calling c from python with ctypes: passing vectors -

i want call c function python using ctypes. documentation don't understand how pass pointer vectors. function want call is:

double f(int n, double* x)   {     int i;     double p=1;     (i=0; i< n; ++)        p = p * x[i];     return p;   } 

i have modified function void pointer, becomes f(int, void*) internal cast double. following:

def f(x):   n = len(x)   libc = '/path/to/lib.so'   cn = c_int(n)   px = pointer(x)   cx = c_void_p(px)   libc.restype = c_double   l = libc.f(cn, cx)   return l 

i assume x numpy array, not sure how numpy array organized in memory , if best solution.

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edit:

none of proposed methods work numpy array, maybe due how defining array:

x = np.array([], 'float64') f = open(file,'r') line in f:   x = np.append(x,float(line)) 

but of them work if have explicit list [1,2,3,4,5], rather list has been defined somewhere else , referred x

based on @sven marnach's answer:

#!/usr/bin/env python import ctypes import numpy np numpy.ctypeslib import ndpointer  libf = ctypes.cdll.loadlibrary('/path/to/lib.so') libf.f.restype = ctypes.c_double libf.f.argtypes = [ctypes.c_int, ndpointer(ctypes.c_double)]  def f(a):     return libf.f(a.size, np.ascontiguousarray(a, np.float64))  if __name__=="__main__":     # slice create non-contiguous array     = np.arange(1, 7, dtype=np.float64)[::2]     assert not a.flags['c_contiguous']     print(a)     print(np.multiply.reduce(a))     print(f(a)) 

output

[ 1.  3.  5.] 15.0 15.0 

removing np.ascontiguousarray() call produces wrong result (6.0 on machine).