ggpointless
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
A side-by-side editorial comparison of checkhelper and qol — release velocity, themes, recent moves, and the top alternatives to consider.
checkhelper grew from a check wrapper into a CRAN pre-submission auditor.
1.0.0 added a whole audit_* family — audit_downloads(), audit_description(), audit_dontrun() and audit_citation() — each parsing package source statically and returning a tibble of hits paired with a suggested fix. The package is now defending that position: 1.0.1 rc1 is a submission candidate answering a CRAN archival notice, after roxygen2 8.x moved DESCRIPTION's RoxygenNote field and broke a find_missing_tags() test fixture.
A SAS-to-R comfort layer that has quietly grown into its own dialect.
qol is a one-maintainer R package aimed at analysts moving from SAS: SAS-shaped verbs (compute., if./else_if., retain_value, do_if blocks), format-driven tabulation through any_table()/summarise_plus(), and styled Excel output as the default destination. Releases land roughly monthly and each one is large. The recent line has shifted from adding verbs to letting conditions be written as parsed character strings, which is the closest the package gets to reproducing SAS syntax inside R.
1.0.0 added a whole audit_* family — audit_downloads(), audit_description(), audit_dontrun() and audit_citation() — each parsing package source statically and returning a tibble of hits paired with a suggested fix. The package is now defending that position: 1.0.1 rc1 is a submission candidate answering a CRAN archival notice, after roxygen2 8.x moved DESCRIPTION's RoxygenNote field and broke a find_missing_tags() test fixture.
The design commitment is static analysis — AST walks via getParseData(), line-by-line Rd reading, no eval() and no namespace loading — so the tool can report on a package it never runs. That commitment is what made the roxygen2 8.x break survivable: the audit pipeline itself was verified correct under 8.1.0 and only the test scaffolding had to go, now guarded by a dedicated regression test. fix_globals(write = TRUE) is being sanded down in parallel, no longer flattening per-function grouping comments or writing a degenerate empty globalVariables() shell.
The immediate move is the 1.0.1 submission itself, clearing the archival notice. Beyond that, each additional CRAN incoming-check rule remains a candidate for another audit_* function; the open question these notes still leave is whether the family ever gets a single combined entry point.
qol is a one-maintainer R package aimed at analysts moving from SAS: SAS-shaped verbs (compute., if./else_if., retain_value, do_if blocks), format-driven tabulation through any_table()/summarise_plus(), and styled Excel output as the default destination. Releases land roughly monthly and each one is large. The recent line has shifted from adding verbs to letting conditions be written as parsed character strings, which is the closest the package gets to reproducing SAS syntax inside R.
Three threads are visible across these releases. Syntax fidelity is the newest: ifelse_multi() introduced character-string conditions with SAS-style writing, and if./else_if. immediately picked the style up. Tabulation flexibility is the constant — any_table() gains per-variable statistic selection, nested variable combinations in brackets, vector order_by, compute support. The third is ecosystem plumbing the maintainer builds when a gap appears: file I/O in 1.3.0, a console message system, global style options, macro variables, and in 1.3.2 a code_statistics() script scanner. Renames to dodge data.table and dplyr masking recur often enough to be a pattern.
The maintainer flagged the new percentile behaviour as a first iteration that only works with few grouping variables, so a performance pass on it is the clearest outstanding item. Beyond that the character-condition syntax has reached three functions in two releases and looks likely to spread to the remaining filter-bearing verbs.
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 checkhelper or qol.
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
surveytidy taught every dplyr verb to operate on a whole collection of surveys at once.
surveycore declared its API stable with every survey design type covered.
PEIMAN2 cut its annotation database loose from its release cycle without breaking CRAN.
prospectr spent its biggest release in years fixing spectra it had been quietly mangling.
See all checkhelper alternatives → · See all qol alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-packages — within Infra & APIs. checkhelper 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. checkhelper 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 Infra & APIs products to evaluate alongside.
Top checkhelper alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "checkhelper alternatives" section above for the current picks, or visit /alternatives/checkhelper for the full list with editorial commentary on each.
Top qol alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "qol alternatives" section above for the current picks, or visit /alternatives/qol for the full list with editorial commentary on each.