lintr
Static Code Analysis for R (by r-lib)
box
Write reusable, composable and modular R code (by klmr)
lintr | box | |
---|---|---|
4 | 31 | |
1,150 | 811 | |
0.8% | - | |
9.4 | 7.5 | |
9 days ago | 22 days ago | |
R | R | |
GNU General Public License v3.0 or later | MIT License |
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.
lintr
Posts with mentions or reviews of lintr.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-23.
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lintr update - CRAN release coming soon!
Looks like they're close to 3.0.0. https://github.com/r-lib/lintr/milestone/2
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What are some best practices in R that are rarely adhered to?
lintr: https://github.com/jimhester/lintr
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IDE suggestions to improve coding
I don't know any equivalent prompts that will pop up in RStudio, but I run lintr and goodpractice on fancy code, these make some performance suggestions.
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.
What are some alternatives?
When comparing lintr and box you can also consider the following projects:
tidytable - Tidy interface to 'data.table'
renv - renv: Project environments for R.
ggplot2 - An implementation of the Grammar of Graphics in R
rnim - A bridge between R and Nim
workflowr - Organize your project into a research website
rspm - RStudio Package Manager
sys - Easily create reusable command line scripts with R
types - Types for R
fun - Module for functional programming in R
rocker - R configurations for Docker
uktrade - An R package containing convenient functions to load HMRC Overseas Trade Statistics, Regional Trade Statistics, and custom URLs using HMRC's API.