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Data Piping

Data piping in Ductape enables dynamic referencing and transfer of data between feature inputs, event sequences, and outputs. It is a core mechanism for building flexible, reusable, and maintainable workflows. Data piping is used throughout the SDK, especially in IFeatureEvent and output mapping.

Supported Data Piping Notations​

You can use the following notations to reference data dynamically in your feature definitions:

NotationDescription
$Input{field}Retrieves a value directly from the feature's input
$Sequence{sequence}{event}{key}Accesses a specific key from an event within a sequence
$Variable{app_tag}{key}References a variable associated with the app identified by app_tag
$Constant{app_tag}{key}Accesses a constant defined for the app identified by app_tag
$Auth{auth_tag}{context}{token}Retrieves an authentication token for secure communications

How Data Piping Works​

  • Inputs: Use $Input{field} to reference initial feature input values.
  • Event Sequences: Use $Sequence{sequence}{event}{key} to pass data between events in a sequence.
  • Variables & Constants: Use $Variable{app_tag}{key} and $Constant{app_tag}{key} for dynamic and static values defined at the app level.
  • Authentication: Use $Auth{auth_tag}{context}{token} to inject tokens into event inputs or headers.
  • Outputs: Map results using any of the above notations to build structured, dynamic feature outputs.

Example: Data Piping in Action​

const featureEvent: IFeatureEvent = {
  type: FeatureEventTypes.ACTION,
  event: 'process_payment',
  input: {
    userId: `$Input{user_id}`,
    orderId: `$Sequence{order_flow}{create_order}{order_id}`,
    token: `$Auth{bearer_access}{header}{token}`,
    email: `$Variable{user_service}{email}`,
    currency: `$Constant{payments}{currency_code}`,
  },
  retries: 2,
  allow_fail: false,
};

Best Practices​

  • Use data piping to keep your features dynamic and reusable.
  • Reference only the data you need to keep event inputs and outputs concise.
  • Use variables and constants to avoid hardcoding values.
  • Document your data piping usage for maintainability.
  • Test your data flows to ensure correct resolution of all references.

See Also​