Buffer Types Only Allowed As Function Local Variables, But That's What I'm Doing

Cython doesn't like numpy arrays in closures? %%cython import numpy as np cimport numpy as np def f(np.ndarray[double, ndim=1] a): def g (double b): return a+b re

Solution 1:

There's a few work-rounds:

1. Only assign the type to the variable within the inner function:

   def f(a):
       def g(double b):
           cdef np.ndarray[double, ndim=1] a_typed = a
           return a_typed+b
   
       return g(1)
   

   This has a small cost associated with checking the type on each call of g, the significance of which depends on how much other work you're doing in g.

2. Use a mixture of memoryviews and untyped variables.

   def f(a):
      cdef double[:] memview_of_a =a
   
      def g(double b):
          memview_of_a[0] =0# example of indexing operationreturn a+b
   
      returng(1)
   

   The thing to remember here is that memview_of_a and a look at the same data, so you can access it in two different ways. Array indexing is quick with the memoryview. Things like scalar operations on arrays aren't actually affected by the type information so there's really no reason to force it to be a specific type.

In summary, it's a limitation, but there are workrounds (although they aren't very neat).