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fastplyr vs scoringutils

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

fastplyr vs scoringutils: at a glance

Featurefastplyrscoringutils
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdataframe-performance, dplyr-alternative, query-optimization, cran-policyforecast evaluation, probabilistic scoring, multivariate forecasts, s3 classes
Last editorial update44m 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 scoringutils?

scoringutils pushes forecast scoring past univariate outcomes into multivariate and ordinal ones.

scoringutils evaluates probabilistic forecasts in R. Since the 2.0.0 rewrite it is organised around typed forecast objects — quantile, sample, binary, point, nominal — built by as_forecast_<type>() constructors and scored through S3 methods. Version 2.2.0 adds multivariate sample and point types with the variogram score, and 2.1.0 added ordinal forecasts.

Read the full scoringutils trajectory →

fastplyr vs scoringutils: 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.

S
scoringutils
ANALYTICS
0.0

scoringutils pushes forecast scoring past univariate outcomes into multivariate and ordinal ones.

◆ Current state

scoringutils evaluates probabilistic forecasts in R. Since the 2.0.0 rewrite it is organised around typed forecast objects — quantile, sample, binary, point, nominal — built by as_forecast_<type>() constructors and scored through S3 methods. Version 2.2.0 adds multivariate sample and point types with the variogram score, and 2.1.0 added ordinal forecasts.

◆ Where it's heading

The forecast-type system introduced in 2.0.0 is the engine of everything since: each release fits another outcome shape into it rather than reworking the scoring interface. Multivariate support is the largest of those additions because it scores the dependence structure between variables, not just marginal accuracy. Type and constructor names are still being reconciled — forecast_sample_multivariate was renamed to forecast_multivariate_sample with a deprecation window.

◆ Prediction

Expect further forecast types and metrics slotted into the same constructor pattern, and the deprecated forecast_sample_multivariate alias and is_forecast_sample_multivariate() to be removed once that window closes.

Alternatives to fastplyr and scoringutils

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 scoringutils.

See all fastplyr alternatives → · See all scoringutils alternatives →

Recent activity from fastplyr and scoringutils

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

  1. 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
  2. 4mo agoscoringutilsMultivariate forecast scoring and the variogram score
  3. 8mo agofastplyrIn-place sorting arrives with a C++17 requirement
  4. 10mo agofastplyrGroup-unaware expressions evaluated on the whole frame
  5. 11mo agoscoringutilsQuantile levels rounded to avoid float duplicates
  6. 1y agoscoringutilsOptional p-values in pairwise comparisons; PIT fix
  7. 1y agofastplyrf_mutate and f_reframe complete the verb set
  8. 1y agoscoringutilsOrdinal forecasts get their own class and metrics
  9. 1y agofastplyrDynamic argument evaluation and f_pull
  10. 1y agofastplyrf_fill added and grouped joins repaired
  11. 1y agoscoringutilsRewrite: typed forecast objects and pluggable metrics
  12. 2y agoscoringutilsTwo bug fixes and package-site infrastructure

Frequently asked questions

What is the difference between fastplyr and scoringutils?

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

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

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