{
    "info": {
        "author": "David Eyk",
        "author_email": "deyk@crossway.org",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3.5",
            "Topic :: Database",
            "Topic :: Internet :: WWW/HTTP",
            "Topic :: Software Development :: Libraries"
        ],
        "description": "Duo: A powerful, dynamic, pythonic interface to AWS DynamoDB\n============================================================\n\n\n.. image:: https://travis-ci.org/eykd/duo.svg?branch=master\n           :target: https://travis-ci.org/eykd/duo#\n\n.. image:: https://coveralls.io/repos/github/eykd/duo/badge.svg?branch=master\n           :target: https://coveralls.io/github/eykd/duo?branch=master\n\n\n\n\n\nDuo provides a few straightforward, Pythonic abstractions for working\nwith Amazon Web Services' DynamoDB. It's a very light wrapper around\n`boto.dynamodb.layer2`, so you have full access to that excellent\nlibrary when you need it, but you don't have to sweat the details when\nyou don't.\n\nStern warning:\n--------------\n\nNo seriously, it's a very light wrapper around\n`boto.dynamodb.layer2`. If you stray much beyond the usage examples\nbelow, you'd do best to be familiar with Boto's DynamoDB API. `The\ndocs`_ are excellent. Reading `duo's source`_ may also be helpful. It's\nkept short for that reason.\n\n.. _The docs: http://boto.readthedocs.org/en/latest/ref/dynamodb.html\n.. _duo's source: https://github.com/eykd/duo/blob/master/duo.py\n\n\nUsage:\n------\n\n`duo` is made up of one module::\n\n    >>> import duo\n\nThe module isn't very big (at the time of this writing, ~700\nlines). If you want to know how something works, `you should read it`_.\n\n.. _you should read it: https://github.com/eykd/duo/blob/master/duo.py\n\nPre-create your tables in the AWS console, then write simple classes\nto access them. `duo.Table` Sub-classes are automatically registered\nwith the db::\n\n    >>> class MyHashKeyTable(duo.Table):\n    ...     table_name = 'my_hashkey_table'\n    ...     hash_key_name = 'slug'\n    ...     range_key_name = None  # Implicit default\n\n\n`duo.Item` is a thin wrapper around `boto.dynamodb.items.Item`, with\nlots of syntactic sugar. `duo.Item` sub-classs are automatically\nregistered with the db::\n\n    >>> import datetime\n\n    >>> class MyHashKeyItem(duo.Item):\n    ...     table_name = 'my_hashkey_table'\n    ...     hash_key_name = 'slug'\n    ...\n    ...     slug = duo.UnicodeField()\n    ...     my_field = duo.UnicodeField(default='foo')\n    ...     on_this_date = duo.DateField(default=lambda o: datetime.date.today())\n\n\nDatabases and Tables use dict-like access syntax::\n\n    >>> db = duo.DynamoDB(key='access_key', secret='secret_key')\n\n    >>> # The correct Table sub-class is matched by table name:\n    >>> table = duo.DynamoDB['my_hashkey_table']\n\n    >>> # The correct Item sub-class is matched by table name:\n    >>> item = table['new-item']\n\n    >>> # Items are actually dict subclasses, but that's not where the\n    >>> # fun is. They can only store unicode strings and integers:\n    >>> item['slug']\n    'new-item'\n\n\nSpecify a field on an Item sub-class to get useful data types::\n\n    >>> item.is_new\n    True\n\n    >>> # A field doesn't exist initially...\n    >>> item['my_field']\n    Traceback (most recent call last):\n      File \"...\", line 1, in <module>\n        item['my_field']\n    KeyError: 'my_field'\n\n    >>> # But we specified a default.\n    >>> item.my_field\n    'foo'\n\n    >>> # The default, once accessed, gets populated:\n    >>> item['my_field']\n    'foo'\n\n    >>> # Or we can set our own value...\n    >>> item.my_field = 'bar'\n\n    >>> item['my_field']\n    'bar'\n\n    >>> # Finally, we save it to DynamoDB.\n    >>> item.put()\n\n    >>> item.is_new\n    False\n\n\nCaching:\n--------\n\nDuo integrates with any cache that implements a `python-memcached`\\\n-compatible interface, namely, the following::\n\n    import pylibmc\n    cache = pylibmc.Client(['127.0.0.1'])\n    cache.get(<keyname>)\n    cache.set(<keyname>, <duration-in-seconds>)\n    cache.delete(<keyname>)\n\nIntegrate caching by passing the cache to the db constructor::\n\n    >>> import duo\n    >>> db = duo.DynamoDB(key='access_key', secret='secret_key', cache=cache)\n\nYou can also specify a cache object on a per-table or per-item basis::\n\n   >>> class MyHashKeyTable(duo.Table):\n    ...     cache = pylibmc.Client(['127.0.0.1'])\n    ...\n    ...     table_name = 'my_hashkey_table'\n    ...     hash_key_name = 'slug'\n    ...     range_key_name = None  # Implicit default\n\n\nCaching is turned off by default, but you can turn it on by specifying\na `cache_duration` as an integer (0 is forever)::\n\n    >>> class MyHashKeyItem(duo.Item):\n    ...     cache_duration = 30  # 30 seconds\n    ...\n    ...     table_name = 'my_hashkey_table'\n    ...     hash_key_name = 'slug'\n    ...\n    ...     slug = duo.UnicodeField()\n    ...     my_field = duo.UnicodeField(default='foo')\n    ...     on_this_date = duo.DateField(default=lambda o: datetime.date.today())\n\n\nCache keys are determined by hash key, range key, and a cache prefix\n(set on the Table). By default, the cache prefix is the table name::\n\n    >>> table = duo.DynamoDB['my_hashkey_table']\n    >>> item = table['new-item']\n    >>> item.cache_prefix is None\n    True\n    >>>item._cache_key\n    'my_hashkey_table_new-item'\n    >>> MyHashKeyTable.cache_prefix = 'hello_world'\n    >>> item._get_cache_key()\n    'hello_world_new-item'\n\n\nCHANGELOG\n---------\n\n0.3.1\n^^^^^\n\nFixed bug whereby EnumMeta and subclasses were not comparing properly (re: at all) in Python 3.\n\n0.3.0\n^^^^^\n\nAdd Python 3 compatibility.\n\n0.2.5\n^^^^^\n\nget_item() now writes to the cache, even though it doesn't read from the cache.\n\n0.2.4\n^^^^^\n\nAdded a custom get_item to Table, for specifying consistent reads,\netc. Used by __getitem__, for simpler code!\n\n0.2.3\n^^^^^\n\nOne more packaging fix, so pip won't explode. Thanks, cbrinker!\n\n\n0.2.2\n^^^^^\n\nTable.scan() and .query() should return extended Items.\n\n\n0.2.1\n^^^^^\n\nCorrections/improvements to setup.py. Packaging is HARD.\n\n\n0.2\n^^^\n\nInitial public release.\n",
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