Code demo for https://youtu.be/xgIkRcYY70k

vectorize_demo.py

import time
import numpy as np

def timeit():
    """
    a utility decoration to time running time
    """
    def decorator(func):
        def wrapper(*args, **kwargs):
            start = time.time()
            func(*args, **kwargs)
            end = time.time()
            print(f"running time: {end - start} secs")
            return end - start
        return wrapper
    return decorator

@timeit()
def add_iteratively(n):
    """
    add numbers up to n
    """
    sum = 0
    for i in range(n + 1):
        sum += i
    print(sum)

@timeit()
def add_vectorize(n):
    """
    add numbers up to n
    """
    sum = np.sum(np.arange(n + 1))
    print(sum)


@timeit()
def add_mul_iteratively(v, w, b):
    out = np.zeros(len(v))
    for i in range(len(v)):
        out[i] = v[i] * w[i] + b

@timeit()
def mul_vectorize(v, w, b):
    v * w + b

@timeit()
def dot_iteratively(x, m):
    """
    matrix multiplication of x and m without using numpy
    m = np.array([[1, 2, 3, 4, 5]])
    x = np.random.rand(7, 5)
    """
    out = np.zeros(x.shape[0])

    total = 0
    for i in range(x.shape[0]):
        total = 0
        for j in range(x.shape[1]):
            total += x[i][j] * m[0][j]
        out[i] = total
    # print(out)


@timeit()
def dot_vectorize(x, m):
    # print(x.dot(m.T))
    x.dot(m.T)


@timeit()
def tim_solution(x):
    x.rotate(3)

@timeit()
def optim_solution(x):
    x.rotate(-2)

if __name__ == "__main__":
    from collections import deque
    x = deque(range(5), maxlen=5)

    a = tim_solution(x)
    b = optim_solution(x)
    print(f"A magnitude of {a // b} difference")