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Sorting algorithms

CI

Getting the hang out of (sorting) algorithms. See also https://tensin.name/sorting-algorithms/.

Prerequisites

Algorithms

Each of the implemented sorting algorithms resides in a separate Python module (in the algorithms.impl package). The implemented algorithms are listed below.

Module name Description
bubble_sort Bubble sort
heapsort Heapsort
insertion_sort Insertion sort
median Median value
merge_sort Merge sort
quicksort Quicksort
selection_sort Selection sort

Some algorithms actually come in different variants. For example, the implementation of quicksort includes a number of versions depending on how the pivot element is chosen, be it the first, the second, the middle, the last or a random element of the sequence.

Testing

You can test each of the algorithms above by passing a sequence of integer numbers to the corresponding script.

> python -m algorithms.impl.heapsort 5 3 4 1 2
[1, 2, 3, 4, 5]
> python -m algorithms.impl.quicksort 5 3 4 1 2
[1, 2, 3, 4, 5]
[1, 2, 3, 4, 5]
[1, 2, 3, 4, 5]
[1, 2, 3, 4, 5]
[1, 2, 3, 4, 5]

You can use "test.py" to quickly generate an input list of some kind and display the result of executing one of the implemented algorithms. Consult the output of test.py --help to learn how to use the script.

> ./test.py --input best --length 1000 median_heaps
499.5
> ./test.py --input worst --length 10 quicksort_random
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Plotting

You can generate similar plots you might've seen at https://tensin.name/sorting-algorithms/ using "plot.py". Consult the output of plot.py --help to learn how to use the script.

> ./plot.py merge_sort --min 0 --max 200 --input best --iterations 1000
> ./plot.py median_sorting --min 0 --max 200 --input average --iterations 100 --output median_sorting.png

If you're having problems using the script (like having excessive noise in the measurement results), try minimizing background activity of your OS and applications. For example, on Windows 8.1 I got very reasonable plots after booting into Safe Mode and running the script with a higher priority while also setting its CPU affinity:

> start /affinity 1 /realtime plot.py ...

License

Distributed under the MIT License. See LICENSE.txt for details.