https://github.com/jonperk318/sorting-algorithms
Comparing the efficiencies of sorting algorithms in Python, Java, C++, and JavaScript
https://github.com/jonperk318/sorting-algorithms
bubble-sort counting-sort cpp heapsort insertion-sort java javascript matplotlib merge-sort mergesort python3 quick-sort quicksort radix-sort selection-sort sorting-algorithm sorting-algorithm-visualizations sorting-algorithms sorting-algorithms-implemented
Last synced: 2 months ago
JSON representation
Comparing the efficiencies of sorting algorithms in Python, Java, C++, and JavaScript
- Host: GitHub
- URL: https://github.com/jonperk318/sorting-algorithms
- Owner: jonperk318
- License: mit
- Created: 2024-07-07T02:23:31.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-08-25T04:52:38.000Z (10 months ago)
- Last Synced: 2025-02-16T08:43:35.077Z (4 months ago)
- Topics: bubble-sort, counting-sort, cpp, heapsort, insertion-sort, java, javascript, matplotlib, merge-sort, mergesort, python3, quick-sort, quicksort, radix-sort, selection-sort, sorting-algorithm, sorting-algorithm-visualizations, sorting-algorithms, sorting-algorithms-implemented
- Language: C++
- Homepage: https://jonperk318.github.io/sorting-algorithms/
- Size: 18.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Sorting Algorithms in Four Languages
Comparing the efficiencies of sorting algorithms implemented
in four programming languages: Python, Java, C++, and JavaScript.
Results: https://jonperk318.github.io/sorting-algorithms/
## How to Use
Languages and packages used:
* Python 3.12.2
* Java 21.0.1
* C++ Apple Clang 15.0.0 (clang-1500.3.9.4)
* JavaScript Node 20.15.0
* webpack-cli 5.1.4
First, run `./samples/sample_generator.py` to generate 50 sample arrays of logarithmically-spaced sizes from
10 to 10,000, each containing randomly-generated integers ranging from 1 to 1,000. These arrays are outputted into text
files along with `./samples/sample-sizes.txt`, which contains the array sizes.
Second, run the following four main functions each utilizing eight sorting algorithms implemented in their respective
languages:
* `./python-algorithms/main.py`
* `./java-algorithms/src/Main.java`
* `./cpp-algorithms/main.cpp`
* `./javascript-algorithms/main.js`
These each generate text files containing the sorting times for each algorithm.
Third, run `./src/result-loader.js` to convert these results into `./dist/results.js`, using a format readable by
`./dist/main.js`. To generate this file, run `npx webpack` in the root directory.
## Results
The first four sections show all sorting algorithms in one of four languages. The y-axis
of each graph is scaled logarithmically.
In all four languages, for the largest arrays, bubble sort was the slowest and counting sort was the fastest.
For the smallest arrays, insertion sort was the fastest and either merge sort or counting sort were the slowest.
Python was often the slowest language on average for all except counting sort and radix sort, which on average
had slower times in Java.
JavaScript had the fastest times for larger arrays on all algorithms except for merge sort,
and Java came in second on several others.
## Sources
This project was inspired by:
* The sorting algorithms demonstrated in multiple languages on GeeksforGeeks:
https://www.geeksforgeeks.org/sorting-algorithms/
* A sorting benchmark project by Ilya Frolov:
https://github.com/frolovilya/sorting-benchmark/