HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
A side-by-side editorial comparison of daedalus and profoc — release velocity, themes, recent moves, and the top alternatives to consider.
An epidemic-economic model teaching its interventions to react to the outbreak itself.
daedalus couples an infectious-disease model to sector-level economic costs, letting users test non-pharmaceutical interventions against both epidemic and fiscal outcomes. Over autumn 2025 the intervention layer went from a single fixed closure to sequential timed NPIs and then to closures that lift in response to the model's own instantaneous reproduction number. Alongside that, the cost functions were reworked so illness states map more carefully onto lost productivity.
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.
daedalus couples an infectious-disease model to sector-level economic costs, letting users test non-pharmaceutical interventions against both epidemic and fiscal outcomes. Over autumn 2025 the intervention layer went from a single fixed closure to sequential timed NPIs and then to closures that lift in response to the model's own instantaneous reproduction number. Alongside that, the cost functions were reworked so illness states map more carefully onto lost productivity.
The arc is toward a model that behaves like a policy simulator rather than a scenario calculator: interventions now have their own state machine, R_t is computed inside the ODE system, and event handling has been pulled out of the output object. Correction releases sit between the feature ones, including an indexing fix the maintainers flag as required for accurate projections. The versioning is patch-level but the changes are structural.
With R_t and the next-generation matrix now available in-model, the likely next step is richer response rules keyed to those quantities; the entries give no signal on when a stable 1.0 arrives.
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 daedalus 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 daedalus alternatives → · See all profoc alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — rcpp — within Infra & APIs. daedalus 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. daedalus 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 daedalus alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "daedalus alternatives" section above for the current picks, or visit /alternatives/daedalus 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.