python Queue在两个地方
- 其一:
Source code: Lib/queue.py
The queue module implements multi-producer, multi-consumer queues. It is especially useful in threaded programming when information must be exchanged safely between multiple threads. The Queue class in this module implements all the required locking semantics. It depends on the availability of thread support in Python; see the threading module.
The module implements three types of queue, which differ only in the order in which the entries are retrieved. In a FIFO queue, the first tasks added are the first retrieved. In a LIFO queue, the most recently added entry is the first retrieved (operating like a stack). With a priority queue, the entries are kept sorted (using the heapq module) and the lowest valued entry is retrieved first.
The queue module defines the following classes and exceptions:
- class queue.Queue(maxsize=0)
-
Constructor for a FIFO queue. maxsize is an integer that sets the upperbound limit on the number of items that can be placed in the queue. Insertion will block once this size has been reached, until queue items are consumed. If maxsize is less than or equal to zero, the queue size is infinite.
Queue objects (Queue, LifoQueue, or PriorityQueue) provide the public methods described below.
- Queue.qsize()
-
Return the approximate size of the queue. Note, qsize() > 0 doesn’t guarantee that a subsequent get() will not block, nor will qsize() < maxsize guarantee that put() will not block.
- Queue.empty()
-
Return True if the queue is empty, False otherwise. If empty() returns True it doesn’t guarantee that a subsequent call to put() will not block. Similarly, if empty() returns False it doesn’t guarantee that a subsequent call to get() will not block.
- Queue.full()
-
Return True if the queue is full, False otherwise. If full() returns True it doesn’t guarantee that a subsequent call to get() will not block. Similarly, if full() returns False it doesn’t guarantee that a subsequent call to put() will not block.
- Queue.put(item, block=True, timeout=None)
-
Put item into the queue. If optional args block is true and timeout is None (the default), block if necessary until a free slot is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Full exception if no free slot was available within that time. Otherwise (block is false), put an item on the queue if a free slot is immediately available, else raise the Full exception (timeout is ignored in that case).
- Queue.put_nowait(item)
-
Equivalent to put(item, False).
- Queue.get(block=True, timeout=None)
-
Remove and return an item from the queue. If optional args block is true and timeout is None (the default), block if necessary until an item is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Empty exception if no item was available within that time. Otherwise (block is false), return an item if one is immediately available, else raise the Empty exception (timeout is ignored in that case).
- Queue.get_nowait()
-
Equivalent to get(False).
Two methods are offered to support tracking whether enqueued tasks have been fully processed by daemon consumer threads.
- Queue.task_done()
-
Indicate that a formerly enqueued task is complete. Used by queue consumer threads. For each get() used to fetch a task, a subsequent call to task_done() tells the queue that the processing on the task is complete.
If a join() is currently blocking, it will resume when all items have been processed (meaning that a task_done() call was received for every item that had been put() into the queue).
Raises a ValueError if called more times than there were items placed in the queue.
- Queue.join()
-
Blocks until all items in the queue have been gotten and processed.
The count of unfinished tasks goes up whenever an item is added to the queue. The count goes down whenever a consumer thread calls task_done() to indicate that the item was retrieved and all work on it is complete. When the count of unfinished tasks drops to zero, join() unblocks.
Example of how to wait for enqueued tasks to be completed:
def worker():
while True:
item = q.get()
do_work(item)
q.task_done() q = Queue()
for i in range(num_worker_threads):
t = Thread(target=worker)
t.daemon = True
t.start() for item in source():
q.put(item) q.join() # block until all tasks are done
- 其二:
- class multiprocessing.Queue([maxsize])
-
Returns a process shared queue implemented using a pipe and a few locks/semaphores. When a process first puts an item on the queue a feeder thread is started which transfers objects from a buffer into the pipe.
The usual queue.Empty and queue.Full exceptions from the standard library’s queue module are raised to signal timeouts.
Queue implements all the methods of queue.Queue except for task_done() and join().
- qsize()
-
Return the approximate size of the queue. Because of multithreading/multiprocessing semantics, this number is not reliable.
Note that this may raise NotImplementedError on Unix platforms like Mac OS X where sem_getvalue() is not implemented.
- empty()
-
Return True if the queue is empty, False otherwise. Because of multithreading/multiprocessing semantics, this is not reliable.
- full()
-
Return True if the queue is full, False otherwise. Because of multithreading/multiprocessing semantics, this is not reliable.
- put(obj[, block[, timeout]])
-
Put obj into the queue. If the optional argument block is True (the default) and timeout is None (the default), block if necessary until a free slot is available. If timeout is a positive number, it blocks at most timeout seconds and raises the queue.Full exception if no free slot was available within that time. Otherwise (block is False), put an item on the queue if a free slot is immediately available, else raise the queue.Full exception (timeout is ignored in that case).
- put_nowait(obj)
-
Equivalent to put(obj, False).
- get([block[, timeout]])
-
Remove and return an item from the queue. If optional args block is True (the default) and timeout is None (the default), block if necessary until an item is available. If timeout is a positive number, it blocks at most timeout seconds and raises the queue.Empty exception if no item was available within that time. Otherwise (block is False), return an item if one is immediately available, else raise the queue.Empty exception (timeout is ignored in that case).
- get_nowait()
-
Equivalent to get(False).
multiprocessing.Queue has a few additional methods not found in queue.Queue. These methods are usually unnecessary for most code:
- close()
-
Indicate that no more data will be put on this queue by the current process. The background thread will quit once it has flushed all buffered data to the pipe. This is called automatically when the queue is garbage collected.
- join_thread()
-
Join the background thread. This can only be used after close() has been called. It blocks until the background thread exits, ensuring that all data in the buffer has been flushed to the pipe.
By default if a process is not the creator of the queue then on exit it will attempt to join the queue’s background thread. The process can call cancel_join_thread() to make join_thread() do nothing.
- cancel_join_thread()
-
Prevent join_thread() from blocking. In particular, this prevents the background thread from being joined automatically when the process exits – see join_thread().
A better name for this method might be allow_exit_without_flush(). It is likely to cause enqueued data to lost, and you almost certainly will not need to use it. It is really only there if you need the current process to exit immediately without waiting to flush enqueued data to the underlying pipe, and you don’t care about lost data.
python Queue在两个地方的更多相关文章
- Python -- queue队列模块
一 简单使用 --内置模块哦 import Queuemyqueue = Queue.Queue(maxsize = 10) Queue.Queue类即是一个队列的同步实现.队列长度可为无限或者有限. ...
- Python Queue实现生产与消费
Python Queue模块详解 from:https://blog.linuxeye.com/334.html Python中,队列是线程间最常用的交换数据的形式.Queue模块是提供队列操作的模块 ...
- python --- queue模块使用
1. 什么是队列? 学过数据结构的人都知道,如果不知道队列,请Google(或百度). 2. 在python中什么是多生产者,多消费模型? 简单来说,就是一边生产(多个生产者),一边消费(多个消费者) ...
- python Queue模块
先看一个很简单的例子 #coding:utf8 import Queue #queue是队列的意思 q=Queue.Queue(maxsize=10) #创建一个queue对象 for i in ra ...
- 有两个地方,用到了javabean对象和属性字符串值之间的转换
1.有两个地方,用到了javabean对象和属性字符串值之间的转换 2.一个是接入层spring mvc,将json字符串参数转换为javaBean.通过@RequestBody javaBean方式 ...
- 基础知识:编程语言介绍、Python介绍、Python解释器安装、运行Python解释器的两种方式、变量、数据类型基本使用
2018年3月19日 今日学习内容: 1.编程语言的介绍 2.Python介绍 3.安装Python解释器(多版本共存) 4.运行Python解释器程序两种方式.(交互式与命令行式)(♥♥♥♥♥) 5 ...
- 周一02.3运行python程序的两种方式
一.运行python程序的两种方式 方法一:交互式: 优点:输入一行代码立刻返回结果 缺点:无法永久保存代码 方法二: ...
- 执行python解释器的两种方式
执行python解释器的两种方式 1.交互式 python是高级语言,是解释型语言,逐行翻译,写一句翻译一句 print ('hello world') 2.命令行式 python和python解释器 ...
- 比较python类的两个instance(对象) 是否相等
http://www.yihaomen.com/article/python/281.htm 比较python类的两个instance(对象) 是否相等 作者:轻舞肥羊 日期:2012-10-25 字 ...
随机推荐
- 浏览器获取正确的scrollTop值
window.pageYOffset 被所有浏览器支持除了 IE 6, IE 7, IE 8, 不关doctype的事, 注IE9 开始支持此属性. window.scrollY 被Firefox, ...
- C# 日历类
using System; namespace DotNet.Utilities { /// <summary> /// 农历属性 /// </summary> public ...
- 简单封装axios api
可以在代码逻辑中写axios请求,处理请求结果,但是随着项目越来越大,代码会很繁琐,不容易维护,所以,可以把一些在所有请求中都要处理的逻辑抽取出来,封装成api方法.比如每次请求中都要判断是否有权限, ...
- 撩课-Java每天5道面试题第16天
111.什么是乐观锁(Optimistic Locking)? 悲观锁,正如其名, 它指的是对数据被外界 包括本系统当前的其他事务, 以及来自外部系统的事务处理 修改持保守态度, 因此,在整个数据处理 ...
- JMM和底层实现原理
- Core.Java.Volume.I.Fundamentals.10th.Edition 14.5.8 Volatile域 中文版 章节勘误
今天重扫了corejava 14 并发的一章,在谈到volatile域代替synchronized 应用于并发更新时,看到如下内容,并发更新可用内部锁的方式但会带来阻塞问题,可用volatile域替代 ...
- js 判断浏览器是否64位
js判断是否64位 浏览器 navigator.userAgent.match(/x64/i);
- csharp: datatable get Column datatype or Column Name
/// <summary> ///列表名 /// </summary> /// <param name="table"></param&g ...
- 第二天-while循环 格式化输出 运算符 编码
一.while循环 while 条件: 语句块(循环体) #判断条件是否成立,若成立执行循环体,然后再次判断条件...直到不满足跳出循环 else: 当条件不成立的时候执行这里,和break没 ...
- luogu P3065 first——trie树相关
题目描述 Bessie has been playing with strings again. She found that by changing the order of the alphabe ...