Passing wrapped julia objects with pyfunction and pyfunctionret

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.

Start by tracing the PyCall.pyfunction and PyCall.pyfunctionret entry points, focusing on the PyAny, PyObject, and wrapped Julia-object behavior described in the example. Determine whether unwrapping is supported; done means either a documented invocation that accepts the wrapped Vector{Float64} or a scoped implementation with tests covering this call path.

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