tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and lobstr — 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.
R's object inspector is losing its view of the internals as CRAN closes off the private C API.
lobstr exposes R's internal object representation — sizes, addresses, reference counts, abstract syntax trees. Its two most recent releases are both driven by R's move to a restricted public C API: 1.1.3 stopped reporting a vector's truelength and reworked the reference indicator into refs:n, and 1.2.0 changed what sxp(expand = "environment") shows in order to stay compliant. 1.2.0 also adds src() for exploring srcref objects.
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.
lobstr exposes R's internal object representation — sizes, addresses, reference counts, abstract syntax trees. Its two most recent releases are both driven by R's move to a restricted public C API: 1.1.3 stopped reporting a vector's truelength and reworked the reference indicator into refs:n, and 1.2.0 changed what sxp(expand = "environment") shows in order to stay compliant. 1.2.0 also adds src() for exploring srcref objects.
The package is being rebuilt inside a shrinking window of what R permits. Each release trades some introspection depth for API conformance while trying to keep the diagnostic value intact — showing promise expressions instead of internal frame structures, replacing named with a documented refs scale. Where the constraint does not bite, development continues normally: src() is genuinely new, and the environment-binding fixes remove long-standing errors on for-loop and immediate bindings.
Expect further conformance work, since the notes describe it as ongoing, with any remaining non-API-dependent readouts either reworked or dropped as R tightens further.
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 lobstr.
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 lobstr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. datasetjson and lobstr 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 lobstr 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 lobstr alternatives in Analytics are ranked by recent ship velocity. Browse the "lobstr alternatives" section above for the current picks, or visit /alternatives/lobstr for the full list with editorial commentary on each.