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        "description": "A simple decorator to cache the results of function calls.\n\nInstallation\n------------\n\n.. code:: bash\n\n   pip install cache_em_all\n\nExample\n-------\n\n.. code:: python\n\n   from cache_em_all import Cachable\n\n   @Cachable(\"answer.json\")\n   def answer_to(question):\n       if question == \"life\":\n           import time\n           time.sleep(236500000000000)\n           return 42\n\n   answer_to(\"life\") # Takes 7.5 million years\n   answer_to(\"life\") # Pretty much instant\n\nAfter the first call to ``answer_to``, the result of the function is\nstored in a file ``cache/answer/answer__life.json``. When the function\nis called again (with the same parameters), instead of executing the\nfunction, the decorator will get the result from the file.\n\nAdvanced usage\n--------------\n\nFile types\n~~~~~~~~~~\n\nVarious file types are supported.\n\n+--------------------------------------------+--------------------------+\n| extension                                  | Description              |\n+============================================+==========================+\n| csv                                        | Uses pandas to save the  |\n|                                            | result in a csv file.    |\n|                                            | The return value for the |\n|                                            | function must be a       |\n|                                            | DataFrame or Series.     |\n+--------------------------------------------+--------------------------+\n| json                                       | Saves the result in a    |\n|                                            | json file. Useful for    |\n|                                            | lists, dictionaries and  |\n|                                            | primitive types.         |\n+--------------------------------------------+--------------------------+\n| pkl                                        | Pickles the return       |\n|                                            | value. Return type can   |\n|                                            | be just about anything.  |\n|                                            | May not work well for    |\n|                                            | large (>~2GB) files      |\n+--------------------------------------------+--------------------------+\n| pa                                         | Uses pyarrow to save     |\n|                                            | files. This is generally |\n|                                            | faster than pkl and      |\n|                                            | supports larger files    |\n|                                            | (tested up to 50GB)      |\n+--------------------------------------------+--------------------------+\n\nVersioning\n~~~~~~~~~~\n\nThe ``Cachable`` decorator can accept a version number. This is useful\nfor when you update a function. For example,\n\nYou had the following code:\n\n.. code:: python\n\n   from cache_em_all import Cachable\n\n   @Cachable(\"add.json\")\n   def add(x, y):\n       return x + x\n\nThis is a bug (should be ``x+y``, not ``x+x``), but you\u2019ve run this\nfunction multiple times and there are lots of cached results. Rather\nthan manually deleting the cache folder, you can bump the version number\n(version numbers start at 0).\n\n.. code:: python\n\n   from cache_em_all import Cachable\n\n   @Cachable(\"add.json\", version=1)\n   def add(x, y):\n       return x + y\n\nNow next time the function is called it will invalidate the cache and\nre-run the function.\n\nDo not use this feature in multi-processing code because the writes to\nthe version file do not (yet) use locks.\n\nFolder\n~~~~~~\n\nBy default all cached files are stored in a folder called ``cache``.\nThis can be changed for each function by passing ``folder`` to\n``Cachable``.\n\n.. code:: python\n\n   from cache_em_all import Cachable\n\n   @Cachable(\"add.json\", folder=\"/mnt/ram/fastcache\")\n   def add(x, y):\n       return x + y\n\nYou can also change the default cache dir so that all cache files are by\ndefault saved elsewhere.\n\n.. code:: python\n\n   from cache_em_all import Cachable, set_cache_dir\n   set_cache_dir(\"/mnt/huge_hdd\")\n\n   @Cachable(\"add.json\")\n   def add(x, y):\n       return x + y\n\nDisable cache\n~~~~~~~~~~~~~\n\nYou can also disable the cache by setting ``use`` to ``False``.\n\n.. code:: python\n\n   from cache_em_all import Cachable\n\n   @Cachable(\"add.json\", use=False)\n   def add(x, y):\n       return x + y\n\nThis can be useful for debugging or optmizing the function.",
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        "license": "LICENSE",
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