Using Shared Memory Manager for Mutable Lists

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Now, if you’ve ever worked with large datasets or multiple processes sharing data, you know how frustrating it can be when your code starts throwing errors left and right because of race conditions and synchronization issues. Thats where a shared memory manager comes in handy! It allows us to create a common space for our mutable lists (lists that we can modify) so that multiple processes or threads can access them without having to worry about conflicts.
So, how does it work? Well, let’s say you have two functions: `function_a` and `function_b`. Both of these functions need to access a list called `mylist`, but they also need to modify that same list independently. Without using a shared memory manager, this would be a recipe for disaster!
Heres an example code snippet without the use of a shared memory manager:

# Import necessary libraries
import time
import multiprocessing as mp
from mmap_shared_memory import MMapSharedMemory

# Define function_a
def function_a():
    global mylist # Declare global variable
    while True:
        # Do some stuff with mylist...
        for i in range(10):
            mylist.append(i) # Add element to mylist
            print("Function A added", i, "to the list")
            time.sleep(1) # Pause for 1 second

# Define function_b
def function_b():
    global mylist # Declare global variable
    while True:
        # Do some stuff with mylist...
        for j in range(5):
            mylist[j] = 2 * mylist[j] # Double element in mylist
            print("Function B doubled", mylist[j], "in the list")
            time.sleep(1) # Pause for 1 second

# Check if script is being run directly
if __name__ == '__main__':
    # Create a shared memory manager for our mutable lists
    shm = MMapSharedMemory(1024) # Initialize shared memory manager with size 1024
    mylist = [0] * 50 # Initialize mylist with 50 zeros
    shm.write(mylist, 0) # Write mylist to shared memory manager at index 0
    
    # Start two processes that will access our shared memory manager
    p1 = mp.Process(target=function_a) # Create process for function_a
    p2 = mp.Process(target=function_b) # Create process for function_b
    p1.start() # Start process for function_a
    p2.start() # Start process for function_b
    
    # Wait for the processes to finish
    p1.join() # Wait for process for function_a to finish
    p2.join() # Wait for process for function_b to finish

In this example, we’re using a shared memory manager called `mmap_shared_memory`. This library allows us to create a common space in memory that can be accessed by multiple processes or threads without having to worry about synchronization issues. We initialize the shared memory manager with a list of zeros and then pass it into our functions as an argument.
Now, let’s take a closer look at how this code works:
1. First, we import `multiprocessing` and `mmap_shared_memory`.
2. Next, we initialize the shared memory manager with a size of 1024 bytes (which is more than enough for our list).
3. We create an empty list called `mylist` that has a length of 50. This will be used to store our data in the shared memory manager.
4. We write this list into the shared memory manager using the `write()` method provided by `mmap_shared_memory`.
5. Finally, we start two processes (using `multiprocessing`) that access and modify the same list stored in the shared memory manager.
The beauty of a shared memory manager is that it allows us to avoid race conditions and synchronization issues because all modifications are made directly to the shared memory space rather than through a centralized data structure like a lock or semaphore. This can lead to significant performance improvements, especially when working with large datasets or multiple processes sharing data.
Using a shared memory manager for mutable lists in Python is an easy and effective way to avoid race conditions and synchronization issues while working with large datasets or multiple processes sharing data. Give it a try and let us know how it works for you!

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