Package 'googleCloudStorageR' reference manual

Title:	Interface with Google Cloud Storage API
Description:	Interact with Google Cloud Storage <https://cloud.google.com/storage/> API in R. Part of the 'cloudyr' <https://cloudyr.github.io/> project.
Authors:	Mark Edmondson [aut, cre] , manuteleco [ctb] (<https://github.com/manuteleco>)
Maintainer:	Mark Edmondson <[email protected]>
License:	MIT + file LICENSE
Version:	0.7.0.9000
Built:	2024-10-26 04:57:04 UTC
Source:	https://github.com/cloudyr/googlecloudstorager

Authenticate with Google Cloud Storage API

Description

Authenticate with Google Cloud Storage API

Usage

gcs_auth(json_file = NULL, token = NULL, email = NULL)
gcs_auth(json_file = NULL, token = NULL, email = NULL)

Arguments

`json_file`	Authentication json file you have downloaded from your Google Project
`token`	An existing authentication token you may have by other means
`email`	The email to default authenticate through

Details

The best way to authenticate is to use an environment argument pointing at your authentication file, making this function unnecessary.

Set the file location of your download Google Project JSON file in a GCS_AUTH_FILE argument

Then, when you load the library you should auto-authenticate

However, you can authenticate directly using this function pointing at your JSON auth file. You will still need the two JSON files - the client JSON and the authentication key JSON. gcs_setup can help set-up the latter, the client JSON you will need to download from your Google Cloud Project.

If using JSON files from another source, ensure it has either "https://www.googleapis.com/auth/devstorage.full_control" or "https://www.googleapis.com/auth/cloud-platform" scopes.

Examples


## Not run: 
# on first run, generate a auth key via gcs_setup()

# the json file for the auth key you are using
library(googleCloudStorageR)
gcs_auth("location_of_json_file.json")

#' # to use your own Google Cloud Project credentials
# go to GCP console and download client credentials JSON 
# ideally set this in .Renviron file, not here but just for demonstration
Sys.setenv("GAR_CLIENT_JSON" = "location/of/file.json")
library(googleCloudStorageR)
# should now be able to log in via your own GCP project
gcs_auth()

# reauthentication
# Once you have authenticated, set email to skip the interactive message
gcs_auth(email = "[email protected]")

# or leave unset to bring up menu on which email to auth with
gcs_auth()
# The googleCLoudStorageR package is requesting access to your Google account. 
# Select a pre-authorised account or enter '0' to obtain a new token.
# Press Esc/Ctrl + C to abort.
#1: [email protected]
#2: [email protected]
# you can set authentication for many emails, then switch between them e.g.
gcs_auth(email = "[email protected]")
gcs_list_buckets("my-project") # lists what buckets you have access to
gcs_auth(email = "[email protected]") 
gcs_list_buckets("my-project") # lists second set of buckets


## End(Not run)
## Not run: 
# on first run, generate a auth key via gcs_setup()

# the json file for the auth key you are using
library(googleCloudStorageR)
gcs_auth("location_of_json_file.json")

#' # to use your own Google Cloud Project credentials
# go to GCP console and download client credentials JSON 
# ideally set this in .Renviron file, not here but just for demonstration
Sys.setenv("GAR_CLIENT_JSON" = "location/of/file.json")
library(googleCloudStorageR)
# should now be able to log in via your own GCP project
gcs_auth()

# reauthentication
# Once you have authenticated, set email to skip the interactive message
gcs_auth(email = "[email protected]")

# or leave unset to bring up menu on which email to auth with
gcs_auth()
# The googleCLoudStorageR package is requesting access to your Google account. 
# Select a pre-authorised account or enter '0' to obtain a new token.
# Press Esc/Ctrl + C to abort.
#1: [email protected]
#2: [email protected]
# you can set authentication for many emails, then switch between them e.g.
gcs_auth(email = "[email protected]")
gcs_list_buckets("my-project") # lists what buckets you have access to
gcs_auth(email = "[email protected]") 
gcs_list_buckets("my-project") # lists second set of buckets


## End(Not run)

Compose up to 32 objects into one

Description

This merges objects stored on Cloud Storage into one object.

Usage

gcs_compose_objects(objects, destination, bucket = gcs_get_global_bucket())
gcs_compose_objects(objects, destination, bucket = gcs_get_global_bucket())

Arguments

`objects`	A character vector of object names to combine
`destination`	Name of the new object.
`bucket`	The bucket where the objects sit

Value

Object metadata

Examples


## Not run: 
 gcs_global_bucket("your-bucket")
 objs <- gcs_list_objects()
 
 compose_me <- objs$name[1:30]
 
 gcs_compose_objects(compose_me, "composed/test.json")


## End(Not run)
## Not run: 
 gcs_global_bucket("your-bucket")
 objs <- gcs_list_objects()
 
 compose_me <- objs$name[1:30]
 
 gcs_compose_objects(compose_me, "composed/test.json")


## End(Not run)

Copy an object

Description

Copies an object to a new destination

Usage

gcs_copy_object(
  source_object,
  destination_object,
  source_bucket = gcs_get_global_bucket(),
  destination_bucket = gcs_get_global_bucket(),
  rewriteToken = NULL,
  destinationPredefinedAcl = NULL
)
gcs_copy_object(
  source_object,
  destination_object,
  source_bucket = gcs_get_global_bucket(),
  destination_bucket = gcs_get_global_bucket(),
  rewriteToken = NULL,
  destinationPredefinedAcl = NULL
)

Arguments

`source_object`	The name of the object to copy, or a `gs://` URL
`destination_object`	The name of where to copy the object to, or a `gs://` URL
`source_bucket`	The bucket of the source object
`destination_bucket`	The bucket of the destination
`rewriteToken`	Include this field (from the previous rewrite response) on each rewrite request after the first one, until the rewrite response 'done' flag is true.
`destinationPredefinedAcl`	Apply a predefined set of access controls to the destination object. If not NULL must be one of the predefined access controls such as `"bucketOwnerFullControl"`

Value

If successful, a rewrite object.

Create a new bucket

Description

Create a new bucket in your project

Usage

gcs_create_bucket(
  name,
  projectId,
  location = "US",
  storageClass = c("MULTI_REGIONAL", "REGIONAL", "STANDARD", "NEARLINE", "COLDLINE",
    "DURABLE_REDUCED_AVAILABILITY"),
  predefinedAcl = c("projectPrivate", "authenticatedRead", "private", "publicRead",
    "publicReadWrite"),
  predefinedDefaultObjectAcl = c("bucketOwnerFullControl", "bucketOwnerRead",
    "authenticatedRead", "private", "projectPrivate", "publicRead"),
  projection = c("noAcl", "full"),
  versioning = FALSE,
  lifecycle = NULL
)
gcs_create_bucket(
  name,
  projectId,
  location = "US",
  storageClass = c("MULTI_REGIONAL", "REGIONAL", "STANDARD", "NEARLINE", "COLDLINE",
    "DURABLE_REDUCED_AVAILABILITY"),
  predefinedAcl = c("projectPrivate", "authenticatedRead", "private", "publicRead",
    "publicReadWrite"),
  predefinedDefaultObjectAcl = c("bucketOwnerFullControl", "bucketOwnerRead",
    "authenticatedRead", "private", "projectPrivate", "publicRead"),
  projection = c("noAcl", "full"),
  versioning = FALSE,
  lifecycle = NULL
)

Arguments

`name`	Globally unique name of bucket to create
`projectId`	A valid Google project id
`location`	Location of bucket. See details
`storageClass`	Type of bucket
`predefinedAcl`	Apply predefined access controls to bucket
`predefinedDefaultObjectAcl`	Apply predefined access controls to objects
`projection`	Properties to return. Default noAcl omits acl properties
`versioning`	Set if the bucket supports versioning of its objects
`lifecycle`	A list of gcs_create_lifecycle objects

Details

See here for details on location options

Create a Bucket Access Controls

Description

Create a new access control at the bucket level

Usage

gcs_create_bucket_acl(
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers"),
  role = c("READER", "OWNER")
)
gcs_create_bucket_acl(
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers"),
  role = c("READER", "OWNER")
)

Arguments

`bucket`	Name of a bucket, or a bucket object returned by gcs_create_bucket
`entity`	The entity holding the permission. Not needed for entity_type `allUsers` or `allAuthenticatedUsers`
`entity_type`	what type of entity
`role`	Access permission for entity Used also for when a bucket is updated

Value

Bucket access control object

Create a lifecycle condition

Description

Use this to set rules for how long objects last in a bucket in gcs_create_bucket

Usage

gcs_create_lifecycle(
  age = NULL,
  createdBefore = NULL,
  numNewerVersions = NULL,
  isLive = NULL
)
gcs_create_lifecycle(
  age = NULL,
  createdBefore = NULL,
  numNewerVersions = NULL,
  isLive = NULL
)

Arguments

`age`	Age in days before objects are deleted
`createdBefore`	Deletes all objects before this date
`numNewerVersions`	Deletes all newer versions of this object
`isLive`	If TRUE deletes all live objects, if FALSE deletes all archived versions `numNewerVersions` and `isLive` works only for buckets with object versioning For multiple conditions, pass this object in as a list.

Examples

## Not run: 
  lifecycle <- gcs_create_lifecycle(age = 30)
  
  gcs_create_bucket("your-bucket-lifecycle",
                     projectId = "your-project",
                     location = "EUROPE-NORTH1",
                     storageClass = "REGIONAL",
                     lifecycle = list(lifecycle))



## End(Not run)
## Not run: 
  lifecycle <- gcs_create_lifecycle(age = 30)
  
  gcs_create_bucket("your-bucket-lifecycle",
                     projectId = "your-project",
                     location = "EUROPE-NORTH1",
                     storageClass = "REGIONAL",
                     lifecycle = list(lifecycle))



## End(Not run)

Create a pub/sub notification for a bucket

Description

Add a notification configuration that sends notifications for all supported events.

Usage

gcs_create_pubsub(
  topic,
  project,
  bucket = gcs_get_global_bucket(),
  event_types = NULL
)
gcs_create_pubsub(
  topic,
  project,
  bucket = gcs_get_global_bucket(),
  event_types = NULL
)

Arguments

`topic`	The pub/sub topic name
`project`	The project-id that has the pub/sub topic
`bucket`	The bucket for notifications
`event_types`	What events to activate, leave at default for all

Details

Cloud Pub/Sub notifications allow you to track changes to your Cloud Storage objects. As a minimum you wil need: the Cloud Pub/Sub API activated for the project; sufficient permissions on the bucket you wish to monitor; sufficient permissions on the project to receive notifications; an existing pub/sub topic; have given your service account at least pubsub.publisher permission.

Examples


## Not run: 

project <- "myproject"
bucket <- "mybucket"

# get the email to give access
gcs_get_service_email(project)

# once email has access, create a new pub/sub topic for your bucket
gcs_create_pubsub("gcs_r", project, bucket)


## End(Not run)


## Not run: 

project <- "myproject"
bucket <- "mybucket"

# get the email to give access
gcs_get_service_email(project)

# once email has access, create a new pub/sub topic for your bucket
gcs_create_pubsub("gcs_r", project, bucket)


## End(Not run)

Delete a bucket

Description

Delete the bucket, and all its objects

Usage

gcs_delete_bucket(
  bucket,
  ifMetagenerationMatch = NULL,
  ifMetagenerationNotMatch = NULL,
  force_delete = FALSE
)

gcs_delete_bucket_objects(bucket, include_versions = FALSE)
gcs_delete_bucket(
  bucket,
  ifMetagenerationMatch = NULL,
  ifMetagenerationNotMatch = NULL,
  force_delete = FALSE
)

gcs_delete_bucket_objects(bucket, include_versions = FALSE)

Arguments

`bucket`	Name of the bucket, or a bucket object
`ifMetagenerationMatch`	Delete only if metageneration matches
`ifMetagenerationNotMatch`	Delete only if metageneration does not match
`force_delete`	If the bucket contains objects it will prevent deletion, including objects in a versioned bucket that previously existed. Setting this to TRUE will force deletion of those objects before deleting the bucket itself.
`include_versions`	Whether to include all historic versions of the objects to delete

Delete an object

Description

Deletes an object from a bucket

Usage

gcs_delete_object(
  object_name,
  bucket = gcs_get_global_bucket(),
  generation = NULL
)
gcs_delete_object(
  object_name,
  bucket = gcs_get_global_bucket(),
  generation = NULL
)

Arguments

object_name

Object to be deleted, or a gs:// URL

bucket

Bucket to delete object from

generation

If present, deletes a specific version.

Default if generation is NULL is to delete the latest version.

Value

If successful, TRUE.

Delete pub/sub notifications for a bucket

Description

Delete notification configurations for a bucket.

Usage

gcs_delete_pubsub(config_name, bucket = gcs_get_global_bucket())
gcs_delete_pubsub(config_name, bucket = gcs_get_global_bucket())

Arguments

`config_name`	The ID of the pubsub configuration
`bucket`	The bucket for notifications

Details

Value

TRUE if successful

Get the download URL

Description

Create the download URL for objects in buckets

Usage

gcs_download_url(object_name, bucket = gcs_get_global_bucket(), public = FALSE)
gcs_download_url(object_name, bucket = gcs_get_global_bucket(), public = FALSE)

Arguments

`object_name`	A vector of object names
`bucket`	A vector of bucket names
`public`	TRUE to return a public URL

Details

bucket names should be length 1 or same length as object_name

Download URLs can be either authenticated behind a login that you may need to update access for via gcs_update_object_acl, or public to all if their predefinedAcl = 'publicRead'

Use the public = TRUE to return the URL accessible to all, which changes the domain name from storage.cloud.google.com to storage.googleapis.com

Value

the URL for downloading objects

Save your R session to the cloud on startup/exit

Description

Place within your .Rprofile to load and save your session data automatically

Usage

gcs_first(bucket = Sys.getenv("GCS_SESSION_BUCKET"))

gcs_last(bucket = Sys.getenv("GCS_SESSION_BUCKET"))
gcs_first(bucket = Sys.getenv("GCS_SESSION_BUCKET"))

gcs_last(bucket = Sys.getenv("GCS_SESSION_BUCKET"))

Arguments

bucket

The bucket holding your session data. See Details.

Details

The folder you want to save to Google Cloud Storage will also need to have a yaml file called _gcssave.yaml in the root of the directory. It can hold the following arguments:

[Required] bucket - the GCS bucket to save to
[Optional] loaddir - if the folder name is different to the current, where to load the R session from
[Optional] pattern - a regex of what files to save at the end of the session
[Optional] load_on_startup - if FALSE will not attempt to load on startup

The bucket name is also set via the environment arg GCE_SESSION_BUCKET. The yaml bucket name will take precedence if both are set.

The folder is named on GCS the full working path to the working directory e.g. /Users/mark/dev/your-r-project which is what is looked for on startup. If you create a new R project with the same filepath and bucket as an existing saved set, the files will download automatically when you load R from that folder (when starting an RStudio project).

If you load from a different filepath (e.g. with loadir set in yaml), when you exit and save the files will be saved under your new present working directory.

Files with the same name will not be overwritten. If you want them to be, delete or rename them then reload the R session.

This function does not act like git, or intended as a replacement - its main use is imagined to be for using RStudio Server within disposable Docker containers on Google Cloud Engine (e.g. via googleComputeEngineR)

For authentication for GCS, the easiest way is to make sure your authentication file is available in environment file GCS_AUTH_FILE, or if on Google Compute Engine it will reuse the Google Cloud authentication via gar_gce_auth

Examples


## Not run: 

.First <- function(){
  googleCloudStorageR::gcs_first()
}


.Last <- function(){
  googleCloudStorageR::gcs_last()
}



## End(Not run)

## Not run: 

.First <- function(){
  googleCloudStorageR::gcs_first()
}


.Last <- function(){
  googleCloudStorageR::gcs_last()
}



## End(Not run)

Get bucket info

Description

Meta data about the bucket

Usage

gcs_get_bucket(
  bucket = gcs_get_global_bucket(),
  ifMetagenerationMatch = NULL,
  ifMetagenerationNotMatch = NULL,
  projection = c("noAcl", "full")
)
gcs_get_bucket(
  bucket = gcs_get_global_bucket(),
  ifMetagenerationMatch = NULL,
  ifMetagenerationNotMatch = NULL,
  projection = c("noAcl", "full")
)

Arguments

`bucket`	Name of a bucket, or a bucket object returned by gcs_create_bucket
`ifMetagenerationMatch`	Return only if metageneration matches
`ifMetagenerationNotMatch`	Return only if metageneration does not match
`projection`	Properties to return. Default noAcl omits acl properties

Value

A bucket resource object

Examples


## Not run: 

buckets <- gcs_list_buckets("your-project")

## use the name of the bucket to get more meta data
bucket_meta <- gcs_get_bucket(buckets$name[[1]])


## End(Not run)

## Not run: 

buckets <- gcs_list_buckets("your-project")

## use the name of the bucket to get more meta data
bucket_meta <- gcs_get_bucket(buckets$name[[1]])


## End(Not run)

Get Bucket Access Controls

Description

Returns the ACL entry for the specified entity on the specified bucket

Usage

gcs_get_bucket_acl(
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers")
)
gcs_get_bucket_acl(
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers")
)

Arguments

bucket

Name of a bucket, or a bucket object returned by gcs_create_bucket

entity

The entity holding the permission. Not needed for entity_type allUsers or allAuthenticatedUsers

entity_type

what type of entity

Used also for when a bucket is updated

Value

Bucket access control object

Examples


## Not run: 

buck_meta <- gcs_get_bucket(projection = "full")

acl <- gcs_get_bucket_acl(entity_type = "project",
                          entity = gsub("project-","",
                                        buck_meta$acl$entity[[1]]))


## End(Not run)
## Not run: 

buck_meta <- gcs_get_bucket(projection = "full")

acl <- gcs_get_bucket_acl(entity_type = "project",
                          entity = gsub("project-","",
                                        buck_meta$acl$entity[[1]]))


## End(Not run)

Get global bucket name

Description

Bucket name set this session to use by default

Usage

gcs_get_global_bucket()
gcs_get_global_bucket()

Details

Set the bucket name via gcs_global_bucket

Value

Bucket name

Get an object in a bucket directly

Description

This retrieves an object directly.

Usage

gcs_get_object(
  object_name,
  bucket = gcs_get_global_bucket(),
  meta = FALSE,
  saveToDisk = NULL,
  overwrite = FALSE,
  parseObject = TRUE,
  parseFunction = gcs_parse_download,
  generation = NULL,
  fields = NULL
)
gcs_get_object(
  object_name,
  bucket = gcs_get_global_bucket(),
  meta = FALSE,
  saveToDisk = NULL,
  overwrite = FALSE,
  parseObject = TRUE,
  parseFunction = gcs_parse_download,
  generation = NULL,
  fields = NULL
)

Arguments

`object_name`	name of object in the bucket that will be URL encoded, or a `gs://` URL
`bucket`	bucket containing the objects. Not needed if using a `gs://` URL
`meta`	If TRUE then get info about the object, not the object itself
`saveToDisk`	Specify a filename to save directly to disk
`overwrite`	If saving to a file, whether to overwrite it
`parseObject`	If saveToDisk is NULL, whether to parse with `parseFunction`
`parseFunction`	If saveToDisk is NULL, the function that will parse the download. Defaults to gcs_parse_download
`generation`	The generation number for the noncurrent version, if you have object versioning enabled in your bucket e.g. `"1560468815691234"`
`fields`	Selector specifying a subset of fields to include in the response.

Details

This differs from providing downloads via a download link as you can do via gcs_download_url

object_name can use a gs:// URI instead, in which case it will take the bucket name from that URI and bucket argument will be overridden. The URLs should be in the form gs://bucket/object/name

By default if you want to get the object straight into an R session the parseFunction is gcs_parse_download which wraps httr's content.

If you want to use your own function (say to unzip the object) then supply it here. The first argument should take the downloaded object.

Value

The object, or TRUE if successfully saved to disk.

Examples


## Not run: 

## something to download
## data.frame that defaults to be called "mtcars.csv"
gcs_upload(mtcars)

## get the mtcars csv from GCS, convert it to an R obj
gcs_get_object("mtcars.csv")

## get the mtcars csv from GCS, save it to disk
gcs_get_object("mtcars.csv", saveToDisk = "mtcars.csv")


## default gives a warning about missing column name.
## custom parse function to suppress warning
f <- function(object){
  suppressWarnings(httr::content(object, encoding = "UTF-8"))
}

## get mtcars csv with custom parse function.
gcs_get_object("mtcars.csv", parseFunction = f)

## download an RDS file using helper gcs_parse_rds()

gcs_get_object("obj.rds", parseFunction = gcs_parse_rds)

## to download from a folder in your bucket
my_folder <- "your_folder/"
objs <- gcs_list_objects(prefix = my_folder)

dir.create(my_folder)

# download all the objects to that folder
dls <- lapply(objs$name, function(x) gcs_get_object(x, saveToDisk = x))



## End(Not run)

## Not run: 

## something to download
## data.frame that defaults to be called "mtcars.csv"
gcs_upload(mtcars)

## get the mtcars csv from GCS, convert it to an R obj
gcs_get_object("mtcars.csv")

## get the mtcars csv from GCS, save it to disk
gcs_get_object("mtcars.csv", saveToDisk = "mtcars.csv")


## default gives a warning about missing column name.
## custom parse function to suppress warning
f <- function(object){
  suppressWarnings(httr::content(object, encoding = "UTF-8"))
}

## get mtcars csv with custom parse function.
gcs_get_object("mtcars.csv", parseFunction = f)

## download an RDS file using helper gcs_parse_rds()

gcs_get_object("obj.rds", parseFunction = gcs_parse_rds)

## to download from a folder in your bucket
my_folder <- "your_folder/"
objs <- gcs_list_objects(prefix = my_folder)

dir.create(my_folder)

# download all the objects to that folder
dls <- lapply(objs$name, function(x) gcs_get_object(x, saveToDisk = x))



## End(Not run)

Check the access control settings for an object for one entity

Description

Returns the default object ACL entry for the specified entity on the specified bucket.

Usage

gcs_get_object_acl(
  object_name,
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers"),
  generation = NULL
)
gcs_get_object_acl(
  object_name,
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers"),
  generation = NULL
)

Arguments

`object_name`	Name of the object
`bucket`	Name of a bucket
`entity`	The entity holding the permission. Not needed for entity_type `allUsers` or `allAuthenticatedUsers`
`entity_type`	The type of entity
`generation`	If present, selects a spcfic revision of the object

Examples


## Not run: 

# single user
gcs_update_object_acl("mtcars.csv", 
     bucket = gcs_get_global_bucket(),
     entity = "[email protected]",
     entity_type = "user"))
     
acl <- gcs_get_object_acl("mtcars.csv", entity = "[email protected]")

# all users
gcs_update_object_acl("mtcars.csv", 
    bucket = gcs_get_global_bucket(),
    entity_type = "allUsers"))
    
acl <- gcs_get_object_acl("mtcars.csv", entity_type = "allUsers")



## End(Not run)
## Not run: 

# single user
gcs_update_object_acl("mtcars.csv", 
     bucket = gcs_get_global_bucket(),
     entity = "[email protected]",
     entity_type = "user"))
     
acl <- gcs_get_object_acl("mtcars.csv", entity = "[email protected]")

# all users
gcs_update_object_acl("mtcars.csv", 
    bucket = gcs_get_global_bucket(),
    entity_type = "allUsers"))
    
acl <- gcs_get_object_acl("mtcars.csv", entity_type = "allUsers")



## End(Not run)

Get the email of service account associated with the bucket

Description

Use this to get the right email so you can give it pubsub.publisher permission.

Usage

gcs_get_service_email(project)
gcs_get_service_email(project)

Arguments

project

The project name containing the bucket

Details

This service email can be different from the email in the service JSON. Give this pubsub.publisher permission in the Google cloud console.

Set global bucket name

Description

Set a bucket name used for this R session

Usage

gcs_global_bucket(bucket)
gcs_global_bucket(bucket)

Arguments

bucket

bucket name you want this session to use by default, or a bucket object

Details

This sets a bucket to a global environment value so you don't need to supply the bucket argument to other API calls.

Value

The bucket name (invisibly)

List buckets

Description

List the buckets your projectId has access to

Usage

gcs_list_buckets(
  projectId,
  prefix = "",
  projection = c("noAcl", "full"),
  maxResults = 1000,
  detail = c("summary", "full")
)
gcs_list_buckets(
  projectId,
  prefix = "",
  projection = c("noAcl", "full"),
  maxResults = 1000,
  detail = c("summary", "full")
)

Arguments

`projectId`	Project containing buckets to list
`prefix`	Filter results to names beginning with this prefix
`projection`	Properties to return. Default noAcl omits acl properties
`maxResults`	Max number of results
`detail`	Set level of detail

Details

Columns returned by detail are:

summary - name, storageClass, location ,updated
full - as above plus: id, selfLink, projectNumber, timeCreated, metageneration, etag

Value

data.frame of buckets

Examples


## Not run: 

buckets <- gcs_list_buckets("your-project")

## use the name of the bucket to get more meta data
bucket_meta <- gcs_get_bucket(buckets$name[[1]])


## End(Not run)

## Not run: 

buckets <- gcs_list_buckets("your-project")

## use the name of the bucket to get more meta data
bucket_meta <- gcs_get_bucket(buckets$name[[1]])


## End(Not run)

List objects in a bucket

Description

List objects in a bucket

Usage

gcs_list_objects(
  bucket = gcs_get_global_bucket(),
  detail = c("summary", "more", "full"),
  prefix = NULL,
  delimiter = NULL,
  versions = FALSE
)
gcs_list_objects(
  bucket = gcs_get_global_bucket(),
  detail = c("summary", "more", "full"),
  prefix = NULL,
  delimiter = NULL,
  versions = FALSE
)

Arguments

`bucket`	bucket containing the objects
`detail`	Set level of detail
`prefix`	Filter results to objects whose names begin with this prefix
`delimiter`	Use to list objects like a directory listing.
`versions`	If `TRUE`, lists all versions of an object as distinct results in order of increasing generation number.

Details

Columns returned by detail are:

summary - name, size, updated
more - as above plus: bucket, contentType, storageClass, timeCreated
full - as above plus: id, selfLink, generation, metageneration, md5Hash, mediaLink, crc32c, etag

delimited returns results in a directory-like mode: items will contain only objects whose names, aside from the prefix, do not contain delimiter. In conjunction with the prefix filter, the use of the delimiter parameter allows the list method to operate like a directory listing, despite the object namespace being flat. For example, if delimiter were set to "/", then listing objects from a bucket that contains the objects "a/b", "a/c", "dddd", "eeee", "e/f" would return objects "dddd" and "eeee", and prefixes "a/" and "e/".

Value

A data.frame of the objects

List pub/sub notifications for a bucket

Description

List notification configurations for a bucket.

Usage

gcs_list_pubsub(bucket = gcs_get_global_bucket())
gcs_list_pubsub(bucket = gcs_get_global_bucket())

Arguments

bucket

The bucket for notifications

Details

Load .RData objects or sessions from the Google Cloud

Description

Load R objects that have been saved using gcs_save or gcs_save_image

Usage

gcs_load(
  file = ".RData",
  bucket = gcs_get_global_bucket(),
  envir = .GlobalEnv,
  saveToDisk = file,
  overwrite = TRUE
)
gcs_load(
  file = ".RData",
  bucket = gcs_get_global_bucket(),
  envir = .GlobalEnv,
  saveToDisk = file,
  overwrite = TRUE
)

Arguments

`file`	Where the files are stored
`bucket`	Bucket the stored objects are in
`envir`	Environment to load objects into
`saveToDisk`	Where to save the loaded file. Default same file name
`overwrite`	If file exists, overwrite. Default TRUE.

Details

The argument file's default is to load an image file called .RData from gcs_save_image into the Global environment.

This would overwrite your existing .RData file in the working directory, so change the file name if you don't wish this to be the case.

Value

TRUE if successful

Make metadata for an object

Description

Use this to pass to uploads in gcs_upload

Usage

gcs_metadata_object(
  object_name = NULL,
  metadata = NULL,
  md5Hash = NULL,
  crc32c = NULL,
  contentLanguage = NULL,
  contentEncoding = NULL,
  contentDisposition = NULL,
  cacheControl = NULL
)
gcs_metadata_object(
  object_name = NULL,
  metadata = NULL,
  md5Hash = NULL,
  crc32c = NULL,
  contentLanguage = NULL,
  contentEncoding = NULL,
  contentDisposition = NULL,
  cacheControl = NULL
)

Arguments

`object_name`	Name of the object. GCS uses this version if also set elsewhere, or a `gs://` URL
`metadata`	User-provided metadata, in key/value pairs
`md5Hash`	MD5 hash of the data; encoded using base64
`crc32c`	CRC32c checksum, as described in RFC 4960, Appendix B; encoded using base64 in big-endian byte order
`contentLanguage`	Content-Language of the object data
`contentEncoding`	Content-Encoding of the object data
`contentDisposition`	Content-Disposition of the object data
`cacheControl`	Cache-Control directive for the object data

Value

Object metadata for uploading of class gar_Object

Parse downloaded objects straight into R

Description

Wrapper for httr's content. This is the default function used in gcs_get_object

Usage

gcs_parse_download(object, encoding = "UTF-8")

gcs_parse_rds(object)
gcs_parse_download(object, encoding = "UTF-8")

gcs_parse_rds(object)

Arguments

`object`	The object downloaded
`encoding`	Default to UTF-8

Details

gcs_parse_rds will parse .rds files created via saveRDS without saving to disk

Retry a resumeable upload

Description

Used internally in gcs_upload, you can also use this for failed uploads within one week of generating the upload URL

Usage

gcs_retry_upload(
  retry_object = NULL,
  upload_url = NULL,
  file = NULL,
  type = NULL
)
gcs_retry_upload(
  retry_object = NULL,
  upload_url = NULL,
  file = NULL,
  type = NULL
)

Arguments

`retry_object`	A object of class `gcs_upload_retry`.
`upload_url`	As created in a failed upload via gcs_upload
`file`	The file location to upload
`type`	The file type, guessed if NULL Either supply a retry object, or the upload_url, file and type manually yourself. The function will first check to see how much has been uploaded already, then try to send up the remaining bytes.

Value

If successful, an object metadata object, if not an gcs_upload_retry object.

Save .RData objects to the Google Cloud

Description

Performs save then saves it to Google Cloud Storage.

Usage

gcs_save(..., file, bucket = gcs_get_global_bucket(), envir = parent.frame())
gcs_save(..., file, bucket = gcs_get_global_bucket(), envir = parent.frame())

Arguments

`...`	The names of the objects to be saved (as symbols or character strings).
`file`	The file name that will be uploaded (conventionally with file extension `.RData`)
`bucket`	Bucket to store objects in
`envir`	Environment to search for objects to be saved

Details

For all session data use gcs_save_image instead.

gcs_save(ob1, ob2, ob3, file = "mydata.RData") will save the objects specified to an .RData file then save it to Cloud Storage, to be loaded later using gcs_load.

For any other use, its better to use gcs_upload and gcs_get_object instead.

Restore the R objects using gcs_load(bucket = "your_bucket")

This will overwrite any data within your local environment with the same name.

Value

The GCS object

Save/Load all files in directory to Google Cloud Storage

Description

This function takes all the files in the directory, zips them, and saves/loads/deletes them to the cloud. The upload name will be the directory name.

Usage

gcs_save_all(
  directory = getwd(),
  bucket = gcs_get_global_bucket(),
  pattern = "",
  predefinedAcl = c("private", "bucketLevel", "authenticatedRead",
    "bucketOwnerFullControl", "bucketOwnerRead", "projectPrivate", "publicRead",
    "default")
)

gcs_load_all(
  directory = getwd(),
  bucket = gcs_get_global_bucket(),
  exdir = directory,
  list = FALSE
)

gcs_delete_all(directory = getwd(), bucket = gcs_get_global_bucket())
gcs_save_all(
  directory = getwd(),
  bucket = gcs_get_global_bucket(),
  pattern = "",
  predefinedAcl = c("private", "bucketLevel", "authenticatedRead",
    "bucketOwnerFullControl", "bucketOwnerRead", "projectPrivate", "publicRead",
    "default")
)

gcs_load_all(
  directory = getwd(),
  bucket = gcs_get_global_bucket(),
  exdir = directory,
  list = FALSE
)

gcs_delete_all(directory = getwd(), bucket = gcs_get_global_bucket())

Arguments

`directory`	The folder to upload/download
`bucket`	Bucket to store within
`pattern`	An optional regular expression. Only file names which match the regular expression will be saved.
`predefinedAcl`	Specify user access to object. Default is 'private'. Set to 'bucketLevel' for buckets with bucket level access enabled.
`exdir`	When downloading, specify a destination directory if required
`list`	When downloading, only list where the files would unzip to

Details

Zip/unzip is performed before upload and after download using zip.

Value

When uploading the GCS meta object; when downloading TRUE if successful

Examples


## Not run: 

gcs_save_all(
  directory = "path-to-all-images",
  bucket = "my-bucket",
  predefinedAcl = "bucketLevel")

## End(Not run)
## Not run: 

gcs_save_all(
  directory = "path-to-all-images",
  bucket = "my-bucket",
  predefinedAcl = "bucketLevel")

## End(Not run)

Save an R session to the Google Cloud

Description

Performs save.image then saves it to Google Cloud Storage.

Usage

gcs_save_image(
  file = ".RData",
  bucket = gcs_get_global_bucket(),
  saveLocation = NULL,
  envir = parent.frame()
)
gcs_save_image(
  file = ".RData",
  bucket = gcs_get_global_bucket(),
  saveLocation = NULL,
  envir = parent.frame()
)

Arguments

`file`	Where to save the file in GCS and locally
`bucket`	Bucket to store objects in
`saveLocation`	Which folder in the bucket to save file
`envir`	Environment to save from

Details

gcs_save_image(bucket = "your_bucket") will save all objects in the workspace to .RData folder on Google Cloud Storage within your_bucket.

Restore the objects using gcs_load(bucket = "your_bucket")

This will overwrite any data with the same name in your current local environment.

Value

The GCS object

Help set-up googleCloudStorageR

Description

Use this to make a wizard to walk through set-up steps

Usage

gcs_setup()
gcs_setup()

Details

This function assumes you have at least a Google Cloud Platform project setup, from which it can generate the necessary authentication keys and set up authentication.

It uses gar_setup_menu to create the wizard. You will need to have owner access to the project you are using.

After each menu option has completed, restart R and reload the library and this function to continue to the next step.

Upon successful set-up, you should see a message similar to Successfully auto-authenticated via /xxxx/googlecloudstorager-auth-key.json and Set default bucket name to 'xxxx' when you load the library via library(googleCloudStorageR)

Examples


## Not run: 

library(googleCloudStorageR)
gcs_setup()


## End(Not run)

## Not run: 

library(googleCloudStorageR)
gcs_setup()


## End(Not run)

Create a signed URL

Description

This creates a signed URL which you can share with others who may or may not have a Google account. The object will be available until the specified timestamp.

Usage

gcs_signed_url(
  meta_obj,
  expiration_ts = Sys.time() + 3600,
  verb = "GET",
  md5hash = NULL,
  includeContentType = FALSE
)
gcs_signed_url(
  meta_obj,
  expiration_ts = Sys.time() + 3600,
  verb = "GET",
  md5hash = NULL,
  includeContentType = FALSE
)

Arguments

`meta_obj`	A meta object from gcs_get_object
`expiration_ts`	A timestamp of class `"POSIXct"` such as from `Sys.time()` or a numeric in seconds from Unix Epoch. Default is 60 mins.
`verb`	The URL verb of access e.g. `GET` or `PUT`. Default `GET`
`md5hash`	An optional md5 digest value
`includeContentType`	For getting the URL via browsers this should be set to `FALSE` (the default). Otherwise, set to `TRUE` to include the content type of the object in the request needed.

Details

Create a URL with a time-limited read and write to an object, regardless whether they have a Google account

Examples


## Not run: 

obj <- gcs_get_object("your_file", meta = TRUE)

signed <- gcs_signed_url(obj)

temp <- tempfile()
on.exit(unlink(temp))

download.file(signed, destfile = temp)
file.exists(temp)


## End(Not run)

## Not run: 

obj <- gcs_get_object("your_file", meta = TRUE)

signed <- gcs_signed_url(obj)

temp <- tempfile()
on.exit(unlink(temp))

download.file(signed, destfile = temp)
file.exists(temp)


## End(Not run)

Source an R script from the Google Cloud

Description

Download an R script and run it immediately via source

Usage

gcs_source(script, bucket = gcs_get_global_bucket(), ...)
gcs_source(script, bucket = gcs_get_global_bucket(), ...)

Arguments

`script`	The name of the script on GCS
`bucket`	Bucket the stored objects are in
`...`	Passed to source

Value

TRUE if successful

Change access to an object in a bucket

Description

Updates Google Cloud Storage ObjectAccessControls

Usage

gcs_update_object_acl(
  object_name,
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers"),
  role = c("READER", "OWNER")
)
gcs_update_object_acl(
  object_name,
  bucket = gcs_get_global_bucket(),
  entity = "",
  entity_type = c("user", "group", "domain", "project", "allUsers",
    "allAuthenticatedUsers"),
  role = c("READER", "OWNER")
)

Arguments

`object_name`	Object to update
`bucket`	Google Cloud Storage bucket
`entity`	entity to update or add, such as an email
`entity_type`	what type of entity
`role`	Access permission for entity

Details

An entity is an identifier for the entity_type.

entity="user" may have userId or email
entity="group" may have groupId or email
entity="domain" may have domain
entity="project" may have team-projectId

For example:

entity="user" could be [email protected]
entity="group" could be [email protected]
entity="domain" could be example.com which is a Google Apps for Business domain.

Value

TRUE if successful

Upload a file of arbitrary type

Description

Upload up to 5TB

Usage

gcs_upload(
  file,
  bucket = gcs_get_global_bucket(),
  type = NULL,
  name = deparse(substitute(file)),
  object_function = NULL,
  object_metadata = NULL,
  predefinedAcl = c("private", "bucketLevel", "authenticatedRead",
    "bucketOwnerFullControl", "bucketOwnerRead", "projectPrivate", "publicRead",
    "default"),
  upload_type = c("simple", "resumable")
)

gcs_upload_set_limit(upload_limit = 5e+06)
gcs_upload(
  file,
  bucket = gcs_get_global_bucket(),
  type = NULL,
  name = deparse(substitute(file)),
  object_function = NULL,
  object_metadata = NULL,
  predefinedAcl = c("private", "bucketLevel", "authenticatedRead",
    "bucketOwnerFullControl", "bucketOwnerRead", "projectPrivate", "publicRead",
    "default"),
  upload_type = c("simple", "resumable")
)

gcs_upload_set_limit(upload_limit = 5e+06)

Arguments

`file`	data.frame, list, R object or filepath (character) to upload file
`bucket`	bucketname you are uploading to
`type`	MIME type, guessed from file extension if NULL
`name`	What to call the file once uploaded. Default is the filepath
`object_function`	If not NULL, a `function(input, output)`
`object_metadata`	Optional metadata for object created via gcs_metadata_object
`predefinedAcl`	Specify user access to object. Default is 'private'. Set to 'bucketLevel' for buckets with bucket level access enabled.
`upload_type`	Override automatic decision on upload type
`upload_limit`	Upload limit in bytes

Details

When using object_function it expects a function with two arguments:

input The object you supply in file to write from
output The filename you write to

By default the upload_type will be 'simple' if under 5MB, 'resumable' if over 5MB. Use gcs_upload_set_limit to modify this boundary - you may want it smaller on slow connections, higher on faster connections. 'Multipart' upload is used if you provide a object_metadata.

If object_function is NULL and file is not a character filepath, the defaults are:

file's class is data.frame - write.csv
file's class is list - toJSON

If object_function is not NULL and file is not a character filepath, then object_function will be applied to the R object specified in file before upload. You may want to also use name to ensure the correct file extension is used e.g. name = 'myobject.feather'

If file or name argument contains folders e.g. /data/file.csv then the file will be uploaded with the same folder structure e.g. in a /data/ folder. Use name to override this.

Value

If successful, a metadata object

scopes

Requires scopes https://storage.googleapis.com/auth/devstorage.read_write or https://storage.googleapis.com/auth/devstorage.full_control

Examples


## Not run: 

## set global bucket so don't need to keep supplying in future calls
gcs_global_bucket("my-bucket")

## by default will convert dataframes to csv
gcs_upload(mtcars)

## mtcars has been renamed to mtcars.csv
gcs_list_objects()

## to specify the name, use the name argument
gcs_upload(mtcars, name = "my_mtcars.csv")

## when looping, its best to specify the name else it will take
## the deparsed function call e.g. X[[i]]
my_files <- list.files("my_uploads")
lapply(my_files, function(x) gcs_upload(x, name = x))

## you can supply your own function to transform R objects before upload
f <- function(input, output){
  write.csv2(input, file = output)
}

gcs_upload(mtcars, name = "mtcars_csv2.csv", object_function = f)

# upload to a bucket with bucket level ACL set
gcs_upload(mtcars, predefinedAcl = "bucketLevel")

# modify boundary between simple and resumable uploads
# default 5000000L is 5MB
gcs_upload_set_limit(1000000L)

## End(Not run)



## Not run: 

## set global bucket so don't need to keep supplying in future calls
gcs_global_bucket("my-bucket")

## by default will convert dataframes to csv
gcs_upload(mtcars)

## mtcars has been renamed to mtcars.csv
gcs_list_objects()

## to specify the name, use the name argument
gcs_upload(mtcars, name = "my_mtcars.csv")

## when looping, its best to specify the name else it will take
## the deparsed function call e.g. X[[i]]
my_files <- list.files("my_uploads")
lapply(my_files, function(x) gcs_upload(x, name = x))

## you can supply your own function to transform R objects before upload
f <- function(input, output){
  write.csv2(input, file = output)
}

gcs_upload(mtcars, name = "mtcars_csv2.csv", object_function = f)

# upload to a bucket with bucket level ACL set
gcs_upload(mtcars, predefinedAcl = "bucketLevel")

# modify boundary between simple and resumable uploads
# default 5000000L is 5MB
gcs_upload_set_limit(1000000L)

## End(Not run)

Change or fetch bucket version status

Description

Turn bucket versioning on or off, check status (default), or list archived versions of objects in the bucket and view their generation numbers.

Usage

gcs_version_bucket(bucket, action = c("status", "enable", "disable", "list"))
gcs_version_bucket(bucket, action = c("status", "enable", "disable", "list"))

Arguments

`bucket`	gcs bucket
`action`	"status", "enable", "disable", or "list"

Value

If action="list" a versioned_objects dataframe If action="status" a boolean on if versioning is TRUE or FALSE If action="enable" or "disable" TRUE if operation is successful

Examples


## Not run: 
  buck <- gcs_get_global_bucket()
  gcs_version_bucket(buck, action = "disable")
  
  gcs_version_bucket(buck, action = "status")
  # Versioning is NOT ENABLED for "your-bucket"
  gcs_version_bucket(buck, action = "enable")
  # TRUE
  gcs_version_bucket(buck, action = "status")
  # Versioning is ENABLED for "your-bucket"
  gcs_version_bucket(buck, action = "list")



## End(Not run)

## Not run: 
  buck <- gcs_get_global_bucket()
  gcs_version_bucket(buck, action = "disable")
  
  gcs_version_bucket(buck, action = "status")
  # Versioning is NOT ENABLED for "your-bucket"
  gcs_version_bucket(buck, action = "enable")
  # TRUE
  gcs_version_bucket(buck, action = "status")
  # Versioning is ENABLED for "your-bucket"
  gcs_version_bucket(buck, action = "list")



## End(Not run)

Get the Google Cloud Storage API host to use for requests

Description

Uses the STORAGE_EMULATOR_HOST environment variable if set, otherwise uses the default host (the real Google Cloud Storage API).

Usage

get_storage_host()
get_storage_host()

Value

The host to use for requests (includes scheme, host and port)

googleCloudStorageR

Description

Interact with Google Cloud Storage API in R. Part of the 'cloudyr' project.

Check if the Google Cloud Storage API is emulated

Description

Check if the Google Cloud Storage API is emulated

Usage

is.storage_emulated()
is.storage_emulated()

Value

TRUE if the Google Cloud Storage API is emulated, FALSE otherwise

Package 'googleCloudStorageR'

Help Index

Authenticate with Google Cloud Storage API

Description

Usage

Arguments

Details

Examples

Compose up to 32 objects into one

Description

Usage

Arguments

Value

See Also

Examples

Copy an object

Description

Usage

Arguments

Value

See Also

Create a new bucket

Description

Usage

Arguments

Details

See Also

Create a Bucket Access Controls

Description

Usage

Arguments

Value

See Also

Create a lifecycle condition

Description

Usage

Arguments

See Also

Examples

Create a pub/sub notification for a bucket

Description

Usage

Arguments

Details

See Also

Examples

Delete a bucket

Description

Usage

Arguments

See Also

Delete an object

Description

Usage

Arguments

Value

See Also

Delete pub/sub notifications for a bucket

Description

Usage

Arguments

Details

Value

See Also

Get the download URL

Description

Usage

Arguments

Details

Value

See Also

Save your R session to the cloud on startup/exit

Description

Usage

Arguments

Details

See Also

Examples

Get bucket info

Description