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rATTAINS vs sdsfun
A side-by-side editorial comparison of rATTAINS and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
rATTAINS vs sdsfun: at a glance
What is rATTAINS?
The R client for EPA water quality data spent two releases undoing its own promises about data shape.
rATTAINS wraps the EPA's ATTAINS API, which holds state water quality assessments and impaired-waters listings. The package reached 1.0.0 by promising stable, consistently rectangled return structures, then walked that promise back in 1.1.0 when it dropped the dependency doing the rectangling. As of 1.2.0 it also requires an API key, because ATTAINS itself began requiring one in May 2026.
What is sdsfun?
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.
rATTAINS vs sdsfun: editorial side-by-side
rATTAINS
0.0ANALYTICS
The R client for EPA water quality data spent two releases undoing its own promises about data shape.
◆ Current state
rATTAINS wraps the EPA's ATTAINS API, which holds state water quality assessments and impaired-waters listings. The package reached 1.0.0 by promising stable, consistently rectangled return structures, then walked that promise back in 1.1.0 when it dropped the dependency doing the rectangling. As of 1.2.0 it also requires an API key, because ATTAINS itself began requiring one in May 2026.
◆ Where it's heading
The direction is toward a thinner, lower-maintenance wrapper. Caching went in 0.1.4 when hoardr was archived, tidyjson and janitor went earlier, tibblify went in 1.1.0, and each removal handed a little more data-shaping responsibility back to the user — the current advice is to pass .unnest = FALSE and rectangle the results with whatever tidying package you prefer. Release cadence is slow and mostly reactive: upstream API terms, archived dependencies, and compatibility with test tooling account for most of the log. The package's centre of gravity is staying installable and honest about what ATTAINS returns rather than smoothing it over.
◆ Prediction
Given the pattern, the next release is likelier to be a compatibility or upstream-driven fix than new endpoint coverage; how the API key requirement affects users in scripted and CI contexts is the obvious open question the entries do not yet answer.
sdsfun
0.0ANALYTICS
A spatial-statistics utility package exists to be depended on, and is built accordingly.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to rATTAINS and sdsfun
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 rATTAINS or sdsfun.
cfbfastr
College football's open data client hit v2 — and now reports how many API calls you have left.
rnpn
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
rempsyc
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
eulerr
The area-proportional Euler diagram package is finished software, and maintained like it.
See all rATTAINS alternatives → · See all sdsfun alternatives →
Recent activity from rATTAINS and sdsfun
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agorATTAINSATTAINS now requires an API key, and the package follows
- 8mo agorATTAINSThe tibblify dependency goes, and with it the stable data shapes ⚡
- 10mo agosdsfunPackage load stops touching the RNG state
- 1y agorATTAINSTest suite updated for vcr v2
- 1y agosdsfunUnified partial correlation testing and head/tails discretization
- 1y agosdsfunMissing-value handling added to linear trend removal
- 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
- 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
- 1y agosdsfunFast geodetector q-value estimator added
- 3y agorATTAINS1.0.0 commits to stable return structures via tibblify
- 3y agorATTAINSCaching removed after hoardr was archived
- 4y agorATTAINSRequests retry on timeout, with offline detection
Frequently asked questions
What is the difference between rATTAINS and sdsfun?
Both compete on the same themes — r-package — within Analytics. rATTAINS 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.
Is rATTAINS better than sdsfun?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rATTAINS 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.
What are the best alternatives to rATTAINS?
Top rATTAINS alternatives in Analytics are ranked by recent ship velocity. Browse the "rATTAINS alternatives" section above for the current picks, or visit /alternatives/rattains for the full list with editorial commentary on each.
What are the best alternatives to sdsfun?
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.