脱机安装软件包列表:依次获取依赖关系

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我有一堆软件包的源文件及其依赖关系,我想在没有互联网访问的计算机上安装.我想在其他计算机上使用U盘安装所有这些,但某些软件包的安装失败,因为在软件包之前没有安装依赖项.在需要它们的包之前,我如何获得依次安装的顺序?

这是我目前的方法获取包,它们的依赖关系,并按照正确的顺序来获取它们:

# find the dependencies for the packages I want
# from https://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 https://stackoverflow.com/a/10841614/1036500
library(tools)
write_PACKAGES(local_CRAN)@H_403_4@ 
 

现在假设我在另一台电脑上安装了R和RStudio(和Rtools或Xcode),没有互联网连接,我插上USB棒,打开RProj文件来设置工作目录,并运行这个脚本:

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

## 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" )@H_403_4@ 
 

这工作相当不错,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,:
  there is no package called ‘httr’
3: In library(package,:
  there is no package called ‘devtools’
4: In library(package,:
  there is no package called ‘ggplot2’
5: In library(package,:
  there is no package called ‘tidyr’
6: In library(package,:
  there is no package called ‘rmarkdown’@H_403_4@ 
 

似乎编织者必须在rmarkdown之前进行,在tidyr和ggplot2之前重塑2等.

必须有一个更简单和更完整的解决方案来获取文件列表的问题,需要按照正确顺序放置所有依赖关系.最简单的方法是什么(不使用任何贡献的包)?

这是我目前正在开发的系统,我正在使用源版本的软件包来试图为离线计算机(OSX / Linux / Windows)做任何事情做准备:

> 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@H_403_4@ 
 

编辑以下Andrie的有用的评论,我已经与miniCRAN一起去,从小插曲中缺少的是如何从本地的repo实际安装包.这是我试过的:

library("miniCRAN")

# Specify list of packages to download
pkgs <- c('stringr','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,type  = "source" )@H_403_4@ 
 

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)@H_403_4@ 
 

我在这里缺少什么?

编辑是的,我没有正确使用file:///,它应该是这样的:

install.packages(pkgs,repos = paste0("file:///",local_CRAN),type = "source")@H_403_4@ 
 

这让我感到震惊,这一切基本上都是按预期的方式工作的.非常感谢.现在我只是想看看:致命错误:curl / curl.h:没有这样的文件或目录,这是阻止RCurl和httr安装.

miniCRAN包可以帮助这个.您可以告诉miniCRAN您想要安装的软件包列表,然后找出依赖关系,下载这些软件包,并在本地计算机上创建一个名为CRAN的存储库,即它遵守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找到最新的开发版本
>请参阅project wiki链接到演示文稿,博客文章

要从本地的miniCRAN存储库安装,您有两个选项.

>首先,你可以使用URI约定文件:///.例如

install.packages("ggplot2",repos="file:///path/to/file/")@H_403_4@ 
 

>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,您的本地存储库将看起来和感觉完全一样,就像一个CRAN镜像,除了它只包含你想要的包.

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