R: Configure a Python Environment

configure_environment {reticulate} | R 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).

[Package reticulate version 1.23 Index]