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    "info": {
        "author": "Vipin Sharma",
        "author_email": "sh.vipin@gmail.com",
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            "License :: OSI Approved :: MIT License",
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        "description": "# Pali\n\nPali is a simple Thread Pool library for Python. It is compatible with Python3 as well as Python2.\n\nPali can be used for:\n- Creating Data Pipelines.\n- Handling requests in Messaging Brokers (on the top of TCP/IP layer).\n- Simulating any stress testing systems.\n- API Testing systems.\n\nUsage\n------------\n\nPali is simple to use. Pali's Worker Pool works on tasks with well defined interface in ```pali.task.Task```.\nNew Tasks can be extended from it as following. ```_run``` method is important and mandatory to define as the\nThread Pool internally looks and invokes this function as start of the task.\n\n```\n>>> from pali import worker, task\n>>> class MyTask(task.Task):\n...     def __init__(self, ident):\n...         self.task_id = ident\n...         self.done = False\n...\n...     def _run(self):\n...         self.done = True\n\n```\n\nThread Pool in itself can work either as context manager or can be invoked manually. Example below shows it's use\nas context manager.\n\n```\n# create 10 tasks\n>>> tasks = [MyTask(i) for i in range(10)]\n\n# Start a Thread Pool and push tasks on it.\n# Tasks are processed as and when they come.\n>>> with worker.ThreadPool(3) as tpool:\n...     _ = [tpool.append_task(t) for t in tasks]\n\n# Check the status of Tasks\n>>> status = [t.done for t in tasks]\n>>> status\n[True, True, True, True, True, True, True, True, True, True]\n```\n\nFurther examples can be found at https://github.com/gitvipin/Pali/tree/master/tests that reflect different ways os using ThreadPool.\n\n\nRequirements\n------------\nPython 2.7+ and Python 3.4+\n\nShare and enjoy!\n\n\n",
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        "name": "pali",
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