mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
datawizard vs mlr3tuning
A side-by-side editorial comparison of datawizard and mlr3tuning — release velocity, themes, recent moves, and the top alternatives to consider.
datawizard vs mlr3tuning: at a glance
What is datawizard?
datawizard is turning easystats' data layer into a general-purpose I/O and reshaping tool
datawizard handles the data preparation half of the easystats stack — reshaping, recoding, describing, and reading and writing files. The 1.x releases have pushed hardest on I/O: parquet via nanoparquet, then password-protected R formats, alongside a run of breaking cleanups in data_to_wide(), data_modify() and describe_distribution().
What is mlr3tuning?
mlr3tuning is rebuilding its async machinery under a stable public surface
mlr3tuning provides hyperparameter optimization for the mlr3 ecosystem, and its recent history is dominated by the asynchronous tuning path: archive freezing, callback stages around queue evaluation, and version-locked compatibility with the rush backend. Releases pair a small feature with several fixes and an explicit compatibility line naming the mlr3 or rush version they track. The most recent release drops all workarounds for older rush versions, which suggests that dependency has stabilized enough to require rather than accommodate.
datawizard vs mlr3tuning: editorial side-by-side
datawizard
0.0ANALYTICS
datawizard is turning easystats' data layer into a general-purpose I/O and reshaping tool
◆ Current state
datawizard handles the data preparation half of the easystats stack — reshaping, recoding, describing, and reading and writing files. The 1.x releases have pushed hardest on I/O: parquet via nanoparquet, then password-protected R formats, alongside a run of breaking cleanups in data_to_wide(), data_modify() and describe_distribution().
◆ Where it's heading
The package is willing to break its own interfaces to reach behavior users expect from tidyr and friends — data_to_wide() explicitly moved toward pivot_wider() semantics, and data_modify() stopped guessing whether a string was an expression. Output formatting is consolidating behind insight's display() and tinytable. The direction is fewer surprises and more file formats, not more statistics.
◆ Prediction
Expect encryption and format support to extend past R-native files if it continues, and further alignment of print and display behavior with the shared insight infrastructure.
mlr3tuning
2.5ANALYTICS
mlr3tuning is rebuilding its async machinery under a stable public surface
◆ Current state
mlr3tuning provides hyperparameter optimization for the mlr3 ecosystem, and its recent history is dominated by the asynchronous tuning path: archive freezing, callback stages around queue evaluation, and version-locked compatibility with the rush backend. Releases pair a small feature with several fixes and an explicit compatibility line naming the mlr3 or rush version they track. The most recent release drops all workarounds for older rush versions, which suggests that dependency has stabilized enough to require rather than accommodate.
◆ Where it's heading
Two things are being tidied at once. The async archive is converging on a consistent data.table representation across batch and async variants, so results are shaped the same regardless of how tuning ran. Separately, the package is becoming a better ecosystem citizen — unioning tuner properties on load instead of overwriting them, removing its callbacks on unload, and raising informative errors from AutoTuner accessors on an untrained model. Both are the marks of a package used as a dependency more than as a destination.
◆ Prediction
With rush pinned to 1.2.0 and the compatibility shims gone, the next release is likely to expose more of the async path through callbacks rather than change the tuning interface.
Alternatives to datawizard and mlr3tuning
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 datawizard or mlr3tuning.
mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
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
tidyposterior
A finished Bayesian model-comparison package in pure maintenance mode
See all datawizard alternatives → · See all mlr3tuning alternatives →
Recent activity from datawizard and mlr3tuning
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18d agomlr3tuningmlr3tuning 1.6.1 stops clobbering other packages' tuner properties
- 3mo agodatawizardEncrypted data files via a password argument on read/write
- 4mo agomlr3tuningmlr3tuning 1.6.0 aligns archive column order across tuning classes
- 8mo agomlr3tuningmlr3tuning 1.5.1 tracks xgboost 3.1.2.1
- 8mo agomlr3tuningmlr3tuning 1.5.0 adds queue evaluation stages to async callbacks
- 10mo agodatawizarddata_to_wide() moves toward pivot_wider() semantics
- 1y agodatawizardParquet read and write support via nanoparquet
- 1y agomlr3tuningmlr3tuning 1.4.0 unifies logging under a base mlr3 logger
- 1y agodatawizarddata_modify() stops inferring expressions from strings
- 1y agodatawizarddatawizard 1.0.2
- 1y agodatawizarddata_arrange() preserves single-column data frames
- 1y agomlr3tuningmlr3tuning 1.3.0 adds a frozen async archive and leaner worker storage
Frequently asked questions
What is the difference between datawizard and mlr3tuning?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3tuning 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 datawizard better than mlr3tuning?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3tuning 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 datawizard?
Top datawizard alternatives in Analytics are ranked by recent ship velocity. Browse the "datawizard alternatives" section above for the current picks, or visit /alternatives/datawizard for the full list with editorial commentary on each.
What are the best alternatives to mlr3tuning?
Top mlr3tuning alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3tuning alternatives" section above for the current picks, or visit /alternatives/mlr3tuning for the full list with editorial commentary on each.