Retool
Retool is retiring standalone Assist while folding the same capability into the app builder.
A side-by-side editorial comparison of FoRecoML and tidyaudit — release velocity, themes, recent moves, and the top alternatives to consider.
The machine-learning arm of a forecast reconciliation toolkit, four months old and already sharing its sibling's plumbing.
FoRecoML brings machine-learning approaches to forecast reconciliation across cross-sectional, temporal, and cross-temporal frameworks through csrml(), terml(), and ctrml(). It reached CRAN in April 2026 and has since spent both releases integrating with FoReco rather than expanding its own method set: results are now FoReco's foreco objects, and print() and summary() report framework, approach, problem dimensions, features, training sample size, combination matrix, and trained models.
Pipeline provenance for tidyverse workflows, recording what changed at each step without keeping the data.
tidyaudit records lightweight metadata snapshots as data flows through a pipeline — row and column counts, NA counts, and structured diffs between any two points — without storing the data itself. Taps are operation-aware, so join, filter, and anti-join steps each report what that operation specifically did, and validation helpers cover join integrity, primary keys, and variable relationships. The trail can now be exported as a self-contained interactive HTML diagram or serialized to JSON or RDS.
FoRecoML brings machine-learning approaches to forecast reconciliation across cross-sectional, temporal, and cross-temporal frameworks through csrml(), terml(), and ctrml(). It reached CRAN in April 2026 and has since spent both releases integrating with FoReco rather than expanding its own method set: results are now FoReco's foreco objects, and print() and summary() report framework, approach, problem dimensions, features, training sample size, combination matrix, and trained models.
This package is being built as a satellite, not a competitor. Adopting FoReco's exported new_foreco_class() constructor within days of that class appearing means FoRecoML results drop straight into the same print, summary, plot, and components methods as analytically reconciled ones — which is what makes machine-learning and classical reconciliation directly comparable in a single workflow. The 1.1.1 argument-validation work landed in the same minute as the equivalent change in FoReco, so the two are being maintained as one release train.
With the integration work done, the next release is more likely to add or expose machine-learning approaches than to keep reshaping output; the structured summary already enumerates features and trained models, which suggests inspection tooling is where attention has been.
tidyaudit records lightweight metadata snapshots as data flows through a pipeline — row and column counts, NA counts, and structured diffs between any two points — without storing the data itself. Taps are operation-aware, so join, filter, and anti-join steps each report what that operation specifically did, and validation helpers cover join integrity, primary keys, and variable relationships. The trail can now be exported as a self-contained interactive HTML diagram or serialized to JSON or RDS.
The arc is from inspection to artifact. The first release made the trail something you print and read; 0.2.0 made it something you can hand to someone else or feed to another program, with the HTML export deliberately requiring no server and no Shiny. Reporting has been refined in the same direction, with a tabular changes block showing from-and-to values with row, column, and NA deltas. The remaining work in the window is defensive — a factor-handling path rebuilt because R-devel tightened what as.data.frame.table() accepts in row names.
With serialization and a standalone export in place, the natural next step is making trails comparable across runs rather than only across steps within one, though nothing in the entries commits to it yet.
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 FoRecoML or tidyaudit.
Retool is retiring standalone Assist while folding the same capability into the app builder.
WPML made machine translation the default, and its point releases keep chasing WordPress and page builders.
A forest plot package that keeps handing users control of one more graphical detail.
Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.
A microbiome network model that got itself un-archived by deleting the dependency that killed it.
Three releases in ten days, every one of them a CRAN reviewer's correction rather than a code change.
See all FoRecoML alternatives → · See all tidyaudit alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. FoRecoML and tidyaudit 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. FoRecoML and tidyaudit 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 FoRecoML alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "FoRecoML alternatives" section above for the current picks, or visit /alternatives/forecoml for the full list with editorial commentary on each.
Top tidyaudit alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tidyaudit alternatives" section above for the current picks, or visit /alternatives/tidyaudit for the full list with editorial commentary on each.