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findduplicates-tpy program, and in general it is best to design programs from the ground up with multiprocessing in mind (The program findduplicates-mpy is provided with the book s examples; it does the same job as findduplicatestpy but works in a very different way and uses the multiprocessing module)
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Another solution being developed is a threading-friendly version of the CPython interpreter; see wwwcodegooglecom/p/python-threadsafe for the latest project status
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Summary
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This chapter showed how to create programs that can execute other programs using the standard library s subprocess module Programs that are run using subprocess can be given command-line data, can be fed data to their standard input, and can have their standard output (and standard error) read Using child processes allows us to take maximum advantage of multicore processors and leaves concurrency issues to be handled by the operating system The downside is that if we need to share data or synchronize processes we must devise some kind of communication mechanism, for example, shared memory (eg, using the mmap module), shared les, or networking, and this can require care to get right The chapter also showed how to create multithreaded programs Unfortunately, such programs cannot take full advantage of multiple cores (if run using the standard CPython interpreter), so for Python, using multiple processes is often a more practical solution where performance is concerned Nonetheless, we saw that the queue module and Python s locking mechanisms, such as threadingLock, make threaded programming as straightforward as possible and that for simple programs that only need to use queue objects like queueQueue and queuePriorityQueue, we may be able to completely avoid using explicit locks Although multithreaded programming is undoubtedly fashionable, it can be much more demanding to write, maintain, and debug multithreaded programs than single-threaded ones However, multithreaded programs allow for straightforward communication, for example, using shared data (providing we use a queue class or use locking), and make it much easier to synchronize (eg, to gather results) than using child processes Threading can also be very useful in GUI (Graphical User Interface) programs that must carry out long-running tasks while maintaining responsiveness, including the ability to cancel the task being worked on But if a good communication mechanism between processes is used, such as shared memory, or the process-transparent queue offered by the multiprocessing package, using multiple processes can often be a viable alternative to multiple threads
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The following chapter shows another example of a threaded program; a server that handles each client request in a separate thread, and that uses locks to protect shared data
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Exercises
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1 Copy and modify the grepword-ppy program so that instead of the child processes printing their output, the main program gathers the results, and after all the child processes have nished, sorts and prints the results This only requires editing the main() function and changing three lines and adding three lines The exercise does require some thought and care, and you will need to read the subprocess module s documentation A solution is given in grepword-p_anspy 2 Write a multithreaded program that reads the les listed on the command line (and the les in any directories listed on the command line, recursively) For any le that is an XML le (ie, it begins with the characters < xml ), parse the le using an XML parser and produce a list of the unique tags used by the le or an error message if a parsing error occurs Here is a sample of the program s output from one particular run:
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/data/dvdsxml is an XML file that uses the following tags: dvd dvds /data/badaix is an XML file that has the following error: mismatched tag: line 7889, column 2 /data/incidentsaix is an XML file that uses the following tags: airport incident incidents narrative
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The easiest way to write the program is to modify a copy of the findduplicates-tpy program, although you can of course write the program entirely from scratch Small changes will need to be made to the Worker class s __init__() and run() methods, and the process() method will need to be rewritten entirely (but needs only around twenty lines) The program s main() function will need several simpli cations and so will one line of the print_results() function The usage message will also need to be modi ed to match the one shown here:
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Usage: xmlsummarypy [options] [path] outputs a summary of the XML files in path; path defaults to Options: -h, --help
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