osmapiR
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
A side-by-side editorial comparison of dfms and osmextract — release velocity, themes, recent moves, and the top alternatives to consider.
Peer-reviewed, feature-complete, and now able to hand its models to other forecasting engines.
dfms estimates dynamic factor models in R, the workhorse for nowcasting economic activity from ragged, mixed-frequency data. The package worked through the Banbura and Modugno (2014) specification in stages — quarterly variables in 0.3.0, AR(1) idiosyncratic errors combined with mixed frequency in 0.4.0 — then declared 1.0.0 feature-complete on completing rOpenSci peer review, adding news decomposition to attribute forecast revisions to specific data releases. Version 1.0.1 adds convert(), which exports fitted models to dlm or KFAS state-space objects.
osmextract stopped throwing your OpenStreetMap downloads away at the end of every session.
osmextract downloads OpenStreetMap extracts from Geofabrik, BBBike and openstreetmap.fr and translates them into sf objects via GDAL. The 0.6.0 release moved its download cache from `tempdir()` to a persistent `tools::R_user_dir()` location and raised the R floor to 4.1.0 to get it. It also made spatial `place` inputs self-clipping: pass an sf or bbox object and the boundary is now set to match, so only the relevant slice of a country-sized extract is processed.
dfms estimates dynamic factor models in R, the workhorse for nowcasting economic activity from ragged, mixed-frequency data. The package worked through the Banbura and Modugno (2014) specification in stages — quarterly variables in 0.3.0, AR(1) idiosyncratic errors combined with mixed frequency in 0.4.0 — then declared 1.0.0 feature-complete on completing rOpenSci peer review, adding news decomposition to attribute forecast revisions to specific data releases. Version 1.0.1 adds convert(), which exports fitted models to dlm or KFAS state-space objects.
The package has finished the implementation programme it set out in its 2023 vignette and is now working on the edges: interoperability with other state-space packages rather than more estimation methods of its own. The convert() function is the clearest signal — instead of implementing smoothing and prediction intervals natively, it hands the model to packages that already have them. The rOpenSci move also puts it on a review-backed, documented footing that research users can cite.
Expect continued interoperability and diagnostic work rather than new estimators, since the maintainer has explicitly scoped the package as complete. Bug fixes against RcppArmadillo releases will likely remain the other recurring driver.
osmextract downloads OpenStreetMap extracts from Geofabrik, BBBike and openstreetmap.fr and translates them into sf objects via GDAL. The 0.6.0 release moved its download cache from `tempdir()` to a persistent `tools::R_user_dir()` location and raised the R floor to 4.1.0 to get it. It also made spatial `place` inputs self-clipping: pass an sf or bbox object and the boundary is now set to match, so only the relevant slice of a country-sized extract is processed.
Two threads run through every release. One is chasing GDAL — SQL syntax adjusted for 3.10, ogr2ogr options fixed for 3.9, and an `osmconf.ini` that 0.6.0 finally keeps automatically in sync with whatever sf or GDAL provides rather than shipping a snapshot. The other is the road-network extraction added experimentally in 0.3.1, which has been quietly accumulating real routing semantics since: `access = no` links retained when the mode-specific tag permits them, a `oneway` column by default for driving, and `motor_vehicle` always included.
Given that `oe_get_network()` has gained transport-mode detail in three separate releases while remaining flagged as experimental, the next substantive work is most likely there — either more modes or a formal exit from experimental status.
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 dfms or osmextract.
osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.
ymlthis retired itself, naming Quarto as the reason it no longer needs to exist.
forestly built an interactive safety review tool, then taught it to produce submission-ready RTF.
pharmaverseadam is the pharmaverse's test-data mirror, and it now covers neurology.
pkglite's whole job is knowing which files in an R package are text — and it keeps getting better at guessing.
gMCPLite exists to be gMCP without Java, and its releases guard that boundary rather than extend it.
See all dfms alternatives → · See all osmextract alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dfms and osmextract 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. dfms and osmextract 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 dfms alternatives in Analytics are ranked by recent ship velocity. Browse the "dfms alternatives" section above for the current picks, or visit /alternatives/dfms for the full list with editorial commentary on each.
Top osmextract alternatives in Analytics are ranked by recent ship velocity. Browse the "osmextract alternatives" section above for the current picks, or visit /alternatives/osmextract for the full list with editorial commentary on each.