rollupTree
The recursive-computation engine under massProps grows the accessors its consumer needed
A side-by-side editorial comparison of rstudio.prefs and tf — release velocity, themes, recent moves, and the top alternatives to consider.
Four years dormant, rstudio.prefs returns under a new maintainer.
The package scripts RStudio's own settings — preferences, secondary repositories, keyboard shortcuts — as code you can drop into a project or an onboarding doc. After 0.1.9 in July 2022 it went quiet for four years. 0.2.0 ends that with a maintainer handoff from Daniel D. Sjoberg to S.A. van der Wulp, a shortcut-removal path, and a fix for a corrupted addins.json entry that made reassigned shortcuts fail silently.
tf gave functional data a second dimension: curves whose values are vectors.
tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.
The package scripts RStudio's own settings — preferences, secondary repositories, keyboard shortcuts — as code you can drop into a project or an onboarding doc. After 0.1.9 in July 2022 it went quiet for four years. 0.2.0 ends that with a maintainer handoff from Daniel D. Sjoberg to S.A. van der Wulp, a shortcut-removal path, and a fix for a corrupted addins.json entry that made reassigned shortcuts fail silently.
The through-line is teaching every setter how to unset. Secondary repositories got NULL removal back in 0.1.6; 0.2.0 extends the same convention to keyboard shortcuts. Most of the rest of 0.2.0 is arrears — a stale documentation URL that hid preferences such as enable_splash_screen, a deprecated purrr::update_list() call, and check_shortcut_consistency() erroring early on an unknown name.
With a new maintainer and refreshed GitHub Actions, the near-term work is likely more catch-up of the same kind: remaining deprecated dependencies and the preference list that fetch_rstudio_prefs() reads from RStudio's docs. Nothing in these notes points past RStudio settings as the scope.
tf supplies the vector classes underneath the tidyfun stack — tfd for raw functional observations, tfb for basis-represented ones, both built on vctrs so curves sit in a data frame column and behave like any other vector. Until July that codomain was scalar. The 0.5.0 release adds tfd_mv and tfb_mv, classes for functions whose values are vectors in R^d, and rebuilds the analysis verbs to match.
The package is widening what a functional observation can be, then porting the toolkit onto it. Registration arrived first in 0.4.0 for univariate curves and immediately gained an srvf_mv method for aligning components jointly, and tfb_mfpc() ports principal component analysis to the multivariate case with a single set of scores shared across components. Alongside that runs steady dependency shedding — mvtnorm and pracma both replaced by inlined samplers that reproduce prior draws bit-for-bit, glue dropped for cli in the previous release — and an unusually long tail of NA-handling and edge-case fixes, several caught in pre-release review of the new classes.
The new classes ship with FPCA, registration and shape alignment but the release notes describe tidyfun::tf_unnest() as the consumer of one new export, so the visible next step is the rest of the tidyfun stack catching up to vector-valued columns. Expect follow-up patches on the vctrs casting paths, which is where most of this release's late fixes clustered.
Other Infra & APIs products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either rstudio.prefs or tf.
The recursive-computation engine under massProps grows the accessors its consumer needed
A mass-properties rollup spends a year on documentation and follows its sibling's API
Six months of releases and not one of them touched the scoring models
A cognitive-science sampling package ships once, then goes quiet for eighteen months
A Bayesian volatility sampler in its maintenance decade, paying for its own speed
A black-box interpreter reaches CRAN, then learns multi-class and survival responses
See all rstudio.prefs alternatives → · See all tf alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-packages — within Infra & APIs. rstudio.prefs is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rstudio.prefs is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top rstudio.prefs alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "rstudio.prefs alternatives" section above for the current picks, or visit /alternatives/rstudio-prefs for the full list with editorial commentary on each.
Top tf alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tf alternatives" section above for the current picks, or visit /alternatives/tf for the full list with editorial commentary on each.