configure_environment: Configure a Python Environment

View source: R/python-packages.R

configure_environmentR Documentation

Configure a Python Environment

Description

Configure a Python environment, satisfying the Python dependencies of any loaded R packages.

Usage

configure_environment(package = NULL, force = FALSE)

Arguments

package

The name of a package to configure. When NULL, reticulate will instead look at all loaded packages and discover their associated Python requirements.

force

Boolean; force configuration of the Python environment? Note that configure_environment() is a no-op within non-interactive R sessions. Use this if you require automatic environment configuration, e.g. when testing a package on a continuous integration service.

Details

Normally, this function should only be used by package authors, who want to ensure that their package dependencies are installed in the active Python environment. For example:

.onLoad <- function(libname, pkgname) {
  reticulate::configure_environment(pkgname)
}

If the Python session has not yet been initialized, or if the user is not using the default Miniconda Python installation, no action will be taken. Otherwise, reticulate will take this as a signal to install any required Python dependencies into the user's Python environment.

If you'd like to disable reticulate's auto-configure behavior altogether, you can set the environment variable:

RETICULATE_AUTOCONFIGURE = FALSE

e.g. in your ~/.Renviron or similar.

Note that, in the case where the Python session has not yet been initialized, reticulate will automatically ensure your required Python dependencies are installed after the Python session is initialized (when appropriate).


reticulate documentation built on Jan. 8, 2023, 1:09 a.m.