Cross-Platform File System Operations Based on 'libuv'

A cross-platform interface to file system operations, built on top of the 'libuv' C library.

fs provides a cross-platform, uniform interface to file system operations. It shares the same back-end component as nodejs, the libuv C library, which brings the benefit of extensive real-world use and rigorous cross-platform testing. The name, and some of the interface, is partially inspired by Rust’s fs module.

Installation

You can install the released version of fs from CRAN with:

install.packages("fs")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("r-lib/fs")

Comparison vs base equivalents

fs functions smooth over some of the idiosyncrasies of file handling with base R functions:

• Vectorization. All fs functions are vectorized, accepting multiple paths as input. Base functions are inconsistently vectorized.

• Predictable return values that always convey a path. All fs functions return a character vector of paths, a named integer or a logical vector, where the names give the paths. Base return values are more varied: they are often logical or contain error codes which require downstream processing.

• Explicit failure. If fs operations fail, they throw an error. Base functions tend to generate a warning and a system dependent error code. This makes it easy to miss a failure.

• UTF-8 all the things. fs functions always convert input paths to UTF-8 and return results as UTF-8. This gives you path encoding consistency across OSes. Base functions rely on the native system encoding.

• Naming convention. fs functions use a consistent naming convention. Because base R’s functions were gradually added over time there are a number of different conventions used (e.g. path.expand() vs normalizePath(); Sys.chmod() vs file.access()).

Tidy paths

fs functions always return ‘tidy’ paths. Tidy paths

• Always use / to delimit directories
• never have multiple / or trailing /

Tidy paths are also coloured (if your terminal supports it) based on the file permissions and file type. This colouring can be customised or extended by setting the LS_COLORS environment variable, in the same output format as GNU dircolors.

Usage

fs functions are divided into four main categories:

• path_ for manipulating and constructing paths
• file_ for files
• dir_ for directories
• link_ for links

Directories and links are special types of files, so file_ functions will generally also work when applied to a directory or link.

library(fs)
 
# Construct a path to a file with `path()`
path("foo", "bar", letters[1:3], ext = "txt")
#> foo/bar/a.txt foo/bar/b.txt foo/bar/c.txt
 
# list files in the current directory
dir_ls()
#> CRAN-RELEASE         DESCRIPTION          LICENSE.md           
#> NAMESPACE            NEWS.md              R                    
#> README.Rmd           README.md            _pkgdown.yml         
#> appveyor.yml         bar                  check.R              
#> codecov.yml          cran-comments.md     docs                 
#> example              follow.R             fs.Rcheck            
#> fs.Rproj             fs_1.2.2.9000.tar.gz inst                 
#> man                  man-roxygen          script.R             
#> src                  tests
 
# create a new directory
tmp <- dir_create(file_temp())
tmp
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f7126ece07c
 
# create new files in that directory
file_create(path(tmp, "my-file.txt"))
dir_ls(tmp)
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f7126ece07c/my-file.txt
 
# remove files from the directory
file_delete(path(tmp, "my-file.txt"))
dir_ls(tmp)
#> character(0)
 
# remove the directory
dir_delete(tmp)

fs is designed to work well with the pipe, though because it is a minimal-dependency infrastructure package it doesn’t provide the pipe itself. You will need to attach magrittr or similar.

library(magrittr)
 
paths <- file_temp() %>%
  dir_create() %>%
  path(letters[1:5]) %>%
  file_create()
paths
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f713ca22ebf/a
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f713ca22ebf/b
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f713ca22ebf/c
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f713ca22ebf/d
#> /var/folders/dt/r5s12t392tb5sk181j3gs4zw0000gn/T/RtmpM84M38/file16f713ca22ebf/e
 
paths %>% file_delete()

fs functions also work well in conjunction with other tidyverse packages, like dplyr and purrr.

Some examples…

suppressMessages(
  library(tidyverse))

Filter files by type, permission and size

dir_info("src", recursive = FALSE) %>%
  filter(type == "file", permissions == "u+r", size > "10KB") %>%
  arrange(desc(size)) %>%
  select(path, permissions, size, modification_time)
#> # A tibble: 10 x 4
#>    path                permissions        size modification_time  
#>    <fs::path>          <fs::perms> <fs::bytes> <dttm>             
#>  1 src/RcppExports.o   rw-r--r--        655.5K 2018-05-20 17:39:19
#>  2 src/dir.o           rw-r--r--        442.7K 2018-05-20 17:39:19
#>  3 src/fs.so           rwxr-xr-x        435.3K 2018-05-20 17:39:29
#>  4 src/id.o            rw-r--r--        383.2K 2018-05-20 17:39:18
#>  5 src/file.o          rw-r--r--        347.5K 2018-05-20 17:39:18
#>  6 src/path.o          rw-r--r--        257.4K 2018-05-20 17:39:18
#>  7 src/link.o          rw-r--r--        224.3K 2018-05-20 17:39:18
#>  8 src/utils.o         rw-r--r--        117.9K 2018-05-20 17:39:18
#>  9 src/error.o         rw-r--r--         17.3K 2018-05-20 17:39:15
#> 10 src/RcppExports.cpp rw-r--r--         11.4K 2018-05-20 17:39:14

Tabulate and display folder size.

dir_info("src", recursive = TRUE) %>%
  group_by(directory = path_dir(path)) %>%
  tally(wt = size, sort = TRUE)
#> # A tibble: 54 x 2
#>    directory                                        n
#>    <fs::path>                             <fs::bytes>
#>  1 src                                          2.86M
#>  2 src/libuv                                    2.44M
#>  3 src/libuv/src/unix                           1.08M
#>  4 src/libuv/autom4te.cache                     1.08M
#>  5 src/libuv/test                             865.36K
#>  6 src/libuv/src/win                          683.14K
#>  7 src/libuv/docs/src/static                  328.32K
#>  8 src/libuv/m4                               319.95K
#>  9 src/libuv/include                          192.33K
#> 10 src/libuv/docs/src/static/diagrams.key     184.04K
#> # ... with 44 more rows

Read a collection of files into one data frame.

dir_ls() returns a named vector, so it can be used directly with purrr::map_df(.id).

# Create separate files for each species
iris %>%
  split(.$Species) %>%
  map(select, -Species) %>%
  iwalk(~ write_tsv(.x, paste0(.y, ".tsv")))
 
# Show the files
iris_files <- dir_ls(glob = "*.tsv")
iris_files
#> setosa.tsv     versicolor.tsv virginica.tsv
 
# Read the data into a single table, including the filenames
iris_files %>%
  map_df(read_tsv, .id = "file", col_types = cols(), n_max = 2)
#> # A tibble: 6 x 5
#>   file           Sepal.Length Sepal.Width Petal.Length Petal.Width
#>   <chr>                 <dbl>       <dbl>        <dbl>       <dbl>
#> 1 setosa.tsv              5.1         3.5          1.4         0.2
#> 2 setosa.tsv              4.9         3            1.4         0.2
#> 3 versicolor.tsv          7           3.2          4.7         1.4
#> 4 versicolor.tsv          6.4         3.2          4.5         1.5
#> 5 virginica.tsv           6.3         3.3          6           2.5
#> 6 virginica.tsv           5.8         2.7          5.1         1.9
 
file_delete(iris_files)

Feedback wanted!

We hope fs is a useful tool for both analysis scripts and packages. Please open GitHub issues for any feature requests or bugs.

In particular, we have found non-ASCII filenames in non-English locales on Windows to be especially tricky to reproduce and handle correctly. Feedback from users who use commonly have this situation is greatly appreciated.