README.md
In needy: needy

needy

needy is a small utility library designed to make testing function inputs less difficult. R is a dynamically typed language, but larger projects need input checking for scalabity.

needy offers a single function, require_a( ), which lets you specify the traits an input object should have, such as class, size, numerical properties or number of parameters, while reducing boilerplate code and aiding debugging.

A typical example where needy is useful is when trying to safeguard against invalid inputs when defining a function, by defining what types of inputs it is well defined for.

IndMap maps a two-parameter function across a list x and x's indices 1, 2, ..., n. It is only well defined if f is a binary (or variadic) function, and x is a list, a vector, or a pairlist. [1]

safeIndMap <- function (f, x) {

    pcall <- sys.call()
    require_a("binary function", f, pcall)
    require_a(c("vector", "pairlist"), x)
    Map(f, x, seq_along(x))
}

If safeIndMap is now called with a three-variable function, a descriptive error is thrown showing the three-variable function. This error says that it was triggered by the fact that f wasn't a binary function, which is a pretty clear error message.

safeIndMap( function (a, b, c) a+b+c, 1:10 )

Error: safeIndMap(function(a, b, c) a + b + c, 1:10): 
    the value function (a, b, c) a + b + c didn't match any of the following compound traits:
    binary and function

We can be fairly confident now that if the user passes incorrect input to safeIndMap they should be able to figure out what went wrong quickly.

For a full list of implemented traits, use the aptly named implemented_traits(). As of version 0.1.1, the following traits are implemented.

currently implemented traits:
 any, array, atomic, binary, boolean, call, character, closure, complex, data.frame, double, environment, expression, factor, false, finite, function, functionable, infinite, integer, language, length_one, length_three, length_two, length_zero, list, listy, logical, matrix, na, name, named, nan, nonnegative, null, nullary, numeric, object, pairlist, positive, primitive, raw, recursive, s4, string, symbol, table, ternary, true, unary, variadic, vector, whole

See the R documentation ?require_a for more detailed usage information.

Sometimes is it more convenient to give a trait a value cannot have. For this reason (as of version 0.2) traits can be negated.

safeNotNull <- function (x) {

    pcall <-sys.call()
    require_a("!null", x, pcall)
    X
}

For a full list of implemented traits, use the aptly named implemented_traits(). See the R documentation ?require_a for more detailed usage information.

I wrote needy because it fits a use case I have very tidely; I have two large libraries (mchof and arrow, for those who are interested), and I needed a way of reducing the amount of ``if (is.function(f)) stop() boilerplate code, and of standardising error messages. Needy ticks both boxes. Over times I will improve this library substantially, but if this library doesn't fit your needs at the moment I recommend:

Assertive is currently the more mature of the two libraries, and falls more into the category of data validation (checking if data are email addresses, hex colours, ...). Assertthat seems to be more general, but it isn't available on CRAN currently (July 5th 2013).

The MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

[1] yes, pairlists aren't really used in R, but we might as well make our code as general as possible. The 'listy' trait is a shorthand for c("vector", "pairlist").