JSON to JSON

• JSONata: A powerful JSON querying and transformation language with built-in functions for filtering, aggregation, and computation. Ideal for advanced querying, concise expressions, and complex or ad-hoc data manipulation.
• JSLT: A structured JSON transformation language designed for clear input-to-output mapping and format conversion. Best suited for template-driven transformations and controlled structural changes.
  

• Data: Static or dynamic input JSON.

• Qntrl File ID: Provide a file-based JSON input instead of inline data (optional).

• Script Type: Select JSONata or JSLT from the dropdown.

• Script: Script the transformation logic

• Variables: Define variables to reference within the script

{
  "Json 2 Json Converter": {
      "start": true,
      "module": "json_conversion",
      "task_id": "json_to_json",
      "payload": {
	  "qntrl_file_id": "{file_id}",
	  "script_type": "JSONata",
	  "script": "Account.Order.Product"
      },
      "next": "End"
 }
}

JSLT

{
   "Json 2 Json Converter": {
"start": true,
"module": "json_conversion",
"task_id": "json_to_json",
"payload": {
      "qntrl_file_id": "{file_id}",
"script_type": "Jslt",
"script": {
     "user": {
"name": "upper-case(.name)",
"age": ".age",
"location": ".city",
"isAdult": ".age >= 18"
   }
}
},
"next": "End"
   }
}

JSONata with Variables

{
  "Json 2 Json Converter": {
      "start":true,
      "module": "json_conversion",
      "task_id": "json_to_json",
      "payload": {
	 "variables": {
	     "greeting": "Hello"
	 },
	 "data": {
	     "name": "Alice"
	 },
	 "script_type": "JSONata",
	    "script": "$greeting & ', ' & name"
	 }
       "next": "End"
    },
} 

CSV to JSON    

Converts a CSV file into JSON. Supports custom delimiters, headers, quote characters, and null value handling.

• Has Header: Enable if the first row contains column headers. When enabled, the first row is used as column names. When disabled, columns are auto-named as column1, column2, etc.
  

• Header: Manually define column names when Has Header is disabled.

• Delimiter: Character used to separate values (e.g., comma, semicolon)

• Quote Char: Character used to quote fields containing special characters, preventing them from being split.

• Escape Char: Character used to escape the quote character within a field.

• NA Values: Strings to treat as missing values (NaN).

• Null Substitute: Replacement value for recognized NaN entries.
  

When defining headers manually (i.e., Has Header is disabled), each column entry supports the following keys:

• name: The column name to assign in the JSON output.

• type: The data type of the column (e.g., string, number, datetime).

• input: Specify the format and timezone of the date value in the source CSV.

• output: Specify the desired format and locale of the date value in the JSON output.

{
    "New State 1": {
"type": "task",
"module": "json_conversion",
"task_id": "csv_to_json",
"payload": {
     "qntrl_file_id": "{file_id}",
     "has_header": false,
     "delimiter": ",",
     "quote_char": "\"",
     "headers": [
      {
   "name": "EmployeeID",
   "type": "number"
      },
      {
   "name": "DOB",
   "type": "datetime",
   "input": {
      "format": "yyyy-MM-dd HH:mm:ss",
      "zone": "UTC"
         },
         "output": {
      "format": "yyyy-MMMM-dd HH:mm:ss",
      "locale": "fr"
        }

          }
      ]
     },
     "end": true
   }
}

XML to JSON 

{
    "XML Json Converter": {
	"start":true,
	"module": "json_conversion",
	"task_id": "xml_to_json",
	"payload": {
		"qntrl_file_id": {file_id},
		"range":5
	},
        "next": "End"
    },
}

YAML to JSON  

Converts a YAML file into JSON format. Supports alias limiting to handle complex YAML structures safely.

• Max Aliases: Specify the maximum number of YAML aliases (references) allowed. YAML supports anchors (&) and aliases to reference repeated values.

{
  "YAML Json Converter": {
      "start": true,
       "module": "json_conversion",
       "task_id": "yaml_to_json",
       "payload": {
          "qntrl_file_id": "{file_id}",
          "max_aliases": 10
       },
     "next": "End"
  }
}

XLSX to JSON  

Converts spreadsheet data from an Excel file into JSON. Supports sheet selection and flexible header configuration.

• Sheet Index: Index of the sheet to process.

• Sheet Name: Name of the sheet to process.

• Has Header: Indicates whether the first row contains column headers.

• Header Index: Row index to use as the header row   

Header Behavior:  

• If has_header = true, the first row is treated as column names.

• If has_header = false, columns are auto-generated as column1, column2, etc.

• You can manually define column names when headers are not present.

Code View

{
  "XLSX Json Converter": {
      "start": true,
      "module": "json_conversion",
      "task_id": "xlsx_to_json",
      "payload": {
         "qntrl_file_id": "{file_id}",
         "has_header": true,
         "headers": [
          {
             "name": "person",
             "type": "string"
          },
          {
            "name": "age",
            "type": "number"
          },
          {
            "name": "DOB",
            "type": "datetime",
            "input": {
               "format": "yyyy-MM-dd HH:mm:ss",
               "zone": "UTC"
            },
            "output": {
               "format": "yyyy-MMMM-dd HH:mm:ss",
               "locale": "fr"
            }
         }
      ]
    },
    "next": "End"
  }
}

TXT to JSON  

Converts structured text files into JSON. Supports three parsing methods depending on the structure of your text file.

Builder View Additional Properties

• Delimiter: Character used to split values in delimiter-based parsing (e.g., ,, |, >).

• Has Header: Enable this option if the first row contains column headers. When enabled, the first row is treated as column names.

• Columns: If Has Header is disabled, define columns manually by specifying the column name, data type, and parsing rule.

• Parsing Methods  

• Delimiter-Based Parsing: Used when values in the text file are separated by a consistent character such as ,, |, or >.

• Index-Based (Fixed-Width) Parsing: Used for fixed-length text files where each field occupies a defined character position. Specify the start and end positions to define column boundaries.

• Regex-Based Parsing: Used for unstructured or semi-structured text files (e.g., log files) where fields are identified using pattern matching.

Delimiter-based parsing and fixed-width parsing cannot be used simultaneously.

Code View

i) Index Based Transformation

-> Input  

John                Doe                 35  
Jane                Smith               28  
Bob                 Johnson           42  

-> Config

{
  "TXT Json Converter": {
      "start": true,
      "module": "json_conversion",
      "task_id": "txt_to_json",
      "payload": {
         "qntrl_file_id": "{file_id}",
         "has_header": false,
         "columns": [
          {
             "name": "firstName",
             "start": 0,
             "end": 19,
             "type": "string"
         },
         {
            "name": "lastName",
            "start": 20,
            "end": 39,
            "type": "string"
         },
         {
            "name": "age",
            "start": 40,
            "end": 42,
            "type": "number"
        }
      ]
    }
  }
}

-> Response

[
  { "firstName": "John", "lastName": "Doe", "age": 35 },
  { "firstName": "Jane", "lastName": "Smith", "age": 28 },
  { "firstName": "Bob", "lastName": "Johnson", "age": 42 }
]

ii) Regex Based Transformation

-> Input  

2025-07-29 10:00:00 INFO User logged in
2025-07-29 10:05:00 ERROR Failed to load resource
2025-07-29 10:10:00 INFO User logged out

-> Config

 {
  "TXT Json Converter": {
      "start": true,
      "module": "json_conversion",
      "task_id": "txt_to_json",
      "payload": {
         "qntrl_file_id": "{file_id}",
         "has_header": false,
         "columns": [
          {
             "name": "date",
             "regex": "^\\d{4}-\\d{2}-\\d{2}",
             "type": "date"
          },
          {
             "name": "time",
             "regex": "\\d{2}:\\d{2}:\\d{2}",
             "type": "time",
             "format": "HH:mm:ss"
         },
         {
             "name": "level",
             "regex": "(INFO|ERROR|WARN)",
             "type": "string"
         },
         {
             "name": "message",
             "regex": "(INFO|ERROR|WARN) (.*)$",
             "type": "string"
         }
       ]
    }
  }
}

-> Response

[
  {
      "date": "2025-07-29",
      "time": "10:00:00",
      "level": "INFO",
      "message": "User logged in"
  },
  {
      "date": "2025-07-29",
      "time": "10:05:00",
      "level": "ERROR",
      "message": "Failed to load resource"
  },
  {
      "date": "2025-07-29",
      "time": "10:10:00",
      "level": "INFO",
      "message": "User logged out"
  }
]	

iii) Delimiter Based Transformation  

-> Input  

John | Doe | true | 1985-12-15
Jane | Smith | false | 1990-05-10
Bob | Johnson | true | 1978-03-22

-> Config

{
  "TXT Json Converter": {
    "start": true,
    "module": "json_conversion",
    "task_id": "txt_to_json",
    "payload": {
      "qntrl_file_id": "{file_id}",
      "has_header": false,
      "delimiter": "|",
      "columns": [
        {
          "name": "firstName",
          "type": "string"
        },
        {
          "name": "lastName",
          "type": "string"
        },
        {
          "name": "isActive",
          "type": "boolean"
        },
        {
          "name": "birthDate",
          "type": "date"
        }
      ]
    }
  }
}

-> Response

[
{
    "firstName": "John",
    "lastName": "Doe",
    "isActive": true,
    "birthDate": "1985-12-15"
},
{
    "firstName": "Jane",
    "lastName": "Smith",
    "isActive": false,
    "birthDate": "1990-05-10"
},
{
    "firstName": "Bob",
    "lastName": "Johnson",
    "isActive": true,
    "birthDate": "1978-03-22"
}
]