Are locks unnecessary in multi-threaded Python code because of the GIL?

Question

If you are relying on an implementation of Python that has a Global Interpreter Lock (i.e. CPython) and writing multithreaded code, do you really need locks at all?

Answer 1

You will still need locks if you share state between threads. The GIL only protects the interpreter internally. You can still have inconsistent updates in your own code.

For example:

#!/usr/bin/env python
import threading

shared_balance = 0

class Deposit(threading.Thread):
    def run(self):
        for _ in xrange(1000000):
            global shared_balance
            balance = shared_balance
            balance += 100
            shared_balance = balance

class Withdraw(threading.Thread):
    def run(self):
        for _ in xrange(1000000):
            global shared_balance
            balance = shared_balance
            balance -= 100
            shared_balance = balance

threads = [Deposit(), Withdraw()]

for thread in threads:
    thread.start()

for thread in threads:
    thread.join()

print shared_balance

Here, your code can be interrupted between reading the shared state (balance = shared_balance) and writing the changed result back (shared_balance = balance), causing a lost update. The result is a random value for the shared state.

To make the updates consistent, run methods would need to lock the shared state around the read-modify-write sections (inside the loops) or have some way to detect when the shared state had changed since it was read.