webchem
Adding chemical databases with one hand while public ones close programmatic access with the other.
A side-by-side editorial comparison of lobstr and mlr3spatial — release velocity, themes, recent moves, and the top alternatives to consider.
R's object inspector is losing its view of the internals as CRAN closes off the private C API.
lobstr exposes R's internal object representation — sizes, addresses, reference counts, abstract syntax trees. Its two most recent releases are both driven by R's move to a restricted public C API: 1.1.3 stopped reporting a vector's truelength and reworked the reference indicator into refs:n, and 1.2.0 changed what sxp(expand = "environment") shows in order to stay compliant. 1.2.0 also adds src() for exploring srcref objects.
Raster prediction in mlr3 finally returns class probabilities, not just hard labels.
mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.
lobstr exposes R's internal object representation — sizes, addresses, reference counts, abstract syntax trees. Its two most recent releases are both driven by R's move to a restricted public C API: 1.1.3 stopped reporting a vector's truelength and reworked the reference indicator into refs:n, and 1.2.0 changed what sxp(expand = "environment") shows in order to stay compliant. 1.2.0 also adds src() for exploring srcref objects.
The package is being rebuilt inside a shrinking window of what R permits. Each release trades some introspection depth for API conformance while trying to keep the diagnostic value intact — showing promise expressions instead of internal frame structures, replacing named with a documented refs scale. Where the constraint does not bite, development continues normally: src() is genuinely new, and the environment-binding fixes remove long-standing errors on for-loop and immediate bindings.
Expect further conformance work, since the notes describe it as ongoing, with any remaining non-API-dependent readouts either reworked or dropped as R tightens further.
mlr3spatial connects mlr3 learners to raster and vector spatial data, handling chunked prediction over large rasters through DataBackendRaster. Development is slow and fix-heavy: most releases in the last two years were compatibility work against mlr3 and paradox rather than new capability. 0.7.0 is the exception.
The package tracks the mlr3 core rather than leading it — 0.5.0 and 0.6.1 exist to absorb upstream changes in paradox and mlr3. Against that background, 0.7.0 adding probability predictions to predict_spatial() is the first genuine capability increase in a while, arriving alongside two DataBackendRaster fixes for multi-band sources and similarly-named layers. Cadence is roughly one release per year.
Given the pattern, the next release is more likely to be compatibility work against a new mlr3 or terra version than another feature; further raster-backend edge cases around layer naming are the visible loose end.
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 lobstr or mlr3spatial.
Adding chemical databases with one hand while public ones close programmatic access with the other.
The spatiotemporal companion to sf, moving at the pace of the packages around it.
An interface to Europe's long-term ecosystem research network that went quiet after 2.0.
Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.
Stopped trusting the cloud to prepare its taxonomic databases and does the conversion locally.
Went from estimating felling dates to doing the crossdating that produces them.
See all lobstr alternatives → · See all mlr3spatial alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. lobstr and mlr3spatial 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. lobstr and mlr3spatial 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 lobstr alternatives in Analytics are ranked by recent ship velocity. Browse the "lobstr alternatives" section above for the current picks, or visit /alternatives/lobstr for the full list with editorial commentary on each.
Top mlr3spatial alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3spatial alternatives" section above for the current picks, or visit /alternatives/mlr3spatial for the full list with editorial commentary on each.