box
Write reusable, composable and modular R code (by klmr)
fun
Module for functional programming in R (by klmr)
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
box
Posts with mentions or reviews of box.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-04.
- Trying to Replicate Excel financial Functions
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Can someone explain how R project are organized and deployed?
As for organising code within a project, as mentioned packages really don’t allow this beyond collation order. The best solution in this space is the ‘box’ package which implements a fully-featured module system for R. ‘box’ notably gets used by some folks to implement large-scale Shiny applications; if this is what you’re after, I would recommend the ‘rhino’ framework, which builds upon Siny and ‘box’.
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Good practice with long R scripts - any examples?
You can write amazing, clean, modular code with the box package.
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Does anyone feel like R is actually vastly worse for dependency/environment management than Python?
I would look into box https://github.com/klmr/box if you haven’t heard of it already
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"Managing large codebases in R" webinar (Oct. 6, 2022)
Shapeless plug: check out the already mentioned ‘box’, I think it’s strictly superior to ‘import’ (but I’m biased).
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Get tsarted wiht R using this Cheat Sheet - DataCamp
By contrast, R code doesn’t need to change the working directory at all! Having to do so hides other flaws in the code. For instance, when trying to load code or data, use the tools provided by R. That is, write packages and use system.file or, when not writing packages, use ‘box’.
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Which R function do you find somewhat tricky?
‘box’ fixes that.
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Restructuring a large R project. Need advice on how to wire up file paths and associated objects.
I think your use-case is best addressed by the ‘targets’ package. But I would also recommend checking out the ‘box’ package for a more general way of structuring R projects in modules which isn’t supported well natively by R (disclaimer: I wrote that package). Writing R code as modules fundamentally side-steps the issue of having to deal with absolute paths. Instead, all code and data are either contained in the module or can be accessed relative to the working directory.
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[Q] Loading `dplyr` packages within a function but not outside of it
However, using ‘box’, as recommended in another comment, allows you to achieve the same effect with less (and cleaner) code, by declaring your imports locally with the box::use function.
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Is it possible to see what functions are used from what library?
If you're writing you're own code you can use packageName::functionName(), or the box package. Which is definitely useful on larger codebases.
fun
Posts with mentions or reviews of fun.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-03-27.
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What would you like to see from an R2 / R++ / R#
Yes, totally agreed. You already suggested strengthening the functional programming aspect of R and that’s definitely a very important point. For instance, The fact that R < 4.0.1 has no concise lambda syntax is a travesty (that’s why I wrote my own: x -> x * 2), closely followed by lack of function composition.
What are some alternatives?
When comparing box and fun you can also consider the following projects:
renv - renv: Project environments for R.
rnim - A bridge between R and Nim
ggplot2 - An implementation of the Grammar of Graphics in R
tidytable - Tidy interface to 'data.table'
sys - Easily create reusable command line scripts with R
workflowr - Organize your project into a research website
lintr - Static Code Analysis for R
rspm - RStudio Package Manager
rocker - R configurations for Docker
types - Types for R
uktrade - An R package containing convenient functions to load HMRC Overseas Trade Statistics, Regional Trade Statistics, and custom URLs using HMRC's API.