greta (version 0.6.0)

greta_set_python: Choose the Python environment greta uses

Description

greta runs on Python (via TensorFlow and TensorFlow Probability). By default it uses uv (via the reticulate R package) to install a compatible Python, TensorFlow, and TensorFlow Probability automatically on first use. greta_set_python() persistently selects which Python environment greta uses: the managed (uv) environment, a conda environment (for example one created by install_greta_deps()), or your own Python. greta_reset_python() clears the stored choice, returning to greta's automatic resolution.

To choose which versions of TensorFlow and TensorFlow Probability the managed (uv) environment installs, see greta_set_deps() - dependency versions are separate from the choice of Python environment.

Usage

greta_set_python(backend = c("uv", "conda", "path"), path = NULL, name = NULL)
greta_reset_python()

Value

Invisibly, the stored preference (NULL for greta_reset_python()).

Arguments

backend

Which Python environment to use. One of:

• "uv" (default): the managed (uv) environment. reticulate installs a compatible Python, TensorFlow, and TensorFlow Probability automatically on first use.

• "conda": a conda environment, named by name.

• "path": a specific Python, given by path.

path

Only for backend = "path". Path to a Python executable, or to an environment directory (a virtualenv or conda prefix) containing one. When given a directory, greta looks for bin/python (Unix) or Scripts/python.exe (Windows) inside it. Pointing at an already-installed environment on disk never downloads anything, which makes it useful for offline or restricted-network setups.

name

Only for backend = "conda". Name of the conda environment to use. Defaults to "greta-env-tf2", the environment created by install_greta_deps().

Details

greta resolves which Python to use, in this order:

1. The RETICULATE_PYTHON environment variable, if set (usually in ~/.Renviron, your .Rprofile, or your shell environment). This always wins: it takes precedence over any stored preference.

2. Your stored preference, set with greta_set_python().

3. An auto-detected "greta-env-tf2" conda environment (created by install_greta_deps()) - kept so setups from older greta versions keep working after upgrading.

4. Otherwise, the managed (uv) environment (the default as of greta 0.6.0): reticulate installs a compatible Python, TensorFlow, and TensorFlow Probability automatically on first use. No setup is needed - this happens "automagically".

For the managed (uv) environment, greta automatically enables uv's offline mode once the environment is installed, so it no longer reaches out to PyPI. Set UV_OFFLINE=0 yourself to force online resolution (for example, to refresh the environment), or UV_OFFLINE=1 to force offline mode - greta never overrides a value you have already set.

To check which Python greta is currently using, and which it will use after a restart, call greta_sitrep().

If a stored preference appears to be ignored, RETICULATE_PYTHON is usually why: remove it from wherever it is set (for example ~/.Renviron), then restart R. Note that Sys.unsetenv() within a session is not enough, as the choice is applied when greta loads.

Your choice is stored under tools::R_user_dir("greta", "config") and applied the next time greta is loaded, so you will need to restart R for it to take effect.

See Also

greta_set_deps(), greta_sitrep(), install_greta_deps(), greta_remove()

Examples

if (FALSE) {
# use the managed (uv) environment (the default)
greta_set_python()

# use the conda environment from install_greta_deps()
greta_set_python("conda")

# use a differently-named conda environment
greta_set_python("conda", name = "my-tf-env")

# use a specific Python binary, or an environment directory
greta_set_python("path", path = "/path/to/python")
greta_set_python("path", path = "/opt/python-envs/greta")

# clear the stored choice and return to automatic resolution
greta_reset_python()
}