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        "author": "Sven R. Kunze",
        "author_email": "srkunze@mail.de",
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            "Development Status :: 2 - Pre-Alpha",
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            "License :: OSI Approved :: MIT License",
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        "description": "FORK_\n=====\n\nWrite a classic sequential program. Then convert it into a parallel one.\n\n\nWhy?\n----\n\nIt runs faster.\n\n\nWhat if not?\n------------\n\nDon't use it.\n\n\nHow?\n----\n\nBefore:\n\n.. code:: python\n\n    for image in images:\n        create_thumbnail(image)\n\nAfter:\n\n.. code:: python\n\n    from fork import fork\n\n    for image in images:\n        fork(create_thumbnail, image)\n\n\nWhat about return values?\n-------------------------\n\nAs usual:\n\n.. code:: python\n\n    result = fork(my_func, *args, **kwargs)\n\nIt's a proxy object that behaves almost exactly like the real return value of ``my_func`` except that\nit's lazy.\n\n\nHow lazy?\n---------\n\nVery lazy. You can even add, multiply, etc. such proxy results without blocking which come in\nquite handy, especially in loops. Use ``fork.await``, ``str``, ``print``, etc. to force evaluation\nand get the real and non-lazy value back.\n\n.. code:: python\n\n    sizes = 0\n    for image in images:\n        sizes += fork(create_thumbnail, image) # lazy evaluation\n    print(sizes)                               # forces evaluation\n\n\nThreads or Processes?\n---------------------\n\nYou don't need to bother. fork will take care of that for you.\n\nYou can assist fork by decorating your functions; not decorating defaults to ``fork.cpu_bound``:\n\n.. code:: python\n\n    @io_bound\n    def call_remote_webservice():\n        # implementation\n\n    @cpu_bound\n    def heavy_computation(n):\n        # implementation\n\n\nException handling\n------------------\n\nOriginal (sequential) tracebacks are preserved. That should make debugging easier.\nHowever, don't try to catch exceptions. You better want to exit and see them.\nWhen you force evaluation potential exceptions will be raised.\n\n\nAdvanced Feature: Force Specific Type of Execution\n--------------------------------------------------\n\nIf you really need more control over the type of execution, use ``fork.process`` or ``fork.thread``.\nThey work just like ``fork.fork`` but enforce the corresponding type of background execution.\n\n.. code:: python\n\n    import pkg_resources\n\n    for worker_function in pkg_resources.iter_entry_points(group='worker'):\n        process(worker_function)\n\n\nAdvanced Feature: Multiple Execution At Once\n--------------------------------------------\n\nYou can shorten your programs by using ``fork.map``. It works like ``fork.fork`` but submits\na function multiple times for each item given by an iterable.\n\n.. code:: python\n\n    results = fork.map(create_thumbnail, images)\n\n``fork.map_process`` and ``fork.map_thread`` work accordingly and force a specific type of\nexecution. Use those if really necessary.\nOtherwise, just use ``fork.map``. fork take care for you in this case again.\n\nIn order to wait for the completion of a set of result proxies, use ``fork.await_all``. If you want to\nunblock by the first unblocking result proxy, call ``fork.await_any``.\n\nThere are also blocking variants available: ``fork.block_map``, ``fork.block_map_process`` and\n``fork.block_map_thread``; in case you need some syntactic sugar:\n\n.. code:: python\n\n    fork.await_all(fork.map(create_thumbnail, images))\n    # equals\n    fork.block_map(create_thumbnail, images)\n\n\nConclusion\n----------\n\nGood\n****\n\n- easy to give it a try / easy way from sequential to parallel and back\n- results evaluate lazily\n- sequential tracebacks are preserved\n- it's thread-safe / cascading forks possible\n- compatible with Python 2 and 3\n\nBad\n***\n\n- weird calling syntax (no syntax support)\n- type(result) == ResultProxy\n- not working with lambdas due to PickleError\n- needs fix:\n\n  - not working with coroutines (asyncio_) yet (working on it)\n\n- cannot fix efficiently:\n\n  - exception handling (force evaluation when entering and leaving try blocks)\n\n- ideas are welcome :-)\n\n\n.. _FORK: https://pypi.python.org/pypi/xfork\n.. _asyncio: https://docs.python.org/3/library/asyncio.html\n",
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