There's not much of one in everyday work.

However, according to the documentation for both functions (accessed by putting a ? before the function name and hitting enter), require is used inside functions, as it outputs a warning and continues if the package is not found, whereas library will throw an error.

Another benefit of require() is that it returns a logical value by default. TRUE if the packages is loaded, FALSE if it isn't.

> test <- library("abc")
Error in library("abc") : there is no package called 'abc'
> test
Error: object 'test' not found
> test <- require("abc")
Loading required package: abc
Warning message:
In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called 'abc'
> test
[1] FALSE

So you can use require() in constructions like the one below. Which mainly handy if you want to distribute your code to our R installation were packages might not be installed.

if(require("lme4")){
    print("lme4 is loaded correctly")
} else {
    print("trying to install lme4")
    install.packages("lme4")
    if(require(lme4)){
        print("lme4 installed and loaded")
    } else {
        stop("could not install lme4")
    }
}

Always use library. Never use require.

tl;dr: require breaks one of the fundamental rules of robust software systems: fail early.

In a nutshell, this is because, when using require, your code might yield different, erroneous results, without signalling an error. This is rare but not hypothetical! Consider this code, which yields different results depending on whether {dplyr} can be loaded:

require(dplyr)

x = data.frame(y = seq(100))
y = 1
filter(x, y == 1)

This can lead to subtly wrong results. Using library instead of require throws an error here, signalling clearly that something is wrong. This is good.

It also makes debugging all other failures more difficult: If you require a package at the start of your script and use its exports in line 500, you’ll get an error message “object ‘foo’ not found” in line 500, rather than an error “there is no package called ‘bla’”.

The only acceptable use case of require is when its return value is immediately checked, as some of the other answers show. This is a fairly common pattern but even in these cases it is better (and recommended, see below) to instead separate the existence check and the loading of the package. That is: use requireNamespace instead of require in these cases.

More technically, require actually calls library internally (if the package wasn’t already attached — require thus performs a redundant check, because library also checks whether the package was already loaded). Here’s a simplified implementation of require to illustrate what it does:

require = function (package) {
    already_attached = paste('package:', package) %in% search()
    if (already_attached) return(TRUE)
    maybe_error = try(library(package, character.only = TRUE)) 
    success = ! inherits(maybe_error, 'try-error')
    if (! success) cat("Failed")
    success
}

Experienced R developers agree:

Yihui Xie, author of {knitr}, {bookdown} and many other packages says:

Ladies and gentlemen, I've said this before: require() is the wrong way to load an R package; use library() instead

Hadley Wickham, author of more popular R packages than anybody else, says

Use library(x) in data analysis scripts. […] You never need to use require() (requireNamespace() is almost always better)

You can use require() if you want to install packages if and only if necessary, such as:

if (!require(package, character.only=T, quietly=T)) {
    install.packages(package)
    library(package, character.only=T)
}

For multiple packages you can use

for (package in c('<package1>', '<package2>')) {
    if (!require(package, character.only=T, quietly=T)) {
        install.packages(package)
        library(package, character.only=T)
    }
}

Pro tips:

• When used inside the script, you can avoid a dialog screen by specifying the repos parameter of install.packages(), such as

  install.packages(package, repos="http://cran.us.r-project.org")
  

• You can wrap require() and library() in suppressPackageStartupMessages() to, well, suppress package startup messages, and also use the parameters require(..., quietly=T, warn.conflicts=F) if needed to keep the installs quiet.

?library

and you will see:

library(package) and require(package) both load the package with name package and put it on the search list. require is designed for use inside other functions; it returns FALSE and gives a warning (rather than an error as library() does by default) if the package does not exist. Both functions check and update the list of currently loaded packages and do not reload a package which is already loaded. (If you want to reload such a package, call detach(unload = TRUE) or unloadNamespace first.) If you want to load a package without putting it on the search list, use requireNamespace.

My initial theory about the difference was that library loads the packages whether it is already loaded or not, i.e. it might reload an already loaded package, while require just checks that it is loaded, or loads it if it isn't (thus the use in functions that rely on a certain package). The documentation refutes this, however, and explicitly states that neither function will reload an already loaded package.

Here seems to be the difference on an already loaded package. While it is true that both require and library do not load the package. Library does a lot of other things before it checks and exits.

I would recommend removing "require" from the beginning of a function running 2mil times anyway, but if, for some reason I needed to keep it. require is technically a faster check.

microbenchmark(req = require(microbenchmark), lib = library(microbenchmark),times = 100000)
Unit: microseconds
 expr    min     lq      mean median     uq        max neval
  req  3.676  5.181  6.596968  5.655  6.177   9456.006 1e+05
  lib 17.192 19.887 27.302907 20.852 22.490 255665.881 1e+05