最近我似乎和合作者分享了很多代码。他们中的许多人是新手/中级R用户,并没有意识到他们必须安装他们还没有的包。
是否有一种优雅的方式来调用installed.packages(),比较那些我正在加载和安装如果丢失?
最近我似乎和合作者分享了很多代码。他们中的许多人是新手/中级R用户,并没有意识到他们必须安装他们还没有的包。
是否有一种优雅的方式来调用installed.packages(),比较那些我正在加载和安装如果丢失?
当前回答
今天,我偶然发现了rlang包提供的两个方便函数,即is_installed()和check_installed()。
从帮助页面(强调添加):
These functions check that packages are installed with minimal side effects. If installed, the packages will be loaded but not attached. is_installed() doesn't interact with the user. It simply returns TRUE or FALSE depending on whether the packages are installed. In interactive sessions, check_installed() asks the user whether to install missing packages. If the user accepts, the packages are installed [...]. If the session is non interactive or if the user chooses not to install the packages, the current evaluation is aborted.
interactive()
#> [1] FALSE
rlang::is_installed(c("dplyr"))
#> [1] TRUE
rlang::is_installed(c("foobarbaz"))
#> [1] FALSE
rlang::check_installed(c("dplyr"))
rlang::check_installed(c("foobarbaz"))
#> Error:
#> ! The package `foobarbaz` is required.
由reprex包在2022-03-25创建(v2.0.1)
其他回答
让我分享一点疯狂:
c("ggplot2","ggsci", "hrbrthemes", "gghighlight", "dplyr") %>% # What will you need to load for this script?
(function (x) ifelse(t =!(x %in% installed.packages()),
install.packages(x[t]),
lapply(x, require)))
非常基本的一个。
pkgs = c("pacman","data.table")
if(length(new.pkgs <- setdiff(pkgs, rownames(installed.packages())))) install.packages(new.pkgs)
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/
source("https://bioconductor.org/biocLite.R")
if (!require("ggsci")) biocLite("ggsci")