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train | Property._retrieve_value | Internal helper to retrieve the value for this Property from an entity.
This returns None if no value is set, or the default argument if
given. For a repeated Property this returns a list if a value is
set, otherwise None. No additional transformations are applied. | ndb/model.py | def _retrieve_value(self, entity, default=None):
"""Internal helper to retrieve the value for this Property from an entity.
This returns None if no value is set, or the default argument if
given. For a repeated Property this returns a list if a value is
set, otherwise None. No additional transformati... | def _retrieve_value(self, entity, default=None):
"""Internal helper to retrieve the value for this Property from an entity.
This returns None if no value is set, or the default argument if
given. For a repeated Property this returns a list if a value is
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train | Property._get_base_value_unwrapped_as_list | Like _get_base_value(), but always returns a list.
Returns:
A new list of unwrapped base values. For an unrepeated
property, if the value is missing or None, returns [None]; for a
repeated property, if the original value is missing or None or
empty, returns []. | ndb/model.py | def _get_base_value_unwrapped_as_list(self, entity):
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Returns:
A new list of unwrapped base values. For an unrepeated
property, if the value is missing or None, returns [None]; for a
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train | Property._opt_call_from_base_type | Call _from_base_type() if necessary.
If the value is a _BaseValue instance, unwrap it and call all
_from_base_type() methods. Otherwise, return the value
unchanged. | ndb/model.py | def _opt_call_from_base_type(self, value):
"""Call _from_base_type() if necessary.
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train | Property._opt_call_to_base_type | Call _to_base_type() if necessary.
If the value is a _BaseValue instance, return it unchanged.
Otherwise, call all _validate() and _to_base_type() methods and
wrap it in a _BaseValue instance. | ndb/model.py | def _opt_call_to_base_type(self, value):
"""Call _to_base_type() if necessary.
If the value is a _BaseValue instance, return it unchanged.
Otherwise, call all _validate() and _to_base_type() methods and
wrap it in a _BaseValue instance.
"""
if not isinstance(value, _BaseValue):
value = _B... | def _opt_call_to_base_type(self, value):
"""Call _to_base_type() if necessary.
If the value is a _BaseValue instance, return it unchanged.
Otherwise, call all _validate() and _to_base_type() methods and
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"""
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train | Property._call_from_base_type | Call all _from_base_type() methods on the value.
This calls the methods in the reverse method resolution order of
the property's class. | ndb/model.py | def _call_from_base_type(self, value):
"""Call all _from_base_type() methods on the value.
This calls the methods in the reverse method resolution order of
the property's class.
"""
methods = self._find_methods('_from_base_type', reverse=True)
call = self._apply_list(methods)
return call(va... | def _call_from_base_type(self, value):
"""Call all _from_base_type() methods on the value.
This calls the methods in the reverse method resolution order of
the property's class.
"""
methods = self._find_methods('_from_base_type', reverse=True)
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train | Property._call_to_base_type | Call all _validate() and _to_base_type() methods on the value.
This calls the methods in the method resolution order of the
property's class. | ndb/model.py | def _call_to_base_type(self, value):
"""Call all _validate() and _to_base_type() methods on the value.
This calls the methods in the method resolution order of the
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"""
methods = self._find_methods('_validate', '_to_base_type')
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train | Property._call_shallow_validation | Call the initial set of _validate() methods.
This is similar to _call_to_base_type() except it only calls
those _validate() methods that can be called without needing to
call _to_base_type().
An example: suppose the class hierarchy is A -> B -> C ->
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"""Call the initial set of _validate() methods.
This is similar to _call_to_base_type() except it only calls
those _validate() methods that can be called without needing to
call _to_base_type().
An example: suppose the class hierarchy is A -> B -> C ->
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This is similar to _call_to_base_type() except it only calls
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train | Property._find_methods | Compute a list of composable methods.
Because this is a common operation and the class hierarchy is
static, the outcome is cached (assuming that for a particular list
of names the reversed flag is either always on, or always off).
Args:
*names: One or more method names.
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"""Compute a list of composable methods.
Because this is a common operation and the class hierarchy is
static, the outcome is cached (assuming that for a particular list
of names the reversed flag is either always on, or always off).
Args:
*names: One ... | def _find_methods(cls, *names, **kwds):
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Because this is a common operation and the class hierarchy is
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train | Property._apply_list | Return a single callable that applies a list of methods to a value.
If a method returns None, the last value is kept; if it returns
some other value, that replaces the last value. Exceptions are
not caught. | ndb/model.py | def _apply_list(self, methods):
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some other value, that replaces the last value. Exceptions are
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train | Property._apply_to_values | Apply a function to the property value/values of a given entity.
This retrieves the property value, applies the function, and then
stores the value back. For a repeated property, the function is
applied separately to each of the values in the list. The
resulting value or list of values is both stored... | ndb/model.py | def _apply_to_values(self, entity, function):
"""Apply a function to the property value/values of a given entity.
This retrieves the property value, applies the function, and then
stores the value back. For a repeated property, the function is
applied separately to each of the values in the list. The... | def _apply_to_values(self, entity, function):
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stores the value back. For a repeated property, the function is
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train | Property._get_value | Internal helper to get the value for this Property from an entity.
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list if it is not set. | ndb/model.py | def _get_value(self, entity):
"""Internal helper to get the value for this Property from an entity.
For a repeated Property this initializes the value to an empty
list if it is not set.
"""
if entity._projection:
if self._name not in entity._projection:
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"""Internal helper to get the value for this Property from an entity.
For a repeated Property this initializes the value to an empty
list if it is not set.
"""
if entity._projection:
if self._name not in entity._projection:
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train | Property._delete_value | Internal helper to delete the value for this Property from an entity.
Note that if no value exists this is a no-op; deleted values will
not be serialized but requesting their value will return None (or
an empty list in the case of a repeated Property). | ndb/model.py | def _delete_value(self, entity):
"""Internal helper to delete the value for this Property from an entity.
Note that if no value exists this is a no-op; deleted values will
not be serialized but requesting their value will return None (or
an empty list in the case of a repeated Property).
"""
if... | def _delete_value(self, entity):
"""Internal helper to delete the value for this Property from an entity.
Note that if no value exists this is a no-op; deleted values will
not be serialized but requesting their value will return None (or
an empty list in the case of a repeated Property).
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train | Property._is_initialized | Internal helper to ask if the entity has a value for this Property.
This returns False if a value is stored but it is None. | ndb/model.py | def _is_initialized(self, entity):
"""Internal helper to ask if the entity has a value for this Property.
This returns False if a value is stored but it is None.
"""
return (not self._required or
((self._has_value(entity) or self._default is not None) and
self._get_value(entity... | def _is_initialized(self, entity):
"""Internal helper to ask if the entity has a value for this Property.
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"""
return (not self._required or
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train | Property._serialize | Internal helper to serialize this property to a protocol buffer.
Subclasses may override this method.
Args:
entity: The entity, a Model (subclass) instance.
pb: The protocol buffer, an EntityProto instance.
prefix: Optional name prefix used for StructuredProperty
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projection=None):
"""Internal helper to serialize this property to a protocol buffer.
Subclasses may override this method.
Args:
entity: The entity, a Model (subclass) instance.
pb: The protocol buffer, an Enti... | def _serialize(self, entity, pb, prefix='', parent_repeated=False,
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entity: The entity, a Model (subclass) instance.
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train | Property._deserialize | Internal helper to deserialize this property from a protocol buffer.
Subclasses may override this method.
Args:
entity: The entity, a Model (subclass) instance.
p: A Property Message object (a protocol buffer).
depth: Optional nesting depth, default 1 (unused here, but used
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entity: The entity, a Model (subclass) instance.
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train | ModelKey._set_value | Setter for key attribute. | ndb/model.py | def _set_value(self, entity, value):
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train | StructuredProperty._get_value | Override _get_value() to *not* raise UnprojectedPropertyError. | ndb/model.py | def _get_value(self, entity):
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train | Model.__get_arg | Internal helper method to parse keywords that may be property names. | ndb/model.py | def __get_arg(cls, kwds, kwd):
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train | Model._set_attributes | Internal helper to set attributes from keyword arguments.
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train | Model._find_uninitialized | Internal helper to find uninitialized properties.
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"""Internal helper to find uninitialized properties.
Returns:
A set of property names.
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train | Model._check_initialized | Internal helper to check for uninitialized properties.
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"""Internal helper to check for uninitialized properties.
Raises:
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train | Model._reset_kind_map | Clear the kind map. Useful for testing. | ndb/model.py | def _reset_kind_map(cls):
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default_model: The model class to use if the kind can't be found.
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kind: A string representing the name of the kind to lookup.
default_model: The model class to use if the kind can't be found.
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The model class for the requested kind.
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kind: A string representing the name of the kind to lookup.
default_model: The model class to use if the kind can't be found.
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train | Model._to_pb | Internal helper to turn an entity into an EntityProto protobuf. | ndb/model.py | def _to_pb(self, pb=None, allow_partial=False, set_key=True):
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if not allow_partial:
self._check_initialized()
if pb is None:
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train | Model._key_to_pb | Internal helper to copy the key into a protobuf. | ndb/model.py | def _key_to_pb(self, pb):
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train | Model._from_pb | Internal helper to create an entity from an EntityProto protobuf. | ndb/model.py | def _from_pb(cls, pb, set_key=True, ent=None, key=None):
"""Internal helper to create an entity from an EntityProto protobuf."""
if not isinstance(pb, entity_pb.EntityProto):
raise TypeError('pb must be a EntityProto; received %r' % pb)
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train | Model._get_property_for | Internal helper to get the Property for a protobuf-level property. | ndb/model.py | def _get_property_for(self, p, indexed=True, depth=0):
"""Internal helper to get the Property for a protobuf-level property."""
parts = p.name().split('.')
if len(parts) <= depth:
# Apparently there's an unstructured value here.
# Assume it is a None written for a missing value.
# (It coul... | def _get_property_for(self, p, indexed=True, depth=0):
"""Internal helper to get the Property for a protobuf-level property."""
parts = p.name().split('.')
if len(parts) <= depth:
# Apparently there's an unstructured value here.
# Assume it is a None written for a missing value.
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train | Model._clone_properties | Internal helper to clone self._properties if necessary. | ndb/model.py | def _clone_properties(self):
"""Internal helper to clone self._properties if necessary."""
cls = self.__class__
if self._properties is cls._properties:
self._properties = dict(cls._properties) | def _clone_properties(self):
"""Internal helper to clone self._properties if necessary."""
cls = self.__class__
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train | Model._fake_property | Internal helper to create a fake Property. | ndb/model.py | def _fake_property(self, p, next, indexed=True):
"""Internal helper to create a fake Property."""
self._clone_properties()
if p.name() != next and not p.name().endswith('.' + next):
prop = StructuredProperty(Expando, next)
prop._store_value(self, _BaseValue(Expando()))
else:
compressed... | def _fake_property(self, p, next, indexed=True):
"""Internal helper to create a fake Property."""
self._clone_properties()
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prop = StructuredProperty(Expando, next)
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train | Model._to_dict | Return a dict containing the entity's property values.
Args:
include: Optional set of property names to include, default all.
exclude: Optional set of property names to skip, default none.
A name contained in both include and exclude is excluded. | ndb/model.py | def _to_dict(self, include=None, exclude=None):
"""Return a dict containing the entity's property values.
Args:
include: Optional set of property names to include, default all.
exclude: Optional set of property names to skip, default none.
A name contained in both include and exclude is exc... | def _to_dict(self, include=None, exclude=None):
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include: Optional set of property names to include, default all.
exclude: Optional set of property names to skip, default none.
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train | Model._fix_up_properties | Fix up the properties by calling their _fix_up() method.
Note: This is called by MetaModel, but may also be called manually
after dynamically updating a model class. | ndb/model.py | def _fix_up_properties(cls):
"""Fix up the properties by calling their _fix_up() method.
Note: This is called by MetaModel, but may also be called manually
after dynamically updating a model class.
"""
# Verify that _get_kind() returns an 8-bit string.
kind = cls._get_kind()
if not isinstan... | def _fix_up_properties(cls):
"""Fix up the properties by calling their _fix_up() method.
Note: This is called by MetaModel, but may also be called manually
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"""
# Verify that _get_kind() returns an 8-bit string.
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train | Model._check_properties | Internal helper to check the given properties exist and meet specified
requirements.
Called from query.py.
Args:
property_names: List or tuple of property names -- each being a string,
possibly containing dots (to address subproperties of structured
properties).
Raises:
In... | ndb/model.py | def _check_properties(cls, property_names, require_indexed=True):
"""Internal helper to check the given properties exist and meet specified
requirements.
Called from query.py.
Args:
property_names: List or tuple of property names -- each being a string,
possibly containing dots (to addre... | def _check_properties(cls, property_names, require_indexed=True):
"""Internal helper to check the given properties exist and meet specified
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Called from query.py.
Args:
property_names: List or tuple of property names -- each being a string,
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train | Model._query | Create a Query object for this class.
Args:
distinct: Optional bool, short hand for group_by = projection.
*args: Used to apply an initial filter
**kwds: are passed to the Query() constructor.
Returns:
A Query object. | ndb/model.py | def _query(cls, *args, **kwds):
"""Create a Query object for this class.
Args:
distinct: Optional bool, short hand for group_by = projection.
*args: Used to apply an initial filter
**kwds: are passed to the Query() constructor.
Returns:
A Query object.
"""
# Validating dist... | def _query(cls, *args, **kwds):
"""Create a Query object for this class.
Args:
distinct: Optional bool, short hand for group_by = projection.
*args: Used to apply an initial filter
**kwds: are passed to the Query() constructor.
Returns:
A Query object.
"""
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train | Model._gql | Run a GQL query. | ndb/model.py | def _gql(cls, query_string, *args, **kwds):
"""Run a GQL query."""
from .query import gql # Import late to avoid circular imports.
return gql('SELECT * FROM %s %s' % (cls._class_name(), query_string),
*args, **kwds) | def _gql(cls, query_string, *args, **kwds):
"""Run a GQL query."""
from .query import gql # Import late to avoid circular imports.
return gql('SELECT * FROM %s %s' % (cls._class_name(), query_string),
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train | Model._put_async | Write this entity to Cloud Datastore.
This is the asynchronous version of Model._put(). | ndb/model.py | def _put_async(self, **ctx_options):
"""Write this entity to Cloud Datastore.
This is the asynchronous version of Model._put().
"""
if self._projection:
raise datastore_errors.BadRequestError('Cannot put a partial entity')
from . import tasklets
ctx = tasklets.get_context()
self._prep... | def _put_async(self, **ctx_options):
"""Write this entity to Cloud Datastore.
This is the asynchronous version of Model._put().
"""
if self._projection:
raise datastore_errors.BadRequestError('Cannot put a partial entity')
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train | Model._get_or_insert | Transactionally retrieves an existing entity or creates a new one.
Positional Args:
name: Key name to retrieve or create.
Keyword Args:
namespace: Optional namespace.
app: Optional app ID.
parent: Parent entity key, if any.
context_options: ContextOptions object (not keyword args... | ndb/model.py | def _get_or_insert(*args, **kwds):
"""Transactionally retrieves an existing entity or creates a new one.
Positional Args:
name: Key name to retrieve or create.
Keyword Args:
namespace: Optional namespace.
app: Optional app ID.
parent: Parent entity key, if any.
context_option... | def _get_or_insert(*args, **kwds):
"""Transactionally retrieves an existing entity or creates a new one.
Positional Args:
name: Key name to retrieve or create.
Keyword Args:
namespace: Optional namespace.
app: Optional app ID.
parent: Parent entity key, if any.
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train | Model._get_or_insert_async | Transactionally retrieves an existing entity or creates a new one.
This is the asynchronous version of Model._get_or_insert(). | ndb/model.py | def _get_or_insert_async(*args, **kwds):
"""Transactionally retrieves an existing entity or creates a new one.
This is the asynchronous version of Model._get_or_insert().
"""
# NOTE: The signature is really weird here because we want to support
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... | def _get_or_insert_async(*args, **kwds):
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This is the asynchronous version of Model._get_or_insert().
"""
# NOTE: The signature is really weird here because we want to support
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train | Model._allocate_ids | Allocates a range of key IDs for this model class.
Args:
size: Number of IDs to allocate. Either size or max can be specified,
not both.
max: Maximum ID to allocate. Either size or max can be specified,
not both.
parent: Parent key for which the IDs will be allocated.
**ctx_... | ndb/model.py | def _allocate_ids(cls, size=None, max=None, parent=None, **ctx_options):
"""Allocates a range of key IDs for this model class.
Args:
size: Number of IDs to allocate. Either size or max can be specified,
not both.
max: Maximum ID to allocate. Either size or max can be specified,
not ... | def _allocate_ids(cls, size=None, max=None, parent=None, **ctx_options):
"""Allocates a range of key IDs for this model class.
Args:
size: Number of IDs to allocate. Either size or max can be specified,
not both.
max: Maximum ID to allocate. Either size or max can be specified,
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train | Model._allocate_ids_async | Allocates a range of key IDs for this model class.
This is the asynchronous version of Model._allocate_ids(). | ndb/model.py | def _allocate_ids_async(cls, size=None, max=None, parent=None,
**ctx_options):
"""Allocates a range of key IDs for this model class.
This is the asynchronous version of Model._allocate_ids().
"""
from . import tasklets
ctx = tasklets.get_context()
cls._pre_allocate_ids... | def _allocate_ids_async(cls, size=None, max=None, parent=None,
**ctx_options):
"""Allocates a range of key IDs for this model class.
This is the asynchronous version of Model._allocate_ids().
"""
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ctx = tasklets.get_context()
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train | Model._get_by_id | Returns an instance of Model class by ID.
This is really just a shorthand for Key(cls, id, ...).get().
Args:
id: A string or integer key ID.
parent: Optional parent key of the model to get.
namespace: Optional namespace.
app: Optional app ID.
**ctx_options: Context options.
... | ndb/model.py | def _get_by_id(cls, id, parent=None, **ctx_options):
"""Returns an instance of Model class by ID.
This is really just a shorthand for Key(cls, id, ...).get().
Args:
id: A string or integer key ID.
parent: Optional parent key of the model to get.
namespace: Optional namespace.
app: ... | def _get_by_id(cls, id, parent=None, **ctx_options):
"""Returns an instance of Model class by ID.
This is really just a shorthand for Key(cls, id, ...).get().
Args:
id: A string or integer key ID.
parent: Optional parent key of the model to get.
namespace: Optional namespace.
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train | Model._get_by_id_async | Returns an instance of Model class by ID (and app, namespace).
This is the asynchronous version of Model._get_by_id(). | ndb/model.py | def _get_by_id_async(cls, id, parent=None, app=None, namespace=None,
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"""Returns an instance of Model class by ID (and app, namespace).
This is the asynchronous version of Model._get_by_id().
"""
key = Key(cls._get_kind(), id, parent=parent, app=app, namespace=name... | def _get_by_id_async(cls, id, parent=None, app=None, namespace=None,
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"""Returns an instance of Model class by ID (and app, namespace).
This is the asynchronous version of Model._get_by_id().
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cls: A ndb.model.Model class.
default_hook: Callable specified by ndb internally (do not override).
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train | _ConstructReference | Construct a Reference; the signature is the same as for Key. | ndb/key.py | def _ConstructReference(cls, pairs=None, flat=None,
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train | _ReferenceFromPairs | Construct a Reference from a list of pairs.
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train | _ReferenceFromSerialized | Construct a Reference from a serialized Reference. | ndb/key.py | def _ReferenceFromSerialized(serialized):
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train | _DecodeUrlSafe | Decode a url-safe base64-encoded string.
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train | Key._parse_from_ref | Construct a Reference; the signature is the same as for Key. | ndb/key.py | def _parse_from_ref(cls, pairs=None, flat=None,
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train | Key.parent | Return a Key constructed from all but the last (kind, id) pairs.
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train | Key.string_id | Return the string id in the last (kind, id) pair, if any.
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train | Key.integer_id | Return the integer id in the last (kind, id) pair, if any.
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"""Return the integer id in the last (kind, id) pair, if any.
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An integer id, or None if the key has a string id or is incomplete.
"""
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train | Key.flat | Return a tuple of alternating kind and id values. | ndb/key.py | def flat(self):
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flat = []
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flat.append(id)
return tuple(flat) | def flat(self):
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train | Key.reference | Return the Reference object for this Key.
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NOTE: The caller should not mutate the return value. | ndb/key.py | def reference(self):
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NOTE: The caller should not mutate the return value.
"""
if self.__reference is None:
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train | Key.urlsafe | Return a url-safe string encoding this Key's Reference.
This string is compatible with other APIs and languages and with
the strings used to represent Keys in GQL and in the App Engine
Admin Console. | ndb/key.py | def urlsafe(self):
"""Return a url-safe string encoding this Key's Reference.
This string is compatible with other APIs and languages and with
the strings used to represent Keys in GQL and in the App Engine
Admin Console.
"""
# This is 3-4x faster than urlsafe_b64decode()
urlsafe = base64.b... | def urlsafe(self):
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This string is compatible with other APIs and languages and with
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train | Key.get_async | Return a Future whose result is the entity for this Key.
If no such entity exists, a Future is still returned, and the
Future's eventual return result be None. | ndb/key.py | def get_async(self, **ctx_options):
"""Return a Future whose result is the entity for this Key.
If no such entity exists, a Future is still returned, and the
Future's eventual return result be None.
"""
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train | add_flow_exception | Add an exception that should not be logged.
The argument must be a subclass of Exception. | ndb/tasklets.py | def add_flow_exception(exc):
"""Add an exception that should not be logged.
The argument must be a subclass of Exception.
"""
global _flow_exceptions
if not isinstance(exc, type) or not issubclass(exc, Exception):
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as_set = set(_flow_exc... | def add_flow_exception(exc):
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The argument must be a subclass of Exception.
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train | _init_flow_exceptions | Internal helper to initialize _flow_exceptions.
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"""Internal helper to initialize _flow_exceptions.
This automatically adds webob.exc.HTTPException, if it can be imported.
"""
global _flow_exceptions
_flow_exceptions = ()
add_flow_exception(datastore_errors.Rollback)
try:
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except ImportError:
... | def _init_flow_exceptions():
"""Internal helper to initialize _flow_exceptions.
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global _flow_exceptions
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Example:
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train | _message_to_entity | Recursive helper for _to_base_type() to convert a message to an entity.
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train | EnumProperty._validate | Validate an Enum value.
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train | MessageProperty._to_base_type | Convert a Message value to a Model instance (entity). | ndb/msgprop.py | def _to_base_type(self, msg):
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train | _ClassKeyProperty._get_value | Compute and store a default value if necessary. | ndb/polymodel.py | def _get_value(self, entity):
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train | PolyModel._from_pb | Override.
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"""Override.
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prop_name = cls.class_._name
class_name = []
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train | PolyModel._get_kind | Override.
Make sure that the kind returned is the root class of the
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"""Override.
Make sure that the kind returned is the root class of the
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train | PolyModel._get_hierarchy | Internal helper to return the list of polymorphic base classes.
This returns a list of class objects, e.g. [Animal, Feline, Cat]. | ndb/polymodel.py | def _get_hierarchy(cls):
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train | find_env_paths_in_basedirs | Returns all potential envs in a basedir | environment_kernels/envs_common.py | def find_env_paths_in_basedirs(base_dirs):
"""Returns all potential envs in a basedir"""
# get potential env path in the base_dirs
env_path = []
for base_dir in base_dirs:
env_path.extend(glob.glob(os.path.join(
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# self.log.info("Found the ... | def find_env_paths_in_basedirs(base_dirs):
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env_path = []
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train | convert_to_env_data | Converts a list of paths to environments to env_data.
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train | validate_IPykernel | Validates that this env contains an IPython kernel and returns info to start it
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python_exe_name = find_exe(venv_dir, "python")
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train | validate_IRkernel | Validates that this env contains an IRkernel kernel and returns info to start it
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"""
r_exe_name = find_exe(venv_dir, "R")
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train | find_exe | Finds a exe with that name in the environment path | environment_kernels/envs_common.py | def find_exe(env_dir, name):
"""Finds a exe with that name in the environment path"""
if platform.system() == "Windows":
name = name + ".exe"
# find the binary
exe_name = os.path.join(env_dir, name)
if not os.path.exists(exe_name):
exe_name = os.path.join(env_dir, "bin", name)
... | def find_exe(env_dir, name):
"""Finds a exe with that name in the environment path"""
if platform.system() == "Windows":
name = name + ".exe"
# find the binary
exe_name = os.path.join(env_dir, name)
if not os.path.exists(exe_name):
exe_name = os.path.join(env_dir, "bin", name)
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train | get_virtualenv_env_data | Finds kernel specs from virtualenv environments
env_data is a structure {name -> (resourcedir, kernel spec)} | environment_kernels/envs_virtualenv.py | def get_virtualenv_env_data(mgr):
"""Finds kernel specs from virtualenv environments
env_data is a structure {name -> (resourcedir, kernel spec)}
"""
if not mgr.find_virtualenv_envs:
return {}
mgr.log.debug("Looking for virtualenv environments in %s...", mgr.virtualenv_env_dirs)
# fi... | def get_virtualenv_env_data(mgr):
"""Finds kernel specs from virtualenv environments
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"""
if not mgr.find_virtualenv_envs:
return {}
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train | source_bash | Simply bash-specific wrapper around source-foreign
Returns a dict to be used as a new environment | environment_kernels/activate_helper.py | def source_bash(args, stdin=None):
"""Simply bash-specific wrapper around source-foreign
Returns a dict to be used as a new environment"""
args = list(args)
new_args = ['bash', '--sourcer=source']
new_args.extend(args)
return source_foreign(new_args, stdin=stdin) | def source_bash(args, stdin=None):
"""Simply bash-specific wrapper around source-foreign
Returns a dict to be used as a new environment"""
args = list(args)
new_args = ['bash', '--sourcer=source']
new_args.extend(args)
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train | source_zsh | Simply zsh-specific wrapper around source-foreign
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"""Simply zsh-specific wrapper around source-foreign
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args = list(args)
new_args = ['zsh', '--sourcer=source']
new_args.extend(args)
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args = list(args)
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train | source_cmd | Simple cmd.exe-specific wrapper around source-foreign.
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"""Simple cmd.exe-specific wrapper around source-foreign.
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"""
args = list(args)
fpath = locate_binary(args[0])
args[0] = fpath if fpath else args[0]
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function does not add these spaces. This ... | environment_kernels/activate_helper.py | def argvquote(arg, force=False):
""" Returns an argument quoted in such a way that that CommandLineToArgvW
on Windows will return the argument string unchanged.
This is the same thing Popen does when supplied with an list of arguments.
Arguments in a command line should be separated by spaces; this
... | def argvquote(arg, force=False):
""" Returns an argument quoted in such a way that that CommandLineToArgvW
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... | Cadair/jupyter_environment_kernels | python | https://github.com/Cadair/jupyter_environment_kernels/blob/3da304550b511bda7d5d39280379b5ca39bb31bc/environment_kernels/activate_helper.py#L124-L155 | [
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train | escape_windows_cmd_string | Returns a string that is usable by the Windows cmd.exe.
The escaping is based on details here and emperical testing:
http://www.robvanderwoude.com/escapechars.php | environment_kernels/activate_helper.py | def escape_windows_cmd_string(s):
"""Returns a string that is usable by the Windows cmd.exe.
The escaping is based on details here and emperical testing:
http://www.robvanderwoude.com/escapechars.php
"""
for c in '()%!^<>&|"':
s = s.replace(c, '^' + c)
s = s.replace('/?', '/.')
retur... | def escape_windows_cmd_string(s):
"""Returns a string that is usable by the Windows cmd.exe.
The escaping is based on details here and emperical testing:
http://www.robvanderwoude.com/escapechars.php
"""
for c in '()%!^<>&|"':
s = s.replace(c, '^' + c)
s = s.replace('/?', '/.')
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train | source_foreign | Sources a file written in a foreign shell language. | environment_kernels/activate_helper.py | def source_foreign(args, stdin=None):
"""Sources a file written in a foreign shell language."""
parser = _ensure_source_foreign_parser()
ns = parser.parse_args(args)
if ns.prevcmd is not None:
pass # don't change prevcmd if given explicitly
elif os.path.isfile(ns.files_or_code[0]):
... | def source_foreign(args, stdin=None):
"""Sources a file written in a foreign shell language."""
parser = _ensure_source_foreign_parser()
ns = parser.parse_args(args)
if ns.prevcmd is not None:
pass # don't change prevcmd if given explicitly
elif os.path.isfile(ns.files_or_code[0]):
... | [
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train | _is_executable_file | Checks that path is an executable regular file, or a symlink towards one.
This is roughly ``os.path isfile(path) and os.access(path, os.X_OK)``.
This function was forked from pexpect originally:
Copyright (c) 2013-2014, Pexpect development team
Copyright (c) 2012, Noah Spurrier <noah@noah.org>
PE... | environment_kernels/activate_helper.py | def _is_executable_file(path):
"""Checks that path is an executable regular file, or a symlink towards one.
This is roughly ``os.path isfile(path) and os.access(path, os.X_OK)``.
This function was forked from pexpect originally:
Copyright (c) 2013-2014, Pexpect development team
Copyright (c) 2012,... | def _is_executable_file(path):
"""Checks that path is an executable regular file, or a symlink towards one.
This is roughly ``os.path isfile(path) and os.access(path, os.X_OK)``.
This function was forked from pexpect originally:
Copyright (c) 2013-2014, Pexpect development team
Copyright (c) 2012,... | [
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train | foreign_shell_data | Extracts data from a foreign (non-xonsh) shells. Currently this gets
the environment, aliases, and functions but may be extended in the future.
Parameters
----------
shell : str
The name of the shell, such as 'bash' or '/bin/sh'.
interactive : bool, optional
Whether the shell should... | environment_kernels/activate_helper.py | def foreign_shell_data(shell, interactive=True, login=False, envcmd=None,
aliascmd=None, extra_args=(), currenv=None,
safe=False, prevcmd='', postcmd='', funcscmd=None,
sourcer=None, use_tmpfile=False, tmpfile_ext=None,
runcmd=N... | def foreign_shell_data(shell, interactive=True, login=False, envcmd=None,
aliascmd=None, extra_args=(), currenv=None,
safe=False, prevcmd='', postcmd='', funcscmd=None,
sourcer=None, use_tmpfile=False, tmpfile_ext=None,
runcmd=N... | [
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train | to_bool | Converts to a boolean in a semantically meaningful way. | environment_kernels/activate_helper.py | def to_bool(x):
""""Converts to a boolean in a semantically meaningful way."""
if isinstance(x, bool):
return x
elif isinstance(x, str):
return False if x.lower() in _FALSES else True
else:
return bool(x) | def to_bool(x):
""""Converts to a boolean in a semantically meaningful way."""
if isinstance(x, bool):
return x
elif isinstance(x, str):
return False if x.lower() in _FALSES else True
else:
return bool(x) | [
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train | parse_env | Parses the environment portion of string into a dict. | environment_kernels/activate_helper.py | def parse_env(s):
"""Parses the environment portion of string into a dict."""
m = ENV_RE.search(s)
if m is None:
return {}
g1 = m.group(1)
env = dict(ENV_SPLIT_RE.findall(g1))
return env | def parse_env(s):
"""Parses the environment portion of string into a dict."""
m = ENV_RE.search(s)
if m is None:
return {}
g1 = m.group(1)
env = dict(ENV_SPLIT_RE.findall(g1))
return env | [
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train | get_conda_env_data | Finds kernel specs from conda environments
env_data is a structure {name -> (resourcedir, kernel spec)} | environment_kernels/envs_conda.py | def get_conda_env_data(mgr):
"""Finds kernel specs from conda environments
env_data is a structure {name -> (resourcedir, kernel spec)}
"""
if not mgr.find_conda_envs:
return {}
mgr.log.debug("Looking for conda environments in %s...", mgr.conda_env_dirs)
# find all potential env paths... | def get_conda_env_data(mgr):
"""Finds kernel specs from conda environments
env_data is a structure {name -> (resourcedir, kernel spec)}
"""
if not mgr.find_conda_envs:
return {}
mgr.log.debug("Looking for conda environments in %s...", mgr.conda_env_dirs)
# find all potential env paths... | [
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train | _find_conda_env_paths_from_conda | Returns a list of path as given by `conda env list --json`.
Returns empty list, if conda couldn't be called. | environment_kernels/envs_conda.py | def _find_conda_env_paths_from_conda(mgr):
"""Returns a list of path as given by `conda env list --json`.
Returns empty list, if conda couldn't be called.
"""
# this is expensive, so make it configureable...
if not mgr.use_conda_directly:
return []
mgr.log.debug("Looking for conda envir... | def _find_conda_env_paths_from_conda(mgr):
"""Returns a list of path as given by `conda env list --json`.
Returns empty list, if conda couldn't be called.
"""
# this is expensive, so make it configureable...
if not mgr.use_conda_directly:
return []
mgr.log.debug("Looking for conda envir... | [
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train | EnvironmentKernelSpecManager.validate_env | Check the name of the environment against the black list and the
whitelist. If a whitelist is specified only it is checked. | environment_kernels/core.py | def validate_env(self, envname):
"""
Check the name of the environment against the black list and the
whitelist. If a whitelist is specified only it is checked.
"""
if self.whitelist_envs and envname in self.whitelist_envs:
return True
elif self.whitelist_envs... | def validate_env(self, envname):
"""
Check the name of the environment against the black list and the
whitelist. If a whitelist is specified only it is checked.
"""
if self.whitelist_envs and envname in self.whitelist_envs:
return True
elif self.whitelist_envs... | [
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train | EnvironmentKernelSpecManager._get_env_data | Get the data about the available environments.
env_data is a structure {name -> (resourcedir, kernel spec)} | environment_kernels/core.py | def _get_env_data(self, reload=False):
"""Get the data about the available environments.
env_data is a structure {name -> (resourcedir, kernel spec)}
"""
# This is called much too often and finding-process is really expensive :-(
if not reload and getattr(self, "_env_data_cache... | def _get_env_data(self, reload=False):
"""Get the data about the available environments.
env_data is a structure {name -> (resourcedir, kernel spec)}
"""
# This is called much too often and finding-process is really expensive :-(
if not reload and getattr(self, "_env_data_cache... | [
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train | EnvironmentKernelSpecManager.find_kernel_specs_for_envs | Returns a dict mapping kernel names to resource directories. | environment_kernels/core.py | def find_kernel_specs_for_envs(self):
"""Returns a dict mapping kernel names to resource directories."""
data = self._get_env_data()
return {name: data[name][0] for name in data} | def find_kernel_specs_for_envs(self):
"""Returns a dict mapping kernel names to resource directories."""
data = self._get_env_data()
return {name: data[name][0] for name in data} | [
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train | EnvironmentKernelSpecManager.get_all_kernel_specs_for_envs | Returns the dict of name -> kernel_spec for all environments | environment_kernels/core.py | def get_all_kernel_specs_for_envs(self):
"""Returns the dict of name -> kernel_spec for all environments"""
data = self._get_env_data()
return {name: data[name][1] for name in data} | def get_all_kernel_specs_for_envs(self):
"""Returns the dict of name -> kernel_spec for all environments"""
data = self._get_env_data()
return {name: data[name][1] for name in data} | [
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