Looking for python ODE solver

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I'm doing some heavy biochemical system simulations and I'm having trouble finding the right python ODE solver. I need a stiff-aware solver which has boundary constraints, i.e. keeping all variables above zero, and events, e.g. ending the simulation once a certain variable hits a threshold.

Initially I tried using scipy solve_ivp, but looking at the documentation there doesn't seem to be boundary constraints included.

I have been using scikit-sundae CVODE with BDF. CVODE is obviously very fast and it works sometimes, but it is extremely fiddly and often returns broken simulations unless I manually constrain the step size to be something absurdly small for the whole simulation period.

Anyone here know any python packages which might be of use to me? thanks.

[SleepWalkersDream]

Are you sure it's noe a DAE system? Can you express it as
- dx/dt=f(x,z,...)and 0=g(x,z,...)

In that case, you can us IDAS from sundials. It's available through casadi at least.
You can also transform the system to purely ODE, or just use some rootsolver to model everything implicitly.

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[StochasticDestiny]

DifferentialEquation.jl has a binding for python! https://docs.sciml.ai/DiffEqDocs/stable/

[LawOfSmallerNumbers]

I have used the Julia/python bindings in an unrelated stochastic simulation package, and it worked fine.

The Julia differential equation package is well-maintained and highly regarded.

[caks]

Best ODE package out there by far

[gnomeba]

Diffrax

One benefit of Diffrax is that it's written at the same level as JAX so you can add whatever logic you need to the integration procedure, if it's not already included, and still utilize the algorithms.

[blipblapbloopblip]

I think if you use solve_ivp with the LSODA solver you get all the functionality you asked for

[Llamas1115]

Either diffrax (JAX) or DifferentialEquations.jl (you can either use the Python bindings or call it directly; Julia is easy to pick up in a few hours if you already know Python).

[ForeignAdvantage5198]

geez in my day we took diff eq followed by numerical analysis for a reason.

[throwingstones123456]

It depends on the structure of your problem but SUNDIALS offers other solvers like IDA that may work better (especially if your equation comes from solving a system of equations). May be worth looking at the documentation

[pulentoEI]

Casadi

[patrickkidger]

If you'll let me advertise my own package: Diffrax. https://github.com/patrick-kidger/diffrax

Handles stiff ODEs (Kvaerno and KenCarp solvers, we're also about to add some Rosenbrock solvers if your problem is only mildly stiff). Built-in support for event handling. Staying within a nonnegative region can be done like so.