tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and typst-gather — 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.
Extracted from Quarto's CLI, typst-gather learned to explain a dependency tree before fetching it.
typst-gather collects Typst packages into a local cache so documents build offline and hermetically. It was extracted from quarto-cli and reached CRAN-equivalent shape in three releases over a single day, then added an `analyze` subcommand that walks `@Preview` and `@Local` imports — following transitive dependencies of local packages — and prints structured JSON without downloading or copying anything.
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.
typst-gather collects Typst packages into a local cache so documents build offline and hermetically. It was extracted from quarto-cli and reached CRAN-equivalent shape in three releases over a single day, then added an `analyze` subcommand that walks `@Preview` and `@Local` imports — following transitive dependencies of local packages — and prints structured JSON without downloading or copying anything.
The 0.2.0 restructuring is the tell: subcommands with backwards compatibility, config readable from stdin, and every diagnostic message moved to stderr so stdout carries nothing but JSON. Those are the conventions of a tool meant to be called by another program, not typed by a person. Given its origin inside Quarto's toolchain, the plausible consumer is a build system that needs to know a document's package requirements before deciding what to fetch.
The analyze path currently reports imports; the natural extension visible from here is acting on that report — lockfile output or verification that a cache satisfies a document's dependency set — though the entries do not commit to either.
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 typst-gather.
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 typst-gather 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 typst-gather 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 typst-gather 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 typst-gather alternatives in Analytics are ranked by recent ship velocity. Browse the "typst-gather alternatives" section above for the current picks, or visit /alternatives/typst-gather for the full list with editorial commentary on each.