Python - Timer Threads

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A Timer starts its work after a delay and can be canceled at any point within that delay time period.

Threading

Python includes sophisticated tools for managing concurrent operations using processes and threads. Even many relatively simple programs can be made to run faster by applying techniques for running parts of the job concurrently using these modules.

subprocess provides an API for creating and communicating with secondary processes. It is especially good for running programs that produce or consume text, since the API supports passing data back and forth through the standard input and output channels of the new process.

The signal module exposes the UNIX signal mechanism for sending events to other processes. The signals are processed asynchronously, usually by interrupting what the program is doing when the signal arrives. Signalling is useful as a coarse messaging system, but other inter-process communication techniques are more reliable and can deliver more complicated messages.

threading includes a high-level, object-oriented API for working with concurrency from Python. Thread objects run concurrently within the same process and share memory. Using threads is an easy way to scale for tasks that are more I/O bound than CPU bound.

The multiprocessing module mirrors threading, except that instead of a Thread class it provides a Process. Each Process is a true system process without shared memory, but multiprocessing provides features for sharing data and passing messages between them. In many cases, converting from threads to processes is as simple as changing a few import statements.

import threading
import time
import logging

logging.basicConfig(level=logging.DEBUG,
    format=‘(%(threadName)-10s) %(message)s‘,
)

def worker():
    while 1:
        time.sleep(3)
        logging.debug(‘worker running‘)

threads = []
for i in range(2):
    
    # t = threading.Thread(target=worker)
    t = threading.Timer(1, worker)
    threads.append(t)
    t.start()
    logging.debug(‘loop running‘)

将threading.Thread对象改为Timer,构造对象的参数也改为相应的(延迟时间, 函数名).

比较重要的是绿色背景的代码,这个是用于调试。这也提醒了我,线程是进程的一个“逻辑”分支。

调试信息如下:

(MainThread) loop running
(MainThread) loop running
(Thread-2  ) worker running
(Thread-1  ) worker running
(Thread-1  ) worker running
(Thread-2  ) worker running
(Thread-2  ) worker running
(Thread-1  ) worker running
(Thread-1  ) worker running
(Thread-2  ) worker running

以下是我自己用画图的理解:

Python - Timer Threads

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原文地址：http://www.cnblogs.com/dotdog/p/4599492.html