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Bump the all-julia-packages group across 1 directory with 2 updates#45

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@dependabot dependabot Bot commented on behalf of github May 6, 2026

Updates the requirements on Catalyst and DiffEqBase to permit the latest version.
Updates Catalyst to 16.1.1

Release notes

Sourced from Catalyst's releases.

v16.1.1

Catalyst v16.1.1

Diff since v16.1.0

Merged pull requests:

Changelog

Sourced from Catalyst's changelog.

Breaking updates and feature summaries across releases

Unreleased (on master)

Catalyst 16.1

  • Added use_jump_ratelaws keyword argument to ode_model, sde_model, hybrid_model, ODEProblem, SDEProblem, and HybridProblem. When set to true, both drift and diffusion terms use the jump/stochastic rate law (binomial propensities) instead of the ODE rate law (power-based). This gives the mathematically correct CLE derived from the CME when species populations are integers. Defaults to false for backward compatibility.

Catalyst 16.0

Catalyst 16 is a major release that transitions from ModelingToolkit (MT) v9 to ModelingToolkitBase (the base for ModelingToolkit v11); introduces unified hybrid model support for mixed ODE/SDE/Jump systems; supports user-provided coupled ODEs, SDEs, jump processes, and jump-diffusions; and modernizes the conversion and problem-creation API.

Please also see the ModelingToolkit NEWS.md for all the changes that have occurred in ModelingToolkit as part of v10 and v11, and which are now relevant for Catalyst users.

BREAKING: ModelingToolkitBase replaces ModelingToolkit

  • Catalyst now depends on and re-exports ModelingToolkitBase instead of ModelingToolkit. This ensures Catalyst remains fully MIT-licensed after the library split that occurred in ModelingToolkit v11. ModelingToolkitBase provides the core symbolic system infrastructure (types, accessors, problem construction) that Catalyst needs. With this update, Catalyst moves from ModelingToolkit v9 to ModelingToolkitBase 1.12+ (part of ModelingToolkit v11).

    Most commonly used functions (unknowns, parameters, equations, @mtkcompile, etc.) are available through ModelingToolkitBase. However, if you relied on structural_simplify, now part of mtkcompile, for reducing models with algebraic equations, you may need to explicitly load ModelingToolkit to obtain equivalent levels of model reduction and optimization:

    using Catalyst
    using ModelingToolkit  # only if you need MTK-specific features not in MTKBase

    The version of mtkcompile in ModelingToolkitBase is less feature filled than in ModelingToolkit, but please be aware that the latter version now loads AGPL-licensed libraries that may impose additional restrictions on your code.

BREAKING: Conversion functions renamed

... (truncated)

Commits
  • 080e5cb Update project version to 16.1.1
  • 2f67115 Merge pull request #1456 from SciML/as/unpin
  • f534762 build: unpin OrdinaryDiffEqCore and StochasticDiffEq
  • 64f3df6 Merge pull request #1441 from sebapersson/sbmlimporter
  • 1315737 uncomment doc page in pages.jl
  • affe366 update with codex feedback
  • cc472e3 update for new syntax
  • 4d1d324 Merge pull request #1443 from SciML/turing_doc_page
  • da09456 Merge branch 'master' into sbmlimporter
  • 93b9062 up
  • Additional commits viewable in compare view

Updates DiffEqBase to 7.2.0

Changelog

Sourced from DiffEqBase's changelog.

OrdinaryDiffEq.jl v7 / DifferentialEquations.jl v8 Breaking Changes

This release bumps to SciMLBase v3, RecursiveArrayTools v4, and includes breaking changes across DiffEqBase, OrdinaryDiffEqCore, and all solver sublibraries. It also coincides with the DifferentialEquations.jl v8 umbrella release, which is itself a breaking change to the user-facing meta-package.

DifferentialEquations.jl v8: scope reduction

DifferentialEquations.jl v8 no longer re-exports the full SciML solver suite. Previously, using DifferentialEquations pulled in OrdinaryDiffEq, StochasticDiffEq, DelayDiffEq, BoundaryValueDiffEq, Sundials, JumpProcesses, SteadyStateDiffEq, LinearSolve, NonlinearSolve, Optimization, etc. — a large default surface that drove up using time and made it unclear which package any given solver actually came from.

In v8, using DifferentialEquations only loads OrdinaryDiffEq. All other solver families have been removed from the umbrella. If your code relied on DifferentialEquations for SDEs, DDEs, BVPs, jumps, steady states, or any non-ODE solver, you will need to add the topic-specific package to your project explicitly.

Migration

Find the topic you need a solver for and add the corresponding sublib(s) directly. The DiffEqDocs tutorials and solver pages now specify, per algorithm, which package it ships from. Common cases:

Topic Old (DiffEq v7 umbrella) New (DiffEq v8)
ODEs using DifferentialEquations using OrdinaryDiffEq (or using OrdinaryDiffEqTsit5, OrdinaryDiffEqRosenbrock, … for individual solver families)
Stochastic ODEs using DifferentialEquations using StochasticDiffEq
Delay ODEs using DifferentialEquations using DelayDiffEq
Boundary value problems using DifferentialEquations using BoundaryValueDiffEq (or one of BoundaryValueDiffEqMIRK, BoundaryValueDiffEqFIRK, BoundaryValueDiffEqShooting, …)
Jump processes using DifferentialEquations using JumpProcesses
Steady state using DifferentialEquations using SteadyStateDiffEq
DAEs (mass matrix or implicit) using DifferentialEquations using OrdinaryDiffEq (mass matrix), using Sundials (IDA), or topic sublib
Sundials wrappers (CVODE, IDA, ARKODE) using DifferentialEquations using Sundials
Linear / nonlinear / optimization using DifferentialEquations using LinearSolve / using NonlinearSolve / using Optimization

For ODE work specifically, prefer importing only the sublib you need (e.g. using OrdinaryDiffEqTsit5: Tsit5) rather than the umbrella using OrdinaryDiffEq — the v7 ecosystem split lets you trim using time substantially. The DiffEqDocs tutorials and solver index annotate every algorithm with its host sublib.

Why

Removing the meta-package's broad re-exports lets each topic's package version cycle independently, eliminates the long using DifferentialEquations precompile chain for users who only need ODEs, and makes the dependency graph for any given script honest about what's actually being loaded.

This change is independent of the OrdinaryDiffEq v7 changes below — OrdinaryDiffEq v7 ships with DifferentialEquations v8, but you can also use OrdinaryDiffEq v7 directly without the umbrella package at all.

OrdinaryDiffEq.jl v7 Breaking Changes

This release bumps to SciMLBase v3, RecursiveArrayTools v4, and includes breaking changes across DiffEqBase, OrdinaryDiffEqCore, and all solver sublibraries.

Themes of the v7 release

Most of the breaking changes fall into a small set of recurring themes. Keep these in mind while reading the migration table — they explain why an individual change exists and often suggest the right migration direction:

  • Time to first solve (TTFS) reduction. Direct deps on Static.jl, StaticArrayInterface.jl, Polyester.jl, and StaticArrays.jl were dropped; using OrdinaryDiffEq now loads only the default solver set; ODEFunction switched to AutoSpecialize. All of this means less code loaded and more precompilation caching on first solve.
  • Type stability everywhere. All Bool solver/solve keyword arguments (autodiff, verbose, alias, lazy, …) were replaced by typed objects. Passing a Bool no longer changes dispatch in ways the compiler cannot specialize on, and the reverse is no longer allowed to silently fall back through slow generic paths.
  • Generality beyond ForwardDiff. chunk_size, diff_type, standardtag, etc. encoded ForwardDiff-specific or FiniteDiff-specific knobs on every solver. They are replaced by the ADTypes interface (AutoForwardDiff, AutoFiniteDiff, AutoEnzyme, AutoZygote, …) so every solver automatically generalizes to any AD backend.
  • Controller is now an object, not a pile of solve kwargs. gamma, beta1, beta2, qmin, qmax, qsteady_min, qsteady_max, qoldinit were moved onto concrete PIController / PIDController / IController / PredictiveController structs, and EEst moved to the controller cache. This is prep work for pluggable controllers and removes a large amount of dead state from the integrator struct.
  • Cleanup of old re-exports / deprecations. Functions like has_destats (now has_stats), sol.destats (now sol.stats), DEAlgorithm/DEProblem/DESolution abstract types, tuples()/intervals(), QuadratureProblem, fastpow, concrete_solve, etc. were on a deprecation path for one or more minor releases. v7 removes them.

Recommended upgrade path

... (truncated)

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Updates the requirements on [Catalyst](https://github.com/SciML/Catalyst.jl) and [DiffEqBase](https://github.com/SciML/OrdinaryDiffEq.jl) to permit the latest version.

Updates `Catalyst` to 16.1.1
- [Release notes](https://github.com/SciML/Catalyst.jl/releases)
- [Changelog](https://github.com/SciML/Catalyst.jl/blob/master/HISTORY.md)
- [Commits](SciML/Catalyst.jl@v15.0.0...v16.1.1)

Updates `DiffEqBase` to 7.2.0
- [Release notes](https://github.com/SciML/OrdinaryDiffEq.jl/releases)
- [Changelog](https://github.com/SciML/OrdinaryDiffEq.jl/blob/master/NEWS.md)
- [Commits](https://github.com/SciML/OrdinaryDiffEq.jl/commits)

---
updated-dependencies:
- dependency-name: Catalyst
  dependency-version: 16.1.1
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DiffEqBase
  dependency-version: 7.2.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file julia Pull requests that update julia code labels May 6, 2026
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dependabot Bot commented on behalf of github May 7, 2026

Superseded by #46.

@dependabot dependabot Bot closed this May 7, 2026
@dependabot dependabot Bot deleted the dependabot/julia/all-julia-packages-444bf0bb5e branch May 7, 2026 09:58
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