Python Projects for Beginners a ten-Week Bootcamp Approach to Python Programming

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Python Projects for Beginners A Ten Week Bootcamp Approach to Python

Step	Value of Variable	Description
Code
1	list: [0, 6, 8, 14, 32]	sort the list immediately	list.sort( )
2	mid: 2	Find the middle, 5 / 2, round down	len(list) // 2
3	value: 8	don’t return true, 8 is not 14	list[2]
4	condition: False	8 is less than 14 don’t run block	if list[2] > 14
5	list: [14, 32]	Run block, cut off first half of list	list = list[mid + 1 : ]
2	mid: 1	Middle index is 1 because 2 / 2	len(list) // 2
3	value: 32	don’t return true, 32 is not 14	list[1]
4	list: [14]	Run block, cut off second half of list	list = list[ : mid - 1]
2	mid: 0	Find the middle, 1 / 2, round down	len(list) // 2
3	return true	value at mid index is 14 return true	return True

A linear search would require us to search the list item by item to see if the number we’re looking for was in the list. When thinking about efficiency and how long a search may take to complete the task, it would be based on the length of the list. As the length of the list grows, so does the time it takes to find the number we’re looking for. With a Binary Search, however, the time it takes to find a number within a list only takes a minimal number of steps even when the list is a million numbers. For example, when you search a list of one million numbers, a linear search could take one million tries to find the number, but a Binary Search would be able to find it within 20 guesses. As it searches, it cuts the list in half. Within 10 guesses you’re already working with a list of under 2,000 items. This is the beauty of an efficient algorithm. Let’s walk through each step together to understand how the algorithm is programmed.

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