tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of orbital and r2rtf — release velocity, themes, recent moves, and the top alternatives to consider.
Turning fitted tidymodels into SQL, one model family at a time — and the boosting engines just landed.
orbital converts a fitted tidymodels workflow into a database expression so prediction runs where the data lives, no R session in the loop. Its value is entirely a function of coverage, and 0.5.0 was the largest coverage release yet: catboost and lightgbm boosted trees, rpart decision trees, earth-backed MARS, glmnet multinomial regression, and both randomForest and ranger random forests, all for numeric, class, and probability predictions. The 0.5.1 follow-up is corrective, fixing SQL that Snowflake and other engines rejected because it cast booleans directly to numeric.
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
r2rtf builds the RTF tables, listings and figures that go into clinical study reports, and its recent releases have been about widening who and what it can serve rather than changing how tables are composed. The 1.2.0 release added internationalization — a SimSun font path for Chinese characters plus hyphenation control — and 1.3.0 followed with write_docx() and write_html(), turning the LibreOffice conversion the package had documented into exported functions.
orbital converts a fitted tidymodels workflow into a database expression so prediction runs where the data lives, no R session in the loop. Its value is entirely a function of coverage, and 0.5.0 was the largest coverage release yet: catboost and lightgbm boosted trees, rpart decision trees, earth-backed MARS, glmnet multinomial regression, and both randomForest and ranger random forests, all for numeric, class, and probability predictions. The 0.5.1 follow-up is corrective, fixing SQL that Snowflake and other engines rejected because it cast booleans directly to numeric.
The package has been working outward in rings: recipe preprocessing steps first, then model types, then post-processing via the tailor package in 0.4.0, with show_query() added so users can inspect what actually gets sent. Recent releases show the constraint shifting from R-side translation to SQL dialect compatibility — the bugs now are about what a specific database will accept, not whether a model can be expressed. estimate_orbital_size() in 0.5.1 acknowledges the other practical limit, since generated expressions can grow large enough to matter before you generate them.
With the major boosting and ensemble engines covered, expect the next releases to keep chasing dialect-specific SQL correctness across warehouses rather than adding model families.
r2rtf builds the RTF tables, listings and figures that go into clinical study reports, and its recent releases have been about widening who and what it can serve rather than changing how tables are composed. The 1.2.0 release added internationalization — a SimSun font path for Chinese characters plus hyphenation control — and 1.3.0 followed with write_docx() and write_html(), turning the LibreOffice conversion the package had documented into exported functions.
Two threads run through the window. One is output reach: RTF remains the composition target, but the artifacts that come out of it now include DOCX and HTML, and page numbering can be made table-relative across multi-page tables. The other is durability under a moving R and font stack — the ANSI/Unicode converter was rebuilt, the LaTeX mapping table generated from code rather than shipped as sysdata, unlist() usage fixed for R 4.5, and graphics-device leaks that produced stray Rplots.pdf closed off.
Having exported DOCX and HTML conversion, the likely next step is filling in what those formats lose relative to RTF — pagination and footnote fidelity are the obvious gaps. The i18n path currently covers Chinese only, so additional font families are the other plausible direction.
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 orbital or r2rtf.
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 orbital alternatives → · See all r2rtf alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. orbital and r2rtf 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. orbital and r2rtf 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 orbital alternatives in Analytics are ranked by recent ship velocity. Browse the "orbital alternatives" section above for the current picks, or visit /alternatives/orbital for the full list with editorial commentary on each.
Top r2rtf alternatives in Analytics are ranked by recent ship velocity. Browse the "r2rtf alternatives" section above for the current picks, or visit /alternatives/r2rtf for the full list with editorial commentary on each.