Tag: IPC

Python Signals

Python has a signal module that is used to respond to signals generated by the operating system. Signals are a very low-level form of interprocess communication, but there are some cases where a program may wish to respond to a signal. For example, it may be useful to watch for program signals when writing developer toolkits.

This post demonstrates how to respond to an alarm signal. The example is borrowed from Programming Python: Powerful Object-Oriented Programming. I added my own comments to help explain the workings of the program.

Code

import sys, signal, time


# Function that returns the time
def now():
    return time.asctime()


# Function that handles the signal
def onSignal(signum, stackframe):
    print('Got alarm', signum, 'at', now())


while True:
    print('Setting at', now())
    
    # This tells the program to respond to the alarm signal
    # by calling the onSignal function
    signal.signal(signal.SIGALRM, onSignal)
    
    # Raise SIGALRM (Note this can be done by other processes also)
    signal.alarm(5)
    
    signal.pause()

Explanation

The code defines an onSignal function that works as a handler to operating system signals found on lines 10-11. All it does is prints text to the console. On line 19, we register onSignal as a handler for the SIGALRM os signal. Line 22 shows how to raise an os signal, which then invokes onSignal. Note that we don’t have to have our programs actually raise signals. We can also simply listen for other os signals raised by other programs (for example, the kill signal which is raised by executing killall in a unix shell).

References

Lutz, Mark. Programming Python. Beijing, OReilly, 2013.

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Python Sockets

Network sockets are extremely useful for interprocess communication (IPC). Not only do network sockets allow processes to communicate on the same machine, but we can also use sockets to communicate over a network. This post shows the most basic demonstration of network sockets using an example borrowed from Programming Python: Powerful Object-Oriented Programming. I added my own comments to help explain the program.

Code

from socket import socket, AF_INET, SOCK_STREAM

port = 50008
host = 'localhost'


# Function to create a server
def server():
    # Create a network socket
    sock = socket(AF_INET, SOCK_STREAM)

    # Bind the socket to localhost with our port
    sock.bind(('', port))

    # Listen for up to 5 connections
    sock.listen(5)
    while True:
        # Wait for a client
        conn, addr = sock.accept()

        # Grab a megabyte of data from the client
        data = conn.recv(1024)

        # Create a reply string
        reply = 'server got: [{}]'.format(data)

        # Send the reply back to the client
        conn.send(reply.encode())


# Function to create a socket client
def client(name):
    # Create a socket
    sock = socket(AF_INET, SOCK_STREAM)

    # Connect the socket to the server
    sock.connect((host, port))

    # Send a message to the server
    sock.send(name.encode())

    # Receive a megabyte of data from the server
    reply = sock.recv(1024)

    # Close our connection
    sock.close()

    # Print the output
    print('Client got: [{}]'.format(reply))


if __name__ == '__main__':
    from threading import Thread

    # Create a thread for the server
    sthread = Thread(target=server)
    sthread.daemon = True
    sthread.start()

    # Create 5 client threads
    for i in range(5):
        Thread(target=client, args=('client{}'.format(i),)).start()

Explanation

The example program creates a basic client / server program. The program uses threads to help keep the program simple. One thread calls the server function defined on lines 8-28 and the remaining five threads call the client function found on line 32-49. The server thread creates a network server that accepts up to five connections from the client threads.

The server function starts by creating a socket object (called sock). On line 13, the program binds our socket to the machines localhost address and the port number specified on line 3. On line 16, the socket waits for up to five connections. Then the server enters a loop on line 17.

Inside of the of the loop, we have a call to sock.accept(). This function accepts a connection from a client and returns a connection and address object. Out program only uses the connection object. The program reads data from the client on line 22 using conn.recv. The conn.recv function takes a number of bytes to read from the client. The conn.recv returns binary information and the program stores it in the data varaible. Lines 25 and 28 show how to send information back to the client using conn.send. The conn.send function expects binary information, which is why we call encode() on the reply variable.

The client function acts almost exactly like the server function. The socket client is created on line 34. We use the connect function (line 37) to connect to the server and pass it a tuple containing the host and the port number. Unlike the server, which has its own dedicated connection object, the client uses the socket object itself to send and receive information to and from the server. On line 40, the program calls sock.send() and passes it a binary string to send to the server. The response from the server is collected on line 43 using sock.recv(). When the client is finished, it needs to close its connection to the server using sock.close().

References

Lutz, Mark. Programming Python. Beijing, OReilly, 2013.

Python Basic Pipes

Python provides two main avenues of parallel processing. One avenue is to use multithreading where a program itself multitasks, while the other approach is to have a program relaunch itself as a separate program in a new process. One approach is not necessarily better than the other approach but instead, should be throught of as tools for different use cases. Threads have low overhead and share a program’s memory space, which allows for easy communication between threads. Processes operate as if we launched a new copy of the program from our operating system and allow programs to spread themselves out over an operating system or even a network.

However, processes do not share a global memory space, which means they need a way to communicate with one another. One approach to interprocess communication (IPC) is to use pipes. This post shows an example of IPC using pipes taken from Programming Python: Powerful Object-Oriented Programming. I have added my own comments to the code for clarity.

Code

import os, time


# Function called by child processes
def child(pipeout):
    zzz = 0
    while True:
        time.sleep(zzz)

        # We have to encode our string to binary to use
        # with pipes
        msg = ('Spam {}'.format(zzz)).encode()

        # Send the data back to the parent process
        os.write(pipeout, msg)
        zzz = (zzz + 1) % 5


def parent():
    # Creates our pipes. The pipeout gets passed to the child
    # process while parent keeps pipein
    pipein, pipeout = os.pipe()

    if os.fork() == 0:
        # We are now in the child process so call child and supply
        # it with pipeout so that it can send information back to
        # the parent.
        child(pipeout)
    else:
        # This is the parent process
        while True:
            # Read data from the child process
            # This call blocks until there is data
            line = os.read(pipein, 32)

            # Print to the console
            print('Parent {} got [{}] as {}'.format(os.getpid(), line, time.time()))


if __name__ == '__main__':
    parent()

Explanation

We have two functions in the program named child() and parent(). The child() function is intended to run in child processes while parent() contains the main program. Parent() is defined on lines 19-37. The function begins by calling os.pipe() on line 22 which returns a tuple containing two ends of a single pipe. Pipes are unidirectional and thus pipein is used by the parent to read data that comes from the child process. The child process uses pipeout to send data to the parent.

The program forks into two different processes on line 24. The program is in the child process when os.fork() returns zero. Line 28 calls the child() function and passes pipeout to the child function so that the child process can send data back to the parent. The child process enters an infinite loop on line 7. On line 12, a msg variable is created that contains a String variable. Pipe send binary data, so we have to call encode() on the String to convert it to a binary string. Then on line 15, we send the msg varaiable back to the parent using os.write and supplying pipeout and msg to that function.

The parent process continues on line 31. It attempts to read data from the child process on line 34 using os.read. Notice that os.read requires a pipein variable and the size of binary data to read (32 bytes in this program). If the pipe contains data, os.read returns immedialy and stores the value in the line variable. Otherwise, os.read blocks the program until the pipe has data. The parent process prints the data on line 37.

References

Lutz, Mark. Programming Python. Beijing, OReilly, 2013.

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