Class for representing a single entity in the Cloud Datastore.
Classes
Entity
Entity(key=None, exclude_from_indexes=())
Entities are akin to rows in a relational database
An entity storing the actual instance of data.
Each entity is officially represented with a xref_Key, however it is possible that you might create an entity with only a partial key (that is, a key with a kind, and possibly a parent, but without an ID). In such a case, the datastore service will automatically assign an ID to the partial key.
Entities in this API act like dictionaries with extras built in that allow you to delete or persist the data stored on the entity.
Entities are mutable and act like a subclass of a dictionary. This means you could take an existing entity and change the key to duplicate the object.
Use xref_get to retrieve an existing entity:
.. testsetup:: entity-ctor
import os
import uuid
from google.cloud import datastore
from tests.system.test_system import Config # system tests
unique = os.getenv('CIRCLE_BUILD_NUM', str(uuid.uuid4())[0:8])
client = datastore.Client(namespace='ns{}'.format(unique))
key = client.key('EntityKind', 1234, namespace='_Doctest')
entity = datastore.Entity(key=key)
entity['property'] = 'value'
Config.TO_DELETE.append(entity)
client.put(entity)
.. doctest:: entity-ctor
>>> client.get(key)
<Entity('EntityKind', 1234) {'property': 'value'}>
You can the set values on the entity just like you would on any other dictionary.
.. doctest:: entity-ctor
>>> entity['age'] = 20
>>> entity['name'] = 'JJ'
However, not all types are allowed as a value for a Google Cloud Datastore entity. The following basic types are supported by the API:
datetime.datetime
- xref_Key
bool
float
int
(as well aslong
in Python 2)unicode
(calledstr
in Python 3)bytes
(calledstr
in Python 2)- xref_GeoPoint
- :data:
None
In addition, three container types are supported:
list
- xref_Entity
dict
(will just be treated like anEntity
without a key orexclude_from_indexes
)
Each entry in a list must be one of the value types (basic or
container) and each value in an
xref_Entity must as well. In
this case an xref_Entity as a
container acts as a dict
, but also has the special annotations
of key
and exclude_from_indexes
.
And you can treat an entity like a regular Python dictionary:
.. testsetup:: entity-dict
from google.cloud import datastore
entity = datastore.Entity()
entity['age'] = 20
entity['name'] = 'JJ'
.. doctest:: entity-dict
>>> sorted(entity.keys())
['age', 'name']
>>> sorted(entity.items())
[('age', 20), ('name', 'JJ')]
Parameters | |
---|---|
Name | Description |
key |
Key
Optional key to be set on entity. |
exclude_from_indexes |
tuple of string
Names of fields whose values are not to be indexed for this entity. |