tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of daiquiri and tidymodels — release velocity, themes, recent moves, and the top alternatives to consider.
A data-quality report generator that finished its API rewrite and has been coasting on small features since.
daiquiri turns a raw clinical or administrative dataset into an HTML report of time-series data-quality plots, driven by a field-type specification the user writes. The public API settled in 2022 after a wholesale rename for rOpenSci acceptance, and releases since then have added specification conveniences rather than new report content. The 1.2.0 release is the first in nearly two years.
The meta-package ships almost nothing, which is exactly what a version-pinning shim should do
The tidymodels package is a loader and version pin for the modeling framework's core set rather than a place where features live. Its entire changelog consists of updated dependency versions, adjustments to how tidymodels_prefer() resolves name conflicts against other packages, and the occasional addition of a package to the core set — workflowsets in 0.1.3, tailor in 1.4.0. The most recent releases moved the package's own code from the magrittr pipe to R's base pipe and patched a bug where some attached packages were omitted.
daiquiri turns a raw clinical or administrative dataset into an HTML report of time-series data-quality plots, driven by a field-type specification the user writes. The public API settled in 2022 after a wholesale rename for rOpenSci acceptance, and releases since then have added specification conveniences rather than new report content. The 1.2.0 release is the first in nearly two years.
Development has shifted from restructuring the interface to lowering the cost of using it — field_types_advanced() lets users name only the columns they care about and default the rest, which is the kind of change that matters when a dataset has hundreds of fields. Plot rendering is getting incremental attention (heatmap scaling) rather than new visualisation types. Cadence is roughly annual.
Expect the next release to continue trimming specification boilerplate for wide datasets rather than adding report sections; the entries give no indication of a new plot type or output format in progress.
The tidymodels package is a loader and version pin for the modeling framework's core set rather than a place where features live. Its entire changelog consists of updated dependency versions, adjustments to how tidymodels_prefer() resolves name conflicts against other packages, and the occasional addition of a package to the core set — workflowsets in 0.1.3, tailor in 1.4.0. The most recent releases moved the package's own code from the magrittr pipe to R's base pipe and patched a bug where some attached packages were omitted.
Release cadence tracks the ecosystem rather than any roadmap of its own: a version bump when member packages release, a tidymodels_prefer() rule when a new conflict appears — DALEX::explains() over dplyr::explains(), recipes::update() over other update() methods. Additions to the core set are the only structurally interesting events, and there have been two in seven releases. Everything else is plumbing that exists so a single library() call attaches a consistent set of versions.
The next release will most likely be another version-set update, with any new core package the only thing worth noting. Feature news for this framework will keep arriving in the member packages, not here.
Other Analytics 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 daiquiri or tidymodels.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all daiquiri alternatives → · See all tidymodels alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. daiquiri and tidymodels are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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. daiquiri and tidymodels are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top daiquiri alternatives in Analytics are ranked by recent ship velocity. Browse the "daiquiri alternatives" section above for the current picks, or visit /alternatives/daiquiri for the full list with editorial commentary on each.
Top tidymodels alternatives in Analytics are ranked by recent ship velocity. Browse the "tidymodels alternatives" section above for the current picks, or visit /alternatives/tidymodels for the full list with editorial commentary on each.