https://github.com/cloudyr/googleComputeEngineR

An R interface to the Google Cloud Compute API, for launching virtual machines
https://github.com/cloudyr/googleComputeEngineR

api cloud-computing cloudyr google-cloud googleauthr launching-virtual-machines r

Last synced: about 1 month ago
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An R interface to the Google Cloud Compute API, for launching virtual machines

• Host: GitHub
• URL: https://github.com/cloudyr/googleComputeEngineR
• Owner: cloudyr
• License: other
• Created: 2016-09-23T11:39:19.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-06-01T20:56:48.000Z (over 2 years ago)
• Last Synced: 2024-11-28T20:37:28.580Z (about 1 month ago)
• Topics: api, cloud-computing, cloudyr, google-cloud, googleauthr, launching-virtual-machines, r
• Language: R
• Homepage: https://cloudyr.github.io/googleComputeEngineR/
• Size: 7.1 MB
• Stars: 152
• Watchers: 11
• Forks: 41
• Open Issues: 44
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE

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• jimsghstars - cloudyr/googleComputeEngineR - An R interface to the Google Cloud Compute API, for launching virtual machines (R)

README

        
# googleComputeEngineR

[![CRAN](http://www.r-pkg.org/badges/version/googleComputeEngineR)](http://cran.r-project.org/package=googleComputeEngineR)

[![Build Status](https://travis-ci.org/cloudyr/googleComputeEngineR.png?branch=master)](https://travis-ci.org/cloudyr/googleComputeEngineR)

[![codecov.io](https://codecov.io/github/cloudyr/googleComputeEngineR/coverage.svg?branch=master)](https://codecov.io/github/cloudyr/googleComputeEngineR?branch=master)

`googleComputeEngineR` provides an R interface to the Google Cloud Compute Engine API, for launching virtual machines.  It looks to make the deployment of cloud resources for R as painless as possible, and includes some special templates to launch R-specific resources such as RStudio, Shiny, and OpenCPU with a few lines from your local R session.

> See all documentation on the [googleComputeEngineR website](https://cloudyr.github.io/googleComputeEngineR/)

## TL;DR - Creating an RStudio server VM

1. Configure a Google Cloud Project with billing.

2. Download a service account key JSON file.

3. Put your default project, zone and JSON file location in your `.Renviron`.

4. Run `library(googleComputeEngineR)` and auto-authenticate.

5. Run `vm <- gce_vm(template = "rstudio", name = "rstudio-server", username = "mark", password = "mark1234")` (or other credentials) to start up an RStudio Server.

6. Wait for it to install, login via the returned URL.

A video guide to setup and launching an RStudio server has been kindly created by Donal Phipps and is [available at this link](https://www.youtube.com/watch?v=1oM0NZbRhSI).

 

## Thanks to

* Scott Chamberlin for the [analogsea](https://github.com/sckott/analogsea) package for launching Digital Ocean VMs, which inspired the SSH connector functions for this one.

* Winston Chang for the [harbor](https://github.com/wch/harbor/) package where the docker functions come from.  If `harbor` will be published to CRAN, it will become a dependency for this one.

* Henrik Bengtsson for help in integrating the fantastic [future](https://cran.r-project.org/web/packages/future/index.html) package that allows asynchronous R functions run in GCE clusters.

* Carl Boettiger and Dirk Eddelbuettel for [rocker](https://hub.docker.com/u/rocker/) that Docker containers some of the R templates used in this package. 

## Install

CRAN version:

```r

install.packages("googleComputeEngineR")

```

Development version:

```r

if (!require("ghit")) {

    install.packages("ghit")

}

ghit::install_github("cloudyr/googleComputeEngineR")

```

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[![cloudyr project logo](http://i.imgur.com/JHS98Y7.png)](https://github.com/cloudyr)