# Bradley N. Miller, David L. Ranum
# Introduction to Data Structures and Algorithms in Python
# Copyright 2005
#
#queue.py
class Queue:
def __init__(self):
self.items = []
def isEmpty(self):
return self.items == []
def enqueue(self, item):
self.items.insert(0,item)
def dequeue(self):
return self.items.pop()
def size(self):
return len(self.items)
2.处理输入数据
将一个列表作为输入,将每一个记录处理为具有相同位数的字符串(用字符串类型时为了方便处理)
def inDataProcess(lis):
max_lengh = max([len(lis[i]) for i in range(len(lis))]) # 查询记录中最长的字符串
return [x.zfill(max_lengh) for x in lis] # 将每一个记录都通过添加前导0的方式转化为一样的长度
3.基数排序主函数
def radixSort(seq:list):
source_data = inDataProcess(seq) # 输入处理
res = [] # 用于保存结果列表
big_queue = Queue() # 用于转化的队列
for ele in source_data:
big_queue.enqueue(ele)
for i in range(len(source_data[0])-1,-1,-1):
buckets = [] # 用于保存每一趟的10各基数桶
for num in range(10): # 建立10个基数桶
bucket = Queue()
buckets.append(bucket)
# 在基数桶中插入数据
while not big_queue.isEmpty():
currentEle = big_queue.dequeue() # 大队列中出队一个元素
index = int(currentEle[i]) # 根据元素对应位上的值添加进对应的基数桶中
buckets[index].enqueue(currentEle)
# 把基数桶串联起来
new_big_queue = Queue()
for bucket in buckets:
while not bucket.isEmpty():
out = bucket.dequeue()
new_big_queue.enqueue(out)
# print(new_big_queue.size())
# 修改big_queue
big_queue = new_big_queue
# 将大队列中的元素保存到结果列表中
while not big_queue.isEmpty():
res.append(big_queue.dequeue().lstrip('0')) # 利用lstrip('0')去掉前导0
return res
4.测试及结果
if __name__ == '__main__':
lis = [20,101,39,431,58,600,8,4,999,634,157,199,208,138,389,691,400,932,856,843,401,923]
lis = [str(i) for i in lis]
print(radixSort(lis))
''' 结果>>>['4', '8', '20', '39', '58', '101', '138', '157', '199', '208', '389', '400', '401', '431', '600', '634', '691',
'843', '856', '923', '932', '999']'''
