RandomPerson

The RandomPerson transformer is designed to populate specified database columns with personal attributes such as first name, last name, title and gender.

Parameters

Name	Description	Default	Required	Supported DB types
columns	The name of the column to be affected		Yes	text, varchar, char, bpchar, citext
gender	set specific gender (possible values: Male, Female, Any)	Any	No	-
gender_mapping	Specify gender name to possible values when using dynamic mode in "gender" parameter	Any	No	-
fallback_gender	Specify fallback gender if not mapped when using dynamic mode in "gender" parameter	Any	No	-
engine	The engine used for generating the values [random, hash]. Use hash for deterministic generation	random	No	-

Description

The RandomPerson transformer utilizes a comprehensive list of first names to inject random first names into the designated database column. This feature allows for the creation of diverse and realistic user profiles by simulating a variety of first names without using real user data.

column object attributes

• name — the name of the column where the personal attributes will be stored. This value is required.

• template - the template for the column value. You can use the next attributes: .FirstName, .LastName or .Title. For example, if you want to generate a full name, you can use the next template: "{{ .FirstName }} {{ .LastName }}"

• hashing - the bool value. Indicates whether the column value must be passed through the hashing function. The default value is false. If all column has hashing set to false (by default), then all columns will be hashed.

• keep_null - the bool value. Indicates whether NULL values should be preserved. The default value is true

gender_mapping object attributes

gender_mapping - a dictionary that maps the gender value when gender parameters works in dynamic mode. The default value is:

{
  "Male": [
    "male",
    "M",
    "m",
    "man",
    "Man"
  ],
  "Female": [
    "female",
    "F",
    "f",
    "w",
    "woman",
    "Woman"
  ]
}

fallback_gender

Gender that will be used if gender_mapping was not found. This parameter is optional and required only for gender parameter in dynamic mode. The default value is Any.

Example: Populate random first name and last name for table user_profiles in static mode

This example demonstrates how to use the RandomPerson transformer to populate the name and surname columns in the user_profiles table with random first names, last name, respectively.

Create table user_profiles and insert data

CREATE TABLE personal_data
(
    id      SERIAL PRIMARY KEY,
    name    VARCHAR(100),
    surname VARCHAR(100),
    sex     CHAR(1) CHECK (sex IN ('M', 'F'))
);

-- Insert sample data into the table
INSERT INTO personal_data (name, surname, sex)
VALUES ('John', 'Doe', 'M'),
       ('Jane', 'Smith', 'F'),
       ('Alice', 'Johnson', 'F'),
       ('Bob', 'Lee', 'M');

RandomPerson transformer example

- schema: public
  name: personal_data
  transformers:
    - name: "RandomPerson"
      params:
        gender: "Any"
        columns:
          - name: "name"
            template: "{{ .FirstName }}"
          - name: "surname"
            template: "{{ .LastName }}"
        engine: "hash"

Result

Column	OriginalValue	TransformedValue
name	John	Zane
surname	Doe	McCullough

Example: Populate random first name and last name for table user_profiles in dynamic mode

This example demonstrates how to use the RandomPerson transformer to populate the name, surname using dynamic gender

RandomPerson transformer example with dynamic mode

- schema: public
  name: personal_data
  transformers:
    - name: "RandomPerson"
      params:
        columns:
          - name: "name"
            template: "{{ .FirstName }}"
          - name: "surname"
            template: "{{ .LastName }}"
        engine: "random"
      dynamic_params:
        gender:
          column: sex

Result:

Column	OriginalValue	TransformedValue
name	John	Martin
surname	Doe	Mueller