An index signifying all fields should be in the index.
Example:
>>> AllIndex('MostRecentlyJoined', parts=[
... HashKey('username'),
... RangeKey('date_joined')
... ])
An abstract class for defining schema indexes.
Contains most of the core functionality for the index. Subclasses must define a projection_type to pass to DynamoDB.
Returns the attribute definition structure DynamoDB expects.
Example:
>>> index.definition()
{
'AttributeName': 'username',
'AttributeType': 'S',
}
Returns the schema structure DynamoDB expects.
Example:
>>> index.schema()
{
'IndexName': 'LastNameIndex',
'KeySchema': [
{
'AttributeName': 'username',
'KeyType': 'HASH',
},
],
'Projection': {
'ProjectionType': 'KEYS_ONLY',
}
}
An abstract class for defining schema fields.
Contains most of the core functionality for the field. Subclasses must define an attr_type to pass to DynamoDB.
Creates a Python schema field, to represent the data to pass to DynamoDB.
Requires a name parameter, which should be a string name of the field.
Optionally accepts a data_type parameter, which should be a constant from boto.dynamodb2.types. (Default: STRING)
Returns the attribute definition structure DynamoDB expects.
Example:
>>> field.definition()
{
'AttributeName': 'username',
'AttributeType': 'S',
}
Returns the schema structure DynamoDB expects.
Example:
>>> field.schema()
{
'AttributeName': 'username',
'KeyType': 'HASH',
}
An index signifying all fields should be in the index.
Example:
>>> GlobalAllIndex('MostRecentlyJoined', parts=[
... HashKey('username'),
... RangeKey('date_joined')
... ],
... throughput={
... 'read': 2,
... 'write': 1,
... })
An abstract class for defining global indexes.
Contains most of the core functionality for the index. Subclasses must define a projection_type to pass to DynamoDB.
Returns the schema structure DynamoDB expects.
Example:
>>> index.schema()
{
'IndexName': 'LastNameIndex',
'KeySchema': [
{
'AttributeName': 'username',
'KeyType': 'HASH',
},
],
'Projection': {
'ProjectionType': 'KEYS_ONLY',
},
'ProvisionedThroughput': {
'ReadCapacityUnits': 5,
'WriteCapacityUnits': 5
}
}
An index signifying only certain fields should be in the index.
Example:
>>> GlobalIncludeIndex('GenderIndex', parts=[
... HashKey('username'),
... RangeKey('date_joined')
... ],
... includes=['gender'],
... throughput={
... 'read': 2,
... 'write': 1,
... })
An index signifying only key fields should be in the index.
Example:
>>> GlobalKeysOnlyIndex('MostRecentlyJoined', parts=[
... HashKey('username'),
... RangeKey('date_joined')
... ],
... throughput={
... 'read': 2,
... 'write': 1,
... })
An field representing a hash key.
Example:
>>> from boto.dynamodb2.types import NUMBER
>>> HashKey('username')
>>> HashKey('date_joined', data_type=NUMBER)
Creates a Python schema field, to represent the data to pass to DynamoDB.
Requires a name parameter, which should be a string name of the field.
Optionally accepts a data_type parameter, which should be a constant from boto.dynamodb2.types. (Default: STRING)
An index signifying only certain fields should be in the index.
Example:
>>> IncludeIndex('GenderIndex', parts=[
... HashKey('username'),
... RangeKey('date_joined')
... ], includes=['gender'])
An index signifying only key fields should be in the index.
Example:
>>> KeysOnlyIndex('MostRecentlyJoined', parts=[
... HashKey('username'),
... RangeKey('date_joined')
... ])
An field representing a range key.
Example:
>>> from boto.dynamodb2.types import NUMBER
>>> HashKey('username')
>>> HashKey('date_joined', data_type=NUMBER)
Creates a Python schema field, to represent the data to pass to DynamoDB.
Requires a name parameter, which should be a string name of the field.
Optionally accepts a data_type parameter, which should be a constant from boto.dynamodb2.types. (Default: STRING)
An object representing the item data within a DynamoDB table.
An item is largely schema-free, meaning it can contain any data. The only limitation is that it must have data for the fields in the Table‘s schema.
This object presents a dictionary-like interface for accessing/storing data. It also tries to intelligently track how data has changed throughout the life of the instance, to be as efficient as possible about updates.
Empty items, or items that have no data, are considered falsey.
Constructs an (unsaved) Item instance.
To persist the data in DynamoDB, you’ll need to call the Item.save (or Item.partial_save) on the instance.
Requires a table parameter, which should be a Table instance. This is required, as DynamoDB’s API is focus around all operations being table-level. It’s also for persisting schema around many objects.
Optionally accepts a data parameter, which should be a dictionary of the fields & values of the item.
Optionally accepts a loaded parameter, which should be a boolean. True if it was preexisting data loaded from DynamoDB, False if it’s new data from the user. Default is False.
Example:
>>> users = Table('users')
>>> user = Item(users, data={
... 'username': 'johndoe',
... 'first_name': 'John',
... 'date_joined': 1248o61592,
... })
# Change existing data.
>>> user['first_name'] = 'Johann'
# Add more data.
>>> user['last_name'] = 'Doe'
# Delete data.
>>> del user['date_joined']
# Iterate over all the data.
>>> for field, val in user.items():
... print "%s: %s" % (field, val)
username: johndoe
first_name: John
date_joined: 1248o61592
Builds up a list of expecations to hand off to DynamoDB on save.
Largely internal.
Deletes the item’s data to DynamoDB.
Returns True on success.
Example:
# Buh-bye now.
>>> user.delete()
Returns a Python-style dict of the keys/values.
Largely internal.
Returns a DynamoDB-style dict of the keys/values.
Largely internal.
This is only useful when being handed raw data from DynamoDB directly. If you have a Python datastructure already, use the __init__ or manually set the data instead.
Largely internal, unless you know what you’re doing or are trying to mix the low-level & high-level APIs.
Marks an Item instance as no longer needing to be saved.
Example:
>>> user.needs_save()
False
>>> user['first_name'] = 'Johann'
>>> user.needs_save()
True
>>> user.mark_clean()
>>> user.needs_save()
False
DEPRECATED: Marks an Item instance as needing to be saved.
This method is no longer necessary, as the state tracking on Item has been improved to automatically detect proper state.
Returns whether or not the data has changed on the Item.
Optionally accepts a data argument, which accepts the output from self._determine_alterations() if you’ve already called it. Typically unnecessary to do. Default is None.
Example:
>>> user.needs_save()
False
>>> user['first_name'] = 'Johann'
>>> user.needs_save()
True
Saves only the changed data to DynamoDB.
Extremely useful for high-volume/high-write data sets, this allows you to update only a handful of fields rather than having to push entire items. This prevents many accidental overwrite situations as well as saves on the amount of data to transfer over the wire.
Returns True on success, False if no save was performed or the write failed.
Example:
>>> user['last_name'] = 'Doh!'
# Only the last name field will be sent to DynamoDB.
>>> user.partial_save()
Runs through all fields & encodes them to be handed off to DynamoDB as part of an save (put_item) call.
Largely internal.
Runs through ONLY the changed/deleted fields & encodes them to be handed off to DynamoDB as part of an partial_save (update_item) call.
Largely internal.
Saves all data to DynamoDB.
By default, this attempts to ensure that none of the underlying data has changed. If any fields have changed in between when the Item was constructed & when it is saved, this call will fail so as not to cause any data loss.
If you’re sure possibly overwriting data is acceptable, you can pass an overwrite=True. If that’s not acceptable, you may be able to use Item.partial_save to only write the changed field data.
Optionally accepts an overwrite parameter, which should be a boolean. If you provide True, the item will be forcibly overwritten within DynamoDB, even if another process changed the data in the meantime. (Default: False)
Returns True on success, False if no save was performed.
Example:
>>> user['last_name'] = 'Doh!'
# All data on the Item is sent to DynamoDB.
>>> user.save()
# If it fails, you can overwrite.
>>> user.save(overwrite=True)
A class used to lazily handle page-to-page navigation through a set of results.
It presents a transparent iterator interface, so that all the user has to do is use it in a typical for loop (or list comprehension, etc.) to fetch results, even if they weren’t present in the current page of results.
This is used by the Table.query & Table.scan methods.
Example:
>>> users = Table('users')
>>> results = ResultSet()
>>> results.to_call(users.query, username__gte='johndoe')
# Now iterate. When it runs out of results, it'll fetch the next page.
>>> for res in results:
... print res['username']
When the iterator runs out of results, this method is run to re-execute the callable (& arguments) to fetch the next page.
Largely internal.
Sets up the callable & any arguments to run it with.
This is stored for subsequent calls so that those queries can be run without requiring user intervention.
Example:
# Just an example callable.
>>> def squares_to(y):
... for x in range(1, y):
... yield x**2
>>> rs = ResultSet()
# Set up what to call & arguments.
>>> rs.to_call(squares_to, y=3)
Used by Table as the context manager for batch writes.
You likely don’t want to try to use this object directly.
Interacts & models the behavior of a DynamoDB table.
The Table object represents a set (or rough categorization) of records within DynamoDB. The important part is that all records within the table, while largely-schema-free, share the same schema & are essentially namespaced for use in your application. For example, you might have a users table or a forums table.
Sets up a new in-memory Table.
This is useful if the table already exists within DynamoDB & you simply want to use it for additional interactions. The only required parameter is the table_name. However, under the hood, the object will call describe_table to determine the schema/indexes/throughput. You can avoid this extra call by passing in schema & indexes.
IMPORTANT - If you’re creating a new Table for the first time, you should use the Table.create method instead, as it will persist the table structure to DynamoDB.
Requires a table_name parameter, which should be a simple string of the name of the table.
Optionally accepts a schema parameter, which should be a list of BaseSchemaField subclasses representing the desired schema.
Optionally accepts a throughput parameter, which should be a dictionary. If provided, it should specify a read & write key, both of which should have an integer value associated with them.
Optionally accepts a indexes parameter, which should be a list of BaseIndexField subclasses representing the desired indexes.
Optionally accepts a global_indexes parameter, which should be a list of GlobalBaseIndexField subclasses representing the desired indexes.
Optionally accepts a connection parameter, which should be a DynamoDBConnection instance (or subclass). This is primarily useful for specifying alternate connection parameters.
Example:
# The simple, it-already-exists case.
>>> conn = Table('users')
# The full, minimum-extra-calls case.
>>> from boto import dynamodb2
>>> users = Table('users', schema=[
... HashKey('username'),
... RangeKey('date_joined', data_type=NUMBER)
... ], throughput={
... 'read':20,
... 'write': 10,
... }, indexes=[
... KeysOnlyIndex('MostRecentlyJoined', parts=[
... HashKey('username')
... RangeKey('date_joined')
... ]),
... ], global_indexes=[
... GlobalAllIndex('UsersByZipcode', parts=[
... HashKey('zipcode'),
... RangeKey('username'),
... ],
... throughput={
... 'read':10,
... 'write":10,
... }),
... ], connection=dynamodb2.connect_to_region('us-west-2',
... aws_access_key_id='key',
... aws_secret_access_key='key',
... ))
Fetches many specific items in batch from a table.
Requires a keys parameter, which should be a list of dictionaries. Each dictionary should consist of the keys values to specify.
Optionally accepts a consistent parameter, which should be a boolean. If you provide True, a strongly consistent read will be used. (Default: False)
Optionally accepts an attributes parameter, which should be a tuple. If you provide any attributes only these will be fetched from DynamoDB.
Returns a ResultSet, which transparently handles the pagination of results you get back.
Example:
>>> results = users.batch_get(keys=[
... {
... 'username': 'johndoe',
... },
... {
... 'username': 'jane',
... },
... {
... 'username': 'fred',
... },
... ])
>>> for res in results:
... print res['first_name']
'John'
'Jane'
'Fred'
Allows the batching of writes to DynamoDB.
Since each write/delete call to DynamoDB has a cost associated with it, when loading lots of data, it makes sense to batch them, creating as few calls as possible.
This returns a context manager that will transparently handle creating these batches. The object you get back lightly-resembles a Table object, sharing just the put_item & delete_item methods (which are all that DynamoDB can batch in terms of writing data).
DynamoDB’s maximum batch size is 25 items per request. If you attempt to put/delete more than that, the context manager will batch as many as it can up to that number, then flush them to DynamoDB & continue batching as more calls come in.
Example:
# Assuming a table with one record...
>>> with users.batch_write() as batch:
... batch.put_item(data={
... 'username': 'johndoe',
... 'first_name': 'John',
... 'last_name': 'Doe',
... 'owner': 1,
... })
... # Nothing across the wire yet.
... batch.delete_item(username='bob')
... # Still no requests sent.
... batch.put_item(data={
... 'username': 'jane',
... 'first_name': 'Jane',
... 'last_name': 'Doe',
... 'date_joined': 127436192,
... })
... # Nothing yet, but once we leave the context, the
... # put/deletes will be sent.
Returns a (very) eventually consistent count of the number of items in a table.
Lag time is about 6 hours, so don’t expect a high degree of accuracy.
Example:
>>> users.count()
6
Creates a new table in DynamoDB & returns an in-memory Table object.
This will setup a brand new table within DynamoDB. The table_name must be unique for your AWS account. The schema is also required to define the key structure of the table.
IMPORTANT - You should consider the usage pattern of your table up-front, as the schema & indexes can NOT be modified once the table is created, requiring the creation of a new table & migrating the data should you wish to revise it.
IMPORTANT - If the table already exists in DynamoDB, additional calls to this method will result in an error. If you just need a Table object to interact with the existing table, you should just initialize a new Table object, which requires only the table_name.
Requires a table_name parameter, which should be a simple string of the name of the table.
Requires a schema parameter, which should be a list of BaseSchemaField subclasses representing the desired schema.
Optionally accepts a throughput parameter, which should be a dictionary. If provided, it should specify a read & write key, both of which should have an integer value associated with them.
Optionally accepts a indexes parameter, which should be a list of BaseIndexField subclasses representing the desired indexes.
Optionally accepts a global_indexes parameter, which should be a list of GlobalBaseIndexField subclasses representing the desired indexes.
Optionally accepts a connection parameter, which should be a DynamoDBConnection instance (or subclass). This is primarily useful for specifying alternate connection parameters.
Example:
>>> users = Table.create('users', schema=[
... HashKey('username'),
... RangeKey('date_joined', data_type=NUMBER)
... ], throughput={
... 'read':20,
... 'write': 10,
... }, indexes=[
... KeysOnlyIndex('MostRecentlyJoined', parts=[
... RangeKey('date_joined')
... ]), global_indexes=[
... GlobalAllIndex('UsersByZipcode', parts=[
... HashKey('zipcode'),
... RangeKey('username'),
... ],
... throughput={
... 'read':10,
... 'write':10,
... }),
... ])
Deletes a table in DynamoDB.
IMPORTANT - Be careful when using this method, there is no undo.
Returns True on success.
Example:
>>> users.delete()
True
Deletes a single item. You can perform a conditional delete operation that deletes the item if it exists, or if it has an expected attribute value.
Conditional deletes are useful for only deleting items if specific conditions are met. If those conditions are met, DynamoDB performs the delete. Otherwise, the item is not deleted.
To specify the expected attribute values of the item, you can pass a dictionary of conditions to expected. Each condition should follow the pattern <attributename>__<comparison_operator>=<value_to_expect>.
IMPORTANT - Be careful when using this method, there is no undo.
To specify the key of the item you’d like to get, you can specify the key attributes as kwargs.
Optionally accepts an expected parameter which is a dictionary of expected attribute value conditions.
Optionally accepts a conditional_operator which applies to the expected attribute value conditions:
Returns True on success, False on failed conditional delete.
Example:
# A simple hash key.
>>> users.delete_item(username='johndoe')
True
# A complex hash+range key.
>>> users.delete_item(username='jane', last_name='Doe')
True
# With a key that is an invalid variable name in Python.
# Also, assumes a different schema than previous examples.
>>> users.delete_item(**{
... 'date-joined': 127549192,
... })
True
# Conditional delete
>>> users.delete_item(username='johndoe',
... expected={'balance__eq': 0})
True
Describes the current structure of the table in DynamoDB.
This information will be used to update the schema, indexes and throughput information on the Table. Some calls, such as those involving creating keys or querying, will require this information to be populated.
It also returns the full raw datastructure from DynamoDB, in the event you’d like to parse out additional information (such as the ItemCount or usage information).
Example:
>>> users.describe()
{
# Lots of keys here...
}
>>> len(users.schema)
2
Fetches an item (record) from a table in DynamoDB.
To specify the key of the item you’d like to get, you can specify the key attributes as kwargs.
Optionally accepts a consistent parameter, which should be a boolean. If you provide True, it will perform a consistent (but more expensive) read from DynamoDB. (Default: False)
Optionally accepts an attributes parameter, which should be a list of fieldname to fetch. (Default: None, which means all fields should be fetched)
Returns an Item instance containing all the data for that record.
Raises an ItemNotFound exception if the item is not found.
Example:
# A simple hash key.
>>> john = users.get_item(username='johndoe')
>>> john['first_name']
'John'
# A complex hash+range key.
>>> john = users.get_item(username='johndoe', last_name='Doe')
>>> john['first_name']
'John'
# A consistent read (assuming the data might have just changed).
>>> john = users.get_item(username='johndoe', consistent=True)
>>> john['first_name']
'Johann'
# With a key that is an invalid variable name in Python.
# Also, assumes a different schema than previous examples.
>>> john = users.get_item(**{
... 'date-joined': 127549192,
... })
>>> john['first_name']
'John'
Returns the fields necessary to make a key for a table.
If the Table does not already have a populated schema, this will request it via a Table.describe call.
Returns a list of fieldnames (strings).
Example:
# A simple hash key.
>>> users.get_key_fields()
['username']
# A complex hash+range key.
>>> users.get_key_fields()
['username', 'last_name']
Return whether an item (record) exists within a table in DynamoDB.
To specify the key of the item you’d like to get, you can specify the key attributes as kwargs.
Optionally accepts a consistent parameter, which should be a boolean. If you provide True, it will perform a consistent (but more expensive) read from DynamoDB. (Default: False)
Optionally accepts an attributes parameter, which should be a list of fieldnames to fetch. (Default: None, which means all fields should be fetched)
Returns True if an Item is present, False if not.
Example:
# Simple, just hash-key schema.
>>> users.has_item(username='johndoe')
True
# Complex schema, item not present.
>>> users.has_item(
... username='johndoe',
... date_joined='2014-01-07'
... )
False
Look up an entry in DynamoDB. This is mostly backwards compatible with boto.dynamodb. Unlike get_item, it takes hash_key and range_key first, although you may still specify keyword arguments instead.
Also unlike the get_item command, if the returned item has no keys (i.e., it does not exist in DynamoDB), a None result is returned, instead of an empty key object.
>>> user = users.lookup(username)
>>> user = users.lookup(username, consistent=True)
>>> app = apps.lookup('my_customer_id', 'my_app_id')
Returns a new, blank item
This is mostly for consistency with boto.dynamodb
Saves an entire item to DynamoDB.
By default, if any part of the Item‘s original data doesn’t match what’s currently in DynamoDB, this request will fail. This prevents other processes from updating the data in between when you read the item & when your request to update the item’s data is processed, which would typically result in some data loss.
Requires a data parameter, which should be a dictionary of the data you’d like to store in DynamoDB.
Optionally accepts an overwrite parameter, which should be a boolean. If you provide True, this will tell DynamoDB to blindly overwrite whatever data is present, if any.
Returns True on success.
Example:
>>> users.put_item(data={
... 'username': 'jane',
... 'first_name': 'Jane',
... 'last_name': 'Doe',
... 'date_joined': 126478915,
... })
True
WARNING: This method is provided strictly for backward-compatibility. It returns results in an incorrect order.
If you are writing new code, please use Table.query_2.
Queries for a set of matching items in a DynamoDB table.
Queries can be performed against a hash key, a hash+range key or against any data stored in your local secondary indexes. Query filters can be used to filter on arbitrary fields.
Note - You can not query against arbitrary fields within the data stored in DynamoDB unless you specify query_filter values.
To specify the filters of the items you’d like to get, you can specify the filters as kwargs. Each filter kwarg should follow the pattern <fieldname>__<filter_operation>=<value_to_look_for>. Query filters are specified in the same way.
Optionally accepts a limit parameter, which should be an integer count of the total number of items to return. (Default: None - all results)
Optionally accepts an index parameter, which should be a string of name of the local secondary index you want to query against. (Default: None)
Optionally accepts a reverse parameter, which will present the results in reverse order. (Default: False - normal order)
Optionally accepts a consistent parameter, which should be a boolean. If you provide True, it will force a consistent read of the data (more expensive). (Default: False - use eventually consistent reads)
Optionally accepts a attributes parameter, which should be a tuple. If you provide any attributes only these will be fetched from DynamoDB. This uses the AttributesToGet and set’s Select to SPECIFIC_ATTRIBUTES API.
Optionally accepts a max_page_size parameter, which should be an integer count of the maximum number of items to retrieve per-request. This is useful in making faster requests & prevent the scan from drowning out other queries. (Default: None - fetch as many as DynamoDB will return)
Optionally accepts a query_filter which is a dictionary of filter conditions against any arbitrary field in the returned data.
Optionally accepts a conditional_operator which applies to the query filter conditions:
Returns a ResultSet, which transparently handles the pagination of results you get back.
Example:
# Look for last names equal to "Doe".
>>> results = users.query(last_name__eq='Doe')
>>> for res in results:
... print res['first_name']
'John'
'Jane'
# Look for last names beginning with "D", in reverse order, limit 3.
>>> results = users.query(
... last_name__beginswith='D',
... reverse=True,
... limit=3
... )
>>> for res in results:
... print res['first_name']
'Alice'
'Jane'
'John'
# Use an LSI & a consistent read.
>>> results = users.query(
... date_joined__gte=1236451000,
... owner__eq=1,
... index='DateJoinedIndex',
... consistent=True
... )
>>> for res in results:
... print res['first_name']
'Alice'
'Bob'
'John'
'Fred'
# Filter by non-indexed field(s)
>>> results = users.query(
... last_name__eq='Doe',
... reverse=True,
... query_filter={
... 'first_name__beginswith': 'A'
... }
... )
>>> for res in results:
... print res['first_name'] + ' ' + res['last_name']
'Alice Doe'
Queries the exact count of matching items in a DynamoDB table.
Queries can be performed against a hash key, a hash+range key or against any data stored in your local secondary indexes. Query filters can be used to filter on arbitrary fields.
To specify the filters of the items you’d like to get, you can specify the filters as kwargs. Each filter kwarg should follow the pattern <fieldname>__<filter_operation>=<value_to_look_for>. Query filters are specified in the same way.
Optionally accepts an index parameter, which should be a string of name of the local secondary index you want to query against. (Default: None)
Optionally accepts a consistent parameter, which should be a boolean. If you provide True, it will force a consistent read of the data (more expensive). (Default: False - use eventually consistent reads)
Optionally accepts a query_filter which is a dictionary of filter conditions against any arbitrary field in the returned data.
Optionally accepts a conditional_operator which applies to the query filter conditions:
Returns an integer which represents the exact amount of matched items.
| Parameters: | scan_index_forward (boolean) – Specifies ascending (true) or descending (false) traversal of the index. DynamoDB returns results reflecting the requested order determined by the range key. If the data type is Number, the results are returned in numeric order. For String, the results are returned in order of ASCII character code values. For Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values. |
|---|
| Parameters: | limit (integer) – The maximum number of items to evaluate (not necessarily the number of matching items). |
|---|
Example:
# Look for last names equal to "Doe".
>>> users.query_count(last_name__eq='Doe')
5
# Use an LSI & a consistent read.
>>> users.query_count(
... date_joined__gte=1236451000,
... owner__eq=1,
... index='DateJoinedIndex',
... consistent=True
... )
2
Scans across all items within a DynamoDB table.
Scans can be performed against a hash key or a hash+range key. You can additionally filter the results after the table has been read but before the response is returned by using query filters.
To specify the filters of the items you’d like to get, you can specify the filters as kwargs. Each filter kwarg should follow the pattern <fieldname>__<filter_operation>=<value_to_look_for>.
Optionally accepts a limit parameter, which should be an integer count of the total number of items to return. (Default: None - all results)
Optionally accepts a segment parameter, which should be an integer of the segment to retrieve on. Please see the documentation about Parallel Scans (Default: None - no segments)
Optionally accepts a total_segments parameter, which should be an integer count of number of segments to divide the table into. Please see the documentation about Parallel Scans (Default: None - no segments)
Optionally accepts a max_page_size parameter, which should be an integer count of the maximum number of items to retrieve per-request. This is useful in making faster requests & prevent the scan from drowning out other queries. (Default: None - fetch as many as DynamoDB will return)
Optionally accepts an attributes parameter, which should be a tuple. If you provide any attributes only these will be fetched from DynamoDB. This uses the AttributesToGet and set’s Select to SPECIFIC_ATTRIBUTES API.
Returns a ResultSet, which transparently handles the pagination of results you get back.
Example:
# All results.
>>> everything = users.scan()
# Look for last names beginning with "D".
>>> results = users.scan(last_name__beginswith='D')
>>> for res in results:
... print res['first_name']
'Alice'
'John'
'Jane'
# Use an ``IN`` filter & limit.
>>> results = users.scan(
... age__in=[25, 26, 27, 28, 29],
... limit=1
... )
>>> for res in results:
... print res['first_name']
'Alice'
Updates table attributes in DynamoDB.
Currently, the only thing you can modify about a table after it has been created is the throughput.
Requires a throughput parameter, which should be a dictionary. If provided, it should specify a read & write key, both of which should have an integer value associated with them.
Returns True on success.
Example:
# For a read-heavier application...
>>> users.update(throughput={
... 'read': 20,
... 'write': 10,
... })
True
# To also update the global index(es) throughput.
>>> users.update(throughput={
... 'read': 20,
... 'write': 10,
... },
... global_secondary_indexes={
... 'TheIndexNameHere': {
... 'read': 15,
... 'write': 5,
... }
... })
True
Get all available regions for the Amazon DynamoDB service.
| Return type: | list |
|---|---|
| Returns: | A list of boto.regioninfo.RegionInfo |
Amazon DynamoDB Overview This is the Amazon DynamoDB API Reference. This guide provides descriptions and samples of the low-level DynamoDB API. For information about DynamoDB application development, go to the `Amazon DynamoDB Developer Guide`_.
Instead of making the requests to the low-level DynamoDB API directly from your application, we recommend that you use the AWS Software Development Kits (SDKs). The easy-to-use libraries in the AWS SDKs make it unnecessary to call the low-level DynamoDB API directly from your application. The libraries take care of request authentication, serialization, and connection management. For more information, go to `Using the AWS SDKs with DynamoDB`_ in the Amazon DynamoDB Developer Guide .
If you decide to code against the low-level DynamoDB API directly, you will need to write the necessary code to authenticate your requests. For more information on signing your requests, go to `Using the DynamoDB API`_ in the Amazon DynamoDB Developer Guide .
The following are short descriptions of each low-level API action, organized by function.
Managing Tables
For conceptual information about managing tables, go to `Working with Tables`_ in the Amazon DynamoDB Developer Guide .
Reading Data
For conceptual information about reading data, go to `Working with Items`_ and `Query and Scan Operations`_ in the Amazon DynamoDB Developer Guide .
Modifying Data
For conceptual information about modifying data, go to `Working with Items`_ and `Query and Scan Operations`_ in the Amazon DynamoDB Developer Guide .
alias of JSONResponseError
The BatchGetItem operation returns the attributes of one or more items from one or more tables. You identify requested items by primary key.
A single operation can retrieve up to 16 MB of data, which can contain as many as 100 items. BatchGetItem will return a partial result if the response size limit is exceeded, the table’s provisioned throughput is exceeded, or an internal processing failure occurs. If a partial result is returned, the operation returns a value for UnprocessedKeys . You can use this value to retry the operation starting with the next item to get.
For example, if you ask to retrieve 100 items, but each individual item is 300 KB in size, the system returns 52 items (so as not to exceed the 16 MB limit). It also returns an appropriate UnprocessedKeys value so you can get the next page of results. If desired, your application can include its own logic to assemble the pages of results into one data set.
If none of the items can be processed due to insufficient provisioned throughput on all of the tables in the request, then BatchGetItem will return a ProvisionedThroughputExceededException . If at least one of the items is successfully processed, then BatchGetItem completes successfully, while returning the keys of the unread items in UnprocessedKeys .
If DynamoDB returns any unprocessed items, you should retry the batch operation on those items. However, we strongly recommend that you use an exponential backoff algorithm . If you retry the batch operation immediately, the underlying read or write requests can still fail due to throttling on the individual tables. If you delay the batch operation using exponential backoff, the individual requests in the batch are much more likely to succeed.
For more information, go to `Batch Operations and Error Handling`_ in the Amazon DynamoDB Developer Guide .
By default, BatchGetItem performs eventually consistent reads on every table in the request. If you want strongly consistent reads instead, you can set ConsistentRead to True for any or all tables.
In order to minimize response latency, BatchGetItem retrieves items in parallel.
When designing your application, keep in mind that DynamoDB does not return attributes in any particular order. To help parse the response by item, include the primary key values for the items in your request in the AttributesToGet parameter.
If a requested item does not exist, it is not returned in the result. Requests for nonexistent items consume the minimum read capacity units according to the type of read. For more information, see `Capacity Units Calculations`_ in the Amazon DynamoDB Developer Guide .
| Parameters: | request_items (map) – |
|---|
Each element in the map consists of the following:
items in the table. For each primary key, you must provide all of the key attributes. For example, with a hash type primary key, you only need to specify the hash attribute. For a hash-and-range type primary key, you must specify both the hash attribute and the range attribute.
table. By default, all attributes are returned. If a specified attribute is not found, it does not appear in the result. Note that AttributesToGet has no effect on provisioned throughput consumption. DynamoDB determines capacity units consumed based on item size, not on the amount of data that is returned to an application.
False (the default), an eventually consistent read is used.
| Parameters: | return_consumed_capacity (string) – A value that if set to TOTAL, the response includes ConsumedCapacity data for tables and indexes. If set to INDEXES, the response includes ConsumedCapacity for indexes. If set to NONE (the default), ConsumedCapacity is not included in the response. |
|---|
The BatchWriteItem operation puts or deletes multiple items in one or more tables. A single call to BatchWriteItem can write up to 16 MB of data, which can comprise as many as 25 put or delete requests. Individual items to be written can be as large as 400 KB.
The individual PutItem and DeleteItem operations specified in BatchWriteItem are atomic; however BatchWriteItem as a whole is not. If any requested operations fail because the table’s provisioned throughput is exceeded or an internal processing failure occurs, the failed operations are returned in the UnprocessedItems response parameter. You can investigate and optionally resend the requests. Typically, you would call BatchWriteItem in a loop. Each iteration would check for unprocessed items and submit a new BatchWriteItem request with those unprocessed items until all items have been processed.
Note that if none of the items can be processed due to insufficient provisioned throughput on all of the tables in the request, then BatchWriteItem will return a ProvisionedThroughputExceededException .
If DynamoDB returns any unprocessed items, you should retry the batch operation on those items. However, we strongly recommend that you use an exponential backoff algorithm . If you retry the batch operation immediately, the underlying read or write requests can still fail due to throttling on the individual tables. If you delay the batch operation using exponential backoff, the individual requests in the batch are much more likely to succeed.
For more information, go to `Batch Operations and Error Handling`_ in the Amazon DynamoDB Developer Guide .
With BatchWriteItem , you can efficiently write or delete large amounts of data, such as from Amazon Elastic MapReduce (EMR), or copy data from another database into DynamoDB. In order to improve performance with these large-scale operations, BatchWriteItem does not behave in the same way as individual PutItem and DeleteItem calls would For example, you cannot specify conditions on individual put and delete requests, and BatchWriteItem does not return deleted items in the response.
If you use a programming language that supports concurrency, such as Java, you can use threads to write items in parallel. Your application must include the necessary logic to manage the threads. With languages that don’t support threading, such as PHP, you must update or delete the specified items one at a time. In both situations, BatchWriteItem provides an alternative where the API performs the specified put and delete operations in parallel, giving you the power of the thread pool approach without having to introduce complexity into your application.
Parallel processing reduces latency, but each specified put and delete request consumes the same number of write capacity units whether it is processed in parallel or not. Delete operations on nonexistent items consume one write capacity unit.
If one or more of the following is true, DynamoDB rejects the entire batch write operation:
| Parameters: | request_items (map) – |
|---|
The item to be deleted is identified by a Key subelement:
the ! item. Each entry in this map consists of an attribute name and an attribute value. For each primary key, you must provide all of the key attributes. For example, with a hash type primary key, you only need to specify the hash attribute. For a hash-and-range type primary key, you must specify both the hash attribute and the range attribute.
item to be put is identified by an Item subelement:
consists of an attribute name and an attribute value. Attribute values must not be null; string and binary type attributes must have lengths greater than zero; and set type attributes must not be empty. Requests that contain empty values will be rejected with a ValidationException exception. If you specify any attributes that are part of an index key, then the data types for those attributes must match those of the schema in the table’s attribute definition.
| Parameters: |
|
|---|
The CreateTable operation adds a new table to your account. In an AWS account, table names must be unique within each region. That is, you can have two tables with same name if you create the tables in different regions.
CreateTable is an asynchronous operation. Upon receiving a CreateTable request, DynamoDB immediately returns a response with a TableStatus of CREATING. After the table is created, DynamoDB sets the TableStatus to ACTIVE. You can perform read and write operations only on an ACTIVE table.
If you want to create multiple tables with secondary indexes on them, you must create them sequentially. Only one table with secondary indexes can be in the CREATING state at any given time.
You can use the DescribeTable API to check the table status.
| Parameters: |
|
|---|
Each KeySchemaElement in the array is composed of:
| Parameters: | local_secondary_indexes (list) – |
|---|
Each local secondary index in the array includes the following:
only for this table.
The key schema must begin with the same hash key attribute as the table.
the table into the index. These are in addition to the primary key attributes and index key attributes, which are automatically projected. Each attribute specification is composed of:
ProjectionType - One of the following:
- KEYS_ONLY - Only the index and primary keys are projected into the
index.
- INCLUDE - Only the specified table attributes are projected into
the index. The list of projected attributes are in NonKeyAttributes .
ALL - All of the table attributes are projected into the index.
are projected into the secondary index. The total count of attributes specified in NonKeyAttributes , summed across all of the secondary indexes, must not exceed 20. If you project the same attribute into two different indexes, this counts as two distinct attributes when determining the total.
| Parameters: | global_secondary_indexes (list) – |
|---|
only for this table.
KeySchema - Specifies the key schema for the global secondary index.
the table into the index. These are in addition to the primary key attributes and index key attributes, which are automatically projected. Each attribute specification is composed of:
ProjectionType - One of the following:
- KEYS_ONLY - Only the index and primary keys are projected into the
index.
- INCLUDE - Only the specified table attributes are projected into
the index. The list of projected attributes are in NonKeyAttributes .
ALL - All of the table attributes are projected into the index.
are projected into the secondary index. The total count of attributes specified in NonKeyAttributes , summed across all of the secondary indexes, must not exceed 20. If you project the same attribute into two different indexes, this counts as two distinct attributes when determining the total.
global secondary index, consisting of read and write capacity units.
| Parameters: | provisioned_throughput (dict) – Represents the provisioned throughput settings for a specified table or index. The settings can be modified using the UpdateTable operation. |
|---|
Deletes a single item in a table by primary key. You can perform a conditional delete operation that deletes the item if it exists, or if it has an expected attribute value.
In addition to deleting an item, you can also return the item’s attribute values in the same operation, using the ReturnValues parameter.
Unless you specify conditions, the DeleteItem is an idempotent operation; running it multiple times on the same item or attribute does not result in an error response.
Conditional deletes are useful for deleting items only if specific conditions are met. If those conditions are met, DynamoDB performs the delete. Otherwise, the item is not deleted.
| Parameters: |
|---|
| Parameters: | expected (map) – |
|---|
This parameter does not support lists or maps.
Expected contains the following:
supplied attribute. The number of values in the list depends on the ComparisonOperator being used. For type Number, value comparisons are numeric. String value comparisons for greater than, equals, or less than are based on ASCII character code values. For example, a is greater than A, and aa is greater than B. For a list of code values, see `http://en.wikipedia.org/wiki/ASCII#ASCII_printable_characters`_. For type Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values, for example when evaluating query expressions.
AttributeValueList . When performing the comparison, DynamoDB uses strongly consistent reads. The following comparison operators are available: EQ | NE | LE | LT | GE | GT | NOT_NULL | NULL | CONTAINS | NOT_CONTAINS | BEGINS_WITH | IN | BETWEEN The following are descriptions of each comparison operator.
and maps. AttributeValueList can contain only one AttributeValue element of type String, Number, Binary, String Set, Number Set, or Binary Set. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}. > <li>
lists and maps. AttributeValueList can contain only one AttributeValue of type String, Number, Binary, String Set, Number Set, or Binary Set. If an item contains an AttributeValue of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
datatypes, including lists and maps.
datatypes, including lists and maps.
AttributeValueList can contain only one AttributeValue element of type String, Number, or Binary (not a set type). If the target attribute of the comparison is of type String, then the operator checks for a substring match. If the target attribute of the comparison is of type Binary, then the operator looks for a subsequence of the target that matches the input. If the target attribute of the comparison is a set (” SS”, ” NS”, or ” BS”), then the operator evaluates to true if it finds an exact match with any member of the set. CONTAINS is supported for lists: When evaluating ” a CONTAINS b”, ” a” can be a list; however, ” b” cannot be a set, a map, or a list.
value in a set. AttributeValueList can contain only one AttributeValue element of type String, Number, or Binary (not a set type). If the target attribute of the comparison is a String, then the operator checks for the absence of a substring match. If the target attribute of the comparison is Binary, then the operator checks for the absence of a subsequence of the target that matches the input. If the target attribute of the comparison is a set (” SS”, ” NS”, or ” BS”), then the operator evaluates to true if it does not find an exact match with any member of the set. NOT_CONTAINS is supported for lists: When evaluating ” a NOT CONTAINS b”, ” a” can be a list; however, ” b” cannot be a set, a map, or a list.
only one AttributeValue of type String or Binary (not a Number or a set type). The target attribute of the comparison must be of type String or Binary (not a Number or a set type). > <li>
AttributeValueList can contain one or more AttributeValue elements of type String, Number, or Binary (not a set type). These attributes are compared against an existing set type attribute of an item. If any elements of the input set are present in the item attribute, the expression evaluates to true.
or equal to the second value. AttributeValueList must contain two AttributeValue elements of the same type, either String, Number, or Binary (not a set type). A target attribute matches if the target value is greater than, or equal to, the first element and less than, or equal to, the second element. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not compare to {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}
Value - A value for DynamoDB to compare with an attribute.
before attempting the conditional operation:
value already exists in the table. If it is found, then the condition evaluates to true; otherwise the condition evaluate to false.
not exist in the table. If in fact the value does not exist, then the assumption is valid and the condition evaluates to true. If the value is found, despite the assumption that it does not exist, the condition evaluates to false.
| Parameters: | conditional_operator (string) – |
|---|
This parameter does not support lists or maps.
A logical operator to apply to the conditions in the Expected map:
map evaluates to true.
entire map evaluates to true.
If you omit ConditionalOperator , then AND is the default.
The operation will succeed only if the entire map evaluates to true.
| Parameters: | return_values (string) – |
|---|
then nothing is returned. (This setting is the default for ReturnValues .)
ALL_OLD - The content of the old item is returned.
| Parameters: |
|
|---|
An expression can contain any of the following:
Boolean functions: ATTRIBUTE_EXIST | CONTAINS | BEGINS_WITH
Logical operators: NOT | AND | OR
| Parameters: | expression_attribute_names (map) – |
|---|
expression.
name in an expression.
misinterpreted in an expression.
= “Jones”`
The expression can now be simplified as follows:
| Parameters: | expression_attribute_values (map) – |
|---|
One or more values that can be substituted in an expression.
“d”:{“S”:”Discontinued”} }`
The expression can now be simplified as follows:
The DeleteTable operation deletes a table and all of its items. After a DeleteTable request, the specified table is in the DELETING state until DynamoDB completes the deletion. If the table is in the ACTIVE state, you can delete it. If a table is in CREATING or UPDATING states, then DynamoDB returns a ResourceInUseException . If the specified table does not exist, DynamoDB returns a ResourceNotFoundException . If table is already in the DELETING state, no error is returned.
When you delete a table, any indexes on that table are also deleted.
Use the DescribeTable API to check the status of the table.
| Parameters: | table_name (string) – The name of the table to delete. |
|---|
Returns information about the table, including the current status of the table, when it was created, the primary key schema, and any indexes on the table.
| Parameters: | table_name (string) – The name of the table to describe. |
|---|
The GetItem operation returns a set of attributes for the item with the given primary key. If there is no matching item, GetItem does not return any data.
GetItem provides an eventually consistent read by default. If your application requires a strongly consistent read, set ConsistentRead to True. Although a strongly consistent read might take more time than an eventually consistent read, it always returns the last updated value.
| Parameters: |
|---|
| Parameters: | attributes_to_get (list) – |
|---|
| Parameters: |
|
|---|
| Parameters: | expression_attribute_names (map) – |
|---|
expression.
name in an expression.
misinterpreted in an expression.
= “Jones”`
The expression can now be simplified as follows:
Returns an array of table names associated with the current account and endpoint. The output from ListTables is paginated, with each page returning a maximum of 100 table names.
| Parameters: |
|
|---|
Creates a new item, or replaces an old item with a new item. If an item that has the same primary key as the new item already exists in the specified table, the new item completely replaces the existing item. You can perform a conditional put operation (add a new item if one with the specified primary key doesn’t exist), or replace an existing item if it has certain attribute values.
In addition to putting an item, you can also return the item’s attribute values in the same operation, using the ReturnValues parameter.
When you add an item, the primary key attribute(s) are the only required attributes. Attribute values cannot be null. String and Binary type attributes must have lengths greater than zero. Set type attributes cannot be empty. Requests with empty values will be rejected with a ValidationException exception.
You can request that PutItem return either a copy of the original item (before the update) or a copy of the updated item (after the update). For more information, see the ReturnValues description below.
For more information about using this API, see `Working with Items`_ in the Amazon DynamoDB Developer Guide .
| Parameters: |
|---|
Each element in the Item map is an AttributeValue object.
| Parameters: | expected (map) – |
|---|
This parameter does not support lists or maps.
Expected contains the following:
supplied attribute. The number of values in the list depends on the ComparisonOperator being used. For type Number, value comparisons are numeric. String value comparisons for greater than, equals, or less than are based on ASCII character code values. For example, a is greater than A, and aa is greater than B. For a list of code values, see `http://en.wikipedia.org/wiki/ASCII#ASCII_printable_characters`_. For type Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values, for example when evaluating query expressions.
AttributeValueList . When performing the comparison, DynamoDB uses strongly consistent reads. The following comparison operators are available: EQ | NE | LE | LT | GE | GT | NOT_NULL | NULL | CONTAINS | NOT_CONTAINS | BEGINS_WITH | IN | BETWEEN The following are descriptions of each comparison operator.
and maps. AttributeValueList can contain only one AttributeValue element of type String, Number, Binary, String Set, Number Set, or Binary Set. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}. > <li>
lists and maps. AttributeValueList can contain only one AttributeValue of type String, Number, Binary, String Set, Number Set, or Binary Set. If an item contains an AttributeValue of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
datatypes, including lists and maps.
datatypes, including lists and maps.
AttributeValueList can contain only one AttributeValue element of type String, Number, or Binary (not a set type). If the target attribute of the comparison is of type String, then the operator checks for a substring match. If the target attribute of the comparison is of type Binary, then the operator looks for a subsequence of the target that matches the input. If the target attribute of the comparison is a set (” SS”, ” NS”, or ” BS”), then the operator evaluates to true if it finds an exact match with any member of the set. CONTAINS is supported for lists: When evaluating ” a CONTAINS b”, ” a” can be a list; however, ” b” cannot be a set, a map, or a list.
value in a set. AttributeValueList can contain only one AttributeValue element of type String, Number, or Binary (not a set type). If the target attribute of the comparison is a String, then the operator checks for the absence of a substring match. If the target attribute of the comparison is Binary, then the operator checks for the absence of a subsequence of the target that matches the input. If the target attribute of the comparison is a set (” SS”, ” NS”, or ” BS”), then the operator evaluates to true if it does not find an exact match with any member of the set. NOT_CONTAINS is supported for lists: When evaluating ” a NOT CONTAINS b”, ” a” can be a list; however, ” b” cannot be a set, a map, or a list.
only one AttributeValue of type String or Binary (not a Number or a set type). The target attribute of the comparison must be of type String or Binary (not a Number or a set type). > <li>
AttributeValueList can contain one or more AttributeValue elements of type String, Number, or Binary (not a set type). These attributes are compared against an existing set type attribute of an item. If any elements of the input set are present in the item attribute, the expression evaluates to true.
or equal to the second value. AttributeValueList must contain two AttributeValue elements of the same type, either String, Number, or Binary (not a set type). A target attribute matches if the target value is greater than, or equal to, the first element and less than, or equal to, the second element. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not compare to {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}
Value - A value for DynamoDB to compare with an attribute.
before attempting the conditional operation:
value already exists in the table. If it is found, then the condition evaluates to true; otherwise the condition evaluate to false.
not exist in the table. If in fact the value does not exist, then the assumption is valid and the condition evaluates to true. If the value is found, despite the assumption that it does not exist, the condition evaluates to false.
| Parameters: | return_values (string) – |
|---|
then nothing is returned. (This setting is the default for ReturnValues .)
the content of the old item is returned.
| Parameters: |
|
|---|
This parameter does not support lists or maps.
A logical operator to apply to the conditions in the Expected map:
map evaluates to true.
entire map evaluates to true.
If you omit ConditionalOperator , then AND is the default.
The operation will succeed only if the entire map evaluates to true.
| Parameters: | condition_expression (string) – |
|---|
An expression can contain any of the following:
Boolean functions: ATTRIBUTE_EXIST | CONTAINS | BEGINS_WITH
Logical operators: NOT | AND | OR
| Parameters: | expression_attribute_names (map) – |
|---|
expression.
name in an expression.
misinterpreted in an expression.
= “Jones”`
The expression can now be simplified as follows:
| Parameters: | expression_attribute_values (map) – |
|---|
One or more values that can be substituted in an expression.
“d”:{“S”:”Discontinued”} }`
The expression can now be simplified as follows:
A Query operation directly accesses items from a table using the table primary key, or from an index using the index key. You must provide a specific hash key value. You can narrow the scope of the query by using comparison operators on the range key value, or on the index key. You can use the ScanIndexForward parameter to get results in forward or reverse order, by range key or by index key.
Queries that do not return results consume the minimum number of read capacity units for that type of read operation.
If the total number of items meeting the query criteria exceeds the result set size limit of 1 MB, the query stops and results are returned to the user with LastEvaluatedKey to continue the query in a subsequent operation. Unlike a Scan operation, a Query operation never returns both an empty result set and a LastEvaluatedKey . The LastEvaluatedKey is only provided if the results exceed 1 MB, or if you have used Limit .
You can query a table, a local secondary index, or a global secondary index. For a query on a table or on a local secondary index, you can set ConsistentRead to true and obtain a strongly consistent result. Global secondary indexes support eventually consistent reads only, so do not specify ConsistentRead when querying a global secondary index.
| Parameters: |
|
|---|
specified table or index. If you query a local secondary index, then for each matching item in the index DynamoDB will fetch the entire item from the parent table. If the index is configured to project all item attributes, then all of the data can be obtained from the local secondary index, and no fetching is required.
Retrieves all attributes that have been projected into the index. If the index is configured to project all attributes, this return value is equivalent to specifying ALL_ATTRIBUTES.
matching items themselves.
AttributesToGet . This return value is equivalent to specifying AttributesToGet without specifying any value for Select . If you query a local secondary index and request only attributes that are projected into that index, the operation will read only the index and not the table. If any of the requested attributes are not projected into the local secondary index, DynamoDB will fetch each of these attributes from the parent table. This extra fetching incurs additional throughput cost and latency. If you query a global secondary index, you can only request attributes that are projected into the index. Global secondary index queries cannot fetch attributes from the parent table.
| Parameters: | attributes_to_get (list) – |
|---|
| Parameters: |
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| Parameters: | key_conditions (map) – The selection criteria for the query. For a query on a table, you can have conditions only on the table primary key attributes. You must specify the hash key attribute name and value as an EQ condition. You can optionally specify a second condition, referring to the range key attribute. |
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supplied attribute. The number of values in the list depends on the ComparisonOperator being used. For type Number, value comparisons are numeric. String value comparisons for greater than, equals, or less than are based on ASCII character code values. For example, a is greater than A, and aa is greater than B. For a list of code values, see `http://en.wikipedia.org/wiki/ASCII#ASCII_printable_characters`_. For Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values, for example when evaluating query expressions.
example, equals, greater than, less than, and so on. For KeyConditions , only the following comparison operators are supported: EQ | LE | LT | GE | GT | BEGINS_WITH | BETWEEN The following are descriptions of these comparison operators.
of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}.
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
only one AttributeValue of type String or Binary (not a Number or a set type). The target attribute of the comparison must be of type String or Binary (not a Number or a set type). > <li>
or equal to the second value. AttributeValueList must contain two AttributeValue elements of the same type, either String, Number, or Binary (not a set type). A target attribute matches if the target value is greater than, or equal to, the first element and less than, or equal to, the second element. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not compare to {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}
| Parameters: | query_filter (map) – |
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This parameter does not support lists or maps.
supplied attribute. The number of values in the list depends on the operator specified in ComparisonOperator . For type Number, value comparisons are numeric. String value comparisons for greater than, equals, or less than are based on ASCII character code values. For example, a is greater than A, and aa is greater than B. For a list of code values, see `http://en.wikipedia.org/wiki/ASCII#ASCII_printable_characters`_. For type Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values, for example when evaluating query expressions. For information on specifying data types in JSON, see `JSON Data Format`_ in the Amazon DynamoDB Developer Guide .
example, equals, greater than, less than, etc. The following comparison operators are available: EQ | NE | LE | LT | GE | GT | NOT_NULL | NULL | CONTAINS | NOT_CONTAINS | BEGINS_WITH | IN | BETWEEN For complete descriptions of all comparison operators, see `API_Condition.html`_.
| Parameters: | conditional_operator (string) – |
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This parameter does not support lists or maps.
A logical operator to apply to the conditions in the QueryFilter map:
map evaluates to true.
entire map evaluates to true.
If you omit ConditionalOperator , then AND is the default.
The operation will succeed only if the entire map evaluates to true.
| Parameters: | scan_index_forward (boolean) – A value that specifies ascending (true) or descending (false) traversal of the index. DynamoDB returns results reflecting the requested order determined by the range key. If the data type is Number, the results are returned in numeric order. For type String, the results are returned in order of ASCII character code values. For type Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values. |
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| Parameters: | exclusive_start_key (map) – The primary key of the first item that this operation will evaluate. Use the value that was returned for LastEvaluatedKey in the previous operation. |
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| Parameters: |
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| Parameters: | filter_expression (string) – A condition that evaluates the query results and returns only the desired values. |
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| Parameters: | expression_attribute_names (map) – |
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expression.
name in an expression.
misinterpreted in an expression.
= “Jones”`
The expression can now be simplified as follows:
| Parameters: | expression_attribute_values (map) – |
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One or more values that can be substituted in an expression.
“d”:{“S”:”Discontinued”} }`
The expression can now be simplified as follows:
The Scan operation returns one or more items and item attributes by accessing every item in the table. To have DynamoDB return fewer items, you can provide a ScanFilter operation.
If the total number of scanned items exceeds the maximum data set size limit of 1 MB, the scan stops and results are returned to the user as a LastEvaluatedKey value to continue the scan in a subsequent operation. The results also include the number of items exceeding the limit. A scan can result in no table data meeting the filter criteria.
The result set is eventually consistent.
By default, Scan operations proceed sequentially; however, for faster performance on large tables, applications can request a parallel Scan operation by specifying the Segment and TotalSegments parameters. For more information, see `Parallel Scan`_ in the Amazon DynamoDB Developer Guide .
| Parameters: |
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| Parameters: |
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ALL_ATTRIBUTES - Returns all of the item attributes.
matching items themselves.
AttributesToGet . This return value is equivalent to specifying AttributesToGet without specifying any value for Select .
| Parameters: | scan_filter (map) – |
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This parameter does not support lists or maps.
supplied attribute. The number of values in the list depends on the operator specified in ComparisonOperator . For type Number, value comparisons are numeric. String value comparisons for greater than, equals, or less than are based on ASCII character code values. For example, a is greater than A, and aa is greater than B. For a list of code values, see `http://en.wikipedia.org/wiki/ASCII#ASCII_printable_characters`_. For Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values, for example when evaluating query expressions. For information on specifying data types in JSON, see `JSON Data Format`_ in the Amazon DynamoDB Developer Guide .
example, equals, greater than, less than, etc. The following comparison operators are available: EQ | NE | LE | LT | GE | GT | NOT_NULL | NULL | CONTAINS | NOT_CONTAINS | BEGINS_WITH | IN | BETWEEN For complete descriptions of all comparison operators, see `Condition`_.
| Parameters: | conditional_operator (string) – |
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This parameter does not support lists or maps.
A logical operator to apply to the conditions in the ScanFilter map:
map evaluates to true.
entire map evaluates to true.
If you omit ConditionalOperator , then AND is the default.
The operation will succeed only if the entire map evaluates to true.
| Parameters: | exclusive_start_key (map) – The primary key of the first item that this operation will evaluate. Use the value that was returned for LastEvaluatedKey in the previous operation. |
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| Parameters: |
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If you specify TotalSegments , you must also specify Segment .
| Parameters: | segment (integer) – For a parallel Scan request, Segment identifies an individual segment to be scanned by an application worker. |
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If you specify Segment , you must also specify TotalSegments .
| Parameters: | projection_expression (string) – One or more attributes to retrieve from the table. These attributes can include scalars, sets, or elements of a JSON document. The attributes in the expression must be separated by commas. |
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| Parameters: | filter_expression (string) – A condition that evaluates the scan results and returns only the desired values. |
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| Parameters: | expression_attribute_names (map) – |
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expression.
name in an expression.
misinterpreted in an expression.
= “Jones”`
The expression can now be simplified as follows:
| Parameters: | expression_attribute_values (map) – |
|---|
One or more values that can be substituted in an expression.
“d”:{“S”:”Discontinued”} }`
The expression can now be simplified as follows:
Edits an existing item’s attributes, or adds a new item to the table if it does not already exist. You can put, delete, or add attribute values. You can also perform a conditional update (insert a new attribute name-value pair if it doesn’t exist, or replace an existing name-value pair if it has certain expected attribute values).
You can also return the item’s attribute values in the same UpdateItem operation using the ReturnValues parameter.
| Parameters: |
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| Parameters: | attribute_updates (map) – |
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Value - The new value, if applicable, for this attribute.
action is only valid for an existing attribute whose data type is Number or is a set; do not use ADD for other data types. If an item with the specified primary key is found in the table, the following values perform the following actions:
already exists, it is replaced by the new value.
specified for DELETE. The data type of the specified value must match the existing value’s data type. If a set of values is specified, then those values are subtracted from the old set. For example, if the attribute value was the set [a,b,c] and the DELETE action specifies [a,c], then the final attribute value is [b]. Specifying an empty set is an error.
not already exist. If the attribute does exist, then the behavior of ADD depends on the data type of the attribute:
then Value is mathematically added to the existing attribute. If Value is a negative number, then it is subtracted from the existing attribute.
Value is appended to the existing set. For example, if the attribute value is the set [1,2], and the ADD action specified [3], then the final attribute value is [1,2,3]. An error occurs if an ADD action is specified for a set attribute and the attribute type specified does not match the existing set type. Both sets must have the same primitive data type. For example, if the existing data type is a set of strings, Value must also be a set of strings.
values perform the following actions:
primary key, and then adds the attribute.
DELETE - Causes nothing to happen; there is no attribute to delete.
key and number (or set of numbers) for the attribute value. The only data types allowed are Number and Number Set.
| Parameters: | expected (map) – |
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This parameter does not support lists or maps.
Expected contains the following:
supplied attribute. The number of values in the list depends on the ComparisonOperator being used. For type Number, value comparisons are numeric. String value comparisons for greater than, equals, or less than are based on ASCII character code values. For example, a is greater than A, and aa is greater than B. For a list of code values, see `http://en.wikipedia.org/wiki/ASCII#ASCII_printable_characters`_. For type Binary, DynamoDB treats each byte of the binary data as unsigned when it compares binary values, for example when evaluating query expressions.
AttributeValueList . When performing the comparison, DynamoDB uses strongly consistent reads. The following comparison operators are available: EQ | NE | LE | LT | GE | GT | NOT_NULL | NULL | CONTAINS | NOT_CONTAINS | BEGINS_WITH | IN | BETWEEN The following are descriptions of each comparison operator.
and maps. AttributeValueList can contain only one AttributeValue element of type String, Number, Binary, String Set, Number Set, or Binary Set. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}. > <li>
lists and maps. AttributeValueList can contain only one AttributeValue of type String, Number, Binary, String Set, Number Set, or Binary Set. If an item contains an AttributeValue of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not equal {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
AttributeValue element of type String, Number, or Binary (not a set type). If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not equal {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}. > <li>
datatypes, including lists and maps.
datatypes, including lists and maps.
AttributeValueList can contain only one AttributeValue element of type String, Number, or Binary (not a set type). If the target attribute of the comparison is of type String, then the operator checks for a substring match. If the target attribute of the comparison is of type Binary, then the operator looks for a subsequence of the target that matches the input. If the target attribute of the comparison is a set (” SS”, ” NS”, or ” BS”), then the operator evaluates to true if it finds an exact match with any member of the set. CONTAINS is supported for lists: When evaluating ” a CONTAINS b”, ” a” can be a list; however, ” b” cannot be a set, a map, or a list.
value in a set. AttributeValueList can contain only one AttributeValue element of type String, Number, or Binary (not a set type). If the target attribute of the comparison is a String, then the operator checks for the absence of a substring match. If the target attribute of the comparison is Binary, then the operator checks for the absence of a subsequence of the target that matches the input. If the target attribute of the comparison is a set (” SS”, ” NS”, or ” BS”), then the operator evaluates to true if it does not find an exact match with any member of the set. NOT_CONTAINS is supported for lists: When evaluating ” a NOT CONTAINS b”, ” a” can be a list; however, ” b” cannot be a set, a map, or a list.
only one AttributeValue of type String or Binary (not a Number or a set type). The target attribute of the comparison must be of type String or Binary (not a Number or a set type). > <li>
AttributeValueList can contain one or more AttributeValue elements of type String, Number, or Binary (not a set type). These attributes are compared against an existing set type attribute of an item. If any elements of the input set are present in the item attribute, the expression evaluates to true.
or equal to the second value. AttributeValueList must contain two AttributeValue elements of the same type, either String, Number, or Binary (not a set type). A target attribute matches if the target value is greater than, or equal to, the first element and less than, or equal to, the second element. If an item contains an AttributeValue element of a different type than the one specified in the request, the value does not match. For example, {“S”:”6”} does not compare to {“N”:”6”}. Also, {“N”:”6”} does not compare to {“NS”:[“6”, “2”, “1”]}
Value - A value for DynamoDB to compare with an attribute.
before attempting the conditional operation:
value already exists in the table. If it is found, then the condition evaluates to true; otherwise the condition evaluate to false.
not exist in the table. If in fact the value does not exist, then the assumption is valid and the condition evaluates to true. If the value is found, despite the assumption that it does not exist, the condition evaluates to false.
| Parameters: | conditional_operator (string) – |
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This parameter does not support lists or maps.
A logical operator to apply to the conditions in the Expected map:
map evaluates to true.
entire map evaluates to true.
If you omit ConditionalOperator , then AND is the default.
The operation will succeed only if the entire map evaluates to true.
| Parameters: | return_values (string) – |
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then nothing is returned. (This setting is the default for ReturnValues .)
then the content of the old item is returned.
returned.
returned.
returned.
| Parameters: |
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The following action values are available for UpdateExpression .
these attribute already exist, they are replaced by the new values. You can also use SET to add or subtract from an attribute that is of type Number. SET supports the following functions:
attribute at the specified path, then if_not_exists evaluates to operand; otherwise, it evaluates to path. You can use this function to avoid overwriting an attribute that may already be present in the item.
element added to it. You can append the new element to the start or the end of the list by reversing the order of the operands.
These function names are case-sensitive.
REMOVE - Removes one or more attributes from an item.
not already exist. If the attribute does exist, then the behavior of ADD depends on the data type of the attribute:
then Value is mathematically added to the existing attribute. If Value is a negative number, then it is subtracted from the existing attribute.
Value is added to the existing set. For example, if the attribute value is the set [1,2], and the ADD action specified [3], then the final attribute value is [1,2,3]. An error occurs if an ADD action is specified for a set attribute and the attribute type specified does not match the existing set type. Both sets must have the same primitive data type. For example, if the existing data type is a set of strings, the Value must also be a set of strings.
ADD can only be used on top-level attributes, not nested attributes.
specified, then those values are subtracted from the old set. For example, if the attribute value was the set [a,b,c] and the DELETE action specifies [a,c], then the final attribute value is [b]. Specifying an empty set is an error. The DELETE action only supports Number and set data types. In addition, DELETE can only be used on top-level attributes, not nested attributes.
An expression can contain any of the following:
Boolean functions: ATTRIBUTE_EXIST | CONTAINS | BEGINS_WITH
Logical operators: NOT | AND | OR
| Parameters: | condition_expression (string) – |
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An expression can contain any of the following:
Boolean functions: ATTRIBUTE_EXIST | CONTAINS | BEGINS_WITH
Logical operators: NOT | AND | OR
| Parameters: | expression_attribute_names (map) – |
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expression.
name in an expression.
misinterpreted in an expression.
= “Jones”`
The expression can now be simplified as follows:
| Parameters: | expression_attribute_values (map) – |
|---|
One or more values that can be substituted in an expression.
“d”:{“S”:”Discontinued”} }`
The expression can now be simplified as follows:
Updates the provisioned throughput for the given table. Setting the throughput for a table helps you manage performance and is part of the provisioned throughput feature of DynamoDB.
The provisioned throughput values can be upgraded or downgraded based on the maximums and minimums listed in the `Limits`_ section in the Amazon DynamoDB Developer Guide .
The table must be in the ACTIVE state for this operation to succeed. UpdateTable is an asynchronous operation; while executing the operation, the table is in the UPDATING state. While the table is in the UPDATING state, the table still has the provisioned throughput from before the call. The new provisioned throughput setting is in effect only when the table returns to the ACTIVE state after the UpdateTable operation.
You cannot add, modify or delete indexes using UpdateTable . Indexes can only be defined at table creation time.
| Parameters: |
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| Parameters: | global_secondary_index_updates (list) – An array of one or more global secondary indexes on the table, together with provisioned throughput settings for each index. |
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