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6.2 Storing Per-Thread Information

Credit: John E. Barham

6.2.1 Problem

You need to allocate storage to each thread for objects that only that thread can use.

6.2.2 Solution

Thread-specific storage is a useful pattern, and Python does not support it directly. A simple dictionary, protected by a lock, makes it pretty easy to program. For once, it's slightly more general, and not significantly harder, to program to the lower-level thread module, rather than to the more common, higher-level threading module that Python also offers on top of it:

    import thread
    """ We're running on a single-threaded OS (or the Python interpreter has
    not been compiled to support threads), so return a standard dictionary. """
    _tss = {}
    def get_thread_storage(  ):
        return _tss
    """ We do have threads; so, to work: """
    _tss = {}
    _tss_lock = thread.allocate_lock(  )
    def get_thread_storage(  ):
        """ Return a thread-specific storage dictionary. """
        thread_id = thread.get_ident(  ) # Identify the calling thread
        tss = _tss.get(thread_id)
        if tss is None: # First time being called by this thread
            try: # Entering critical section
                _tss_lock.acquire(  )
                _tss[thread_id] = tss = {} # Create thread-specific dictionary
                _tss_lock.release(  )
        return tss

6.2.3 Discussion

The get_thread_storage function in this recipe returns a thread-specific storage dictionary. It is a generalization of the get_transaction function from ZODB, the object database underlying Zope. The returned dictionary can be used to store data that is private to the thread.

One benefit of multithreaded programs is that all of the threads can share global objects. Often, however, each thread needs some storage of its own梖or example, to store a network or database connection unique to itself. Indeed, such externally oriented objects are best kept under the control of a single thread to avoid multiple possibilities of highly peculiar behavior, race conditions, and so on.

The get_thread_storage function returns a dictionary object that is unique to each thread. For an exhaustive treatment of thread-specific storage (albeit aimed at C++ programmers), see http://www.cs.wustl.edu/~schmidt/PDF/TSS-pattern.pdf.

A useful extension would be to add a delete_thread_storage function, particularly if a way could be found to automate its being called upon thread termination. Python's threading architecture does not make this task particularly easy. You could spawn a watcher thread to do the deletion after a join with the calling thread, but that might be rather heavyweight. The recipe as presented, without deletion, is quite appropriate for the common architecture in which you have a pool of (typically daemonic) worker threads that are spawned at the start and do not go away until the end of the whole process.

6.2.4 See Also

"Thread-specific Storage: an Object Behavioral Pattern for Efficiently Accessing per-Thread State", by Douglas Schmidt, Timothy Harrisson, and Nat Pryce (http://www.cs.wustl.edu/~schmidt/PDF/TSS-pattern.pdf).

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