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cyclocomp vs hubEvals

A side-by-side editorial comparison of cyclocomp and hubEvals — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

cyclocomp vs hubEvals: at a glance

FeaturecyclocomphubEvals
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesstatic-analysis, code-complexity, linting, r-packageforecast-evaluation, scoring, epidemiology, r-package
Last editorial update16m ago1h ago
WebsiteVisit →Visit →

What is cyclocomp?

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.

Read the full cyclocomp trajectory →

What is hubEvals?

Forecast-hub scoring that learned to handle joint, sample-based predictions.

hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.

Read the full hubEvals trajectory →

cyclocomp vs hubEvals: editorial side-by-side

C
cyclocomp
ANALYTICS
0.0

A cyclomatic complexity checker that ships once every couple of years, and lands when it does.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

Expect the next change to arrive the same way, as a contributed patch serving a linting or CI workflow rather than as planned development.

H
hubEvals
ANALYTICS
2.5

Forecast-hub scoring that learned to handle joint, sample-based predictions.

◆ Current state

hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.

◆ Where it's heading

Two threads dominate. The first is coverage of output types, which reached its widest point with sample-based and compound scoring. The second, and the one occupying every recent release, is making relative skill degrade gracefully: single-model input, comparison groups with one model, and groups missing the requested baseline have each been converted from a cryptic upstream abort into a defined result. That pattern — inherited scoringutils errors being caught and given hub-specific meaning — is the clearest signal of where this package adds value.

◆ Prediction

Expect continued work smoothing scoringutils error surfaces into hub-aware behaviour, and performance attention on relative skill, which was explicitly optimised in the latest release.

Alternatives to cyclocomp and hubEvals

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 hubEvals.

See all cyclocomp alternatives → · See all hubEvals alternatives →

Recent activity from cyclocomp and hubEvals

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 24d agohubEvalsScored-forecast counts and faster relative skill
  2. 1mo agohubEvalsDisaggregated relative skill no longer aborts the whole call
  3. 1mo agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
  4. 5mo agocyclocompcyclocomp_package_dir() gains a quiet argument
  5. 5mo agohubEvalsSample output types and multivariate compound scoring
  6. 6mo agohubEvalsScoring on transformed scales via transform arguments
  7. 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
  8. 2y agocyclocompLarge speedup on long linear code
  9. 2y agocyclocompComplexity checks run against a local package tree

Frequently asked questions

What is the difference between cyclocomp and hubEvals?

Both compete on the same themes — r-package — within Analytics. hubEvals 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.

Is cyclocomp better than hubEvals?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hubEvals 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.

What are the best alternatives to cyclocomp?

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.

What are the best alternatives to hubEvals?

Top hubEvals alternatives in Analytics are ranked by recent ship velocity. Browse the "hubEvals alternatives" section above for the current picks, or visit /alternatives/hubevals for the full list with editorial commentary on each.