 Okay, track down a simple framework for collaboration in a little programming workflow. All we know that little programming in R is amazing. It can produce high quality documents, presentations, thesis, reports, and so on, using a lot of packages that can support our work. There is a huge problem in this type of workflow and this problem is collaboration. If you ever try to collaborate on this kind of file, you have probably realized that it's very hard. Why? Basically, we have to collaborate with different kinds of people, not people like us, but also with the average Microsoft Wall user. We have to collaborate on the plaintext files, so the stage before the compilation. And furthermore, we have to collaborate without revision tools of Microsoft Word and Google Docs. And this can be really hard, especially for text-based documents. Wait, we have Git. Given that we are working on plaintext file, we can use Git as always. Of course, Git is very powerful, but not for text-based documents. Why? Let's imagine a standard text-based file and modify it with Word. You can change a sentence, a single letter, a word, and everything that is going on is extremely clear. However, doing the same stuff with Git can be really hard because even if you change a little part, Git will tell you that you change the entire line because Git is not made for text-based documents. So in an ideal world, we need a tool that allows us to collaborate in a very intuitive way as Word does. But at the same time, we need a user-friendly tool, but also a powerful tool for experts. And we want all the amazing features of a little programming workflow. Yeah, this tool can be very mind-blowing. And the idea is to use a Traktown package in order to solve this problem, which is a big picture. Let's imagine that we have our local computer and we have our file with R, with Git, and all the framework that we usually use. And sometimes we need to collaborate on a project. And we can use the upload file function in order to upload our document on Google Doc. Then we can share the Google Doc link and review the plaintext document with other colleagues. Once the review ends, we can use the download file function in order to integrate all changes in our local plaintext file version. And then, of course, this process can be repeated as much as necessary in order to produce the final document. But instead of talking about the package, let's see how it works in action. So the first step is to use the upload file function. And basically, we have our local file and loading the Traktown package. And using the upload file function, it's very easy. We can provide the local file name, the Google Drive location, and the option to remove code chunks temporarily. Basically, in a few seconds, we will have our documents uploaded on Google Drive. Then we can share our documents on Google Doc, and the review process can start. And so basically, we share a link. We can make all our changes, comments, and so on. We can use all our fancy tools in Google Doc, such as spell checking, corrections, and so on. That is the entire history of changes. After accepting all our revision, we are ready to download the file. And using the download file function on the final version, we can easily download all the changes and integrate it with the local file version. And basically, what we will have is our final file with all changes ready to be needed in order to have the final output. The package has a lot of interesting features, such as the support for both Harmarkdown and R&V files. We have this powerful system in order to hide or restore chunks between the upload and download process. And of course, given that there is a great part of this workflow that is local, we can easily integrate the online review process with a local Git workflow. If you want to have more information, check the full documentation on GitHub. And I want to thank all the developers of this package. And also I want to thank my research group at the University of Padua that support our work. And of course, I want also to thank you for your attention.