# Python Version Configuration

## Locating Python

It is not uncommon for several installations of Python to be available on a given system. The reticulate package can bind to almost any Python installations, and provides a variety of convenient ways to allow the user to implicitly or explicitly specify which Python installation to select.

Note that for reticulate to bind to a version of Python it must have been compiled with shared library support (i.e. with the `--enable-shared` flag).

Consider the following code:

    library(reticulate)
    py_eval("1+1")

In this case, reticulate will search for a suitable Python installation. In the absence of other hints (detailed below), reticulate will fallback to an environment named “r-reticulate”, creating it if necessary.

Consider another case:

    library(reticulate)
    scipy <- import("scipy")
    scipy$amin(c(1,3,5,7))

In this case, reticulate will first look for an environment named “r-scipy”, and if that doesn’t exist, it will fallback to the environment named “r-reticulate”.

## Providing Hints

There are a few ways you can provide hints as to which version of Python should be used:

1. By setting the value of the `RETICULATE_PYTHON` environment variable to a Python binary. Note that if you set this environment variable, then the specified version of Python will always be used (i.e. this is prescriptive rather than advisory). To set the value of `RETICULATE_PYTHON`, insert `Sys.setenv(RETICULATE_PYTHON = PATH)` into your project’s .Rprofile, where `PATH` is your preferred Python binary.

2. By calling one of the these functions:

Function | Description
--- | ---
`use_python()` | Specify the path a specific Python binary.
`use_virtualenv()` | Specify the name of (or path to) a Python virtualenv.
`use_condaenv()` | Specify the name of a Conda environment.

For example:

    library(reticulate)
    use_python("/usr/local/bin/python")
    use_virtualenv("~/myenv")
    use_condaenv("myenv")

If the `use_virtualenv()` function is supplied a name of a virtual environment (as opposed to a path), it will look in the virtualenv root directory, by default `~/.virtualenvs`, and configurable by setting the environment variable `WORKON_HOME`.

The `use_condaenv()` function will use whatever conda binary is found on the `PATH`. If you want to use a specific alternate version you can use the `conda` parameter. For example:

    use_condaenv(condaenv = "r-nlp", conda = "/opt/anaconda3/bin/conda")

Note that the `use_*()` functions take an optional `required` argument. By default, a value of `required = NULL` is equivalent to `required = TRUE` in most circumstances. If `required = FALSE` is supplied, then the call is considered an optional hint as to where to find Python (i.e. it doesn’t produce an error if the specified version doesn’t exist).

## Order of Discovery

The order in which Python installation will be discovered and used is as follows:

1. If specified, the location referenced by the `RETICULATE_PYTHON` environment variable. (Path to a Python binary)

2. If specified, the location referenced by the `RETICULATE_PYTHON_ENV` environment variable. (Path to or name of a virtual environment or conda environment)

3. If specified, the location referenced by calls to `use_python()`, `use_virtualenv()`, and `use_condaenv()` with `required = TRUE` (the default).

4. If the environment variable `VIRTUAL_ENV` is defined (typically from running an `activate` script before R started, or from having the “Automatically activate project-local Python environments” option enabled in the RStudio IDE), then the Python from the activated environment is used.

5. If the current working directory contains a pyproject.toml file from a poetry environment, the Python installation from the poetry environment is used.

6. If the current working directory contains a Pipfile associated with a pipenv, the Python installation from pipenv is used.

7. If the current working directory contains a directory named “venv”, “virtualenv”, “.venv”, or “.virtualenv”, and that directory is a Python virtual environment, the Python from the virtual environment is used.

8. If there was a call (typically from within a package using reticulate), of the form: `import("bar", delay_load = list(environment = "r-barlyr")`, and there exists a virtual environment or conda environment named `"r-barlyr"`, it is used.

9. If any call to `use_python()`, `use_virtualenv()`, or `use_condaenv()` was made with `required = FALSE`, or from within a packages `.onLoad()` function, and the referenced python installation exists, it is used.

10. If there was a call to `import("bar")`, and there exists a virtual environment or conda environment named `"r-bar"`, it is used.

11. If specified, the location referenced by the `RETICULATE_PYTHON_FALLBACK` environment variable. (Path to a python binary)

12. In the absence of any expression of preference via one of the ways outlined above, reticulate falls back to using a virtual environment named `"r-reticulate"`. If one does not exist, reticulate will offer to create one.

13. If the “r-reticulate” environment is not available and cannot be created, then we fall back to using the Python on the `PATH`, or on Windows, the Python referenced by the registry. If both `python` and `python3` are on the `PATH`, then reticulate will prefer `python3`, unless only `python` has NumPy installed, or `python3` is built for a different architecture than R (e.g., x86).

## Python Packages

You can learn more about installing Python packages into virtualenvs or Conda environments in the article on Installing Python Packages.

## Configuration Info

You can use the `py_config()` function to query for information about the specific version of Python in use as well as a list of other Python versions discovered on the system:

    py_config()

You can also use the `py_discover_config()` function to see what version of Python will be used without actually loading Python:

    py_discover_config()