Delta Lake
A 4.4.0 tag appears, but the feed carries only its release plumbing
A side-by-side editorial comparison of cyclocomp and distributions3 — release velocity, themes, recent moves, and the top alternatives to consider.
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
cyclocomp measures cyclomatic complexity of R functions and packages, and is best known as the engine behind lintr's complexity rule. It has three releases in the visible window spread across nearly three years. The current one, 1.1.2, adds a quiet argument to cyclocomp_package_dir(); the two before it, shipped a day apart in 2023, added a large speedup and the package-directory entry point itself.
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.
cyclocomp measures cyclomatic complexity of R functions and packages, and is best known as the engine behind lintr's complexity rule. It has three releases in the visible window spread across nearly three years. The current one, 1.1.2, adds a quiet argument to cyclocomp_package_dir(); the two before it, shipped a day apart in 2023, added a large speedup and the package-directory entry point itself.
This is a small tool that reached feature-complete and now moves only when a downstream consumer needs something. Every change in the window is externally contributed, and each addresses a concrete integration need: a function that works on a local package tree rather than an installed one, complexity results sorted so the worst offenders come first, and output suppression for programmatic callers. The 2023 pair shipped a day apart because the new entry point immediately exposed a performance problem on long linear code.
Expect the next change to arrive the same way, as a contributed patch serving a linting or CI workflow rather than as planned development.
An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.
Growth used to arrive as new distribution families contributed from outside - the extreme-value set, Erlang, later the Poisson binomial. This release changes the axis: alongside two new distributions it adds an inference layer (score, hessian) and a forecast-evaluation one (crps() methods against scoringRules), which are capabilities about distributions rather than more of them. Dependency weight is being cut at the same time, with ggplot2 demoted to Suggests and glue replaced by base R sprintf().
With numeric fallbacks and the derivative generics in place, expect analytic score() and hessian() methods to be filled in across more of the distribution catalogue. The constructor-default change is the likeliest source of follow-up fixes, since calls like Poisson() now return a length-zero distribution where they previously errored.
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 cyclocomp or distributions3.
A 4.4.0 tag appears, but the feed carries only its release plumbing
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio ships through release branches, and the notes are commit messages
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
Fulcrum is betting its whole map stack on Esri, with a hard Google Maps cutoff on September 1.
Holistics keeps fencing in the AI layer it spent the summer building.
See all cyclocomp alternatives → · See all distributions3 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 cyclocomp alternatives in Analytics are ranked by recent ship velocity. Browse the "cyclocomp alternatives" section above for the current picks, or visit /alternatives/cyclocomp for the full list with editorial commentary on each.
Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.