array

array 定义了一个非常类似list的模块，其array 函数接受两个参数，第一个参数是预先定义好的类型，第二个参数，一般为一个序列。 很少见到

import arraya = array.array('b',b'abcd')print(a)print(a[0])

输出：

array('b', [97, 98, 99, 100])97

heapq

heapq 是python中实现堆排序的模块。

from heapq import *import random# 创建一个堆排序data = []for i in range(10):    heappush(data,random.randint(1,20))print(data)# 使用 heappop 移除最小的元素small_num = heappop(data)print(small_num)print('pop移除最小元素后: ',data)# 使用heapreplace替换最小元素，会先执行pop，然后replacen = heapreplace(data,100)print(n)print('执行replace后:',data)# n个最大 / n个最小lagest = nlargest(3,data)small = nsmallest(3,data)print("3个最大的值：",lagest)print("3个最小的值：",small)

输出

[2, 3, 8, 7, 4, 18, 12, 17, 16, 13]2pop移除最小元素后:  [3, 4, 8, 7, 13, 18, 12, 17, 16]3执行replace后: [4, 7, 8, 16, 13, 18, 12, 17, 100]3个最大的值： [100, 18, 17]3个最小的值： [4, 7, 8]

queue

队列，在线程一节有总结过，有先进先出队列，也有优先级队列，队列结合线程，可以保证线程之间通信的安全。这里主要看一下优先级队列

from queue import PriorityQueueimport threadingimport functoolsQ = PriorityQueue()@functools.total_orderingclass Job:    def __init__(self,priority,desc):        self.priority = priority        self.desc = desc        return     # 定义优先级比较    def __eq__(self,other):        try:            self.priority == other.priority        except AttributeError as e:            return NotImplemented        def __lt__(self,other):        try:            self.priority < other.priority        except AssertionError:            return NotImplementeddef worker():    while not Q.empty():        item = Q.get()        import time         time.sleep(1)        print(item.desc)        Q.all_tasks_doneif __name__ == "__main__":    Q.put(Job(3,"mid job"))    Q.put(Job(10,"important job"))    Q.put(Job(1,"low job"))    ts = [threading.Thread(target=worker),threading.Thread(target=worker)]    for t in ts:        t.start()        t.join()

输出

important jobmid joblow job