tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of censored and textrecipes — release velocity, themes, recent moves, and the top alternatives to consider.
censored keeps survival models aligned with parsnip's shifting prediction contracts
censored supplies survival-analysis engines to parsnip, and its release history is dominated by staying in step with the rest of tidymodels rather than shipping independent features. The 0.2.0 and 0.3.0 releases added engines and prediction types; everything since has been contract alignment — quantile prediction format, hardhat test adaptation, flexsurv preparation.
Text features finally stay sparse all the way to the model.
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
censored supplies survival-analysis engines to parsnip, and its release history is dominated by staying in step with the rest of tidymodels rather than shipping independent features. The 0.2.0 and 0.3.0 releases added engines and prediction types; everything since has been contract alignment — quantile prediction format, hardhat test adaptation, flexsurv preparation.
The package is settling into a downstream role where parsnip and hardhat set the interface and censored implements it for censored regression. Breaking changes arrive from upstream, not from new ideas here. The substantive engine work — aorsf, flexsurvspline, glmnet multi_predict — is behind it, and recent cycles are thin.
Expect the next releases to track further parsnip prediction-type changes rather than add engines; the entries do not show new survival methods in progress.
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
Two forces drive this package. One is memory: text produces wide, mostly-zero matrices, and the sparse work is the direct answer, landing in the same period that workflows learned to fit and predict on dgCMatrix input. The other is upstream churn — the tweets tokenizer was deprecated because tokenizers deprecated it, the politeness feature disappeared when textfeatures left Suggests. The package's own agenda is consistency; its release timing belongs to its dependencies.
Expect the sparse argument to spread to the remaining column-producing steps, since only four of them have it, and expect more steps to be reworked as recipes' own sparse-data support matures.
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 censored or textrecipes.
Finished, widely taught, and shipping roxygen fixes.
The package that made calibration a step instead of an afterthought.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
patchwork stopped being a ggplot composer and became a page composer.
See all censored alternatives → · See all textrecipes alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — tidymodels — within Analytics. censored and textrecipes 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. censored and textrecipes 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 censored alternatives in Analytics are ranked by recent ship velocity. Browse the "censored alternatives" section above for the current picks, or visit /alternatives/censored for the full list with editorial commentary on each.
Top textrecipes alternatives in Analytics are ranked by recent ship velocity. Browse the "textrecipes alternatives" section above for the current picks, or visit /alternatives/textrecipes for the full list with editorial commentary on each.