Welcome to Building R Packages

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Building R Packages

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Johns Hopkins University

Building R Packages

157 classificações

Curso 3 de 5 em Specialization Mastering Software Development in R

Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community-based standards and provides a good user experience. This course covers the primary means by which R software is organized and distributed to others. We cover R package development, writing good documentation and vignettes, writing robust software, cross-platform development, continuous integration tools, and distributing packages via CRAN and GitHub. Learners will produce R packages that satisfy the criteria for submission to CRAN.

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Getting Started with R Packages

Welcome to Building R Packages2:15

Conheça os instrutores

Roger D. Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Brooke Anderson
Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University

So at this point we have shown people how to write their own R code and

then to wrap it in into functions.

And then, this is the step where we show them how to wrap those function

into packages.

>> Yeah, so the bottom line I think is, if you want people to actually use your code,

it's gotta be in a package.

Sending them a script or

sending them some file that has a bunch of functions is fine.

But it's not organized, there's not necessarily any documentation,

there's not necessarily a tutorial of explaining how to use all these things.

And so, a package is really just a mechanism for organizing your code,

organizing your documentation, explaining to people how to use it.

And making it really kind of friendly.

>> Yeah. >> And so,

it's really more about the user, and kind of providing some of the niceties

that users need to kind of learn how to use your code.

>> I would agree.

I also think that the process of writing the documentation and putting functions

together helps organize the logic for the groups of functions you're creating.

>> Right, I think it also helps,

you to think about what are the functions that users need and

what are the functions that are just kind of in support of running the code.

And so, it's kind of a natural extension of writing a function itself.

Originally we started out with here's some code and then we kind of abstracted that

to say here's a function and here the inputs and the outputs.

And now the packages kind of natural next level where you talk about here are bunch

of functions.

Here, the functions that kind of like the ones that you want to call,

that you need to do to accomplish specific task.

>> Right, and then once you've written a package often you'll want to share it.

So we're going to talk some of this about how to use GitHub to share your package

and to check on other people's packages and pull them into you.

>> Yeah and I think another thing were going to talk about is quality control,

which is really important if you want to have a lot people using your package and

to kind of maintain the quality and make that the code is always working.

So we're going to talk about testing and kind of continuous integration for

maintaining your packages.

>> Yeah, because this builds on writing code and wrapping the code into functions

this is probably going to be most comfortable, I would say for

somebody who's already taken the first two courses in this specialization.

>> Yeah, definitely.

>> Yeah.

I'm so excited the people are interested in this topic.

And we're really excited that we're getting the chance to

teach you how to build R packages.

>> Yeah, I mean it's a really important skill, and

I think that I'm just very excited to see what you can build.

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