This week, we're updating our course layouts and descriptions. Presentation and materials always gently change over time, but just occasionally there's a need to make a step change to clear out some of the old and roll in the new. That's now happening - but over a long and complex site it's not instant and you'll see sections of the site changing up to and including 19th September.
See also [here] for status update
Multiple processes (forking) in Python
What is forking
If you want a process to head off in two different directions, you can fork
it. That results in identical copies of the process being created - the original (parent) and the copy (child), each with their own complete set of variables, and program counter, etc.
The clever thing is that the parent can tell
it's the parent because the fork
function return the process id of the child to it, and the child can tell its the child because it gets a false return from the fork. Thus you can test the code and have parent and child go off in different logic:
gerald = fork()
Full Sample source
Why would you fork a process?
if not gerald:
# child - doesn't know parent's PID
# parent - gets process id of child
If you're writing something like a print driver, then it can be a good idea to fork a process off to print, while you continue with the main parent code.
We've got an example of this technique in use to "ping" to a whole series of remote systems ... forking off a new child each time that an IP address is entered, with potentially lots of children waiting for slow / inaccessible hosts in parallel
Full Sample Source
What is you want to correlate responses from the children?
The "trick" here is to open a pipe before
you fork; forking connects the read handle in the child to the write handle in the parent, and vice versa, so that the child can remain in touch with the child.
Full Sample source
Note that that parent process will now have to wait for the child - so you're not getting the same parallel benefits. You can use signals, and methods that check whether data's available in the buffers, to add greater flexibility if you need to do so.
Python threads are a lighter weight way of parallel processing - where execution remains within a single process. I've got an article about that [here] in the solution centre.
You can also start off two completely independent processes - on the same computer or on different computers - and have them talk through a network port - TCP or UDP. That's a subject for a further post! Now made [here]
Associated topics are indexed as below, or enter http://melksh.am/nnnn for individual articlesP223 - Perl - Interprocess Communication 
Run other processes from within your Perl program - (2012-12-03) 
Handling binary data in Perl is easy! - (2011-08-30) 
What are .pid files? - (2010-10-23) 
Children, zombies, and reaping processes - (2010-10-23) 
Perl - doing several things at the same time - (2010-09-25) 
Perl Socket Programming Examples - (2008-12-02) 
Perl - multiprocess applications - (2006-02-13)Y303 - Python Network Programming 
Python network programming - new FTP and socket level examples - (2013-05-14) 
Running operating system commands from your Python program - (2010-05-14) 
TCP v UDP / Client v Server - Python examples - (2010-03-25) 
Python - fresh examples of all the fundamentals - (2009-08-20) 
Counting Words in Python via the web - (2009-08-18)
Some other Articles
Ruth Davis, 1916 - 2010Email metrics and filteringGarlic bread without garlicMultiple processes (forking) in PythonMethods that run on classes (static methods) in PythonFlexible search and replace in PythonNew brochures for the Melksham areaThe World Company Register - is it another scam?Can my dog eat potatoes? Doggie Dietary Research, and political sleaze!
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