A memoryview is essentially a generalized NumPy array structure in Python itself (without the math). It allows you to share memory between data-structures (things like PIL images, SQLlite data-bases, NumPy arrays, etc.) without first copying. This is very important for large data sets. With it you can do things like memory-map to a very large … Read more
Just for a further reference, cython online docs says this is because Cython is using a deprecated Numpy API, and for the time being, it’s just a warning that we can ignore.
One reason memoryviews are useful is that they can be sliced without copying the underlying data, unlike bytes/str. For example, take the following toy example. import time for n in (100000, 200000, 300000, 400000): data = b’x’*n start = time.time() b = data while b: b = b[1:] print(f’ bytes {n} {time.time() – start:0.3f}’) for … Read more