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        "author": "Carlos Ferras",
        "author_email": "c4rlos.ferra5@gmail.com",
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        "description": "## Ormuco Code Challenge\n\nThis project has been created only for demonstration purpose.\n>\n> ### The challenge\n>\n> At Ormuco, we want to optimize every bits of software we write. Your goal is to write a new library that can be integrated to the Ormuco stack. Dealing with network issues everyday, latency is our biggest problem. Thus, your challenge is to write a new Geo Distributed LRU (Least Recently Used) cache with time expiration. This library will be used extensively by many of our services so it needs to meet the following criteria:\n> 1. Simplicity. Integration needs to be dead simple.\n> 2. Resilient to network failures or crashes.\n> 3. Near real time replication of data across Geolocation. Writes need to be in real time.\n> 4. Data consistency across regions\n> 5. Locality of reference, data should almost always be available from the closest region\n> 6. Flexible Schema\n> 7. Cache can expire\u00a0\n>\n\n### The Answer\n\nsource directory: `./cache`\n\n>\n> This feature is not finished yet, but the idea to implement is:\n> 1. In each remote server create a local cache\n> 2. Each independent cache will have other 2 optional roles at the same time; as server cache and as client cache\n> 3. As server cache it will have the responsibility to synchronize all its client caches\n> 4. As client cache it will have the responsibility to notify its server cache each time a change occurs\n> 5. All this communication will be through sockets in independent threads each one\n> 6. If the connection gets broken in any point the caches networks remaining will continue working as independent networks\n> 7. If a server gets disconnected from the caches network, its cache will work locally without any problem\n> 8. The developer in charge to deploy the system will have the responsibility to decide which server is a cache server or client or both\n>\n\nusage:\n\n- Run `pip3 install cf_LRU_cache`\n\nusage for a local cache only: \n```\nfrom lru_cache.lru_cache import LRUCache\n\ndef load_callback(key):\n    \"\"\"This function has the responsibility to load the content \n       to store into the cache\n    \"\"\"\n    return key\n\nlocal_cache = LRUCache(\n    load_callback=load_callback,\n    maximum_capacity=5555,\n    expiration_time=5555\n)\n\n# get data from the cache; it will call `load_callback` if the \n# value is not available\ndata_from_cache = local_cache.get('test_key')\n\n# set data manually into the cache\ndata_from_cache = local_cache.set('test_key', 'test_value')\n\n# More options are only documented into the source code\n```\n\nusage for a distributed cache: \n```\nfrom lru_cache.lru_cache_distributed import LRUCacheDistributed\n\ndef load_callback(key):\n    \"\"\"This function has the responsibility to load the content \n       to store into the cache\n    \"\"\"\n    return key\n\nlocal_cache = LRUCacheDistributed(\n    load_callback=load_callback,\n    maximum_capacity=5555,\n    expiration_time=5555,\n    connection_timeout=5555,\n    remote_address=('192.168.1.1', '5555'),  # to be a client\n    local_address=('', '5555')  # to be a server\n)\n\n# get data from the cache; it will call `load_callback` if the \n# value is not available\ndata_from_cache = local_cache.get('test_key')\n\n# set data manually into the cache\ndata_from_cache = local_cache.set('test_key', 'test_value')\n\n# More options are only documented into the source code\n```",
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        "license": "MIT",
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        "name": "cf-LRU-cache",
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