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 are 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 args. 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 Thread class 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 in turn calls 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, 5, self.counter) print "Exiting " + self.name def print_time(threadName, counter, delay): while counter: if exitFlag: threadName.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 allows you to synchronize threads. A new lock is created by calling the Lock() method, which returns the new lock.
The acquire(blocking) method of the new lock object is used to force threads to run synchronously. The optional blocking parameter enables you to control whether the thread waits to acquire the lock.
If blocking is set to 0, the thread returns 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 blocks and wait for the lock to be released.
The release() method of the new lock object is 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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