r2rtf
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
A side-by-side editorial comparison of slider and tabnet — release velocity, themes, recent moves, and the top alternatives to consider.
Feature-complete since 2021, and every release since has been paying CRAN's C API bill
slider provides sliding-window and index-aware window functions for R, with a C implementation underneath and a specialised fast path for common aggregations. The user-facing surface has been stable since 0.3.0 in late 2022. Everything after that is compliance and platform work: STRING_PTR removed in 0.3.2, OBJECT() removed in 0.3.3, a vctrs callable's C signature corrected, and the minimum R version raised twice.
A tabular deep-learning model in R that keeps widening what counts as a tabular task.
tabnet ports the TabNet attentive tabular architecture to R on torch, wired into tidymodels through parsnip so it slots into workflows, tuning, and case weights like any other engine. The model surface has grown well past plain supervised fitting: unsupervised pretraining, missing values in predictors, multi-outcome fitting, hierarchical multi-label classification, and built-in explainability via tabnet_explain(). The 0.9.x line has been consolidating rather than adding, with 0.9.0 finally making hierarchical classification work correctly by accounting for the ancestor matrix.
slider provides sliding-window and index-aware window functions for R, with a C implementation underneath and a specialised fast path for common aggregations. The user-facing surface has been stable since 0.3.0 in late 2022. Everything after that is compliance and platform work: STRING_PTR removed in 0.3.2, OBJECT() removed in 0.3.3, a vctrs callable's C signature corrected, and the minimum R version raised twice.
Two forces set the release schedule, and neither is feature demand. The first is CRAN closing off non-API C entry points, which packages reaching into R internals for speed have to unwind one accessor at a time — slider is on its second such release with no visible loss of function. The second is vctrs, whose breaking changes slider absorbs ahead of time; 0.2.2 exists solely to prepare for one. The last release that added anything callers can see was 0.3.0's slider_plus() and slider_minus() extension hooks.
Expect the pattern to continue: another non-API accessor removal or a vctrs compatibility release, rather than new window functions. The C-level surface is the only part of this package still moving.
tabnet ports the TabNet attentive tabular architecture to R on torch, wired into tidymodels through parsnip so it slots into workflows, tuning, and case weights like any other engine. The model surface has grown well past plain supervised fitting: unsupervised pretraining, missing values in predictors, multi-outcome fitting, hierarchical multi-label classification, and built-in explainability via tabnet_explain(). The 0.9.x line has been consolidating rather than adding, with 0.9.0 finally making hierarchical classification work correctly by accounting for the ancestor matrix.
Two threads run through the release history. The first is task surface — each minor version tends to admit a class of problem the model previously could not express, from missing data to hierarchy to imbalanced binary outcomes. The second is torch-level performance and correctness, visible in the torch_ignite_adam default that cut pretraining time roughly 30% and the fix for optimizers frozen after checkpointing on cuda and mps. Tidymodels integration is treated as a first-class obligation, with parsnip breaking changes tracked release by release.
The hierarchical path is the least finished: 0.5.0 introduced it and 0.9.0 only just made it effective, so the next releases most likely extend evaluation and explainability to hierarchical fits rather than adding another task type.
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 slider or tabnet.
The clinical-report table engine learned Chinese, then learned to leave RTF entirely
New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing
The stubbing library added httr2 support, then spent a year cutting itself free of everything else
crul took mocking back from webmockr and made it a property of the client itself
Six releases, six identical bodies — the feed carries the package abstract instead of release notes
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
See all slider alternatives → · See all tabnet alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tabnet is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. tabnet is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top slider alternatives in Analytics are ranked by recent ship velocity. Browse the "slider alternatives" section above for the current picks, or visit /alternatives/slider for the full list with editorial commentary on each.
Top tabnet alternatives in Analytics are ranked by recent ship velocity. Browse the "tabnet alternatives" section above for the current picks, or visit /alternatives/tabnet for the full list with editorial commentary on each.