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Distributions.jl vs iris

A side-by-side editorial comparison of Distributions.jl and iris — release velocity, themes, recent moves, and the top alternatives to consider.

Distributions.jl vs iris: at a glance

FeatureDistributions.jliris
SectorAnalyticsAnalytics
Velocity score2.52.5
Sparks · 30d00
Top themesjulia, statistics, distributions, automatic-differentiationearth science, release cadence, python, release candidates
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is Distributions.jl?

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.

Read the full Distributions.jl trajectory →

What is iris?

Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.

Iris tags a release candidate roughly every four to five months — 3.13 through 3.16 over the past year — and the cadence is the only thing the feed actually reports. Every entry is the same seven-line template: a line saying this is a release candidate, conda-forge and PyPI install commands, and a link to a 'What's New' page held elsewhere. No release notes reach the feed at all.

Read the full iris trajectory →

Distributions.jl vs iris: editorial side-by-side

D2.5

Julia's distribution library grinds forward one distribution at a time

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

I
iris
ANALYTICS
2.5

Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.

◆ Current state

Iris tags a release candidate roughly every four to five months — 3.13 through 3.16 over the past year — and the cadence is the only thing the feed actually reports. Every entry is the same seven-line template: a line saying this is a release candidate, conda-forge and PyPI install commands, and a link to a 'What's New' page held elsewhere. No release notes reach the feed at all.

◆ Where it's heading

The version numbers say a mature Met Office library is being maintained on a predictable schedule; nothing in the published entries says what is being maintained. Until the project puts release content in the tag body, its public trail will read as cadence without substance, and readers have to leave the feed to learn anything. The pattern has been identical across four consecutive releases, so it is a deliberate publishing choice rather than an oversight.

◆ Prediction

Expect v3.17.0rc0 around late 2026 on the same schedule, carrying the same boilerplate — the notes will again live on the documentation site rather than in the release entry.

Alternatives to Distributions.jl and iris

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 Distributions.jl or iris.

See all Distributions.jl alternatives → · See all iris alternatives →

Recent activity from Distributions.jl and iris

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 13d agoirisv3.16.0rc0
  2. 16d agoDistributions.jlLogitNormal comment fix and doc typo cleanup
  3. 1mo agoDistributions.jlLooser MvNormal and MvNormalCanon type aliases
  4. 1mo agoDistributions.jlTruncated Chernoff quantile and sparsity tracing fixes
  5. 1mo agoDistributions.jlSparsity tracing works through distribution constructors
  6. 2mo agoDistributions.jlStatsFuns 2 upgrade and CI action bumps
  7. 3mo agoDistributions.jlSufficient statistics and MLE for Chi and Chisq
  8. 4mo agoirisv3.15.0rc0
  9. 9mo agoirisv3.14.0rc0
  10. 1y agoirisv3.13.0rc0

Frequently asked questions

What is the difference between Distributions.jl and iris?

They serve adjacent needs but don't currently overlap on shipped themes. Distributions.jl and iris are shipping at a similar cadence (velocity 2.5 vs 2.5, 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.

Is Distributions.jl better than iris?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Distributions.jl and iris are shipping at a similar cadence (velocity 2.5 vs 2.5, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to Distributions.jl?

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.

What are the best alternatives to iris?

Top iris alternatives in Analytics are ranked by recent ship velocity. Browse the "iris alternatives" section above for the current picks, or visit /alternatives/scitools-iris for the full list with editorial commentary on each.