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bundle vs Tplyr

A side-by-side editorial comparison of bundle and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.

bundle vs Tplyr: at a glance

FeaturebundleTplyr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesserialization, tidymodels, model-deployment, compatibilityclinical-trials, tables, traceability, r-package
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

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.

Read the full bundle trajectory →

What is Tplyr?

Tplyr made clinical summary tables explain where every number came from.

Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.

Read the full Tplyr trajectory →

bundle vs Tplyr: editorial side-by-side

B
bundle
ANALYTICS
0.0

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.

T
Tplyr
ANALYTICS
0.0

Tplyr made clinical summary tables explain where every number came from.

◆ Current state

Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.

◆ Where it's heading

Post-1.0 work has been about completing the metadata story and filling gaps in layer composition rather than adding table types — metadata for missing subjects, add_anti_join(), missing-subject rows, data limiting, and fixes to nested count layers where an inner value appears under several outer groups. Releases cluster tightly after a major version, then go quiet, and the window ends with a patch issued days after the release it corrects.

◆ Prediction

Further releases will most likely continue closing traceability and nested-layer edge cases rather than introducing new layer types, following the pattern of both post-1.0 feature releases.

Alternatives to bundle and Tplyr

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 Tplyr.

See all bundle alternatives → · See all Tplyr alternatives →

Recent activity from bundle and Tplyr

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 8mo agobundlexgboost bundling updated for newer model versions
  2. 1y agobundledbarts BART models become bundleable
  3. 2y agoTplyrMissing-subject metadata, add_anti_join(), and nested-layer fixes
  4. 2y agobundleRecipes steps inside workflows now bundle correctly
  5. 3y agoTplyrMetadata vignette fix and parenthesis hugging
  6. 3y agoTplyrDenominator logic fix ahead of CRAN release
  7. 3y agoTplyrReverse-dependency fix
  8. 3y agoTplyr1.0.0 introduces the traceability metadata framework
  9. 3y agobundleFirst CRAN release

Frequently asked questions

What is the difference between bundle and Tplyr?

They serve adjacent needs but don't currently overlap on shipped themes. bundle and Tplyr 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 Tplyr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bundle and Tplyr 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 Tplyr?

Top Tplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "Tplyr alternatives" section above for the current picks, or visit /alternatives/tplyr for the full list with editorial commentary on each.