def __init__(self, *args, **kwargs):
"""Create a new DynamoDB model
This supports both:
>>> DynamoModel(table, "hash_key", "range_key", attrs)
>>> DynamoModel("hash_key", "range_key")
as well as using keyword args:
>>> DynamoModel(table=table, hash_key="hash_key", range_key="range_key")
>>> DynamoModel(hash_key="hash_key", range_key="range_key")
>>> DynamoModel(table, hash_key="hash_key", range_key="range_key")
This could be coming from Layer2, or it could be just called
directly by us."""
if len(args) > 0:
first_arg = args[0]
else:
first_arg = kwargs.get("table")
if first_arg and isinstance(first_arg, Table):
# If the first argment is a Table, then
# we assume this came from Layer2, so just pass this
# on up the chain
return Item.__init__(self, *args, **kwargs)
else:
# Otherwise, we're probably being called directly
# so we should auto-set the table
return Item.__init__(self, self.get_table(), *args, **kwargs)
def __init__(self, *args, **kwargs):
"""Create a new DynamoDB model
This supports both:
>>> DynamoModel(table, "hash_key", "range_key", attrs)
>>> DynamoModel("hash_key", "range_key")
as well as using keyword args:
>>> DynamoModel(table=table, hash_key="hash_key", range_key="range_key")
>>> DynamoModel(hash_key="hash_key", range_key="range_key")
>>> DynamoModel(table, hash_key="hash_key", range_key="range_key")
This could be coming from Layer2, or it could be just called
directly by us."""
if len(args) > 0:
first_arg = args[0]
else:
first_arg = kwargs.get("table")
if first_arg and isinstance(first_arg, Table):
# If the first argment is a Table, then
# we assume this came from Layer2, so just pass this
# on up the chain
return Item.__init__(self, *args, **kwargs)
else:
# Otherwise, we're probably being called directly
# so we should auto-set the table
return Item.__init__(self, self.get_table(), *args, **kwargs)
def __setitem__(self, key, value):
"""Overwrite the setter to automatically
convert types to DynamoDB supported types"""
from datetime import datetime
if isinstance(value, datetime):
value = value.strftime("%Y-%m-%dT%H:%M:%S")
elif isinstance(value, list):
value = set(value)
return Item.__setitem__(self, key, value)
def __setitem__(self, key, value):
"""Overwrite the setter to automatically
convert types to DynamoDB supported types"""
from datetime import datetime
if isinstance(value, datetime):
value = value.strftime("%Y-%m-%dT%H:%M:%S")
elif isinstance(value, list):
value = set(value)
return Item.__setitem__(self, key, value)
def delete(self, *args, **kwargs):
'''Intercept the delete function to also remove this record from CloudSearch
if it is indexed'''
if self._cs_document_endpoint:
from boto.cloudsearch.document import DocumentServiceConnection
conn = DocumentServiceConnection(endpoint=self._cs_document_endpoint)
doc_id = self.id
doc_id = b32encode(doc_id).lower().replace('=', '_')
conn.delete(doc_id, int(time.time()))
conn.commit()
return Item.delete(self, *args, **kwargs)
def get_many(cls, keys, attributes_to_get=None):
"""
Returns a list of :class:`PersistentObject` identical in length to the
list of keys provided. If a key could not be found, it's slot will be
`None`
This operation performs `BatchGetItem` on the DynamoDB store. This
method is typically limited to 100 items. Depending on your configured
capacity, this can easily outstrip it. This method will retry in a loop
until all the keys you asked for are satisfied. `keys` is not limited
to 100 items.
:type keys: list
:param keys: A list of keys
"""
cls._load_meta()
keys = map(cls.prepare_key, keys)
t1 = time.time()
# get the items
items, unprocessed, consumed_capacity = cls._fetch_batch_queue(
cls._get_batch_queue(keys))
# if there are unprocessed items, create a batch from them
if len(unprocessed):
unprocessed_queue = cls._get_batch_queue(unprocessed)
else:
unprocessed_queue = []
# and continue fetching unprocessed items until there are no more
while len(unprocessed_queue):
new_items, new_unprocessed, new_consumed = cls._fetch_batch_queue(
unprocessed_queue)
consumed_capacity += new_consumed
items.extend(new_items)
if len(new_unprocessed):
unprocessed_queue = cls._get_batch_queue(new_unprocessed)
else:
unprocessed_queue = []
# create a hash out of the values' keys for quick reordering
h = dict(
(item[cls._hash_key_name], idx) for idx, item in enumerate(items))
ret = []
for key in keys:
if key in h:
ret.append(cls(Item(cls._table, key, None, items[h[key]])))
else:
ret.append(None)
logger.info(
'Got %i of %s in %s ConsumedCapacityUnits=%f' %
(len(items), cls.__name__, time.time() - t1, consumed_capacity))
return ret
def get_item(self, table, hash_key, range_key=None,
attributes_to_get=None, consistent_read=False):
"""
Retrieve an existing item from the table.
:type table: :class:`boto.dynamodb.table.Table`
:param table: The Table object from which the item is retrieved.
:type hash_key: int|long|float|str|unicode
:param hash_key: The HashKey of the requested item. The
type of the value must match the type defined in the
schema for the table.
:type range_key: int|long|float|str|unicode
:param range_key: The optional RangeKey of the requested item.
The type of the value must match the type defined in the
schema for the table.
:type attributes_to_get: list
:param attributes_to_get: A list of attribute names.
If supplied, only the specified attribute names will
be returned. Otherwise, all attributes will be returned.
:type consistent_read: bool
:param consistent_read: If True, a consistent read
request is issued. Otherwise, an eventually consistent
request is issued.
"""
key = self.build_key_from_values(table.schema, hash_key, range_key)
response = self.layer1.get_item(table.name, key,
attributes_to_get, consistent_read,
object_hook=item_object_hook)
item = Item(table, hash_key, range_key, response['Item'])
if 'ConsumedCapacityUnits' in response:
item.consumed_units = response['ConsumedCapacityUnits']
return item
def new_item(self, hash_key, range_key=None, attrs=None):
"""
Return an new, unsaved Item which can later be PUT to
Amazon DynamoDB.
"""
return Item(self, hash_key, range_key, attrs)
def save(self, *args, **kwargs): self.on_save_or_update() Item.save(self, *args, **kwargs) self.after_save_or_update()
def __setitem__(self, key, value): '''Overwrite the setter to automatically convert types to DynamoDB supported types''' return Item.__setitem__(self, key, self.convert(key, value))
def save(self, *args, **kwargs): self.on_save_or_update() if self._cs_document_endpoint: self.save_to_cloudsearch() Item.save(self, *args, **kwargs) self.after_save_or_update()
def __setattr__(self, name, val): prop = self.find_property(name) if prop: self[name] = val else: Item.__setattr__(self, name, val)
