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:
install.packages("fs")And the development version from GitHub with:
pak::pak("r-lib/fs")fs functions smooth over some of the idiosyncrasies of file handling with base R functions:
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Vectorization. All fs functions are vectorized, accepting multiple paths as input. Base functions are inconsistently vectorized.
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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.
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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.
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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.
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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()vsnormalizePath();Sys.chmod()vsfile.access()).
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 pathsfile_for filesdir_for directorieslink_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()
#> DESCRIPTION LICENSE LICENSE.md MAINTENANCE.md
#> NAMESPACE NEWS.md R README.Rmd
#> README.md _pkgdown.yml cleanup codecov.yml
#> cran-comments.md fs.Rproj inst man
#> man-roxygen src tests vignettes
# create a new directory
tmp <- dir_create(file_temp())
tmp
#> /var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e375b43f7c8
# create new files in that directory
file_create(path(tmp, "my-file.txt"))
dir_ls(tmp)
#> /var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e375b43f7c8/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/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e377e50d1e9/a
#> /var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e377e50d1e9/b
#> /var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e377e50d1e9/c
#> /var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e377e50d1e9/d
#> /var/folders/ph/fpcmzfd16rgbbk8mxvy9m2_h0000gn/T/RtmpxNODwI/file5e377e50d1e9/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", recurse = FALSE) %>%
filter(type == "file", permissions == "u+r", size > "10KB") %>%
arrange(desc(size)) %>%
select(path, permissions, size, modification_time)
#> # A tibble: 12 × 4
#> path permissions size modification_time
#> <fs::path> <fs::perms> <fs::bytes> <dttm>
#> 1 src/fs.so rwxr-xr-x 309.3K 2023-07-10 18:01:44
#> 2 src/id.o rw-r--r-- 185.7K 2023-07-10 18:01:17
#> 3 src/dir.o rw-r--r-- 115.1K 2023-07-10 18:01:16
#> 4 src/path.o rw-r--r-- 113.6K 2023-07-10 18:01:18
#> 5 src/link.o rw-r--r-- 91.6K 2023-07-10 18:01:18
#> 6 src/getmode.o rw-r--r-- 83.1K 2023-07-10 18:01:17
#> 7 src/utils.o rw-r--r-- 80.8K 2023-07-10 18:01:18
#> 8 src/file.o rw-r--r-- 66.1K 2023-07-10 18:01:17
#> 9 src/init.o rw-r--r-- 20.4K 2023-07-10 18:01:17
#> 10 src/error.o rw-r--r-- 20.1K 2023-07-10 18:01:16
#> 11 src/fs.o rw-r--r-- 12K 2023-07-10 18:01:17
#> 12 src/file.cc rw-r--r-- 11.7K 2023-07-10 17:54:06Tabulate and display folder size.
dir_info("src", recurse = TRUE) %>%
group_by(directory = path_dir(path)) %>%
tally(wt = size, sort = TRUE)
#> # A tibble: 14 × 2
#> directory n
#> <chr> <fs::bytes>
#> 1 src/libuv-1.44.2 2.87M
#> 2 src/libuv-1.44.2/src/unix 1.46M
#> 3 src 1.11M
#> 4 src/libuv-1.44.2/test 1.05M
#> 5 src/libuv-1.44.2/src/win 742.07K
#> 6 src/libuv-1.44.2/m4 356.7K
#> 7 src/libuv-1.44.2/src 353.05K
#> 8 src/libuv-1.44.2/include/uv 137.44K
#> 9 src/libuv-1.44.2/img 106.71K
#> 10 src/unix 76.56K
#> 11 src/libuv-1.44.2/include 66.23K
#> 12 src/bsd 20.02K
#> 13 src/windows 4.73K
#> 14 src/libuv-1.44.2/test/fixtures 453Read 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 × 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)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.
Please note that the fs project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.