Raises error if predicate is FALSE in any columns selected

Meant for use in a data analysis pipeline, this function will just return the data it's supplied if there are no FALSEs when the predicate is applied to every element of the columns indicated. If any element in any of the columns, when applied to the predicate, is FALSE, then this function will raise an error, effectively terminating the pipeline early.

Usage

assert(
  data,
  predicate,
  ...,
  success_fun = success_continue,
  error_fun = error_stop,
  skip_chain_opts = FALSE,
  obligatory = FALSE,
  defect_fun = defect_append,
  description = NA
)

Arguments

data

A data frame

predicate

A function that returns FALSE when violated

...

Comma separated list of unquoted expressions. Uses dplyr's select to select columns from data.

success_fun

Function to call if assertion passes. Defaults to returning data.

error_fun

Function to call if assertion fails. Defaults to printing a summary of all errors.

skip_chain_opts

If TRUE, success_fun and error_fun are used even if assertion is called within a chain.

obligatory

If TRUE and assertion failed the data is marked as defective. For defective data, all the following rules are handled by defect_fun function.

defect_fun

Function to call when data is defective. Defaults to skipping assertion and storing info about it in special attribute.

description

Custom description of the rule. Is stored in result reports and data.

Value

By default, the data is returned if predicate assertion is TRUE and and error is thrown if not. If a non-default

success_fun or error_fun is used, the return values of these function will be returned.

Details

For examples of possible choices for the success_fun and error_fun parameters, run help("success_and_error_functions")

Note

See vignette("assertr") for how to use this in context

See also

verify insist assert_rows insist_rows

Examples