
A “Jupyter” of DiffEq: Python+R Bindings for DifferentialEquations.jl (Julia) - ChrisRackauckas
http://juliadiffeq.org/2018/04/30/Jupyter.html
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eigenspace
Theres a good (if slightly out of date) comparison between the features for
ODE solving, putting DifferentialEquations.jl against the suites commonly used
in other langauges: [http://www.stochasticlifestyle.com/comparison-
differential-e...](http://www.stochasticlifestyle.com/comparison-differential-
equation-solver-suites-matlab-r-julia-python-c-fortran/) (linked in the blog
as well)

Worth checking out.

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Edit: Nevermind, its not out of date

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piever
Interesting write up! Hope this can incentivize python/r users to give Julia a
try.

I'd be curious to see if there is any progress on the matlab interoperability
as well (my field is mostly matlab).

~~~
ChrisRackauckas
The problem is that mexjulia is the established package for those bindings,
but it needs an update for newer versions of MATLAB
([https://github.com/twadleigh/mexjulia/issues/58](https://github.com/twadleigh/mexjulia/issues/58))
which won't happen because the author moved on
([https://github.com/twadleigh/mexjulia#mexjulia-embedding-
jul...](https://github.com/twadleigh/mexjulia#mexjulia-embedding-julia-in-the-
matlab-process)). If anyone is willing to put time into building/maintaining
the binding libraries I'd be willing to use them. The issue is that, for any
non-OSS language, the essential tooling (CI, benchmarking, accessibility) are
absent, making it hard to maintain bindings for.

