r - 离线安装包列表: getting dependencies in order

Question

我已经获得了一堆软件包及其依赖项的源文件，我想将它们安装在无法访问互联网的计算机上。我想使用 USB 内存棒将所有这些安装在其他计算机上，但某些软件包的安装失败，因为依赖项没有在软件包之前安装。如何在需要它们的包之前按顺序安装依赖项？

这是我当前获取包及其依赖项并按正确顺序获取它们的方法:

# find the dependencies for the packages I want
# from http://stackoverflow.com/a/15650828/1036500
getPackages <- function(packs){
  packages <- unlist(
    tools::package_dependencies(packs, available.packages(),
                                which=c("Depends", "Imports"), recursive=TRUE)
  )
  packages <- union(packages, packs)
  packages
}

# packages I want 
my_packages <- c('stringr', 'devtools', 'ggplot2', 'dplyr', 'tidyr', 'rmarkdown', 'knitr', 'reshape2', 'gdata')

# get names of dependencies and try to get them in the right order, this seems ridiculous... 
my_packages_and_dependencies <- getPackages(my_packages)
dependencies_only <- setdiff(my_packages_and_dependencies, my_packages)
deps_of_deps <- getPackages(dependencies_only)
deps_of_deps_of_deps <- getPackages(deps_of_deps)
my_packages_and_dependencies <- unique(c(deps_of_deps_of_deps, deps_of_deps, dependencies_only, my_packages))

# where to keep the source?
local_CRAN <- paste0(getwd(), "/local_CRAN")

# get them from CRAN, source files
download.packages(pkgs = my_packages_and_dependencies, destdir = local_CRAN, type = "source")
# note that 'tools', 'methods', 'utils, 'stats', etc. art not on CRAN, but are part of base

# from http://stackoverflow.com/a/10841614/1036500
library(tools)
write_PACKAGES(local_CRAN)

现在假设我在另一台计算机上全新安装了 R 和 RStudio(以及 Rtools 或 Xcode)并且没有互联网连接，我插入 USB 内存棒，打开 RProj 文件以设置工作目录，然后运行此命令脚本:

#############################################################

## Install from source (Windows/OSX/Linux)

# What do I want to install?
my_packages_and_dependencies <- c("methods", "tools", "bitops", "stats", "colorspace", "graphics", 
                                  "tcltk", "Rcpp", "digest", "jsonlite", "mime", "RCurl", "R6", 
                                  "stringr", "brew", "grid", "RColorBrewer", "dichromat", "munsell", 
                                  "plyr", "labeling", "grDevices", "utils", "httr", "memoise", 
                                  "whisker", "evaluate", "rstudioapi", "roxygen2", "gtable", "scales", 
                                  "proto", "MASS", "assertthat", "magrittr", "lazyeval", "DBI", 
                                  "stringi", "yaml", "htmltools", "caTools", "formatR", "highr", 
                                  "markdown", "gtools", "devtools", "ggplot2", "dplyr", "tidyr", 
                                  "rmarkdown", "knitr", "reshape2", "gdata")

# where are the source files? 
local_CRAN <- paste0(getwd(), "/local_CRAN")

# scan all packages and get files names of wanted source pckgs
# I've got other things in this dir also
wanted_package_source_filenames <- list.files(local_CRAN, pattern = "tar.gz", full.names = TRUE)

# put them in order to make sure deps go first, room for improvement here...
trims <- c(local_CRAN, "/",  "tar.gz")
x1 <- gsub(paste(trims, collapse = "|"), "", wanted_package_source_filenames)
x2 <- sapply( strsplit(x1, "_"), "[[", 1)
idx <- match(my_packages_and_dependencies, x2)
wanted_package_source_filenames <- na.omit(wanted_package_source_filenames[idx])

install.packages(wanted_package_source_filenames, 
                 repos = NULL, 
                 dependencies = TRUE, 
                 contrib.url = local_CRAN, # I thought this would take care of getting dependencies automatically...
                 type  = "source" )

这工作得相当好，但仍然有一些软件包无法安装:

sapply(my_packages_and_dependencies, require, character.only = TRUE) 

 methods        tools       bitops        stats 
        TRUE         TRUE         TRUE         TRUE 
  colorspace     graphics        tcltk         Rcpp 
        TRUE         TRUE         TRUE         TRUE 
      digest     jsonlite         mime        RCurl 
        TRUE         TRUE         TRUE        FALSE 
          R6      stringr         brew         grid 
        TRUE         TRUE         TRUE         TRUE 
RColorBrewer    dichromat      munsell         plyr 
        TRUE         TRUE         TRUE         TRUE 
    labeling    grDevices        utils         httr 
        TRUE         TRUE         TRUE        FALSE 
     memoise      whisker     evaluate   rstudioapi 
        TRUE         TRUE         TRUE         TRUE 
    roxygen2       gtable       scales        proto 
        TRUE         TRUE         TRUE         TRUE 
        MASS   assertthat     magrittr     lazyeval 
        TRUE         TRUE         TRUE         TRUE 
         DBI      stringi         yaml    htmltools 
        TRUE         TRUE         TRUE         TRUE 
     caTools      formatR        highr     markdown 
        TRUE         TRUE         TRUE         TRUE 
      gtools     devtools      ggplot2        dplyr 
        TRUE        FALSE        FALSE         TRUE 
       tidyr    rmarkdown        knitr     reshape2 
       FALSE        FALSE         TRUE         TRUE 
       gdata 
        TRUE 
Warning messages:
1: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘RCurl’
2: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘httr’
3: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘devtools’
4: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘ggplot2’
5: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘tidyr’
6: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘rmarkdown’

似乎 knitr 必须出现在 rmarkdown 之前，reshape2 必须出现在 tidyr 和 ggplot2 之前，等等。

必须有一个更简单、更完整的解决方案来解决按非常特定的顺序获取源文件列表的问题，并将所有依赖项按正确的顺序放置。最简单的方法是什么(不使用任何贡献的包)？

这是我当前正在使用的系统，我正在使用软件包的源版本，试图为离线计算机(OSX/Linux/Windows)做好准备:

> sessionInfo()
R version 3.1.2 (2014-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
 [1] tcltk     grid      tools     stats     graphics 
 [6] grDevices utils     datasets  methods   base     

other attached packages:
 [1] gdata_2.13.3       reshape2_1.4.1    
 [3] knitr_1.9          dplyr_0.4.1       
 [5] gtools_3.4.1       markdown_0.7.4    
 [7] highr_0.4          formatR_1.0       
 [9] caTools_1.17.1     htmltools_0.2.6   
[11] yaml_2.1.13        stringi_0.4-1     
[13] DBI_0.3.1          lazyeval_0.1.10   
[15] magrittr_1.5       assertthat_0.1    
[17] proto_0.3-10       scales_0.2.4      
[19] gtable_0.1.2       roxygen2_4.1.0    
[21] rstudioapi_0.2     evaluate_0.5.5    
[23] whisker_0.3-2      memoise_0.2.1     
[25] labeling_0.3       plyr_1.8.1        
[27] munsell_0.4.2      dichromat_2.0-0   
[29] RColorBrewer_1.1-2 brew_1.0-6        
[31] stringr_0.6.2      R6_2.0.1          
[33] mime_0.2           jsonlite_0.9.14   
[35] digest_0.6.8       Rcpp_0.11.4       
[37] colorspace_1.2-5   bitops_1.0-6      
[39] MASS_7.3-35       

loaded via a namespace (and not attached):
[1] parallel_3.1.2

编辑按照Andrie的有用评论，我尝试了miniCRAN，小插图中缺少的一点是如何实际从本地存储库安装软件包。这是我尝试过的:

library("miniCRAN")

# Specify list of packages to download
pkgs <- c('stringr', 'devtools', 'ggplot2', 'dplyr', 'tidyr', 'rmarkdown', 'knitr', 'reshape2', 'gdata')

# Make list of package URLs
revolution <- c(CRAN="http://cran.revolutionanalytics.com")
pkgList <- pkgDep(pkgs, repos=revolution, type="source" )
pkgList

# Set location to store source files 
local_CRAN <- paste0(getwd(), "/local_CRAN")

# Make repo for source
makeRepo(pkgList, path = local_CRAN, repos = revolution, type = "source")

# install...
install.packages(pkgs, 
                 repos = local_CRAN, # do I really need "file:///"?
                 dependencies = TRUE, 
                 contrib.url = local_CRAN,
                 type  = "source" )

结果是:

Installing packages into ‘C:/emacs/R/win-library/3.1’
(as ‘lib’ is unspecified)
Warning in install.packages :
  unable to access index for repository C:/Users/.../local_CRAN/src/contrib
Warning in install.packages :
  packages ‘stringr’, ‘devtools’, ‘ggplot2’, ‘dplyr’, ‘tidyr’, ‘rmarkdown’, ‘knitr’, ‘reshape2’, ‘gdata’ are not available (for R version 3.1.2)

我在这里缺少什么？

编辑是的，我错过了file:///的正确使用，它应该是这样的:

install.packages(pkgs, 
                 repos = paste0("file:///", local_CRAN),
                 type = "source")

这让我深受感动，现在一切基本上都按预期工作了。非常感谢。现在我只需查看以下内容: fatal error :curl/curl.h:没有这样的文件或目录，这会阻止 RCurl 和 httr 安装。

Answer 1

包 miniCRAN 可以帮助解决这个问题。您告诉 miniCRAN 您想要安装的软件包列表，然后它会找出依赖关系，下载这些软件包并在您的本地计算机上创建一个行为类似于 CRAN 的存储库，即它尊重 install.packages() 等

更多信息:

• Available on CRAN

• 阅读vignette

• 我们正在积极开发 miniCRAN。跟踪进度并在 github miniCRAN repository 查找最新的开发版本

• 请参阅 project wiki获取演示文稿、博客文章等的链接

要从本地 miniCRAN 存储库安装，您有两种选择。

1. 首先，您可以使用 URI 约定 file:///。例如

   install.packages("ggplot2", repos="file:///path/to/file/")
   

2. 或者，您可以将目标配置为 HTTP 服务器，并通过 URL 使您的存储库可用。在这种情况下，您的本地存储库的外观和感觉与 CRAN 镜像完全相同，只是它只包含您想要的包。