TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
A side-by-side editorial comparison of arcgisutils and forecasting — release velocity, themes, recent moves, and the top alternatives to consider.
The R-ArcGIS plumbing layer grew a portal administration API and geoprocessing job support.
arcgisutils is the foundation of the R interface to ArcGIS — token handling, standardized httr2 request construction, and conversion between Esri JSON and R types for the packages built on top of it. Version 0.4.0 in October 2025 broadened it well past that role, adding functions to enumerate a portal's federated servers, users and resources, search content with automatic pagination, and submit geoprocessing jobs through new S7 classes. Token management has been on its current footing since 0.2.0, which moved tokens into an internal environment supporting multiple named keys.
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
arcgisutils is the foundation of the R interface to ArcGIS — token handling, standardized httr2 request construction, and conversion between Esri JSON and R types for the packages built on top of it. Version 0.4.0 in October 2025 broadened it well past that role, adding functions to enumerate a portal's federated servers, users and resources, search content with automatic pagination, and submit geoprocessing jobs through new S7 classes. Token management has been on its current footing since 0.2.0, which moved tokens into an internal environment supporting multiple named keys.
The package is expanding from request plumbing into direct coverage of the ArcGIS Enterprise administrative and geoprocessing surface, which is a different kind of work from what it existed to support. Much of the new surface is marked experimental, so the shape is still being settled. Alongside the expansion runs steady API tidying — three deprecations and two functions removed outright in the same release, one of which dropped the dbplyr dependency.
The experimental sharing-API and URL-parsing functions are the most likely to change or firm up next, and the geoprocessing classes suggest job execution will be built out further. Given this package sits beneath arcgislayers, the deprecations introduced here will need a corresponding pass downstream.
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
The release pattern is maintenance on an eight-year cadence dictated entirely by the surrounding ecosystem: 1.1.1 rebuilt under R 4.0.4, 1.1.2 under R 4.3.2, 1.1.3 under R 4.6.1, each reporting whether the numbers moved. They mostly have not — the recurring note is minor numerical differences confined to the prophet forecasts in vignette('CHILI_prophet'). The only substantive change in the visible history is 1.1.0's methodological tidy-up of the scoring comparisons.
Nothing in these entries points to new functionality; the next release is most likely another vignette rebuild whenever a dependency change or a CRAN check failure forces one.
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 arcgisutils or forecasting.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
College football's open data client hit v2 — and now reports how many API calls you have left.
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
See all arcgisutils alternatives → · See all forecasting alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. arcgisutils and forecasting 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. arcgisutils and forecasting 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 arcgisutils alternatives in Analytics are ranked by recent ship velocity. Browse the "arcgisutils alternatives" section above for the current picks, or visit /alternatives/arcgisutils for the full list with editorial commentary on each.
Top forecasting alternatives in Analytics are ranked by recent ship velocity. Browse the "forecasting alternatives" section above for the current picks, or visit /alternatives/forecasting for the full list with editorial commentary on each.