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SDTM supplemental-qualifier merging got sturdier, then the package went quiet for two years.
Comparison · Analytics
GSODR vs mlr3extralearners
A side-by-side editorial comparison of GSODR and mlr3extralearners — release velocity, themes, recent moves, and the top alternatives to consider.
GSODR vs mlr3extralearners: at a glance
What is GSODR?
A weather-station data client that broke one return type to hand back distances instead of bare IDs.
GSODR fetches and tidies NOAA Global Surface Summary of the Day weather data for R. The 4.0.0 release made nearest_stations() return a data.table of full station metadata plus distance in kilometres rather than a character vector of station IDs, with a documented one-liner for anyone who only wanted the IDs. Nothing has shipped since March 2024.
What is mlr3extralearners?
The mlr3 learner catalogue is growing fast and pruning hyperparameters just as deliberately.
mlr3extralearners is the overflow catalogue for mlr3 learners that do not ship in the core packages — currently spanning H2O, Botorch, fastai, glmnet, survival and competing-risks models. The last two feature releases added roughly thirty learners between them. 1.6.0 then went the other way, cutting hyperparameters that were never correctly forwarded.
GSODR vs mlr3extralearners: editorial side-by-side
GSODR
0.0ANALYTICS
A weather-station data client that broke one return type to hand back distances instead of bare IDs.
◆ Current state
GSODR fetches and tidies NOAA Global Surface Summary of the Day weather data for R. The 4.0.0 release made nearest_stations() return a data.table of full station metadata plus distance in kilometres rather than a character vector of station IDs, with a documented one-liner for anyone who only wanted the IDs. Nothing has shipped since March 2024.
◆ Where it's heading
The package is mature and its releases read as upkeep: refreshing the internal ISD history database, dropping dependencies in favour of base and curl, and hardening the download path against station-year combinations that do not exist. The 4.0.0 change fits the same pattern of returning more structure by default rather than making callers query twice.
◆ Prediction
The most likely next release is another internal station-history refresh; there is no signal of new data sources or analysis features in these entries.
mlr3extralearners
0.0ANALYTICS
The mlr3 learner catalogue is growing fast and pruning hyperparameters just as deliberately.
◆ Current state
mlr3extralearners is the overflow catalogue for mlr3 learners that do not ship in the core packages — currently spanning H2O, Botorch, fastai, glmnet, survival and competing-risks models. The last two feature releases added roughly thirty learners between them. 1.6.0 then went the other way, cutting hyperparameters that were never correctly forwarded.
◆ Where it's heading
Two forces are visible. The catalogue expands in bursts — 1.4.0 and 1.5.0 each added large batches, including a full H2O family and Bayesian regression models — while the maintenance releases in between are dominated by skipping tests on platforms where Python-backed learners crash. 1.6.0 marks a shift toward correctness of the existing surface: priority_lasso parameter sets reduced to what actually passes through, and Cox-inapplicable glmnet parameters removed.
◆ Prediction
The Python-backed learners are the recurring source of platform instability, so expect continued pinning and test-skipping there alongside the next batch of additions.
Alternatives to GSODR and mlr3extralearners
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 GSODR or mlr3extralearners.
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logrx
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lobstr
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giscoR
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FedData
FedData has spent two major versions migrating US federal geodata off R's retiring spatial stack.
See all GSODR alternatives → · See all mlr3extralearners alternatives →
Recent activity from GSODR and mlr3extralearners
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agomlr3extralearnersHyperparameter sets pruned where arguments were never forwarded
- 3mo agomlr3extralearnersDependency version updates
- 4mo agomlr3extralearnersPlatform-specific test skips
- 4mo agomlr3extralearnersSixteen new learners, including a full H2O family
- 6mo agomlr3extralearnersTwenty new learners and a survival learner rename
- 2y agoGSODRnearest_stations() returns metadata and distances
- 2y agoGSODRStation history refresh and internal tidying
- 2y agoGSODRBad station-year requests warn instead of failing the batch
Frequently asked questions
What is the difference between GSODR and mlr3extralearners?
They serve adjacent needs but don't currently overlap on shipped themes. GSODR and mlr3extralearners 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 GSODR better than mlr3extralearners?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. GSODR and mlr3extralearners 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 GSODR?
Top GSODR alternatives in Analytics are ranked by recent ship velocity. Browse the "GSODR alternatives" section above for the current picks, or visit /alternatives/gsodr for the full list with editorial commentary on each.
What are the best alternatives to mlr3extralearners?
Top mlr3extralearners alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3extralearners alternatives" section above for the current picks, or visit /alternatives/mlr3extralearners for the full list with editorial commentary on each.