tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
bundle vs tidymodels
A side-by-side editorial comparison of bundle and tidymodels — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodelsr-packages
bundle vs tidymodels: at a glance
What is bundle?
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
bundle solves a narrow, real problem: many R model objects hold pointers to external state — compiled boosters, Java handles, torch tensors — that do not survive being saved and reloaded in another session. It wraps them so they do. The package has shipped four releases since 2022, and the shape of each is the same: extend coverage to another model class, or repair coverage that an upstream release broke.
What is tidymodels?
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.
bundle vs tidymodels: editorial side-by-side
bundle
0.0ANALYTICS
Four releases in three years, each one teaching the serializer about a model type it couldn't carry
◆ Current state
bundle solves a narrow, real problem: many R model objects hold pointers to external state — compiled boosters, Java handles, torch tensors — that do not survive being saved and reloaded in another session. It wraps them so they do. The package has shipped four releases since 2022, and the shape of each is the same: extend coverage to another model class, or repair coverage that an upstream release broke.
◆ Where it's heading
Coverage is the product, so the release cadence is set by the ecosystem rather than by a roadmap. dbarts arrived in 0.1.2, along with extra work to preserve xgboost's nfeatures and feature_names through a round trip; 0.1.3 exists because xgboost changed its model format again. The 0.1.1 fix — recipes steps nested inside workflows — points at the same underlying issue one level up, where the object needing bundling is buried inside a tidymodels pipeline rather than passed directly.
◆ Prediction
Expect the next release to follow the same trigger: either a new parsnip engine that carries external pointers, or another upstream format change in one of the engines already covered. xgboost has now forced two of the four releases.
tidymodels
0.0ANALYTICS
The meta-package ships almost nothing, which is exactly what a version-pinning shim should do
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to bundle and tidymodels
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 bundle or tidymodels.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all bundle alternatives → · See all tidymodels alternatives →
Recent activity from bundle and tidymodels
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agobundlexgboost bundling updated for newer model versions
- 11mo agotidymodelsFix for packages omitted from attachment
- 11mo agotidymodelstailor joins the core set; base pipe replaces magrittr
- 1y agotidymodelsConflict preferences added for DALEX and recipes
- 1y agobundledbarts BART models become bundleable
- 2y agobundleRecipes steps inside workflows now bundle correctly
- 3y agotidymodelsConflict preferences and pinned versions refreshed
- 3y agobundleFirst CRAN release
- 4y agotidymodelsVersion refresh and testthat 3e migration
- 4y agotidymodelsRotating startup messages and an analysis template
Frequently asked questions
What is the difference between bundle and tidymodels?
Both compete on the same themes — tidymodels, r-packages — within Analytics. bundle 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.
Is bundle better than tidymodels?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bundle 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.
What are the best alternatives to bundle?
Top bundle alternatives in Analytics are ranked by recent ship velocity. Browse the "bundle alternatives" section above for the current picks, or visit /alternatives/bundle for the full list with editorial commentary on each.
What are the best alternatives to tidymodels?
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.