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fastplyr vs modeltime.resample

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

fastplyr vs modeltime.resample: at a glance

Featurefastplyrmodeltime.resample
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdataframe-performance, dplyr-alternative, query-optimization, cran-policytime series, cross-validation, tidymodels, compatibility maintenance
Last editorial update48m ago2h ago
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What is fastplyr?

A fast dplyr stand-in that keeps finding new places to skip work entirely.

fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.

Read the full fastplyr trajectory →

What is modeltime.resample?

modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.

modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.

Read the full modeltime.resample trajectory →

fastplyr vs modeltime.resample: editorial side-by-side

F
fastplyr
ANALYTICS
0.0

A fast dplyr stand-in that keeps finding new places to skip work entirely.

◆ Current state

fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.

◆ Where it's heading

The optimization strategy has shifted from making individual functions fast to reasoning about expressions before evaluating them — 0.9.9 began marking simple operators as group-unaware so expressions built only from them are evaluated across the whole data frame rather than per group. That is a structural bet: the package increasingly inspects what you wrote to decide how much work is actually needed. Running alongside it is a steady tightening of build requirements, with C++17, R 4.5.0 and CRAN's C API rules all landing within a year.

◆ Prediction

Expect the group-unaware classification to widen to more functions, since each addition compounds across every grouped expression, and expect the dependency floors to keep rising as the package tracks CRAN's compiled-code policy.

M0.0

modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.

◆ Current state

modeltime.resample runs time series cross-validation over modeltime models, returning per-resample predictions and accuracy plots. Version 0.3.0 is the substantive release in view: tune 2.0.0 compatibility, deterministic seeding via withr, guaranteed .predictions output, and clearer failures when resample fits break. The three releases before it are dependency chores.

◆ Where it's heading

Every entry here is compatibility work against something upstream — hardhat 1.0.0, workflows regression mode, then tune 2.0.0 twice. The 0.3.0 notes show a second concern emerging alongside it: making failures legible, with .notes on failed fits, actionable errors from unnest_modeltime_resamples(), and fallback logic when prediction columns go missing across versions. Reproducibility gets the same treatment through explicit seeding.

◆ Prediction

Expect the next release to track the next tidymodels breaking change, with any new work continuing on error reporting rather than resampling strategies.

Alternatives to fastplyr and modeltime.resample

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 fastplyr or modeltime.resample.

See all fastplyr alternatives → · See all modeltime.resample alternatives →

Recent activity from fastplyr and modeltime.resample

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

  1. 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
  2. 8mo agofastplyrIn-place sorting arrives with a C++17 requirement
  3. 10mo agofastplyrGroup-unaware expressions evaluated on the whole frame
  4. 11mo agomodeltime.resampletune 2.0 support, deterministic seeding, clearer errors
  5. 11mo agomodeltime.resampleDependency cleanup ahead of the next tune release
  6. 1y agofastplyrf_mutate and f_reframe complete the verb set
  7. 1y agofastplyrDynamic argument evaluation and f_pull
  8. 1y agofastplyrf_fill added and grouped joins repaired
  9. 3y agomodeltime.resampleFixes workflows in regression mode
  10. 4y agomodeltime.resampleUpdates for hardhat 1.0.0

Frequently asked questions

What is the difference between fastplyr and modeltime.resample?

They serve adjacent needs but don't currently overlap on shipped themes. fastplyr and modeltime.resample 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 fastplyr better than modeltime.resample?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastplyr and modeltime.resample 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 fastplyr?

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

What are the best alternatives to modeltime.resample?

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