{"id":18260,"date":"2021-06-20T19:30:23","date_gmt":"2021-06-20T19:30:23","guid":{"rendered":"https:\/\/www.askpython.com\/?p=18260"},"modified":"2021-06-22T15:47:28","modified_gmt":"2021-06-22T15:47:28","slug":"synchronization-in-python","status":"publish","type":"post","link":"https:\/\/www.askpython.com\/python\/examples\/synchronization-in-python","title":{"rendered":"Synchronization in Python – Synchronize Threads in Python"},"content":{"rendered":"\n

Let’s talk about synchronization in Python. Multithreading<\/a> allows your computer to perform actions in parallel, utilizing multiple cores\/ multiple CPUs present on your system. However, when it comes to reading and updating shared variables at the same time, it can lead to erroneous results. We will learn how to synchronize threads to give correct results.<\/p>\n\n\n\n

Understanding the Race Condition in Multithreading<\/h2>\n\n\n\n

When 2 or more threads try to access a shared resource simultaneously and change the data, the final value of such variables is unpredictable. This is because the thread scheduling algorithm can swap between threads at any time and you don’t know which thread will execute first. This scenario is called a race condition.<\/p>\n\n\n\n

Let us take an example where we transfer some amount from one bank account to another using threads. We will create 100 threads to transfer 1 unit from account1 to account2.<\/p>\n\n\n

\nimport threading\nimport time\n\nclass BankAccount():\n  def __init__(self, name, balance):\n    self.name = name\n    self.balance = balance\n\n  def __str__(self):\n    return self.name\n\n# These accounts are our shared resources\naccount1 = BankAccount("account1", 100)\naccount2 = BankAccount("account2", 0)\n\nclass BankTransferThread(threading.Thread):\n  def __init__(self, sender, receiver, amount):\n    threading.Thread.__init__(self)\n    self.sender = sender\n    self.receiver = receiver\n    self.amount = amount\n  \n  def run(self):\n    sender_initial_balance = self.sender.balance\n    sender_initial_balance -= self.amount\n    # Inserting delay to allow switch between threads\n    time.sleep(0.001)\n    self.sender.balance = sender_initial_balance\n    \n    receiver_initial_balance = self.receiver.balance\n    receiver_initial_balance += self.amount\n    # Inserting delay to allow switch between threads\n    time.sleep(0.001)\n    self.receiver.balance = receiver_initial_balance\n\nif __name__ == "__main__":\n  \n  threads = []\n\n  for i in range(100):\n    threads.append(BankTransferThread(account1, account2, 1))\n\n  for thread in threads:\n    thread.start()\n\n  for thread in threads:\n    thread.join()\n\n  print(account1.balance)\n  print(account2.balance)\n<\/pre><\/div>\n\n
\naccount1 98\naccount2 3\n<\/pre><\/div>\n\n\n
Initially, account1 has 100 units and account2 has 0 units. <\/p>\n\n\n\n
After 100 transfers of 1 unit, account1 should have 0 units and the account2 should have 100 units. However, we got different results. If we run this multiple times, we will get different results.<\/p>\n\n\n\n
Synchronization in Python – Different Methods to Synchronize Threads<\/h2>\n\n\n\n
Lets see how to synchronize threads to avoid race conditions.<\/p>\n\n\n\n
1. Lock Objects<\/h3>\n\n\n\n
A Lock object is the most basic synchronization primitive which is not owned by a particular thread when locked. A Lock object does not keep information about which thread has a permit of the lock and any thread can release the lock.<\/p>\n\n\n\n
The Lock object is in one of the 2 states, “locked” and “unlocked”. When the Lock object is created, it is in the “unlocked” state. There are only 3 methods in the lock object:<\/p>\n\n\n\n