Transform Node

The Transform Node restructures input data by mapping fields to a new output format.

Define mapping rules to extract values from input paths and assign them to custom output paths.

Purpose

Data Shaping: Adapt data from one format to another for downstream nodes.
Simplification: Flatten or extract only the necessary fields.
Field Renaming: Change the names of keys in a data object.
Normalization: Standardize disparate data structures into a unified format.

Configuration

Configurable properties:

Property	Type	Description	Default
label	string (optional)	Descriptive name for the node instance.	'Transform Data'
mappingRules	Array<MappingRule>	Ordered list of rules defining how input fields are mapped to output fields.	[]

`MappingRule` Structure

id: string – Unique identifier for the rule.
inputPath: string – Path to extract value from the input data.
outputPath: string – Path to assign the value in the output object.
enabled: boolean – Only enabled rules are applied.

Path Syntax for Input and Output

Important: Define the exact syntax for inputPath and outputPath.

Path Language: Use dot notation (user.address.city), JSONPath ($.user.address.city), or bracket notation.
Arrays: How to access/iterate items? (e.g. items[0].price, items[*].price)
Creation: Does outputPath auto-create nested objects/arrays if needed?
Missing Input: If an inputPath does not exist, is it omitted or set as undefined?
Example: inputPath: "userInfo.id", outputPath: "userId"

Inputs and Outputs

Input (Left Handle):
Receives an object (usually JSON) from upstream.

Output (Right Handle, id: "output"):
Emits a new object after applying all enabled mapping rules.

Logic of Mapping

Receives input data.
Initializes an empty output object.
Iterates over mappingRules in order.
For each enabled rule:

Retrieves value at inputPath from input.
Assigns it to outputPath in output.

After all rules, emits the final output object.

If multiple rules write to the same outputPath, clarify if last-wins or a merge happens.

Example: Reformatting User Data

Input Data Object:

{
"userInfo": {
  "id": "usr_123",
  "personal": {
    "firstName": "John",
    "lastName": "Doe",
    "contact": {
      "email": "john.doe@example.com"
    }
  },
  "accountStatus": "active"
}
}

Node Configuration:

label: Reformat User for System B
mappingRules:
- { id: 'r1', inputPath: 'userInfo.id', outputPath: 'userId', enabled: true }
- { id: 'r2', inputPath: 'userInfo.personal.firstName', outputPath: 'customer.firstName', enabled: true }
- { id: 'r3', inputPath: 'userInfo.personal.lastName', outputPath: 'customer.lastName', enabled: true }
- { id: 'r4', inputPath: 'userInfo.personal.contact.email', outputPath: 'customer.emailAddress', enabled: true }
- { id: 'r5', inputPath: 'userInfo.accountStatus', outputPath: 'status', enabled: true }

Output Data Object:

{
"userId": "usr_123",
"customer": {
  "firstName": "John",
  "lastName": "Doe",
  "emailAddress": "john.doe@example.com"
},
"status": "active"
}

Notes and Considerations

Path Syntax: Double-check path syntax per your implementation.
Data Types: Types are preserved (e.g., string stays string).
Debugging: Disable rules to isolate problems or check path validity.

The Transform Node ensures data is in the right format for every step in your workflow.