For more information, see the documentation for boto3.

Boto3 , the next version of Boto, is now stable and recommended for general use. It can be used side-by-side with Boto in the same project, so it is easy to start using Boto3 in your existing projects as well as new projects. Going forward, API updates and all new feature work will be focused on Boto3.

You are viewing the documentation for an older version of boto (boto2).

An Introduction to boto’s DynamoDB interface¶

This tutorial focuses on the boto interface to AWS’ DynamoDB. This tutorial assumes that you have boto already downloaded and installed.

Warning This tutorial covers the ORIGINAL release of DynamoDB. It has since been supplanted by a second major version & an updated API to talk to the new version. The documentation for the new version of DynamoDB (& boto’s support for it) is at DynamoDB v2.

Creating a Connection¶ The first step in accessing DynamoDB is to create a connection to the service. To do so, the most straight forward way is the following: >>> import boto.dynamodb >>> conn = boto . dynamodb . connect_to_region ( 'us-west-2', aws_access_key_id='<YOUR_AWS_KEY_ID>', aws_secret_access_key='<YOUR_AWS_SECRET_KEY>') >>> conn <boto.dynamodb.layer2.Layer2 object at 0x3fb3090> Bear in mind that if you have your credentials in boto config in your home directory, the two keyword arguments in the call above are not needed. More details on configuration can be found in Boto Config. The boto.dynamodb.connect_to_region() function returns a boto.dynamodb.layer2.Layer2 instance, which is a high-level API for working with DynamoDB. Layer2 is a set of abstractions that sit atop the lower level boto.dynamodb.layer1.Layer1 API, which closely mirrors the Amazon DynamoDB API. For the purpose of this tutorial, we’ll just be covering Layer2.

Listing Tables¶ Now that we have a DynamoDB connection object, we can then query for a list of existing tables in that region: >>> conn . list_tables () ['test-table', 'another-table']

Creating Tables¶ DynamoDB tables are created with the Layer2.create_table method. While DynamoDB’s items (a rough equivalent to a relational DB’s row) don’t have a fixed schema, you do need to create a schema for the table’s hash key element, and the optional range key element. This is explained in greater detail in DynamoDB’s Data Model documentation. We’ll start by defining a schema that has a hash key and a range key that are both strings: >>> message_table_schema = conn . create_schema ( hash_key_name='forum_name', hash_key_proto_value=str, range_key_name='subject', range_key_proto_value=str ) The next few things to determine are table name and read/write throughput. We’ll defer explaining throughput to the DynamoDB’s Provisioned Throughput docs. We’re now ready to create the table: >>> table = conn . create_table ( name='messages', schema=message_table_schema, read_units=10, write_units=10 ) >>> table Table(messages) This returns a boto.dynamodb.table.Table instance, which provides simple ways to create (put), update, and delete items.

Getting a Table¶ To retrieve an existing table, use Layer2.get_table : >>> conn . list_tables () ['test-table', 'another-table', 'messages'] >>> table = conn . get_table ( 'messages' ) >>> table Table(messages) Layer2.get_table , like Layer2.create_table , returns a boto.dynamodb.table.Table instance. Keep in mind that Layer2.get_table will make an API call to retrieve various attributes of the table including the creation time, the read and write capacity, and the table schema. If you already know the schema, you can save an API call and create a boto.dynamodb.table.Table object without making any calls to Amazon DynamoDB: >>> table = conn . table_from_schema ( name='messages', schema=message_table_schema) If you do this, the following fields will have None values: create_time

status

read_units

write_units In addition, the item_count and size_bytes will be 0. If you create a table object directly from a schema object and decide later that you need to retrieve any of these additional attributes, you can use the Table.refresh method: >>> from boto.dynamodb.schema import Schema >>> table = conn . table_from_schema ( name='messages', schema=Schema.create(hash_key=('forum_name', 'S'), range_key=('subject', 'S'))) >>> print table . write_units None >>> # Now we decide we need to know the write_units: >>> table . refresh () >>> print table . write_units 10 The recommended best practice is to retrieve a table object once and use that object for the duration of your application. So, for example, instead of this: class Application ( object ): def __init__ ( self , layer2 ): self . _layer2 = layer2 def retrieve_item ( self , table_name , key ): return self . _layer2 . get_table ( table_name ) . get_item ( key ) You can do something like this instead: class Application ( object ): def __init__ ( self , layer2 ): self . _layer2 = layer2 self . _tables_by_name = {} def retrieve_item ( self , table_name , key ): table = self . _tables_by_name . get ( table_name ) if table is None : table = self . _layer2 . get_table ( table_name ) self . _tables_by_name [ table_name ] = table return table . get_item ( key )

Describing Tables¶ To get a complete description of a table, use Layer2.describe_table : >>> conn . list_tables () ['test-table', 'another-table', 'messages'] >>> conn . describe_table ( 'messages' ) { 'Table': { 'CreationDateTime': 1327117581.624, 'ItemCount': 0, 'KeySchema': { 'HashKeyElement': { 'AttributeName': 'forum_name', 'AttributeType': 'S' }, 'RangeKeyElement': { 'AttributeName': 'subject', 'AttributeType': 'S' } }, 'ProvisionedThroughput': { 'ReadCapacityUnits': 10, 'WriteCapacityUnits': 10 }, 'TableName': 'messages', 'TableSizeBytes': 0, 'TableStatus': 'ACTIVE' } }

Adding Items¶ Continuing on with our previously created messages table, adding an: >>> table = conn . get_table ( 'messages' ) >>> item_data = { 'Body': 'http://url_to_lolcat.gif', 'SentBy': 'User A', 'ReceivedTime': '12/9/2011 11:36:03 PM', } >>> item = table . new_item ( # Our hash key is 'forum' hash_key='LOLCat Forum', # Our range key is 'subject' range_key='Check this out!', # This has the attrs=item_data ) The Table.new_item method creates a new boto.dynamodb.item.Item instance with your specified hash key, range key, and attributes already set. Item is a dict sub-class, meaning you can edit your data as such: item [ 'a_new_key' ] = 'testing' del item [ 'a_new_key' ] After you are happy with the contents of the item, use Item.put to commit it to DynamoDB: >>> item . put ()

Retrieving Items¶ Now, let’s check if it got added correctly. Since DynamoDB works under an ‘eventual consistency’ mode, we need to specify that we wish a consistent read, as follows: >>> table = conn . get_table ( 'messages' ) >>> item = table . get_item ( # Your hash key was 'forum_name' hash_key='LOLCat Forum', # Your range key was 'subject' range_key='Check this out!' ) >>> item { # Note that this was your hash key attribute (forum_name) 'forum_name': 'LOLCat Forum', # This is your range key attribute (subject) 'subject': 'Check this out!' 'Body': 'http://url_to_lolcat.gif', 'ReceivedTime': '12/9/2011 11:36:03 PM', 'SentBy': 'User A', }

Updating Items¶ To update an item’s attributes, simply retrieve it, modify the value, then Item.put it again: >>> table = conn . get_table ( 'messages' ) >>> item = table . get_item ( hash_key='LOLCat Forum', range_key='Check this out!' ) >>> item [ 'SentBy' ] = 'User B' >>> item . put ()

Working with Decimals¶ To avoid the loss of precision, you can stipulate that the decimal.Decimal type be used for numeric values: >>> import decimal >>> conn . use_decimals () >>> table = conn . get_table ( 'messages' ) >>> item = table . new_item ( hash_key='LOLCat Forum', range_key='Check this out!' ) >>> item [ 'decimal_type' ] = decimal . Decimal ( '1.12345678912345' ) >>> item . put () >>> print table . get_item ( 'LOLCat Forum' , 'Check this out!' ) {u'forum_name': 'LOLCat Forum', u'decimal_type': Decimal('1.12345678912345'), u'subject': 'Check this out!'} You can enable the usage of decimal.Decimal by using either the use_decimals method, or by passing in the Dynamizer class for the dynamizer param: >>> from boto.dynamodb.types import Dynamizer >>> conn = boto . dynamodb . connect_to_region ( dynamizer = Dynamizer ) This mechanism can also be used if you want to customize the encoding/decoding process of DynamoDB types.

Deleting Items¶ To delete items, use the Item.delete method: >>> table = conn . get_table ( 'messages' ) >>> item = table . get_item ( hash_key='LOLCat Forum', range_key='Check this out!' ) >>> item . delete ()