Miniconda, Python, and Matlab (experimental) Environment
The goal of rpymat is to create a single isolated Miniconda and Python environment for reproducible pipeline scripts. The package is a shell of reticulate package, but provides more stable behaviors, especially on 'ARM' machines.
You can install the released version of rpymat from CRAN with:
install.packages("rpymat")
Configure python after installation
# change `python_ver` accordingly rpymat::configure_conda(python_ver = 'auto')
Add Python or conda packages
# Add conda packages
rpymat::add_packages(c('pandas', 'numpy'))
# Add conda packages from channels
rpymat::add_packages(c('h5py'), channel = "conda-forge")
# Add pip packages
rpymat::add_packages(c('sklearn'), pip = TRUE)
# Install Jupyterlab, will install # numpy, h5py, matplotlib, pandas, # jupyter, jupyterlab, jupyterlab-git, ipywidgets, jupyter-server-proxy # jupyterlab_latex, jupyterlab_github, matlab_kernel rpymat::add_jupyter() # Launch Jupyterlab rpymat::jupyter_launch(async = FALSE)
rpymat::jupyter_launch(
async = TRUE, workdir = "~",
port = 18888, open_browser = TRUE,
token = "IwontTellYouMyToken"
)
To query existing servers
rpymat::jupyter_server_list() #> host port token #> 1 127.0.0.1 8888 3hzWfGPa0EOmonaNS48jrTvpw07KiX7VKerA9ZTFJMkCOJMgfB #> 2 127.0.0.1 18888 IwontTellYouMyToken
To stop a server
rpymat::jupyter_server_stop(port = 18888)Use
rpymat with reticulate
# Initialize the isolated environment rpymat::ensure_rpymat() rpymat::repl_python()
Then run python code interactively.
Alternatively, you can use rpymat::run_script(path) to execute Python scripts, and use reticulate::py to obtain the results.
The following command will erase the environment completely.
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