so it’s tempting to use common Python metaphors for working with them. If we wanted to create a NumPy array with the numbers 0-1000, we could in theory do this: x = np.array([_ for _ in range ...

Here’s how to use Cython to accelerate array iterations in NumPy ... for x in range(x_max): for y in range(y_max): view2d[x,y] = something() # pure-Python mode: import cython @cython.boundscheck ...