python multithreaded programming 4: deadlock and reentrant lock

Deadlock

When multiple resources are shared between threads, if two threads each occupy part of the resources and wait for each other's resources at the same time, a deadlock will occur. Although deadlocks occur rarely, when they do occur they can cause the application to stop responding. Let’s look at an example of deadlock:

# encoding: UTF-8
import threading
import time
  
class MyThread(threading.Thread):
    def do1(self):
        global resA, resB
        if mutexA.acquire():
             msg = self.name+' got resA'
             print msg
               
             if mutexB.acquire(1):
                 msg = self.name+' got resB'
                 print msg
                 mutexB.release()
             mutexA.release()
    def do2(self):
        global resA, resB
        if mutexB.acquire():
             msg = self.name+' got resB'
             print msg
               
             if mutexA.acquire(1):
                 msg = self.name+' got resA'
                 print msg
                 mutexA.release()
             mutexB.release()
   
      
    def run(self):
        self.do1()
        self.do2()
resA = 0
resB = 0
  
mutexA = threading.Lock()
mutexB = threading.Lock()
  
def test():
    for i in range(5):
        t = MyThread()
        t.start()
if __name__ == '__main__':
    test()

Execution result:

Thread-1 got resA

Thread-1 got resB

Thread-1 got resB

Thread-1 got resA

Thread-2 got resA

Thread-2 got resB

Thread-2 got resB

Thread-2 got resA

Thread-3 got resA

Thread-3 got resB

Thread-3 got resB

Thread-3 got resA

Thread-5 got resA

Thread-5 got resB

Thread-5 got resB

Thread-4 got resA

The process has died at this time.

Reentrant lock

A simpler deadlock situation is when a thread "iterates" to request the same resource, which will directly cause a deadlock:

import threading
import time
  
class MyThread(threading.Thread):
    def run(self):
        global num
        time.sleep(1)
  
        if mutex.acquire(1): 
            num = num+1
            msg = self.name+' set num to '+str(num)
            print msg
            mutex.acquire()
            mutex.release()
            mutex.release()
num = 0
mutex = threading.Lock()
def test():
    for i in range(5):
        t = MyThread()
        t.start()
if __name__ == '__main__':
    test()

In order to support multiple requests for the same resource in the same thread, Python provides a "reentrant lock": threading.RLock. RLock maintains a Lock and a counter variable internally. The counter records the number of acquires, so that the resource can be required multiple times. Until all acquires of a thread are released, other threads can obtain resources. In the above example, if RLock is used instead of Lock, no deadlock will occur:

import threading
import time
  
class MyThread(threading.Thread):
    def run(self):
        global num
        time.sleep(1)
  
        if mutex.acquire(1): 
            num = num+1
            msg = self.name+' set num to '+str(num)
            print msg
            mutex.acquire()
            mutex.release()
            mutex.release()
num = 0
mutex = threading.RLock()
def test():
    for i in range(5):
        t = MyThread()
        t.start()
if __name__ == '__main__':
    test()

Execution result:

Thread-1 set num to 1

Thread-3 set num to 2

Thread-2 set num to 3

Thread-5 set num to 4

Thread-4 set num to 5