Python beginner, understanding some code

Here is a Python representation of a Neural Network Neuron that I'm trying to understand

class Network(object):

    def __init__(self, sizes):
        self.num_layers = len(sizes)
        self.sizes = sizes
        self.biases = [np.random.randn(y, 1) for y in sizes[1:]]
        self.weights = [np.random.randn(y, x) 
                        for x, y in zip(sizes[:-1], sizes[1:])]

Here is my current understanding :

• self.num_layers = len(sizes): Return the number of items in sizes
• self.sizes = sizes: assign self instance sizes to function parameter sizes
• self.biases = sizes: generate an array of elements from the standard normal distribution (indicated by np.random.randn(y, 1))

What is the following line computing?

self.weights = [np.random.randn(y, x)
    for x, y in zip(sizes[:-1], sizes[1:])]

I'm new to Python. Can this code be used within a Python shell so I can gain a better understanding by invoking each line separately ?