mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
patchwork vs workflows
A side-by-side editorial comparison of patchwork and workflows — release velocity, themes, recent moves, and the top alternatives to consider.
patchwork vs workflows: at a glance
What is patchwork?
patchwork stopped being a ggplot composer and became a page composer.
patchwork assembles plots into compositions with arithmetic operators, and the 1.x line has steadily hardened that grammar: guide and axis collection, free() to exempt a plot from alignment, inset_element() for overlays, and list-like behaviour so lapply() and length() work on a patchwork. Version 1.3.0 added native gt table support. The two releases since are a load-time warning fix and a compatibility pass for the next ggplot2 release.
What is workflows?
The tidymodels pipeline grew a third stage, and it happens after the model runs.
workflows bundles a preprocessor and a model into one object that tidymodels can fit, tune and extract from. Version 1.3.0 added a post stage backed by the tailor package, wired through every generic a workflow supports — augment, tidy, tunable, tune_args, required_pkgs and parameter extraction. Version 1.2.0 added sparse data support so fit() and predict() accept dgCMatrix and sparse tibbles. Earlier releases in view are boundary tightening: erroring on unknown model modes, on trained recipes, and on silently ignored formula offsets.
patchwork vs workflows: editorial side-by-side
patchwork
0.0ANALYTICS
patchwork stopped being a ggplot composer and became a page composer.
◆ Current state
patchwork assembles plots into compositions with arithmetic operators, and the 1.x line has steadily hardened that grammar: guide and axis collection, free() to exempt a plot from alignment, inset_element() for overlays, and list-like behaviour so lapply() and length() work on a patchwork. Version 1.3.0 added native gt table support. The two releases since are a load-time warning fix and a compatibility pass for the next ggplot2 release.
◆ Where it's heading
The centre of gravity is shifting from alignment mechanics to composition scope. Early releases were almost entirely bug fixes against grid and ggplot2 internals — strip placement, fixed aspect ratios, guide merging. Recent ones add object types and escape hatches instead. Between feature cycles the package is in maintenance defined by ggplot2's release calendar, which is what 1.3.1 is in its entirety.
◆ Prediction
Expect wrap_table() to grow beyond gt to other table objects, and expect the next substantive release to be triggered by a ggplot2 internals change rather than by a patchwork roadmap.
workflows
0.0ANALYTICS
The tidymodels pipeline grew a third stage, and it happens after the model runs.
◆ Current state
workflows bundles a preprocessor and a model into one object that tidymodels can fit, tune and extract from. Version 1.3.0 added a post stage backed by the tailor package, wired through every generic a workflow supports — augment, tidy, tunable, tune_args, required_pkgs and parameter extraction. Version 1.2.0 added sparse data support so fit() and predict() accept dgCMatrix and sparse tibbles. Earlier releases in view are boundary tightening: erroring on unknown model modes, on trained recipes, and on silently ignored formula offsets.
◆ Where it's heading
The object is filling out into a complete pipeline description rather than a preprocessing-plus-model pair. Postprocessing is the structural addition — calibration and threshold selection were previously done by hand after prediction, outside anything tidymodels could tune or record — and the fact that it arrived integrated with tunable() and tune_args() rather than as a standalone step is the point. The rest of the arc is the steady tidymodels habit of converting silent guesses into errors.
◆ Prediction
Expect tailor postprocessors to spread through tune and workflowsets next, since the parameter and tuning generics were wired up first, and expect sparse support to extend to more engines after lightgbm.
Alternatives to patchwork and workflows
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 patchwork or workflows.
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 patchwork alternatives → · See all workflows alternatives →
Recent activity from patchwork and workflows
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agoworkflowsWorkflows gain a postprocessing stage via tailor ⚡
- 11mo agopatchworkFix spurious load-time warnings
- 1y agopatchworkCompatibility pass for the next ggplot2 release
- 1y agoworkflowsSparse matrices work through fit() and predict()
- 1y agopatchworkgt tables become first-class patchwork objects ⚡
- 2y agoworkflowsaugment() aligns with parsnip; censored regression supported
- 2y agopatchworkAxis collection and free() arrive
- 3y agopatchworkPatchworks behave like lists; NULL becomes a no-op
- 3y agoworkflowsRegister tuning generics unconditionally
- 3y agoworkflowsMissing parsnip extensions now error early; unsupervised specs supported
- 3y agoworkflowsMode guessing removed; silent offset handling now errors
- 3y agopatchworkClearer error when plotting space is too small
Frequently asked questions
What is the difference between patchwork and workflows?
They serve adjacent needs but don't currently overlap on shipped themes. patchwork and workflows 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 patchwork better than workflows?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. patchwork and workflows 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 patchwork?
Top patchwork alternatives in Analytics are ranked by recent ship velocity. Browse the "patchwork alternatives" section above for the current picks, or visit /alternatives/patchwork for the full list with editorial commentary on each.
What are the best alternatives to workflows?
Top workflows alternatives in Analytics are ranked by recent ship velocity. Browse the "workflows alternatives" section above for the current picks, or visit /alternatives/workflows-r for the full list with editorial commentary on each.