tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
rlistings vs tabnet
A side-by-side editorial comparison of rlistings and tabnet — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
rlistings vs tabnet: at a glance
What is rlistings?
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.
What is tabnet?
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.
rlistings vs tabnet: editorial side-by-side
rlistings
0.0ANALYTICS
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
Expect pagination fidelity to remain the focus, with changes arriving as formatters exposes more of its layout machinery rather than as rlistings-native features.
tabnet
2.5ANALYTICS
A tabular deep-learning model in R that keeps widening what counts as a tabular task.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to rlistings and tabnet
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 rlistings or tabnet.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all rlistings alternatives → · See all tabnet alternatives →
Recent activity from rlistings and tabnet
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 21d agotabnetvip dependency moves to r-universe
- 2mo agotabnetHierarchical classification made effective, augment() added
- 6mo agotabnetentmax15 and sparsemax15 masks, AUM loss for imbalanced data
- 1y agotabnetBugfix release for R 4.5 and dials tuning
- 1y agorlistingsError and message handling for difftime and zero-row listings
- 1y agorlistingsTrueType font support and col_gap in pagination
- 2y agotabnetCase weights and warm-start parameters via parsnip
- 2y agorlistingssplit_into_pages_by_var() and pagination moved onto formatters
- 2y agotabnetHierarchical multi-label classification via data.tree ⚡
Frequently asked questions
What is the difference between rlistings and tabnet?
Both compete on the same themes — r-package — within Analytics. 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.
Is rlistings better than tabnet?
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.
What are the best alternatives to rlistings?
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.
What are the best alternatives to tabnet?
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.