This article covers the step-by-step instructions for installing the Azure ML SDK for R.

You do not need run this if you are working on an Azure Machine Learning Compute Instance, as the compute instance already has the Azure ML SDK preinstalled.

## Install Conda

If you do not have Conda already installed on your machine, you will first need to install it, since the Azure ML R SDK uses reticulate to bind to the Python SDK. We recommend installing Miniconda, which is a smaller, lightweight version of Anaconda. Choose the 64-bit binary for Python 3.5 or later.

## Install the azuremlsdk R package

The stable release of the Azure ML SDK can be installed from CRAN or the development version can be installed from GitHub. You will need remotes to install the azuremlsdk package.

install.packages('remotes')

Then, you can use the install_github or install_cran functions to install the package.

remotes::install_github('https://github.com/Azure/azureml-sdk-for-r')

remotes::install_cran('azuremlsdk', repos = 'https://cloud.r-project.org/')

If you are using R installed from CRAN, which comes with 32-bit and 64-bit binaries, you may need to specify the parameter INSTALL_opts=c("--no-multiarch") to only build for the current 64-bit architecture.

remotes::install_cran('azuremlsdk', repos = 'https://cloud.r-project.org/', INSTALL_opts=c("--no-multiarch"))

## Install the Azure ML Python SDK

Lastly, use the azuremlsdk R library to install the latest version of the Python SDK.

If using an Azure Machine Learning Compute Instance or a CRAN installation with reticulate >= 1.14, use the azuremlsdk::install_azureml() function with the conda environment set to r-reticulate.

azuremlsdk::install_azureml(envname = 'r-reticulate')

If using a CRAN installation with reticulate < 1.14 or a GitHub installation, the correct conda environment will be selected automatically. There is no need to specify the envname parameter.

azuremlsdk::install_azureml()

If you would like to override the default version, environment name, or Python version, you can pass in those arguments. If you would like to restart the R session after installation or delete the conda environment if it already exists and create a new environment, you can also do so:

azuremlsdk::install_azureml(version = NULL,
envname = "<your conda environment name>",
conda_python_version = "<desired python version>",
restart_session = TRUE,
remove_existing_env = TRUE)

## Test installation

You can confirm your installation worked by loading the library and successfully retrieving a run.

library(azuremlsdk)
get_current_run()

## Troubleshooting

• In step 3 of the installation, if you get ssl errors on windows, it is due to an outdated openssl binary. Install the latest openssl binaries from here.

• If installation fails due to this error:

Error in strptime(xx, f, tz = tz) :
(converted from warning) unable to identify current timezone 'C':
please set environment variable 'TZ'
In R CMD INSTALL
Error in i.p(...) :
(converted from warning) installation of package ‘C:/.../azureml_0.4.0.tar.gz’ had non-zero exit
status

You will need to set your time zone environment variable to GMT and restart the installation process.

Sys.setenv(TZ='GMT')
• If the following permission error occurs while installing in RStudio, change your RStudio session to administrator mode, and re-run the installation command.

Downloading GitHub repo Azure/azureml-sdk-for-r@master
Skipping 2 packages ahead of CRAN: reticulate, rlang
Running R CMD build...

Error: (converted from warning) invalid package
'C:/.../file2b441bf23631'
In R CMD INSTALL
Error in i.p(...) :
(converted from warning) installation of package
‘C:/.../file2b441bf23631’ had non-zero exit status
In addition: Warning messages:
1: In file(con, "r") :
cannot open file 'C:...\file2b44144a540f': Permission denied
2: In file(con, "r") :
cannot open file 'C:...\file2b4463c21577': Permission denied