Mercurial > repos > shellac > guppy_basecaller
annotate env/lib/python3.7/site-packages/boto/dynamodb2/table.py @ 2:6af9afd405e9 draft
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| author | shellac | 
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| date | Thu, 14 May 2020 14:56:58 -0400 | 
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changeset | 1 import boto | 
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changeset | 2 from boto.dynamodb2 import exceptions | 
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changeset | 3 from boto.dynamodb2.fields import (HashKey, RangeKey, | 
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changeset | 4 AllIndex, KeysOnlyIndex, IncludeIndex, | 
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changeset | 5 GlobalAllIndex, GlobalKeysOnlyIndex, | 
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changeset | 6 GlobalIncludeIndex) | 
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changeset | 7 from boto.dynamodb2.items import Item | 
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changeset | 8 from boto.dynamodb2.layer1 import DynamoDBConnection | 
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changeset | 9 from boto.dynamodb2.results import ResultSet, BatchGetResultSet | 
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changeset | 10 from boto.dynamodb2.types import (NonBooleanDynamizer, Dynamizer, FILTER_OPERATORS, | 
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changeset | 11 QUERY_OPERATORS, STRING) | 
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changeset | 12 from boto.exception import JSONResponseError | 
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changeset | 13 | 
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changeset | 14 | 
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changeset | 15 class Table(object): | 
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changeset | 16 """ | 
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changeset | 17 Interacts & models the behavior of a DynamoDB table. | 
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changeset | 18 | 
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changeset | 19 The ``Table`` object represents a set (or rough categorization) of | 
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changeset | 20 records within DynamoDB. The important part is that all records within the | 
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changeset | 21 table, while largely-schema-free, share the same schema & are essentially | 
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changeset | 22 namespaced for use in your application. For example, you might have a | 
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changeset | 23 ``users`` table or a ``forums`` table. | 
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changeset | 24 """ | 
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changeset | 25 max_batch_get = 100 | 
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changeset | 26 | 
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changeset | 27 _PROJECTION_TYPE_TO_INDEX = dict( | 
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changeset | 28 global_indexes=dict( | 
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changeset | 29 ALL=GlobalAllIndex, | 
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changeset | 30 KEYS_ONLY=GlobalKeysOnlyIndex, | 
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changeset | 31 INCLUDE=GlobalIncludeIndex, | 
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changeset | 32 ), local_indexes=dict( | 
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changeset | 33 ALL=AllIndex, | 
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changeset | 34 KEYS_ONLY=KeysOnlyIndex, | 
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changeset | 35 INCLUDE=IncludeIndex, | 
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changeset | 36 ) | 
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changeset | 37 ) | 
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changeset | 38 | 
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changeset | 39 def __init__(self, table_name, schema=None, throughput=None, indexes=None, | 
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changeset | 40 global_indexes=None, connection=None): | 
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changeset | 41 """ | 
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changeset | 42 Sets up a new in-memory ``Table``. | 
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changeset | 43 | 
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changeset | 44 This is useful if the table already exists within DynamoDB & you simply | 
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changeset | 45 want to use it for additional interactions. The only required parameter | 
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changeset | 46 is the ``table_name``. However, under the hood, the object will call | 
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changeset | 47 ``describe_table`` to determine the schema/indexes/throughput. You | 
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changeset | 48 can avoid this extra call by passing in ``schema`` & ``indexes``. | 
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changeset | 49 | 
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changeset | 50 **IMPORTANT** - If you're creating a new ``Table`` for the first time, | 
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changeset | 51 you should use the ``Table.create`` method instead, as it will | 
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changeset | 52 persist the table structure to DynamoDB. | 
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changeset | 53 | 
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changeset | 54 Requires a ``table_name`` parameter, which should be a simple string | 
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changeset | 55 of the name of the table. | 
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changeset | 56 | 
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changeset | 57 Optionally accepts a ``schema`` parameter, which should be a list of | 
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changeset | 58 ``BaseSchemaField`` subclasses representing the desired schema. | 
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changeset | 59 | 
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changeset | 60 Optionally accepts a ``throughput`` parameter, which should be a | 
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changeset | 61 dictionary. If provided, it should specify a ``read`` & ``write`` key, | 
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changeset | 62 both of which should have an integer value associated with them. | 
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changeset | 63 | 
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changeset | 64 Optionally accepts a ``indexes`` parameter, which should be a list of | 
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changeset | 65 ``BaseIndexField`` subclasses representing the desired indexes. | 
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changeset | 66 | 
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changeset | 67 Optionally accepts a ``global_indexes`` parameter, which should be a | 
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changeset | 68 list of ``GlobalBaseIndexField`` subclasses representing the desired | 
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changeset | 69 indexes. | 
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changeset | 70 | 
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changeset | 71 Optionally accepts a ``connection`` parameter, which should be a | 
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changeset | 72 ``DynamoDBConnection`` instance (or subclass). This is primarily useful | 
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changeset | 73 for specifying alternate connection parameters. | 
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changeset | 74 | 
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changeset | 75 Example:: | 
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changeset | 76 | 
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changeset | 77 # The simple, it-already-exists case. | 
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changeset | 78 >>> conn = Table('users') | 
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changeset | 79 | 
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changeset | 80 # The full, minimum-extra-calls case. | 
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changeset | 81 >>> from boto import dynamodb2 | 
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changeset | 82 >>> users = Table('users', schema=[ | 
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changeset | 83 ... HashKey('username'), | 
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changeset | 84 ... RangeKey('date_joined', data_type=NUMBER) | 
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changeset | 85 ... ], throughput={ | 
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changeset | 86 ... 'read':20, | 
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changeset | 87 ... 'write': 10, | 
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changeset | 88 ... }, indexes=[ | 
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changeset | 89 ... KeysOnlyIndex('MostRecentlyJoined', parts=[ | 
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changeset | 90 ... HashKey('username') | 
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changeset | 91 ... RangeKey('date_joined') | 
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changeset | 92 ... ]), | 
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changeset | 93 ... ], global_indexes=[ | 
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changeset | 94 ... GlobalAllIndex('UsersByZipcode', parts=[ | 
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changeset | 95 ... HashKey('zipcode'), | 
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changeset | 96 ... RangeKey('username'), | 
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changeset | 97 ... ], | 
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changeset | 98 ... throughput={ | 
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changeset | 99 ... 'read':10, | 
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changeset | 100 ... 'write':10, | 
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changeset | 101 ... }), | 
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changeset | 102 ... ], connection=dynamodb2.connect_to_region('us-west-2', | 
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changeset | 103 ... aws_access_key_id='key', | 
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changeset | 104 ... aws_secret_access_key='key', | 
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changeset | 105 ... )) | 
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changeset | 106 | 
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changeset | 107 """ | 
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changeset | 108 self.table_name = table_name | 
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changeset | 109 self.connection = connection | 
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changeset | 110 self.throughput = { | 
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changeset | 111 'read': 5, | 
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changeset | 112 'write': 5, | 
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changeset | 113 } | 
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changeset | 114 self.schema = schema | 
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changeset | 115 self.indexes = indexes | 
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changeset | 116 self.global_indexes = global_indexes | 
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changeset | 117 | 
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changeset | 118 if self.connection is None: | 
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changeset | 119 self.connection = DynamoDBConnection() | 
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changeset | 120 | 
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changeset | 121 if throughput is not None: | 
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changeset | 122 self.throughput = throughput | 
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changeset | 123 | 
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changeset | 124 self._dynamizer = NonBooleanDynamizer() | 
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changeset | 125 | 
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changeset | 126 def use_boolean(self): | 
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changeset | 127 self._dynamizer = Dynamizer() | 
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changeset | 128 | 
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changeset | 129 @classmethod | 
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changeset | 130 def create(cls, table_name, schema, throughput=None, indexes=None, | 
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changeset | 131 global_indexes=None, connection=None): | 
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changeset | 132 """ | 
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changeset | 133 Creates a new table in DynamoDB & returns an in-memory ``Table`` object. | 
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changeset | 134 | 
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changeset | 135 This will setup a brand new table within DynamoDB. The ``table_name`` | 
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changeset | 136 must be unique for your AWS account. The ``schema`` is also required | 
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changeset | 137 to define the key structure of the table. | 
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changeset | 138 | 
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changeset | 139 **IMPORTANT** - You should consider the usage pattern of your table | 
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changeset | 140 up-front, as the schema can **NOT** be modified once the table is | 
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changeset | 141 created, requiring the creation of a new table & migrating the data | 
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changeset | 142 should you wish to revise it. | 
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changeset | 143 | 
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changeset | 144 **IMPORTANT** - If the table already exists in DynamoDB, additional | 
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changeset | 145 calls to this method will result in an error. If you just need | 
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changeset | 146 a ``Table`` object to interact with the existing table, you should | 
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changeset | 147 just initialize a new ``Table`` object, which requires only the | 
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changeset | 148 ``table_name``. | 
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changeset | 149 | 
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changeset | 150 Requires a ``table_name`` parameter, which should be a simple string | 
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changeset | 151 of the name of the table. | 
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changeset | 152 | 
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changeset | 153 Requires a ``schema`` parameter, which should be a list of | 
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changeset | 154 ``BaseSchemaField`` subclasses representing the desired schema. | 
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changeset | 155 | 
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changeset | 156 Optionally accepts a ``throughput`` parameter, which should be a | 
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changeset | 157 dictionary. If provided, it should specify a ``read`` & ``write`` key, | 
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changeset | 158 both of which should have an integer value associated with them. | 
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changeset | 159 | 
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changeset | 160 Optionally accepts a ``indexes`` parameter, which should be a list of | 
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changeset | 161 ``BaseIndexField`` subclasses representing the desired indexes. | 
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changeset | 162 | 
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changeset | 163 Optionally accepts a ``global_indexes`` parameter, which should be a | 
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changeset | 164 list of ``GlobalBaseIndexField`` subclasses representing the desired | 
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changeset | 165 indexes. | 
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changeset | 166 | 
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changeset | 167 Optionally accepts a ``connection`` parameter, which should be a | 
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changeset | 168 ``DynamoDBConnection`` instance (or subclass). This is primarily useful | 
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changeset | 169 for specifying alternate connection parameters. | 
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changeset | 170 | 
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changeset | 171 Example:: | 
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changeset | 172 | 
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changeset | 173 >>> users = Table.create('users', schema=[ | 
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changeset | 174 ... HashKey('username'), | 
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changeset | 175 ... RangeKey('date_joined', data_type=NUMBER) | 
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changeset | 176 ... ], throughput={ | 
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changeset | 177 ... 'read':20, | 
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changeset | 178 ... 'write': 10, | 
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changeset | 179 ... }, indexes=[ | 
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changeset | 180 ... KeysOnlyIndex('MostRecentlyJoined', parts=[ | 
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changeset | 181 ... HashKey('username'), | 
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changeset | 182 ... RangeKey('date_joined'), | 
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changeset | 183 ... ]), global_indexes=[ | 
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changeset | 184 ... GlobalAllIndex('UsersByZipcode', parts=[ | 
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changeset | 185 ... HashKey('zipcode'), | 
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changeset | 186 ... RangeKey('username'), | 
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changeset | 187 ... ], | 
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changeset | 188 ... throughput={ | 
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changeset | 189 ... 'read':10, | 
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changeset | 190 ... 'write':10, | 
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changeset | 191 ... }), | 
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changeset | 192 ... ]) | 
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changeset | 193 | 
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changeset | 194 """ | 
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changeset | 195 table = cls(table_name=table_name, connection=connection) | 
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changeset | 196 table.schema = schema | 
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changeset | 197 | 
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changeset | 198 if throughput is not None: | 
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changeset | 199 table.throughput = throughput | 
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changeset | 200 | 
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changeset | 201 if indexes is not None: | 
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changeset | 202 table.indexes = indexes | 
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changeset | 203 | 
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changeset | 204 if global_indexes is not None: | 
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changeset | 205 table.global_indexes = global_indexes | 
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changeset | 206 | 
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changeset | 207 # Prep the schema. | 
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changeset | 208 raw_schema = [] | 
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changeset | 209 attr_defs = [] | 
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changeset | 210 seen_attrs = set() | 
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changeset | 211 | 
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changeset | 212 for field in table.schema: | 
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changeset | 213 raw_schema.append(field.schema()) | 
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changeset | 214 # Build the attributes off what we know. | 
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changeset | 215 seen_attrs.add(field.name) | 
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changeset | 216 attr_defs.append(field.definition()) | 
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changeset | 217 | 
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changeset | 218 raw_throughput = { | 
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changeset | 219 'ReadCapacityUnits': int(table.throughput['read']), | 
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changeset | 220 'WriteCapacityUnits': int(table.throughput['write']), | 
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changeset | 221 } | 
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changeset | 222 kwargs = {} | 
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changeset | 223 | 
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changeset | 224 kwarg_map = { | 
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changeset | 225 'indexes': 'local_secondary_indexes', | 
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changeset | 226 'global_indexes': 'global_secondary_indexes', | 
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changeset | 227 } | 
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changeset | 228 for index_attr in ('indexes', 'global_indexes'): | 
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changeset | 229 table_indexes = getattr(table, index_attr) | 
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changeset | 230 if table_indexes: | 
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changeset | 231 raw_indexes = [] | 
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changeset | 232 for index_field in table_indexes: | 
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changeset | 233 raw_indexes.append(index_field.schema()) | 
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changeset | 234 # Make sure all attributes specified in the indexes are | 
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changeset | 235 # added to the definition | 
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changeset | 236 for field in index_field.parts: | 
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changeset | 237 if field.name not in seen_attrs: | 
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changeset | 238 seen_attrs.add(field.name) | 
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changeset | 239 attr_defs.append(field.definition()) | 
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changeset | 240 | 
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changeset | 241 kwargs[kwarg_map[index_attr]] = raw_indexes | 
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changeset | 242 | 
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changeset | 243 table.connection.create_table( | 
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changeset | 244 table_name=table.table_name, | 
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changeset | 245 attribute_definitions=attr_defs, | 
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changeset | 246 key_schema=raw_schema, | 
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changeset | 247 provisioned_throughput=raw_throughput, | 
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changeset | 248 **kwargs | 
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changeset | 249 ) | 
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changeset | 250 return table | 
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changeset | 251 | 
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changeset | 252 def _introspect_schema(self, raw_schema, raw_attributes=None): | 
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changeset | 253 """ | 
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changeset | 254 Given a raw schema structure back from a DynamoDB response, parse | 
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changeset | 255 out & build the high-level Python objects that represent them. | 
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changeset | 256 """ | 
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changeset | 257 schema = [] | 
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changeset | 258 sane_attributes = {} | 
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changeset | 259 | 
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changeset | 260 if raw_attributes: | 
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changeset | 261 for field in raw_attributes: | 
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changeset | 262 sane_attributes[field['AttributeName']] = field['AttributeType'] | 
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changeset | 263 | 
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changeset | 264 for field in raw_schema: | 
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changeset | 265 data_type = sane_attributes.get(field['AttributeName'], STRING) | 
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changeset | 266 | 
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changeset | 267 if field['KeyType'] == 'HASH': | 
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changeset | 268 schema.append( | 
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changeset | 269 HashKey(field['AttributeName'], data_type=data_type) | 
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changeset | 270 ) | 
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changeset | 271 elif field['KeyType'] == 'RANGE': | 
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changeset | 272 schema.append( | 
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changeset | 273 RangeKey(field['AttributeName'], data_type=data_type) | 
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changeset | 274 ) | 
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changeset | 275 else: | 
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changeset | 276 raise exceptions.UnknownSchemaFieldError( | 
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changeset | 277 "%s was seen, but is unknown. Please report this at " | 
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changeset | 278 "https://github.com/boto/boto/issues." % field['KeyType'] | 
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changeset | 279 ) | 
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changeset | 280 | 
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changeset | 281 return schema | 
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changeset | 282 | 
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changeset | 283 def _introspect_all_indexes(self, raw_indexes, map_indexes_projection): | 
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changeset | 284 """ | 
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changeset | 285 Given a raw index/global index structure back from a DynamoDB response, | 
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changeset | 286 parse out & build the high-level Python objects that represent them. | 
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changeset | 287 """ | 
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changeset | 288 indexes = [] | 
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changeset | 289 | 
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changeset | 290 for field in raw_indexes: | 
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changeset | 291 index_klass = map_indexes_projection.get('ALL') | 
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changeset | 292 kwargs = { | 
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changeset | 293 'parts': [] | 
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changeset | 294 } | 
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changeset | 295 | 
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changeset | 296 if field['Projection']['ProjectionType'] == 'ALL': | 
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changeset | 297 index_klass = map_indexes_projection.get('ALL') | 
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changeset | 298 elif field['Projection']['ProjectionType'] == 'KEYS_ONLY': | 
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changeset | 299 index_klass = map_indexes_projection.get('KEYS_ONLY') | 
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changeset | 300 elif field['Projection']['ProjectionType'] == 'INCLUDE': | 
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changeset | 301 index_klass = map_indexes_projection.get('INCLUDE') | 
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changeset | 302 kwargs['includes'] = field['Projection']['NonKeyAttributes'] | 
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changeset | 303 else: | 
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changeset | 304 raise exceptions.UnknownIndexFieldError( | 
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changeset | 305 "%s was seen, but is unknown. Please report this at " | 
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changeset | 306 "https://github.com/boto/boto/issues." % \ | 
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changeset | 307 field['Projection']['ProjectionType'] | 
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changeset | 308 ) | 
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changeset | 309 | 
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changeset | 310 name = field['IndexName'] | 
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changeset | 311 kwargs['parts'] = self._introspect_schema(field['KeySchema'], None) | 
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changeset | 312 indexes.append(index_klass(name, **kwargs)) | 
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changeset | 313 | 
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changeset | 314 return indexes | 
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changeset | 315 | 
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changeset | 316 def _introspect_indexes(self, raw_indexes): | 
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changeset | 317 """ | 
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changeset | 318 Given a raw index structure back from a DynamoDB response, parse | 
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changeset | 319 out & build the high-level Python objects that represent them. | 
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changeset | 320 """ | 
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changeset | 321 return self._introspect_all_indexes( | 
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changeset | 322 raw_indexes, self._PROJECTION_TYPE_TO_INDEX.get('local_indexes')) | 
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changeset | 323 | 
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changeset | 324 def _introspect_global_indexes(self, raw_global_indexes): | 
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changeset | 325 """ | 
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changeset | 326 Given a raw global index structure back from a DynamoDB response, parse | 
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changeset | 327 out & build the high-level Python objects that represent them. | 
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changeset | 328 """ | 
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changeset | 329 return self._introspect_all_indexes( | 
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changeset | 330 raw_global_indexes, | 
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changeset | 331 self._PROJECTION_TYPE_TO_INDEX.get('global_indexes')) | 
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changeset | 332 | 
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changeset | 333 def describe(self): | 
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changeset | 334 """ | 
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changeset | 335 Describes the current structure of the table in DynamoDB. | 
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changeset | 336 | 
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changeset | 337 This information will be used to update the ``schema``, ``indexes``, | 
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changeset | 338 ``global_indexes`` and ``throughput`` information on the ``Table``. Some | 
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changeset | 339 calls, such as those involving creating keys or querying, will require | 
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changeset | 340 this information to be populated. | 
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changeset | 341 | 
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changeset | 342 It also returns the full raw data structure from DynamoDB, in the | 
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changeset | 343 event you'd like to parse out additional information (such as the | 
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changeset | 344 ``ItemCount`` or usage information). | 
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changeset | 345 | 
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changeset | 346 Example:: | 
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changeset | 347 | 
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changeset | 348 >>> users.describe() | 
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changeset | 349 { | 
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changeset | 350 # Lots of keys here... | 
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changeset | 351 } | 
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changeset | 352 >>> len(users.schema) | 
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changeset | 353 2 | 
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changeset | 354 | 
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changeset | 355 """ | 
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changeset | 356 result = self.connection.describe_table(self.table_name) | 
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changeset | 357 | 
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changeset | 358 # Blindly update throughput, since what's on DynamoDB's end is likely | 
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changeset | 359 # more correct. | 
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changeset | 360 raw_throughput = result['Table']['ProvisionedThroughput'] | 
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changeset | 361 self.throughput['read'] = int(raw_throughput['ReadCapacityUnits']) | 
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changeset | 362 self.throughput['write'] = int(raw_throughput['WriteCapacityUnits']) | 
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changeset | 363 | 
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changeset | 364 if not self.schema: | 
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changeset | 365 # Since we have the data, build the schema. | 
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changeset | 366 raw_schema = result['Table'].get('KeySchema', []) | 
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changeset | 367 raw_attributes = result['Table'].get('AttributeDefinitions', []) | 
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changeset | 368 self.schema = self._introspect_schema(raw_schema, raw_attributes) | 
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changeset | 369 | 
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changeset | 370 if not self.indexes: | 
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changeset | 371 # Build the index information as well. | 
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changeset | 372 raw_indexes = result['Table'].get('LocalSecondaryIndexes', []) | 
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changeset | 373 self.indexes = self._introspect_indexes(raw_indexes) | 
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changeset | 374 | 
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changeset | 375 # Build the global index information as well. | 
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changeset | 376 raw_global_indexes = result['Table'].get('GlobalSecondaryIndexes', []) | 
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changeset | 377 self.global_indexes = self._introspect_global_indexes(raw_global_indexes) | 
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changeset | 378 | 
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changeset | 379 # This is leaky. | 
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changeset | 380 return result | 
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changeset | 381 | 
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changeset | 382 def update(self, throughput=None, global_indexes=None): | 
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changeset | 383 """ | 
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changeset | 384 Updates table attributes and global indexes in DynamoDB. | 
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changeset | 385 | 
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changeset | 386 Optionally accepts a ``throughput`` parameter, which should be a | 
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changeset | 387 dictionary. If provided, it should specify a ``read`` & ``write`` key, | 
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changeset | 388 both of which should have an integer value associated with them. | 
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changeset | 389 | 
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changeset | 390 Optionally accepts a ``global_indexes`` parameter, which should be a | 
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changeset | 391 dictionary. If provided, it should specify the index name, which is also | 
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changeset | 392 a dict containing a ``read`` & ``write`` key, both of which | 
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changeset | 393 should have an integer value associated with them. If you are writing | 
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changeset | 394 new code, please use ``Table.update_global_secondary_index``. | 
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changeset | 395 | 
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changeset | 396 Returns ``True`` on success. | 
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changeset | 397 | 
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changeset | 398 Example:: | 
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changeset | 399 | 
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changeset | 400 # For a read-heavier application... | 
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changeset | 401 >>> users.update(throughput={ | 
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changeset | 402 ... 'read': 20, | 
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changeset | 403 ... 'write': 10, | 
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changeset | 404 ... }) | 
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changeset | 405 True | 
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changeset | 406 | 
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changeset | 407 # To also update the global index(es) throughput. | 
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changeset | 408 >>> users.update(throughput={ | 
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changeset | 409 ... 'read': 20, | 
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changeset | 410 ... 'write': 10, | 
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changeset | 411 ... }, | 
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changeset | 412 ... global_secondary_indexes={ | 
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changeset | 413 ... 'TheIndexNameHere': { | 
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changeset | 414 ... 'read': 15, | 
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changeset | 415 ... 'write': 5, | 
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changeset | 416 ... } | 
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changeset | 417 ... }) | 
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changeset | 418 True | 
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changeset | 419 """ | 
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changeset | 420 | 
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changeset | 421 data = None | 
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changeset | 422 | 
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changeset | 423 if throughput: | 
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changeset | 424 self.throughput = throughput | 
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changeset | 425 data = { | 
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changeset | 426 'ReadCapacityUnits': int(self.throughput['read']), | 
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changeset | 427 'WriteCapacityUnits': int(self.throughput['write']), | 
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changeset | 428 } | 
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changeset | 429 | 
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changeset | 430 gsi_data = None | 
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changeset | 431 | 
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changeset | 432 if global_indexes: | 
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changeset | 433 gsi_data = [] | 
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changeset | 434 | 
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changeset | 435 for gsi_name, gsi_throughput in global_indexes.items(): | 
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changeset | 436 gsi_data.append({ | 
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changeset | 437 "Update": { | 
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changeset | 438 "IndexName": gsi_name, | 
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changeset | 439 "ProvisionedThroughput": { | 
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changeset | 440 "ReadCapacityUnits": int(gsi_throughput['read']), | 
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changeset | 441 "WriteCapacityUnits": int(gsi_throughput['write']), | 
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changeset | 442 }, | 
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changeset | 443 }, | 
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changeset | 444 }) | 
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changeset | 445 | 
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changeset | 446 if throughput or global_indexes: | 
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changeset | 447 self.connection.update_table( | 
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changeset | 448 self.table_name, | 
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changeset | 449 provisioned_throughput=data, | 
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changeset | 450 global_secondary_index_updates=gsi_data, | 
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changeset | 451 ) | 
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changeset | 452 | 
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changeset | 453 return True | 
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changeset | 454 else: | 
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changeset | 455 msg = 'You need to provide either the throughput or the ' \ | 
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changeset | 456 'global_indexes to update method' | 
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changeset | 457 boto.log.error(msg) | 
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changeset | 458 | 
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changeset | 459 return False | 
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changeset | 460 | 
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changeset | 461 def create_global_secondary_index(self, global_index): | 
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changeset | 462 """ | 
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changeset | 463 Creates a global index in DynamoDB after the table has been created. | 
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changeset | 464 | 
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changeset | 465 Requires a ``global_indexes`` parameter, which should be a | 
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changeset | 466 ``GlobalBaseIndexField`` subclass representing the desired index. | 
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changeset | 467 | 
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changeset | 468 To update ``global_indexes`` information on the ``Table``, you'll need | 
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changeset | 469 to call ``Table.describe``. | 
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changeset | 470 | 
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changeset | 471 Returns ``True`` on success. | 
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changeset | 472 | 
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changeset | 473 Example:: | 
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changeset | 474 | 
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changeset | 475 # To create a global index | 
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changeset | 476 >>> users.create_global_secondary_index( | 
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changeset | 477 ... global_index=GlobalAllIndex( | 
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changeset | 478 ... 'TheIndexNameHere', parts=[ | 
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changeset | 479 ... HashKey('requiredHashkey', data_type=STRING), | 
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changeset | 480 ... RangeKey('optionalRangeKey', data_type=STRING) | 
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changeset | 481 ... ], | 
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changeset | 482 ... throughput={ | 
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changeset | 483 ... 'read': 2, | 
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changeset | 484 ... 'write': 1, | 
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changeset | 485 ... }) | 
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changeset | 486 ... ) | 
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changeset | 487 True | 
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changeset | 488 | 
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changeset | 489 """ | 
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changeset | 490 | 
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changeset | 491 if global_index: | 
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changeset | 492 gsi_data = [] | 
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changeset | 493 gsi_data_attr_def = [] | 
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changeset | 494 | 
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changeset | 495 gsi_data.append({ | 
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changeset | 496 "Create": global_index.schema() | 
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changeset | 497 }) | 
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changeset | 498 | 
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changeset | 499 for attr_def in global_index.parts: | 
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changeset | 500 gsi_data_attr_def.append(attr_def.definition()) | 
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changeset | 501 | 
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changeset | 502 self.connection.update_table( | 
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changeset | 503 self.table_name, | 
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changeset | 504 global_secondary_index_updates=gsi_data, | 
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changeset | 505 attribute_definitions=gsi_data_attr_def | 
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changeset | 506 ) | 
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changeset | 507 | 
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changeset | 508 return True | 
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changeset | 509 else: | 
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changeset | 510 msg = 'You need to provide the global_index to ' \ | 
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changeset | 511 'create_global_secondary_index method' | 
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changeset | 512 boto.log.error(msg) | 
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changeset | 513 | 
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changeset | 514 return False | 
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changeset | 515 | 
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changeset | 516 def delete_global_secondary_index(self, global_index_name): | 
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changeset | 517 """ | 
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changeset | 518 Deletes a global index in DynamoDB after the table has been created. | 
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changeset | 519 | 
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changeset | 520 Requires a ``global_index_name`` parameter, which should be a simple | 
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changeset | 521 string of the name of the global secondary index. | 
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changeset | 522 | 
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changeset | 523 To update ``global_indexes`` information on the ``Table``, you'll need | 
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changeset | 524 to call ``Table.describe``. | 
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changeset | 525 | 
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changeset | 526 Returns ``True`` on success. | 
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changeset | 527 | 
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changeset | 528 Example:: | 
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changeset | 529 | 
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changeset | 530 # To delete a global index | 
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changeset | 531 >>> users.delete_global_secondary_index('TheIndexNameHere') | 
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changeset | 532 True | 
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changeset | 533 | 
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changeset | 534 """ | 
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changeset | 535 | 
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changeset | 536 if global_index_name: | 
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changeset | 537 gsi_data = [ | 
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changeset | 538 { | 
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changeset | 539 "Delete": { | 
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changeset | 540 "IndexName": global_index_name | 
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changeset | 541 } | 
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changeset | 542 } | 
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changeset | 543 ] | 
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changeset | 544 | 
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changeset | 545 self.connection.update_table( | 
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changeset | 546 self.table_name, | 
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changeset | 547 global_secondary_index_updates=gsi_data, | 
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changeset | 548 ) | 
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changeset | 549 | 
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changeset | 550 return True | 
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changeset | 551 else: | 
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changeset | 552 msg = 'You need to provide the global index name to ' \ | 
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changeset | 553 'delete_global_secondary_index method' | 
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changeset | 554 boto.log.error(msg) | 
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changeset | 555 | 
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changeset | 556 return False | 
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changeset | 557 | 
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changeset | 558 def update_global_secondary_index(self, global_indexes): | 
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changeset | 559 """ | 
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changeset | 560 Updates a global index(es) in DynamoDB after the table has been created. | 
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changeset | 561 | 
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changeset | 562 Requires a ``global_indexes`` parameter, which should be a | 
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changeset | 563 dictionary. If provided, it should specify the index name, which is also | 
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changeset | 564 a dict containing a ``read`` & ``write`` key, both of which | 
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changeset | 565 should have an integer value associated with them. | 
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changeset | 566 | 
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changeset | 567 To update ``global_indexes`` information on the ``Table``, you'll need | 
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changeset | 568 to call ``Table.describe``. | 
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changeset | 569 | 
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changeset | 570 Returns ``True`` on success. | 
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changeset | 571 | 
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changeset | 572 Example:: | 
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changeset | 573 | 
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changeset | 574 # To update a global index | 
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changeset | 575 >>> users.update_global_secondary_index(global_indexes={ | 
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changeset | 576 ... 'TheIndexNameHere': { | 
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changeset | 577 ... 'read': 15, | 
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changeset | 578 ... 'write': 5, | 
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changeset | 579 ... } | 
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changeset | 580 ... }) | 
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changeset | 581 True | 
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changeset | 582 | 
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changeset | 583 """ | 
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changeset | 584 | 
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changeset | 585 if global_indexes: | 
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changeset | 586 gsi_data = [] | 
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changeset | 587 | 
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changeset | 588 for gsi_name, gsi_throughput in global_indexes.items(): | 
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changeset | 589 gsi_data.append({ | 
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changeset | 590 "Update": { | 
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changeset | 591 "IndexName": gsi_name, | 
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changeset | 592 "ProvisionedThroughput": { | 
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changeset | 593 "ReadCapacityUnits": int(gsi_throughput['read']), | 
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changeset | 594 "WriteCapacityUnits": int(gsi_throughput['write']), | 
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changeset | 595 }, | 
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changeset | 596 }, | 
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changeset | 597 }) | 
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changeset | 598 | 
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changeset | 599 self.connection.update_table( | 
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changeset | 600 self.table_name, | 
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changeset | 601 global_secondary_index_updates=gsi_data, | 
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changeset | 602 ) | 
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changeset | 603 return True | 
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changeset | 604 else: | 
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changeset | 605 msg = 'You need to provide the global indexes to ' \ | 
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changeset | 606 'update_global_secondary_index method' | 
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changeset | 607 boto.log.error(msg) | 
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changeset | 608 | 
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changeset | 609 return False | 
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changeset | 610 | 
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changeset | 611 def delete(self): | 
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changeset | 612 """ | 
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changeset | 613 Deletes a table in DynamoDB. | 
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changeset | 614 | 
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changeset | 615 **IMPORTANT** - Be careful when using this method, there is no undo. | 
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changeset | 616 | 
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changeset | 617 Returns ``True`` on success. | 
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changeset | 618 | 
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changeset | 619 Example:: | 
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changeset | 620 | 
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changeset | 621 >>> users.delete() | 
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changeset | 622 True | 
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changeset | 623 | 
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changeset | 624 """ | 
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changeset | 625 self.connection.delete_table(self.table_name) | 
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changeset | 626 return True | 
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changeset | 627 | 
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changeset | 628 def _encode_keys(self, keys): | 
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changeset | 629 """ | 
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changeset | 630 Given a flat Python dictionary of keys/values, converts it into the | 
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changeset | 631 nested dictionary DynamoDB expects. | 
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changeset | 632 | 
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changeset | 633 Converts:: | 
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changeset | 634 | 
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changeset | 635 { | 
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changeset | 636 'username': 'john', | 
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changeset | 637 'tags': [1, 2, 5], | 
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changeset | 638 } | 
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changeset | 639 | 
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changeset | 640 ...to...:: | 
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changeset | 641 | 
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changeset | 642 { | 
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changeset | 643 'username': {'S': 'john'}, | 
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changeset | 644 'tags': {'NS': ['1', '2', '5']}, | 
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changeset | 645 } | 
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changeset | 646 | 
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changeset | 647 """ | 
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changeset | 648 raw_key = {} | 
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changeset | 649 | 
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changeset | 650 for key, value in keys.items(): | 
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changeset | 651 raw_key[key] = self._dynamizer.encode(value) | 
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changeset | 652 | 
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changeset | 653 return raw_key | 
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changeset | 654 | 
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changeset | 655 def get_item(self, consistent=False, attributes=None, **kwargs): | 
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changeset | 656 """ | 
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changeset | 657 Fetches an item (record) from a table in DynamoDB. | 
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changeset | 658 | 
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changeset | 659 To specify the key of the item you'd like to get, you can specify the | 
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changeset | 660 key attributes as kwargs. | 
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changeset | 661 | 
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changeset | 662 Optionally accepts a ``consistent`` parameter, which should be a | 
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changeset | 663 boolean. If you provide ``True``, it will perform | 
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changeset | 664 a consistent (but more expensive) read from DynamoDB. | 
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changeset | 665 (Default: ``False``) | 
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changeset | 666 | 
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changeset | 667 Optionally accepts an ``attributes`` parameter, which should be a | 
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changeset | 668 list of fieldname to fetch. (Default: ``None``, which means all fields | 
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changeset | 669 should be fetched) | 
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changeset | 670 | 
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changeset | 671 Returns an ``Item`` instance containing all the data for that record. | 
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changeset | 672 | 
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changeset | 673 Raises an ``ItemNotFound`` exception if the item is not found. | 
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changeset | 674 | 
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changeset | 675 Example:: | 
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changeset | 676 | 
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changeset | 677 # A simple hash key. | 
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changeset | 678 >>> john = users.get_item(username='johndoe') | 
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changeset | 679 >>> john['first_name'] | 
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changeset | 680 'John' | 
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changeset | 681 | 
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changeset | 682 # A complex hash+range key. | 
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changeset | 683 >>> john = users.get_item(username='johndoe', last_name='Doe') | 
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changeset | 684 >>> john['first_name'] | 
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changeset | 685 'John' | 
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changeset | 686 | 
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changeset | 687 # A consistent read (assuming the data might have just changed). | 
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changeset | 688 >>> john = users.get_item(username='johndoe', consistent=True) | 
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changeset | 689 >>> john['first_name'] | 
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changeset | 690 'Johann' | 
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changeset | 691 | 
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changeset | 692 # With a key that is an invalid variable name in Python. | 
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changeset | 693 # Also, assumes a different schema than previous examples. | 
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changeset | 694 >>> john = users.get_item(**{ | 
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changeset | 695 ... 'date-joined': 127549192, | 
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changeset | 696 ... }) | 
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changeset | 697 >>> john['first_name'] | 
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changeset | 698 'John' | 
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changeset | 699 | 
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changeset | 700 """ | 
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changeset | 701 raw_key = self._encode_keys(kwargs) | 
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changeset | 702 item_data = self.connection.get_item( | 
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changeset | 703 self.table_name, | 
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changeset | 704 raw_key, | 
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changeset | 705 attributes_to_get=attributes, | 
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changeset | 706 consistent_read=consistent | 
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changeset | 707 ) | 
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changeset | 708 if 'Item' not in item_data: | 
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changeset | 709 raise exceptions.ItemNotFound("Item %s couldn't be found." % kwargs) | 
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changeset | 710 item = Item(self) | 
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changeset | 711 item.load(item_data) | 
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changeset | 712 return item | 
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changeset | 713 | 
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changeset | 714 def has_item(self, **kwargs): | 
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changeset | 715 """ | 
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changeset | 716 Return whether an item (record) exists within a table in DynamoDB. | 
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changeset | 717 | 
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changeset | 718 To specify the key of the item you'd like to get, you can specify the | 
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changeset | 719 key attributes as kwargs. | 
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changeset | 720 | 
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changeset | 721 Optionally accepts a ``consistent`` parameter, which should be a | 
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changeset | 722 boolean. If you provide ``True``, it will perform | 
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changeset | 723 a consistent (but more expensive) read from DynamoDB. | 
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changeset | 724 (Default: ``False``) | 
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changeset | 725 | 
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changeset | 726 Optionally accepts an ``attributes`` parameter, which should be a | 
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changeset | 727 list of fieldnames to fetch. (Default: ``None``, which means all fields | 
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changeset | 728 should be fetched) | 
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changeset | 729 | 
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changeset | 730 Returns ``True`` if an ``Item`` is present, ``False`` if not. | 
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changeset | 731 | 
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changeset | 732 Example:: | 
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changeset | 733 | 
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changeset | 734 # Simple, just hash-key schema. | 
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changeset | 735 >>> users.has_item(username='johndoe') | 
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changeset | 736 True | 
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changeset | 737 | 
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changeset | 738 # Complex schema, item not present. | 
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changeset | 739 >>> users.has_item( | 
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changeset | 740 ... username='johndoe', | 
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changeset | 741 ... date_joined='2014-01-07' | 
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changeset | 742 ... ) | 
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changeset | 743 False | 
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changeset | 744 | 
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changeset | 745 """ | 
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changeset | 746 try: | 
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changeset | 747 self.get_item(**kwargs) | 
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changeset | 748 except (JSONResponseError, exceptions.ItemNotFound): | 
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changeset | 749 return False | 
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changeset | 750 | 
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changeset | 751 return True | 
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changeset | 752 | 
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changeset | 753 def lookup(self, *args, **kwargs): | 
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changeset | 754 """ | 
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changeset | 755 Look up an entry in DynamoDB. This is mostly backwards compatible | 
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changeset | 756 with boto.dynamodb. Unlike get_item, it takes hash_key and range_key first, | 
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changeset | 757 although you may still specify keyword arguments instead. | 
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changeset | 758 | 
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changeset | 759 Also unlike the get_item command, if the returned item has no keys | 
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changeset | 760 (i.e., it does not exist in DynamoDB), a None result is returned, instead | 
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changeset | 761 of an empty key object. | 
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changeset | 762 | 
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changeset | 763 Example:: | 
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changeset | 764 >>> user = users.lookup(username) | 
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changeset | 765 >>> user = users.lookup(username, consistent=True) | 
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changeset | 766 >>> app = apps.lookup('my_customer_id', 'my_app_id') | 
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changeset | 767 | 
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changeset | 768 """ | 
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changeset | 769 if not self.schema: | 
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changeset | 770 self.describe() | 
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changeset | 771 for x, arg in enumerate(args): | 
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changeset | 772 kwargs[self.schema[x].name] = arg | 
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changeset | 773 ret = self.get_item(**kwargs) | 
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changeset | 774 if not ret.keys(): | 
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changeset | 775 return None | 
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changeset | 776 return ret | 
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changeset | 777 | 
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changeset | 778 def new_item(self, *args): | 
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changeset | 779 """ | 
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changeset | 780 Returns a new, blank item | 
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changeset | 781 | 
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changeset | 782 This is mostly for consistency with boto.dynamodb | 
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changeset | 783 """ | 
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changeset | 784 if not self.schema: | 
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changeset | 785 self.describe() | 
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changeset | 786 data = {} | 
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changeset | 787 for x, arg in enumerate(args): | 
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changeset | 788 data[self.schema[x].name] = arg | 
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changeset | 789 return Item(self, data=data) | 
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changeset | 790 | 
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changeset | 791 def put_item(self, data, overwrite=False): | 
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changeset | 792 """ | 
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changeset | 793 Saves an entire item to DynamoDB. | 
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changeset | 794 | 
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changeset | 795 By default, if any part of the ``Item``'s original data doesn't match | 
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changeset | 796 what's currently in DynamoDB, this request will fail. This prevents | 
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changeset | 797 other processes from updating the data in between when you read the | 
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changeset | 798 item & when your request to update the item's data is processed, which | 
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changeset | 799 would typically result in some data loss. | 
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changeset | 800 | 
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changeset | 801 Requires a ``data`` parameter, which should be a dictionary of the data | 
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changeset | 802 you'd like to store in DynamoDB. | 
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changeset | 803 | 
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changeset | 804 Optionally accepts an ``overwrite`` parameter, which should be a | 
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changeset | 805 boolean. If you provide ``True``, this will tell DynamoDB to blindly | 
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changeset | 806 overwrite whatever data is present, if any. | 
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changeset | 807 | 
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changeset | 808 Returns ``True`` on success. | 
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changeset | 809 | 
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changeset | 810 Example:: | 
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changeset | 811 | 
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changeset | 812 >>> users.put_item(data={ | 
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changeset | 813 ... 'username': 'jane', | 
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changeset | 814 ... 'first_name': 'Jane', | 
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changeset | 815 ... 'last_name': 'Doe', | 
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changeset | 816 ... 'date_joined': 126478915, | 
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changeset | 817 ... }) | 
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changeset | 818 True | 
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changeset | 819 | 
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changeset | 820 """ | 
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changeset | 821 item = Item(self, data=data) | 
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changeset | 822 return item.save(overwrite=overwrite) | 
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changeset | 823 | 
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changeset | 824 def _put_item(self, item_data, expects=None): | 
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changeset | 825 """ | 
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changeset | 826 The internal variant of ``put_item`` (full data). This is used by the | 
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changeset | 827 ``Item`` objects, since that operation is represented at the | 
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changeset | 828 table-level by the API, but conceptually maps better to telling an | 
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changeset | 829 individual ``Item`` to save itself. | 
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changeset | 830 """ | 
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changeset | 831 kwargs = {} | 
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changeset | 832 | 
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changeset | 833 if expects is not None: | 
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changeset | 834 kwargs['expected'] = expects | 
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changeset | 835 | 
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changeset | 836 self.connection.put_item(self.table_name, item_data, **kwargs) | 
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changeset | 837 return True | 
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changeset | 838 | 
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changeset | 839 def _update_item(self, key, item_data, expects=None): | 
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changeset | 840 """ | 
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changeset | 841 The internal variant of ``put_item`` (partial data). This is used by the | 
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changeset | 842 ``Item`` objects, since that operation is represented at the | 
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changeset | 843 table-level by the API, but conceptually maps better to telling an | 
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changeset | 844 individual ``Item`` to save itself. | 
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changeset | 845 """ | 
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changeset | 846 raw_key = self._encode_keys(key) | 
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changeset | 847 kwargs = {} | 
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changeset | 848 | 
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changeset | 849 if expects is not None: | 
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changeset | 850 kwargs['expected'] = expects | 
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changeset | 851 | 
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changeset | 852 self.connection.update_item(self.table_name, raw_key, item_data, **kwargs) | 
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changeset | 853 return True | 
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changeset | 854 | 
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changeset | 855 def delete_item(self, expected=None, conditional_operator=None, **kwargs): | 
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changeset | 856 """ | 
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changeset | 857 Deletes a single item. You can perform a conditional delete operation | 
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changeset | 858 that deletes the item if it exists, or if it has an expected attribute | 
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changeset | 859 value. | 
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changeset | 860 | 
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changeset | 861 Conditional deletes are useful for only deleting items if specific | 
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changeset | 862 conditions are met. If those conditions are met, DynamoDB performs | 
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changeset | 863 the delete. Otherwise, the item is not deleted. | 
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changeset | 864 | 
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changeset | 865 To specify the expected attribute values of the item, you can pass a | 
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changeset | 866 dictionary of conditions to ``expected``. Each condition should follow | 
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changeset | 867 the pattern ``<attributename>__<comparison_operator>=<value_to_expect>``. | 
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changeset | 868 | 
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changeset | 869 **IMPORTANT** - Be careful when using this method, there is no undo. | 
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changeset | 870 | 
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changeset | 871 To specify the key of the item you'd like to get, you can specify the | 
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changeset | 872 key attributes as kwargs. | 
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changeset | 873 | 
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changeset | 874 Optionally accepts an ``expected`` parameter which is a dictionary of | 
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changeset | 875 expected attribute value conditions. | 
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changeset | 876 | 
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changeset | 877 Optionally accepts a ``conditional_operator`` which applies to the | 
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changeset | 878 expected attribute value conditions: | 
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changeset | 879 | 
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changeset | 880 + `AND` - If all of the conditions evaluate to true (default) | 
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changeset | 881 + `OR` - True if at least one condition evaluates to true | 
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changeset | 882 | 
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changeset | 883 Returns ``True`` on success, ``False`` on failed conditional delete. | 
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changeset | 884 | 
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changeset | 885 Example:: | 
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changeset | 886 | 
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changeset | 887 # A simple hash key. | 
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changeset | 888 >>> users.delete_item(username='johndoe') | 
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changeset | 889 True | 
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changeset | 890 | 
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changeset | 891 # A complex hash+range key. | 
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changeset | 892 >>> users.delete_item(username='jane', last_name='Doe') | 
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changeset | 893 True | 
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changeset | 894 | 
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changeset | 895 # With a key that is an invalid variable name in Python. | 
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changeset | 896 # Also, assumes a different schema than previous examples. | 
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changeset | 897 >>> users.delete_item(**{ | 
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changeset | 898 ... 'date-joined': 127549192, | 
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changeset | 899 ... }) | 
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changeset | 900 True | 
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changeset | 901 | 
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changeset | 902 # Conditional delete | 
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changeset | 903 >>> users.delete_item(username='johndoe', | 
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changeset | 904 ... expected={'balance__eq': 0}) | 
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changeset | 905 True | 
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changeset | 906 """ | 
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changeset | 907 expected = self._build_filters(expected, using=FILTER_OPERATORS) | 
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changeset | 908 raw_key = self._encode_keys(kwargs) | 
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changeset | 909 | 
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changeset | 910 try: | 
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changeset | 911 self.connection.delete_item(self.table_name, raw_key, | 
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changeset | 912 expected=expected, | 
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changeset | 913 conditional_operator=conditional_operator) | 
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changeset | 914 except exceptions.ConditionalCheckFailedException: | 
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changeset | 915 return False | 
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changeset | 916 | 
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changeset | 917 return True | 
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changeset | 918 | 
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changeset | 919 def get_key_fields(self): | 
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changeset | 920 """ | 
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changeset | 921 Returns the fields necessary to make a key for a table. | 
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changeset | 922 | 
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changeset | 923 If the ``Table`` does not already have a populated ``schema``, | 
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changeset | 924 this will request it via a ``Table.describe`` call. | 
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changeset | 925 | 
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changeset | 926 Returns a list of fieldnames (strings). | 
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changeset | 927 | 
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changeset | 928 Example:: | 
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changeset | 929 | 
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changeset | 930 # A simple hash key. | 
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changeset | 931 >>> users.get_key_fields() | 
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changeset | 932 ['username'] | 
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changeset | 933 | 
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changeset | 934 # A complex hash+range key. | 
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changeset | 935 >>> users.get_key_fields() | 
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changeset | 936 ['username', 'last_name'] | 
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changeset | 937 | 
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changeset | 938 """ | 
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changeset | 939 if not self.schema: | 
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changeset | 940 # We don't know the structure of the table. Get a description to | 
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changeset | 941 # populate the schema. | 
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changeset | 942 self.describe() | 
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changeset | 943 | 
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changeset | 944 return [field.name for field in self.schema] | 
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changeset | 945 | 
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changeset | 946 def batch_write(self): | 
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changeset | 947 """ | 
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changeset | 948 Allows the batching of writes to DynamoDB. | 
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changeset | 949 | 
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changeset | 950 Since each write/delete call to DynamoDB has a cost associated with it, | 
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changeset | 951 when loading lots of data, it makes sense to batch them, creating as | 
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changeset | 952 few calls as possible. | 
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changeset | 953 | 
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changeset | 954 This returns a context manager that will transparently handle creating | 
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changeset | 955 these batches. The object you get back lightly-resembles a ``Table`` | 
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changeset | 956 object, sharing just the ``put_item`` & ``delete_item`` methods | 
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changeset | 957 (which are all that DynamoDB can batch in terms of writing data). | 
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changeset | 958 | 
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changeset | 959 DynamoDB's maximum batch size is 25 items per request. If you attempt | 
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changeset | 960 to put/delete more than that, the context manager will batch as many | 
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changeset | 961 as it can up to that number, then flush them to DynamoDB & continue | 
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changeset | 962 batching as more calls come in. | 
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changeset | 963 | 
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changeset | 964 Example:: | 
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changeset | 965 | 
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changeset | 966 # Assuming a table with one record... | 
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changeset | 967 >>> with users.batch_write() as batch: | 
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changeset | 968 ... batch.put_item(data={ | 
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changeset | 969 ... 'username': 'johndoe', | 
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changeset | 970 ... 'first_name': 'John', | 
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changeset | 971 ... 'last_name': 'Doe', | 
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changeset | 972 ... 'owner': 1, | 
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changeset | 973 ... }) | 
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changeset | 974 ... # Nothing across the wire yet. | 
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changeset | 975 ... batch.delete_item(username='bob') | 
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changeset | 976 ... # Still no requests sent. | 
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changeset | 977 ... batch.put_item(data={ | 
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changeset | 978 ... 'username': 'jane', | 
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changeset | 979 ... 'first_name': 'Jane', | 
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changeset | 980 ... 'last_name': 'Doe', | 
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changeset | 981 ... 'date_joined': 127436192, | 
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changeset | 982 ... }) | 
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changeset | 983 ... # Nothing yet, but once we leave the context, the | 
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changeset | 984 ... # put/deletes will be sent. | 
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changeset | 985 | 
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changeset | 986 """ | 
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changeset | 987 # PHENOMENAL COSMIC DOCS!!! itty-bitty code. | 
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changeset | 988 return BatchTable(self) | 
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changeset | 989 | 
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changeset | 990 def _build_filters(self, filter_kwargs, using=QUERY_OPERATORS): | 
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changeset | 991 """ | 
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changeset | 992 An internal method for taking query/scan-style ``**kwargs`` & turning | 
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changeset | 993 them into the raw structure DynamoDB expects for filtering. | 
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changeset | 994 """ | 
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changeset | 995 if filter_kwargs is None: | 
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changeset | 996 return | 
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changeset | 997 | 
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changeset | 998 filters = {} | 
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changeset | 999 | 
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changeset | 1000 for field_and_op, value in filter_kwargs.items(): | 
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changeset | 1001 field_bits = field_and_op.split('__') | 
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changeset | 1002 fieldname = '__'.join(field_bits[:-1]) | 
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changeset | 1003 | 
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changeset | 1004 try: | 
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changeset | 1005 op = using[field_bits[-1]] | 
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changeset | 1006 except KeyError: | 
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changeset | 1007 raise exceptions.UnknownFilterTypeError( | 
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changeset | 1008 "Operator '%s' from '%s' is not recognized." % ( | 
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changeset | 1009 field_bits[-1], | 
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changeset | 1010 field_and_op | 
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changeset | 1011 ) | 
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changeset | 1012 ) | 
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changeset | 1013 | 
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changeset | 1014 lookup = { | 
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changeset | 1015 'AttributeValueList': [], | 
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changeset | 1016 'ComparisonOperator': op, | 
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changeset | 1017 } | 
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changeset | 1018 | 
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changeset | 1019 # Special-case the ``NULL/NOT_NULL`` case. | 
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changeset | 1020 if field_bits[-1] == 'null': | 
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changeset | 1021 del lookup['AttributeValueList'] | 
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changeset | 1022 | 
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changeset | 1023 if value is False: | 
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changeset | 1024 lookup['ComparisonOperator'] = 'NOT_NULL' | 
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changeset | 1025 else: | 
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changeset | 1026 lookup['ComparisonOperator'] = 'NULL' | 
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changeset | 1027 # Special-case the ``BETWEEN`` case. | 
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changeset | 1028 elif field_bits[-1] == 'between': | 
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changeset | 1029 if len(value) == 2 and isinstance(value, (list, tuple)): | 
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changeset | 1030 lookup['AttributeValueList'].append( | 
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changeset | 1031 self._dynamizer.encode(value[0]) | 
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changeset | 1032 ) | 
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changeset | 1033 lookup['AttributeValueList'].append( | 
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changeset | 1034 self._dynamizer.encode(value[1]) | 
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changeset | 1035 ) | 
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changeset | 1036 # Special-case the ``IN`` case | 
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changeset | 1037 elif field_bits[-1] == 'in': | 
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changeset | 1038 for val in value: | 
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changeset | 1039 lookup['AttributeValueList'].append(self._dynamizer.encode(val)) | 
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changeset | 1040 else: | 
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changeset | 1041 # Fix up the value for encoding, because it was built to only work | 
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changeset | 1042 # with ``set``s. | 
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changeset | 1043 if isinstance(value, (list, tuple)): | 
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changeset | 1044 value = set(value) | 
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changeset | 1045 lookup['AttributeValueList'].append( | 
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changeset | 1046 self._dynamizer.encode(value) | 
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changeset | 1047 ) | 
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changeset | 1048 | 
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changeset | 1049 # Finally, insert it into the filters. | 
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changeset | 1050 filters[fieldname] = lookup | 
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changeset | 1051 | 
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changeset | 1052 return filters | 
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changeset | 1053 | 
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changeset | 1054 def query(self, limit=None, index=None, reverse=False, consistent=False, | 
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changeset | 1055 attributes=None, max_page_size=None, **filter_kwargs): | 
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changeset | 1056 """ | 
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changeset | 1057 **WARNING:** This method is provided **strictly** for | 
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changeset | 1058 backward-compatibility. It returns results in an incorrect order. | 
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changeset | 1059 | 
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changeset | 1060 If you are writing new code, please use ``Table.query_2``. | 
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changeset | 1061 """ | 
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changeset | 1062 reverse = not reverse | 
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changeset | 1063 return self.query_2(limit=limit, index=index, reverse=reverse, | 
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changeset | 1064 consistent=consistent, attributes=attributes, | 
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changeset | 1065 max_page_size=max_page_size, **filter_kwargs) | 
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changeset | 1066 | 
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changeset | 1067 def query_2(self, limit=None, index=None, reverse=False, | 
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changeset | 1068 consistent=False, attributes=None, max_page_size=None, | 
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changeset | 1069 query_filter=None, conditional_operator=None, | 
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changeset | 1070 **filter_kwargs): | 
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changeset | 1071 """ | 
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changeset | 1072 Queries for a set of matching items in a DynamoDB table. | 
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changeset | 1073 | 
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changeset | 1074 Queries can be performed against a hash key, a hash+range key or | 
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changeset | 1075 against any data stored in your local secondary indexes. Query filters | 
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changeset | 1076 can be used to filter on arbitrary fields. | 
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changeset | 1077 | 
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changeset | 1078 **Note** - You can not query against arbitrary fields within the data | 
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changeset | 1079 stored in DynamoDB unless you specify ``query_filter`` values. | 
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changeset | 1080 | 
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changeset | 1081 To specify the filters of the items you'd like to get, you can specify | 
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changeset | 1082 the filters as kwargs. Each filter kwarg should follow the pattern | 
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changeset | 1083 ``<fieldname>__<filter_operation>=<value_to_look_for>``. Query filters | 
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changeset | 1084 are specified in the same way. | 
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changeset | 1085 | 
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changeset | 1086 Optionally accepts a ``limit`` parameter, which should be an integer | 
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changeset | 1087 count of the total number of items to return. (Default: ``None`` - | 
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changeset | 1088 all results) | 
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changeset | 1089 | 
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changeset | 1090 Optionally accepts an ``index`` parameter, which should be a string of | 
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changeset | 1091 name of the local secondary index you want to query against. | 
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changeset | 1092 (Default: ``None``) | 
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changeset | 1093 | 
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changeset | 1094 Optionally accepts a ``reverse`` parameter, which will present the | 
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changeset | 1095 results in reverse order. (Default: ``False`` - normal order) | 
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changeset | 1096 | 
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changeset | 1097 Optionally accepts a ``consistent`` parameter, which should be a | 
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changeset | 1098 boolean. If you provide ``True``, it will force a consistent read of | 
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changeset | 1099 the data (more expensive). (Default: ``False`` - use eventually | 
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changeset | 1100 consistent reads) | 
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changeset | 1101 | 
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changeset | 1102 Optionally accepts a ``attributes`` parameter, which should be a | 
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changeset | 1103 tuple. If you provide any attributes only these will be fetched | 
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changeset | 1104 from DynamoDB. This uses the ``AttributesToGet`` and set's | 
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changeset | 1105 ``Select`` to ``SPECIFIC_ATTRIBUTES`` API. | 
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changeset | 1106 | 
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changeset | 1107 Optionally accepts a ``max_page_size`` parameter, which should be an | 
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changeset | 1108 integer count of the maximum number of items to retrieve | 
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changeset | 1109 **per-request**. This is useful in making faster requests & prevent | 
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changeset | 1110 the scan from drowning out other queries. (Default: ``None`` - | 
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changeset | 1111 fetch as many as DynamoDB will return) | 
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changeset | 1112 | 
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changeset | 1113 Optionally accepts a ``query_filter`` which is a dictionary of filter | 
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changeset | 1114 conditions against any arbitrary field in the returned data. | 
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changeset | 1115 | 
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changeset | 1116 Optionally accepts a ``conditional_operator`` which applies to the | 
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changeset | 1117 query filter conditions: | 
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changeset | 1118 | 
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changeset | 1119 + `AND` - True if all filter conditions evaluate to true (default) | 
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changeset | 1120 + `OR` - True if at least one filter condition evaluates to true | 
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changeset | 1121 | 
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changeset | 1122 Returns a ``ResultSet`` containing ``Item``s, which transparently handles the pagination of | 
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changeset | 1123 results you get back. | 
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changeset | 1124 | 
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changeset | 1125 Example:: | 
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changeset | 1126 | 
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changeset | 1127 # Look for last names equal to "Doe". | 
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changeset | 1128 >>> results = users.query(last_name__eq='Doe') | 
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changeset | 1129 >>> for res in results: | 
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changeset | 1130 ... print res['first_name'] | 
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changeset | 1131 'John' | 
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changeset | 1132 'Jane' | 
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changeset | 1133 | 
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changeset | 1134 # Look for last names beginning with "D", in reverse order, limit 3. | 
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changeset | 1135 >>> results = users.query( | 
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changeset | 1136 ... last_name__beginswith='D', | 
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changeset | 1137 ... reverse=True, | 
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changeset | 1138 ... limit=3 | 
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changeset | 1139 ... ) | 
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changeset | 1140 >>> for res in results: | 
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changeset | 1141 ... print res['first_name'] | 
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changeset | 1142 'Alice' | 
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changeset | 1143 'Jane' | 
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changeset | 1144 'John' | 
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changeset | 1145 | 
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changeset | 1146 # Use an LSI & a consistent read. | 
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changeset | 1147 >>> results = users.query( | 
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changeset | 1148 ... date_joined__gte=1236451000, | 
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changeset | 1149 ... owner__eq=1, | 
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changeset | 1150 ... index='DateJoinedIndex', | 
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changeset | 1151 ... consistent=True | 
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changeset | 1152 ... ) | 
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changeset | 1153 >>> for res in results: | 
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changeset | 1154 ... print res['first_name'] | 
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changeset | 1155 'Alice' | 
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changeset | 1156 'Bob' | 
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changeset | 1157 'John' | 
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changeset | 1158 'Fred' | 
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changeset | 1159 | 
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changeset | 1160 # Filter by non-indexed field(s) | 
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changeset | 1161 >>> results = users.query( | 
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changeset | 1162 ... last_name__eq='Doe', | 
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changeset | 1163 ... reverse=True, | 
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changeset | 1164 ... query_filter={ | 
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changeset | 1165 ... 'first_name__beginswith': 'A' | 
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changeset | 1166 ... } | 
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changeset | 1167 ... ) | 
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changeset | 1168 >>> for res in results: | 
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changeset | 1169 ... print res['first_name'] + ' ' + res['last_name'] | 
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changeset | 1170 'Alice Doe' | 
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changeset | 1171 | 
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changeset | 1172 """ | 
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changeset | 1173 if self.schema: | 
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changeset | 1174 if len(self.schema) == 1: | 
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changeset | 1175 if len(filter_kwargs) <= 1: | 
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changeset | 1176 if not self.global_indexes or not len(self.global_indexes): | 
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changeset | 1177 # If the schema only has one field, there's <= 1 filter | 
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changeset | 1178 # param & no Global Secondary Indexes, this is user | 
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changeset | 1179 # error. Bail early. | 
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changeset | 1180 raise exceptions.QueryError( | 
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changeset | 1181 "You must specify more than one key to filter on." | 
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changeset | 1182 ) | 
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changeset | 1183 | 
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changeset | 1184 if attributes is not None: | 
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changeset | 1185 select = 'SPECIFIC_ATTRIBUTES' | 
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changeset | 1186 else: | 
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changeset | 1187 select = None | 
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changeset | 1188 | 
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changeset | 1189 results = ResultSet( | 
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changeset | 1190 max_page_size=max_page_size | 
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changeset | 1191 ) | 
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changeset | 1192 kwargs = filter_kwargs.copy() | 
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changeset | 1193 kwargs.update({ | 
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changeset | 1194 'limit': limit, | 
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changeset | 1195 'index': index, | 
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changeset | 1196 'reverse': reverse, | 
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changeset | 1197 'consistent': consistent, | 
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changeset | 1198 'select': select, | 
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changeset | 1199 'attributes_to_get': attributes, | 
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changeset | 1200 'query_filter': query_filter, | 
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changeset | 1201 'conditional_operator': conditional_operator, | 
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changeset | 1202 }) | 
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changeset | 1203 results.to_call(self._query, **kwargs) | 
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changeset | 1204 return results | 
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changeset | 1205 | 
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changeset | 1206 def query_count(self, index=None, consistent=False, conditional_operator=None, | 
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changeset | 1207 query_filter=None, scan_index_forward=True, limit=None, | 
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changeset | 1208 exclusive_start_key=None, **filter_kwargs): | 
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changeset | 1209 """ | 
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changeset | 1210 Queries the exact count of matching items in a DynamoDB table. | 
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changeset | 1211 | 
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changeset | 1212 Queries can be performed against a hash key, a hash+range key or | 
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changeset | 1213 against any data stored in your local secondary indexes. Query filters | 
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changeset | 1214 can be used to filter on arbitrary fields. | 
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changeset | 1215 | 
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changeset | 1216 To specify the filters of the items you'd like to get, you can specify | 
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changeset | 1217 the filters as kwargs. Each filter kwarg should follow the pattern | 
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changeset | 1218 ``<fieldname>__<filter_operation>=<value_to_look_for>``. Query filters | 
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changeset | 1219 are specified in the same way. | 
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changeset | 1220 | 
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changeset | 1221 Optionally accepts an ``index`` parameter, which should be a string of | 
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changeset | 1222 name of the local secondary index you want to query against. | 
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changeset | 1223 (Default: ``None``) | 
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changeset | 1224 | 
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changeset | 1225 Optionally accepts a ``consistent`` parameter, which should be a | 
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changeset | 1226 boolean. If you provide ``True``, it will force a consistent read of | 
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changeset | 1227 the data (more expensive). (Default: ``False`` - use eventually | 
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changeset | 1228 consistent reads) | 
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changeset | 1229 | 
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changeset | 1230 Optionally accepts a ``query_filter`` which is a dictionary of filter | 
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changeset | 1231 conditions against any arbitrary field in the returned data. | 
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changeset | 1232 | 
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changeset | 1233 Optionally accepts a ``conditional_operator`` which applies to the | 
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changeset | 1234 query filter conditions: | 
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changeset | 1235 | 
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changeset | 1236 + `AND` - True if all filter conditions evaluate to true (default) | 
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changeset | 1237 + `OR` - True if at least one filter condition evaluates to true | 
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changeset | 1238 | 
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changeset | 1239 Optionally accept a ``exclusive_start_key`` which is used to get | 
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changeset | 1240 the remaining items when a query cannot return the complete count. | 
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changeset | 1241 | 
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changeset | 1242 Returns an integer which represents the exact amount of matched | 
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changeset | 1243 items. | 
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changeset | 1244 | 
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changeset | 1245 :type scan_index_forward: boolean | 
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changeset | 1246 :param scan_index_forward: Specifies ascending (true) or descending | 
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changeset | 1247 (false) traversal of the index. DynamoDB returns results reflecting | 
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changeset | 1248 the requested order determined by the range key. If the data type | 
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changeset | 1249 is Number, the results are returned in numeric order. For String, | 
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changeset | 1250 the results are returned in order of ASCII character code values. | 
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changeset | 1251 For Binary, DynamoDB treats each byte of the binary data as | 
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changeset | 1252 unsigned when it compares binary values. | 
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changeset | 1253 | 
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changeset | 1254 If ScanIndexForward is not specified, the results are returned in | 
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changeset | 1255 ascending order. | 
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changeset | 1256 | 
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changeset | 1257 :type limit: integer | 
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changeset | 1258 :param limit: The maximum number of items to evaluate (not necessarily | 
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changeset | 1259 the number of matching items). | 
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changeset | 1260 | 
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changeset | 1261 Example:: | 
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changeset | 1262 | 
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changeset | 1263 # Look for last names equal to "Doe". | 
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changeset | 1264 >>> users.query_count(last_name__eq='Doe') | 
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changeset | 1265 5 | 
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changeset | 1266 | 
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changeset | 1267 # Use an LSI & a consistent read. | 
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changeset | 1268 >>> users.query_count( | 
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changeset | 1269 ... date_joined__gte=1236451000, | 
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changeset | 1270 ... owner__eq=1, | 
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changeset | 1271 ... index='DateJoinedIndex', | 
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changeset | 1272 ... consistent=True | 
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changeset | 1273 ... ) | 
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changeset | 1274 2 | 
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changeset | 1275 | 
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changeset | 1276 """ | 
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changeset | 1277 key_conditions = self._build_filters( | 
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changeset | 1278 filter_kwargs, | 
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changeset | 1279 using=QUERY_OPERATORS | 
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changeset | 1280 ) | 
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changeset | 1281 | 
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changeset | 1282 built_query_filter = self._build_filters( | 
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changeset | 1283 query_filter, | 
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changeset | 1284 using=FILTER_OPERATORS | 
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changeset | 1285 ) | 
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changeset | 1286 | 
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changeset | 1287 count_buffer = 0 | 
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changeset | 1288 last_evaluated_key = exclusive_start_key | 
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changeset | 1289 | 
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changeset | 1290 while True: | 
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changeset | 1291 raw_results = self.connection.query( | 
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changeset | 1292 self.table_name, | 
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changeset | 1293 index_name=index, | 
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changeset | 1294 consistent_read=consistent, | 
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changeset | 1295 select='COUNT', | 
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changeset | 1296 key_conditions=key_conditions, | 
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changeset | 1297 query_filter=built_query_filter, | 
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changeset | 1298 conditional_operator=conditional_operator, | 
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changeset | 1299 limit=limit, | 
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changeset | 1300 scan_index_forward=scan_index_forward, | 
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changeset | 1301 exclusive_start_key=last_evaluated_key | 
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changeset | 1302 ) | 
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changeset | 1303 | 
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changeset | 1304 count_buffer += int(raw_results.get('Count', 0)) | 
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changeset | 1305 last_evaluated_key = raw_results.get('LastEvaluatedKey') | 
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changeset | 1306 if not last_evaluated_key or count_buffer < 1: | 
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changeset | 1307 break | 
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changeset | 1308 | 
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changeset | 1309 return count_buffer | 
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changeset | 1310 | 
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changeset | 1311 def _query(self, limit=None, index=None, reverse=False, consistent=False, | 
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changeset | 1312 exclusive_start_key=None, select=None, attributes_to_get=None, | 
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changeset | 1313 query_filter=None, conditional_operator=None, **filter_kwargs): | 
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changeset | 1314 """ | 
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changeset | 1315 The internal method that performs the actual queries. Used extensively | 
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changeset | 1316 by ``ResultSet`` to perform each (paginated) request. | 
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changeset | 1317 """ | 
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changeset | 1318 kwargs = { | 
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changeset | 1319 'limit': limit, | 
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changeset | 1320 'index_name': index, | 
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changeset | 1321 'consistent_read': consistent, | 
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changeset | 1322 'select': select, | 
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changeset | 1323 'attributes_to_get': attributes_to_get, | 
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changeset | 1324 'conditional_operator': conditional_operator, | 
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changeset | 1325 } | 
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changeset | 1326 | 
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changeset | 1327 if reverse: | 
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changeset | 1328 kwargs['scan_index_forward'] = False | 
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changeset | 1329 | 
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changeset | 1330 if exclusive_start_key: | 
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changeset | 1331 kwargs['exclusive_start_key'] = {} | 
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changeset | 1332 | 
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changeset | 1333 for key, value in exclusive_start_key.items(): | 
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changeset | 1334 kwargs['exclusive_start_key'][key] = \ | 
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changeset | 1335 self._dynamizer.encode(value) | 
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changeset | 1336 | 
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changeset | 1337 # Convert the filters into something we can actually use. | 
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changeset | 1338 kwargs['key_conditions'] = self._build_filters( | 
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changeset | 1339 filter_kwargs, | 
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changeset | 1340 using=QUERY_OPERATORS | 
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changeset | 1341 ) | 
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changeset | 1342 | 
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changeset | 1343 kwargs['query_filter'] = self._build_filters( | 
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changeset | 1344 query_filter, | 
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changeset | 1345 using=FILTER_OPERATORS | 
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changeset | 1346 ) | 
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changeset | 1347 | 
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changeset | 1348 raw_results = self.connection.query( | 
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changeset | 1349 self.table_name, | 
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changeset | 1350 **kwargs | 
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changeset | 1351 ) | 
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changeset | 1352 results = [] | 
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changeset | 1353 last_key = None | 
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changeset | 1354 | 
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changeset | 1355 for raw_item in raw_results.get('Items', []): | 
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changeset | 1356 item = Item(self) | 
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changeset | 1357 item.load({ | 
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changeset | 1358 'Item': raw_item, | 
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changeset | 1359 }) | 
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changeset | 1360 results.append(item) | 
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changeset | 1361 | 
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changeset | 1362 if raw_results.get('LastEvaluatedKey', None): | 
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changeset | 1363 last_key = {} | 
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changeset | 1364 | 
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changeset | 1365 for key, value in raw_results['LastEvaluatedKey'].items(): | 
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changeset | 1366 last_key[key] = self._dynamizer.decode(value) | 
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changeset | 1367 | 
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changeset | 1368 return { | 
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changeset | 1369 'results': results, | 
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changeset | 1370 'last_key': last_key, | 
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changeset | 1371 } | 
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changeset | 1372 | 
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changeset | 1373 def scan(self, limit=None, segment=None, total_segments=None, | 
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changeset | 1374 max_page_size=None, attributes=None, conditional_operator=None, | 
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changeset | 1375 **filter_kwargs): | 
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changeset | 1376 """ | 
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changeset | 1377 Scans across all items within a DynamoDB table. | 
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changeset | 1378 | 
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changeset | 1379 Scans can be performed against a hash key or a hash+range key. You can | 
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changeset | 1380 additionally filter the results after the table has been read but | 
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changeset | 1381 before the response is returned by using query filters. | 
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changeset | 1382 | 
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changeset | 1383 To specify the filters of the items you'd like to get, you can specify | 
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changeset | 1384 the filters as kwargs. Each filter kwarg should follow the pattern | 
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changeset | 1385 ``<fieldname>__<filter_operation>=<value_to_look_for>``. | 
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changeset | 1386 | 
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changeset | 1387 Optionally accepts a ``limit`` parameter, which should be an integer | 
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changeset | 1388 count of the total number of items to return. (Default: ``None`` - | 
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changeset | 1389 all results) | 
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changeset | 1390 | 
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changeset | 1391 Optionally accepts a ``segment`` parameter, which should be an integer | 
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changeset | 1392 of the segment to retrieve on. Please see the documentation about | 
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changeset | 1393 Parallel Scans (Default: ``None`` - no segments) | 
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changeset | 1394 | 
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changeset | 1395 Optionally accepts a ``total_segments`` parameter, which should be an | 
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changeset | 1396 integer count of number of segments to divide the table into. | 
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changeset | 1397 Please see the documentation about Parallel Scans (Default: ``None`` - | 
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changeset | 1398 no segments) | 
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changeset | 1399 | 
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changeset | 1400 Optionally accepts a ``max_page_size`` parameter, which should be an | 
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changeset | 1401 integer count of the maximum number of items to retrieve | 
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changeset | 1402 **per-request**. This is useful in making faster requests & prevent | 
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changeset | 1403 the scan from drowning out other queries. (Default: ``None`` - | 
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changeset | 1404 fetch as many as DynamoDB will return) | 
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changeset | 1405 | 
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changeset | 1406 Optionally accepts an ``attributes`` parameter, which should be a | 
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changeset | 1407 tuple. If you provide any attributes only these will be fetched | 
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changeset | 1408 from DynamoDB. This uses the ``AttributesToGet`` and set's | 
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changeset | 1409 ``Select`` to ``SPECIFIC_ATTRIBUTES`` API. | 
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changeset | 1410 | 
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changeset | 1411 Returns a ``ResultSet``, which transparently handles the pagination of | 
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changeset | 1412 results you get back. | 
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changeset | 1413 | 
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changeset | 1414 Example:: | 
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changeset | 1415 | 
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changeset | 1416 # All results. | 
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changeset | 1417 >>> everything = users.scan() | 
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changeset | 1418 | 
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changeset | 1419 # Look for last names beginning with "D". | 
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changeset | 1420 >>> results = users.scan(last_name__beginswith='D') | 
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changeset | 1421 >>> for res in results: | 
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changeset | 1422 ... print res['first_name'] | 
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changeset | 1423 'Alice' | 
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changeset | 1424 'John' | 
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changeset | 1425 'Jane' | 
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changeset | 1426 | 
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changeset | 1427 # Use an ``IN`` filter & limit. | 
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changeset | 1428 >>> results = users.scan( | 
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changeset | 1429 ... age__in=[25, 26, 27, 28, 29], | 
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changeset | 1430 ... limit=1 | 
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changeset | 1431 ... ) | 
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changeset | 1432 >>> for res in results: | 
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changeset | 1433 ... print res['first_name'] | 
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changeset | 1434 'Alice' | 
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changeset | 1435 | 
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changeset | 1436 """ | 
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changeset | 1437 results = ResultSet( | 
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changeset | 1438 max_page_size=max_page_size | 
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changeset | 1439 ) | 
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changeset | 1440 kwargs = filter_kwargs.copy() | 
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changeset | 1441 kwargs.update({ | 
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changeset | 1442 'limit': limit, | 
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changeset | 1443 'segment': segment, | 
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changeset | 1444 'total_segments': total_segments, | 
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changeset | 1445 'attributes': attributes, | 
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changeset | 1446 'conditional_operator': conditional_operator, | 
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changeset | 1447 }) | 
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changeset | 1448 results.to_call(self._scan, **kwargs) | 
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changeset | 1449 return results | 
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changeset | 1450 | 
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changeset | 1451 def _scan(self, limit=None, exclusive_start_key=None, segment=None, | 
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changeset | 1452 total_segments=None, attributes=None, conditional_operator=None, | 
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changeset | 1453 **filter_kwargs): | 
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changeset | 1454 """ | 
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changeset | 1455 The internal method that performs the actual scan. Used extensively | 
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changeset | 1456 by ``ResultSet`` to perform each (paginated) request. | 
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changeset | 1457 """ | 
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changeset | 1458 kwargs = { | 
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changeset | 1459 'limit': limit, | 
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changeset | 1460 'segment': segment, | 
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changeset | 1461 'total_segments': total_segments, | 
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changeset | 1462 'attributes_to_get': attributes, | 
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changeset | 1463 'conditional_operator': conditional_operator, | 
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changeset | 1464 } | 
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changeset | 1465 | 
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changeset | 1466 if exclusive_start_key: | 
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changeset | 1467 kwargs['exclusive_start_key'] = {} | 
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changeset | 1468 | 
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changeset | 1469 for key, value in exclusive_start_key.items(): | 
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changeset | 1470 kwargs['exclusive_start_key'][key] = \ | 
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changeset | 1471 self._dynamizer.encode(value) | 
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changeset | 1472 | 
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changeset | 1473 # Convert the filters into something we can actually use. | 
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changeset | 1474 kwargs['scan_filter'] = self._build_filters( | 
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changeset | 1475 filter_kwargs, | 
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changeset | 1476 using=FILTER_OPERATORS | 
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changeset | 1477 ) | 
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changeset | 1478 | 
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changeset | 1479 raw_results = self.connection.scan( | 
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changeset | 1480 self.table_name, | 
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changeset | 1481 **kwargs | 
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changeset | 1482 ) | 
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changeset | 1483 results = [] | 
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changeset | 1484 last_key = None | 
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changeset | 1485 | 
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changeset | 1486 for raw_item in raw_results.get('Items', []): | 
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changeset | 1487 item = Item(self) | 
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changeset | 1488 item.load({ | 
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changeset | 1489 'Item': raw_item, | 
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changeset | 1490 }) | 
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changeset | 1491 results.append(item) | 
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changeset | 1492 | 
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changeset | 1493 if raw_results.get('LastEvaluatedKey', None): | 
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changeset | 1494 last_key = {} | 
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changeset | 1495 | 
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changeset | 1496 for key, value in raw_results['LastEvaluatedKey'].items(): | 
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changeset | 1497 last_key[key] = self._dynamizer.decode(value) | 
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changeset | 1498 | 
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changeset | 1499 return { | 
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changeset | 1500 'results': results, | 
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changeset | 1501 'last_key': last_key, | 
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changeset | 1502 } | 
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changeset | 1503 | 
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changeset | 1504 def batch_get(self, keys, consistent=False, attributes=None): | 
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changeset | 1505 """ | 
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changeset | 1506 Fetches many specific items in batch from a table. | 
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changeset | 1507 | 
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changeset | 1508 Requires a ``keys`` parameter, which should be a list of dictionaries. | 
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changeset | 1509 Each dictionary should consist of the keys values to specify. | 
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changeset | 1510 | 
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changeset | 1511 Optionally accepts a ``consistent`` parameter, which should be a | 
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changeset | 1512 boolean. If you provide ``True``, a strongly consistent read will be | 
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changeset | 1513 used. (Default: False) | 
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changeset | 1514 | 
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changeset | 1515 Optionally accepts an ``attributes`` parameter, which should be a | 
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changeset | 1516 tuple. If you provide any attributes only these will be fetched | 
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changeset | 1517 from DynamoDB. | 
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changeset | 1518 | 
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changeset | 1519 Returns a ``ResultSet``, which transparently handles the pagination of | 
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changeset | 1520 results you get back. | 
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changeset | 1521 | 
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changeset | 1522 Example:: | 
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changeset | 1523 | 
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changeset | 1524 >>> results = users.batch_get(keys=[ | 
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changeset | 1525 ... { | 
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changeset | 1526 ... 'username': 'johndoe', | 
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changeset | 1527 ... }, | 
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changeset | 1528 ... { | 
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changeset | 1529 ... 'username': 'jane', | 
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changeset | 1530 ... }, | 
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changeset | 1531 ... { | 
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changeset | 1532 ... 'username': 'fred', | 
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changeset | 1533 ... }, | 
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changeset | 1534 ... ]) | 
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changeset | 1535 >>> for res in results: | 
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changeset | 1536 ... print res['first_name'] | 
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changeset | 1537 'John' | 
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changeset | 1538 'Jane' | 
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changeset | 1539 'Fred' | 
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changeset | 1540 | 
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changeset | 1541 """ | 
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changeset | 1542 # We pass the keys to the constructor instead, so it can maintain it's | 
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changeset | 1543 # own internal state as to what keys have been processed. | 
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changeset | 1544 results = BatchGetResultSet(keys=keys, max_batch_get=self.max_batch_get) | 
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changeset | 1545 results.to_call(self._batch_get, consistent=consistent, attributes=attributes) | 
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changeset | 1546 return results | 
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changeset | 1547 | 
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changeset | 1548 def _batch_get(self, keys, consistent=False, attributes=None): | 
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changeset | 1549 """ | 
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changeset | 1550 The internal method that performs the actual batch get. Used extensively | 
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changeset | 1551 by ``BatchGetResultSet`` to perform each (paginated) request. | 
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changeset | 1552 """ | 
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changeset | 1553 items = { | 
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changeset | 1554 self.table_name: { | 
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changeset | 1555 'Keys': [], | 
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changeset | 1556 }, | 
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changeset | 1557 } | 
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changeset | 1558 | 
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changeset | 1559 if consistent: | 
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changeset | 1560 items[self.table_name]['ConsistentRead'] = True | 
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changeset | 1561 | 
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changeset | 1562 if attributes is not None: | 
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changeset | 1563 items[self.table_name]['AttributesToGet'] = attributes | 
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changeset | 1564 | 
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changeset | 1565 for key_data in keys: | 
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changeset | 1566 raw_key = {} | 
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changeset | 1567 | 
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changeset | 1568 for key, value in key_data.items(): | 
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changeset | 1569 raw_key[key] = self._dynamizer.encode(value) | 
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changeset | 1570 | 
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changeset | 1571 items[self.table_name]['Keys'].append(raw_key) | 
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changeset | 1572 | 
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changeset | 1573 raw_results = self.connection.batch_get_item(request_items=items) | 
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changeset | 1574 results = [] | 
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changeset | 1575 unprocessed_keys = [] | 
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changeset | 1576 | 
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changeset | 1577 for raw_item in raw_results['Responses'].get(self.table_name, []): | 
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changeset | 1578 item = Item(self) | 
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changeset | 1579 item.load({ | 
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changeset | 1580 'Item': raw_item, | 
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changeset | 1581 }) | 
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changeset | 1582 results.append(item) | 
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changeset | 1583 | 
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changeset | 1584 raw_unprocessed = raw_results.get('UnprocessedKeys', {}).get(self.table_name, {}) | 
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changeset | 1585 | 
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changeset | 1586 for raw_key in raw_unprocessed.get('Keys', []): | 
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changeset | 1587 py_key = {} | 
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changeset | 1588 | 
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changeset | 1589 for key, value in raw_key.items(): | 
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changeset | 1590 py_key[key] = self._dynamizer.decode(value) | 
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changeset | 1591 | 
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changeset | 1592 unprocessed_keys.append(py_key) | 
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changeset | 1593 | 
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changeset | 1594 return { | 
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changeset | 1595 'results': results, | 
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changeset | 1596 # NEVER return a ``last_key``. Just in-case any part of | 
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changeset | 1597 # ``ResultSet`` peeks through, since much of the | 
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changeset | 1598 # original underlying implementation is based on this key. | 
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changeset | 1599 'last_key': None, | 
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changeset | 1600 'unprocessed_keys': unprocessed_keys, | 
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changeset | 1601 } | 
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changeset | 1602 | 
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changeset | 1603 def count(self): | 
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changeset | 1604 """ | 
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changeset | 1605 Returns a (very) eventually consistent count of the number of items | 
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changeset | 1606 in a table. | 
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changeset | 1607 | 
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changeset | 1608 Lag time is about 6 hours, so don't expect a high degree of accuracy. | 
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changeset | 1609 | 
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changeset | 1610 Example:: | 
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changeset | 1611 | 
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changeset | 1612 >>> users.count() | 
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changeset | 1613 6 | 
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changeset | 1614 | 
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changeset | 1615 """ | 
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changeset | 1616 info = self.describe() | 
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changeset | 1617 return info['Table'].get('ItemCount', 0) | 
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changeset | 1618 | 
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changeset | 1619 | 
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changeset | 1620 class BatchTable(object): | 
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changeset | 1621 """ | 
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changeset | 1622 Used by ``Table`` as the context manager for batch writes. | 
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changeset | 1623 | 
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changeset | 1624 You likely don't want to try to use this object directly. | 
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changeset | 1625 """ | 
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changeset | 1626 def __init__(self, table): | 
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changeset | 1627 self.table = table | 
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changeset | 1628 self._to_put = [] | 
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changeset | 1629 self._to_delete = [] | 
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changeset | 1630 self._unprocessed = [] | 
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changeset | 1631 | 
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changeset | 1632 def __enter__(self): | 
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changeset | 1633 return self | 
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changeset | 1634 | 
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changeset | 1635 def __exit__(self, type, value, traceback): | 
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changeset | 1636 if self._to_put or self._to_delete: | 
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changeset | 1637 # Flush anything that's left. | 
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changeset | 1638 self.flush() | 
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changeset | 1639 | 
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changeset | 1640 if self._unprocessed: | 
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changeset | 1641 # Finally, handle anything that wasn't processed. | 
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changeset | 1642 self.resend_unprocessed() | 
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changeset | 1643 | 
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changeset | 1644 def put_item(self, data, overwrite=False): | 
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changeset | 1645 self._to_put.append(data) | 
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changeset | 1646 | 
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changeset | 1647 if self.should_flush(): | 
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changeset | 1648 self.flush() | 
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changeset | 1649 | 
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changeset | 1650 def delete_item(self, **kwargs): | 
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changeset | 1651 self._to_delete.append(kwargs) | 
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changeset | 1652 | 
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changeset | 1653 if self.should_flush(): | 
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changeset | 1654 self.flush() | 
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changeset | 1655 | 
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changeset | 1656 def should_flush(self): | 
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changeset | 1657 if len(self._to_put) + len(self._to_delete) == 25: | 
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changeset | 1658 return True | 
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changeset | 1659 | 
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changeset | 1660 return False | 
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changeset | 1661 | 
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changeset | 1662 def flush(self): | 
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changeset | 1663 batch_data = { | 
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changeset | 1664 self.table.table_name: [ | 
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changeset | 1665 # We'll insert data here shortly. | 
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changeset | 1666 ], | 
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changeset | 1667 } | 
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changeset | 1668 | 
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changeset | 1669 for put in self._to_put: | 
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changeset | 1670 item = Item(self.table, data=put) | 
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changeset | 1671 batch_data[self.table.table_name].append({ | 
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changeset | 1672 'PutRequest': { | 
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changeset | 1673 'Item': item.prepare_full(), | 
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changeset | 1674 } | 
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changeset | 1675 }) | 
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changeset | 1676 | 
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changeset | 1677 for delete in self._to_delete: | 
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changeset | 1678 batch_data[self.table.table_name].append({ | 
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changeset | 1679 'DeleteRequest': { | 
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changeset | 1680 'Key': self.table._encode_keys(delete), | 
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changeset | 1681 } | 
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changeset | 1682 }) | 
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changeset | 1683 | 
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changeset | 1684 resp = self.table.connection.batch_write_item(batch_data) | 
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changeset | 1685 self.handle_unprocessed(resp) | 
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changeset | 1686 | 
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changeset | 1687 self._to_put = [] | 
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changeset | 1688 self._to_delete = [] | 
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changeset | 1689 return True | 
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changeset | 1690 | 
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changeset | 1691 def handle_unprocessed(self, resp): | 
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changeset | 1692 if len(resp.get('UnprocessedItems', [])): | 
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changeset | 1693 table_name = self.table.table_name | 
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changeset | 1694 unprocessed = resp['UnprocessedItems'].get(table_name, []) | 
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changeset | 1695 | 
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changeset | 1696 # Some items have not been processed. Stow them for now & | 
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changeset | 1697 # re-attempt processing on ``__exit__``. | 
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changeset | 1698 msg = "%s items were unprocessed. Storing for later." | 
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changeset | 1699 boto.log.info(msg % len(unprocessed)) | 
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changeset | 1700 self._unprocessed.extend(unprocessed) | 
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changeset | 1701 | 
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changeset | 1702 def resend_unprocessed(self): | 
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changeset | 1703 # If there are unprocessed records (for instance, the user was over | 
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changeset | 1704 # their throughput limitations), iterate over them & send until they're | 
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changeset | 1705 # all there. | 
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changeset | 1706 boto.log.info( | 
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changeset | 1707 "Re-sending %s unprocessed items." % len(self._unprocessed) | 
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changeset | 1708 ) | 
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changeset | 1709 | 
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changeset | 1710 while len(self._unprocessed): | 
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changeset | 1711 # Again, do 25 at a time. | 
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changeset | 1712 to_resend = self._unprocessed[:25] | 
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changeset | 1713 # Remove them from the list. | 
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changeset | 1714 self._unprocessed = self._unprocessed[25:] | 
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changeset | 1715 batch_data = { | 
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changeset | 1716 self.table.table_name: to_resend | 
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changeset | 1717 } | 
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changeset | 1718 boto.log.info("Sending %s items" % len(to_resend)) | 
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changeset | 1719 resp = self.table.connection.batch_write_item(batch_data) | 
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changeset | 1720 self.handle_unprocessed(resp) | 
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changeset | 1721 boto.log.info( | 
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changeset | 1722 "%s unprocessed items left" % len(self._unprocessed) | 
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changeset | 1723 ) | 
