mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
hardhat vs textrecipes
A side-by-side editorial comparison of hardhat and textrecipes — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodels
hardhat vs textrecipes: at a glance
What is hardhat?
hardhat keeps adding the contracts tidymodels needs next
hardhat is the infrastructure layer under tidymodels, defining the preprocessing and extraction contracts other packages implement. Its releases read as a list of new generics and vector classes: extract_postprocessor(), extract_fit_time(), extract_tailor(), and a quantile_pred() class for quantile-regression output. The newest release is narrow warning and missing-value handling in mold().
What is textrecipes?
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.
hardhat vs textrecipes: editorial side-by-side
hardhat
0.0ANALYTICS
hardhat keeps adding the contracts tidymodels needs next
◆ Current state
hardhat is the infrastructure layer under tidymodels, defining the preprocessing and extraction contracts other packages implement. Its releases read as a list of new generics and vector classes: extract_postprocessor(), extract_fit_time(), extract_tailor(), and a quantile_pred() class for quantile-regression output. The newest release is narrow warning and missing-value handling in mold().
◆ Where it's heading
Each addition here lands ahead of a user-facing feature elsewhere in tidymodels — the postprocessor and tailor generics precede the postprocessing workflow, quantile_pred() precedes quantile prediction in parsnip. The package's own surface stays deliberately small and its cadence follows what the rest of the stack is about to need.
◆ Prediction
Expect further extraction generics and prediction-type classes as tidymodels builds out postprocessing, with hardhat's own API remaining thin.
textrecipes
0.0ANALYTICS
Text features finally stay sparse all the way to the model.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to hardhat and textrecipes
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 hardhat or textrecipes.
mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk
timetk swallowed anomalize whole, then went quiet for two years
modelbased
modelbased is turning marginal effects into a full contrast grammar
parameters
easystats' parameters package absorbs one more model class every few weeks
See all hardhat alternatives → · See all textrecipes alternatives →
Recent activity from hardhat and textrecipes
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agohardhatmold() warning and quantile missing-value fixes
- 11mo agohardhatextract_tailor() generic added
- 1y agotextrecipesHashing and TF-IDF steps can emit sparse vectors ⚡
- 1y agohardhatquantile_pred() class for quantile regression output
- 1y agotextrecipesstep_textfeatures() sped up; clean_levels NA bug fixed
- 2y agohardhatextract_postprocessor() and extract_fit_time() generics
- 2y agohardhatDocumentation topic renamed at CRAN's request
- 2y agotextrecipestextfeatures dependency dropped; politeness feature removed
- 2y agotextrecipesuntokenize and normalization return factors
- 2y agotextrecipeskeep_original_cols everywhere; hashing column order fixed
- 3y agotextrecipesTunable arguments documented; name collisions now error
- 3y agohardhatMulti-outcome prediction helpers and one-hot factor encoding
Frequently asked questions
What is the difference between hardhat and textrecipes?
Both compete on the same themes — tidymodels — within Analytics. hardhat 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.
Is hardhat better than textrecipes?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hardhat 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.
What are the best alternatives to hardhat?
Top hardhat alternatives in Analytics are ranked by recent ship velocity. Browse the "hardhat alternatives" section above for the current picks, or visit /alternatives/hardhat for the full list with editorial commentary on each.
What are the best alternatives to textrecipes?
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.