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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.


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


And the development version from GitHub with:

# install.packages("devtools")

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 customized or extended by setting the LS_COLORS environment variable, in the same output format as GNU dircolors.


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.


# 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
#> DESCRIPTION       Makefile         NAMESPACE        
#>          R                README.Rmd        
#> _pkgdown.yml     codecov.yml fs.Rproj         
#> inst             man              man-roxygen      revdep           
#> script.R         src              tests            vignettes

# create a new directory
tmp <- dir_create(file_temp())
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa117df4099f

# create new files in that directory
file_create(path(tmp, "my-file.txt"))
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa117df4099f/my-file.txt

# remove files from the directory
file_delete(path(tmp, "my-file.txt"))
#> character(0)

# remove the directory

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.


paths <- file_temp() %>%
  dir_create() %>%
  path(letters[1:5]) %>%
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa11686663e2/a
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa11686663e2/b
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa11686663e2/c
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa11686663e2/d
#> /var/folders/9x/_8jnmxwj3rq1t90mlr6_0k1w0000gn/T/RtmppbMbhP/fileaa11686663e2/e

paths %>% file_delete()

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

Some examples…


Filter files by type, permission and size

dir_info("src", recurse = FALSE) %>%
  filter(type == "file", permissions == "u+r", size > "10KB") %>%
  arrange(desc(size)) %>%
  select(path, permissions, size, modification_time)
#> # A tibble: 12 x 4
#>    path                     permissions        size modification_time  
#>    <fs::path>               <fs::perms> <fs::bytes> <dttm>             
#>  1 src/libuv-v1.38.1.tar.gz rw-r--r--         1.19M 2020-07-30 15:34:04
#>  2 src/                rwxr-xr-x       256.12K 2020-07-31 13:49:54
#>  3 src/id.o                 rw-r--r--       173.61K 2020-07-31 13:49:54
#>  4 src/dir.o                rw-r--r--       107.33K 2020-07-31 13:49:54
#>  5 src/path.o               rw-r--r--        99.26K 2020-07-31 13:49:54
#>  6 src/utils.o              rw-r--r--        75.12K 2020-07-31 13:49:54
#>  7 src/getmode.o            rw-r--r--        71.07K 2020-07-31 13:49:54
#>  8 src/link.o               rw-r--r--        69.95K 2020-07-31 13:49:54
#>  9 src/file.o               rw-r--r--        48.67K 2020-07-31 13:49:54
#> 10 src/error.o              rw-r--r--        18.41K 2020-07-31 13:49:54
#> 11 src/init.o               rw-r--r--        16.86K 2020-07-31 13:49:54
#> 12 src/              rw-r--r--        11.01K 2020-04-01 12:30:55

Tabulate and display folder size.

dir_info("src", recurse = TRUE) %>%
  group_by(directory = path_dir(path)) %>%
  tally(wt = size, sort = TRUE)
#> # A tibble: 97 x 2
#>    directory                                  n
#>    <chr>                            <fs::bytes>
#>  1 src/libuv-v1.38.1                      4.28M
#>  2 src/libuv-1.38.1                       2.67M
#>  3 src                                    2.15M
#>  4 src/libuv-v1.38.1/autom4te.cache       1.15M
#>  5 src/libuv-v1.38.1/test                 1.08M
#>  6 src/libuv-1.38.1/src/win             731.12K
#>  7 src/libuv-v1.38.1/src/win            731.12K
#>  8 src/libuv-1.38.1/src/unix            591.54K
#>  9 src/libuv-v1.38.1/src/unix           586.58K
#> 10 src/libuv-v1.38.1/m4                 354.63K
#> # … with 87 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")
#> 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


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.