def __reduce__(self):
"""
Pickling should return the model._meta.fields instance of the field,
not a new copy of that field. So, we use the app registry to load the
model and then the field back.
"""
if not hasattr(self, 'model'):
# Fields are sometimes used without attaching them to models (for
# example in aggregation). In this case give back a plain field
# instance. The code below will create a new empty instance of
# class self.__class__, then update its dict with self.__dict__
# values - so, this is very close to normal pickle.
state = self.__dict__.copy()
# The _get_default cached_property can't be pickled due to lambda
# usage.
state.pop('_get_default', None)
return _empty, (self.__class__,), state
return _load_field, (self.model._meta.app_label, self.model._meta.object_name,
self.name)
python类cached_property()的实例源码
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if model._meta.abstract:
continue
fields_with_relations = (
f for f in model._meta._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.remote_field.model, six.string_types):
related_objects_graph[f.remote_field.model._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def cached_property(fn):
"""Dummy cached_property fn, to make setup.py work before installed."""
return fn
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
opts = model._meta
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if opts.abstract:
continue
fields_with_relations = (
f for f in opts._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.remote_field.model, six.string_types):
related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta.concrete_model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
opts = model._meta
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if opts.abstract:
continue
fields_with_relations = (
f for f in opts._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.remote_field.model, six.string_types):
related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta.concrete_model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if model._meta.abstract:
continue
fields_with_relations = (
f for f in model._meta._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.remote_field.model, six.string_types):
related_objects_graph[f.remote_field.model._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def __new__(mcs, name, bases, attrs):
# We can't use it on __init__ because
# cached_property fires on property's __get__
for attr in mcs.CACHED_ATTRS:
if attr in attrs:
attrs[attr] = cached_property(attrs[attr])
return super(WidgetMeta, mcs).__new__(mcs, name, bases, attrs)
def __str__(self):
display_name = self.person.fullname()
party = self.political_party() # do not use the cached_property here because this might fail tests during creation phase
if party:
display_name += ' (' + str(party.name_short) + ')'
return display_name
def get_party(self):
""" this non cached version is needed for cron jobs that gave cache errors when using the cached_property """
if self.person.surname == '':
return None
if not self.document:
return None
members = PartyMember.get_at_date(person=self.person, date=self.document.date_published)
if members.exists():
return members[0].party
return None
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if model._meta.abstract:
continue
fields_with_relations = (
f for f in model._meta._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.remote_field.model, six.string_types):
related_objects_graph[f.remote_field.model._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
opts = model._meta
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if opts.abstract:
continue
fields_with_relations = (
f for f in opts._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.remote_field.model, six.string_types):
related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta.concrete_model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def _populate_directed_relation_graph(self):
"""
This method is used by each model to find its reverse objects. As this
method is very expensive and is accessed frequently (it looks up every
field in a model, in every app), it is computed on first access and then
is set as a property on every model.
"""
related_objects_graph = defaultdict(list)
all_models = self.apps.get_models(include_auto_created=True)
for model in all_models:
# Abstract model's fields are copied to child models, hence we will
# see the fields from the child models.
if model._meta.abstract:
continue
fields_with_relations = (
f for f in model._meta._get_fields(reverse=False, include_parents=False)
if f.is_relation and f.related_model is not None
)
for f in fields_with_relations:
if not isinstance(f.rel.to, six.string_types):
related_objects_graph[f.rel.to._meta].append(f)
for model in all_models:
# Set the relation_tree using the internal __dict__. In this way
# we avoid calling the cached property. In attribute lookup,
# __dict__ takes precedence over a data descriptor (such as
# @cached_property). This means that the _meta._relation_tree is
# only called if related_objects is not in __dict__.
related_objects = related_objects_graph[model._meta]
model._meta.__dict__['_relation_tree'] = related_objects
# It seems it is possible that self is not in all_models, so guard
# against that with default for get().
return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE)
def get_prefetcher(instance, through_attr, to_attr):
"""
For the attribute 'through_attr' on the given instance, finds
an object that has a get_prefetch_queryset().
Returns a 4 tuple containing:
(the object with get_prefetch_queryset (or None),
the descriptor object representing this relationship (or None),
a boolean that is False if the attribute was not found at all,
a boolean that is True if the attribute has already been fetched)
"""
prefetcher = None
is_fetched = False
# For singly related objects, we have to avoid getting the attribute
# from the object, as this will trigger the query. So we first try
# on the class, in order to get the descriptor object.
rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
if rel_obj_descriptor is None:
attr_found = hasattr(instance, through_attr)
else:
attr_found = True
if rel_obj_descriptor:
# singly related object, descriptor object has the
# get_prefetch_queryset() method.
if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
prefetcher = rel_obj_descriptor
if rel_obj_descriptor.is_cached(instance):
is_fetched = True
else:
# descriptor doesn't support prefetching, so we go ahead and get
# the attribute on the instance rather than the class to
# support many related managers
rel_obj = getattr(instance, through_attr)
if hasattr(rel_obj, 'get_prefetch_queryset'):
prefetcher = rel_obj
if through_attr != to_attr:
# Special case cached_property instances because hasattr
# triggers attribute computation and assignment.
if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
is_fetched = to_attr in instance.__dict__
else:
is_fetched = hasattr(instance, to_attr)
else:
is_fetched = through_attr in instance._prefetched_objects_cache
return prefetcher, rel_obj_descriptor, attr_found, is_fetched
def get_prefetcher(instance, through_attr, to_attr):
"""
For the attribute 'through_attr' on the given instance, finds
an object that has a get_prefetch_queryset().
Returns a 4 tuple containing:
(the object with get_prefetch_queryset (or None),
the descriptor object representing this relationship (or None),
a boolean that is False if the attribute was not found at all,
a boolean that is True if the attribute has already been fetched)
"""
prefetcher = None
is_fetched = False
# For singly related objects, we have to avoid getting the attribute
# from the object, as this will trigger the query. So we first try
# on the class, in order to get the descriptor object.
rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
if rel_obj_descriptor is None:
attr_found = hasattr(instance, through_attr)
else:
attr_found = True
if rel_obj_descriptor:
# singly related object, descriptor object has the
# get_prefetch_queryset() method.
if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
prefetcher = rel_obj_descriptor
if rel_obj_descriptor.is_cached(instance):
is_fetched = True
else:
# descriptor doesn't support prefetching, so we go ahead and get
# the attribute on the instance rather than the class to
# support many related managers
rel_obj = getattr(instance, through_attr)
if hasattr(rel_obj, 'get_prefetch_queryset'):
prefetcher = rel_obj
if through_attr != to_attr:
# Special case cached_property instances because hasattr
# triggers attribute computation and assignment.
if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
is_fetched = to_attr in instance.__dict__
else:
is_fetched = hasattr(instance, to_attr)
else:
is_fetched = through_attr in instance._prefetched_objects_cache
return prefetcher, rel_obj_descriptor, attr_found, is_fetched
def get_prefetcher(instance, through_attr, to_attr):
"""
For the attribute 'through_attr' on the given instance, finds
an object that has a get_prefetch_queryset().
Returns a 4 tuple containing:
(the object with get_prefetch_queryset (or None),
the descriptor object representing this relationship (or None),
a boolean that is False if the attribute was not found at all,
a boolean that is True if the attribute has already been fetched)
"""
prefetcher = None
is_fetched = False
# For singly related objects, we have to avoid getting the attribute
# from the object, as this will trigger the query. So we first try
# on the class, in order to get the descriptor object.
rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
if rel_obj_descriptor is None:
attr_found = hasattr(instance, through_attr)
else:
attr_found = True
if rel_obj_descriptor:
# singly related object, descriptor object has the
# get_prefetch_queryset() method.
if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
prefetcher = rel_obj_descriptor
if rel_obj_descriptor.is_cached(instance):
is_fetched = True
else:
# descriptor doesn't support prefetching, so we go ahead and get
# the attribute on the instance rather than the class to
# support many related managers
rel_obj = getattr(instance, through_attr)
if hasattr(rel_obj, 'get_prefetch_queryset'):
prefetcher = rel_obj
if through_attr != to_attr:
# Special case cached_property instances because hasattr
# triggers attribute computation and assignment.
if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
is_fetched = to_attr in instance.__dict__
else:
is_fetched = hasattr(instance, to_attr)
else:
is_fetched = through_attr in instance._prefetched_objects_cache
return prefetcher, rel_obj_descriptor, attr_found, is_fetched
