Algorithms，最全的Python算法仓库

​学习编程、最全学习Python最好的法仓方式就是练习，哪怕是最全新手，只要不断地敲代码输出，法仓肯定会有神效。最全

Python的法仓练手项目很多，特别是最全Github上，建议不管新手、法仓老司机都去看看。源码下载最全

这里推荐给大家一个Gitthub上练习的法仓项目，算法仓库-algorithms。最全

https://github.com/keon/algorithms

这里面集合众多核心算法的法仓Python实现，比如排序、最全图计算、法仓回溯、最全队列、流计算、堆、搜索、压缩等等。站群服务器

该仓库支持第三方库安装，在python中进行调用，非常方便。

首先使用pip进行安装：

pip3 install algorithms

然后导入相关模块进行调用，比如sort模块里的merge_sort归并排序算法。

from algorithms.sort import merge_sort

if __name__ == "__main__":

my_list = [1, 8, 3, 5, 6]

my_list = merge_sort(my_list)

print(my_list)

举几个常见的算法案例。

1. 排序算法-桶排序def bucket_sort(arr):

Bucket Sort

Complexity: O(n^2)

The complexity is dominated by nextSort

# The number of buckets and make buckets

num_buckets = len(arr)

buckets = [[] for bucket in range(num_buckets)]

# Assign values into bucket_sort

for value in arr:

index = value * num_buckets // (max(arr) + 1)

buckets[index].append(value)

# Sort

sorted_list = []

for i in range(num_buckets):

sorted_list.extend(next_sort(buckets[i]))

return sorted_list

def next_sort(arr):

# We will use insertion sort here.

for i in range(1, len(arr)):

j = i - 1

key = arr[i]

while arr[j] > key and j >= 0:

arr[j+1] = arr[j]

j = j - 1

arr[j + 1] = key

return arr2. 机器学习-最近邻插值法import math

def distance(x,y):

"""[summary]

HELPER-FUNCTION

calculates the (eulidean) distance between vector x and y.

Arguments:

x { [tuple]} -- [vector]

y { [tuple]} -- [vector]

"""

assert len(x) == len(y), "The vector must have same length"

result = ()

sum = 0

for i in range(len(x)):

result += (x[i] -y[i],)

for component in result:

sum += component**2

return math.sqrt(sum)

def nearest_neighbor(x, tSet):

"""[summary]

Implements the nearest neighbor algorithm

Arguments:

x { [tupel]} -- [vector]

tSet { [dict]} -- [training set]

Returns:

[type] -- [result of the AND-function]

"""

assert isinstance(x, tuple) and isinstance(tSet, dict)

current_key = ()

min_d = float(inf)

for key in tSet:

d = distance(x, key)

if d < min_d:

min_d = d

current_key = key

return tSet[current_key]3. 字符串解码编码# Implement the encode and decode methods.

def encode(strs):

"""Encodes a list of strings to a single string.

:type strs: List[str]

:rtype: str

"""

res =

for string in strs.split():

res += str(len(string)) + ":" + string

return res

def decode(s):

"""Decodes a single string to a list of strings.

:type s: str

:rtype: List[str]

"""

strs = []

i = 0

while i < len(s):

index = s.find(":", i)

size = int(s[i:index])

strs.append(s[index+1: index+1+size])

i = index+1+size

return strs4. 直方分布def get_histogram(input_list: list) -> dict:

"""

Get histogram representation

:param input_list: list with different and unordered values

:return histogram: dict with histogram of input_list

"""

# Create dict to store histogram

histogram = { }

# For each list value, add one to the respective histogram dict position

for i in input_list:

histogram[i] = histogram.get(i, 0) + 1

return histogram

个人感觉这个仓库里的算法很齐全，适合做练习，小伙伴们可以试试。​

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