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        "author": "Jamie Cockburn and Andrew Binnie",
        "author_email": "jamie_cockburn@hotmail.co.uk",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "============================\npython-multiprocessing-utils\n============================\n\nMultiprocessing utilities\n\n************\nShared locks\n************\n\n\"Shared\" version of the standard ``Lock()`` and ``RLock()`` classes found in\nthe ``multiprocessing``/``threading`` modules.\n\nShared locks can be acquired in two modes, shared and exclusive.\n\nAny number of processes/threads can acquire the lock in shared mode.\n\nOnly one process/thread can acquire the lock in exclusive mode.\n\nA process/thread attempting to exclusively acquire the lock will block\nuntil the lock has been released by all other threads/processes.\n\nA process/thread attempting to shared acquire the lock will only block\nwhile there is an exclusive lock.\n\nThis is a little like database locks, which can be acquired for shared reading,\nor exclusive writing.\n\n::\n\n    lock = multiprocessing_utils.SharedLock()\n\n    def exclusive_worker():\n        with lock.exclusive():\n            # this code will only run when no other\n            # process/thread in a lock context\n\n    def shared_worker():\n        with lock:\n            # this code will run so long as no\n            # thread/process holds an exclusive lock\n\n***************************************\nmultiprocess-safe ``threading.local()``\n***************************************\n\nA process (and thread) safe version of ``threading.local()``\n\n::\n\n    l = multiprocessing_utils.local()\n    l.x = 1\n\n    def f():\n        try:\n            print(l.x)\n        except Attribute:\n            print(\"x not set\")\n    f()                                        # prints \"1\"\n    threading.Thread(target=f).start()         # prints \"x not set\"\n    multiprocessing.Process(target=f).start()  # prints \"x not set\"\n\nDifference to standard ``threading.local()``\n--------------------------------------------\n\nA standard ``threading.local()`` instance created before forking (via\n``os.fork()`` or ``multiprocessing.Process()``) will be \"local\" as expected\nand the new process will have access to any data set before the fork.\n\nUsing a standard ``threading.local()`` in the example above would yield:\n\n::\n\n    f()                                        # prints \"1\"\n    threading.Thread(target=f).start()         # prints \"x not set\"\n    multiprocessing.Process(target=f).start()  # prints \"1\" :(\n\n\n",
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        "keywords": "",
        "license": "MIT",
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        "name": "multiprocessing-utils",
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        "summary": "Multiprocessing utils (shared locks and thread locals)",
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