This issue will be used to track common interface option handling. This is a constant time factor so it's not the biggest deal, but I feel that we can improve some applications by reducing common latency here.

It would be helpful to have some text on how contributions should be made.
This includes how to setup the development environment and how to run the tests.

I'm attempting to run the example posted on the GitHub page for diffeqpy. I've installed diffeqpy successfully on a Mac Pro (2019) running Mac OS X 10.15.4 (Catalina). I'm running the Anaconda distribution for Python ver. 3.7.6.

The code I'm running is the following:

#!/Users/user/opt/anaconda3/bin/python
from diffeqpy import de

def f(u,p,t):
    return -u

u0 = 0.5
tspan = (0.,

What I've noticed is that most (I didn't check all of them) PDE notebooks need to be rerun: all cells just display error messages.

E.g.:

http://benchmarks.juliadiffeq.org/html/MOLPDE/allen_cahn_spectral_wpd.html

http://benchmarks.juliadiffeq.org/html/MOLPDE/kdv_spectral_wpd.html

When following the monte carlo parameter estimation example (https://docs.juliadiffeq.org/stable/analysis/parameter_estimation/index.html) a deprecation message is received
parallel_type has been deprecated. Please refer to the docs for the new dispatch-based system.

When modifying the code to use the new dispatch system as the deprecation message suggests,

ensemble_prob = EnsembleProb