pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of slendr and usmap — release velocity, themes, recent moves, and the top alternatives to consider.
Population-genetic simulation in R, opened up to selection and finally easier to install.
slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
usmap plots US state and county maps in an Alaska- and Hawaii-inset projection and joins user data to them by FIPS code. Over the last two years it has been rebuilt underneath: the map data moved out to a companion usmapdata package, the geometry became sf, and a data_year parameter lets a plot match the vintage of the data being plotted. Version 1.0.0 marks ten years of the project and adds Puerto Rico across every function.
slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().
Since the 1.0.0 release added non-neutral simulation, the work has shifted from capability to friction. A large share of recent notes concerns Python environment handling, conda activation races on Windows, dependency pruning that made shiny optional, and argument names that misled users, as when gene_flow()'s rate argument turned out to mean total ancestry proportion rather than a rate. That is the profile of a package whose scientific surface is settled and whose remaining problems are the ones users actually hit.
Expect the uv-based environment path to move from fallback to default once it has proven itself, given the notes already describe an environment variable for making it so. The deprecated rate argument in gene_flow() is explicitly slated for removal in a future major release, which is the clearest signal here of what a 2.0 would contain.
usmap plots US state and county maps in an Alaska- and Hawaii-inset projection and joins user data to them by FIPS code. Over the last two years it has been rebuilt underneath: the map data moved out to a companion usmapdata package, the geometry became sf, and a data_year parameter lets a plot match the vintage of the data being plotted. Version 1.0.0 marks ten years of the project and adds Puerto Rico across every function.
The package has separated what it draws from how it draws, and that separation is what makes the recent releases possible: annual map vintages ship in usmapdata without touching usmap, and Puerto Rico could be backfilled into every existing year at once. The remaining work is coverage and defaults rather than architecture, and the Puerto Rico exclusion default is already governed by an environment variable rather than a code change.
Expect the annual map vintage to keep arriving through usmapdata, with usmap itself changing only where a new territory or a projection default needs handling.
Other Infra & APIs 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 slendr or usmap.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Fitness-tracking analysis in slow maintenance, still absorbing upstream breakage.
See all slendr alternatives → · See all usmap alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. slendr and usmap 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. slendr and usmap 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 Infra & APIs products to evaluate alongside.
Top slendr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "slendr alternatives" section above for the current picks, or visit /alternatives/slendr for the full list with editorial commentary on each.
Top usmap alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "usmap alternatives" section above for the current picks, or visit /alternatives/usmap for the full list with editorial commentary on each.