typed memoryviews in NumPy using the python buffer protocol (PEP 3118)

typed_mv.py

import numpy as NP

d = NP.random.randint(1, 10, 40).reshape(8, 5)

mv = memoryview(d)

 def mem_addr(arr):
   '''
   returns: location of a NumPy array in memory, or
    more precisely, a pointer to the first item in array
   pass in: a NumPy array
   '''
  return arr.__array_interface__['data'][0]
  
  # two arrays w/ the same memory location share a common data buffer;
  # however because the value returned from mem_attr is just a pointer
  # to the first item in the array, mem_attr does not know if one 
  # array is a slice of another, eg, a vs a[:5]
  # to identify that case, use the fn below:
  
  # from the book on IPython by Cyrille Rossant (http://ipython-books.github.io/featured-01/):
  
  def get_data_buffer(arr):
    base = arr
    while isinstance(base.base, NP.ndarray):
      base = base.base
    return base
    
  def arrays_share_same_buffer(arr1, arr2):
    return get_data_bufffer(arr1) is get_data_buffer(arr2)