Why use a dependency manager? about ds-pipelines-1 HOT 5 CLOSED

Pipelines tools like make are difficult to use in R since these tools are language agnostic. Therefore, these tools add extra friction and obstruct the workflow if applied into particular language like R.

In the meantime, using a package like drake that is designed for R would work well within the language. The user can write functions instead of script files. Moreover, the functions return objects which will be saved automatically instead of output that need to be saved manually. In addition, R-focus interface to define the skippable steps of the workflow instead of MakeFiles.

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I find it interesting how eight simple steps can make the workflow easy for collaborators and make reproducibility possible. The first step is file organization and naming, it is a simple and valuable tool. A good file organizing and proper naming will be useful for collaborators including myself. Also, adopting one organization method that includes file separation is also a useful tool. For example, separating code scripts from data files is an easy and good workflow. The final step to organize files is creating the Readme files and continuously updating it with any project/file changes.

The second step for reproducibility is to perform all tasks using a script. It’s a simple step that allows all project collaborators to keep a record of all the changes made to a project or a data file. In the meantime, this step will allow collaborators to reproduce the change to any file/data. The third step is automating the process which also a simple step that can save the collaborator time for past and future work.

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Your text look great. I am going to close this even though it is assigned to Alison so you can move on.

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Great comments @RAtshan! ✨

You could consider GNU make to be a great grandparent of the packages we asked you to install early in this lesson (drake, remake, and scipiper). The lead of drake has added a lot of useful features to dependency management systems in R, and has a great way of summarizing why we put energy into using these tools. "Skip the work you don't need"

We'd like you to next check out a short part of Will's video on drake

📺 Activity: watch video on drake from at least 3:33 to 7:42 (you are welcome to watch the whole thing)

Use a github comment on this issue to let us know what contrasts you identified between solutions in make and what is offered in R-specific tools, like drake. Please use less than 300 words. Then assign your onboarding cohort team member this issue to read what you wrote. When they are done, welcome them to comment with any questions or comments.

When you are satisfied with the discussion, you can close this issue and I'll direct you to the next one.

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When you are done poking around, check out the next issue.

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