Data Mapper

Transform and map data between flow steps in Fastn. Route outputs from connectors, variables, and secrets into the format your next step needs.

The Data Mapper component lets you reshape and route data between flow steps. You can map outputs from previous steps, variables, or secrets into a new object structure that downstream steps require. Unlike the Converter, which changes data formats (for example, JSON to CSV), the Data Mapper restructures fields within the same format — renaming keys, combining values, or extracting nested properties.

For example,

This example mapping step titled "Content" can be used when you need to map data (usually text) from a previous step and ensure it's passed forward as a string.

Params mapped in configuration

res = steps.chatGPT.output.choices[0].message.content

• Here, res is the variable inside the Content step.

• It is mapped directly from the ChatGPT connector's output: steps.chatGPT.output.choices[0].message.content.

• The mapped value must always resolve to a string type, since Content steps are designed to pass textual data forward.

Example

• Pass the response from ChatGPT as plain text into another step (e.g., a database insert, a file generator, or a Slack notification).

To make this easier, the AI agent in the top-right corner offers smart suggestions for mapping your data. It helps you quickly pull values from previous steps or any flow data. You can simply drag and drop items like Headers, Inputs, Steps, Secrets, or App Config into the field you want to configure; making your mappings faster, more accurate, and less manual.

You can map values either in JSON, JavaScript, C#, Form, or Python Lambda.

Example JSON Mapping

{
  "json": {
    "res": "{{data.steps.chatGPT.output.choices[0].message.content}}"
  },
  "actions": {
    "json": {
      "action": [],
      "targetType": "object"
    },
    "json.res": {
      "action": [],
      "targetType": "object"
    }
  }
}

You can learn more about Data Mapping in Flows here.