memoryview

In my program code I've got numpy value arrays and numpy index arrays. Both kinds are preallocated and predefined during program initialization. Each part of the program has one array values on which calculations are performed, and three index arrays idx_from_exch , idx_values and idx_to_exch . There is on global value array to exchange the values of several parts: exch_arr . The index arrays most of the times have between 2 and 5 indices, seldom (most probably never) more indices are needed. dtype=np.int32 , shape and values are constant during the whole program run. Thus I set ndarray.flags

I have a function (from an external Python library) that returns a memoryview object that I want to process in Cython. Is there a way to convert it to a typed memoryview of bytes (without copy) for efficiency? And how would I do that? This doesn't work: mv = memoryview(b'1234') cdef char[:] *tmv tmv = mv ^ ------------------------------------------------------------ /home/me/.cache/ipython/cython/_cython_magic_f9f608355444e2d6828580906623cea8.pyx:3:6: Cannot convert Python object to '__Pyx_memviewslice *' This answer linked by @CodeSurgeon is a possibility to do it. However, since Cython 0.28

I have a question regarding numpys memory views: Suppose we have two arrays with memory: import numpy as np import gc x = np.arange(4*3).reshape(4,3).astype(float) y = (np.arange(5) - 5).astype(float) y_ref = y We use these ( x , y ) in a framework, such that we cannot just redefine them, as the user may have linked them for himself (as in y_ref ). Now we want to combine their memory in one view. So, that the single view, say p shares the memory with both arrays. I did it in the following way, but do not know if this causes a memory leak: p = np.empty(x.size+y.size, dtype=float) # create new

I have a python memoryview pointing to a bytes object on which I would like to perform some processing in cython. My problem is: because the bytes object is not writable, cython does not allow constructing a typed (cython) memoryview from it I cannot use pointers either because I cannot get a pointer to the memoryview start Example: In python: array = memoryview(b'abcdef')[3:] In cython: cdef char * my_ptr = &array[0] fails to compile with the message: Cannot take address of Python variable cdef char[:] my_view = array fails at runtime with the message: BufferError: memoryview: underlying