tidyr
tidyr replaced separate() with a family that says what it does.
A side-by-side editorial comparison of cmdstanpy and dowhy — release velocity, themes, recent moves, and the top alternatives to consider.
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
CmdStanPy is at v1.3.0, which added a diagnose method on CmdStanModel, sampler timing information, create_inits() across the stanfit classes, and much faster MCMC CSV parsing. Every release in this window opens with the same notice: the next non-bugfix release will be 2.0 and will remove existing deprecations. In line with that, 1.3.0 drops Python 3.8 and renames the metric argument to inv_metric.
DoWhy adds one estimation method a year and keeps its identification edge.
DoWhy is at v0.14, which added a doubly robust estimator and Python 3.13 support. The releases before it followed the same shape: v0.13 brought the Generalized Adjustment Criterion for identification, v0.12 added time-series effect estimation and a rank-based anomaly scorer. Between the feature releases sit patch versions handling pandas and CUDA breakage.
CmdStanPy is at v1.3.0, which added a diagnose method on CmdStanModel, sampler timing information, create_inits() across the stanfit classes, and much faster MCMC CSV parsing. Every release in this window opens with the same notice: the next non-bugfix release will be 2.0 and will remove existing deprecations. In line with that, 1.3.0 drops Python 3.8 and renames the metric argument to inv_metric.
The package tracks upstream Stan and prepares for its own break. New inference methods arrive as Stan ships them — Laplace with Stan 2.32, Pathfinder with 2.33 — while the interface work is mostly deprecation staging and CSV input-output performance. The repeated 2.0 warning across two years of releases suggests the cut has been deferred more than once.
The notice at the top of every release points to 2.0 as the next non-bugfix version, removing the deprecations staged here including the metric argument.
DoWhy is at v0.14, which added a doubly robust estimator and Python 3.13 support. The releases before it followed the same shape: v0.13 brought the Generalized Adjustment Criterion for identification, v0.12 added time-series effect estimation and a rank-based anomaly scorer. Between the feature releases sit patch versions handling pandas and CUDA breakage.
Two threads run through the window. The identification side — DoWhy's differentiator against libraries that only estimate — keeps gaining criteria, from frontdoor with multiple variables through the Generalized Adjustment Criterion. The GCM side grows separately with missing-data handling, classifier selection logic and calibration work. The two halves are converging on a single API rather than staying separate entry points.
Given the pace of one estimator or criterion per release and the experimental flags still on missing-data support in GCM, the next release most likely promotes existing experimental features rather than opening a new estimation family.
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 cmdstanpy or dowhy.
tidyr replaced separate() with a family that says what it does.
modeltime built conformal intervals in, then went quiet on features.
performance keeps adding ways to check a model you have already fitted.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
See all cmdstanpy alternatives → · See all dowhy alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — python — within Analytics. cmdstanpy and dowhy 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. cmdstanpy and dowhy 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 Analytics products to evaluate alongside.
Top cmdstanpy alternatives in Analytics are ranked by recent ship velocity. Browse the "cmdstanpy alternatives" section above for the current picks, or visit /alternatives/cmdstanpy for the full list with editorial commentary on each.
Top dowhy alternatives in Analytics are ranked by recent ship velocity. Browse the "dowhy alternatives" section above for the current picks, or visit /alternatives/dowhy for the full list with editorial commentary on each.