["python","numpy","multidimensional-array","flatten","numpy-ndarray"]
What is the difference between flatten and ravel functions in numpy?

import numpy as np y = np.array(((1,2,3),(4,5,6),(7,8,9))) OUTPUT: print(y.flatten()) [1 2 3 4 5 6 7 8 9] print(y.ravel()) [1 2 3 4 5 6 7 8 9] Both function return the same list. Then what is the need of two different functions performing same job.
The current API is that: flatten always returns a copy. ravel returns a contiguous view of the original array whenever possible. This isn't visible in the printed output, but if you modify the array returned by ravel, it may modify the entries in the original array. If you modify the entries in an array returned from flatten this will never happen. ravel will often be faster since no memory is copied, but you have to be more careful about modifying the array it returns. reshape((-1,)) gets a view whenever the strides of the array allow it even if that means you don't always get a contiguous array.