[chestertn]

One of the things I don't like about the Julia ecosystem is the monolithic libraries that have tons of dependencies. DiffEq is one of those. I think its fine to write a script but if you want to develop something more sophisticated, you want to keep your dependencies lean.

[krull10]

You can always (slightly) reduce the DiffEq dependencies by adding OrdinaryDiffEq.jl instead of the meta DifferentialEquations.jl package. But lots of those dependencies arise from supporting modular functionality (changing BLAS, linear solvers, Jacobian calculation methods, in vs. out of place workflows, etc.). That said, the newer extension functionality may let more and more of the dependencies get factored out into optional extensions as time goes on.

[ChrisRackauckas]

And you can always use the "Simple" versions, SimpleDiffEq.jl, SimpleNonlinearSolve.jl. Those libraries were made so that users could use exactly the same syntax but with dumbed down solvers with essentially zero latency. But yes the complete solvers are doing lots of fancy things for fancy cases, but SimpleTsit5 is recommended in the docs for small cases where you don't need all of the extra bells and whistles.

[chestertn]

I think it’s also the design philosophy. JuMP and ForwardDiff are great success stories and are packages very light on dependencies. I like those.

The DiffEq library seems to pull you towards the SciML ecosystem and that might not be agreeable to everyone.

For instance a known Julia project that simulates diff equations seems to have implemented their own solver

https://github.com/CliMA/Oceananigans.jl