tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
dtplyr vs lime
A side-by-side editorial comparison of dtplyr and lime — release velocity, themes, recent moves, and the top alternatives to consider.
dtplyr vs lime: at a glance
What is dtplyr?
dtplyr stopped hijacking data.table objects and became an opt-in translator
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
What is lime?
lime survives on compatibility patches years after its research moment
lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.
dtplyr vs lime: editorial side-by-side
dtplyr
0.0ANALYTICS
dtplyr stopped hijacking data.table objects and became an opt-in translator
◆ Current state
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
◆ Where it's heading
The package is trailing dplyr's own feature releases rather than leading them, adding each new verb once it settles upstream. Performance work is targeted at specific verbs where data.table has a faster primitive: setorder() for arrange(), reference drops for select(), rleid() for consecutive_id(). Release cadence has thinned considerably since 2023.
◆ Prediction
Expect further one-for-one translations as dplyr adds verbs, and continued fixes around .by and non-standard column names; the entries show no sign of a broader redesign.
lime
0.0ANALYTICS
lime survives on compatibility patches years after its research moment
◆ Current state
lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.
◆ Where it's heading
The package is in custodial maintenance — kept installable and compatible with the model packages it explains, rather than developed. The 2022 handover is the most consequential entry in the window because it determined that the package would keep getting patches at all.
◆ Prediction
Expect the next release to be another compatibility fix triggered by an upstream model package, not new explanation methods.
Alternatives to dtplyr and lime
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 dtplyr or lime.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
Recent activity from dtplyr and lime
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agolimeCompatibility across all xgboost versions
- 11mo agodtplyrreframe(), case_match() and consecutive_id() gain translations
- 3y agodtplyrcrayon dependency dropped
- 3y agodtplyrVerbs stop auto-dispatching; lazy_dt() now required ⚡
- 3y agodtplyrdtplyr 1.2.2
- 3y agolimeMaintainer handover to Emil Hvitfeldt
- 4y agodtplyrdtplyr 1.2.1
- 4y agodtplyrEight tidyr verbs gain data.table translations
- 5y agolimeorder() fix and lighter dependencies
- 6y agolimeNamespace fix following glmnet changes
- 7y agolimeexplain() gains pass-through args and gower_pow tuning
- 8y agolimeh2o support, NA handling and date feature types
Frequently asked questions
What is the difference between dtplyr and lime?
They serve adjacent needs but don't currently overlap on shipped themes. dtplyr and lime 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 dtplyr better than lime?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dtplyr and lime 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 dtplyr?
Top dtplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dtplyr alternatives" section above for the current picks, or visit /alternatives/dtplyr for the full list with editorial commentary on each.
What are the best alternatives to lime?
Top lime alternatives in Analytics are ranked by recent ship velocity. Browse the "lime alternatives" section above for the current picks, or visit /alternatives/lime-r for the full list with editorial commentary on each.