tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of hoardr and tern — release velocity, themes, recent moves, and the top alternatives to consider.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
hoardr manages local cache directories for other R packages — where files go, how they are keyed, whether they exist. It underpins caching in several rOpenSci data clients. The last functional additions were in 2018; everything since is a patch issued because CRAN reported a test failure or the maintainer changed.
tern is migrating its entire analysis-function catalogue off make_afun(), one release at a time.
tern builds the clinical-trial tables, listings, and graphs layer on top of rtables — occurrence counts, survival summaries, ANCOVA, incidence rates, subgroup and biomarker tabulations. The visible work across the window is a systematic refactor: dozens of analysis functions rewritten to drop make_afun() and adopt a common analysis-function style driven by rtables' additional_fun_params. Feature additions ride along with it.
hoardr manages local cache directories for other R packages — where files go, how they are keyed, whether they exist. It underpins caching in several rOpenSci data clients. The last functional additions were in 2018; everything since is a patch issued because CRAN reported a test failure or the maintainer changed.
This is infrastructure that has reached its final shape. Three of the last three releases were reactive: two responses to CRAN test-failure notifications, one to a maintainer handover. The single behavioural change in that stretch — forward slashes in paths on every operating system — is a consistency fix for downstream packages rather than a feature. Its release cadence is set by CRAN's checks, not by demand.
Expect the next release to be triggered by another CRAN check failure rather than by new functionality, matching every release since 2018.
tern builds the clinical-trial tables, listings, and graphs layer on top of rtables — occurrence counts, survival summaries, ANCOVA, incidence rates, subgroup and biomarker tabulations. The visible work across the window is a systematic refactor: dozens of analysis functions rewritten to drop make_afun() and adopt a common analysis-function style driven by rtables' additional_fun_params. Feature additions ride along with it.
This is a multi-release architectural migration, not incremental polish. Each release converts another batch of functions, and the count is large — roughly two dozen in the most recent entry alone, after a comparable batch the release before. Alongside it, the denom parameter is being threaded through counting functions and g_lineplot is accumulating layout control, both patterns of standardising arguments that previously varied per function.
The refactor should continue until the make_afun() dependency is gone entirely, with the remaining tabulate_* and biomarker functions the likely next batch; the entries give no date for completion.
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 hoardr or tern.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. hoardr and tern are shipping at a similar cadence (velocity 0.0 vs 0.0, 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. hoardr and tern are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top hoardr alternatives in Analytics are ranked by recent ship velocity. Browse the "hoardr alternatives" section above for the current picks, or visit /alternatives/hoardr for the full list with editorial commentary on each.
Top tern alternatives in Analytics are ranked by recent ship velocity. Browse the "tern alternatives" section above for the current picks, or visit /alternatives/tern for the full list with editorial commentary on each.