tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
datapack vs lime
A side-by-side editorial comparison of datapack and lime — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:maintenance-mode
datapack vs lime: at a glance
What is datapack?
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
datapack assembles heterogeneous data files and metadata into a single transportable bundle, serialised as an OAI-ORE resource map and BagIt archive, for deposit into repositories like DataONE. Its functional surface settled with the 1.3.x line, which made assembled packages editable rather than write-once. Since then the releases have been sparse and defensive: SHA-256 as the default checksum in 1.4.0, BagIt spec conformance in 1.4.1, and a 2025 patch that states outright it contains no new features.
What is lime?
The R port of LIME has shipped one commit in three years, and it was an xgboost compatibility patch
lime is the R implementation of local interpretable model-agnostic explanations, and it is effectively in preservation rather than development. Its last substantive feature release was 0.5.0 in 2019; 0.5.3 in 2022 recorded a maintainer handover and general upkeep; 0.5.4 in December 2025 exists solely to keep the package working across xgboost versions. Six releases span eight years, and only two of them contain features.
datapack vs lime: editorial side-by-side
datapack
0.0ANALYTICS
The DataONE bundler learned to edit packages in 2017 and has coasted on that ever since
◆ Current state
datapack assembles heterogeneous data files and metadata into a single transportable bundle, serialised as an OAI-ORE resource map and BagIt archive, for deposit into repositories like DataONE. Its functional surface settled with the 1.3.x line, which made assembled packages editable rather than write-once. Since then the releases have been sparse and defensive: SHA-256 as the default checksum in 1.4.0, BagIt spec conformance in 1.4.1, and a 2025 patch that states outright it contains no new features.
◆ Where it's heading
The arc runs from assembly to correctness of the resulting archive. Later releases keep tightening the metadata the resource map must carry — dc:creator always present, dcterms:modified always updated, the package correctly flagged as modified after any access-policy change — because a bundle whose provenance record is subtly wrong is worse than one that fails outright. The three-year gap between 1.4.1 and 1.4.2, and the latter's CRAN-note content, place this package firmly in preservation.
◆ Prediction
Expect the next release, if any, to be another CRAN-compliance patch rather than functional work. The 1.4.2 note that it contains no new features is the clearest statement in the feed about where this package sits.
lime
0.0ANALYTICS
The R port of LIME has shipped one commit in three years, and it was an xgboost compatibility patch
◆ Current state
lime is the R implementation of local interpretable model-agnostic explanations, and it is effectively in preservation rather than development. Its last substantive feature release was 0.5.0 in 2019; 0.5.3 in 2022 recorded a maintainer handover and general upkeep; 0.5.4 in December 2025 exists solely to keep the package working across xgboost versions. Six releases span eight years, and only two of them contain features.
◆ Where it's heading
The pattern is upstream-driven survival: every release since 0.5.0 responds to a change in something lime depends on — glmnet's namespace, order() semantics on data frames, xgboost's interface. The one deliberate change in that stretch was moving htmlwidgets, shiny and shinythemes to Suggests, which lightens installation for the majority of users who never open the interactive explainer. Nothing in the feed indicates work on the explanation method itself.
◆ Prediction
Expect the next release, whenever it comes, to be another compatibility patch triggered by a dependency change rather than anything touching how explanations are computed. The three-year gaps make timing unpredictable.
Alternatives to datapack 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 datapack or lime.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all datapack alternatives → · See all lime alternatives →
Recent activity from datapack and lime
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agolimexgboost compatibility restored across versions
- 10mo agodatapackCRAN documentation and CI cleanup
- 3y agolimeMaintainer handover and general upkeep
- 4y agodatapackBagIt serialisation brought in line with the current spec
- 5y agolimeShiny dependencies moved to Suggests
- 5y agodatapackSHA-256 becomes the default checksum algorithm
- 6y agolimeNamespace fix for glmnet changes
- 6y agodatapackResource map metadata guaranteed; removeRelationships() added
- 7y agolimegower_pow added and lambda aligned with the Python implementation
- 8y agolimeh2o support, NA handling, and date columns held during permutation
- 8y agodatapackupdateMetadata no longer drops package relationships
- 9y agodatapackAssembled data packages become editable in place ⚡
Frequently asked questions
What is the difference between datapack and lime?
Both compete on the same themes — maintenance-mode — within Analytics. datapack 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 datapack better than lime?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. datapack 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 datapack?
Top datapack alternatives in Analytics are ranked by recent ship velocity. Browse the "datapack alternatives" section above for the current picks, or visit /alternatives/datapack 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 for the full list with editorial commentary on each.