OHPL
A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.
A side-by-side editorial comparison of fastplyr and scoringutils — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | fastplyr | scoringutils |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | dataframe-performance, dplyr-alternative, query-optimization, cran-policy | forecast evaluation, probabilistic scoring, multivariate forecasts, s3 classes |
| Last editorial update | 44m ago | 2h ago |
| Website | Visit → | Visit → |
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.
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.
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.
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.
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.
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.
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.
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.
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.
A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.
Belgium's invasive-species indicator toolkit is in steady refinement, one plotting edge case at a time.
The ICES stock assessment client took upload away in 2024 and spent two years giving it back.
A discrete global grid generator grew cell traversal and became a usable spatial index.
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
A cloud-chart package quietly swapping its dependencies for its maintainer's own libraries.
See all fastplyr alternatives → · See all scoringutils alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
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.
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.