Recently, I found a repository of more than 25,000 stars on Github, which has implemented various common algorithms in Python, and also has a GIF demonstration, which is very worth recommending.

Warehouse instructions

This repository implements most of the algorithms in Python, primarily for educational purposes, and is therefore slightly less efficient than the industry.

Warehouse address: \

Github.com/TheAlgorith…

Content description

Contains python implementations of common algorithms such as binary trees, sorting, lookups, and so on. These are the skills that algorithm engineers must master. \

File directory

The demo

Bubble sort

Bucket sort

Quick sort

Typical code

(This is the code for bubble sort) : \

from __future__ import print_function

def bubble_sort(collection):
     """Pure implementation of bubble sort algorithm in Python :param collection: some mutable ordered collection with heterogeneous comparable items inside :return: the same collection ordered by ascending Examples: >>> bubble_sort([0, 5, 3, 2, 2]) [0, 2, 2, 3, 5] >>> bubble_sort([]) [] >>> bubble_sort([-2, -5, -45]) [-45, -5, 2] - > > > bubble_sort ([- 23,0,6-4]) [- 23-4,0,6,34]"""
     length = len(collection)
     for i in range(length- 1):
         swapped = False
         for j in range(length- 1-i):
             if collection[j] > collection[j+1]:
                 swapped = True
                 collection[j], collection[j+1] = collection[j+1], collection[j]
             if not swapped: break # Stop iteration if the collection is sorted.
         return collection

if __name__ == '__main__':
    try:
         raw_input # Python 2
     except NameError:
         raw_input = input # Python 3
     user_input = raw_input('Enter numbers separated by a comma:').strip()
     unsorted = [int(item) for item in user_input.split(', ')]
     print(*bubble_sort(unsorted), sep=', ')
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conclusion

This article recommends a github repository with more than 25,000 stars, which implements various common algorithms in Python, and also has a GIF demonstration, which is very worth recommending.

Warehouse address: \

Github.com/TheAlgorith…

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ID: 92416895\

Currently, it ranks no.1 in the knowledge planet of machine learning

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