simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of healthyR.data and mmconvert — release velocity, themes, recent moves, and the top alternatives to consider.
From a bundled hospital dataset to a live CMS API client.
healthyR.data supplies the data layer for the healthyverse packages. It began by shipping hospital data inside the package and now fetches from CMS and provider endpoints at call time through get_cms_meta_data(), fetch_cms_data(), and their provider counterparts. The most recent release is a single httr2 compatibility fix.
A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since
mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.
healthyR.data supplies the data layer for the healthyverse packages. It began by shipping hospital data inside the package and now fetches from CMS and provider endpoints at call time through get_cms_meta_data(), fetch_cms_data(), and their provider counterparts. The most recent release is a single httr2 compatibility fix.
The 2023 release added roughly twenty current_*_data() accessors, one per CMS measure file - a wide but static surface. The 2024 releases replaced that approach with metadata lookup plus generic fetchers, then taught the fetchers to handle CSV, Excel, and ZIP payloads rather than API responses alone. The package's weight has moved from what it ships to what it can retrieve.
With the fetch layer generalised, the next visible work is more likely record-limit and error handling around httr2 than further per-measure accessors.
mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.
The package has reached the natural end state of a reference-data converter — the reference data stopped moving, so the package stopped moving. Releases now arrive roughly annually and exist to keep CRAN checks green. The 0.14 release shipped the same day as sibling qtl2convert 0.36, confirming these are batch maintenance passes across the maintainer's packages rather than independent development.
Without a new mouse genome build or a revised Cox map, the next release is likely another CRAN-check accommodation rather than new functionality.
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 healthyR.data or mmconvert.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all healthyR.data alternatives → · See all mmconvert alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. healthyR.data and mmconvert 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. healthyR.data and mmconvert 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 healthyR.data alternatives in Analytics are ranked by recent ship velocity. Browse the "healthyR.data alternatives" section above for the current picks, or visit /alternatives/healthyr-data for the full list with editorial commentary on each.
Top mmconvert alternatives in Analytics are ranked by recent ship velocity. Browse the "mmconvert alternatives" section above for the current picks, or visit /alternatives/mmconvert for the full list with editorial commentary on each.