Distributions

Use Custom fields to choose from a weighted value pool. The current shape is an options.distribution object mapping each value to a weight:

{
  "name": "country",
  "type": "Custom",
  "options": {
    "distribution": {"DE": 10, "AT": 2, "CH": 1, "FR": 1},
    "stringify": true
  }
}

Weights are normalized. Here the expected shares are about 71.4% DE, 14.3% AT and 7.1% each CH and FR. A small random sample will not necessarily match those proportions exactly.

Custom values are strings by default. With stringify: false, JSON scalar spellings such as true or 42 can become booleans or numbers; this does not turn arbitrary object text into a nested object.

Numeric ranges

{"name":"age","type":"Number","options":{"min":18,"max":80}}

Use the options exposed by your installation's field catalogue. There is no generic documented gaussian, pareto or recent_bias option across all field types. For a particular statistical distribution, implement and validate the sampling in a scenario.

Sequences and relationships

Date and Datetime fields support sequence options for ordered or spaced dates. Parent-window options constrain child dates within a parent's time window, and progression options can model ordered status changes. Configure these through the field editor's available controls and inspect a sample containing several related records.

For reusable weighted lists, save a custom data type or install a value library from the Hub.

Reproducibility

Pass an integer seed to POST /datamaker and retain the same fields, quantity and locale to reproduce internal generation. Save the request definition alongside test code. A seed does not freeze AI output, database contents, API responses or Python Script execution, and it is not a promise that outputs remain identical across generator upgrades.