Advanced Data Generation Customization

Drafta allows users to customize generated data by specifying formats, value ranges, and example patterns. This enables the creation of more precise test data that aligns with real-world expectations.

Syntax Format

Customization follows this pattern:

field_name: data_type @data_format min_value-max_value (example_format)

Components:

• field_name: The name of the field.
• data_type: One of string, number, boolean, or enum.
• data_format: An optional format specifier (e.g., uuid, email, date).
• min_value-max_value: Defines the valid range (only for number).
• example_format: Provides an example structure for guidance.

Basic Field Customization

This example defines a user schema with customized field types, including UUIDs, full names, numeric ranges, and boolean probabilities.

User:
  id: string @uuid
  name: string @full_name
  age: number 18-65
  is_active: boolean

Generated Output:

{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "name": "Alice Johnson",
  "age": 34,
  "is_active": true
}

Customizing Strings and Numbers

This example customizes product data by specifying formats such as UUIDs, product names, price ranges with a currency format, and stock limits.

Product:
  id: string @uuid
  name: string @product_name
  price: number 5.00-999.99 (currency)
  stock: number 0-1000
  available: boolean

Generated Output:

{
  "id": "d290f1ee-6c54-4b01-90e6-d701748f0851",
  "name": "Wireless Mouse",
  "price": 49.99,
  "stock": 120,
  "available": true
}

String Formats

This example focuses on string data formats, including sentences, paragraphs, full names, and formatted dates.

Document:
  title: string @sentence
  description: string @paragraph
  author: string @full_name
  published_date: string @date (YYYY-MM-DD)

Generated Output:

{
  "title": "The Future of AI",
  "description": "Artificial Intelligence is transforming industries across the globe, making processes more efficient and improving decision-making capabilities.",
  "author": "Jane Doe",
  "published_date": "2025-02-20"
}

String Abbreviations

This example defines full names and their abbreviations with a fixed length constraint.

State:
  name: string @full_name
  abbreviation: string @state_abbr
  country: string full_name

Generated Output:

{
  "name": "California",
  "abbreviation": "CA",
  "country": "United States"
}

Referencing Objects with Customization

This example demonstrates referencing other objects while applying constraints on numeric values and date formatting.

Invoice:
  invoice_id: string @uuid
  customer: $User
  items: [$Product]
  total: number 20.00-10000.00 (currency)
  issued_date: string @date (YYYY-MM-DD)

Generated Output:

{
  "invoice_id": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
  "customer": {
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "name": "Alice Johnson",
    "age": 34,
    "is_active": true
  },
  "items": [
    {
      "id": "d290f1ee-6c54-4b01-90e6-d701748f0851",
      "name": "Wireless Mouse",
      "price": 49.99,
      "stock": 120,
      "available": true
    }
  ],
  "total": 299.99,
  "issued_date": "2025-02-20"
}

These examples illustrate how to fine-tune data generation in Drafta, ensuring realistic and domain-specific test datasets.