tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and ymlthis — release velocity, themes, recent moves, and the top alternatives to consider.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
ymlthis built R Markdown YAML front matter programmatically — a fluent `yml_*()` interface plus RStudio add-ins, so users did not have to hand-write metadata blocks whose valid fields were scattered across output-format documentation. Version 1.0.0 declares the package retired, with only CRAN-preserving changes to follow, and states the reason plainly: Quarto now provides good YAML support.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
The package's roadmap is not its own — it tracks a CDISC standard that is still moving, and 0.3.0 is what happens when the standard revises: object model, read and write paths, and JSON backend all changed together. Performance was addressed in the same pass, which matters because submission datasets are large enough that a slow serialiser is a real constraint.
The next significant release will most likely follow the next Dataset-JSON schema revision rather than an internal roadmap, given that 0.3.0 was driven entirely by the 1.1.0 update.
ymlthis built R Markdown YAML front matter programmatically — a fluent `yml_*()` interface plus RStudio add-ins, so users did not have to hand-write metadata blocks whose valid fields were scattered across output-format documentation. Version 1.0.0 declares the package retired, with only CRAN-preserving changes to follow, and states the reason plainly: Quarto now provides good YAML support.
The retirement is the endpoint of a long drift. Between 2020 and 2022 every release was reactive — patching around a crayon update that mangled rendered YAML, tracking shiny 1.6, following roxygen2 7.0.0, fixing a typo in an add-in. No new capability has landed in six years, and the four-year gap before 1.0.0 had already answered the question the release note finally makes explicit.
Nothing further of substance is expected — the stated policy is changes only where CRAN requires them, so the next release, if any, will be a compatibility patch.
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 datasetjson or ymlthis.
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.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
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.
See all datasetjson alternatives → · See all ymlthis alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. datasetjson and ymlthis 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. datasetjson and ymlthis 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 datasetjson alternatives in Analytics are ranked by recent ship velocity. Browse the "datasetjson alternatives" section above for the current picks, or visit /alternatives/datasetjson for the full list with editorial commentary on each.
Top ymlthis alternatives in Analytics are ranked by recent ship velocity. Browse the "ymlthis alternatives" section above for the current picks, or visit /alternatives/ymlthis for the full list with editorial commentary on each.