def _is_ndb(self):
"""Determine whether the model of the instance is an NDB model.
Returns:
Boolean indicating whether or not the model is an NDB or DB model.
"""
# issubclass will fail if one of the arguments is not a class, only
# need worry about new-style classes since ndb and db models are
# new-style
if isinstance(self._model, type):
if ndb is not None and issubclass(self._model, ndb.Model):
return True
elif issubclass(self._model, db.Model):
return False
raise TypeError('Model class not an NDB or DB model: %s.' %
(self._model,))
python类Model()的实例源码
_google_appengine_ext_ndb.py 文件源码
项目：Tinychat-Bot--Discontinued
作者: Tinychat
项目源码
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def encode_ndb_key(key, encoder=None):
"""
When encountering an L{ndb.Key} instance, find the entity in the datastore
and encode that.
"""
klass = ndb.Model._kind_map.get(key.kind())
referenced_object = _get_by_class_key(
encoder,
klass,
key,
)
if not referenced_object:
encoder.writeElement(None)
return
encoder.writeObject(referenced_object)
def make_directed_query(self, kind_class, keys_only=False):
"""Construct a query for this key range, including the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, use keys_only on Query?
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
Raises:
KeyRangeError: if self.direction is not in (KeyRange.ASC, KeyRange.DESC).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_directed_ndb_query(kind_class, keys_only=keys_only)
assert self._app is None, '_app is not supported for db.Query'
direction = self.__get_direction("", "-")
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("%s__key__" % direction)
query = self.filter_query(query)
return query
def make_ascending_query(self, kind_class, keys_only=False, filters=None):
"""Construct a query for this key range without setting the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, query only for keys.
filters: optional list of filters to apply to the query. Each filter is
a tuple: (<property_name_as_str>, <query_operation_as_str>, <value>).
User filters are applied first.
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_ascending_ndb_query(
kind_class, keys_only=keys_only, filters=filters)
assert self._app is None, '_app is not supported for db.Query'
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("__key__")
query = self.filter_query(query, filters=filters)
return query
def make_ascending_ndb_query(self, kind_class, keys_only=False, filters=None):
"""Construct an NDB query for this key range, without the scan direction.
Args:
kind_class: An ndb.Model subclass.
keys_only: bool, default False, query only for keys.
Returns:
An ndb.Query instance.
"""
assert issubclass(kind_class, ndb.Model)
if keys_only:
default_options = ndb.QueryOptions(keys_only=True)
else:
default_options = None
query = kind_class.query(app=self._app,
namespace=self.namespace,
default_options=default_options)
query = self.filter_ndb_query(query, filters=filters)
query = query.order(kind_class._key)
return query
def make_directed_query(self, kind_class, keys_only=False):
"""Construct a query for this key range, including the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, use keys_only on Query?
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
Raises:
KeyRangeError: if self.direction is not in (KeyRange.ASC, KeyRange.DESC).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_directed_ndb_query(kind_class, keys_only=keys_only)
assert self._app is None, '_app is not supported for db.Query'
direction = self.__get_direction("", "-")
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("%s__key__" % direction)
query = self.filter_query(query)
return query
def make_ascending_query(self, kind_class, keys_only=False, filters=None):
"""Construct a query for this key range without setting the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, query only for keys.
filters: optional list of filters to apply to the query. Each filter is
a tuple: (<property_name_as_str>, <query_operation_as_str>, <value>).
User filters are applied first.
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_ascending_ndb_query(
kind_class, keys_only=keys_only, filters=filters)
assert self._app is None, '_app is not supported for db.Query'
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("__key__")
query = self.filter_query(query, filters=filters)
return query
def make_ascending_ndb_query(self, kind_class, keys_only=False, filters=None):
"""Construct an NDB query for this key range, without the scan direction.
Args:
kind_class: An ndb.Model subclass.
keys_only: bool, default False, query only for keys.
Returns:
An ndb.Query instance.
"""
assert issubclass(kind_class, ndb.Model)
if keys_only:
default_options = ndb.QueryOptions(keys_only=True)
else:
default_options = None
query = kind_class.query(app=self._app,
namespace=self.namespace,
default_options=default_options)
query = self.filter_ndb_query(query, filters=filters)
query = query.order(kind_class._key)
return query
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a CredentialsProperty
or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the datastore.
If the model you are using is an NDB model, using a cache will be
redundant since the model uses an instance cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a CredentialsProperty
or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the datastore.
If the model you are using is an NDB model, using a cache will be
redundant since the model uses an instance cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a
CredentialsProperty or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the
datastore. If the model you are using is an NDB model, using
a cache will be redundant since the model uses an instance
cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no '
'key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def _is_ndb(self):
"""Determine whether the model of the instance is an NDB model.
Returns:
Boolean indicating whether or not the model is an NDB or DB model.
"""
# issubclass will fail if one of the arguments is not a class, only
# need worry about new-style classes since ndb and db models are
# new-style
if isinstance(self._model, type):
if ndb is not None and issubclass(self._model, ndb.Model):
return True
elif issubclass(self._model, db.Model):
return False
raise TypeError('Model class not an NDB or DB model: %s.' %
(self._model,))
def make_directed_query(self, kind_class, keys_only=False):
"""Construct a query for this key range, including the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, use keys_only on Query?
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
Raises:
KeyRangeError: if self.direction is not in (KeyRange.ASC, KeyRange.DESC).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_directed_ndb_query(kind_class, keys_only=keys_only)
assert self._app is None, '_app is not supported for db.Query'
direction = self.__get_direction("", "-")
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("%s__key__" % direction)
query = self.filter_query(query)
return query
def make_ascending_query(self, kind_class, keys_only=False, filters=None):
"""Construct a query for this key range without setting the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, query only for keys.
filters: optional list of filters to apply to the query. Each filter is
a tuple: (<property_name_as_str>, <query_operation_as_str>, <value>).
User filters are applied first.
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_ascending_ndb_query(
kind_class, keys_only=keys_only, filters=filters)
assert self._app is None, '_app is not supported for db.Query'
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("__key__")
query = self.filter_query(query, filters=filters)
return query
def make_ascending_ndb_query(self, kind_class, keys_only=False, filters=None):
"""Construct an NDB query for this key range, without the scan direction.
Args:
kind_class: An ndb.Model subclass.
keys_only: bool, default False, query only for keys.
Returns:
An ndb.Query instance.
"""
assert issubclass(kind_class, ndb.Model)
if keys_only:
default_options = ndb.QueryOptions(keys_only=True)
else:
default_options = None
query = kind_class.query(app=self._app,
namespace=self.namespace,
default_options=default_options)
query = self.filter_ndb_query(query, filters=filters)
query = query.order(kind_class._key)
return query
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a
CredentialsProperty or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the
datastore. If the model you are using is an NDB model, using
a cache will be redundant since the model uses an instance
cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no '
'key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def _is_ndb(self):
"""Determine whether the model of the instance is an NDB model.
Returns:
Boolean indicating whether or not the model is an NDB or DB model.
"""
# issubclass will fail if one of the arguments is not a class, only
# need worry about new-style classes since ndb and db models are
# new-style
if isinstance(self._model, type):
if ndb is not None and issubclass(self._model, ndb.Model):
return True
elif issubclass(self._model, db.Model):
return False
raise TypeError('Model class not an NDB or DB model: %s.' %
(self._model,))
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a CredentialsProperty
or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the datastore.
If the model you are using is an NDB model, using a cache will be
redundant since the model uses an instance cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def query_purchase_with_customer_key():
# [START purchase_with_customer_key_models]
class Customer(ndb.Model):
name = ndb.StringProperty()
class Purchase(ndb.Model):
customer = ndb.KeyProperty(kind=Customer)
price = ndb.IntegerProperty()
# [END purchase_with_customer_key_models]
def query_purchases_for_customer_via_key(customer_entity):
purchases = Purchase.query(
Purchase.customer == customer_entity.key).fetch()
return purchases
return Customer, Purchase, query_purchases_for_customer_via_key
def query_purchase_with_ancestor_key():
# [START purchase_with_ancestor_key_models]
class Customer(ndb.Model):
name = ndb.StringProperty()
class Purchase(ndb.Model):
price = ndb.IntegerProperty()
# [END purchase_with_ancestor_key_models]
def create_purchase_for_customer_with_ancestor(customer_entity):
purchase = Purchase(parent=customer_entity.key)
return purchase
def query_for_purchases_of_customer_with_ancestor(customer_entity):
purchases = Purchase.query(ancestor=customer_entity.key).fetch()
return purchases
return (Customer, Purchase,
create_purchase_for_customer_with_ancestor,
query_for_purchases_of_customer_with_ancestor)
def testEventuallyConsistentGlobalQueryResult(self):
class TestModel(ndb.Model):
pass
user_key = ndb.Key('User', 'ryan')
# Put two entities
ndb.put_multi([
TestModel(parent=user_key),
TestModel(parent=user_key)
])
# Global query doesn't see the data.
self.assertEqual(0, TestModel.query().count(3))
# Ancestor query does see the data.
self.assertEqual(2, TestModel.query(ancestor=user_key).count(3))
# [END HRD_example_1]
# [START HRD_example_2]
def testDeterministicOutcome(self):
# 50% chance to apply.
self.policy.SetProbability(.5)
# Use the pseudo random sequence derived from seed=2.
self.policy.SetSeed(2)
class TestModel(ndb.Model):
pass
TestModel().put()
self.assertEqual(0, TestModel.query().count(3))
self.assertEqual(0, TestModel.query().count(3))
# Will always be applied before the third query.
self.assertEqual(1, TestModel.query().count(3))
# [END HRD_example_2]
# [START main]
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a CredentialsProperty
or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the datastore.
If the model you are using is an NDB model, using a cache will be
redundant since the model uses an instance cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def __init__(self, model, key_name, property_name, cache=None, user=None):
"""Constructor for Storage.
Args:
model: db.Model or ndb.Model, model class
key_name: string, key name for the entity that has the credentials
property_name: string, name of the property that is a CredentialsProperty
or CredentialsNDBProperty.
cache: memcache, a write-through cache to put in front of the datastore.
If the model you are using is an NDB model, using a cache will be
redundant since the model uses an instance cache and memcache for you.
user: users.User object, optional. Can be used to grab user ID as a
key_name if no key name is specified.
"""
if key_name is None:
if user is None:
raise ValueError('StorageByKeyName called with no key name or user.')
key_name = user.user_id()
self._model = model
self._key_name = key_name
self._property_name = property_name
self._cache = cache
def _from_base_type(self, ent):
"""Convert a Model instance (entity) to a Message value."""
if ent._projection:
# Projection query result. Reconstitute the message from the fields.
return _projected_entity_to_message(ent, self._message_type)
blob = ent.blob_
if blob is not None:
protocol = self._protocol_impl
else:
# Perhaps it was written using a different protocol.
protocol = None
for name in _protocols_registry.names:
key = '__%s__' % name
if key in ent._values:
blob = ent._values[key]
if isinstance(blob, model._BaseValue):
blob = blob.b_val
protocol = _protocols_registry.lookup_by_name(name)
break
if blob is None or protocol is None:
return None # This will reveal the underlying dummy model.
msg = protocol.decode_message(self._message_type, blob)
return msg
def _message_to_entity(msg, modelclass):
"""Recursive helper for _to_base_type() to convert a message to an entity.
Args:
msg: A Message instance.
modelclass: A Model subclass.
Returns:
An instance of modelclass.
"""
ent = modelclass()
for prop_name, prop in modelclass._properties.iteritems():
if prop._code_name == 'blob_': # TODO: Devise a cleaner test.
continue # That's taken care of later.
value = getattr(msg, prop_name)
if value is not None and isinstance(prop, model.StructuredProperty):
if prop._repeated:
value = [_message_to_entity(v, prop._modelclass) for v in value]
else:
value = _message_to_entity(value, prop._modelclass)
setattr(ent, prop_name, value)
return ent
def make_ascending_query(self, kind_class, keys_only=False, filters=None):
"""Construct a query for this key range without setting the scan direction.
Args:
kind_class: A kind implementation class (a subclass of either
db.Model or ndb.Model).
keys_only: bool, default False, query only for keys.
filters: optional list of filters to apply to the query. Each filter is
a tuple: (<property_name_as_str>, <query_operation_as_str>, <value>).
User filters are applied first.
Returns:
A db.Query or ndb.Query instance (corresponding to kind_class).
"""
if ndb is not None:
if issubclass(kind_class, ndb.Model):
return self.make_ascending_ndb_query(
kind_class, keys_only=keys_only, filters=filters)
assert self._app is None, '_app is not supported for db.Query'
query = db.Query(kind_class, namespace=self.namespace, keys_only=keys_only)
query.order("__key__")
query = self.filter_query(query, filters=filters)
return query
def make_ascending_ndb_query(self, kind_class, keys_only=False, filters=None):
"""Construct an NDB query for this key range, without the scan direction.
Args:
kind_class: An ndb.Model subclass.
keys_only: bool, default False, query only for keys.
Returns:
An ndb.Query instance.
"""
assert issubclass(kind_class, ndb.Model)
if keys_only:
default_options = ndb.QueryOptions(keys_only=True)
else:
default_options = None
query = kind_class.query(app=self._app,
namespace=self.namespace,
default_options=default_options)
query = self.filter_ndb_query(query, filters=filters)
query = query.order(kind_class._key)
return query
def _validate_filters_ndb(cls, filters, model_class):
"""Validate ndb.Model filters."""
if not filters:
return
properties = model_class._properties
for f in filters:
prop, _, val = f
if prop not in properties:
raise errors.BadReaderParamsError(
"Property %s is not defined for entity type %s",
prop, model_class._get_kind())
try:
properties[prop]._do_validate(val)
except db.BadValueError, e:
raise errors.BadReaderParamsError(e)
model_datastore_input_reader.py 文件源码
项目：Deploy_XXNET_Server
作者: jzp820927
项目源码
文件源码
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def validate(cls, job_config):
"""Inherit docs."""
super(ModelDatastoreInputReader, cls).validate(job_config)
params = job_config.input_reader_params
entity_kind = params[cls.ENTITY_KIND_PARAM]
try:
model_class = util.for_name(entity_kind)
except ImportError, e:
raise errors.BadReaderParamsError("Bad entity kind: %s" % e)
if cls.FILTERS_PARAM in params:
filters = params[cls.FILTERS_PARAM]
if issubclass(model_class, db.Model):
cls._validate_filters(filters, model_class)
else:
cls._validate_filters_ndb(filters, model_class)
property_range.PropertyRange(filters, entity_kind)
