tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of chattr and tern.rbmi — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window.
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.
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.
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.
tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window.
This is a thin adapter package and behaves like one — it moves when CRAN or an upstream dependency forces it to. Between 2022 and 2024 the feed shows only version bumps, and the 2025 releases are packaging concerns rather than analysis changes.
Expect the next release to be triggered by a CRAN check failure or an {rbmi} update rather than by new tabulation features.
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 tern.rbmi.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all chattr alternatives → · See all tern.rbmi alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. chattr and tern.rbmi 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. chattr and tern.rbmi 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.
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.
Top tern.rbmi alternatives in Analytics are ranked by recent ship velocity. Browse the "tern.rbmi alternatives" section above for the current picks, or visit /alternatives/tern-rbmi for the full list with editorial commentary on each.