from random import randint
from timeit import Timer

def sequential_search(a_list, item):
    pos = 0

    while pos < len(a_list):
        if a_list[pos] == item:
            return True
        pos = pos + 1

    return False



def binary_search(a_list, item):
    first = 0
    last = len(a_list) - 1

    while first <= last:
        midpoint = (first + last) // 2
        if a_list[midpoint] == item:
            return True
        elif item < a_list[midpoint]:
            last = midpoint - 1
        else:
            first = midpoint + 1

    return False


#In order to enable the timer code to produce a random number to search for every time, it helps if
#we create a small helper function that wraps the random # generator as part of what is timed.
def linear_search_wrapper(data):
    item = randint(0,len(data)*2) #You have a 50% chance of looking for a value in the dataset
    sequential_search(data,item)
def binary_search_wrapper(data):
    item = randint(0,len(data)*2) #You have a 50% chance of looking for a value in the dataset
    binary_search(data,item)


#Test time for Linear Search
#This is expected to be n
print("linear_search() should be O(n)")
for size in [1000,2000,1000000]:
    data = list(range(size))
    t1 = Timer("linear_search_wrapper(data)", "from __main__ import linear_search_wrapper,data")
    print(f"linearSearch({size}) : {t1.timeit(number=1000)*1000:15.2f} microseconds")
print()


#Test time for Binary Search
#This is expected to be n
print("binary)search() should be O(log n)")
for size in [1000,2000,1000000]:
    data = list(range(size))
    t1 = Timer("binary_search_wrapper(data)", "from __main__ import binary_search_wrapper,data")
    print(f"binarySearch({size}) : {t1.timeit(number=1000)*1000:15.2f} microseconds")
print()