How to map source fields to target fields from comma-separated string values

Content

The goal of this article is to write a DataWeave transformation that translates the source fields to target fields from a comma-separated string value.

For example, we have a list of source field names as input and the expected target field to be mapped before we pass this to the next component.

We want the following output:

Scenario 1:

Fields Transformation:

Input:

{
  "columnList": "all"
}


Output:


{
  "columnList": "all"
}

        

Scenario 2:

Fields Transformation:

Note: Additional checks

- Map only those fields listed in the above list.

- Trim spaces to avoid any mismatch with the field names.

- Remove duplicates in case of.

- Remove empty fields or null empty strings

Input:

{
  "columnList": "siteName,network,productCode,productName"
}


Output:

{  "columnList": "merchantNameLocation,merchantNetwork,globalProductCode,globalProductDescription"
}         

PROCEDURE

Using DataWeave inbuilt core functions we could achieve the above scenarios, the following expression implements the desired output: 

DataWeave Input Scenarios:

Mixed Case

{
    "columnList": "AlL"
}
 

{
    "columnList": "aLl"
}
 

Duplicate Fields

{
    "columnList": "siteName,network, siteName,productCode,productName"
}
 

Empty Strings

{
    "columnList": "siteName,network, ,productCode, ,productName"
}
 

Spaces before or after fields

{
    "columnList": "siteName,network,productCode, productName , "
}

 
camelize

{
    "columnList": "SiteName,Network, ,productCode, ,productName"

}        

DataWeave Script:

%dw 2.0
import * from dw::core::Strings

fun fromStringSourceFieldToTargetFields(string) =
  if (lower(string) == "all")
    "All"
  else
    trim(camelize(string)) splitBy "," map (trim($) match {
      case "siteName" -> "merchantNameLocation"
      case "network" -> "merchantNetwork"
      case "productCode" -> "globalProductCode"
      case "productName" -> "globalProductDescription"
      else -> ""
    }) filter ($ != "") distinctBy ($) joinBy ","
output application/json  
---
{
  "columnList": fromStringSourceFieldToTargetFields(payload.columnList)
}        

DataWeave Output:

Output:

{ 
"columnList":
"merchantNameLocation,merchantNetwork,globalProductCode,globalProductDescription"
}
        

DataWeave Playground

Conclusion

It's easy to learn the below commonly used DataWeave functions, to solve day-to-day integration mapping requirements.

For more details, find the below MuleSoft Developer Documentation.

lower | map | splitBy | If else | trim | distinctBy | filter | camelize | joinBy | match | fun | DataWeave Language

Happy Learning ...!

Vikas Kerehalli

#mymulesofttutorial MuleSoft Developers #mulesoftcommunity #mulesoft