R library for interacting with the Google Cloud Storage JSON API (api docs).
Google Cloud Storage charges you for storage (prices here).
You can use your own Google Project with a credit card added to create buckets, where the charges will apply. This can be done in the Google API Console
By default, all cloudyr packages look for the access key ID and secret access key in environment variables. You can also use this to specify a default bucket, and auto-authentication upon attaching the library. For example:
Sys.setenv("GCS_CLIENT_ID" = "mykey",
"GCS_CLIENT_SECRET" = "mysecretkey",
"GCS_WEB_CLIENT_ID" = "my-shiny-key",
"GCS_WEB_CLIENT_SECRET" = "my-shiny-secret-key",
"GCS_DEFAULT_BUCKET" = "my-default-bucket",
"GCS_AUTH_FILE" = "/fullpath/to/service-auth.json")
These can alternatively be set on the command line or via an Renviron.site or .Renviron file (https://cran.r-project.org/web/packages/httr/vignettes/api-packages.html
).
Authentication can be carried out each session via gcs_auth
. The first time you run this you will be sent to a Google login prompt in your browser to allow the googleCloudStorageR
project access (or the Google project you configure).
Once authenticated a file named .httr-oauth
is saved to your working directory. On subsequent authentication this file will hold your authentication details, and you won’t need to go via the browser. Deleting this file, or setting new_user=TRUE
will start the authentication flow again.
library(googleCloudStorageR)
## first time this will send you to the browser to authenticate
gcs_auth()
## to authenticate with a fresh user, delete .httr-oauth or run with new_user=TRUE
gcs_auth(new_user = TRUE)
...call functions...etc...
Each new R session will need to run gcs_auth()
to authenticate future API calls.
Alternatively, you can specify the location of a service account JSON file taken from your Google Project, or the location of a previously created .httr-oauth
token in a system environment:
Sys.setenv("GCS_AUTH_FILE" = "/fullpath/to/auth.json")
This file will then used for authentication via gcs_auth()
when you load the library:
## GCS_AUTH_FILE set so auto-authentication
library(googleCloudStorageR)
## no need for gcs_auth()
gcs_get_bucket("your-bucket")
To avoid specifying the bucket in the functions below, you can set the name of your default bucket via environmental variables or via the function gcs_global_bucket()
. See the Setting environment variables
section below for more details.
## set bucket via environment
Sys.setenv("GCS_DEFAULT_BUCKET" = "my-default-bucket")
library(googleCloudStorageR)
## optional, if you haven't set environment argument GCS_AUTH_FILE
## gcs_auth()
## check what the default bucket is
gcs_get_global_bucket()
[1] "my-default-bucket"
## you can also set a default bucket after loading the library for that session
gcs_global_bucket("your-default-bucket-2")
gcs_get_global_bucket()
[1] "my-default-bucket-2"
Once you have a Google project and created a bucket with an object in it, you can download it as below:
library(googleCloudStorageR)
## optional, if you haven't set environment argument GCS_AUTH_FILE
## gcs_auth()
## get your project name from the API console
proj <- "your-project"
## get bucket info
buckets <- gcs_list_buckets(proj)
bucket <- "your-bucket"
bucket_info <- gcs_get_bucket(bucket)
bucket_info
==Google Cloud Storage Bucket==
Bucket: your-bucket
Project Number: 1123123123
Location: EU
Class: STANDARD
Created: 2016-04-28 11:39:06
Updated: 2016-04-28 11:39:06
Meta-generation: 1
eTag: Cxx=
## get object info in the default bucket
objects <- gcs_list_objects()
## save directly to an R object (warning, don't run out of RAM if its a big object)
## the download type is guessed into an appropriate R object
parsed_download <- gcs_get_object(objects$name[[1]])
## if you want to do your own parsing, set parseObject to FALSE
## use httr::content() to parse afterwards
raw_download <- gcs_get_object(objects$name[[1]],
parseObject = FALSE)
## save directly to a file in your working directory
## parseObject has no effect, it is a httr::content(req, "raw") download
gcs_get_object(objects$name[[1]], saveToDisk = "csv_downloaded.csv")
Objects can be uploaded via files saved to disk, or passed in directly if they are data frames or list type R objects. By default, data frames will be converted to CSV via write.csv()
, lists to JSON via jsonlite::toJSON
.
If you want to use other functions for transforming R objects, for example setting row.names = FALSE
or using write.csv2
, pass the function through object_function
## upload a file - type will be guessed from file extension or supply type
write.csv(mtcars, file = filename)
gcs_upload(filename)
## upload an R data.frame directly - will be converted to csv via write.csv
gcs_upload(mtcars)
## upload an R list - will be converted to json via jsonlite::toJSON
gcs_upload(list(a = 1, b = 3, c = list(d = 2, e = 5)))
## upload an R data.frame directly, with a custom function
## function should have arguments 'input' and 'output'
## safest to supply type too
f <- function(input, output) write.csv(input, row.names = FALSE, file = output)
gcs_upload(mtcars,
object_function = f,
type = "text/csv")
You can pass metadata with an object via the function gcs_metadata_object()
.
the name you pass to the metadata object will override the name if it is also set elsewhere.
meta <- gcs_metadata_object("mtcars.csv",
metadata = list(custom1 = 2,
custom_key = 'dfsdfsdfsfs))
gcs_upload(mtcars, object_metadata = meta)
If the file/object is under 5MB, simple uploads are used.
For files > 5MB, resumable uploads are used. This allows you to upload up to 5TB.
If you get an interrupted connection when uploading, gcs_upload
will retry 3 times, if it fails it will return a Retry object, that you can try again later from where the upload stopped. Call this via gcs_retry_upload
## write a big object to a file
big_file <- "big_filename.csv"
write.csv(big_object, file = big_file)
## attempt upload
upload_try <- gcs_upload(big_file)
## if successful, upload_try is an object metadata object
upload_try
==Google Cloud Storage Object==
Name: "big_filename.csv"
Size: 8.5 Gb
Media URL https://www.googleapis.com/download/storage/v1/b/xxxx
Bucket: your-bucket
ID: your-bucket/"test.pdf"/xxxx
MD5 Hash: rshao1nxxxxxY68JZQ==
Class: STANDARD
Created: 2016-08-12 17:33:05
Updated: 2016-08-12 17:33:05
Generation: 1471023185977000
Meta Generation: 1
eTag: CKi90xxxxxEAE=
crc32c: j4i1sQ==
## if unsuccessful after 3 retries, upload_try is a Retry object
==Google Cloud Storage Upload Retry Object==
File Location: big_filename.csv
Retry Upload URL: http://xxxx
Created: 2016-08-12 17:33:05
Type: csv
File Size: 8.5 Gb
Upload Byte: 4343
Upload remaining: 8.1 Gb
## you can retry to upload the remaining data using gcs_retry_upload()
try2 <- gcs_retry_upload(upload_try)
You can change who can access objects via gcs_update_acl
to one of READER
or OWNER
, on a user, group, domain, project or public for all users or authenticated users.
By default you are “OWNER” of all the objects and buckets you upload and create.
## update access of object to READER for all public
gcs_update_object_acl("your-object.csv", entity_type = "allUsers")
## update access of object for user joe@blogs.com to OWNER
gcs_update_acl("your-object.csv",
entity = "joe@blogs.com",
role = "OWNER")
## update access of object for googlegroup users to READER
gcs_update_object_acl("your-object.csv",
entity = "my-group@googlegroups.com",
entity_type = "group")
## update access of object for all users to OWNER on your Google Apps domain
gcs_update_object_acl("your-object.csv",
entity = "yourdomain.com",
entity_type = "domain",
role = OWNER)
Delete an object by passing its name (and bucket if not default)
## returns TRUE is successful, a 404 error if not found
gcs_delete_object("your-object.csv")
Use gcs_get_object_acl()
to see what the current access is for an entity
+ entity_type
.
## default entity_type is user
acl <- gcs_get_object_acl("your-object.csv",
entity = "joe@blogs.com")
acl$role
[1] "OWNER"
## for allUsers and allAuthenticated users, you don't need to supply entity
acl <- gcs_get_object_acl("your-object.csv",
entity_type = "allUsers")
acl$role
[1] "READER"
Once a user (or group or the public) has access, they can reach that object via a download link generated by the function gcs_download_url
download_url <- gcs_download_url("your-object.csv")
download_url
[1] "https://storage.cloud.google.com/your-project/your-object.csv"
Versions of save.image()
, save()
and load()
are implemented called gcs_save_image()
, gcs_save()
and gcs_load()
. These functions save and load the global R session to the cloud.
## save the current R session including all objects
gcs_save_image()
### wipe environment
rm(list = ls())
## load up environment again
gcs_load()
Save specific objects:
cc <- 3
d <- "test1"
gcs_save("cc","d", file = "gcs_save_test.RData")
## remove the objects saved in cloud from local environment
rm(cc,d)
## load them back in from GCS
gcs_load(file = "gcs_save_test.RData")
cc == 3
[1] TRUE
d == "test1"
[1] TRUE
You can also upload .R
code files and source them directly using gcs_source
:
## make a R source file and upload it
cat("x <- 'hello world!'\nx", file = "example.R")
gcs_upload("example.R", name = "example.R")
## source the file to run its code
gcs_source("example.R")
## the code from the upload file has run
x
[1] "hello world!"
The library is also compatible with Shiny authentication flows, so you can create Shiny apps that lets users log in and upload their own data.
An example of that is shown below:
library("shiny")
library("googleAuthR")
library("googleCloudStorageR")
options(googleAuthR.scopes.selected = "https://www.googleapis.com/auth/devstorage.full_control")
## optional, if you want to use your own Google project
# options("googleAuthR.client_id" = "YOUR_CLIENT_ID")
# options("googleAuthR.client_secret" = "YOUR_CLIENT_SECRET")
## you need to start Shiny app on port 1221
## as thats what the default googleAuthR project expects for OAuth2 authentication
## options(shiny.port = 1221)
## print(source('shiny_test.R')$value) or push the "Run App" button in RStudio
shinyApp(
ui = shinyUI(
fluidPage(
googleAuthR::googleAuthUI("login"),
fileInput("picture", "picture"),
textInput("filename", label = "Name on Google Cloud Storage",value = "myObject"),
actionButton("submit", "submit"),
textOutput("meta_file")
)
),
server = shinyServer(function(input, output, session){
access_token <- shiny::callModule(googleAuth, "login")
meta <- eventReactive(input$submit, {
message("Uploading to Google Cloud Storage")
# from googleCloudStorageR
with_shiny(gcs_upload,
file = input$picture$datapath,
# enter your bucket name here
bucket = "gogauth-test",
type = input$picture$type,
name = input$filename,
shiny_access_token = access_token())
})
output$meta_file <- renderText({
req(meta())
str(meta())
paste("Uploaded: ", meta()$name)
})
})
)
There are various functions to manipulate Buckets:
gcs_list_buckets
gcs_get_bucket
gcs_create_bucket
You can get meta data about an object by passing meta=TRUE
to gcs_get_object
gcs_get_object("your-object", "your-bucket", meta = TRUE)
googleCloudStorageR
has its own Google project which is used to call the Google Cloud Storage API, but does not have access to the objects or buckets in your Google Project unless you give permission for the library to access your own buckets during the OAuth2 authentication process.
No other user, including the owner of the Google Cloud Storage API project has access unless you have given them access, but you may want to change to use your own Google Project (that could or could not be the same as the one that holds your buckets).
The instructions below are for when you visit the Google API console (https://console.developers.google.com/apis/
)
Add them by modifying your .Renviron file, or under the following entries:
Sys.setenv("GCS_CLIENT_ID" = "mykey",
"GCS_CLIENT_SECRET" = "mysecretkey")
Alternatively, modify these options after googleAuthR has been loaded:
options("googleAuthR.client_id" = "YOUR_CLIENT_ID")
options("googleAuthR.client_secret" = "YOUR_CLIENT_SECRET")
https://mark.shinyapps.io/searchConsoleRDemo/
http://127.0.0.1:1221
Add them by modifying your .Renviron file, or under the following entries:
Sys.setenv("GCS_WEB_CLIENT_ID" = "mykey",
"GCS_WEB_CLIENT_SECRET" = "mysecretkey")
Alternatively, in your Shiny script modify these options:
options("googleAuthR.webapp.client_id" = "YOUR_CLIENT_ID")
options("googleAuthR.webapp.client_secret" = "YOUR_CLIENT_SECRET")
shiny::runApp(port=1221)
or set a shiny option to default to it: options(shiny.port = 1221)
and launch via the RunApp
button in RStudio.Running on your Shiny Server will work only for the URL from step 3.
library(googleCloudStorage)
, it will look to see if "https://www.googleapis.com/auth/devstorage.full_control"
is set in getOption("googleAuthR.scopes.selected")
and set it if it is not, adding to the existing scopes.Alternativly, set the googleAuthR
option for Google Cloud storage scope after the library has been loaded but before authentication.
options(googleAuthR.scopes.selected = "https://www.googleapis.com/auth/devstorage.full_control")