How to Share Locks Between Processes in Python Multiprocessing Applications

Sharing Locks Across Processes with Python

In multithreaded applications, locks are crucial for synchronizing access to shared resources. However, when these processes are distributed across multiple child processes, sharing locks between them can be a challenge.

Problem:

Consider a function that utilizes a multiprocessing.Lock() object (l) to manage access to critical resources. After creating a pool of worker processes (pool) and a partial function (func) that passes the lock as an argument, an attempt to use pool.map() to distribute the task across multiple processes results in a runtime error: "Lock objects should only be shared between processes through inheritance."

Missing Element:

The error arises because, by default, Python cannot safely pickle regular multiprocessing.Lock() instances for inter-process communication.

Solution:

To overcome this limitation and successfully share the lock across processes, two viable approaches exist:

1. Using a Manager Object:

   • Create a multiprocessing.Manager() instance (m) and pass a Manager.Lock(), which allows secure data sharing between processes.
   • This method introduces additional overhead due to the need for an external manager process and IPC.

2. Passing the Lock at Pool Creation:

   • Pass the regular multiprocessing.Lock() (l) at pool initialization using the initializer kwarg.
   • This makes the lock instance globally accessible within all child processes, eliminating the need for a partial function.

Code Example (Using Second Solution):

<code class="python">from multiprocessing import Pool, Lock

def init(l):
    global lock
    lock = l

def target(iterable_item):
    # Access shared resources using lock

def main():
    l = Lock()
    pool = Pool(initializer=init, initargs=(l,))
    pool.map(target, iterable)
    pool.close()
    pool.join()</code>

By following these methods, you can effectively share locks between processes, enabling synchronization and data sharing in distributed Python applications.

The above is the detailed content of How to Share Locks Between Processes in Python Multiprocessing Applications. For more information, please follow other related articles on the PHP Chinese website!