User’s Guide¶
Sorting¶
Insertion Sort¶
A simple sorting algorithm that builds the final sorted list of items - one item at a time. It can be less efficient on larger lists.
- Best Case: Input is already sorted out. This takes only
O(n)running time. For ex, [1, 2, 3, 4, 5] - in this case it takes only linear time to sort out the items. - Average/Worst Cases: In both the cases, it takes
O(pow(n, 2))running time to sort out the items. In both these cases, the items in the list are either in a reverse order (or) zig-zag order.
You can use Insertion Sort from pyalgos for both list of integers and list of strings.
from pyalgos.sorting import insertion
numbers_sorted = insertion([3, 4, 2, 7, 5, 1])
alphabets_sorted = insertion(['a', 'z', 'y', 'b', 'w'])
assert numbers_sorted == [1, 2, 3, 4, 5, 7]
assert alphabets_sorted == ['a', 'b', 'w', 'y', 'z']
Note
You can provide either list/tuple of values.
Selection Sort¶
A sorting algorithm that build the final sorted list of items. It is inefficient on larger lists.
- Best/Average/Worst Cases: In all these cases, the running time is
O(pow(n, 2)).
You can use Selection Sort from pyalgos for both list of integers and list of strings.
from pyalgos.sorting import selection
numbers_sorted = selection([3, 4, 2, 7, 5, 1])
alphabets_sorted = selection(['a', 'z', 'y', 'b', 'w'])
assert numbers_sorted == [1, 2, 3, 4, 5, 7]
assert alphabets_sorted == ['a', 'b', 'w', 'y', 'z']
Note
You can provide either list/tuple of values.
Merge Sort¶
A sorting algorithm that build the final sorted list of items. It is a divide and conquer algorithm.
- Best/Average/Worst Cases: In all these cases, the running time is
O(n * log(n)).
You can use Merge Sort from pyalgos for both list of integers and list of strings.
from pyalgos.sorting import merge
numbers_sorted = merge([3, 4, 2, 7, 5, 1])
alphabets_sorted = merge(['a', 'z', 'y', 'b', 'w'])
assert numbers_sorted == [1, 2, 3, 4, 5, 7]
assert alphabets_sorted == ['a', 'b', 'w', 'y', 'z']
Note
You can provide either list/tuple of values.