tidyr
tidyr replaced separate() with a family that says what it does.
A side-by-side editorial comparison of cmdstanpy and Distributions.jl — 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.
Julia's distribution library grinds forward one distribution at a time
Distributions.jl ships small, frequent releases against a large and settled API surface. Recent work splits between correctness fixes to individual distributions (LogitNormal formulas, Semicircle quantiles, Truncated Chernoff), incremental fitting support such as sufficient statistics and MLE for Chi and Chisq, and infrastructure moves like more consistent error types and global sparsity tracing through constructors.
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.
Distributions.jl ships small, frequent releases against a large and settled API surface. Recent work splits between correctness fixes to individual distributions (LogitNormal formulas, Semicircle quantiles, Truncated Chernoff), incremental fitting support such as sufficient statistics and MLE for Chi and Chisq, and infrastructure moves like more consistent error types and global sparsity tracing through constructors.
The arc is consolidation rather than expansion: dependencies are being pruned and internals made more predictable so the package composes cleanly with the rest of the Julia numerical stack. Support for sparsity tracing and looser MvNormal type aliases both point at making the library easier to drive from automatic-differentiation and optimization code.
Expect the same cadence of per-distribution fixes and fitting-method additions, with continued work on making constructors transparent to tracing and AD tooling. Nothing in these entries signals a major version or API break.
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 Distributions.jl.
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.
DoWhy adds one estimation method a year and keeps its identification edge.
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.
See all cmdstanpy alternatives → · See all Distributions.jl alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Distributions.jl is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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. Distributions.jl is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 Distributions.jl alternatives in Analytics are ranked by recent ship velocity. Browse the "Distributions.jl alternatives" section above for the current picks, or visit /alternatives/distributions-jl for the full list with editorial commentary on each.