{
    "info": {
        "author": "Tudor Aursulesei",
        "author_email": "thestick613@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "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 :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy",
            "Topic :: Utilities"
        ],
        "description": "========\nOverview\n========\n\n\n\nA distributed redis cache library, which solves the Thundering Herd problem.\n\n* Free software: BSD license\n\nInstallation\n============\n\n::\n\n    pip install thundercache\n\nDocumentation\n=============\n\nhttps://python-thundercache.readthedocs.io/\n\nDevelopment\n===========\n\nTo run the all tests run::\n\n    tox\n\nNote, to combine the coverage data from all the tox environments run:\n\n.. list-table::\n    :widths: 10 90\n    :stub-columns: 1\n\n    - - Windows\n      - ::\n\n            set PYTEST_ADDOPTS=--cov-append\n            tox\n\n    - - Other\n      - ::\n\n            PYTEST_ADDOPTS=--cov-append tox\n\nUsage\n=====\n\n.. code-block:: python\n\n  # Distributed Lock\n  from thundercache import LockFactory, retry_command\n  from redis.sentinel import Sentinel\n\n  sentinel = Sentinel()\n  redis_sentinel_master_instance = retry_command(sentinel.master_for, \"your_sentinel_service_name\", socket_timeout=20)\n\n  locks = LockFactory(expires=720, timeout=10, redis=redis_sentinel_master_instance)\n\n  with locks('my_lock'):\n      # do stuff with a distributed redis lock across different processes and networks\n      # pretty cool right!\n      pass\n\n\n  # Local Redis Cache\n  from thundercache import SmartLocalRedisCacheFactory, BaseCacheMixin)\n  import time\n\n  lcached = SmartLocalRedisCacheFactory()\n\n\n  class MyClass(BaseCacheMixin):\n\n      @lcached(\"method\", max_age=10, critical=2)\n      def method(self, n):\n      time.sleep(n)\n          return n*n\n\n  @lcached(\"somefunc', max_age=10, critical=2)\n  def somefunc(n):\n      time.sleep(n)\n      return n*n\n\n\n  mc = MyClass()\n  print mc.method(3)\n  # prints \"9\" after three seconds\n  print mc.method(3)\n  # prints \"9\" instantly\n\n  print somefunc(2)\n  # prints \"4\" after two seconds\n  print somefunc(2)\n  # prints 4\n\n\n\n  # Distributed Redis Cache\n  from thundercache import SmartRedisCacheFactory, retry_command\n  from redis.sentinel import Sentinel\n\n  sentinel = Sentinel()\n  cached = SmartRedisCacheFactory(sentinel, \"your_sentinel_service_name\")\n  # you can now use the @cached decorator in the same way you use @lcached\n\n\n\n  # Per process cache\n  from thundercache import BaseCache\n\n  class MyClass(BaseCacheMixin):\n      @BaseCache(\"mymethod\", max_age=10)\n      def mymethod(self, n):\n          time.sleep(n)\n          return n*n\n\n  @BaseCache(\"otherfunc', max_age=10)\n  def otherfunc(n):\n      time.sleep(n)\n      return n*n\n\n\n  # You can also chain these decorators\n  @BaseCache('x', 10)\n  @cached('y', 60)\n      def funct_or_method(*args,  **kwargs):\n      return None\n\n::\n\n\nChangelog\n=========\n\n0.1.2 (2017-02-23)\n-----------------------------------------\n\n* First release on PyPI.\n",
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        "keywords": "",
        "license": "BSD",
        "maintainer": "",
        "maintainer_email": "",
        "name": "thundercache",
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        "summary": "A distributed redis cache library, which solves the Thundering Herd problem.",
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