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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:

Configure environment

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)

Use Jupyterlab

# Install Jupyterlab, will install
# numpy, h5py, matplotlib, pandas, 
# jupyter, jupyterlab, jupyterlab-git, ipywidgets, jupyter-server-proxy
# jupyterlab_latex, jupyterlab_github, matlab_kernel

# Launch Jupyterlab
rpymat::jupyter_launch(async = FALSE)

Advanced configurations:

    async = TRUE, workdir = "~",
    port = 18888, open_browser = TRUE,
    token = "IwontTellYouMyToken"

To query existing servers

#>        host  port                                              token
#> 1  8888 3hzWfGPa0EOmonaNS48jrTvpw07KiX7VKerA9ZTFJMkCOJMgfB
#> 2 18888                                IwontTellYouMyToken

To stop a server

rpymat::jupyter_server_stop(port = 18888)

Use rpymat with reticulate

# Initialize the isolated environment



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.