The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Type hints are special comments with a leading #| within
a function body indicating the intended nature of the function’s
arguments in terms of data types, dimensions and even permitted values.
The actual parameters with which the function is called can be evaluated
against these type hint comments using the check_types()
function.
check_types() returns `FALSE if any of the checks fails.
Checking can be aborted after the first error occurs, or it can be
continued until all checks have been performed. Optionally, the user is
shown a message indicating the nature of the problem with the function
arguments. The messages can be completely customized using placerholder
variables for all kinds of relevant information.
Type hint comments always need to be placed inside a
function body and refer to the arguments of that function. They can be
placed anywhere in the function body (even after the call of
check_types(). Type hint comments are regular R comments
but start with #| (hash plus pipe, without blanks in
between). Each function argument will have its own type hint comment
line. Type hint comments can cover a subset of all arguments, so there
can be arguments without any type hint restrictions.
Type hint comments consist of a data type check and (optionally) dimension and value checks:
Data type check: The data type checks for the
data type of the argument. At this point, the data type check needs to
be the first check in a type hint comment and can only comprise one
permitted data type. The syntax is argument_name data_type.
A valid type hint comment consisting only of a data type check could
thus look like this: #| degrees_celsius numeric.
Dimension check: The dimension check checks for
the number and size of the dimensions of the argument. It is constructed
using the dim() function. dim() takes one
parameter per dimension of the argument. The parameters specify the size
of each of the dimensions of the argument either as specific values or
as comparisons. So, the general syntax is:
dim([comparison_operator]dimsize [,[comparison_operator] dim_size]*).
For example, if the argument (called unemployment) is
required to be a dataframe with exactly four columns and at least two
rows then the type hint comment would look like this:
#| unemployment data.frame dim(>=2, 4). When
check_types() evaluates the parameters supplied in the
function call it looks for the number of dimensions of the parameter as
well as the size of each dimension.
Value check: The value check evaluates the
actual value of the parameter supplied in the function call and rejects
the value if it is on an exclude list. Such exclude lists are
constructed using the not() function. The
not() function expects as its arguments the values that
shall not be permitted as parameter values. These values can include
NA and NULL. The general syntax of the
not() function is:
not(excludevalue[,excludevalue]*). If we had an argument
called surname and this argument must not be
NA or "" (empty character) then the required
type hint check would like this:
#| surname character not("", NA). There can be multiple
not-lists in each type hint comment. If the parameter
supplied in the function call consists of, by its nature, multiple
elements, like it is the case with dataframes, list, and matrices, then
the value check fails if any element of the parameter provided
in the function call is on the exclude list.
When formulating dim or not restrictions
you can use the values of other parameters of the function call. So, if
you have a function with two arguments, a number of children
(num.children) and a numeric vector with the ages of these
children
(age.children) you can have a type hint comment for the latter which looks like this:#|
age.children numeric dim(num.children)`.
If any of the checks fails check_types() returns
FALSE, otherwise it returns TRUE. If
show.msg=TRUE then a message will be shown in the R
console. The messages can be customized using templates (see next
section). Depending on the value of abort the checking of
parameters is continued (abort=FALSE) or stopped
immediately (abort=TRUE), i.e. no further checks are
performed after the first error.
The error messages that are shown (if show.msg=TRUE)
when a check fails are based on templates. The templates are provided to
the check_types() function via the messages
argument. messages is a character vector with five
elements, one for each possible kind of error message (or
NULL, if the default error #’ messages shall be used); the
types of error messages are:
General intro message (default:
"Problem in function '#fun()'")
Wrong parameter type (default:
"Argument '#arg' (#argval) is of class #type_is but needs to be of class #type_req.")
Wrong dimension size of parameter (default:
"Size of dimension #dimno of argument '#arg' must be #dimcomp#dim_req, but is actually #dim_is.")
Wrong number of dimensions of parameter (default:
"Number of dimensions of argument '#arg' must be #dimcnt_req but is actually #dimcnt_is.")
Parameter value is not permitted (default:
"#argval is not a valid value for argument #arg.")
The messages provided via the messages argument are
templates that can use predefined placeholders to convey information
relevant for understanding the problem.
#fun: The name of the function of which the parameter
values are to be checked (i.e. the function check_types()
is applied to)
#arg: The name of the argument
#argval: The value of the parameter used in the function call
#type_req: The required type for the argument
#type_is: The actual type of the parameter used in the function call
#dimcnt_req: The required number of dimensions of the argument
#dimcnt_is: The actual number of dimensions of the parameter used in the function call
#dim_req: The required size of the dimension where a dimension size error occurred
#dim_is: The actual size of the dimension where a dimension size error occurred
#dimcomp: The comparison operator used in combination
with #dim_req, the required size of the dimension (e.g. the
>= in >=2, if this dimension of the
argument is to be greater than 1)
#dimno: The index of the dimension where a dimension size error occurred
library(typehint)
celsius_to_fahrenheit <- function(degrees_celsius) {
#| degrees_celsius numeric dim(1) not(NA, NULL)
if(check_types()) return(degrees_celsius * 9/5 + 32)
else return(NA)
}
res <- celsius_to_fahrenheit("100.0")Joachim Zuckarelli
Twitter: [@jsugarelli](https://twitter.com/jsugarelli)
GitHub: https://github.com/jsugarelli/typehint
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.