String {format: "01-" ++ "MM-yyyy"}) as Date {format: "dd-MM-yyyy"}) + |P1M| - |P1D|).day
output application/json  
---
{
  "lastDay": lastDay(payload.lastday)
}

Another Solution with Library

%dw 2.0
import * from dw::core::Dates
output application/json  
---
{
  "lastDay": atBeginningOfMonth(payload.lastday as Date {format: "dd-MM-yyyy"} + |P1M|) - |P1D|
}

10. Add/Update values in objects from other array objects based on matching ID field

Input:-

{
 "id": "0001",
 "type": "donut",
 "name": "Cake",
 "ppu": 0.55,
 "products": [
 {
 "id": "5001",
 "type": "None"
 },
 {
 "id": "5002",
 "type": "Glazed"
 },
 {
 "id": "5005",
 "type": "Sugar"
 },
 {
 "id": "5007",
 "type": "Powdered Sugar"
 },
 {
 "id": "5006",
 "type": "Chocolate with Sprinkles"
 },
 {
 "id": "5003",
 "type": "Chocolate"
 },
 {
 "id": "5004",
 "type": "Maple"
 }
 ],
 "price": [
 {
 "id": "5001",
 "cost": 2
 },
 {
 "id": "5005",
 "cost": 5
 },
 {
 "id": "5007",
 "cost": ""
 },
 {
 "id": "5004",
 "cost": 6
 },
 {
 "id": "5008",
 "cost": ""
 }
 ]
}

Output:-

[
 {
 "id": "5001",
 "type": "None",
 "price": 2
 },
 {
 "id": "5002",
 "type": "Glazed",
 "price": null
 },
 {
 "id": "5005",
 "type": "Sugar",
 "price": 5
 },
 {
 "id": "5007",
 "type": "Powdered Sugar",
 "price": ""
 },
 {
 "id": "5006",
 "type": "Chocolate with Sprinkles",
 "price": null
 },
 {
 "id": "5003",
 "type": "Chocolate",
 "price": null
 },
 {
 "id": "5004",
 "type": "Maple",
 "price": 6
 }
]

Dataweave Code:-

payload.products map ((item, index) -> {
 "id":item.id,
 "type":item."type",
 "price":(payload.price filter $.id == item.id).cost[0]
 }
)

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

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