# Setup FastF1 Connection

# Introduction

This vignette briefly describes setting up the `f1dataR` package to work properly with with the Python package `FastF1`. This guide may help resolve some issues that might arise when you get the following warning or error messages:

- `Ensure fastf1 python package is installed. Please run this to install the most recent version: setup_fastf1()`
- `Error in if (get_fastf1_version() < '3.1') { :` `missing value where TRUE/FALSE needed`

If these happen to you (particularly if you’re a new user of `f1dataR`) read on!

# `f1dataR`’s Relationship to Python

At the core of the `f1dataR` package, the connection to the Python package is created by using `reticulate`. This provides the connection used to call on Python and return objects to R. However, it has to be set up properly to work.

> NOTE: If you are comfortable with `reticulate`, set up a virtualenv or condaenv and point reticulate to that with your .RProfile before calling `library(fastf1)`, and you can skip the rest of this guide.

# Setting up `reticulate`

There are a few options to get the `reticulate` set up in a way that works well for `f1dataR` to use it.

## Accept all defaults

To use all of the defaults and set up the `reticulate` package, you can use the below helper function.

    setup_fastf1()

This will create a virtual environment using your system’s default Python version, and install `fastf1` in that python environment. It will also tell `reticulate` to use that environment instead of just running in your main system. For more information on Python environments read this article (infoworld.com).

# Repeat/Recurring Issues

If you have repeat issues with the package failing to connect to your proper environment, you can force a complete recreation of the virtual environment by calling:

    setup_fastf1(new_env = TRUE)

If you’ve configured the package to use a custom environment name, the above function will require that name supplied as the `envname` parameter.