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Searched defs:will (Results 1 - 3 of 3) sorted by relevance

/external/mockito/src/main/java/org/mockito/
H A D	BDDMockito.java	99 BDDMyOngoingStubbing<T> will(Answer<?> answer); method in interface:BDDMockito.BDDMyOngoingStubbing 159 public BDDMyOngoingStubbing<T> will(Answer<?> answer) { method in class:BDDMockito.BDDOngoingStubbingImpl 336 BDDStubber will(Answer<?> answer); method in interface:BDDMockito.BDDStubber 341 * This method will be removed in version 3.0.0 416 public BDDStubber will(Answer<?> answer) { method in class:BDDMockito.BDDStubberImpl 493 public static BDDStubber will(Answer<?> answer) { method in class:BDDMockito
/external/tcpdump/
H A D	print-olsr.c	`114 uint8_t will; member in struct:olsr_hello 434 ME_TO_DOUBLE(ptr.hello->htime), ptr.hello->will));`
/external/python/cpython2/Lib/pydoc_data/
H A D	topics.py	3 topics = {'assert': u'\nThe "assert" statement\n********************\n\nAssert statements are a convenient way to insert debugging assertions\ninto a program:\n\n assert_stmt ::= "assert" expression ["," expression]\n\nThe simple form, "assert expression", is equivalent to\n\n if __debug__:\n if not expression: raise AssertionError\n\nThe extended form, "assert expression1, expression2", is equivalent to\n\n if __debug__:\n if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that "__debug__" and "AssertionError" refer\nto the built-in variables with those names. In the current\nimplementation, the built-in variable "__debug__" is "True" under\nnormal circumstances, "False" when optimization is requested (command\nline option -O). The current code generator emits no code for an\nassert statement when optimization is requested at compile time. Note\nthat it is unnecessary to include the source code for the expression\nthat failed in the error message; it will be displayed as part of the\nstack trace.\n\nAssignments to "__debug__" are illegal. The value for the built-in\nvariable is determined when the interpreter starts.\n', 5 'atom-identifiers': u'\nIdentifiers (Names)\n***************\n\nAn identifier occurring as an atom is a name. See section Identifiers\nand keywords for lexical definition and section Naming and binding for\ndocumentation of naming and binding.\n\nWhen the name is bound to an object, evaluation of the atom yields\nthat object. When a name is not bound, an attempt to evaluate it\nraises a "NameError" exception.\n\nPrivate name mangling:** When an identifier that textually occurs in\na class definition begins with two or more underscore characters and\ndoes not end in two or more underscores, it is considered a private\nname of that class. Private names are transformed to a longer form\nbefore code is generated for them. The transformation inserts the\nclass name, with leading underscores removed and a single underscore\ninserted, in front of the name. For example, the identifier "__spam"\noccurring in a class named "Ham" will be transformed to "_Ham__spam".\nThis transformation is independent of the syntactical context in which\nthe identifier is used. If the transformed name is extremely long\n(longer than 255 characters), implementation defined truncation may\nhappen. If the class name consists only of underscores, no\ntransformation is done.\n', 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\nowner 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\n "\'__weakref__\'" to the sequence of strings in the __slots__\n declaration.\n\n Changed in version 2.3: Previously, adding "\'__weakref__\'" to the\n __slots__ declaration would not enable support for weak\n references.\n\n* __slots__ are implemented at the class level by creating\n descriptors (Implementing Descriptors) for each variable name. As a\n result, class attributes cannot be used to set default values for\n instance variables defined by __slots__; otherwise, the class\n attribute would overwrite the descriptor assignment.\n\n* The action of a __slots__ declaration is limited to the class\n where it is defined. As a result, subclasses will have a __dict__\n unless they also define __slots__ (which must only contain names\n of any additional slots).\n\n* If a class defines a slot also defined in a base class, the\n instance variable defined by the base class slot is inaccessible\n (except by retrieving its descriptor directly from the base class).\n This renders the meaning of the program undefined. In the future, a\n check may be added to prevent this.\n\n* Nonempty __slots__ does not work for classes derived from\n "variable-length" built-in types such as "long", "str" and "tuple".\n\n* Any non-string iterable may be assigned to __slots__. Mappings\n may also be used; however, in the future, special meaning may be\n assigned to the values corresponding to each key.\n\n* __class__ assignment works only if both classes have the same\n __slots__.\n\n Changed in version 2.6: Previously, __class__ assignment raised an\n error if either new or old class had __slots__.\n', 14 'bltin-file-objects': u'\nFile Objects\n***********\n\nFile objects are implemented using C\'s "stdio" package and can be\ncreated with the built-in "open()" function. File objects are also\nreturned by some other built-in functions and methods, such as\n"os.popen()" and "os.fdopen()" and the "makefile()" method of socket\nobjects. Temporary files can be created using the "tempfile" module,\nand high-level file operations such as copying, moving, and deleting\nfiles and directories can be achieved with the "shutil" module.\n\nWhen a file operation fails for an I/O-related reason, the exception\n"IOError" is raised. This includes situations where the operation is\nnot defined for some reason, like "seek()" on a tty device or writing\na file opened for reading.\n\nFiles have the following methods:\n\nfile.close()\n\n Close the file. A closed file cannot be read or written any more.\n Any operation which requires that the file be open will raise a\n "ValueError" after the file has been closed. Calling "close()"\n more than once is allowed.\n\n As of Python 2.5, you can avoid having to call this method\n explicitly if you use the "with" statement. For example, the\n following code will automatically close f* when the "with" block\n is exited:\n\n from __future__ import with_statement # This isn\'t required in Python 2.6\n\n with open("hello.txt") as f:\n for line in f:\n print line,\n\n In older versions of Python, you would have needed to do this to\n get the same effect:\n\n f = open("hello.txt")\n try:\n for line in f:\n print line,\n finally:\n f.close()\n\n Note: Not all "file-like" types in Python support use as a\n context manager for the "with" statement. If your code is\n intended to work with any file-like object, you can use the\n function "contextlib.closing()" instead of using the object\n directly.\n\nfile.flush()\n\n Flush the internal buffer, like "stdio"\'s "fflush()". This may be\n a no-op on some file-like objects.\n\n Note: "flush()" does not necessarily write the file\'s data to\n disk. Use "flush()" followed by "os.fsync()" to ensure this\n behavior.\n\nfile.fileno()\n\n Return the integer "file descriptor" that is used by the underlying\n implementation to request I/O operations from the operating system.\n This can be useful for other, lower level interfaces that use file\n descriptors, such as the "fcntl" module or "os.read()" and friends.\n\n Note: File-like objects which do not have a real file descriptor\n should not provide this method!\n\nfile.isatty()\n\n Return "True" if the file is connected to a tty(-like) device, else\n "False".\n\n Note: If a file-like object is not associated with a real file,\n this method should not be implemented.\n\nfile.next()\n\n A file object is its own iterator, for example "iter(f)" returns\n f (unless f is closed). When a file is used as an iterator,\n typically in a "for" loop (for example, "for line in f: print\n line.strip()"), the "next()" method is called repeatedly. This\n method returns the next input line, or raises "StopIteration" when\n EOF is hit when the file is open for reading (behavior is undefined\n when the file is open for writing). In order to make a "for" loop\n the most efficient way of looping over the lines of a file (a very\n common operation), the "next()" method uses a hidden read-ahead\n buffer. As a consequence of using a read-ahead buffer, combining\n "next()" with other file methods (like "readline()") does not work\n right. However, using "seek()" to reposition the file to an\n absolute position will flush the read-ahead buffer.\n\n New in version 2.3.\n\nfile.read([size])\n\n Read at most size bytes from the file (less if the read hits EOF\n before obtaining size bytes). If the size argument is negative\n or omitted, read all data until EOF is reached. The bytes are\n returned as a string object. An empty string is returned when EOF\n is encountered immediately. (For certain files, like ttys, it\n makes sense to continue reading after an EOF is hit.) Note that\n this method may call the underlying C function "fread()" more than\n once in an effort to acquire as close to size bytes as possible.\n Also note that when in non-blocking mode, less data than was\n requested may be returned, even if no size parameter was given.\n\n Note: This function is simply a wrapper for the underlying\n "fread()" C function, and will behav 27 'customization': u'\\nBasic customization\\n******************\\n\\nobject.__new__(cls[, ...])\\n\\n Called to create a new instance of class cls. "__new__()" is a\\n static method (special-cased so you need not declare it as such)\\n that takes the class of which an instance was requested as its\\n first argument. The remaining arguments are those passed to the\\n object constructor expression (the call to the class). The return\\n value of "__new__()" should be the new object instance (usually an\\n instance of cls).\\n\\n Typical implementations create a new instance of the class by\\n invoking the superclass\\'s "__new__()" method using\\n "super(currentclass, cls).__new__(cls[, ...])" with appropriate\\n arguments and then modifying the newly-created instance as\\n necessary before returning it.\\n\\n If "__new__()" returns an instance of cls, then the new\\n instance\\'s "__init__()" method will be invoked like\\n "__init__(self[, ...])", where self* is the new instance and the\\n remaining arguments are the same as were passed to "__new__()".\\n\\n If "__new__()" does not return an instance of cls, then the new\\n instance\\'s "__init__()" method will not be invoked.\\n\\n "__new__()" is intended mainly to allow subclasses of immutable\\n types (like int, str, or tuple) to customize instance creation. It\\n is also commonly overridden in custom metaclasses in order to\\n customize class creation.\\n\\nobject.__init__(self[, ...])\\n\\n Called after the instance has been created (by "__new__()"), but\\n before it is returned to the caller. The arguments are those\\n passed to the class constructor expression. If a base class has an\\n "__init__()" method, the derived class\\'s "__init__()" method, if\\n any, must explicitly call it to ensure proper initialization of the\\n base class part of the instance; for example:\\n "BaseClass.__init__(self, [args...])".\\n\\n Because "__new__()" and "__init__()" work together in constructing\\n objects ("__new__()" to create it, and "__init__()" to customise\\n it), no non-"None" value may be returned by "__init__()"; doing so\\n will cause a "TypeError" to be raised at runtime.\\n\\nobject.__del__(self)\\n\\n Called when the instance is about to be destroyed. This is also\\n called a destructor. If a base class has a "__del__()" method, the\\n derived class\\'s "__del__()" method, if any, must explicitly call it\\n to ensure proper deletion of the base class part of the instance.\\n Note that it is possible (though not recommended!) for the\\n "__del__()" method to postpone destruction of the instance by\\n creating a new reference to it. It may then be called at a later\\n time when this new reference is deleted. It is not guaranteed that\\n "__del__()" methods are called for objects that still exist when\\n the interpreter exits.\\n\\n Note: "del x" doesn\\'t directly call "x.__del__()" --- the former\\n decrements the reference count for "x" by one, and the latter is\\n only called when "x"\\'s reference count reaches zero. Some common\\n situations that may prevent the reference count of an object from\\n going to zero include: circular references between objects (e.g.,\\n a doubly-linked list or a tree data structure with parent and\\n child pointers); a reference to the object on the stack frame of\\n a function that caught an exception (the traceback stored in\\n "sys.exc_traceback" keeps the stack frame alive); or a reference\\n to the object on the stack frame that raised an unhandled\\n exception in interactive mode (the traceback stored in\\n "sys.last_traceback" keeps the stack frame alive). The first\\n situation can only be remedied by explicitly breaking the cycles;\\n the latter two situations can be resolved by storing "None" in\\n "sys.exc_traceback" or "sys.last_traceback". Circular references\\n which are garbage are detected when the option cycle detector is\\n enabled (it\\'s on by default), but can only be cleaned up if there\\n are no Python-level "__del__()" methods involved. Refer to the\\n documentation for the "gc" module for more information about how\\n "__del__()" methods are handled by the cycle detector,\\n particularly the description of the "garbage" value.\\n\\n Warning: Due to the precarious circumstances under which\\n "__del__()" methods are invoked, exceptions that occur during\\n their execution are ignored, and a warning is printed to\\n "sys.stderr" instead. Also, when "__del__()" is invoked in\\n response to a module being deleted (e.g., when execution of the\\n program is done), other globals referenced by the "__del__()"\\n method may already have been deleted or in the process of being\\n torn down (e.g. the import machinery shutting down). For this\\n reason, "__del__()" methods should do the absolute minimum needed\\n to maintain external invariants. Starting with version 1.5,\\n Python guarantees that globals whose name begins with a single\\n underscore are deleted from their module before other globals are\\n deleted; if no other references to such globals exist, this may\\n help in assuring that imported modules are still available at the\\n time when the "__del__()" method is called.\\n\\n See also the "-R" command-line option.\\n\\nobject.__repr__(self)\\n\\n Called by the "repr()" built-in function and by string conversions\\n (reverse quotes) to compute the "official" string representation of\\n an object. If at all possible, this should look like a valid\\n Python expression that could be used to recreate an object with the\\n same value (given an appropriate environment). If this is not\\n possible, a string of the form "<...some useful description...>"\\n should be returned. The return value must be a string object. If a\\n class defines "__repr__()" but not "__str__()", then "__repr__()"\\n is also used when an "informal" string representation of instances\\n of that class is required.\\n\\n This is typically used for debugging, so it is important that the\\n representation is information-rich and unambiguous.\\n\\nobject.__str__(self)\\n\\n Called by the "str()" built-in function and by the "print"\\n statement to compute the "informal" string representation of an\\n object. This differs from "__repr__()" in that it does not have to\\n be a valid Python expression: a more convenient or concise\\n representation may be used instead. The return value must be a\\n string object.\\n\\nobject.__lt__(self, other)\\nobject.__le__(self, other)\\nobject.__eq__(self, other)\\nobject.__ne__(self, other)\\nobject.__gt__(self, other)\\nobject.__ge__(self, other)\\n\\n New in version 2.1.\\n\\n These are the so-called "rich comparison" methods, and are called\\n for comparison operators in preference to "__cmp__()" below. The\\n correspondence between operator symbols and method names is as\\n follows: "x<y" calls "x.__lt__(y)", "x<=y" calls "x.__le__(y)",\\n "x==y" calls "x.__eq__(y)", "x!=y" and "x<>y" call "x.__ne__(y)",\\n "x>y" calls "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".\\n\\n A rich comparison method may return the singleton "NotImplemented"\\n if it does not implement the operation for a given pair of\\n arguments. By convention, "False" and "True" are returned for a\\n successful comparison. However, these methods can return any value,\\n so if the comparison operator is used in a Boolean context (e.g.,\\n in the condition of an "if" statement), Python will call "bool()"\\n on the value to determine if the result is true or false.\\n\\n There are no implied relationships among the comparison operators.\\n The truth of "x==y" does not imply that "x!=y" is false.\\n Accordingly, when defining "__eq__()", one should also define\\n "__ne__()" so that the operators will behave as expected. See the\\n paragraph on "__hash__()" for some important notes on creating\\n hashable objects which support custom comparison operations and\\n are usable as dictionary keys.\\n\\n There are no swapped-argument versions of these methods (to be used\\n when the left argument does not support the operation but the right\\n argument does); rather, "__lt__()" and "__gt__()" are each other\\'s\\n reflection, "__le__()" and "__ge__()" are each other\\'s reflection,\\n and "__eq__()" and "__ne__()" are their own reflection.\\n\\n Arguments to rich comparison methods are never coerced.\\n\\n To automatically generate ordering operations from a single root\\n operation, see "functools.total_ordering()".\\n\\nobject.__cmp__(self, other)\\n\\n Called by comparison operations if rich comparison (see above) is\\n not defined. Should return a negative integer if "self < other",\\n zero if "self == other", a positive integer if "self > other". If\\n no "__cmp__()", "__eq__()" or "__ne__()" operation is defined,\\n class instances are compared by object identity ("address"). See\\n also the description of "__hash__()" for some important notes on\\n creating hashable objects which support custom comparison\\n operations and are usable as dictionary keys. (Note: the\\n restriction that exceptions are not propagated by "__cmp__()" has\\n been removed since Python 1.5.)\\n\\nobject.__rcmp__(self, other)\\n\\n Changed in version 2.1: No longer supported.\\n\\nobject.__hash__(self)\\n\\n Called by built-in function "hash()" and for operations on members\\n of hashed collections including "set", "frozenset", and "dict".\\n "__hash__()" should return an integer. The only required property\\n is that objects which compare equal have the same hash value; it is\\n advised to somehow mix together (e.g. using exclusive or) the hash\\n values for the components of the object that also play a part in\\n comparison of objects.\\n\\n If a class does not define a "__cmp__()" or "__eq__()" method it\\n should not define a "__hash__()" operation either; if it defines\\n "__cmp__()" or "__eq__()" but not "__hash__()", its instances will\\n not be usable in hashed collections. If a class defines mutable\\n objects and implements a "__cmp__()" or "__eq__()" method, it\\n should not implement "__hash__()", since hashable collection\\n implementations require that an object\\'s hash value is immutable\\n (if the object\\'s hash value changes, it will be in the wrong hash\\n bucket).\\n\\n User-defined classes have "__cmp__()" and "__hash__()" methods by\\n default; with them, all objects compare unequal (except with\\n themselves) and "x.__hash__()" returns a result derived from\\n "id(x)".\\n\\n Classes which inherit a "__hash__()" method from a parent class but\\n change the meaning of "__cmp__()" or "__eq__()" such that the hash\\n value returned is no longer appropriate (e.g. by switching to a\\n value-based concept of equality instead of the default identity\\n based equality) can explicitly flag themselves as being unhashable\\n by setting "__hash__ = None" in the class definition. Doing so\\n means that not only will instances of the class raise an\\n appropriate "TypeError" when a program attempts to retrieve their\\n hash value, but they will also be correctly identified as\\n unhashable when checking "isinstance(obj, collections.Hashable)"\\n (unlike classes which define their own "__hash__()" to explicitly\\n raise "TypeError").\\n\\n Changed in version 2.5: "__hash__()" may now also return a long\\n integer object; the 32-bit integer is then derived from the hash of\\n that object.\\n\\n Changed in version 2.6: "__hash__" may now be set to "None" to\\n explicitly flag instances of a class as unhashable.\\n\\nobject.__nonzero__(self)\\n\\n Called to implement truth value testing and the built-in operation\\n "bool()"; should return "False" or "True", or their integer\\n equivalents "0" or "1". When this method is not defined,\\n "__len__()" is called, if it is defined, and the object is\\n considered true if its result is nonzero. If a class defines\\n neither "__len__()" nor "__nonzero__()", all its instances are\\n considered true.\\n\\nobject.__unicode__(self)\\n\\n Called to implement "unicode()" built-in; should return a Unicode\\n object. When this method is not defined, string conversion is\\n attempted, and the result of string conversion is converted to\\n Unicode using the system default encoding.\\n', namespace 31 'dynamic-features': u'\\nInteraction with dynamic features\\n********************************\\n\\nThere are several cases where Python statements are illegal when used\\nin conjunction with nested scopes that contain free variables.\\n\\nIf a variable is referenced in an enclosing scope, it is illegal to\\ndelete the name. An error will be reported at compile time.\\n\\nIf the wild card form of import --- "import " --- is used in a\\nfunction and the function contains or is a nested block with free\\nvariables, the compiler will raise a "SyntaxError".\\n\\nIf "exec" is used in a function and the function contains or is a\\nnested block with free variables, the compiler will raise a\\n"SyntaxError" unless the exec explicitly specifies the local namespace\\nfor the "exec". (In other words, "exec obj" would be illegal, but\\n"exec obj in ns" would be legal.)\\n\\nThe "eval()", "execfile()", and "input()" functions and the "exec"\\nstatement do not have access to the full environment for resolving\\nnames. Names may be resolved in the local and global namespaces of\\nthe caller. Free variables are not resolved in the nearest enclosing\\nnamespace, but in the global namespace. [1] The "exec" statement and\\nthe "eval()" and "execfile()" functions have optional arguments to\\noverride the global and local namespace. If only one namespace is\\nspecified, it is used for both.\\n', namespace 43 'identifiers': u'\\nIdentifiers and keywords\\n***********************\\n\\nIdentifiers (also referred to as names) are described by the\\nfollowing lexical definitions:\\n\\n identifier ::= (letter\|"_") (letter \| digit \| "_")\\n letter ::= lowercase \| uppercase\\n lowercase ::= "a"..."z"\\n uppercase ::= "A"..."Z"\\n digit ::= "0"..."9"\\n\\nIdentifiers are unlimited in length. Case is significant.\\n\\n\\nKeywords\\n========\\n\\nThe following identifiers are used as reserved words, or keywords of\\nthe language, and cannot be used as ordinary identifiers. They must\\nbe spelled exactly as written here:\\n\\n and del from not while\\n as elif global or with\\n assert else if pass yield\\n break except import print\\n class exec in raise\\n continue finally is return\\n def for lambda try\\n\\nChanged in version 2.4: "None" became a constant and is now recognized\\nby the compiler as a name for the built-in object "None". Although it\\nis not a keyword, you cannot assign a different object to it.\\n\\nChanged in version 2.5: Using "as" and "with" as identifiers triggers\\na warning. To use them as keywords, enable the "with_statement"\\nfuture feature .\\n\\nChanged in version 2.6: "as" and "with" are full keywords.\\n\\n\\nReserved classes of identifiers\\n===============================\\n\\nCertain classes of identifiers (besides keywords) have special\\nmeanings. These classes are identified by the patterns of leading and\\ntrailing underscore characters:\\n\\n"_"\\n Not imported by "from module import ". The special identifier "_"\\n is used in the interactive interpreter to store the result of the\\n last evaluation; it is stored in the "__builtin__" module. When\\n not in interactive mode, "_" has no special meaning and is not\\n defined. See section The import statement.\\n\\n Note: The name "_" is often used in conjunction with\\n internationalization; refer to the documentation for the\\n "gettext" module for more information on this convention.\\n\\n"____"\\n System-defined names. These names are defined by the interpreter\\n and its implementation (including the standard library). Current\\n system names are discussed in the Special method names section and\\n elsewhere. More will likely be defined in future versions of\\n Python. Any* use of "____" names, in any context, that does not\\n follow explicitly documented use, is subject to breakage without\\n warning.\\n\\n"__"\\n Class-private names. Names in this category, when used within the\\n context of a class definition, are re-written to use a mangled form\\n to help avoid name clashes between "private" attributes of base and\\n derived classes. See section Identifiers (Names).\\n', namespace [all...]

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