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Using benchmarking to guide the adoption of dependencies in R packages

An example with cli
benchmarking
R
cli
R package
software architecture
R package developers often have to take on dependencies for various reasons. Dependencies are external packages that provide extra functionalities or features to another…
Nov 22, 2023
James Mba Azam

 

cfr v0.1.0

new-release
We are very excited to announce the release of a new cfr version v0.1.0. Here is an automatically generated summary of the changes in this version.
Nov 22, 2023
The Epiverse-TRACE development team

 

bpmodels v0.3.1

new-release
We are very excited to announce the release of a new bpmodels version v0.3.1. Here is an automatically generated summary of the changes in this version.
Nov 6, 2023
The Epiverse-TRACE development team

 

Lesser-known reasons to prefer apply() over for loops

R
functional programming
iteration
readability
good practices
The debate regarding the use of for loops versus the apply() function family (apply(), lapply(), vapply(), etc., along with their purrr counterparts: map(), map2(), map_lgl()…
Nov 2, 2023
Hugo Gruson

 

linelist v1.0.0

new-release
We are very excited to announce the release of a new linelist version v1.0.0. Here is a automatically generated summary of the changes in this version.
Oct 19, 2023
The Epiverse-TRACE development team

 

System Dependencies in R Packages & Automatic Testing

package development
R
R package
continuous integration
system dependens
This post has been cross-posted on the R-hub blog, and the R-hub blog maintainers have contributed to the review and improvement of this post.
Sep 26, 2023
Hugo Gruson

 

Communicating development stages of open-source software

open-source
R
R package
versioning
lifecycles
community
Software is not immediately stable when being developed. It undergoes design changes, changes to the user interface (application programming interface, API), and features…
Jul 18, 2023
Joshua W. Lambert

 

Sharing the C++ Code of an Rcpp Package

code sharing
R
R package
Rcpp
interoperability
Using the {Rcpp} package is the dominant method for linking the usability of R with the speed of C++, and can be used to write R packages that are fast and easy to use for…
Jun 5, 2023
Pratik Gupte

 

Extending Data Frames

Creating custom classes and {dplyr} compatibility
data frame
R
R package
interoperability
S3 class
dplyr
R is a commonly used language for data science and statistical computing. Foundational to this is having data structures that allow manipulation of data with minimal effort…
Apr 12, 2023
Joshua W. Lambert

What Should the First 100 Lines of Code Written During an Epidemic Look Like?

outbreak analytics
100 days workshop
participatory research
This vignette summarises the findings from the 100 days and 100 lines of code workshop, hosted in December 2022 by Epiverse-TRACE.
Mar 9, 2023
Carmen Tamayo

Convert Your R Function to an S3 Generic: Benefits, Pitfalls & Design Considerations

R
R package
object orientation
S3
interoperability
To build a tight and well-integrated data pipeline, it may be desirable to rely on object orientation (OO) to automatically pass valuable information from one step to the…
Feb 20, 2023
Hugo Gruson

 

Improving the C++ Code Quality of an Rcpp Package

code quality
R
R package
Rcpp
The R package development ecosystem includes packages such as {lintr} and {styler} that can help to check code style, and to format R code.
Feb 16, 2023
Pratik Gupte

Ensuring & Showcasing the Statistical Correctness of your R Package

code quality
R
R package
testing
We’re evolving in an increasingly data-driven world. And since critical decisions are taken based on results produced by data scientists and data analysts, they need to be…
Feb 13, 2023
Hugo Gruson
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