Dispatch to a named function based on the characteristics of a dataframe

This provides a dataframe analogy to S3 dispatch. If multiple possible dataframe formats are possible for a function, each with different processing requirements, then the choice of function can be made based on matching the input dataframe to a set of iface specifications. The first matching iface specification determines which function is used for dispatch.

Usage

idispatch(x, ..., .default = NULL)

Arguments

x

a dataframe

...

a set of function name=interfacer::iface pairs

.default

a function to apply in the situation where none of the rules can be matched. The default results in an error being thrown.

Value

the result of dispatching the dataframe to the first function that matches the rules in .... Matching is permissive in that the test is passed if a dataframe can be coerced to the iface specified format.

Examples

i1 = iface( col1 = integer ~ "An integer column" )
i2 = iface( col2 = integer ~ "A different integer column" )

# this is an example function that would typically be inside a package, and
# is exported from the package.
extract_mean = function(df, ...) {
  idispatch(df,
    extract_mean.i1 = i1,
    extract_mean.i2 = i2
  )
}

# this is expected to be an internal package function
# the naming convention here is based on S3 but it is not required
extract_mean.i1 = function(df = i1, ...) {
  message("using i1")
  # input validation is not required in functions that are being called using
  # `idispatch` as the validation occurs during dispatch. 
  mean(df$col1)
}

extract_mean.i2 = function(df = i2, uplift = 1, ...) {
  message("using i2")
  mean(df$col2)+uplift
}

# this input matches `i1` and the `extract_mean` call is dispatched 
# via `extract_mean.i1`
test = tibble::tibble( col2 = 1:10 )
extract_mean(test, uplift = 50)
#> using i2
#> [1] 55.5

# this input matches `i2` and the `extract_mean` call is dispatched 
# via `extract_mean.i2`
test2 = tibble::tibble( col1 = 1:10 )
extract_mean(test2, uplift = 50)
#> using i1
#> [1] 5.5

# This input does not match any of the allowable input specifications and 
# generates an error.
test3 = tibble::tibble( wrong_col = 1:10 )
try(extract_mean(test3, uplift = 50))
#> Error : the parameter in extract_mean(...) does not match any of the expected formats.
#> extract_mean.i1 - Error : missing columns: col1
#> extract_mean.i2 - Error : missing columns: col2
#>