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A deadlock may be described as a concurrency failure mode. It is a situation in a program where one or more threads wait for a condition that never occurs. As a result, the threads are unable to progress and the program is stuck or frozen and must be terminated manually.

Deadlock situation may arise in many ways in your concurrent program. Deadlocks are never not developed intentionally, instead, they are in fact a side effect or bug in the code.

Common causes of thread deadlocks are listed below −

  • A thread that attempts to acquire the same mutex lock twice.

  • Threads that wait on each other (e.g. A waits on B, B waits on A).

  • When a thread that fails to release a resource such as lock, semaphore, condition, event, etc.

  • Threads that acquire mutex locks in different orders (e.g. fail to perform lock ordering).

If more than one threads in a multi-threaded application try to gain access to same resource, such as performing read/write operation on same file, it may cause data inconsistency. Hence it is important that the concurrent handling is synchronized so that it is locked for other threads when one thread is using the resource.

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 Lock Object

An object of Lock class has two possible states − locked or unlocked, initially in unlocked state when first created. A lock doesn't belong to any particular thread.

The Lock class defines acquire() and release() methods.

The acquire() Method

When the state is unlocked, this method changes the state to locked and returns immediately. The method takes an optional blocking argument.

Syntax

Lock.acquire(blocking, timeout)

Parameters

  • blocking − If set to False, it means do not block. If a call with blocking set to True would block, return False immediately; otherwise, set the lock to locked and return True.

The return value of this method is True if the lock is acquired successfully; False if not.

The release() Method

When the state is locked, this method in another thread changes it to unlocked. This can be called from any thread, not only the thread which has acquired the lock

Syntax

Lock.release()

The release() method should only be called in the locked state. If an attempt is made to release an unlocked lock, a RuntimeError will be raised.

When the lock is locked, reset it to unlocked, and return. If any other threads are blocked waiting for the lock to become unlocked, allow exactly one of them to proceed. There is no return value of this method.

Example

In the following program, two threads try to call the synchronized() method. One of them acquires the lock and gains the access while the other waits. When the run() method is completed for the first thread, the lock is released and the synchronized method is available for second thread.

When both the threads join, the program comes to an end.

 
from threading import Thread, Lock import time lock=Lock() threads=[] class myThread(Thread): def __init__(self,name): Thread.__init__(self) self.name=name def run(self): lock.acquire() synchronized(self.name) lock.release() def synchronized(threadName): print ("{} has acquired lock and is running synchronized method".format(threadName)) counter=5 while counter: print ('**', end='') time.sleep(2) counter=counter-1 print('\nlock released for', threadName) t1=myThread('Thread1') t2=myThread('Thread2') t1.start() threads.append(t1) t2.start() threads.append(t2) for t in threads: t.join() print ("end of main thread")

It will produce the following output −

Thread1 has acquired lock and is running synchronized method
**********
lock released for Thread1
Thread2 has acquired lock and is running synchronized method
**********
lock released for Thread2
end of main thread

The Semaphore Object

Python supports thread synchronization with another mechanism called semaphore. It is one of the oldest synchronization techniques invented by a well-known computer scientist, Edsger W. Dijkstra.

The basic concept of semaphore is to use an internal counter which is decremented by each acquire() call and incremented by each release() call. The counter can never go below zero; when acquire() finds that it is zero, it blocks, waiting until some other thread calls release().

The Semaphore class in threading module defines acquire() and release() methods.

The acquire() Method

If the internal counter is larger than zero on entry, decrement it by one and return True immediately.

If the internal counter is zero on entry, block until awoken by a call to release(). Once awoken (and the counter is greater than 0), decrement the counter by 1 and return True. Exactly one thread will be awoken by each call to release(). The order in which threads awake is arbitrary.

If blocking parameter is set to False, do not block. If a call without an argument would block, return False immediately; otherwise, do the same thing as when called without arguments, and return True.

The release() Method

Release a semaphore, incrementing the internal counter by 1. When it was zero on entry and other threads are waiting for it to become larger than zero again, wake up n of those threads.

Example

 
from threading import * import time # creating thread instance where count = 3 lock = Semaphore(4) # creating instance def synchronized(name): # calling acquire method lock.acquire() for n in range(3): print('Hello! ', end = '') time.sleep(1) print( name) # calling release method lock.release() # creating multiple thread thread_1 = Thread(target = synchronized , args = ('Thread 1',)) thread_2 = Thread(target = synchronized , args = ('Thread 2',)) thread_3 = Thread(target = synchronized , args = ('Thread 3',)) # calling the threads thread_1.start() thread_2.start() thread_3.start()

It will produce the following output −

Hello! Hello! Hello! Thread 1
Hello! Thread 2
Thread 3
Hello! Hello! Thread 1
Hello! Thread 3
Thread 2
Hello! Hello! Thread 1
Thread 3
Thread 2


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