For performance reasons I would like to wrap Julia functions I am using in Python with the PyCall.pyfunctionret and PyCall.pyfunction wrappers. One of my Julia functions returns an object that is explicitly not converted to a python object using the PyCall.pyfunctionret function. Now I would like to pass this object back into Julia and wrap the function with the PyCall.pyfunction wrapper.
The following example works, but from my understanding it does not actually benefit much from using the pyfunction wrapper, since I have to use the PyAny type and PyCall would still have to infer the type of the object. I would like to specify something more specific than PyAny in my call to pyfunction.
So I have this in julia:
function example(firstnumber, secondnumber)
return Float64[firstnumber, secondnumber]
end
function useobject(obj::Vector{Float64})
println("this is the object:", obj)
end
And in python:
from julia import Main
Main.eval('using PyCall; include("juliafunctions.jl")')
jl_function = Main.eval("pyfunctionret(example, Any, Float64, Float64)")
# These two work as expected - the first returns a converted python object
# (which is a numpy array in this case) and the second returns a simple
# wrapped julia object.
python_object = Main.example(1, 2)
jl_object = jl_function(1, 2)
# Now here is my problem. This works, but I would like to replace
# PyAny here, to avoid the automatic type inference pyjulia has to do in
# this case:
jl_secondfunction = Main.eval("pyfunction(useobject, PyAny)")
jl_secondfunction(jl_object)
I also tried pyfunction(useobject, PyObject) but that just doesn't work at all and I tried pyfunction(useobject, Any), which comes slightly closer to what I want because it passes the wrapped python object into Julia. However, that fails since it doesn't find the correct method for type PyObject.
My questions are the following:
Is my understanding of pyfunction and the use of the PyAny type correct, as in that PyCall still needs to infer the type of the passed in object before attempting any conversion?
Is there a way to pass in the object and have PyCall just unwrap the wrapped julia object? If so what do I need to do to use it? I couldn't figure it out from the documentation
I would be happy to help improving the documentation or adding this feature if it isn't available and if someone could point me in the right direction.
For performance reasons I would like to wrap Julia functions I am using in Python with the
PyCall.pyfunctionret
andPyCall.pyfunction
wrappers. One of my Julia functions returns an object that is explicitly not converted to a python object using thePyCall.pyfunctionret
function. Now I would like to pass this object back into Julia and wrap the function with thePyCall.pyfunction
wrapper.The following example works, but from my understanding it does not actually benefit much from using the
pyfunction
wrapper, since I have to use thePyAny
type and PyCall would still have to infer the type of the object. I would like to specify something more specific thanPyAny
in my call topyfunction
.So I have this in julia:
And in python:
I also tried
pyfunction(useobject, PyObject)
but that just doesn't work at all and I triedpyfunction(useobject, Any)
, which comes slightly closer to what I want because it passes the wrapped python object into Julia. However, that fails since it doesn't find the correct method for type PyObject.My questions are the following:
I would be happy to help improving the documentation or adding this feature if it isn't available and if someone could point me in the right direction.