tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and rtflite — 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.
rtflite stopped being an RTF writer and became the conversion layer for clinical table output.
rtflite generates the RTF tables clinical study reports are built from, a Python answer to the R tooling that has owned this niche. Over one dense month it grew a full export path: DOCX in 2.2.0, DOCX concatenation in 2.3.0, a configurable LibreOffice converter in 2.4.0, and HTML plus PDF in 2.5.0. The three releases since have been documentation, test infrastructure, and typing work — the feature push has stopped and consolidation has started.
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.
rtflite generates the RTF tables clinical study reports are built from, a Python answer to the R tooling that has owned this niche. Over one dense month it grew a full export path: DOCX in 2.2.0, DOCX concatenation in 2.3.0, a configurable LibreOffice converter in 2.4.0, and HTML plus PDF in 2.5.0. The three releases since have been documentation, test infrastructure, and typing work — the feature push has stopped and consolidation has started.
Every format addition routes through the same LibreOffice converter rather than a per-format implementation, and 2.4.0's breaking change made that converter an injectable object you can configure and reuse. That is the shape of a package expecting to run inside a pipeline that produces hundreds of tables, not one that converts a document at a time. The recent quiet — snapshot tests moved onto `pytest-r-snapshot`, docs migrated, pandas and pyarrow dropped from dev dependencies — reads as work to stay dependency-light while the surface stabilizes.
With the export matrix filled in and three consecutive infrastructure-only releases, the next substantive change is most likely on the input side — table construction and pagination — since `page_by` and `subline_by` are the only feature area still generating bug reports in these notes.
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 rtflite.
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 rtflite alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — pharmaverse — within Analytics. datasetjson and rtflite 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 rtflite 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 rtflite alternatives in Analytics are ranked by recent ship velocity. Browse the "rtflite alternatives" section above for the current picks, or visit /alternatives/rtflite for the full list with editorial commentary on each.