Detailed explanation of synchronization lock in python thread-Python Tutorial-php.cn

This article mainly introduces the relevant information of synchronization locks in python threads in detail, which has certain reference value. Interested friends can refer to it

In applications using multi-threads, How to ensure thread safety, synchronization between threads, or access to shared variables are very difficult issues. They are also problems faced when using multi-threading. If not handled well, it will bring serious consequences. Use python multi-threading. Lock Rlock Semaphore Event Condition is provided to ensure synchronization between threads, and the latter ensures mutual exclusion of access to shared variables

Lock & RLock: Mutex locks are used to ensure multi-thread access to shared variables
Semaphore object: An enhanced version of the Lock mutex, which can be owned by multiple threads at the same time, while Lock can only be owned by a certain thread at the same time.
Event object: It is a method of communication between threads, equivalent to a signal. One thread can send a signal to another thread and then let it perform an operation.
Condition object: It can process data only after certain events are triggered or specific conditions are met

1. Lock (mutex lock)

Request lock — Enter the lock pool and wait — Acquire lock — Locked — Release lock

Lock (instruction lock) is the lowest-level synchronization instruction available. When Lock is in the locked state, it is not owned by a specific thread. Lock contains two states - locked and non-locked, and two basic methods.

It can be thought that Lock has a lock pool. When a thread requests a lock, the thread is placed in the pool until it is released from the pool after obtaining the lock. Threads in the pool are in the synchronous blocking state in the state diagram.

Construction method:
Lock()

Instance method:
acquire([timeout]): Put the thread into a synchronous blocking state and try to obtain the lock .
release(): Release the lock. The thread must have acquired the lock before use, otherwise an exception will be thrown.

if mutex.acquire():
 counter += 1
 print "I am %s, set counter:%s" % (self.name, counter)
  mutex.release()

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2. RLock (reentrant lock)

RLock (reentrant lock) is a Synchronization instructions requested multiple times by the same thread. RLock uses the concepts of "owned thread" and "recursion level". When in the locked state, RLock is owned by a thread. The thread that owns the RLock can call acquire() again and needs to call release() the same number of times to release the lock.

It can be considered that RLock contains a lock pool and a counter with an initial value of 0. Each time acquire()/release() is successfully called, the counter will be 1/-1. When it is 0, the lock is in the unlocked state. Locked status.

Construction method:
RLock()

Instance method:
acquire([timeout])/release(): Similar to Lock.

3. Semaphore (shared object access)

Let’s talk about Semaphore again. To be honest, Semaphore is the latest synchronization lock I used. Similar implementations in the past were I used Rlock to implement it, which is relatively convoluted. After all, Rlock requires locking and unlocking in pairs. . .

Semaphore manages a built-in counter,
The built-in counter is -1 whenever acquire() is called;
The built-in counter is 1 when release() is called;
The counter cannot be less than 0; when the counter When 0, acquire() will block the thread until another thread calls release().

Go directly to the code, we control the semaphore to 3, that is to say, 3 threads can use this lock at the same time, and the remaining threads can only block and wait...

#coding:utf-8
#blog xiaorui.cc
import time
import threading

semaphore = threading.Semaphore(3)

def func():
 if semaphore.acquire():
  for i in range(3):
   time.sleep(1)
   print (threading.currentThread().getName() + &#39;获取锁&#39;)
  semaphore.release()
  print (threading.currentThread().getName() + &#39; 释放锁&#39;)


for i in range(5):
 t1 = threading.Thread(target=func)
 t1.start()

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4. Event (inter-thread communication)

Event contains a flag internally, which is initially false.
You can use set() to set it to true;
Or use clear() to reset it to false;
You can use is_set() to check the status of the flag bit;

Another most important function is wait(timeout=None), which is used to block the current thread until the internal flag bit of the event is set to true or the timeout times out. If the internal flag is true, the wait() function understands and returns.

import threading
import time

class MyThread(threading.Thread):
 def __init__(self, signal):
  threading.Thread.__init__(self)
  self.singal = signal

 def run(self):
  print "I am %s,I will sleep ..."%self.name
  self.singal.wait()
  print "I am %s, I awake..." %self.name

if __name__ == "__main__":
 singal = threading.Event()
 for t in range(0, 3):
  thread = MyThread(singal)
  thread.start()

 print "main thread sleep 3 seconds... "
 time.sleep(3)

 singal.set()

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5. Condition (thread synchronization)

Condition can be understood as an advanced tool. Provides more advanced functions than Lock and RLock, allowing us to control complex thread synchronization issues. threadiong.Condition maintains a threadion object internally (the default is RLock), which can be passed in as a parameter when creating a Condigtion object. Condition also provides acquire and release methods, whose meanings are consistent with the acquire and release methods of the host. In fact, they just simply call the corresponding methods of the internal host object. Condition also provides the following methods (especially note: these methods can only be called after acquiring, otherwise a RuntimeError exception will be reported.):

Condition.wait([ timeout]):

wait method releases the internal occupied thread, and the thread is suspended until it is awakened after receiving a notification or times out (if the timeout parameter is provided) . When the thread is awakened and reoccupies the thread, the program will continue to execute.

Condition.notify():

Wake up a suspended thread (if there is a suspended thread). Note: The notify() method will not release the occupied memory.

Condition.notify_all()
Condition.notifyAll()

唤醒所有挂起的线程（如果存在挂起的线程）。注意：这些方法不会释放所占用的琐。

对于Condition有个例子，大家可以观摩下。

from threading import Thread, Condition
import time
import random

queue = []
MAX_NUM = 10
condition = Condition()

class ProducerThread(Thread):
 def run(self):
  nums = range(5)
  global queue
  while True:
   condition.acquire()
   if len(queue) == MAX_NUM:
    print "Queue full, producer is waiting"
    condition.wait()
    print "Space in queue, Consumer notified the producer"
   num = random.choice(nums)
   queue.append(num)
   print "Produced", num
   condition.notify()
   condition.release()
   time.sleep(random.random())


class ConsumerThread(Thread):
 def run(self):
  global queue
  while True:
   condition.acquire()
   if not queue:
    print "Nothing in queue, consumer is waiting"
    condition.wait()
    print "Producer added something to queue and notified the consumer"
   num = queue.pop(0)
   print "Consumed", num
   condition.notify()
   condition.release()
   time.sleep(random.random())


ProducerThread().start()
ConsumerThread().start()

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