modeltime
modeltime built conformal intervals in, then went quiet on features.
A side-by-side editorial comparison of performance and tidyr — release velocity, themes, recent moves, and the top alternatives to consider.
performance keeps adding ways to check a model you have already fitted.
performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.
tidyr replaced separate() with a family that says what it does.
tidyr is at 1.3.2, a collection of argument additions — fill() gains .by, expand_grid() gains .vary — and better error messages around unchop() and pivot_wider_spec(). The structural work is 1.3.0, which introduced separate_wider_delim(), separate_wider_position(), separate_wider_regex(), separate_longer_delim() and separate_longer_position() as thorough replacements for separate(), extract() and separate_rows().
performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.
Two consistent habits. Diagnostics keep gaining arguments to narrow what is examined — ppc_range, x_limits, maximum_dots, show_ci — which reads as a package being used on models large and awkward enough that the defaults stopped working. And simulated residuals via DHARMa keep displacing standard ones as the basis for the checks themselves.
With check_priors() newly added and Bayesian predictive checks now routed through modelbased, the next release most likely extends the Bayesian diagnostic set rather than reworking the frequentist checks.
tidyr is at 1.3.2, a collection of argument additions — fill() gains .by, expand_grid() gains .vary — and better error messages around unchop() and pivot_wider_spec(). The structural work is 1.3.0, which introduced separate_wider_delim(), separate_wider_position(), separate_wider_regex(), separate_longer_delim() and separate_longer_position() as thorough replacements for separate(), extract() and separate_rows().
Two habits define this window. Verbs are being split into explicitly named variants rather than overloaded with arguments, which is what the separate_* family does to separate(). And .by is spreading as the standard way to express grouping inline — nest(.by=) in 1.3.0, fill(.by=) in 1.3.2 — pulling users away from wrapping calls in group_by().
Given that .by has now reached fill() and nest(), the next release most likely extends the same argument to further verbs rather than reworking another function family.
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 performance or tidyr.
modeltime built conformal intervals in, then went quiet on features.
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
See all performance alternatives → · See all tidyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-language — within Analytics. performance and tidyr 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. performance and tidyr 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 performance alternatives in Analytics are ranked by recent ship velocity. Browse the "performance alternatives" section above for the current picks, or visit /alternatives/easystats-performance for the full list with editorial commentary on each.
Top tidyr alternatives in Analytics are ranked by recent ship velocity. Browse the "tidyr alternatives" section above for the current picks, or visit /alternatives/tidyr for the full list with editorial commentary on each.