compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
A side-by-side editorial comparison of hubUtils and libr — release velocity, themes, recent moves, and the top alternatives to consider.
The hubverse's shared plumbing, tracking schema versions and converting output types.
hubUtils is the low-level dependency the rest of the hubverse builds on: schema version tracking, config file reading, example test hubs, and conversion between forecast output types. Its releases are small and cadenced to the hubverse schema itself, with a version bump arriving whenever the config schema advances. The recent work is performance rather than surface.
The SAS datastep clone for R just got roughly nineteen times faster.
libr gives R users SAS-style data libraries and a datastep() construct, sitting alongside logr, reporter and procs in the r-sassy suite for analysts moving clinical workflows off SAS. Most of its release history is narrow bug-fixing in the libname() readers, particularly the sas7bdat engine. The exception dominates the window: a single 2026 release that rewrote datastep() performance and cut the installed package to a quarter of its former size.
hubUtils is the low-level dependency the rest of the hubverse builds on: schema version tracking, config file reading, example test hubs, and conversion between forecast output types. Its releases are small and cadenced to the hubverse schema itself, with a version bump arriving whenever the config schema advances. The recent work is performance rather than surface.
The through-line is that this package absorbs whatever the schema is doing — v5, then v6 with target-data configuration, each arriving with matching accessors and example hubs so the sibling packages can be tested against something real. convert_output_type() is the one piece of genuine computation here, and it has now been optimised by roughly an order of magnitude, suggesting it is being used at scales the original implementation did not anticipate. Everything else is accessors and fixtures.
Expect the next substantive release to track the next hubverse schema version, with any independent work concentrated on convert_output_type(), the only performance-sensitive function in the package.
libr gives R users SAS-style data libraries and a datastep() construct, sitting alongside logr, reporter and procs in the r-sassy suite for analysts moving clinical workflows off SAS. Most of its release history is narrow bug-fixing in the libname() readers, particularly the sas7bdat engine. The exception dominates the window: a single 2026 release that rewrote datastep() performance and cut the installed package to a quarter of its former size.
Two threads run through these entries — steady correctness work on SAS file import, and a much less frequent but far more consequential push on making datastep() viable at real data volumes. The recent fix to empty-variable typing suggests the sas7bdat reader is still where edge cases surface. Having addressed both speed and package size in one release, the obvious remaining pressure is correctness and coverage of SAS semantics rather than throughput.
Expect the next releases to continue narrowing sas7bdat import edge cases, with any further datastep() work aimed at supporting more SAS syntax rather than at speed.
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 hubUtils or libr.
An MLE package rebuilt around composable solvers, then renamed to match.
nabla dropped its C++ engine to chase exact derivatives at any order.
Eight months from first release to keyring caching and workload identity.
A research-project workflow package where the interesting work is in the plumbing.
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
See all hubUtils alternatives → · See all libr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package, performance — within Analytics. libr is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. libr is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top hubUtils alternatives in Analytics are ranked by recent ship velocity. Browse the "hubUtils alternatives" section above for the current picks, or visit /alternatives/hubutils for the full list with editorial commentary on each.
Top libr alternatives in Analytics are ranked by recent ship velocity. Browse the "libr alternatives" section above for the current picks, or visit /alternatives/libr for the full list with editorial commentary on each.