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Documentation Index

Fetch the complete documentation index at: https://docs.dataharbor.co/llms.txt

Use this file to discover all available pages before exploring further.

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Field Targeting

Field paths are shared across Data Control and Data Transform. Once DataHarbor matches an object definition, it resolves each field path against the normalized payload for that object.
Object matching happens first. Field targeting happens second. See Virtual APIs and Data Pipeline for the higher-level request flow.

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Quick reference

PathTargets
emailA top-level scalar field
user.emailA nested field inside an object
"[contacts].email"The email field on every item in the contacts array
"[orders].[items].sku"A nested field inside nested arrays

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Path syntax rules

  • Use dot notation for nested objects.
  • Use bracket segments like "[contacts]" for arrays.
  • Slash notation like address/city is not supported.
  • If the matched payload itself is a root array, the full controls pipeline runs against each object element automatically.

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Nested fields

Use dot notation when the field lives inside one or more nested objects. 
controls:
  - type: redact
    fields:
      - user.ssn
      - billing.card.last4
      - metadata.created_by

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Arrays

Use bracket segments when the field exists inside every item of an array. 
controls:
  - type: tokenize
    fields:
      - "[contacts].email"
      - "[contacts].phone"
      - "[orders].[items].sku"
If the response payload itself is a root array, you do not need a leading array segment. DataHarbor applies the control list to each object element automatically.

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required: true

Set required: true when a missing field should fail the request instead of being skipped. 
controls:
  - type: hash
    fields: [customer_id]
    required: true
Required checks are full-path strict:
  • If an intermediate parent object is missing, the request fails.
  • If the final field is missing, the request fails.
  • For coalesce, all referenced fields being missing or empty also fails when required: true is set.

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Scalar versus structured targets

Filter-style data controls such as redact, tokenize, anonymize, mask, hash, and allow target scalar values only. That means:
  • strings, numbers, and booleans are valid targets
  • objects and arrays are not valid targets for filter controls
If you need to reshape objects instead of replacing scalar values, use Data Transform.

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Transform path rules

Transforms add a few extra path constraints:
  • For combine and coalesce, every source field in fields plus the destination into path must share the same parent path.
  • delete does not use into; it removes the paths named in fields directly.
  • If into already exists, combine and coalesce fail instead of overwriting the field.

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Next steps

Data Control

Apply privacy controls to the fields you target

Data Transform

Create, combine, and remove fields in the same pipeline

Control Block Reference

Review the detailed rules for each control type