HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of finnts and profoc — release velocity, themes, recent moves, and the top alternatives to consider.
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
finnts automates time-series forecasting end to end — feature engineering, model selection, hierarchical reconciliation — on a tidymodels backbone. Recent releases have concentrated on global models (one model fitted across many series) and on hierarchical reconciliation, which has needed repeated correction at weekly granularity. Release notes are auto-generated pull-request lists, so the detail lives in the PRs rather than in the changelog.
A forecast combination package that spun its profiler out into its own project
profoc combines probabilistic forecasts online, using the Bernstein online aggregation family with B-spline smoothing over quantiles and time. The recent releases are infrastructure rather than method: 1.3.4 removed a using namespace arma directive for CRAN compliance and closed a timer edge case, 1.3.3 adjusted the integration with rcpptimer against its now-stable 1.2.0 API. The last release to change what users can do was 1.3.0, which exposed the conline C++ class to R and exported init_experts_list(), make_basis_mats(), make_hat_mats() and post_process_model() so the engine can be driven directly.
finnts automates time-series forecasting end to end — feature engineering, model selection, hierarchical reconciliation — on a tidymodels backbone. Recent releases have concentrated on global models (one model fitted across many series) and on hierarchical reconciliation, which has needed repeated correction at weekly granularity. Release notes are auto-generated pull-request lists, so the detail lives in the PRs rather than in the changelog.
Cadence is roughly annual and the commit history is almost entirely one maintainer, with occasional outside contributions. The direction across the last four releases is consolidation of the forecasting internals — multi-horizon models, feature selection, reconciliation fixes — rather than new surface for users. The changelogs themselves are unedited PR dumps, which makes the arc harder to read than the work probably warrants.
Hierarchical reconciliation has produced a bug fix in three of the last four releases, so the next one likely touches it again; nothing in the entries points to a specific new capability.
profoc combines probabilistic forecasts online, using the Bernstein online aggregation family with B-spline smoothing over quantiles and time. The recent releases are infrastructure rather than method: 1.3.4 removed a using namespace arma directive for CRAN compliance and closed a timer edge case, 1.3.3 adjusted the integration with rcpptimer against its now-stable 1.2.0 API. The last release to change what users can do was 1.3.0, which exposed the conline C++ class to R and exported init_experts_list(), make_basis_mats(), make_hat_mats() and post_process_model() so the engine can be driven directly.
The direction is toward a reusable C++ core with thin language bindings. The timing code that lived inside profoc was extracted into the standalone rcpptimer package in 1.3.2, deliberately so other R packages and Python projects could use it through cpptimer and cppytimer, and the clock header was reworked in 1.3.1 to maximise the code shared between the R and Python versions. Method work sits earlier in the history - periodic splines and penalties in 1.2.0, the penalty() function in 1.1.0 - while the recent cadence, a single release in the last sixteen months, points at a package the maintainer considers finished.
The repeated references to future Python use suggest the next significant work happens outside this package, in the shared C++ components, rather than in profoc's R surface.
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 finnts or profoc.
France's national flood statistics, ported out of Fortran and into R.
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
Fast design-based estimators for experiments, coasting on CRAN patches.
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
IP address vectors for R that hit 1.0 and then went quiet.
A column-key toolkit for stitching decades of ecological field data into one table.
See all finnts alternatives → · See all profoc alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — forecasting, r-package — within Infra & APIs. finnts and profoc 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. finnts and profoc 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 Infra & APIs products to evaluate alongside.
Top finnts alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "finnts alternatives" section above for the current picks, or visit /alternatives/finnts for the full list with editorial commentary on each.
Top profoc alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "profoc alternatives" section above for the current picks, or visit /alternatives/profoc for the full list with editorial commentary on each.