tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of chattr and rstantools — 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.
The scaffolding layer for Stan-backed R packages, maintained rather than extended.
rstantools generates and maintains the build infrastructure that lets an R package ship Stan models — the inst/stan layout, the auto-generated C++, the Rcpp module loading, and the posterior_* generics downstream packages implement. Its releases are dominated by keeping that scaffolding compiling as Stan, StanHeaders, and rstan move underneath it. Version 2.7.0 continues that pattern, its one user-facing change being an allowance for deprecated syntax in specified versions of specified packages.
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.
rstantools generates and maintains the build infrastructure that lets an R package ship Stan models — the inst/stan layout, the auto-generated C++, the Rcpp module loading, and the posterior_* generics downstream packages implement. Its releases are dominated by keeping that scaffolding compiling as Stan, StanHeaders, and rstan move underneath it. Version 2.7.0 continues that pattern, its one user-facing change being an allowance for deprecated syntax in specified versions of specified packages.
This is a stable dependency in maintenance mode, and the release history reads accordingly: compatibility shims for new rstan and Stan RNG versions, C++ standard bumps, and pkgdown housekeeping. The last substantive API growth was 2.5.0's loo_epred() generic and discrete-data loo_pit(). Contributor churn is visible in recent releases, with several first-time contributors handling infrastructure rather than statistics.
Expect the next releases to continue tracking Stan and rstan breakage as it arrives; nothing in the recent entries points to new generics or a change in the package-generation model.
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 rstantools.
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 rstantools alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. rstantools 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rstantools 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.
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 rstantools alternatives in Analytics are ranked by recent ship velocity. Browse the "rstantools alternatives" section above for the current picks, or visit /alternatives/rstantools for the full list with editorial commentary on each.