| /external/python/cpython3/Lib/ |
| plistlib.py | 84 __slots__ = () variable in class:_InternalDict
|
| pprint.py | 82 __slots__ = ['obj'] variable in class:_safe_key
|
| /external/scapy/scapy/contrib/ |
| modbus.py | 636 __slots__ = "defEnum" variable in class:ModbusByteEnumField
|
| /external/scapy/scapy/layers/tls/ |
| session.py | 811 __slots__ = ["tls_session", "rcs_snap_init", "wcs_snap_init"] variable in class:_GenericTLSSessionInheritance
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.10/Lib/pydoc_data/ |
| topics.py | 7 'attribute-access': u'\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of "x.name") for\nclass instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for "self"). "name" is the attribute name. This\n method should return the (computed) attribute value or raise an\n "AttributeError" exception.\n\n Note that if the attribute is found through the normal mechanism,\n "__getattr__()" is not called. (This is an intentional asymmetry\n between "__getattr__()" and "__setattr__()".) This is done both for\n efficiency reasons and because otherwise "__getattr__()" would have\n no way to access other attributes of the instance. Note that at\n least for instance variables, you can fake total control by not\n inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n "__getattribute__()" method below for a way to actually get total\n control in new-style classes.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If "__setattr__()" wants to assign to an instance attribute, it\n should not simply execute "self.name = value" --- this would cause\n a recursive call to itself. Instead, it should insert the value in\n the dictionary of instance attributes, e.g., "self.__dict__[name] =\n value". For new-style classes, rather than accessing the instance\n dictionary, it should call the base class method with the same\n name, for example, "object.__setattr__(self, name, value)".\n\nobject.__delattr__(self, name)\n\n Like "__setattr__()" but for attribute deletion instead of\n assignment. This should only be implemented if "del obj.name" is\n meaningful for the object.\n\n\nMore attribute access for new-style classes\n===========================================\n\nThe following methods only apply to new-style classes.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines "__getattr__()",\n the latter will not be called unless "__getattribute__()" either\n calls it explicitly or raises an "AttributeError". This method\n should return the (computed) attribute value or raise an\n "AttributeError" exception. In order to avoid infinite recursion in\n this method, its implementation should always call the base class\n method with the same name to access any attributes it needs, for\n example, "object.__getattribute__(self, name)".\n\n Note: This method may still be bypassed when looking up special\n methods as the result of implicit invocation via language syntax\n or built-in functions. See Special method lookup for new-style\n classes.\n\n\nImplementing Descriptors\n========================\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' "__dict__".\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or "None" when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an "AttributeError"\n exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n====================\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: "__get__()", "__set__()", and\n"__delete__()". If any of those methods are defined for an object, it\nis said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, "a.x" has a\nlookup chain starting with "a.__dict__[\'x\']", then\n"type(a).__dict__[\'x\']", and continuing through the base classes of\n"type(a)" excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called. Note that descriptors are only invoked for new\nstyle objects or classes (ones that subclass "object()" or "type()").\n\nThe starting point for descriptor invocation is a binding, "a.x". How\nthe arguments are assembled depends on "a":\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: "x.__get__(a)".\n\nInstance Binding\n If binding to a new-style object instance, "a.x" is transformed\n into the call: "type(a).__dict__[\'x\'].__get__(a, type(a))".\n\nClass Binding\n If binding to a new-style class, "A.x" is transformed into the\n call: "A.__dict__[\'x\'].__get__(None, A)".\n\nSuper Binding\n If "a" is an instance of "super", then the binding "super(B,\n obj).m()" searches "obj.__class__.__mro__" for the base class "A"\n immediately preceding "B" and then invokes the descriptor with the\n call: "A.__dict__[\'m\'].__get__(obj, obj.__class__)".\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of "__get__()", "__set__()" and "__delete__()". If it\ndoes not define "__get__()", then accessing the attribute will return\nthe descriptor object itself unless there is a value in the object\'s\ninstance dictionary. If the descriptor defines "__set__()" and/or\n"__delete__()", it is a data descriptor; if it defines neither, it is\na non-data descriptor. Normally, data descriptors define both\n"__get__()" and "__set__()", while non-data descriptors have just the\n"__get__()" method. Data descriptors with "__set__()" and "__get__()"\ndefined always override a redefinition in an instance dictionary. In\ncontrast, non-data descriptors can be overridden by instances.\n\nPython methods (including "staticmethod()" and "classmethod()") are\nimplemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe "property()" function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n=========\n\nBy default, instances of both old and new-style classes have a\ndictionary for attribute storage. This wastes space for objects\nhaving very few instance variables. The space consumption can become\nacute when creating large numbers of instances.\n\nThe default can be overridden by defining *__slots__* in a new-style\nclass definition. The *__slots__* declaration takes a sequence of\ninstance variables and reserves just enough space in each instance to\nhold a value for each variable. Space is saved because *__dict__* is\nnot created for each instance.\n\n__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n new-style class, *__slots__* reserves space for the declared\n variables and prevents the automatic creation of *__dict__* and\n *__weakref__* for each instance.\n\n New in version 2.2.\n\nNotes on using *__slots__*\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises "AttributeError". If\n dynamic assignment of new variables is desired, then add\n "\'__dict__\'" to the sequence of strings in the *__slots__*\n declaration.\n\n Changed in version 2.3: Previously, adding "\'__dict__\'" to the\n *__slots__* declaration would not enable the assignment of new\n attributes not specifically listed in the sequence of instance\n variable names.\n\n* Without a *__weakref__* variable for each instance, classes\n defining *__slots__* do not support weak references to its\n instances. If weak reference support is needed, then add (…)
[all...] |
| /external/python/cpython2/Lib/pydoc_data/ |
| topics.py | 7 'attribute-access': u'\nCustomizing attribute access\n****************************\n\nThe following methods can be defined to customize the meaning of\nattribute access (use of, assignment to, or deletion of "x.name") for\nclass instances.\n\nobject.__getattr__(self, name)\n\n Called when an attribute lookup has not found the attribute in the\n usual places (i.e. it is not an instance attribute nor is it found\n in the class tree for "self"). "name" is the attribute name. This\n method should return the (computed) attribute value or raise an\n "AttributeError" exception.\n\n Note that if the attribute is found through the normal mechanism,\n "__getattr__()" is not called. (This is an intentional asymmetry\n between "__getattr__()" and "__setattr__()".) This is done both for\n efficiency reasons and because otherwise "__getattr__()" would have\n no way to access other attributes of the instance. Note that at\n least for instance variables, you can fake total control by not\n inserting any values in the instance attribute dictionary (but\n instead inserting them in another object). See the\n "__getattribute__()" method below for a way to actually get total\n control in new-style classes.\n\nobject.__setattr__(self, name, value)\n\n Called when an attribute assignment is attempted. This is called\n instead of the normal mechanism (i.e. store the value in the\n instance dictionary). *name* is the attribute name, *value* is the\n value to be assigned to it.\n\n If "__setattr__()" wants to assign to an instance attribute, it\n should not simply execute "self.name = value" --- this would cause\n a recursive call to itself. Instead, it should insert the value in\n the dictionary of instance attributes, e.g., "self.__dict__[name] =\n value". For new-style classes, rather than accessing the instance\n dictionary, it should call the base class method with the same\n name, for example, "object.__setattr__(self, name, value)".\n\nobject.__delattr__(self, name)\n\n Like "__setattr__()" but for attribute deletion instead of\n assignment. This should only be implemented if "del obj.name" is\n meaningful for the object.\n\n\nMore attribute access for new-style classes\n===========================================\n\nThe following methods only apply to new-style classes.\n\nobject.__getattribute__(self, name)\n\n Called unconditionally to implement attribute accesses for\n instances of the class. If the class also defines "__getattr__()",\n the latter will not be called unless "__getattribute__()" either\n calls it explicitly or raises an "AttributeError". This method\n should return the (computed) attribute value or raise an\n "AttributeError" exception. In order to avoid infinite recursion in\n this method, its implementation should always call the base class\n method with the same name to access any attributes it needs, for\n example, "object.__getattribute__(self, name)".\n\n Note: This method may still be bypassed when looking up special\n methods as the result of implicit invocation via language syntax\n or built-in functions. See Special method lookup for new-style\n classes.\n\n\nImplementing Descriptors\n========================\n\nThe following methods only apply when an instance of the class\ncontaining the method (a so-called *descriptor* class) appears in an\n*owner* class (the descriptor must be in either the owner\'s class\ndictionary or in the class dictionary for one of its parents). In the\nexamples below, "the attribute" refers to the attribute whose name is\nthe key of the property in the owner class\' "__dict__".\n\nobject.__get__(self, instance, owner)\n\n Called to get the attribute of the owner class (class attribute\n access) or of an instance of that class (instance attribute\n access). *owner* is always the owner class, while *instance* is the\n instance that the attribute was accessed through, or "None" when\n the attribute is accessed through the *owner*. This method should\n return the (computed) attribute value or raise an "AttributeError"\n exception.\n\nobject.__set__(self, instance, value)\n\n Called to set the attribute on an instance *instance* of the owner\n class to a new value, *value*.\n\nobject.__delete__(self, instance)\n\n Called to delete the attribute on an instance *instance* of the\n owner class.\n\n\nInvoking Descriptors\n====================\n\nIn general, a descriptor is an object attribute with "binding\nbehavior", one whose attribute access has been overridden by methods\nin the descriptor protocol: "__get__()", "__set__()", and\n"__delete__()". If any of those methods are defined for an object, it\nis said to be a descriptor.\n\nThe default behavior for attribute access is to get, set, or delete\nthe attribute from an object\'s dictionary. For instance, "a.x" has a\nlookup chain starting with "a.__dict__[\'x\']", then\n"type(a).__dict__[\'x\']", and continuing through the base classes of\n"type(a)" excluding metaclasses.\n\nHowever, if the looked-up value is an object defining one of the\ndescriptor methods, then Python may override the default behavior and\ninvoke the descriptor method instead. Where this occurs in the\nprecedence chain depends on which descriptor methods were defined and\nhow they were called. Note that descriptors are only invoked for new\nstyle objects or classes (ones that subclass "object()" or "type()").\n\nThe starting point for descriptor invocation is a binding, "a.x". How\nthe arguments are assembled depends on "a":\n\nDirect Call\n The simplest and least common call is when user code directly\n invokes a descriptor method: "x.__get__(a)".\n\nInstance Binding\n If binding to a new-style object instance, "a.x" is transformed\n into the call: "type(a).__dict__[\'x\'].__get__(a, type(a))".\n\nClass Binding\n If binding to a new-style class, "A.x" is transformed into the\n call: "A.__dict__[\'x\'].__get__(None, A)".\n\nSuper Binding\n If "a" is an instance of "super", then the binding "super(B,\n obj).m()" searches "obj.__class__.__mro__" for the base class "A"\n immediately preceding "B" and then invokes the descriptor with the\n call: "A.__dict__[\'m\'].__get__(obj, obj.__class__)".\n\nFor instance bindings, the precedence of descriptor invocation depends\non the which descriptor methods are defined. A descriptor can define\nany combination of "__get__()", "__set__()" and "__delete__()". If it\ndoes not define "__get__()", then accessing the attribute will return\nthe descriptor object itself unless there is a value in the object\'s\ninstance dictionary. If the descriptor defines "__set__()" and/or\n"__delete__()", it is a data descriptor; if it defines neither, it is\na non-data descriptor. Normally, data descriptors define both\n"__get__()" and "__set__()", while non-data descriptors have just the\n"__get__()" method. Data descriptors with "__set__()" and "__get__()"\ndefined always override a redefinition in an instance dictionary. In\ncontrast, non-data descriptors can be overridden by instances.\n\nPython methods (including "staticmethod()" and "classmethod()") are\nimplemented as non-data descriptors. Accordingly, instances can\nredefine and override methods. This allows individual instances to\nacquire behaviors that differ from other instances of the same class.\n\nThe "property()" function is implemented as a data descriptor.\nAccordingly, instances cannot override the behavior of a property.\n\n\n__slots__\n=========\n\nBy default, instances of both old and new-style classes have a\ndictionary for attribute storage. This wastes space for objects\nhaving very few instance variables. The space consumption can become\nacute when creating large numbers of instances.\n\nThe default can be overridden by defining *__slots__* in a new-style\nclass definition. The *__slots__* declaration takes a sequence of\ninstance variables and reserves just enough space in each instance to\nhold a value for each variable. Space is saved because *__dict__* is\nnot created for each instance.\n\n__slots__\n\n This class variable can be assigned a string, iterable, or sequence\n of strings with variable names used by instances. If defined in a\n new-style class, *__slots__* reserves space for the declared\n variables and prevents the automatic creation of *__dict__* and\n *__weakref__* for each instance.\n\n New in version 2.2.\n\nNotes on using *__slots__*\n\n* When inheriting from a class without *__slots__*, the *__dict__*\n attribute of that class will always be accessible, so a *__slots__*\n definition in the subclass is meaningless.\n\n* Without a *__dict__* variable, instances cannot be assigned new\n variables not listed in the *__slots__* definition. Attempts to\n assign to an unlisted variable name raises "AttributeError". If\n dynamic assignment of new variables is desired, then add\n "\'__dict__\'" to the sequence of strings in the *__slots__*\n declaration.\n\n Changed in version 2.3: Previously, adding "\'__dict__\'" to the\n *__slots__* declaration would not enable the assignment of new\n attributes not specifically listed in the sequence of instance\n variable names.\n\n* Without a *__weakref__* variable for each instance, classes\n defining *__slots__* do not support weak references to its\n instances. If weak reference support is needed, then add (…)
[all...] |
| /device/linaro/bootloader/edk2/AppPkg/Applications/Python/Python-2.7.2/Lib/test/ |
| test_builtin.py | 299 __slots__ = []
variable in class:BuiltinTest.test_dir.Foo
306 __slots__ = ["__class__", "__dict__"]
variable in class:BuiltinTest.test_dir.Foo
[all...] |
| pickletester.py | 1041 __slots__ = ["foo"] variable in class:SlotList
[all...] |
| test_weakref.py | 758 __slots__ = "slot1", "slot2"
variable in class:SubclassableWeakrefTestCase.test_subclass_refs_with_slots.MyRef
[all...] |
| /external/python/cpython2/Lib/test/ |
| test_builtin.py | 301 __slots__ = [] variable in class:BuiltinTest.test_dir.Foo
308 __slots__ = ["__class__", "__dict__"] variable in class:BuiltinTest.test_dir.Foo
[all...] |
| test_inspect.py | 120 __slots__ = ("a", "b") variable in class:TestPredicates.test_get_slot_members.C
[all...] |
| /prebuilts/gdb/darwin-x86/lib/python2.7/test/ |
| test_builtin.py | 301 __slots__ = [] variable in class:BuiltinTest.test_dir.Foo
308 __slots__ = ["__class__", "__dict__"] variable in class:BuiltinTest.test_dir.Foo
[all...] |
| pickletester.py | 1073 __slots__ = ["foo"] variable in class:SlotList
[all...] |
| test_inspect.py | 117 __slots__ = ("a", "b") variable in class:TestPredicates.test_get_slot_members.C
[all...] |
| /prebuilts/gdb/linux-x86/lib/python2.7/test/ |
| test_builtin.py | 301 __slots__ = [] variable in class:BuiltinTest.test_dir.Foo
308 __slots__ = ["__class__", "__dict__"] variable in class:BuiltinTest.test_dir.Foo
[all...] |
| pickletester.py | 1073 __slots__ = ["foo"] variable in class:SlotList
[all...] |
| test_inspect.py | 117 __slots__ = ("a", "b") variable in class:TestPredicates.test_get_slot_members.C
[all...] |
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/test/ |
| test_builtin.py | 301 __slots__ = [] variable in class:BuiltinTest.test_dir.Foo
308 __slots__ = ["__class__", "__dict__"] variable in class:BuiltinTest.test_dir.Foo
[all...] |
| /prebuilts/python/linux-x86/2.7.5/lib/python2.7/test/ |
| test_builtin.py | 301 __slots__ = [] variable in class:BuiltinTest.test_dir.Foo
308 __slots__ = ["__class__", "__dict__"] variable in class:BuiltinTest.test_dir.Foo
[all...] |
| /external/python/cpython3/Lib/collections/ |
| __init__.py | 69 __slots__ = 'prev', 'next', 'key', '__weakref__' variable in class:_Link
315 __slots__ = ()
[all...] |
| /external/python/cpython3/Lib/test/ |
| test_exceptions.py | 19 __slots__ = ('x',) variable in class:SlottedNaiveException
[all...] |
| /external/python/cpython3/Lib/unittest/test/testmock/ |
| testhelpers.py | 827 __slots__ = ['slot'] variable in class:SpecSignatureTest.test_autospec_data_descriptor.Foo
|
| /external/python/cpython3/Modules/_decimal/tests/ |
| deccheck.py | 168 __slots__ = ['c', 'p'] variable in class:Context
[all...] |
| /external/scapy/scapy/layers/ |
| dhcp6.py | 282 __slots__ = ["length_from"] variable in class:_DUIDField
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| rnn_cell_impl.py | 464 __slots__ = () variable in class:LSTMStateTuple
[all...] |
