#rstats tidypolars 0.18.0 is available!

tidypolars provides the tidyverse syntax while using polars for better performance.

In this release:
- support more base R functions
- bug fixes (including better NA handling in several functions)
- and more

Changelog: https://www.tidypolars.etiennebacher.com/news/

#rstats I'm very happy to announce Jarl 0.5.0!

Jarl is a very fast R linter, written in Rust. This release brings many improvements and fixes:

- check R code chunks in R Markdown and Quarto docs
- check "@examples" and "@examplesIf" sections if you use roxygen2
- detect unused or duplicated functions in pkgs
- rules on specific pkgs, e.g. on `dplyr::filter()`, are now possible. Feel free to suggest more and in other pkgs too!

Post: https://www.etiennebacher.com/posts/2026-03-23-jarl-0.5.0/

Changelog: https://jarl.etiennebacher.com/changelog

#rstats tidypolars 0.17.0 is available!

tidypolars provides the tidyverse syntax while using polars for better perf.

In this release:

- support new functions from dplyr 1.2.0 (filter_out, when_any...)
- pivot_wider with lazyframe
- bug fixes

and more

News: https://tidypolars.etiennebacher.com/news/

#rstats I'm very happy to announce Jarl 0.4.0!

Jarl is a very fast R linter, written in Rust. This release brings lots of improvements and fixes:

- Jarl can now find unreachable code, meaning code that will never run because it's after a stop(), a return(), etc.
- the suppression comments system (to ignore diagnostics on specific lines) has been entirely rewritten
- and more!

See the blog post: https://www.etiennebacher.com/posts/2026-02-03-jarl-0.4.0

And the full changelog: https://jarl.etiennebacher.com/

#rstats tidypolars 0.16.0 is available!

tidypolars provides the tidyverse syntax while using polars in the background for efficient computations.

In this release:
- more support for unnest and separate functions from tidyr
- new interface to export partitioned output
- more improvements and bug fixes

News: https://www.tidypolars.etiennebacher.com/news/#tidypolars-0160

#rstats I've given a workshop a few days ago on handling large data (think tens to hundreds of millions of rows) with Polars in Python and in R.

Here are my introductory slides: https://brussels-large-data-r-python.etiennebacher.com

And the associated repo: https://github.com/etiennebacher/brussels_teaching_january_2026

#rstats Jarl 0.3.0 is available!

Jarl is a very fast R linter, able to check and fix thousands of lines in milliseconds.

New since initial release:
- 6 new rules
- ignore automatically generated files by default
- bug fixes and perf improvements

All changes: https://jarl.etiennebacher.com/changelog