tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
chattr vs lime
A side-by-side editorial comparison of chattr and lime — release velocity, themes, recent moves, and the top alternatives to consider.
chattr vs lime: at a glance
What is chattr?
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
chattr puts a large language model inside the RStudio IDE, either through a Shiny app or directly at the console. As of 0.3.0 it no longer talks to any model provider itself: all integration goes through ellmer, and the hand-written OpenAI, Databricks and LlamaGPT backends were removed. The package's supported model list is now whatever ellmer supports, and the Shiny app streams responses through ellmer rather than managing a background process.
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.
chattr vs lime: editorial side-by-side
chattr
0.0ANALYTICS
chattr deleted every LLM integration it had written and outsourced the lot to ellmer
◆ Current state
chattr puts a large language model inside the RStudio IDE, either through a Shiny app or directly at the console. As of 0.3.0 it no longer talks to any model provider itself: all integration goes through ellmer, and the hand-written OpenAI, Databricks and LlamaGPT backends were removed. The package's supported model list is now whatever ellmer supports, and the Shiny app streams responses through ellmer rather than managing a background process.
◆ Where it's heading
The first two releases show why that happened. Each provider brought its own error formats, token discovery and response handling, and 0.2.0 is largely a list of per-provider repairs — OpenAI error parsing, Copilot token discovery and model defaults, a new Databricks foundation model backend. Maintaining that surface scales linearly with the number of providers, and the pivot to ellmer trades it for a single dependency. The cost shows up immediately in 0.3.1, which exists solely to absorb a change in ellmer's token object.
◆ Prediction
Expect chattr's releases to now track ellmer's, as 0.3.1 already does, with the package's own work concentrating on the IDE experience rather than model connectivity. New provider support will arrive without a chattr release at all.
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 chattr 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 chattr 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.
Recent activity from chattr and lime
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agolimexgboost compatibility restored across versions
- 0y agochattrAdapts to ellmer's token object change
- 1y agochattrAll model integration moves to ellmer, direct backends removed ⚡
- 2y agochattrDatabricks foundation models added; per-provider error handling fixed
- 2y agochattrFirst release: LLM chat in the RStudio console and app
- 3y agolimeMaintainer handover and general upkeep
- 5y agolimeShiny dependencies moved to Suggests
- 6y agolimeNamespace fix for glmnet changes
- 7y agolimegower_pow added and lambda aligned with the Python implementation
- 8y agolimeh2o support, NA handling, and date columns held during permutation
Frequently asked questions
What is the difference between chattr and lime?
They serve adjacent needs but don't currently overlap on shipped themes. chattr 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 chattr better than lime?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. chattr 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 chattr?
Top chattr alternatives in Analytics are ranked by recent ship velocity. Browse the "chattr alternatives" section above for the current picks, or visit /alternatives/chattr 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.