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arcgisutils vs hoopr

A side-by-side editorial comparison of arcgisutils and hoopr — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:api-client

arcgisutils vs hoopr: at a glance

Featurearcgisutilshoopr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesarcgis, geospatial, api-client, authenticationsports-data, basketball, api-client, httr2
Last editorial update46m ago2h ago
WebsiteVisit →Visit →

What is arcgisutils?

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.

Read the full arcgisutils trajectory →

What is hoopr?

hoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems

hoopR is the sportsdataverse R package for basketball data, wrapping ESPN, NBA Stats, NBA G-League, NCAA and KenPom behind a single set of loaders. Version 3.0.0 replaces httr with httr2 across every one of those backends, drops httr from Imports, and routes all calls through shared internal retry and response helpers. The change is breaking, and it exists because the old stack segfaulted against libcurl 8.x and curl 7.0.0.

Read the full hoopr trajectory →

arcgisutils vs hoopr: editorial side-by-side

A
arcgisutils
ANALYTICS
0.0

The R-ArcGIS plumbing layer grew a portal administration API and geoprocessing job support.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

H
hoopr
ANALYTICS
0.0

hoopR rebuilds its HTTP layer on httr2 to stop segfaulting on modern systems

◆ Current state

hoopR is the sportsdataverse R package for basketball data, wrapping ESPN, NBA Stats, NBA G-League, NCAA and KenPom behind a single set of loaders. Version 3.0.0 replaces httr with httr2 across every one of those backends, drops httr from Imports, and routes all calls through shared internal retry and response helpers. The change is breaking, and it exists because the old stack segfaulted against libcurl 8.x and curl 7.0.0.

◆ Where it's heading

The package's history is two distinct eras. Through 2021-2023 it grew by endpoint accretion — ESPN stat functions, G-League coverage, the NBA live and boxscore V3 families, on-court players in play-by-play — expanding what could be pulled. The recent work is consolidation instead: one HTTP pipeline, one messaging library, data served from the shared sportsdataverse-data releases rather than per-package repositories. The centre of gravity has moved from adding endpoints to making the plumbing survive its dependencies.

◆ Prediction

With the HTTP layer unified behind shared helpers, expect the sibling sportsdataverse packages to follow the same httr2 migration, and hoopR's own next releases to resume endpoint work now that requests run through one pipeline.

Alternatives to arcgisutils and hoopr

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 hoopr.

See all arcgisutils alternatives → · See all hoopr alternatives →

Recent activity from arcgisutils and hoopr

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 4mo agohooprhoopR 3.0.0 moves every API backend to httr2
  2. 10mo agoarcgisutilsPortal administration and geoprocessing jobs join the utility layer
  3. 1y agoarcgisutilsIntegers no longer encoded as floats in feature updates
  4. 2y agoarcgisutilsFirst stable release rebuilds token handling around a token store
  5. 2y agohooprData loaders repoint to sportsdataverse-data; NBA live endpoints
  6. 4y agohooprESPN stat functions and G-League coverage added
  7. 4y agohooprCRAN release with documented return shapes
  8. 4y agohooprhoopR 1.4.4
  9. 4y agohooprhoopR 1.4.3

Frequently asked questions

What is the difference between arcgisutils and hoopr?

Both compete on the same themes — api-client — within Analytics. arcgisutils and hoopr 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.

Is arcgisutils better than hoopr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. arcgisutils and hoopr 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.

What are the best alternatives to arcgisutils?

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.

What are the best alternatives to hoopr?

Top hoopr alternatives in Analytics are ranked by recent ship velocity. Browse the "hoopr alternatives" section above for the current picks, or visit /alternatives/hoopr for the full list with editorial commentary on each.