从源代码重新加载自定义R包

Question

I have created a custom package and would like to deploy it to a remote machine. Here is my current long workflow:

• Create custom package 'my_package_0.1.0.tar.gz'
• scp package to remote machine
• create Remote session
• install.packages("/path/to/my_package0.1.0.tar.gz")
• library('my_package')

When others connect to the machine, they have to run install and library:

• install.packages("/path/to/my_package0.1.0.tar.gz")
• library('my_package')

Is there a way I can share a custom package and have the workflow be:

• Create remote session
• Load package with library('my_package')

Answer 1

Feedback in comments says the best practice is to install the package in a shared location.

Here is how you can find a good place to install the packages.

Running the following shows where libraries are loaded from

.libPaths()
# rserve2 rserve2 /opt/deployr/9.0.1/rserve/R
#root root        /usr/lib64/microsoft-r/3.3/lib64/R/library

There are two locations the R server is looking for libraries. One is owned by root so we shouldn't deploy here. The other location rserve2 has owndership and looks promising. We should create a library subfolder to store the shared packages.

Based on this information, the work flow should be:

• Create custom package 'my_package_0.1.0.tar.gz'
• scp package to remote machine
• create Remote session
• install.packages("/path/to/my_package0.1.0.tar.gz", lib='/opt/deployr/9.0.1/rserve/R/library/' )
• library('my_package')

When others connect to the machine, they can load the shared library:

• library('my_package')