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Distributions.jl vs shiny

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

Distributions.jl vs shiny: at a glance

FeatureDistributions.jlshiny
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesjulia, statistics, distributions, automatic-differentiationr, web-framework, opentelemetry, observability
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 shiny?

Shiny made reactive apps observable, then gave them a way to tear themselves down

Version 1.12.0 added OpenTelemetry support through the {otel} package, emitting spans for session start and end, reactive updates and individual reactive expressions, with collection depth set by an option or environment variable. The releases since have refined it - scoped collection controls in 1.12.1, cleaner stack traces in 1.13.0 - while 1.14.0 turned to lifecycle, adding session$destroy() on module proxies and a non-blocking startApp() for driving apps programmatically.

Read the full shiny trajectory →

Distributions.jl vs shiny: 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.

S
shiny
ANALYTICS
0.0

Shiny made reactive apps observable, then gave them a way to tear themselves down

◆ Current state

Version 1.12.0 added OpenTelemetry support through the {otel} package, emitting spans for session start and end, reactive updates and individual reactive expressions, with collection depth set by an option or environment variable. The releases since have refined it - scoped collection controls in 1.12.1, cleaner stack traces in 1.13.0 - while 1.14.0 turned to lifecycle, adding session$destroy() on module proxies and a non-blocking startApp() for driving apps programmatically.

◆ Where it's heading

The framework is addressing the two things that make Shiny apps hard to run in production: you could not see inside the reactive graph, and you could not reliably dispose of parts of it. Tracing answers the first; scoped destruction of module session proxies answers the second. Both are aimed at long-lived, dynamically composed apps rather than at the single-file demo.

◆ Prediction

Expect the OpenTelemetry attribute names to settle once the deprecated spellings are dropped, and more of the reactive lifecycle to gain explicit teardown hooks now that session$destroy() has established the pattern. Editor integration is a likely area for follow-up after the Ark breakpoint support.

Alternatives to Distributions.jl and shiny

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 shiny.

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

Recent activity from Distributions.jl and shiny

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

  1. 16d agoDistributions.jlLogitNormal comment fix and doc typo cleanup
  2. 1mo agoDistributions.jlLooser MvNormal and MvNormalCanon type aliases
  3. 1mo agoDistributions.jlTruncated Chernoff quantile and sparsity tracing fixes
  4. 1mo agoshinyModule scopes gain session$destroy() for reactive teardown
  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. 5mo agoshinyInteractive breakpoints under Ark; cleaner render stack traces
  9. 8mo agoshinyScoped OpenTelemetry collection controls
  10. 8mo agoshinyShiny adds OpenTelemetry tracing of the reactive graph
  11. 1y agoshinyRegression fixes for input bindings and label updates
  12. 1y agoshinyAuto-reload covers modules and support files

Frequently asked questions

What is the difference between Distributions.jl and shiny?

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.

Is Distributions.jl better than shiny?

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.

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 shiny?

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