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5  'atom-literals': "\nLiterals\n********\n\nPython supports string literals and various numeric literals:\n\n   literal ::= stringliteral | integer | longinteger\n               | floatnumber | imagnumber\n\nEvaluation of a literal yields an object of the given type (string,\ninteger, long integer, floating point number, complex number) with the\ngiven value.  The value may be approximated in the case of floating\npoint and imaginary (complex) literals.  See section *Literals* for\ndetails.\n\nAll literals correspond to immutable data types, and hence the\nobject's identity is less important than its value.  Multiple\nevaluations of literals with the same value (either the same\noccurrence in the program text or a different occurrence) may obtain\nthe same object or a different object with the same value.\n",
21 important
25 'customization': '\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\n an 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 when the instance is created. 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,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``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,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__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\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_traceback`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled 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\n references which are garbage are detected when the option cycle\n detector is enabled (it\'s on by default), but can only be cleaned\n up if there are no Python-level ``__del__()`` methods involved.\n Refer to the documentation for the ``gc`` module for more\n information about how ``__del__()`` methods are handled by the\n cycle detector, particularly the description of the ``garbage``\n value.\n\n Warning: Due to the precarious circumstances under which ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted or in the process of being torn down (e.g. the\n import machinery shutting down). For this reason, ``__del__()``\n methods should do the absolute minimum needed to maintain\n external invariants. Starting with version 1.5, Python\n 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\n conversions (reverse quotes) to compute the "official" string\n representation of an object. If at all possible, this should look\n like a valid Python expression that could be used to recreate an\n object with the same value (given an appropriate environment). If\n this is not possible, a string of the form ``<...some useful\n description...>`` should be returned. The return value must be a\n string object. If a class defines ``__repr__()`` but not\n ``__str__()``, then ``__repr__()`` is also used when an "informal"\n string representation of instances 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\n to 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\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` and\n ``x<>y`` call ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and\n ``x>=y`` calls ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n 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\n the paragraph on ``__hash__()`` for some importantimportant notes on creating *hashable* objects which support custom\n comparison 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\n members of hashed collections including ``set``, ``frozenset``, and\n ``dict``. ``__hash__()`` should return an integer. The only\n required property is that objects which compare equal have the same\n hash value; it is advised to somehow mix together (e.g. using\n exclusive or) the hash values for the components of the object that\n also play a part in comparison of objects.\n\n If a class does not define a ``__cmp__()`` or ``__eq__()`` method\n it should not define a ``__hash__()`` operation either; if it\n defines ``__cmp__()`` or ``__eq__()`` but not ``__hash__()``, its\n instances will not be usable in hashed collections. If a class\n defines mutable objects and implements a ``__cmp__()`` or\n ``__eq__()`` method, it should not implement ``__hash__()``, since\n hashable collection implementations require that a object\'s hash\n value is immutable (if the object\'s hash value changes, it will be\n in the wrong hash bucket).\n\n User-defined classes have ``__cmp__()`` and ``__hash__()`` methods\n by default; with them, all objects compare unequal (except with\n themselves) and ``x.__hash__()`` returns ``id(x)``.\n\n Classes which inherit a ``__hash__()`` method from a parent class\n but change the meaning of ``__cmp__()`` or ``__eq__()`` such that\n the hash value returned is no longer appropriate (e.g. by switching\n to a value-based concept of equality instead of the default\n identity based equality) can explicitly flag themselves as being\n unhashable by setting ``__hash__ = None`` in the class definition.\n Doing so 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',
37 'function': '\nFunction definitions\n********************\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n decorated ::= decorators (classdef | funcdef)\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE\n funcdef ::= "def" funcname "(" [parameter_list] ")" ":" suite\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n ( "*" identifier ["," "**" identifier]\n | "**" identifier\n | defparameter [","] )\n defparameter ::= parameter ["=" expression]\n sublist ::= parameter ("," parameter)* [","]\n parameter ::= identifier | "(" sublist ")"\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code:\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to:\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more top-level *parameters* have the form *parameter*\n``=`` *expression*, the function is said to have "default parameter\nvalues." For a parameter with a default value, the corresponding\n*argument* may be omitted from a call, in which case the parameter\'s\ndefault value is substituted. If a parameter has a default value, all\nfollowing parameters must also have a default value --- this is a\nsyntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated when the function definition\nis executed.** This means that the expression is evaluated once, when\nthe function is defined, and that the same "pre-computed" value is\nused for each call. This is especially important to understand when a\ndefault parameter is a mutable object, such as a list or a dictionary:\nif the function modifies the object (e.g. by appending an item to a\nlist), the default value is in effect modified. This is generally not\nwhat was intended. A way around this is to use ``None`` as the\ndefault, and explicitly test for it in the body of the function, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n"``*identifier``" is present, it is initialized to a tuple receiving\nany excess positional parameters, defaulting to the empty tuple. If\nthe form "``**identifier``" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda forms,\ndescribed in section *Lambdas*. Note that the lambda form is merely a\nshorthand for a simplified function definition; a function defined in\na "``def``" statement can be passed around or assigned to another name\njust like a function defined by a lambda form. The "``def``" form is\nactually more powerful since it allows the execution of multiple\nstatements.\n\n**Programmer\'s note:** Functions are first-class objects. A "``def``"\nform executed inside a function definition defines a local function\nthat can be returned or passed around. Free variables used in the\nnested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n',
61 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\n to 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\n ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` and\n ``x<>y`` call ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and\n ``x>=y`` calls ``x.__ge__(y)``.\n\n A rich comparison method may return the singleton\n ``NotImplemented`` if it does not implement the operation for a\n given pair of arguments. By convention, ``False`` and ``True`` are\n returned for a successful comparison. However, these methods can\n return any value, so if the comparison operator is used in a\n Boolean context (e.g., in the condition of an ``if`` statement),\n Python will call ``bool()`` on the value to determine if the result\n 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\n the paragraph on ``__hash__()`` for some important notes on\n creating *hashable* objects which support custom comparison\n operations and 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\n other\'s reflection, ``__le__()`` and ``__ge__()`` are each other\'s\n reflection, and ``__eq__()`` and ``__ne__()`` are their own\n 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``.\n If no ``__cmp__()``, ``__eq__()`` or ``__ne__()`` operation is\n defined, class instances are compared by object identity\n ("address"). See also the description of ``__hash__()`` for some\n important
65 'truth': "\nTruth Value Testing\n*******************\n\nAny object can be tested for truth value, for use in an ``if`` or\n``while`` condition or as operand of the Boolean operations below. The\nfollowing values are considered false:\n\n* ``None``\n\n* ``False``\n\n* zero of any numeric type, for example, ``0``, ``0L``, ``0.0``,\n ``0j``.\n\n* any empty sequence, for example, ``''``, ``()``, ``[]``.\n\n* any empty mapping, for example, ``{}``.\n\n* instances of user-defined classes, if the class defines a\n ``__nonzero__()`` or ``__len__()`` method, when that method returns\n the integer zero or ``bool`` value ``False``. [1]\n\nAll other values are considered true --- so objects of many types are\nalways true.\n\nOperations and built-in functions that have a Boolean result always\nreturn ``0`` or ``False`` for false and ``1`` or ``True`` for true,\nunless otherwise stated. (Important exception: the Boolean operations\n``or`` and ``and`` always return one of their operands.)\n",
67 ost of the attributes labelled "Writable" check the type of the\n assigned value.\n\n Changed in version 2.4: ``func_name`` is now writable.\n\n Function objects also support getting and setting arbitrary\n attributes, which can be used, for example, to attach metadata\n to functions. Regular attribute dot-notation is used to get and\n set such attributes. *Note that the current implementation only\n supports function attributes on user-defined functions. Function\n attributes on built-in functions may be supported in the\n future.*\n\n Additional information about a function\'s definition can be\n retrieved from its code object; see the description of internal\n types below.\n\n User-defined methods\n A user-defined method object combines a class, a class instance\n (or ``None``) and any callable object (normally a user-defined\n function).\n\n Special read-only attributes: ``im_self`` is the class instance\n object, ``im_func`` is the function object; ``im_class`` is the\n class of ``im_self`` for bound methods or the class that asked\n for the method for unbound methods; ``__doc__`` is the method\'s\n documentation (same as ``im_func.__doc__``); ``__name__`` is the\n method name (same as ``im_func.__name__``); ``__module__`` is\n the name of the module the method was defined in, or ``None`` if\n unavailable.\n\n Changed in version 2.2: ``im_self`` used to refer to the class\n that defined the method.\n\n Changed in version 2.6: For Python 3 forward-compatibility,\n ``im_func`` is also available as ``__func__``, and ``im_self``\n as ``__self__``.\n\n Methods also support accessing (but not setting) the arbitrary\n function attributes on the underlying function object.\n\n User-defined method objects may be created when getting an\n attribute of a class (perhaps via an instance of that class), if\n that attribute is a user-defined function object, an unbound\n user-defined method object, or a class method object. When the\n attribute is a user-defined method object, a new method object\n is only created if the class from which it is being retrieved is\n the same as, or a derived class of, the class stored in the\n original method object; otherwise, the original method object is\n used as it is.\n\n When a user-defined method object is created by retrieving a\n user-defined function object from a class, its ``im_self``\n attribute is ``None`` and the method object is said to be\n unbound. When one is created by retrieving a user-defined\n function object from a class via one of its instances, its\n ``im_self`` attribute is the instance, and the method object is\n said to be bound. In either case, the new method\'s ``im_class``\n attribute is the class from which the retrieval takes place, and\n its ``im_func`` attribute is the original function object.\n\n When a user-defined method object is created by retrieving\n another method object from a class or instance, the behaviour is\n the same as for a function object, except that the ``im_func``\n attribute of the new instance is not the original method object\n but its ``im_func`` attribute.\n\n When a user-defined method object is created by retrieving a\n class method object from a class or instance, its ``im_self``\n attribute is the class itself, and its ``im_func`` attribute is\n the function object underlying the class method.\n\n When an unbound user-defined method object is called, the\n underlying function (``im_func``) is called, with the\n restriction that the first argument must be an instance of the\n proper class (``im_class``) or of a derived class thereof.\n\n When a bound user-defined method object is called, the\n underlying function (``im_func``) is called, inserting the class\n instance (``im_self``) in front of the argument list. For\n instance, when ``C`` is a class which contains a definition for\n a function ``f()``, and ``x`` is an instance of ``C``, calling\n ``x.f(1)`` is equivalent to calling ``C.f(x, 1)``.\n\n When a user-defined method object is derived from a class method\n object, the "class instance" stored in ``im_self`` will actually\n be the class itself, so that calling either ``x.f(1)`` or\n ``C.f(1)`` is equivalent to calling ``f(C,1)`` where ``f`` is\n the underlying function.\n\n Note that the transformation from function object to (unbound or\n bound) method object happens each time the attribute is\n retrieved from the class or instance. In some cases, a fruitful\n optimization is to assign the attribute to a local variable and\n call that local variable. Also notice that this transformation\n only happens for user-defined functions; other callable objects\n (and all non-callable objects) are retrieved without\n transformation. It is also important length)\n\n This method takes a single integer argument *length* and\n computes information about the extended slice that the slice\n object would describe if applied to a sequence of *length*\n items. It returns a tuple of three integers; respectively\n these are the *start* and *stop* indices and the *step* or\n stride length of the slice. Missing or out-of-bounds indices\n are handled in a manner consistent with regular slices.\n\n New in version 2.3.\n\n Static method objects\n Static method objects provide a way of defeating the\n transformation of function objects to method objects described\n above. A static method object is a wrapper around any other\n object, usually a user-defined method object. When a static\n method object is retrieved from a class or a class instance, the\n object actually returned is the wrapped object, which is not\n subject to any further transformation. Static method objects are\n not themselves callable, although the objects they wrap usually\n are. Static method objects are created by the built-in\n ``staticmethod()`` constructor.\n\n Class method objects\n A class method object, like a static method object, is a wrapper\n around another object that alters the way in which that object\n is retrieved from classes and class instances. The behaviour of\n class method objects upon such retrieval is described above,\n under "User-defined methods". Class method objects are created\n by the built-in ``classmethod()`` constructor.\n',