mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
timetk vs workflows
A side-by-side editorial comparison of timetk and workflows — release velocity, themes, recent moves, and the top alternatives to consider.
timetk vs workflows: at a glance
What is timetk?
timetk swallowed anomalize whole, then went quiet for two years
timetk handles time series wrangling, visualization, and feature engineering in a tidyverse idiom. Its defining recent move was absorbing the anomalize package outright in 2.9.0, bringing anomaly detection, cleaning, and the associated plots inside timetk rather than leaving them in a sibling package. Development then paused for nearly two years before 2.9.1, a robustness and documentation 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.
timetk vs workflows: editorial side-by-side
timetk
0.0ANALYTICS
timetk swallowed anomalize whole, then went quiet for two years
◆ Current state
timetk handles time series wrangling, visualization, and feature engineering in a tidyverse idiom. Its defining recent move was absorbing the anomalize package outright in 2.9.0, bringing anomaly detection, cleaning, and the associated plots inside timetk rather than leaving them in a sibling package. Development then paused for nearly two years before 2.9.1, a robustness and documentation release.
◆ Where it's heading
The trajectory before the pause was consolidation: fold in adjacent functionality, then make the visualization layer handle many series at once via trelliscopejs, then broaden feature generation with tk_tsfeatures(). The recent release works on the least glamorous layer — internal generics so date parsing and sequence generation behave consistently across Date, POSIXct, hms, yearmon, and yearqtr — which is the kind of foundation work a package does when it has accumulated too many special cases. The long gap and the CI-refresh content suggest maintenance attention rather than a new direction.
◆ Prediction
The stated gap is the unimplemented twitter method for anomalize(), which is the one concrete outstanding item the release notes name; beyond that the recent work points to consolidation rather than expansion.
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 timetk 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 timetk 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
modelbased
modelbased is turning marginal effects into a full contrast grammar
parameters
easystats' parameters package absorbs one more model class every few weeks
tidyposterior
A finished Bayesian model-comparison package in pure maintenance mode
See all timetk alternatives → · See all workflows alternatives →
Recent activity from timetk and workflows
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agotimetktimetk 2.9.1 makes date parsing consistent across time classes
- 11mo agoworkflowsWorkflows gain a postprocessing stage via tailor ⚡
- 1y agoworkflowsSparse matrices work through fit() and predict()
- 2y agoworkflowsaugment() aligns with parsnip; censored regression supported
- 2y agotimetktimetk 2.9.0 absorbs the anomalize package ⚡
- 3y agoworkflowsRegister tuning generics unconditionally
- 3y agoworkflowsMissing parsnip extensions now error early; unsupervised specs supported
- 3y agoworkflowsMode guessing removed; silent offset handling now errors
- 4y agotimetktimetk 2.8.1 exposes trelliscope plotting parameters
- 4y agotimetktimetk 2.8.0 adds trelliscopejs support for many-series plots
- 4y agotimetktimetk 2.7.0 adds tk_tsfeatures() for grouped feature matrices
- 4y agotimetktimetk 2.6.2 adds .week_start and facet direction controls
Frequently asked questions
What is the difference between timetk and workflows?
They serve adjacent needs but don't currently overlap on shipped themes. timetk 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 timetk better than workflows?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. timetk 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 timetk?
Top timetk alternatives in Analytics are ranked by recent ship velocity. Browse the "timetk alternatives" section above for the current picks, or visit /alternatives/timetk 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.