Package 'quickcheck'

Title: Property Based Testing
Description: Property based testing, inspired by the original 'QuickCheck'. This package builds on the property based testing framework provided by 'hedgehog' and is designed to seamlessly integrate with 'testthat'.
Authors: Andrew McNeil [aut, cre]
Maintainer: Andrew McNeil <[email protected]>
License: MIT + file LICENSE
Version: 0.1.3
Built: 2026-05-31 08:39:10 UTC
Source: https://github.com/armcn/quickcheck

Help Index

Any atomic vector generator

Description

Generate vectors of integer, double, character, logical, date, POSIXct, hms, or factors.

Usage

any_atomic(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_atomic() %>% show_example()
any_atomic(len = 10L, any_na = TRUE) %>% show_example()

Any data frame generator

Description

Generate data.frames.

Usage

any_data_frame(rows = c(1L, 10L), cols = c(1L, 10L), any_na = FALSE)

Arguments

rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).
cols

Number of columns of the generated data frame. If cols is a single number all data frames will have this number of columns. If cols is a numeric vector of length 2 it will produce data frames with columns between a minimum and maximum, inclusive. For example cols = c(1L, 10L) would produce data frames with columns between 1 and 10. To produce empty tibbles set cols = 0L or a range like cols = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_data_frame(rows = 3L, cols = 3L) %>% show_example()

Any data.table generator

Description

Generate data.tables.

Usage

any_data.table(rows = c(1L, 10L), cols = c(1L, 10L), any_na = FALSE)

Arguments

rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).
cols

Number of columns of the generated data frame. If cols is a single number all data frames will have this number of columns. If cols is a numeric vector of length 2 it will produce data frames with columns between a minimum and maximum, inclusive. For example cols = c(1L, 10L) would produce data frames with columns between 1 and 10. To produce empty tibbles set cols = 0L or a range like cols = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_data.table(rows = 3L, cols = 3L) %>% show_example()

Any flat homogeneous list generator

Description

Generate lists in which each element is an atomic scalar of the same class.

Usage

any_flat_homogeneous_list(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_flat_homogeneous_list() %>% show_example()
any_flat_homogeneous_list(len = 10L, any_na = TRUE) %>% show_example()

Any flat list generator

Description

Generate lists in which each element is an atomic scalar.

Usage

any_flat_list(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_flat_list() %>% show_example()
any_flat_list(len = 10L, any_na = TRUE) %>% show_example()

Any list generator

Description

Generate lists containing lists or atomic vectors.

Usage

any_list(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_list() %>% show_example()
any_list(len = 10L, any_na = TRUE) %>% show_example()

Any tibble generator

Description

Generate tibbles.

Usage

any_tibble(rows = c(1L, 10L), cols = c(1L, 10L), any_na = FALSE)

Arguments

rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).
cols

Number of columns of the generated data frame. If cols is a single number all data frames will have this number of columns. If cols is a numeric vector of length 2 it will produce data frames with columns between a minimum and maximum, inclusive. For example cols = c(1L, 10L) would produce data frames with columns between 1 and 10. To produce empty tibbles set cols = 0L or a range like cols = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_tibble(rows = 3L, cols = 3L) %>% show_example()

Any undefined value generator

Description

Generate undefined values. In this case undefined values include NA, NA_integer_, NA_real_, NA_character_, NA_complex_, NULL, -Inf, Inf, and NaN. Values generated are always scalars.

Usage

any_undefined()

Value

A quickcheck_generator object.

Examples

any_undefined() %>% show_example()

Any vector generator

Description

Generate atomic vectors or lists.

Usage

any_vector(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

any_vector() %>% show_example()
any_vector(len = 10L, any_na = TRUE) %>% show_example()

Any R object generator

Description

Generate any R object. This doesn't actually generate any possible object, just the most common ones, namely atomic vectors, lists, data.frames, tibbles, data.tables, and undefined values like NA, NULL, Inf, and NaN.

Usage

anything(any_empty = TRUE, any_undefined = TRUE)

Arguments

any_empty

Whether empty vectors or data frames should be allowed.
any_undefined

Whether undefined values should be allowed.

Value

A quickcheck_generator object.

Examples

anything() %>% show_example()

Convert a quickcheck generator to a hedgehog generator

Description

Convert a quickcheck generator to a hedgehog generator

Usage

as_hedgehog(generator)

Arguments

generator

A quickcheck_generator object.

Value

A quickcheck_generator object.

Examples

is_even <-
  function(a) a %% 2L == 0L
gen_powers_of_two <-
  integer_bounded(1L, 10L, len = 1L) %>%
    as_hedgehog() %>%
    hedgehog::gen.with(function(a) 2 ^ a)
for_all(
  a = from_hedgehog(gen_powers_of_two),
  property = function(a) is_even(a) %>% testthat::expect_true()
)

Character generators

Description

A set of generators for character vectors.

Usage

character_(len = c(1L, 10L), any_na = FALSE, any_empty = FALSE)

character_letters(len = c(1L, 10L), any_na = FALSE, any_empty = FALSE)

character_numbers(len = c(1L, 10L), any_na = FALSE, any_empty = FALSE)

character_alphanumeric(len = c(1L, 10L), any_na = FALSE, any_empty = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
any_empty

Whether empty character values should be allowed.

Value

A quickcheck_generator object.

Examples

character_() %>% show_example()
character_(len = 10L, any_na = TRUE) %>% show_example()
character_(len = 10L, any_empty = TRUE) %>% show_example()

Generate the same value every time

Description

Generate the same value every time

Usage

constant(a)

Arguments

a

Any R object

Value

A quickcheck_generator object.

Examples

constant(NULL) %>% show_example()

Data frame generators

Description

Construct data frame generators in a similar way to base::data.frame.

Usage

data_frame_(..., rows = c(1L, 10L))

Arguments

...

A set of name-value pairs with the values being vector generators.
rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

data_frame_(a = integer_()) %>% show_example()
data_frame_(a = integer_(), b = character_(), rows = 5L) %>% show_example()

Data frame generator with randomized columns

Description

Data frame generator with randomized columns

Usage

data_frame_of(..., rows = c(1L, 10L), cols = c(1L, 10L))

Arguments

...

A set of unnamed generators. The generated data frames will be built with random combinations of these generators.
rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).
cols

Number of columns of the generated data frame. If cols is a single number all data frames will have this number of columns. If cols is a numeric vector of length 2 it will produce data frames with columns between a minimum and maximum, inclusive. For example cols = c(1L, 10L) would produce data frames with columns between 1 and 10. To produce empty tibbles set cols = 0L or a range like cols = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

data_frame_of(logical_(), date_()) %>% show_example()
data_frame_of(any_atomic(), rows = 10L, cols = 5L) %>% show_example()

data.table generators

Description

Construct data.table generators in a similar way to data.table::data.table.

Usage

data.table_(..., rows = c(1L, 10L))

Arguments

...

A set of name-value pairs with the values being vector generators.
rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

data.table_(a = integer_()) %>% show_example()
data.table_(a = integer_(), b = character_(), rows = 5L) %>% show_example()

data.table generator with randomized columns

Description

data.table generator with randomized columns

Usage

data.table_of(..., rows = c(1L, 10L), cols = c(1L, 10L))

Arguments

...

A set of unnamed generators. The generated data.tables will be built with random combinations of these generators.
rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).
cols

Number of columns of the generated data frame. If cols is a single number all data frames will have this number of columns. If cols is a numeric vector of length 2 it will produce data frames with columns between a minimum and maximum, inclusive. For example cols = c(1L, 10L) would produce data frames with columns between 1 and 10. To produce empty tibbles set cols = 0L or a range like cols = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

data.table_of(logical_(), date_()) %>% show_example()
data.table_of(any_atomic(), rows = 10L, cols = 5L) %>% show_example()

Date generators

Description

A set of generators for date vectors.

Usage

date_(len = c(1L, 10L), any_na = FALSE)

date_bounded(left, right, len = c(1L, 10L), any_na = FALSE)

date_left_bounded(left, len = c(1L, 10L), any_na = FALSE)

date_right_bounded(right, len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
left

The minimum possible value for generated numbers, inclusive.
right

The maximum possible value for generated numbers, inclusive.

Value

A quickcheck_generator object.

Examples

date_() %>% show_example()
date_bounded(
  left = as.Date("2020-01-01"),
  right = as.Date("2020-01-10")
) %>% show_example()
date_(len = 10L, any_na = TRUE) %>% show_example()

Double generators

Description

A set of generators for double vectors.

Usage

double_(
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

double_bounded(
  left,
  right,
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE
)

double_left_bounded(
  left,
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

double_right_bounded(
  right,
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

double_positive(
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

double_negative(
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

double_fractional(
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

double_whole(
  len = c(1L, 10L),
  any_na = FALSE,
  any_nan = FALSE,
  any_inf = FALSE,
  big_dbl = FALSE
)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
any_nan

Whether NaN values should be allowed.
any_inf

Whether Inf/-Inf values should be allowed.
big_dbl

Should doubles near the maximum size be included? This may cause problems because if the result of a computation results in a double larger than the maximum it will return Inf.
left

The minimum possible value for generated numbers, inclusive.
right

The maximum possible value for generated numbers, inclusive.

Value

A quickcheck_generator object.

Examples

double_() %>% show_example()
double_(big_dbl = TRUE) %>% show_example()
double_bounded(left = -5, right = 5) %>% show_example()
double_(len = 10L, any_na = TRUE) %>% show_example()
double_(len = 10L, any_nan = TRUE, any_inf = TRUE) %>% show_example()

Equal length vector generator

Description

Generates equal length vectors contained in a list.

Usage

equal_length(..., len = c(1L, 10L))

Arguments

...

A set of named or unnamed vector generators.
len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

equal_length(integer_(), double_()) %>% show_example()
equal_length(a = logical_(), b = character_(), len = 5L) %>% show_example()

Factor generator

Description

A generator for factor vectors.

Usage

factor_(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

factor_() %>% show_example()
factor_(len = 10L, any_na = TRUE) %>% show_example()

Variable length flat list generator

Description

Generate flat lists with all values coming from a single generator. In a flat list all items will be scalars.

Usage

flat_list_of(generator, len = c(1L, 10L))

Arguments

generator

A quickcheck_generator object.
len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

flat_list_of(integer_(), len = 10L) %>% show_example()

Test properties of a function

Description

Test properties of a function

Usage

for_all(
  ...,
  property,
  tests = getOption("quickcheck.tests", 100L),
  shrinks = getOption("quickcheck.shrinks", 100L),
  discards = getOption("quickcheck.discards", 100L)
)

Arguments

...

Named generators
property

A function which takes values from from the generator and calls an expectation on it. This function must have parameters matching the generator names.
tests

The number of tests to run.
shrinks

The maximum number of shrinks to run when shrinking a value to find the smallest counterexample.
discards

The maximum number of discards to permit when running the property.

Value

A testthat expectation object.

Examples

for_all(
  a = numeric_(len = 1L),
  b = numeric_(len = 1L),
  property = function(a, b) testthat::expect_equal(a + b, b + a),
  tests = 10L
)

Convert a hedgehog generator to a quickcheck generator

Description

Convert a hedgehog generator to a quickcheck generator

Usage

from_hedgehog(generator)

Arguments

generator

A hedgehog.internal.gen object.

Value

A quickcheck_generator object.

Examples

is_even <-
  function(a) a %% 2L == 0L

gen_powers_of_two <-
  hedgehog::gen.element(1:10) %>% hedgehog::gen.with(function(a) 2 ^ a)

for_all(
  a = from_hedgehog(gen_powers_of_two),
  property = function(a) is_even(a) %>% testthat::expect_true()
)

hms generators

Description

A set of generators for hms vectors.

Usage

hms_(len = c(1L, 10L), any_na = FALSE)

hms_bounded(left, right, len = c(1L, 10L), any_na = FALSE)

hms_left_bounded(left, len = c(1L, 10L), any_na = FALSE)

hms_right_bounded(right, len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
left

The minimum possible value for generated numbers, inclusive.
right

The maximum possible value for generated numbers, inclusive.

Value

A quickcheck_generator object.

Examples

hms_() %>% show_example()
hms_bounded(
  left = hms::as_hms("00:00:00"),
  right = hms::as_hms("12:00:00")
) %>% show_example()
hms_(len = 10L, any_na = TRUE) %>% show_example()

Integer generators

Description

A set of generators for integer vectors.

Usage

integer_(len = c(1L, 10L), any_na = FALSE, big_int = FALSE)

integer_bounded(left, right, len = c(1L, 10L), any_na = FALSE)

integer_left_bounded(left, len = c(1L, 10L), any_na = FALSE, big_int = FALSE)

integer_right_bounded(right, len = c(1L, 10L), any_na = FALSE, big_int = FALSE)

integer_positive(len = c(1L, 10L), any_na = FALSE, big_int = FALSE)

integer_negative(len = c(1L, 10L), any_na = FALSE, big_int = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
big_int

Should integers near the maximum size be included? This may cause problems because if the result of a computation results in an integer larger than the maximum it will be silently coerced it to a double.
left

The minimum possible value for generated numbers, inclusive.
right

The maximum possible value for generated numbers, inclusive.

Value

A quickcheck_generator object.

Examples

integer_() %>% show_example()
integer_(big_int = TRUE) %>% show_example()
integer_bounded(left = -5L, right = 5L) %>% show_example()
integer_(len = 10L, any_na = TRUE) %>% show_example()

List generator

Description

Generate lists with contents corresponding to the values generated by the input generators.

Usage

list_(...)

Arguments

...

A set of named or unnamed generators.

Value

A quickcheck_generator object.

Examples

list_(integer_(), logical_()) %>% show_example()
list_(a = any_vector(), b = any_vector()) %>% show_example()

Variable length list generator

Description

Generate lists with all values coming from a single generator.

Usage

list_of(generator, len = c(1L, 10L))

Arguments

generator

A quickcheck_generator object.
len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

list_of(integer_(), len = 10L) %>% show_example()

Logical generator

Description

A generator for logical vectors.

Usage

logical_(len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.

Value

A quickcheck_generator object.

Examples

logical_() %>% show_example()
logical_(len = 10L, any_na = TRUE) %>% show_example()

Numeric generators

Description

A set of generators for numeric vectors. Numeric vectors can be either integer or double vectors.

Usage

numeric_(len = c(1L, 10L), any_na = FALSE, big_num = FALSE)

numeric_bounded(left, right, len = c(1L, 10L), any_na = FALSE)

numeric_left_bounded(left, len = c(1L, 10L), any_na = FALSE, big_num = FALSE)

numeric_right_bounded(right, len = c(1L, 10L), any_na = FALSE, big_num = FALSE)

numeric_positive(len = c(1L, 10L), any_na = FALSE, big_num = FALSE)

numeric_negative(len = c(1L, 10L), any_na = FALSE, big_num = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
big_num

Should integers or doubles near the maximum size be included? This may cause problems because if the result of a computation results in a number larger than the maximum an integer will be silently coerced to a double and a double will return Inf.
left

The minimum possible value for generated numbers, inclusive.
right

The maximum possible value for generated numbers, inclusive.

Value

A quickcheck_generator object.

Examples

numeric_() %>% show_example()
numeric_(big_num = TRUE) %>% show_example()
numeric_bounded(left = -5L, right = 5L) %>% show_example()
numeric_(len = 10L, any_na = TRUE) %>% show_example()

Randomly choose between generators

Description

Randomly choose between generators

Usage

one_of(..., prob = NULL)

Arguments

...

A set of unnamed generators.
prob

A vector of probability weights for obtaining the elements of the vector being sampled.

Value

A quickcheck_generator object.

Examples

one_of(integer_(), character_()) %>% show_example()
one_of(constant(NULL), logical_(), prob = c(0.1, 0.9)) %>% show_example()

POSIXct generators

Description

A set of generators for POSIXct vectors.

Usage

posixct_(len = c(1L, 10L), any_na = FALSE)

posixct_bounded(left, right, len = c(1L, 10L), any_na = FALSE)

posixct_left_bounded(left, len = c(1L, 10L), any_na = FALSE)

posixct_right_bounded(right, len = c(1L, 10L), any_na = FALSE)

Arguments

len

Length of the generated vectors. If len is a single number all vectors will have this length. If len is a numeric vector of length 2 it will produce vectors with lengths between a minimum and maximum, inclusive. For example len = c(1L, 10L) would produce vectors with lengths between 1 and 10. To produce empty vectors set len = 0L or a range like len = c(0L, 10L).
any_na

Whether NA values should be allowed.
left

The minimum possible value for generated numbers, inclusive.
right

The maximum possible value for generated numbers, inclusive.

Value

A quickcheck_generator object.

Examples

posixct_() %>% show_example()
posixct_bounded(
  left = as.POSIXct("2020-01-01 00:00:00"),
  right = as.POSIXct("2021-01-01 00:00:00")
) %>% show_example()
posixct_(len = 10L, any_na = TRUE) %>% show_example()

Repeatedly test properties of a function

Description

Repeatedly test properties of a function

Usage

repeat_test(property, tests = getOption("quickcheck.tests", 100L))

Arguments

property

A function with no parameters which includes an expectation.
tests

The number of tests to run.

Value

A testthat expectation object.

Examples

repeat_test(
  property = function() {
    num <- stats::runif(1, min = 0, max = 10)
    testthat::expect_true(num >= 0 && num <= 10)
  }
)

Show an example output of a generator

Description

Show an example output of a generator

Usage

show_example(generator)

Arguments

generator

A quickcheck_generator object.

Value

An example output produced by the generator.

Examples

logical_() %>% show_example()

Tibble generators

Description

Construct tibble generators in a similar way to tibble::tibble.

Usage

tibble_(..., rows = c(1L, 10L))

Arguments

...

A set of name-value pairs with the values being vector generators.
rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

tibble_(a = integer_()) %>% show_example()
tibble_(a = integer_(), b = character_(), rows = 5L) %>% show_example()

Random tibble generator

Description

Random tibble generator

Usage

tibble_of(..., rows = c(1L, 10L), cols = c(1L, 10L))

Arguments

...

A set of unnamed generators. The generated tibbles will be built with random combinations of these generators.
rows

Number of rows of the generated data frame. If rows is a single number all data frames will have this number of rows. If rows is a numeric vector of length 2 it will produce data frames with rows between a minimum and maximum, inclusive. For example rows = c(1L, 10L) would produce data frames with rows between 1 and 10. To produce empty tibbles set rows = 0L or a range like rows = c(0L, 10L).
cols

Number of columns of the generated data frame. If cols is a single number all data frames will have this number of columns. If cols is a numeric vector of length 2 it will produce data frames with columns between a minimum and maximum, inclusive. For example cols = c(1L, 10L) would produce data frames with columns between 1 and 10. To produce empty tibbles set cols = 0L or a range like cols = c(0L, 10L).

Value

A quickcheck_generator object.

Examples

tibble_of(logical_(), date_()) %>% show_example()
tibble_of(any_atomic(), rows = 10L, cols = 5L) %>% show_example()