binary_search.py

import random
import time

def naive_search (l, target):
    for i in range (len(l)):
        if l[i] == target:
            return i
    return -1

#binary search uses divide and conquer! We shall leverage on a SORTED list

def binary_search (l, target, low=None, high=None):
    if low is None:
        low = 0
    if high is None:
        high = len(l) -1
    if high < low:
        return -1

    midpoint = (low + high) // 2

    if l[midpoint] == target:
        return midpoint
    elif target < l[midpoint]:
        return binary_search(l, target, low, midpoint-1)
    else:
        return binary_search(l, target, midpoint+1, high)

if __name__=='__main__': #naive_search(l, target)
    #l = [1, 3, 5, 10, 12]
    #target = 10
    #print(naive_search(l, target))
    #print(naive_search(l, target))

    length = 10000

    sorted_list = set ()
    while len(sorted_list) < length:
        sorted_list.add(random.randint(-3*length, 3*length))
    sorted_list = sorted(list(sorted_list))

    start = time.time()
    for target in sorted_list:
        naive_search(sorted_list, target)
    end = time.time()
    print("Naive Search time: ", (end - start)/length, "seconds")

    start = time.time()
    for target in sorted_list:
        binary_search(sorted_list, target)
    end = time.time()
    print("Binary Search time: ", (end - start)/length, "seconds")