s3 is an R package designed to download files from AWS
S3. Files are downloaded to the R user data
directory (i.e., tools::R_user_dir("s3", "data")) so they can be
cached across all of an R user’s sessions and projects. Specify an
alternative download location by setting the R_USER_DATA_DIR
environment variable (see ?tools::R_user_dir).
A file is specified from AWS S3 using its URI and downloaded using the
s3_get() and s3_get_files() functions; e.g.,
s3_get("s3://modis-aod-nasa/2020.05.22.tif"). The get functions always
(invisibly) return paths to downloaded files, making it straightforward
to read downloaded files into R. Files already present in the download
location will be used before trying to download a file again. This means
more concise code for downloading files, if they are not already
downloaded, and reading files within R.
Install the CRAN latest release inside R with:
install.packages("s3")Install the development version from GitHub:
# install.packages("remotes")
remotes::install_github("geomarker-io/s3")library(s3)Download a single file specified by its S3 URI with:
s3_get("s3://geomarker/testing_downloads/mtcars.rds")If a file has already been downloaded, then it will not be re-downloaded:
s3_get("s3://geomarker/testing_downloads/mtcars.rds")
#> ℹ 's3://geomarker/testing_downloads/mtcars.rds' already exists at '/var/folders/pg/q33bfwtj57d_v3vqpl7g26400000gn/T/RtmpTSph6V/R/s3/geomarker/testing_downloads/mtcars.rds'Download multiple files with:
s3_get_files(c(
"s3://geomarker/testing_downloads/mtcars.rds",
"s3://geomarker/testing_downloads/mtcars_again.rds"
),
confirm = FALSE)
#> ℹ 1 file already exists
#> ℹ 1 file totaling 1.23 kB will be downloaded to /var/folders/pg/q33bfwtj57d_v3vqpl7g26400000gn/T//RtmpTSph6V/R/s3
#> → Downloading 1 file.
#> → Got 0 files, downloading 1
#> ✔ Downloaded 1 file in 150ms.Downloading private files requires the name of the S3 bucket’s region (this is determined automatically when the file is public):
s3_get("s3://geomarker/testing_downloads/mtcars_private.rds", region = "us-east-2")You must have the appropriate AWS S3 credentials set to gain access to
non-public files. As with other AWS command line tools and R packages,
you can use the environment variables AWS_ACCESS_KEY_ID and
AWS_SECRET_ACCESS_KEY to gain access to such files.
It is highly recommended to setup your environment variables outside of
your R script to avoid including sensitive information within your R
script. This can be done by exporting environment variables before
starting R (see AWS CLI
documentation
on this) or by defining them in a .Renviron file (see ?.Renviron
within R).
You can use the internal helper function to check if AWS key environment variables are set.
s3:::check_for_aws_env_vars()
#> ✖ AWS_SECRET_ACCESS_KEY and/or AWS_ACCESS_KEY_ID are unset
#> ℹ Non-public S3 files will not be availableFiles are saved within a directory structure matching that of the S3
URI. s3_get and s3_get_files both invisibly return the file path(s)
of the downloaded files so that they can be further used to access the
downloaded files. This makes it possible for different users with
different operating systems and/or different project file structures and
locations to utilize a downloaded S3 file without changing their source
code:
s3_get("s3://geomarker/testing_downloads/mtcars.rds") |>
readRDS()
#> ℹ 's3://geomarker/testing_downloads/mtcars.rds' already exists at '/var/folders/pg/q33bfwtj57d_v3vqpl7g26400000gn/T/RtmpTSph6V/R/s3/geomarker/testing_downloads/mtcars.rds'
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
#> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2