without looping in Python. Again, this is so all the performance-sensitive work can be done in NumPy itself. Here’s an example: x1 = np.array( [np.arange(0, 10), np.arange(10,20)] ) This creates ...

so that Cython knows how to interpret the argument as a NumPy array (fast) rather than a generic Python object (slow). Here’s an example of a Cython function declaration that takes in a two ...

Let's change our script a bit and replace the Python list with a NumPy array: import numpy as np list = np.full ... Consider how we generate data in Python, for example: list = [1] * 1_000_000 Python ...