Python bisect left vs right

Python bisect left vs right

Here's the information about bisect function from Python:

Python's built-in module bisect provides a way to maintain sorted lists by efficiently searching and inserting elements into these lists. The bisect function in particular is used for finding an insertion point to maintain the sorted order.

There are two types of searches that can be performed using bisect: bisect_left (also known as insort_left) and bisect_right (also known as insort_right).

The left version of the function returns the index where you could insert a given value in order to maintain sorted order, but this assumes that the target is not already in the list. If the item is already present, bisect_left will return an index at which the element should be inserted to maintain the sorting.

Here's how it works:

For example:

    >>> import bisect



numbers = [1, 2, 3]






bisect.bisect_left(numbers, 4)



3

In this case, you could insert 4 at index 3 to maintain sorted order.

The right version of the function also returns where you could insert a given value in order to maintain sorted order, but it does so by considering the end of the list.

Here's how it works:

For example:

    >>> import bisect



numbers = [1, 2, 3]






bisect.bisect_right(numbers, 4)



4

In this case, you could insert 4 at index 4 to maintain sorted order.

The key difference between the two is that bisect_left considers where it would be inserted if there were a missing element in the list, while bisect_right considers where it would be inserted if there were an extra element in the list.

Python binary search standard library

I apologize for the confusion earlier! Here's a detailed explanation of the binary search algorithm implemented in Python using its standard library.

Binary Search:

Binary search is an efficient algorithm for finding an item from a sorted list of items. It works by repeatedly dividing the search interval in half, eliminating half of the possible locations for the target value each iteration.

Here's how it works:

Python Implementation:

def binary_search(lst, target):
low = 0
high = len(lst) - 1
while low <= high:
mid = (low + high) // 2
if lst[mid] == target:
return mid
elif lst[mid] < target:
low = mid + 1
else:
high = mid - 1
return -1
Example usage
sorted_list = [1, 3, 5, 7, 9, 11]
target_value = 5
index = binary_search(sorted_list, target_value)
if index != -1:
print(f"Target value {target_value} found at index {index}.")
else:
print("Target value not found in the list.")

The standard library provides two useful data structures to implement binary search:

Here's how you can use it:

import bisect
sorted_list = [1, 3, 5, 7, 9, 11]
index = bisect.bisect_left(sorted_list, 5)
print(f"The target value {5} is at index {index}.")

In the above code snippet, bisect_left() returns the insertion point for the specified element in the list to maintain the sorted nature of the list.