Algorithms，最全的Python算法仓库

pip3 install algorithms

from algorithms.sort import merge_sortif __name__ == "__main__":my_list = [1, 8, 3, 5, 6]my_list = merge_sort(my_list)print(my_list)

def bucket_sort(arr):''' Bucket SortComplexity: O(n^2)The complexity is dominated by nextSort'''# The number of buckets and make bucketsnum_buckets = len(arr)buckets = [[] for bucket in range(num_buckets)]# Assign values into bucket_sortfor value in arr:index = value * num_buckets // (max(arr) + 1)buckets[index].append(value)# Sortsorted_list = []for i in range(num_buckets):sorted_list.extend(next_sort(buckets[i]))return sorted_listdef next_sort(arr):# We will use insertion sort here.for i in range(1, len(arr)):j = i - 1key = arr[i]while arr[j] > key and j >= 0:arr[j+1] = arr[j]j = j - 1arr[j + 1] = keyreturn arr

import mathdef distance(x,y):"""[summary]HELPER-FUNCTIONcalculates 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 = 0for i in range(len(x)):result += (x[i] -y[i],)for component in result:sum += component**2return math.sqrt(sum)def nearest_neighbor(x, tSet):"""[summary]Implements the nearest neighbor algorithmArguments: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 <h4>3. 字符串解码编码</h4><pre class="brush:javascript;toolbar:false;"># 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)) + ":" + stringreturn resdef decode(s):"""Decodes a single string to a list of strings.:type s: str:rtype: List[str]"""strs = []i = 0while i <h4>4. 直方分布</h4><pre class="brush:javascript;toolbar:false;">def get_histogram(input_list: list) -&gt; 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 histogramhistogram = {}# For each list value, add one to the respective histogram dict positionfor i in input_list:histogram[i] = histogram.get(i, 0) + 1return histogram