if (!require('ggplot2')) install.packages('ggplot2'); library('ggplot2')

“ggplot2”是包。它检查包是否安装，如果没有安装，就安装它。然后不管它采用哪个分支，它都会加载包。

我使用以下将检查包是否安装和依赖项是否更新，然后加载包。

p<-c('ggplot2','Rcpp')
install_package<-function(pack)
{if(!(pack %in% row.names(installed.packages())))
{
  update.packages(ask=F)
  install.packages(pack,dependencies=T)
}
 require(pack,character.only=TRUE)
}
for(pack in p) {install_package(pack)}

completeFun <- function(data, desiredCols) {
  completeVec <- complete.cases(data[, desiredCols])
  return(data[completeVec, ])
}

使用lapply族和匿名函数方法，您可以:

尝试附加所有列出的包。 仅安装缺失(使用||惰性计算)。 尝试再次连接那些在第1步中丢失并在第2步中安装的组件。 打印每个包的最终加载状态(TRUE / FALSE)。 Req <- substitute(require(x, character。only = TRUE)) LBS <- c("plyr"， "psych"， "tm") Sapply (lbs, function(x) eval(req) || {install.packages(x);eval(点播)}) 心理学 真真真真

你可以使用require的返回值:

if(!require(somepackage)){
    install.packages("somepackage")
    library(somepackage)
}

我在安装后使用library，因为如果安装不成功或由于其他原因无法加载包，它将抛出异常。您可以使其更加健壮和可重用:

dynamic_require <- function(package){
  if(eval(parse(text=paste("require(",package,")")))) return(TRUE)
  
  install.packages(package)
  return(eval(parse(text=paste("require(",package,")"))))
}

此方法的缺点是必须以引号传递包名，而对于真正的require则不这样做。

达森·k和我有一个吃豆人包可以很好地做到这一点。包中的p_load函数执行此操作。第一行代码只是为了确保安装了pacman。

if (!require("pacman")) install.packages("pacman")
pacman::p_load(package1, package2, package_n)

使用packrat使共享库完全相同，而不会改变其他环境。

就优雅和最佳实践而言，我认为你从根本上走错了方向。打包程序就是为这些问题而设计的。它是由RStudio由Hadley Wickham开发的。packrat使用自己的目录，将您的程序的所有依赖项安装在其中，而不涉及别人的环境，这样他们就不必安装依赖项并可能弄乱别人的环境系统。

Packrat is a dependency management system for R. R package dependencies can be frustrating. Have you ever had to use trial-and-error to figure out what R packages you need to install to make someone else’s code work–and then been left with those packages globally installed forever, because now you’re not sure whether you need them? Have you ever updated a package to get code in one of your projects to work, only to find that the updated package makes code in another project stop working? We built packrat to solve these problems. Use packrat to make your R projects more: Isolated: Installing a new or updated package for one project won’t break your other projects, and vice versa. That’s because packrat gives each project its own private package library. Portable: Easily transport your projects from one computer to another, even across different platforms. Packrat makes it easy to install the packages your project depends on. Reproducible: Packrat records the exact package versions you depend on, and ensures those exact versions are the ones that get installed wherever you go.

https://rstudio.github.io/packrat/