inlabru
A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time
A side-by-side editorial comparison of humind and predictsr — release velocity, themes, recent moves, and the top alternatives to consider.
The MSNI humanitarian needs framework as code, rewritten and re-broken every year
humind turns household survey data into Multi-Sector Needs Index severity scores across WASH, Protection, SNFI, Food Security, Education and Health. Its version line tracks the annual MSNI framework revision — 2024.x, 2025.x, 2026.x — with narrow correctness patches between rollouts. v2026.2.0 is the current rollout and the most structural one in the visible history: water-quantity scoring moved out into a new mandatory prerequisite, food-security severity now comes from a different matrix, and the impactR4PHU runtime dependency is gone.
A single visible release: the PREDICTS data client patching its download path.
predictsr provides R access to the PREDICTS biodiversity database hosted on the Natural History Museum data portal. Only one release is visible in the feed, 0.2.1, which repairs an API error originating on the portal side and tightens the download path: temporary files are now cleaned up when a download fails, year comparisons no longer compare integers incorrectly, and SHA validation no longer fails on missing values. With one entry there is no cadence to read and no arc to describe.
humind turns household survey data into Multi-Sector Needs Index severity scores across WASH, Protection, SNFI, Food Security, Education and Health. Its version line tracks the annual MSNI framework revision — 2024.x, 2025.x, 2026.x — with narrow correctness patches between rollouts. v2026.2.0 is the current rollout and the most structural one in the visible history: water-quantity scoring moved out into a new mandatory prerequisite, food-security severity now comes from a different matrix, and the impactR4PHU runtime dependency is gone.
Two things move together. The framework content is revised yearly — indicators added, weights corrected, instruments swapped — and the package keeps absorbing pipeline it used to delegate, most visibly by vendoring add_fcs(), add_hhs(), add_rcsi(), add_lcsi() and add_fcm_phase() locally rather than importing them. Each rollout is explicitly breaking and the release notes have grown per-function 'Action:' instructions, which reads as maintainers who expect every downstream dashboard to need rewiring on the same annual clock.
The 2025 line settled into narrow patches immediately after its rollout — 1.2, 1.3 and 1.4 fixed a separator argument, a schema rename and a shelter misclassification rather than adding indicators. Expect the 2026 line to do the same: correctness fixes against the new WASH, FCLCM and shelter-damage logic before any further framework change.
predictsr provides R access to the PREDICTS biodiversity database hosted on the Natural History Museum data portal. Only one release is visible in the feed, 0.2.1, which repairs an API error originating on the portal side and tightens the download path: temporary files are now cleaned up when a download fails, year comparisons no longer compare integers incorrectly, and SHA validation no longer fails on missing values. With one entry there is no cadence to read and no arc to describe.
What can be said from a single release is that the package's failure modes are concentrated where it meets the data portal rather than in its own analysis code, and that the fixes are the kind found by users hitting real downloads: leftover temporary files, checksum validation tripping over NAs, an upstream API change. The adoption of the air formatter and a GitHub Actions check in the same release suggests maintenance tooling being put in place rather than a feature programme.
Too little is visible here to predict a direction with any confidence. The one signal worth noting is that this release was largely reactive to a portal-side change, so future releases are likely to track the data portal's behaviour rather than follow a roadmap of the package's own.
Other Infra & APIs 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 humind or predictsr.
A Bayesian spatial modelling package rebuilding its foundations one breaking release at a time
UK government chart styling in ggplot2, chasing ggplot2 v4 and stretching its palette to five.
A gamma-convolution density package that reached completion in 2018 and has coasted since.
Animal-movement models in R, where new stochastic processes arrive years apart.
A basic DNA and RNA sequence toolkit that went quiet for three years, then jumped to 2.0.
Package citation for R documents, quietly growing to meet Quarto.
See all humind alternatives → · See all predictsr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. humind is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. humind is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top humind alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "humind alternatives" section above for the current picks, or visit /alternatives/humind for the full list with editorial commentary on each.
Top predictsr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "predictsr alternatives" section above for the current picks, or visit /alternatives/predictsr for the full list with editorial commentary on each.