Mock a learnr interactive exercise — mock

Creates an interactive exercise object that can be used in tests without having to create a learnr tutorial.

Usage

mock_exercise(
  user_code = "1 + 1",
  label = "ex",
  chunks = list(),
  engine = "r",
  global_setup = NULL,
  setup_label = NULL,
  solution_code = NULL,
  code_check = NULL,
  error_check = NULL,
  check = NULL,
  tests = NULL,
  exercise.checker = NULL,
  exercise.error.check.code = NULL,
  exercise.df_print = "default",
  exercise.warn_invisible = TRUE,
  exercise.timelimit = 10,
  fig.height = 4,
  fig.width = 6.5,
  fig.retina = 2,
  version = current_exercise_version,
  ...
)

mock_chunk(label, code, exercise = FALSE, engine = "r", ...)

Arguments

user_code, solution_code, global_setup: The user, solution, and global setup code, as strings.
label: The label of the exercise.
chunks: A list of chunks to use for the exercise. Use mock_chunk() to create chunks.
engine: The knitr language engine used by the exercise, equivalent to the engine used for the chunk with exercise = TRUE in a tutorial.
setup_label: The label of the chunk that contains the setup code. The chunk itself should be among the list of chunks provided to the chunks argument and the label of the setup chunk needs to match the label provided to setup_label.
check, code_check, error_check: The checking code, as a string, that would typically be provided in the -check, -code-check and -error-check chunks in a learnr tutorial.
tests: The a string with the exercise testing code that would be provided in the -tests chunk.
exercise.checker: The exercise checker function, as a string. By default, a debug exercise checker is set but will only be used if any of check, code_check or error_check are provided.
exercise.error.check.code: The default code used for error_check and applied only when check or code_check are provided and the user's code throws an error.
exercise.df_print, exercise.warn_invisible, exercise.timelimit, fig.height, fig.width, fig.retina: Common exercise chunk options.
version: The exercise version to emulate, by default mock_exercise() will return an exercise that matches the current exercise version.
...: Additional chunk options as if there were included in the exercise chunk.
code: In mock_chunk(), the code in the mocked chunk.
exercise: In mock_chunk(), is this chunk the exercise chunk? If so, mock_exercise() will not create the exercise chunk for you.

Functions

mock_exercise: Create a learnr exercise object
mock_chunk: Create a mock exercise-supporting chunk

Examples

mock_exercise(
  user_code = "1 + 1",
  solution_code = "2 + 2",
  label = "two-plus-two"
)
#> ```{r "two-plus-two", exercise=TRUE}
#> 1 + 1
#> ```

# Global Setup
mock_exercise(
  user_code = 'storms %>% filter(name = "Roxanne")',
  solution_code = 'storms %>% filter(name == "Roxanne")',
  global_setup = 'library(learnr)\nlibrary(dplyr)',
  label = "filter-storms"
)
#> ```{r "filter-storms", exercise=TRUE}
#> storms %>% filter(name = "Roxanne")
#> ```

# Chained setup chunks
mock_exercise(
  user_code = "roxanne",
  solution_code = "roxanne %>%
  group_by(year, month, day) %>%
  summarize(wind = mean(wind))",
  chunks = list(
    mock_chunk(
      label = "prep-roxanne",
      code = 'roxanne <- storms %>% filter(name == "Roxanne")'
    )
  ),
  setup_label = "prep-roxanne",
  global_setup = "library(learnr)\nlibrary(dplyr)"
)
#> ```{r "prep-roxanne"}
#> roxanne <- storms %>% filter(name == "Roxanne")
#> ```
#> 
#> ```{r "ex", exercise.setup="prep-roxanne", exercise=TRUE}
#> roxanne
#> ```