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### Is there a way do declare a python function or fast_callable fo a cython function ?

I want to get efficient code for a repetitive computation on a "grid" of arguments, using a runtime-defined function (passed as an argument). Basically :

def myfunc(f, somerange, someotherrange):
initstorage()
for x in somerange:
for y in someotherrange:
store(x,y,dosomething(f,x,y))
return storage


In order to accelerate things, I'd like to write myfunc in cython.

I can safely assume that my numerical arguments (x and y) will be coerced to double, so I can further accelerate things gy declaring them as typed. The problem is the function argument f. I can test the nature of f (e. g. before initstorage() and set dosomething to a special_case function according to this nature.

There are basically four cases :

• a symbolic expression : it seems that, in most cases, it pays to generate a fast_callable.

• a fast_callable.

• a Python function or a lambda expression.

• a Cython function declared as cpdef, or a C/C++ function suitably imported.

For this last case, I know the solution : it is enough to declare the relevant function signature with ctypedef, and use this type in the declaration of my function :

ctypedef double (*mytype)(double, double)


and use it to declare myfunc : cpdef myfunc(mytype, double, double): #see above...

with the benefit of acceleration due to static typing.

Can something analogous be done in the three other cases (or possibly in the fast_callable and Python function cases, an expression being convertible to the fast_callable case) ?

### Is there a way do declare a python function or fast_callable fo a cython function ?

I want to get efficient code for a repetitive computation on a "grid" of arguments, using a runtime-defined function (passed as an argument). Basically :

def myfunc(f, somerange, someotherrange):
initstorage()
for x in somerange:
for y in someotherrange:
store(x,y,dosomething(f,x,y))
return storage


In order to accelerate things, I'd like to write myfunc in cython.

I can safely assume that my numerical arguments (x and y) will be coerced to double, so I can further accelerate things gy declaring them as typed. The problem is the function argument f. I can test the nature of f (e. g. before initstorage() and set dosomething to a special_case function according to this nature.

There are basically four cases :

• a symbolic expression : it seems that, in most cases, it pays to generate a fast_callable.

• a fast_callable.

• a Python function or a lambda expression.

• a Cython function declared as cpdef, or a C/C++ function suitably imported.

For this last case, I know the solution : it is enough to declare the relevant function signature with ctypedef, and use this type in the declaration of my function :

ctypedef double (*mytype)(double, double)


and use it to declare myfunc : :

cpdef myfunc(mytype, double, double): #see above...above...


with the benefit of acceleration due to static typing.

Can something analogous be done in the three other cases (or possibly in the fast_callable and Python function cases, an expression being convertible to the fast_callable case) ?