Python wrapper about autodiff HOT 3 OPEN

I also use a mixed C++ and Python approach:
https://reaktoro.org/tutorials/equilibrium/co2-solubility-nacl-brine.html

And I'll also eventually need to have python bindings (I also use pybind11) for at least dual!

I'm currently considering not to generate template expression trees at compile time when performing mathematical/arithmetic operations on dual numbers. This was originally conceived to avoid temporaries as much as possible, and also to allow certain optimizations at compile time. However, since dual is entirely allocated on the stack, it may be that we don't need to be too much concerned about temporaries (since stack allocation and deallocation are fast operations). We can also use move semantics to re-use temporaries as much as possible.

If this gets in place, then we'll be able to perform auto differentiation in Python as well (but of course, this should be done very sparingly, since Python will add some overhead into the mathematical/arithmetic operations that do not exist in the C++ side).

from autodiff.

Definitely would be awesome to get this capability in Python. At the moment my solution is multicomplex algebra that I have been working on with some colleagues and preparing to release pretty soon. Might still be faster than AD, but likely AD is faster.

So far the AD solutions in Python are VERY slow in my experience, so even a reasonable amount of overhead would be pretty acceptable in my opinion.

from autodiff.

We'll definitely have this; also high priority for my research needs!

from autodiff.