packages_installed <- function(pkg_list){
        pkgs <- unlist(pkg_list)
        req <- unlist(lapply(pkgs, require, character.only = TRUE))
        not_installed <- pkgs[req == FALSE]
        lapply(not_installed, install.packages, 
               repos = "http://cran.r-project.org")# add lib.loc if needed
        lapply(pkgs, library, character.only = TRUE)
}

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/

我已经实现了无声安装和加载所需R包的功能。希望也许会有所帮助。代码如下:

# Function to Install and Load R Packages
Install_And_Load <- function(Required_Packages)
{
    Remaining_Packages <- Required_Packages[!(Required_Packages %in% installed.packages()[,"Package"])];

    if(length(Remaining_Packages)) 
    {
        install.packages(Remaining_Packages);
    }
    for(package_name in Required_Packages)
    {
        library(package_name,character.only=TRUE,quietly=TRUE);
    }
}

# Specify the list of required packages to be installed and load    
Required_Packages=c("ggplot2", "Rcpp");

# Call the Function
Install_And_Load(Required_Packages);

是的。如果您有软件包列表，请将其与installed.packages()[，"Package"]的输出进行比较，然后安装缺少的软件包。就像这样:

list.of.packages <- c("ggplot2", "Rcpp")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)

否则:

如果您将代码放在包中并使它们成为依赖项，那么当您安装包时，它们将自动安装。

确定。

您需要比较“已安装的包”和“所需的包”。这非常接近于我用蔓越莓做的事情，因为我需要比较“存储的已知包”和“当前已知的包”，以确定新的和/或更新的包。

就像这样

AP <- available.packages(contrib.url(repos[i,"url"]))   # available t repos[i]

为了获得所有已知的包，模拟调用当前安装的包，并将其与给定的目标包集进行比较。

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)