[#]rstats Package {flint} 0.2.0 is now available via R-universe!
{flint} is a package to quickly find lints and fix them automatically.
This release comes with an important fix when several replacements targeted the same piece of code. It also brings a couple of new linters, and removes some edge cases from existing linters.
All changes: https://flint.etiennebacher.com/news/
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[#]rstats #rshiny #biology #internship Internship offer for Master students:
No knowledge in biology required.
CV and cover letter to be sent at the email address at the top of the file (not me).
More info in the attached files.
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[#]rstats {flint} 0.1.2 is available via R-universe! This release comes with several bug fixes and new linters.
{flint} is a package to detect and automatically fix lints in R code. It is also very fast and compatible with many {lintr} rules.
More info: https://flint.etiennebacher.com/
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[#]rstats tidypolars 0.11.0 is released!
This implements improvements from polars 0.20.0, including inequality joins in inner_join(). Several join helpers are also supported, such as overlaps() and within().
This release also fixes a few bugs, more info in the full changelog:
https://www.tidypolars.etiennebacher.com/news/#tidypolars-0110
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[#]rstats polars 0.20.0 is now available!
This isn't a huge release, but there are still a few additions (and a couple of breaking changes). In particular, polars can now perform inequality joins using the new $join_where()
functions (limited to inner joins for now).
Full changelog: https://pola-rs.github.io/r-polars/NEWS.html#polars-r-package-0200
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[#]rstats Introducing a new package: flint!
{flint} is a package to find lints (~ "bad practices") in R code and automatically fix them. {lintr} does a great job but doesn't fix lints and can be slow on large codebases.
The everyday usage is quite simple: use lint() and its variants to show lints, and use fix() and its variants to automatically fix them (not all lints can be fixed).
https://flint.etiennebacher.com/
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[#]rstats New blog post: using property-based testing in R.
This briefly explains what property-based testing is and presents a couple of situations where it can be useful when developing R packages.
https://www.etiennebacher.com/posts/2024-10-01-using-property-testing-in-r/
(I have a feeling @maelle might be interested ;) )
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[#]rstats I've given a very lightweight presentation on handling large data with polars and tidypolars (for a non-technical audience).
It's not a tutorial, there is very little code. I think it can be useful as a first step to understand what are some problems that one faces with large data (such as order of operations) and how polars can help with that.
https://www.handling-large-data.etiennebacher.com
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As usual, a new {polars} release is accompanied by a new {tidypolars} release (v.0.10.0).
This contains:
pl$read_parquet()
anymoreChangelog: https://tidypolars.etiennebacher.com/news/#tidypolars-0100
[#]rstats
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The R package {polars} version 0.19.1 is now available!
In particular, this brings better support for reading and writing hive partitions for Parquet and IPC files, and it adds several functions to deal with string, list, and binary columns.
As usual, this release also contains performance improvements and breaking changes (some parameters are renamed, some functions are removed, etc.) so it's important to check the changelog: https://pola-rs.github.io/r-polars/NEWS.html#polars-r-package-0190
[#]rstats
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