Python Multithreaded Programming

Python Multithreaded Programming

Running several threads is similar to running several different programs concurrently, but with the following benefits:

Multiple threads within a process share the same data space with the main thread and can therefore share information or communicate with each other more easily than if they were separate processes.

Threads sometimes called light-weight processes and they do not require much memory overhead; they care cheaper than processes.

A thread has a beginning, an execution sequence, and a conclusion. It has an instruction pointer that keeps track of where within its context it is currently running.

It can be pre-empted (interrupted)

It can temporarily be put on hold (also known as sleeping) while other threads are running - this is called yielding.

Starting a New Thread:

To spawn another thread, you need to call following method available in thread module:

thread.start_new_thread ( function,args[, kwargs] )

This method call enables a fast and efficient way to create new threads in both Linux and Windows.

The method call returns immediately and the child thread starts and calls function with the passed list of agrs. When function returns, the thread terminates.

Here, args is a tuple of arguments; use an empty tuple to call function without passing any arguments. kwargs is an optional dictionary of keyword arguments.

Example:

#!/usr/bin/python

 

import thread

import time

 

# Define a function for the thread

def print_time( threadName, delay):

   count = 0

   while count < 5:

      time.sleep(delay)

      count += 1

      print "%s: %s" % ( threadName,time.ctime(time.time()) )

 

# Create two threads as follows

try:

   thread.start_new_thread(print_time, ("Thread-1", 2, ) )

   thread.start_new_thread(print_time, ("Thread-2", 4, ) )

except:

   print "Error: unable to start thread"

 

while 1:

   pass

When the above code is executed, it produces the following result:

Thread-1: Thu Jan 22 15:42:17 2009

Thread-1: Thu Jan 22 15:42:19 2009

Thread-2: Thu Jan 22 15:42:19 2009

Thread-1: Thu Jan 22 15:42:21 2009

Thread-2: Thu Jan 22 15:42:23 2009

Thread-1: Thu Jan 22 15:42:23 2009

Thread-1: Thu Jan 22 15:42:25 2009

Thread-2: Thu Jan 22 15:42:27 2009

Thread-2: Thu Jan 22 15:42:31 2009

Thread-2: Thu Jan 22 15:42:35 2009

Although it is very effective for low-level threading, but the thread module is very limited compared to the newer threading module.

The Threading Module:

The newer threading module included with Python 2.4 provides much more powerful, high-level support for threads than the thread module discussed in the previous section.

The threading module exposes all the methods of the thread module and provides some additional methods:

threading.activeCount(): Returns the number of thread objects that are active.

threading.currentThread(): Returns the number of thread objects in the caller's thread control.

threading.enumerate(): Returns a list of all thread objects that are currently active.

In addition to the methods, the threading module has the Thread class that implements threading. The methods provided by the Threadclass are as follows:

run(): The run() method is the entry point for a thread.

start(): The start() method starts a thread by calling the run method.

join([time]): The join() waits for threads to terminate.

isAlive(): The isAlive() method checks whether a thread is still executing.

getName(): The getName() method returns the name of a thread.

setName(): The setName() method sets the name of a thread.

Creating Thread using Threading Module:

To implement a new thread using the threading module, you have to do the following:

Define a new subclass of the Thread class.

Override the __init__(self [,args]) method to add additional arguments.

Then, override the run(self [,args]) method to implement what the thread should do when started.

Once you have created the new Thread subclass, you can create an instance of it and then start a new thread by invoking the start(), which will in turn call run() method.

Example:

#!/usr/bin/python

 

import threading

import time

 

exitFlag = 0

 

class myThread (threading.Thread):

    def __init__(self, threadID, name, counter):

       threading.Thread.__init__(self)

        self.threadID = threadID

        self.name = name

        self.counter = counter

    def run(self):

        print "Starting " + self.name

        print_time(self.name,self.counter, 5)

        print "Exiting " + self.name

 

def print_time(threadName, delay, counter):

    while counter:

        if exitFlag:

            thread.exit()

        time.sleep(delay)

        print "%s: %s" % (threadName,time.ctime(time.time()))

        counter -= 1

 

# Create new threads

thread1 = myThread(1, "Thread-1", 1)

thread2 = myThread(2, "Thread-2", 2)

 

# Start new Threads

thread1.start()

thread2.start()

 

print "Exiting Main Thread"

When the above code is executed, it produces the following result:

Starting Thread-1

Starting Thread-2

Exiting Main Thread

Thread-1: Thu Mar 21 09:10:03 2013

Thread-1: Thu Mar 21 09:10:04 2013

Thread-2: Thu Mar 21 09:10:04 2013

Thread-1: Thu Mar 21 09:10:05 2013

Thread-1: Thu Mar 21 09:10:06 2013

Thread-2: Thu Mar 21 09:10:06 2013

Thread-1: Thu Mar 21 09:10:07 2013

Exiting Thread-1

Thread-2: Thu Mar 21 09:10:08 2013

Thread-2: Thu Mar 21 09:10:10 2013

Thread-2: Thu Mar 21 09:10:12 2013

Exiting Thread-2

Synchronizing Threads:

The threading module provided with Python includes a simple-to-implement locking mechanism that will allow you to synchronize threads. A new lock is created by calling theLock() method, which returns the new lock.

The acquire(blocking) method of the new lock object would be used to force threads to run synchronously. The optional blocking parameter enables you to control whether the thread will wait to acquire the lock.

If blocking is set to 0, the thread will return immediately with a 0 value if the lock cannot be acquired and with a 1 if the lock was acquired. If blocking is set to 1, the thread will block and wait for the lock to be released.

The release() method of the the new lock object would be used to release the lock when it is no longer required.

Example:

#!/usr/bin/python

 

import threading

import time

 

class myThread (threading.Thread):

    def __init__(self, threadID, name, counter):

       threading.Thread.__init__(self)

        self.threadID = threadID

        self.name = name

        self.counter = counter

    def run(self):

        print "Starting " + self.name

        # Get lock to synchronize threads

        threadLock.acquire()

        print_time(self.name,self.counter, 3)

        # Free lock to release next thread

        threadLock.release()

 

def print_time(threadName, delay, counter):

    while counter:

        time.sleep(delay)

        print "%s: %s" % (threadName,time.ctime(time.time()))

        counter -= 1

 

threadLock = threading.Lock()

threads = []

 

# Create new threads

thread1 = myThread(1, "Thread-1", 1)

thread2 = myThread(2, "Thread-2", 2)

 

# Start new Threads

thread1.start()

thread2.start()

 

# Add threads to thread list

threads.append(thread1)

threads.append(thread2)

 

# Wait for all threads to complete

for t in threads:

    t.join()

print "Exiting Main Thread"

When the above code is executed, it produces the following result:

Starting Thread-1

Starting Thread-2

Thread-1: Thu Mar 21 09:11:28 2013

Thread-1: Thu Mar 21 09:11:29 2013

Thread-1: Thu Mar 21 09:11:30 2013

Thread-2: Thu Mar 21 09:11:32 2013

Thread-2: Thu Mar 21 09:11:34 2013

Thread-2: Thu Mar 21 09:11:36 2013

Exiting Main Thread

Multithreaded Priority Queue:

The Queue module allows you to create a new queue object that can hold a specific number of items. There are following methods to control the Queue:

get(): The get() removes and returns an item from the queue.

put(): The put adds item to a queue.

qsize() : The qsize() returns the number of items that are currently in the queue.

empty(): The empty( ) returns True if queue is empty; otherwise, False.

full(): the full() returns True if queue is full; otherwise, False.

Example:

#!/usr/bin/python

 

import Queue

import threading

import time

 

exitFlag = 0

 

class myThread (threading.Thread):

    def __init__(self, threadID, name, q):

       threading.Thread.__init__(self)

        self.threadID = threadID

        self.name = name

        self.q = q

    def run(self):

        print "Starting " + self.name

        process_data(self.name,self.q)

        print "Exiting " + self.name

 

def process_data(threadName, q):

    while not exitFlag:

        queueLock.acquire()

        if not workQueue.empty():

            data = q.get()

            queueLock.release()

            print "%s processing %s" % (threadName, data)

        else:

            queueLock.release()

        time.sleep(1)

 

threadList = ["Thread-1", "Thread-2", "Thread-3"]

nameList = ["One", "Two", "Three", "Four", "Five"]

queueLock = threading.Lock()

workQueue = Queue.Queue(10)

threads = []

threadID = 1

 

# Create new threads

for tName in threadList:

    thread = myThread(threadID, tName,workQueue)

    thread.start()

    threads.append(thread)

    threadID += 1

 

# Fill the queue

queueLock.acquire()

for word in nameList:

    workQueue.put(word)

queueLock.release()

 

# Wait for queue to empty

while not workQueue.empty():

    pass

 

# Notify threads it's time to exit

exitFlag = 1

 

# Wait for all threads to complete

for t in threads:

    t.join()

print "Exiting Main Thread"

When the above code is executed, it produces the following result:

Starting Thread-1

Starting Thread-2

Starting Thread-3

Thread-1 processing One

Thread-2 processing Two

Thread-3 processing Three

Thread-1 processing Four

Thread-2 processing Five

Exiting Thread-3

Exiting Thread-1

Exiting Thread-2

Exiting Main Thread

 

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