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bundle vs gigs

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

bundle vs gigs: at a glance

Featurebundlegigs
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesserialization, tidymodels, model-deployment, compatibilitygrowth-standards, neonatal-health, r-package, ropensci
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 gigs?

gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.

gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.

Read the full gigs trajectory →

bundle vs gigs: 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.

G
gigs
ANALYTICS
0.0

gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.

◆ Current state

gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.

◆ Where it's heading

The package has moved from vector-in, vector-out conversion helpers to a data.frame-oriented interface with a single classify_growth() entry point that computes whatever outcomes the supplied columns allow. That is a shift from library to tool — the user describes their data rather than picking the right function. The trailing releases suggest the code is settled and the remaining work is packaging and discoverability.

◆ Prediction

With the API rewrite absorbed and hosting moved to rOpenSci, the next substantive release should add growth standards or outcomes rather than reshape the interface again.

Alternatives to bundle and gigs

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 gigs.

See all bundle alternatives → · See all gigs alternatives →

Recent activity from bundle and gigs

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

  1. 8mo agobundlexgboost bundling updated for newer model versions
  2. 1y agogigsDocs and Zenodo archiving
  3. 1y agogigsDocs-only release; nothing changed internally
  4. 1y agogigsConversion API rewritten around data frames and classify_growth()
  5. 1y agobundledbarts BART models become bundleable
  6. 2y agogigsDocumentation fixes for autotest compliance
  7. 2y agogigsINTERGROWTH-21st fetal standards and input validation
  8. 2y agogigsPatch release with documentation update
  9. 2y agobundleRecipes steps inside workflows now bundle correctly
  10. 3y agobundleFirst CRAN release

Frequently asked questions

What is the difference between bundle and gigs?

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

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

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