success_and_error_functions: Success and error functions
In ropensci/assertr: Assertive Programming for R Analysis Pipelines

success_and_error_functions

R Documentation

Success and error functions

Description

The behavior of functions like assert, assert_rows, insist, insist_rows, verify when the assertion passes or fails is configurable via the success_fun and error_fun parameters, respectively. The success_fun parameter takes a function that takes the data passed to the assertion function as a parameter. You can write your own success handler function, but there are a few provided by this package:

success_continue - just returns the data that was passed into the assertion function
success_logical - returns TRUE
success_append - returns the data that was passed into the assertion function but also stores basic information about verification result
success_report - When success results are stored, and each verification ended up with success prints summary of all successful validations
success_df_return - When success results are stored, and each verification ended up with success prints data.frame with verification results

The error_fun parameter takes a function that takes the data passed to the assertion function as a parameter. You can write your own error handler function, but there are a few provided by this package:

error_stop - Prints a summary of the errors and halts execution.
error_report - Prints all the information available about the errors in a "tidy" data.frame (including information such as the name of the predicate used, the offending value, etc...) and halts execution.
error_append - Attaches the errors to a special attribute of data and returns the data. This is chiefly to allow assertr errors to be accumulated in a pipeline so that all assertions can have a chance to be checked and so that all the errors can be displayed at the end of the chain.
error_return - Returns the raw object containing all the errors
error_df_return - Returns a "tidy" data.frame containing all the errors, including informations such as the name of the predicate used, the offending value, etc...
error_logical - returns FALSE
just_warn - Prints a summary of the errors but does not halt execution, it just issues a warning.
warn_report - Prints all the information available about the errors but does not halt execution, it just issues a warning.
defect_report - For single rule and defective data it displays short info about skipping current assertion. For chain_end sums up all skipped rules for defective data.
defect_df_return - For single rule and defective data it returns info data.frame about skipping current assertion. For chain_end returns all skipped rules info data.frame for defective data.

You may find the third type of data verification result. In a scenario when validation rule was obligatory (obligatory = TRUE) in order to execute the following ones we may want to skip them and register that fact. In order to do this there are three callbacks reacting to defective data:

defect_report - For single rule and defective data it displays short info about skipping current assertion.
defect_df_return - For single rule and defective data it returns info data.frame about skipping current assertion.
defect_append - Appends info about skipped rule due to data defect into one of data attributes. Rules skipped on defective data, or its summary, can be returned with proper error_fun callback in chain_end.

Usage

success_logical(data, ...)

success_continue(data, ...)

success_append(data, ...)

success_report(data, ...)

success_df_return(data, ...)

error_stop(errors, data = NULL, warn = FALSE, ...)

just_warn(errors, data = NULL)

error_report(errors, data = NULL, warn = FALSE, ...)

warn_report(errors, data = NULL)

error_append(errors, data = NULL)

warning_append(errors, data = NULL)

error_return(errors, data = NULL)

error_df_return(errors, data = NULL)

error_logical(errors, data = NULL, ...)

defect_append(errors, data, ...)

defect_report(errors, data, ...)

defect_df_return(errors, data, ...)

Arguments

`data`	A data frame
`...`	Further arguments passed to or from other methods
`errors`	A list of objects of class `assertr_errors`
`warn`	If TRUE, assertr will issue a warning instead of an error