STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
hydroloom vs rnpn
A side-by-side editorial comparison of hydroloom and rnpn — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
hydroloom vs rnpn: at a glance
What is hydroloom?
USGS puts a type system over its river network toolkit so errors surface at dispatch
hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.
What is rnpn?
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
rnpn is the R client for the USA National Phenology Network, retrieving observation records, phenometrics and gridded model layers. Version 1.3.0 in March 2025 replaced nearly all of its infrastructure at once — sp and raster dropped, terra made optional, XML swapped for xml2, plyr for dplyr, httr and curl for httr2 — and changed what functions return, with tibbles in place of data.tables and empty tibbles in place of NULL on error. The two releases since have completed the missing-value handling and restored performance lost in the transition.
hydroloom vs rnpn: editorial side-by-side
hydroloom
0.0ANALYTICS
USGS puts a type system over its river network toolkit so errors surface at dispatch
◆ Current state
hydroloom builds and navigates hydrologic flow networks, carrying functionality migrated out of nhdplusTools. Version 1.2.0 introduces an S3 class hierarchy — hy_topo, hy_leveled, hy_node, hy_flownetwork — assigned automatically by hy() and by producer functions, letting the package validate input at dispatch time and emit guided errors. Outlet detection is now defined explicitly: a row is an outlet when its toid is not in id, with reserved values, NA and implicit absence all accepted.
◆ Where it's heading
The package spent its first releases porting and broadening — non-dendritic network support, divergence routing, subsetting that follows diversions out of a basin — and has now turned to making that surface safe to use. The class hierarchy is the structural expression of that turn: instead of every function re-checking whether a data frame has the columns it needs, the type carries the guarantee. The explicit outlet rule resolves a category of failure where valid networks errored on NA or orphan toid values.
◆ Prediction
The release notes flag that subclass attributes are stripped by standard dplyr operations, which is the kind of rough edge that usually generates follow-up work — expect attribute preservation or restoration helpers next.
rnpn
0.0ANALYTICS
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
◆ Current state
rnpn is the R client for the USA National Phenology Network, retrieving observation records, phenometrics and gridded model layers. Version 1.3.0 in March 2025 replaced nearly all of its infrastructure at once — sp and raster dropped, terra made optional, XML swapped for xml2, plyr for dplyr, httr and curl for httr2 — and changed what functions return, with tibbles in place of data.tables and empty tibbles in place of NULL on error. The two releases since have completed the missing-value handling and restored performance lost in the transition.
◆ Where it's heading
The package is being brought onto the current R stack and made honest about missing data, and those are the same project. Converting the -9999 sentinel to NA started in 1.3.0 for download functions and was extended to all columns in 1.4.1; the string "emptyvalue" got the same treatment. Beyond the migration, the feature additions are modest and specific to the domain, such as custom start and end dates for defining a phenometrics season.
◆ Prediction
With the dependency migration finished and sentinel handling now applied across all columns, the next releases most likely return to domain features and to fixes surfaced by the server side, which has already prompted work through migrations and backend moves. The removed progress indicator is an acknowledged regression that may come back.
Alternatives to hydroloom and rnpn
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 hydroloom or rnpn.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all hydroloom alternatives → · See all rnpn alternatives →
Recent activity from hydroloom and rnpn
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agohydroloomhydroloom v1.2.0 ⚡
- 5mo agohydroloomTest tolerances relaxed for CRAN Fedora checks
- 5mo agohydroloomNetwork subsetting and divergence-routed accumulation
- 10mo agohydroloomSort and indexing fixes
- 11mo agornpnSentinel -9999 now converted to NA across all columns
- 1y agornpnCustom season windows for phenometrics, and a speed regression fixed
- 1y agornpnDependency stack and return types replaced wholesale ⚡
- 1y agornpnBackfilled notes for seven earlier maintenance releases
- 1y agohydroloomUpmain and downmain navigation for non-dendritic networks
- 2y agohydroloomInitial release completing the nhdplusTools migration
Frequently asked questions
What is the difference between hydroloom and rnpn?
Both compete on the same themes — r-package — within Analytics. hydroloom and rnpn 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 hydroloom better than rnpn?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hydroloom and rnpn 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 hydroloom?
Top hydroloom alternatives in Analytics are ranked by recent ship velocity. Browse the "hydroloom alternatives" section above for the current picks, or visit /alternatives/hydroloom for the full list with editorial commentary on each.
What are the best alternatives to rnpn?
Top rnpn alternatives in Analytics are ranked by recent ship velocity. Browse the "rnpn alternatives" section above for the current picks, or visit /alternatives/rnpn for the full list with editorial commentary on each.