wooldridge
A textbook data package whose whole job is to stay installable, and whose releases prove how much work that is.
A side-by-side editorial comparison of nuggets and sps — release velocity, themes, recent moves, and the top alternatives to consider.
nuggets keeps compounding on the 2.0 rewrite — more pattern families, lighter install.
nuggets searches for association rules, contrasts and other conditional patterns in the GUHA tradition, with a C++ core behind dig() and an interactive explore() app for reading results. Since the 2.0 rewrite of that core, every release has widened the same three surfaces: more pattern families to mine, more of explore() to inspect them in, and steady performance work underneath. The most recent tag optimises dig() on sparse crisp data with a sparse bit chain and adds clustering characteristics to explore() for association rules.
sps keeps sanding down sequential Poisson sampling rather than adding to it.
The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.
nuggets searches for association rules, contrasts and other conditional patterns in the GUHA tradition, with a C++ core behind dig() and an interactive explore() app for reading results. Since the 2.0 rewrite of that core, every release has widened the same three surfaces: more pattern families to mine, more of explore() to inspect them in, and steady performance work underneath. The most recent tag optimises dig() on sparse crisp data with a sparse bit chain and adds clustering characteristics to explore() for association rules.
Two forces are shaping the package. One is coverage: baseline, complement and paired-baseline contrasts, correlations, tautologies, ancestors and clustering have all been added as first-class dig_ or explore_ surfaces, so the same search engine now answers a widening set of questions. The other is weight — Shiny packages moved from Imports to Suggests, BH and RcppThread dropped, XSIMD updated, parse_condition() rewritten in C++ — which keeps a package with an interactive app from forcing that app's dependencies on every user. Deprecations are handled through lifecycle rather than removed abruptly.
Expect the sparse-data optimisation to extend from crisp to fuzzy data, and explore() to keep gaining tabs as each new pattern family lands, on the roughly six-week cadence the 2.2 line has held.
The package implements sequential Poisson sampling for survey design, covering inclusion probabilities, proportional allocation, replicate weights, and take-all strata. Recent releases are small and tightly scoped: a divisor method helper, an iterator that draws a sample one unit at a time, automatic selection of the replicate-weight parameter, and repeated performance work on inclusion probability calculation.
Development is consolidation rather than expansion. Most releases either speed up an existing routine or remove a decision the user previously had to make by hand, such as picking the smallest parameter that keeps replicate weights non-negative. Documentation and tooling get comparable attention to the algorithms, with a dedicated vignette on inclusion probabilities and a recent switch of test and documentation infrastructure. The API surface has been essentially stable across the window.
Expect continued small ergonomic and performance releases against the existing function set rather than new sampling designs, which is the pattern every release in this window follows.
Other Infra & APIs 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 nuggets or sps.
A textbook data package whose whole job is to stay installable, and whose releases prove how much work that is.
A graph-centrality package that spent 2026 making its existing measures usable at scale, then went quiet.
A test-theory package that grew into a graphical-model toolkit, now spending its releases paying down the API debt that growth created.
projoint spent a year on CRAN paperwork, then shipped a correctness fix it flagged itself.
eratosthenes spends 0.1.0 hardening inputs rather than adding chronology methods.
dqcheckr adds drift analysis, then removes the YAML a user had to hand-write.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. nuggets and sps are shipping at a similar cadence (velocity 2.5 vs 2.5, 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. nuggets and sps are shipping at a similar cadence (velocity 2.5 vs 2.5, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top nuggets alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "nuggets alternatives" section above for the current picks, or visit /alternatives/nuggets for the full list with editorial commentary on each.
Top sps alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "sps alternatives" section above for the current picks, or visit /alternatives/sps for the full list with editorial commentary on each.