How Can I Easily Implement Interprocess Communication in Python?

Interprocess Communication in Python

When working with multiple Python runtimes, it becomes necessary to establish effective interprocess communication. Various methods exist, including:

• Named Pipes (os.mkfifo): While a basic option, it can feel unrefined and prone to errors.
• DBus Services: Suitable for desktop environments, but overly complex for headless systems.
• Sockets: Low-level and manually intensive.

A Comprehensive Solution

To address your specific requirements, consider the multiprocessing library. It provides listeners and clients that seamlessly handle socket communication and enable the transmission of arbitrary Python objects.

Server Implementation

The server can be configured to listen for incoming messages:

<code class="python">from multiprocessing.connection import Listener

address = ('localhost', 6000)
listener = Listener(address, authkey=b'secret password')
conn = listener.accept()
print('connection accepted from', listener.last_accepted)
while True:
    msg = conn.recv()
    # Process the received message here
    if msg == 'close':
        conn.close()
        break
listener.close()</code>

Client Implementation

The client can initiate communication and send commands as Python objects:

<code class="python">from multiprocessing.connection import Client

address = ('localhost', 6000)
conn = Client(address, authkey=b'secret password')
conn.send('close')
# Send arbitrary objects:
# conn.send(['a', 2.5, None, int, sum])
conn.close()</code>

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