fixtuRes

Generate mock data in R using YAML configuration.

Installation

You can install a stable release from CRAN repository:

install.packages("fixtuRes")

You can install the latest version with remotes:

remotes::install_github("jakubnowicki/fixtuRes@develop")

Usage

fixtuRes package provides a set of tools that allow generating random mock data for testing or to use during development. Main one, R6 class named MockDataGenerator is a data generator fed with a configuration provided in a yaml file. You can also use lower level functions designed to generate data frames, vectors or single values.

MockDataGenerator

Let’s say, that you need a data frame with 5 columns. First one should be called “id” and contain a random integer from 100 to 999. Second, “code”, should be a string of three capital letters. Third one, “metric”, is a random numeric value in -10, 10 range. Fourth, called “type”, can be one of “TEST”, “PROD”, “QUA”. Finally, the fifth one is a boolean called “pass”. It should be set to TRUE if metric is above 3, otherwise it should be set to FALSE. To create a data frame that follows those rules you will need a configuration (you can find prepared file here):

my_data_frame:
  columns:
    id:
      type: integer
      min: 100
      max: 999
      unique: TRUE
    code:
      type: string
      pattern: "[A-Z]"
      length: 3
    metric:
      type: numeric
      min: -10
      max: 10
    type:
      type: set
      set: ["TEST", "PROD", "QUA"]
    pass:
      type: calculated
      formula: "metric > 3"

Now you can pass this configuration to a new MockDataGenerator object:

my_mock_generator <- fixtuRes::MockDataGenerator$new("path-to-my-configuration.yml")

And just create a data frame you have just designed:

my_mock_generator$get_data("my_data_frame")

For a detailed description of configuration check this document.

Low level functions are described in R package documentation.

Showcase

You can check fixtuRes in action in Fake Data Generator. It enables live preview of your YAML configuration, downloading YAML itself and generated dataset.