STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of flashlight and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
flashlight hit 1.0 by giving away its SHAP feature and making most of its API internal.
flashlight computes model-agnostic interpretability output — variable importance, partial dependence and effect profiles, breakdown plots — for fitted models in R. Version 1.0.0 in October 2025 executed a contraction announced two years earlier: add_shap() is deprecated in favour of the separate kernelshap and fastshap packages, type = "shap" is gone from every light_* function that accepted it, and eight previously exported helpers became internal. The release also restored compatibility with ggplot2 v4.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
flashlight computes model-agnostic interpretability output — variable importance, partial dependence and effect profiles, breakdown plots — for fitted models in R. Version 1.0.0 in October 2025 executed a contraction announced two years earlier: add_shap() is deprecated in favour of the separate kernelshap and fastshap packages, type = "shap" is gone from every light_* function that accepted it, and eight previously exported helpers became internal. The release also restored compatibility with ggplot2 v4.
The package is narrowing rather than growing, and doing it on a published schedule — 0.9.0 listed the breaking changes, 1.0.0 applied them essentially unchanged. Handing SHAP computation to dedicated packages leaves flashlight as an effects-and-profiles visualization layer rather than an all-purpose interpretability toolkit. Removing the ability to rename result columns via options() points the same way: fewer configuration surfaces, a smaller contract to maintain.
With the deprecation list from 0.9.0 now fully applied, the next releases most likely remove the functions currently deprecated rather than adding capability, and continue tracking ggplot2. The entries show no new analysis method in progress.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
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 flashlight or sdsfun.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all flashlight alternatives → · See all sdsfun alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. flashlight and sdsfun 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. flashlight and sdsfun 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 flashlight alternatives in Analytics are ranked by recent ship velocity. Browse the "flashlight alternatives" section above for the current picks, or visit /alternatives/flashlight for the full list with editorial commentary on each.
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.