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How can Python\'s multiprocessing library simplify Interprocess Communication?
How can Python\'s multiprocessing library simplify Interprocess Communication?
Interprocess Communication in Python
Interprocess communication (IPC) enables communication between multiple running Python processes. Exploring various options, such as using named pipes, dbus services, and sockets, can be challenging. This article presents a higher-level and robust solution using the multiprocessing library.
Using the Multiprocessing Library
The multiprocessing library offers a convenient and efficient way to implement IPC in Python. It provides listeners and clients that encapsulate sockets and allow you to exchange Python objects directly.
Listening for Messages
To create a listening process, use the Listener class:
<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)</code>The listener waits on a specified IP address and port for incoming connections. Once a connection is established, a Connection object (conn) is returned.
Sending Messages
To send messages as Python objects, use the Client class:
<code class="python">from multiprocessing.connection import Client
address = ('localhost', 6000)
conn = Client(address, authkey=b'secret password')
conn.send('close')
conn.close()</code>The Client class connects to the specified address and can send arbitrary objects to the listening process.
Example Implementation
Consider a simple use case where one process (listener.py) listens for messages and the other (client.py) sends a message.
listener.py:
<code class="python">from multiprocessing.connection import Listener
listener = Listener(('localhost', 6000), authkey=b'secret password')
conn = listener.accept()
message = conn.recv()
if message == 'close':
conn.close()
listener.close()
exit(0)
else:
conn.close()
listener.close()
exit(1)</code>client.py:
<code class="python">from multiprocessing.connection import Client
conn = Client(('localhost', 6000), authkey=b'secret password')
conn.send('close')
conn.close()</code>When you run listener.py and then client.py, the listener process will receive the message and exit with return code 0, indicating success. If an invalid message is sent, the listener will exit with a non-zero return code, indicating failure.
This example demonstrates the ease and flexibility of using the multiprocessing library for interprocess communication in Python. It provides a higher-level abstraction over sockets, allowing you to seamlessly send and receive Python objects between processes.
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