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osmapiR vs xplainfi

A side-by-side editorial comparison of osmapiR and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.

osmapiR vs xplainfi: at a glance

FeatureosmapiRxplainfi
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesopenstreetmap, api-client, r-language, geospatialmlr3, feature-importance, interpretability, statistical-inference
Last editorial update1h ago6h ago
WebsiteVisit →Visit →

What is osmapiR?

osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.

osmapiR wraps the full OpenStreetMap API from R — reading and writing map data, changesets, notes, GPX traces and user records — with OAuth2 where the endpoint requires it, pagination handled internally, and atomic calls vectorised. Recent releases have filled in the moderation and social surface: note subscription, user blocks, changeset discussion search. The newest release lets `bbox` arguments arrive as a character string, matrix, vector, an sf `bbox`, or a terra `SpatExtent`.

Read the full osmapiR trajectory →

What is xplainfi?

xplainfi treats feature importance as an estimate with error bars, not a number.

xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.

Read the full xplainfi trajectory →

osmapiR vs xplainfi: editorial side-by-side

O
osmapiR
ANALYTICS
0.0

osmapiR is the rare API client that tracks its server's wiki revision numbers in the changelog.

◆ Current state

osmapiR wraps the full OpenStreetMap API from R — reading and writing map data, changesets, notes, GPX traces and user records — with OAuth2 where the endpoint requires it, pagination handled internally, and atomic calls vectorised. Recent releases have filled in the moderation and social surface: note subscription, user blocks, changeset discussion search. The newest release lets `bbox` arguments arrive as a character string, matrix, vector, an sf `bbox`, or a terra `SpatExtent`.

◆ Where it's heading

Four consecutive releases open with the same line — documentation and code updated for server-side changes, cited by OSM wiki revision range. That is a maintainer treating an evolving remote API as a versioned contract and auditing against it each cycle, which is unusual discipline and the main reason to trust this client over a hand-rolled wrapper. The second thread is fitting into R's spatial conventions rather than exposing OSM's, visible in the bbox coercion work and the httr2 upgrades landing with upstream help.

◆ Prediction

The pattern is stable enough to call: another release synchronised to the next OSM wiki revision range, adding whatever endpoints appeared and adjusting whatever changed shape.

X
xplainfi
ANALYTICS
2.5

xplainfi treats feature importance as an estimate with error bars, not a number.

◆ Current state

xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.

◆ Where it's heading

Two lines of work run in parallel. The statistical side keeps adding inference options — variance corrections, conditional predictive impact, and the Lei et al. observation-wise loss-difference test — while the computational side attacks the cost of refit-based methods, most recently with a batch_size argument that parallelises refits and a default of one refit per resampling iteration. Support for pre-trained learners in 1.1.0 removes the refit requirement entirely in some workflows.

◆ Prediction

The stated reasoning that budget is better spent on resampling iterations than repeated refits suggests n_repeats may be removed from WVIM and LOCO outright, as the release notes hint.

Alternatives to osmapiR and xplainfi

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 osmapiR or xplainfi.

See all osmapiR alternatives → · See all xplainfi alternatives →

Recent activity from osmapiR and xplainfi

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 21d agoxplainfiRefits parallelise; repeated refits deprioritised in favour of resampling
  2. 5mo agoxplainfiPre-trained learners supported; distribution-free inference added
  3. 5mo agoosmapiRbbox arguments accept sf and terra objects
  4. 6mo agoxplainfiVersion bumped to mark the package as released
  5. 9mo agoxplainfiConfidence intervals arrive for feature importance scores
  6. 0y agoosmapiRNote search defaults to creation order; JSON for GPX metadata
  7. 1y agoosmapiRNote subscriptions and user block endpoints added
  8. 1y agoosmapiRChangeset queries gain from and to parameters
  9. 1y agoosmapiRJOSS citation added; single-tag conversion fixed
  10. 2y agoosmapiRComplete OSM API coverage arrives in one release

Frequently asked questions

What is the difference between osmapiR and xplainfi?

They serve adjacent needs but don't currently overlap on shipped themes. xplainfi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is osmapiR better than xplainfi?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. xplainfi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to osmapiR?

Top osmapiR alternatives in Analytics are ranked by recent ship velocity. Browse the "osmapiR alternatives" section above for the current picks, or visit /alternatives/osmapir for the full list with editorial commentary on each.

What are the best alternatives to xplainfi?

Top xplainfi alternatives in Analytics are ranked by recent ship velocity. Browse the "xplainfi alternatives" section above for the current picks, or visit /alternatives/xplainfi for the full list with editorial commentary on each.