tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of ijtiff and rlistings — release velocity, themes, recent moves, and the top alternatives to consider.
A TIFF reader for scientific imaging that spent its recent releases shedding weight and fixing memory bugs.
ijtiff reads and writes TIFF files the way ImageJ writes them, which ordinary R TIFF readers get wrong — multi-channel, multi-frame, and unusual bit depths. The 3.1.x line is dominated by memory correctness in the C tag-handling layer, alongside dropping the large imager dependency from the display path. Cadence is sporadic, with multi-year gaps.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
rlistings renders clinical-trial subject listings and paginates them for regulatory output, sitting alongside rtables on the shared formatters engine. The releases in this window are dominated by pagination correctness: repeated key columns across pages, splitting by a variable, ordered-factor handling, column gaps, and font metrics. Development is a large rotating contributor set inside the insightsengineering organisation.
ijtiff reads and writes TIFF files the way ImageJ writes them, which ordinary R TIFF readers get wrong — multi-channel, multi-frame, and unusual bit depths. The 3.1.x line is dominated by memory correctness in the C tag-handling layer, alongside dropping the large imager dependency from the display path. Cadence is sporadic, with multi-year gaps.
Two threads run through the window. The C layer is being hardened — memory leaks in tag handling, buffer cleanup, PROTECT errors, validation of malformed files — which is the kind of work that surfaces when a package gets run against real-world files at volume. Separately, the R layer is shedding dependencies, with base graphics replacing imager for display. Both make the package cheaper and safer to depend on rather than more capable.
Expect continued C-level correctness work rather than format features, since three of the last three substantive releases were memory or compiler fixes.
rlistings renders clinical-trial subject listings and paginates them for regulatory output, sitting alongside rtables on the shared formatters engine. The releases in this window are dominated by pagination correctness: repeated key columns across pages, splitting by a variable, ordered-factor handling, column gaps, and font metrics. Development is a large rotating contributor set inside the insightsengineering organisation.
The package is progressively delegating pagination to formatters rather than implementing it — paginate_listing() was refactored to call formatters' paginate_to_mpfs() directly, and truetype font support arrived through a new formatters API. That reduces duplicated logic but ties the package's page-break behaviour to a dependency it shares with rtables. Feature work beyond pagination is thin: better error messages for unsupported column classes, a cheatsheet.
Expect pagination fidelity to remain the focus, with changes arriving as formatters exposes more of its layout machinery rather than as rlistings-native features.
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 ijtiff or rlistings.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
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.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all ijtiff alternatives → · See all rlistings alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. ijtiff and rlistings 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. ijtiff and rlistings 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 ijtiff alternatives in Analytics are ranked by recent ship velocity. Browse the "ijtiff alternatives" section above for the current picks, or visit /alternatives/ijtiff for the full list with editorial commentary on each.
Top rlistings alternatives in Analytics are ranked by recent ship velocity. Browse the "rlistings alternatives" section above for the current picks, or visit /alternatives/rlistings for the full list with editorial commentary on each.