Barry Warsaw avatar Barry Warsaw committed 4fe560d

Bump to version 2.6.8rc1.

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Files changed (7)

Include/patchlevel.h

 /*--start constants--*/
 #define PY_MAJOR_VERSION	2
 #define PY_MINOR_VERSION	6
-#define PY_MICRO_VERSION	7
-#define PY_RELEASE_LEVEL	PY_RELEASE_LEVEL_FINAL
-#define PY_RELEASE_SERIAL	0
+#define PY_MICRO_VERSION	8
+#define PY_RELEASE_LEVEL	PY_RELEASE_LEVEL_GAMMA
+#define PY_RELEASE_SERIAL	1
 
 /* Version as a string */
-#define PY_VERSION      	"2.6.7+"
+#define PY_VERSION      	"2.6.8rc1"
 /*--end constants--*/
 
 /* Subversion Revision number of this file (not of the repository) */

Lib/distutils/__init__.py

 #
 
 #--start constants--
-__version__ = "2.6.7"
+__version__ = "2.6.8rc1"
 #--end constants--

Lib/idlelib/idlever.py

-IDLE_VERSION = "2.6.7"
+IDLE_VERSION = "2.6.8rc1"

Lib/pydoc_topics.py

-# Autogenerated by Sphinx on Fri Jun  3 17:50:16 2011
+# Autogenerated by Sphinx on Thu Feb 23 10:54:32 2012
 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\nto\n\n   if __debug__:\n      if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that ``__debug__`` and ``AssertionError``\nrefer to 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\n(command line option -O).  The current code generator emits no code\nfor an assert statement when optimization is requested at compile\ntime.  Note that it is unnecessary to include the source code for the\nexpression that failed in the error message; it will be displayed as\npart of the stack trace.\n\nAssignments to ``__debug__`` are illegal.  The value for the built-in\nvariable is determined when the interpreter starts.\n',
  'assignment': u'\nAssignment statements\n*********************\n\nAssignment statements are used to (re)bind names to values and to\nmodify attributes or items of mutable objects:\n\n   assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)\n   target_list     ::= target ("," target)* [","]\n   target          ::= identifier\n              | "(" target_list ")"\n              | "[" target_list "]"\n              | attributeref\n              | subscription\n              | slicing\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable.  The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list is recursively defined as\nfollows.\n\n* If the target list is a single target: The object is assigned to\n  that target.\n\n* If the target list is a comma-separated list of targets: The object\n  must be an iterable with the same number of items as there are\n  targets in the target list, and the items are assigned, from left to\n  right, to the corresponding targets. (This rule is relaxed as of\n  Python 1.5; in earlier versions, the object had to be a tuple.\n  Since strings are sequences, an assignment like ``a, b = "xy"`` is\n  now legal as long as the string has the right length.)\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n  * If the name does not occur in a ``global`` statement in the\n    current code block: the name is bound to the object in the current\n    local namespace.\n\n  * Otherwise: the name is bound to the object in the current global\n    namespace.\n\n  The name is rebound if it was already bound.  This may cause the\n  reference count for the object previously bound to the name to reach\n  zero, causing the object to be deallocated and its destructor (if it\n  has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in square\n  brackets: The object must be an iterable with the same number of\n  items as there are targets in the target list, and its items are\n  assigned, from left to right, to the corresponding targets.\n\n* If the target is an attribute reference: The primary expression in\n  the reference is evaluated.  It should yield an object with\n  assignable attributes; if this is not the case, ``TypeError`` is\n  raised.  That object is then asked to assign the assigned object to\n  the given attribute; if it cannot perform the assignment, it raises\n  an exception (usually but not necessarily ``AttributeError``).\n\n  Note: If the object is a class instance and the attribute reference\n  occurs on both sides of the assignment operator, the RHS expression,\n  ``a.x`` can access either an instance attribute or (if no instance\n  attribute exists) a class attribute.  The LHS target ``a.x`` is\n  always set as an instance attribute, creating it if necessary.\n  Thus, the two occurrences of ``a.x`` do not necessarily refer to the\n  same attribute: if the RHS expression refers to a class attribute,\n  the LHS creates a new instance attribute as the target of the\n  assignment:\n\n     class Cls:\n         x = 3             # class variable\n     inst = Cls()\n     inst.x = inst.x + 1   # writes inst.x as 4 leaving Cls.x as 3\n\n  This description does not necessarily apply to descriptor\n  attributes, such as properties created with ``property()``.\n\n* If the target is a subscription: The primary expression in the\n  reference is evaluated.  It should yield either a mutable sequence\n  object (such as a list) or a mapping object (such as a dictionary).\n  Next, the subscript expression is evaluated.\n\n  If the primary is a mutable sequence object (such as a list), the\n  subscript must yield a plain integer.  If it is negative, the\n  sequence\'s length is added to it. The resulting value must be a\n  nonnegative integer less than the sequence\'s length, and the\n  sequence is asked to assign the assigned object to its item with\n  that index.  If the index is out of range, ``IndexError`` is raised\n  (assignment to a subscripted sequence cannot add new items to a\n  list).\n\n  If the primary is a mapping object (such as a dictionary), the\n  subscript must have a type compatible with the mapping\'s key type,\n  and the mapping is then asked to create a key/datum pair which maps\n  the subscript to the assigned object.  This can either replace an\n  existing key/value pair with the same key value, or insert a new\n  key/value pair (if no key with the same value existed).\n\n* If the target is a slicing: The primary expression in the reference\n  is evaluated.  It should yield a mutable sequence object (such as a\n  list).  The assigned object should be a sequence object of the same\n  type.  Next, the lower and upper bound expressions are evaluated,\n  insofar they are present; defaults are zero and the sequence\'s\n  length.  The bounds should evaluate to (small) integers.  If either\n  bound is negative, the sequence\'s length is added to it. The\n  resulting bounds are clipped to lie between zero and the sequence\'s\n  length, inclusive.  Finally, the sequence object is asked to replace\n  the slice with the items of the assigned sequence.  The length of\n  the slice may be different from the length of the assigned sequence,\n  thus changing the length of the target sequence, if the object\n  allows it.\n\n**CPython implementation detail:** In the current implementation, the\nsyntax for targets is taken to be the same as for expressions, and\ninvalid syntax is rejected during the code generation phase, causing\nless detailed error messages.\n\nWARNING: Although the definition of assignment implies that overlaps\nbetween the left-hand side and the right-hand side are \'safe\' (for\nexample ``a, b = b, a`` swaps two variables), overlaps *within* the\ncollection of assigned-to variables are not safe!  For instance, the\nfollowing program prints ``[0, 2]``:\n\n   x = [0, 1]\n   i = 0\n   i, x[i] = 1, 2\n   print x\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n   augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n   augtarget                 ::= identifier | attributeref | subscription | slicing\n   augop                     ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="\n             | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions for the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like ``x += 1`` can be rewritten as\n``x = x + 1`` to achieve a similar, but not exactly equal effect. In\nthe augmented version, ``x`` is only evaluated once. Also, when\npossible, the actual operation is performed *in-place*, meaning that\nrather than creating a new object and assigning that to the target,\nthe old object is modified instead.\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n',
  'atom-identifiers': u'\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name.  See section\n*Identifiers and keywords* for lexical definition and section *Naming\nand binding* for documentation 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\n**Private 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 in front of the name, with leading underscores removed, and\na single underscore inserted in front of the class name.  For example,\nthe identifier ``__spam`` occurring in a class named ``Ham`` will be\ntransformed to ``_Ham__spam``.  This transformation is independent of\nthe syntactical context in which the identifier is used.  If the\ntransformed name is extremely long (longer than 255 characters),\nimplementation defined truncation may happen.  If the class name\nconsists only of underscores, no transformation is done.\n',
  'context-managers': u'\nWith Statement Context Managers\n*******************************\n\nNew in version 2.5.\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code.  Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n   Enter the runtime context related to this object. The ``with``\n   statement will bind this method\'s return value to the target(s)\n   specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n   Exit the runtime context related to this object. The parameters\n   describe the exception that caused the context to be exited. If the\n   context was exited without an exception, all three arguments will\n   be ``None``.\n\n   If an exception is supplied, and the method wishes to suppress the\n   exception (i.e., prevent it from being propagated), it should\n   return a true value. Otherwise, the exception will be processed\n   normally upon exit from this method.\n\n   Note that ``__exit__()`` methods should not reraise the passed-in\n   exception; this is the caller\'s responsibility.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n',
  'continue': u'\nThe ``continue`` statement\n**************************\n\n   continue_stmt ::= "continue"\n\n``continue`` may only occur syntactically nested in a ``for`` or\n``while`` loop, but not nested in a function or class definition or\n``finally`` clause within that loop.  It continues with the next cycle\nof the nearest enclosing loop.\n\nWhen ``continue`` passes control out of a ``try`` statement with a\n``finally`` clause, that ``finally`` clause is executed before really\nstarting the next loop cycle.\n',
  'conversions': u'\nArithmetic conversions\n**********************\n\nWhen a description of an arithmetic operator below uses the phrase\n"the numeric arguments are converted to a common type," the arguments\nare coerced using the coercion rules listed at  *Coercion rules*.  If\nboth arguments are standard numeric types, the following coercions are\napplied:\n\n* If either argument is a complex number, the other is converted to\n  complex;\n\n* otherwise, if either argument is a floating point number, the other\n  is converted to floating point;\n\n* otherwise, if either argument is a long integer, the other is\n  converted to long integer;\n\n* otherwise, both must be plain integers and no conversion is\n  necessary.\n\nSome additional rules apply for certain operators (e.g., a string left\nargument to the \'%\' operator). Extensions can define their own\ncoercions.\n',
- '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\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\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 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 the Total Ordering recipe in the ASPN cookbook.\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 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',
+ '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\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 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 the Total Ordering recipe in the ASPN cookbook.\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 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',
  'debugger': u'\n``pdb`` --- The Python Debugger\n*******************************\n\nThe module ``pdb`` defines an interactive source code debugger for\nPython programs.  It supports setting (conditional) breakpoints and\nsingle stepping at the source line level, inspection of stack frames,\nsource code listing, and evaluation of arbitrary Python code in the\ncontext of any stack frame.  It also supports post-mortem debugging\nand can be called under program control.\n\nThe debugger is extensible --- it is actually defined as the class\n``Pdb``. This is currently undocumented but easily understood by\nreading the source.  The extension interface uses the modules ``bdb``\nand ``cmd``.\n\nThe debugger\'s prompt is ``(Pdb)``. Typical usage to run a program\nunder control of the debugger is:\n\n   >>> import pdb\n   >>> import mymodule\n   >>> pdb.run(\'mymodule.test()\')\n   > <string>(0)?()\n   (Pdb) continue\n   > <string>(1)?()\n   (Pdb) continue\n   NameError: \'spam\'\n   > <string>(1)?()\n   (Pdb)\n\n``pdb.py`` can also be invoked as a script to debug other scripts.\nFor example:\n\n   python -m pdb myscript.py\n\nWhen invoked as a script, pdb will automatically enter post-mortem\ndebugging if the program being debugged exits abnormally. After post-\nmortem debugging (or after normal exit of the program), pdb will\nrestart the program. Automatic restarting preserves pdb\'s state (such\nas breakpoints) and in most cases is more useful than quitting the\ndebugger upon program\'s exit.\n\nNew in version 2.4: Restarting post-mortem behavior added.\n\nThe typical usage to break into the debugger from a running program is\nto insert\n\n   import pdb; pdb.set_trace()\n\nat the location you want to break into the debugger.  You can then\nstep through the code following this statement, and continue running\nwithout the debugger using the ``c`` command.\n\nThe typical usage to inspect a crashed program is:\n\n   >>> import pdb\n   >>> import mymodule\n   >>> mymodule.test()\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in ?\n     File "./mymodule.py", line 4, in test\n       test2()\n     File "./mymodule.py", line 3, in test2\n       print spam\n   NameError: spam\n   >>> pdb.pm()\n   > ./mymodule.py(3)test2()\n   -> print spam\n   (Pdb)\n\nThe module defines the following functions; each enters the debugger\nin a slightly different way:\n\npdb.run(statement[, globals[, locals]])\n\n   Execute the *statement* (given as a string) under debugger control.\n   The debugger prompt appears before any code is executed; you can\n   set breakpoints and type ``continue``, or you can step through the\n   statement using ``step`` or ``next`` (all these commands are\n   explained below).  The optional *globals* and *locals* arguments\n   specify the environment in which the code is executed; by default\n   the dictionary of the module ``__main__`` is used.  (See the\n   explanation of the ``exec`` statement or the ``eval()`` built-in\n   function.)\n\npdb.runeval(expression[, globals[, locals]])\n\n   Evaluate the *expression* (given as a string) under debugger\n   control.  When ``runeval()`` returns, it returns the value of the\n   expression.  Otherwise this function is similar to ``run()``.\n\npdb.runcall(function[, argument, ...])\n\n   Call the *function* (a function or method object, not a string)\n   with the given arguments.  When ``runcall()`` returns, it returns\n   whatever the function call returned.  The debugger prompt appears\n   as soon as the function is entered.\n\npdb.set_trace()\n\n   Enter the debugger at the calling stack frame.  This is useful to\n   hard-code a breakpoint at a given point in a program, even if the\n   code is not otherwise being debugged (e.g. when an assertion\n   fails).\n\npdb.post_mortem([traceback])\n\n   Enter post-mortem debugging of the given *traceback* object.  If no\n   *traceback* is given, it uses the one of the exception that is\n   currently being handled (an exception must be being handled if the\n   default is to be used).\n\npdb.pm()\n\n   Enter post-mortem debugging of the traceback found in\n   ``sys.last_traceback``.\n',
  'del': u'\nThe ``del`` statement\n*********************\n\n   del_stmt ::= "del" target_list\n\nDeletion is recursively defined very similar to the way assignment is\ndefined. Rather that spelling it out in full details, here are some\nhints.\n\nDeletion of a target list recursively deletes each target, from left\nto right.\n\nDeletion of a name removes the binding of that name  from the local or\nglobal namespace, depending on whether the name occurs in a ``global``\nstatement in the same code block.  If the name is unbound, a\n``NameError`` exception will be raised.\n\nIt is illegal to delete a name from the local namespace if it occurs\nas a free variable in a nested block.\n\nDeletion of attribute references, subscriptions and slicings is passed\nto the primary object involved; deletion of a slicing is in general\nequivalent to assignment of an empty slice of the right type (but even\nthis is determined by the sliced object).\n',
  'dict': u'\nDictionary displays\n*******************\n\nA dictionary display is a possibly empty series of key/datum pairs\nenclosed in curly braces:\n\n   dict_display   ::= "{" [key_datum_list] "}"\n   key_datum_list ::= key_datum ("," key_datum)* [","]\n   key_datum      ::= expression ":" expression\n\nA dictionary display yields a new dictionary object.\n\nThe key/datum pairs are evaluated from left to right to define the\nentries of the dictionary: each key object is used as a key into the\ndictionary to store the corresponding datum.\n\nRestrictions on the types of the key values are listed earlier in\nsection *The standard type hierarchy*.  (To summarize, the key type\nshould be *hashable*, which excludes all mutable objects.)  Clashes\nbetween duplicate keys are not detected; the last datum (textually\nrightmost in the display) stored for a given key value prevails.\n',
  'shifting': u'\nShifting operations\n*******************\n\nThe shifting operations have lower priority than the arithmetic\noperations:\n\n   shift_expr ::= a_expr | shift_expr ( "<<" | ">>" ) a_expr\n\nThese operators accept plain or long integers as arguments.  The\narguments are converted to a common type.  They shift the first\nargument to the left or right by the number of bits given by the\nsecond argument.\n\nA right shift by *n* bits is defined as division by ``pow(2, n)``.  A\nleft shift by *n* bits is defined as multiplication with ``pow(2,\nn)``.  Negative shift counts raise a ``ValueError`` exception.\n',
  'slicings': u'\nSlicings\n********\n\nA slicing selects a range of items in a sequence object (e.g., a\nstring, tuple or list).  Slicings may be used as expressions or as\ntargets in assignment or ``del`` statements.  The syntax for a\nslicing:\n\n   slicing          ::= simple_slicing | extended_slicing\n   simple_slicing   ::= primary "[" short_slice "]"\n   extended_slicing ::= primary "[" slice_list "]"\n   slice_list       ::= slice_item ("," slice_item)* [","]\n   slice_item       ::= expression | proper_slice | ellipsis\n   proper_slice     ::= short_slice | long_slice\n   short_slice      ::= [lower_bound] ":" [upper_bound]\n   long_slice       ::= short_slice ":" [stride]\n   lower_bound      ::= expression\n   upper_bound      ::= expression\n   stride           ::= expression\n   ellipsis         ::= "..."\n\nThere is ambiguity in the formal syntax here: anything that looks like\nan expression list also looks like a slice list, so any subscription\ncan be interpreted as a slicing.  Rather than further complicating the\nsyntax, this is disambiguated by defining that in this case the\ninterpretation as a subscription takes priority over the\ninterpretation as a slicing (this is the case if the slice list\ncontains no proper slice nor ellipses).  Similarly, when the slice\nlist has exactly one short slice and no trailing comma, the\ninterpretation as a simple slicing takes priority over that as an\nextended slicing.\n\nThe semantics for a simple slicing are as follows.  The primary must\nevaluate to a sequence object.  The lower and upper bound expressions,\nif present, must evaluate to plain integers; defaults are zero and the\n``sys.maxint``, respectively.  If either bound is negative, the\nsequence\'s length is added to it.  The slicing now selects all items\nwith index *k* such that ``i <= k < j`` where *i* and *j* are the\nspecified lower and upper bounds.  This may be an empty sequence.  It\nis not an error if *i* or *j* lie outside the range of valid indexes\n(such items don\'t exist so they aren\'t selected).\n\nThe semantics for an extended slicing are as follows.  The primary\nmust evaluate to a mapping object, and it is indexed with a key that\nis constructed from the slice list, as follows.  If the slice list\ncontains at least one comma, the key is a tuple containing the\nconversion of the slice items; otherwise, the conversion of the lone\nslice item is the key.  The conversion of a slice item that is an\nexpression is that expression.  The conversion of an ellipsis slice\nitem is the built-in ``Ellipsis`` object.  The conversion of a proper\nslice is a slice object (see section *The standard type hierarchy*)\nwhose ``start``, ``stop`` and ``step`` attributes are the values of\nthe expressions given as lower bound, upper bound and stride,\nrespectively, substituting ``None`` for missing expressions.\n',
  'specialattrs': u"\nSpecial Attributes\n******************\n\nThe implementation adds a few special read-only attributes to several\nobject types, where they are relevant.  Some of these are not reported\nby the ``dir()`` built-in function.\n\nobject.__dict__\n\n   A dictionary or other mapping object used to store an object's\n   (writable) attributes.\n\nobject.__methods__\n\n   Deprecated since version 2.2: Use the built-in function ``dir()``\n   to get a list of an object's attributes. This attribute is no\n   longer available.\n\nobject.__members__\n\n   Deprecated since version 2.2: Use the built-in function ``dir()``\n   to get a list of an object's attributes. This attribute is no\n   longer available.\n\ninstance.__class__\n\n   The class to which a class instance belongs.\n\nclass.__bases__\n\n   The tuple of base classes of a class object.\n\nclass.__name__\n\n   The name of the class or type.\n\nThe following attributes are only supported by *new-style class*es.\n\nclass.__mro__\n\n   This attribute is a tuple of classes that are considered when\n   looking for base classes during method resolution.\n\nclass.mro()\n\n   This method can be overridden by a metaclass to customize the\n   method resolution order for its instances.  It is called at class\n   instantiation, and its result is stored in ``__mro__``.\n\nclass.__subclasses__()\n\n   Each new-style class keeps a list of weak references to its\n   immediate subclasses.  This method returns a list of all those\n   references still alive. Example:\n\n      >>> int.__subclasses__()\n      [<type 'bool'>]\n\n-[ Footnotes ]-\n\n[1] Additional information on these special methods may be found in\n    the Python Reference Manual (*Basic customization*).\n\n[2] As a consequence, the list ``[1, 2]`` is considered equal to\n    ``[1.0, 2.0]``, and similarly for tuples.\n\n[3] They must have since the parser can't tell the type of the\n    operands.\n\n[4] To format only a tuple you should therefore provide a singleton\n    tuple whose only element is the tuple to be formatted.\n\n[5] These numbers are fairly arbitrary.  They are intended to avoid\n    printing endless strings of meaningless digits without hampering\n    correct use and without having to know the exact precision of\n    floating point values on a particular machine.\n\n[6] The advantage of leaving the newline on is that returning an empty\n    string is then an unambiguous EOF indication.  It is also possible\n    (in cases where it might matter, for example, if you want to make\n    an exact copy of a file while scanning its lines) to tell whether\n    the last line of a file ended in a newline or not (yes this\n    happens!).\n",
- 'specialnames': u'\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators.  For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``x.__getitem__(i)`` for\nold-style classes and ``type(x).__getitem__(x, i)`` for new-style\nclasses.  Except where mentioned, attempts to execute an operation\nraise an exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled.  For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense.  (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\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\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 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 the Total Ordering recipe in the ASPN cookbook.\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 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\n\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``)\nfor class 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.\n   This method should return the (computed) attribute value or raise\n   an ``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\n   for efficiency reasons and because otherwise ``__getattr__()``\n   would have no way to access other attributes of the instance.  Note\n   that at least for instance variables, you can fake total control by\n   not 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\n   cause a recursive call to itself.  Instead, it should insert the\n   value in the dictionary of instance attributes, e.g.,\n   ``self.__dict__[name] = value``.  For new-style classes, rather\n   than accessing the instance dictionary, it should call the base\n   class method with the same name, for example,\n   ``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\n   ``__getattr__()``, the latter will not be called unless\n   ``__getattribute__()`` either calls it explicitly or raises an\n   ``AttributeError``. This method should return the (computed)\n   attribute value or raise an ``AttributeError`` exception. In order\n   to avoid infinite recursion in this method, its implementation\n   should always call the base class method with the same name to\n   access any attributes it needs, for example,\n   ``object.__getattribute__(self, name)``.\n\n   Note: This method may still be bypassed when looking up special methods\n     as the result of implicit invocation via language syntax or\n     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 the\nclass dictionary of another new-style class, known as the *owner*\nclass. In the examples below, "the attribute" refers to the attribute\nwhose name is the key of the property in the owner class\'\n``__dict__``.  Descriptors can only be implemented as new-style\nclasses themselves.\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\n   ``AttributeError`` 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,\nit is 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\n``type()``).\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the 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\n   ``A`` immediately preceding ``B`` and then invokes the descriptor\n   with the call: ``A.__dict__[\'m\'].__get__(obj, A)``.\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__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary.  If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor.  Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method.  Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary.  In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented 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 defining\n  *__slots__* do not support weak references to its instances. If weak\n  reference support is needed, then add ``\'__weakref__\'`` to the\n  sequence of strings in the *__slots__* 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\n  a 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 instance\n  variable defined by the base class slot is inaccessible (except by\n  retrieving its descriptor directly from the base class). This\n  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\n  ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n  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\n\nCustomizing class creation\n==========================\n\nBy default, new-style classes are constructed using ``type()``. A\nclass definition is read into a separate namespace and the value of\nclass name is bound to the result of ``type(name, bases, dict)``.\n\nWhen the class definition is read, if *__metaclass__* is defined then\nthe callable assigned to it will be called instead of ``type()``. This\nallows classes or functions to be written which monitor or alter the\nclass creation process:\n\n* Modifying the class dictionary prior to the class being created.\n\n* Returning an instance of another class -- essentially performing the\n  role of a factory function.\n\nThese steps will have to be performed in the metaclass\'s ``__new__()``\nmethod -- ``type.__new__()`` can then be called from this method to\ncreate a class with different properties.  This example adds a new\nelement to the class dictionary before creating the class:\n\n   class metacls(type):\n       def __new__(mcs, name, bases, dict):\n           dict[\'foo\'] = \'metacls was here\'\n           return type.__new__(mcs, name, bases, dict)\n\nYou can of course also override other class methods (or add new\nmethods); for example defining a custom ``__call__()`` method in the\nmetaclass allows custom behavior when the class is called, e.g. not\nalways creating a new instance.\n\n__metaclass__\n\n   This variable can be any callable accepting arguments for ``name``,\n   ``bases``, and ``dict``.  Upon class creation, the callable is used\n   instead of the built-in ``type()``.\n\n   New in version 2.2.\n\nThe appropriate metaclass is determined by the following precedence\nrules:\n\n* If ``dict[\'__metaclass__\']`` exists, it is used.\n\n* Otherwise, if there is at least one base class, its metaclass is\n  used (this looks for a *__class__* attribute first and if not found,\n  uses its type).\n\n* Otherwise, if a global variable named __metaclass__ exists, it is\n  used.\n\n* Otherwise, the old-style, classic metaclass (types.ClassType) is\n  used.\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored including logging, interface checking, automatic\ndelegation, automatic property creation, proxies, frameworks, and\nautomatic resource locking/synchronization.\n\n\nCustomizing instance and subclass checks\n========================================\n\nNew in version 2.6.\n\nThe following methods are used to override the default behavior of the\n``isinstance()`` and ``issubclass()`` built-in functions.\n\nIn particular, the metaclass ``abc.ABCMeta`` implements these methods\nin order to allow the addition of Abstract Base Classes (ABCs) as\n"virtual base classes" to any class or type (including built-in\ntypes), and including to other ABCs.\n\nclass.__instancecheck__(self, instance)\n\n   Return true if *instance* should be considered a (direct or\n   indirect) instance of *class*. If defined, called to implement\n   ``isinstance(instance, class)``.\n\nclass.__subclasscheck__(self, subclass)\n\n   Return true if *subclass* should be considered a (direct or\n   indirect) subclass of *class*.  If defined, called to implement\n   ``issubclass(subclass, class)``.\n\nNote that these methods are looked up on the type (metaclass) of a\nclass.  They cannot be defined as class methods in the actual class.\nThis is consistent with the lookup of special methods that are called\non instances, only that in this case the instance is itself a class.\n\nSee also:\n\n   **PEP 3119** - Introducing Abstract Base Classes\n      Includes the specification for customizing ``isinstance()`` and\n      ``issubclass()`` behavior through ``__instancecheck__()`` and\n      ``__subclasscheck__()``, with motivation for this functionality\n      in the context of adding Abstract Base Classes (see the ``abc``\n      module) to the language.\n\n\nEmulating callable objects\n==========================\n\nobject.__call__(self[, args...])\n\n   Called when the instance is "called" as a function; if this method\n   is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n   ``x.__call__(arg1, arg2, ...)``.\n\n\nEmulating container types\n=========================\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well.  The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. (For backwards compatibility, the method\n``__getslice__()`` (see below) can also be defined to handle simple,\nbut not extended slices.) It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``has_key()``,\n``get()``, ``clear()``, ``setdefault()``, ``iterkeys()``,\n``itervalues()``, ``iteritems()``, ``pop()``, ``popitem()``,\n``copy()``, and ``update()`` behaving similar to those for Python\'s\nstandard dictionary objects.  The ``UserDict`` module provides a\n``DictMixin`` class to help create those methods from a base set of\n``__getitem__()``, ``__setitem__()``, ``__delitem__()``, and\n``keys()``. Mutable sequences should provide methods ``append()``,\n``count()``, ``index()``, ``extend()``, ``insert()``, ``pop()``,\n``remove()``, ``reverse()`` and ``sort()``, like Python standard list\nobjects.  Finally, sequence types should implement addition (meaning\nconcatenation) and multiplication (meaning repetition) by defining the\nmethods ``__add__()``, ``__radd__()``, ``__iadd__()``, ``__mul__()``,\n``__rmul__()`` and ``__imul__()`` described below; they should not\ndefine ``__coerce__()`` or other numerical operators.  It is\nrecommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should be equivalent of ``has_key()``;\nfor sequences, it should search through the values.  It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``iterkeys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n   Called to implement the built-in function ``len()``.  Should return\n   the length of the object, an integer ``>=`` 0.  Also, an object\n   that doesn\'t define a ``__nonzero__()`` method and whose\n   ``__len__()`` method returns zero is considered to be false in a\n   Boolean context.\n\nobject.__getitem__(self, key)\n\n   Called to implement evaluation of ``self[key]``. For sequence\n   types, the accepted keys should be integers and slice objects.\n   Note that the special interpretation of negative indexes (if the\n   class wishes to emulate a sequence type) is up to the\n   ``__getitem__()`` method. If *key* is of an inappropriate type,\n   ``TypeError`` may be raised; if of a value outside the set of\n   indexes for the sequence (after any special interpretation of\n   negative values), ``IndexError`` should be raised. For mapping\n   types, if *key* is missing (not in the container), ``KeyError``\n   should be raised.\n\n   Note: ``for`` loops expect that an ``IndexError`` will be raised for\n     illegal indexes to allow proper detection of the end of the\n     sequence.\n\nobject.__setitem__(self, key, value)\n\n   Called to implement assignment to ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support changes to the values for keys, or if new keys\n   can be added, or for sequences if elements can be replaced.  The\n   same exceptions should be raised for improper *key* values as for\n   the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n   Called to implement deletion of ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support removal of keys, or for sequences if elements\n   can be removed from the sequence.  The same exceptions should be\n   raised for improper *key* values as for the ``__getitem__()``\n   method.\n\nobject.__iter__(self)\n\n   This method is called when an iterator is required for a container.\n   This method should return a new iterator object that can iterate\n   over all the objects in the container.  For mappings, it should\n   iterate over the keys of the container, and should also be made\n   available as the method ``iterkeys()``.\n\n   Iterator objects also need to implement this method; they are\n   required to return themselves.  For more information on iterator\n   objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n   Called (if present) by the ``reversed()`` built-in to implement\n   reverse iteration.  It should return a new iterator object that\n   iterates over all the objects in the container in reverse order.\n\n   If the ``__reversed__()`` method is not provided, the\n   ``reversed()`` built-in will fall back to using the sequence\n   protocol (``__len__()`` and ``__getitem__()``).  Objects that\n   support the sequence protocol should only provide\n   ``__reversed__()`` if they can provide an implementation that is\n   more efficient than the one provided by ``reversed()``.\n\n   New in version 2.6.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence.  However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n   Called to implement membership test operators.  Should return true\n   if *item* is in *self*, false otherwise.  For mapping objects, this\n   should consider the keys of the mapping rather than the values or\n   the key-item pairs.\n\n   For objects that don\'t define ``__contains__()``, the membership\n   test first tries iteration via ``__iter__()``, then the old\n   sequence iteration protocol via ``__getitem__()``, see *this\n   section in the language reference*.\n\n\nAdditional methods for emulation of sequence types\n==================================================\n\nThe following optional methods can be defined to further emulate\nsequence objects.  Immutable sequences methods should at most only\ndefine ``__getslice__()``; mutable sequences might define all three\nmethods.\n\nobject.__getslice__(self, i, j)\n\n   Deprecated since version 2.0: Support slice objects as parameters\n   to the ``__getitem__()`` method. (However, built-in types in\n   CPython currently still implement ``__getslice__()``.  Therefore,\n   you have to override it in derived classes when implementing\n   slicing.)\n\n   Called to implement evaluation of ``self[i:j]``. The returned\n   object should be of the same type as *self*.  Note that missing *i*\n   or *j* in the slice expression are replaced by zero or\n   ``sys.maxint``, respectively.  If negative indexes are used in the\n   slice, the length of the sequence is added to that index. If the\n   instance does not implement the ``__len__()`` method, an\n   ``AttributeError`` is raised. No guarantee is made that indexes\n   adjusted this way are not still negative.  Indexes which are\n   greater than the length of the sequence are not modified. If no\n   ``__getslice__()`` is found, a slice object is created instead, and\n   passed to ``__getitem__()`` instead.\n\nobject.__setslice__(self, i, j, sequence)\n\n   Called to implement assignment to ``self[i:j]``. Same notes for *i*\n   and *j* as for ``__getslice__()``.\n\n   This method is deprecated. If no ``__setslice__()`` is found, or\n   for extended slicing of the form ``self[i:j:k]``, a slice object is\n   created, and passed to ``__setitem__()``, instead of\n   ``__setslice__()`` being called.\n\nobject.__delslice__(self, i, j)\n\n   Called to implement deletion of ``self[i:j]``. Same notes for *i*\n   and *j* as for ``__getslice__()``. This method is deprecated. If no\n   ``__delslice__()`` is found, or for extended slicing of the form\n   ``self[i:j:k]``, a slice object is created, and passed to\n   ``__delitem__()``, instead of ``__delslice__()`` being called.\n\nNotice that these methods are only invoked when a single slice with a\nsingle colon is used, and the slice method is available.  For slice\noperations involving extended slice notation, or in absence of the\nslice methods, ``__getitem__()``, ``__setitem__()`` or\n``__delitem__()`` is called with a slice object as argument.\n\nThe following example demonstrate how to make your program or module\ncompatible with earlier versions of Python (assuming that methods\n``__getitem__()``, ``__setitem__()`` and ``__delitem__()`` support\nslice objects as arguments):\n\n   class MyClass:\n       ...\n       def __getitem__(self, index):\n           ...\n       def __setitem__(self, index, value):\n           ...\n       def __delitem__(self, index):\n           ...\n\n       if sys.version_info < (2, 0):\n           # They won\'t be defined if version is at least 2.0 final\n\n           def __getslice__(self, i, j):\n               return self[max(0, i):max(0, j):]\n           def __setslice__(self, i, j, seq):\n               self[max(0, i):max(0, j):] = seq\n           def __delslice__(self, i, j):\n               del self[max(0, i):max(0, j):]\n       ...\n\nNote the calls to ``max()``; these are necessary because of the\nhandling of negative indices before the ``__*slice__()`` methods are\ncalled.  When negative indexes are used, the ``__*item__()`` methods\nreceive them as provided, but the ``__*slice__()`` methods get a\n"cooked" form of the index values.  For each negative index value, the\nlength of the sequence is added to the index before calling the method\n(which may still result in a negative index); this is the customary\nhandling of negative indexes by the built-in sequence types, and the\n``__*item__()`` methods are expected to do this as well.  However,\nsince they should already be doing that, negative indexes cannot be\npassed in; they must be constrained to the bounds of the sequence\nbefore being passed to the ``__*item__()`` methods. Calling ``max(0,\ni)`` conveniently returns the proper value.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``//``, ``%``, ``divmod()``,\n   ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``).  For\n   instance, to evaluate the expression ``x + y``, where *x* is an\n   instance of a class that has an ``__add__()`` method,\n   ``x.__add__(y)`` is called.  The ``__divmod__()`` method should be\n   the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n   should not be related to ``__truediv__()`` (described below).  Note\n   that ``__pow__()`` should be defined to accept an optional third\n   argument if the ternary version of the built-in ``pow()`` function\n   is to be supported.\n\n   If one of those methods does not support the operation with the\n   supplied arguments, it should return ``NotImplemented``.\n\nobject.__div__(self, other)\nobject.__truediv__(self, other)\n\n   The division operator (``/``) is implemented by these methods.  The\n   ``__truediv__()`` method is used when ``__future__.division`` is in\n   effect, otherwise ``__div__()`` is used.  If only one of these two\n   methods is defined, the object will not support division in the\n   alternate context; ``TypeError`` will be raised instead.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rdiv__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``/``, ``%``, ``divmod()``,\n   ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``) with\n   reflected (swapped) operands.  These functions are only called if\n   the left operand does not support the corresponding operation and\n   the operands are of different types. [2] For instance, to evaluate\n   the expression ``x - y``, where *y* is an instance of a class that\n   has an ``__rsub__()`` method, ``y.__rsub__(x)`` is called if\n   ``x.__sub__(y)`` returns *NotImplemented*.\n\n   Note that ternary ``pow()`` will not try calling ``__rpow__()``\n   (the coercion rules would become too complicated).\n\n   Note: If the right operand\'s type is a subclass of the left operand\'s\n     type and that subclass provides the reflected method for the\n     operation, this method will be called before the left operand\'s\n     non-reflected method.  This behavior allows subclasses to\n     override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__idiv__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n   These methods are called to implement the augmented arithmetic\n   assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n   ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``).  These methods\n   should attempt to do the operation in-place (modifying *self*) and\n   return the result (which could be, but does not have to be,\n   *self*).  If a specific method is not defined, the augmented\n   assignment falls back to the normal methods.  For instance, to\n   execute the statement ``x += y``, where *x* is an instance of a\n   class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n   called.  If *x* is an instance of a class that does not define a\n   ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n   considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n   Called to implement the unary arithmetic operations (``-``, ``+``,\n   ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__long__(self)\nobject.__float__(self)\n\n   Called to implement the built-in functions ``complex()``,\n   ``int()``, ``long()``, and ``float()``.  Should return a value of\n   the appropriate type.\n\nobject.__oct__(self)\nobject.__hex__(self)\n\n   Called to implement the built-in functions ``oct()`` and ``hex()``.\n   Should return a string value.\n\nobject.__index__(self)\n\n   Called to implement ``operator.index()``.  Also called whenever\n   Python needs an integer object (such as in slicing).  Must return\n   an integer (int or long).\n\n   New in version 2.5.\n\nobject.__coerce__(self, other)\n\n   Called to implement "mixed-mode" numeric arithmetic.  Should either\n   return a 2-tuple containing *self* and *other* converted to a\n   common numeric type, or ``None`` if conversion is impossible.  When\n   the common type would be the type of ``other``, it is sufficient to\n   return ``None``, since the interpreter will also ask the other\n   object to attempt a coercion (but sometimes, if the implementation\n   of the other type cannot be changed, it is useful to do the\n   conversion to the other type here).  A return value of\n   ``NotImplemented`` is equivalent to returning ``None``.\n\n\nCoercion rules\n==============\n\nThis section used to document the rules for coercion.  As the language\nhas evolved, the coercion rules have become hard to document\nprecisely; documenting what one version of one particular\nimplementation does is undesirable.  Instead, here are some informal\nguidelines regarding coercion.  In Python 3.0, coercion will not be\nsupported.\n\n* If the left operand of a % operator is a string or Unicode object,\n  no coercion takes place and the string formatting operation is\n  invoked instead.\n\n* It is no longer recommended to define a coercion operation. Mixed-\n  mode operations on types that don\'t define coercion pass the\n  original arguments to the operation.\n\n* New-style classes (those derived from ``object``) never invoke the\n  ``__coerce__()`` method in response to a binary operator; the only\n  time ``__coerce__()`` is invoked is when the built-in function\n  ``coerce()`` is called.\n\n* For most intents and purposes, an operator that returns\n  ``NotImplemented`` is treated the same as one that is not\n  implemented at all.\n\n* Below, ``__op__()`` and ``__rop__()`` are used to signify the\n  generic method names corresponding to an operator; ``__iop__()`` is\n  used for the corresponding in-place operator.  For example, for the\n  operator \'``+``\', ``__add__()`` and ``__radd__()`` are used for the\n  left and right variant of the binary operator, and ``__iadd__()``\n  for the in-place variant.\n\n* For objects *x* and *y*, first ``x.__op__(y)`` is tried.  If this is\n  not implemented or returns ``NotImplemented``, ``y.__rop__(x)`` is\n  tried.  If this is also not implemented or returns\n  ``NotImplemented``, a ``TypeError`` exception is raised.  But see\n  the following exception:\n\n* Exception to the previous item: if the left operand is an instance\n  of a built-in type or a new-style class, and the right operand is an\n  instance of a proper subclass of that type or class and overrides\n  the base\'s ``__rop__()`` method, the right operand\'s ``__rop__()``\n  method is tried *before* the left operand\'s ``__op__()`` method.\n\n  This is done so that a subclass can completely override binary\n  operators. Otherwise, the left operand\'s ``__op__()`` method would\n  always accept the right operand: when an instance of a given class\n  is expected, an instance of a subclass of that class is always\n  acceptable.\n\n* When either operand type defines a coercion, this coercion is called\n  before that type\'s ``__op__()`` or ``__rop__()`` method is called,\n  but no sooner.  If the coercion returns an object of a different\n  type for the operand whose coercion is invoked, part of the process\n  is redone using the new object.\n\n* When an in-place operator (like \'``+=``\') is used, if the left\n  operand implements ``__iop__()``, it is invoked without any\n  coercion.  When the operation falls back to ``__op__()`` and/or\n  ``__rop__()``, the normal coercion rules apply.\n\n* In ``x + y``, if *x* is a sequence that implements sequence\n  concatenation, sequence concatenation is invoked.\n\n* In ``x * y``, if one operator is a sequence that implements sequence\n  repetition, and the other is an integer (``int`` or ``long``),\n  sequence repetition is invoked.\n\n* Rich comparisons (implemented by methods ``__eq__()`` and so on)\n  never use coercion.  Three-way comparison (implemented by\n  ``__cmp__()``) does use coercion under the same conditions as other\n  binary operations use it.\n\n* In the current implementation, the built-in numeric types ``int``,\n  ``long`` and ``float`` do not use coercion; the type ``complex``\n  however does use coercion for binary operators and rich comparisons,\n  despite the above rules.  The difference can become apparent when\n  subclassing these types.  Over time, the type ``complex`` may be\n  fixed to avoid coercion. All these types implement a\n  ``__coerce__()`` method, for use by the built-in ``coerce()``\n  function.\n\n\nWith Statement Context Managers\n===============================\n\nNew in version 2.5.\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code.  Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n   Enter the runtime context related to this object. The ``with``\n   statement will bind this method\'s return value to the target(s)\n   specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n   Exit the runtime context related to this object. The parameters\n   describe the exception that caused the context to be exited. If the\n   context was exited without an exception, all three arguments will\n   be ``None``.\n\n   If an exception is supplied, and the method wishes to suppress the\n   exception (i.e., prevent it from being propagated), it should\n   return a true value. Otherwise, the exception will be processed\n   normally upon exit from this method.\n\n   Note that ``__exit__()`` methods should not reraise the passed-in\n   exception; this is the caller\'s responsibility.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n\n\nSpecial method lookup for old-style classes\n===========================================\n\nFor old-style classes, special methods are always looked up in exactly\nthe same way as any other method or attribute. This is the case\nregardless of whether the method is being looked up explicitly as in\n``x.__getitem__(i)`` or implicitly as in ``x[i]``.\n\nThis behaviour means that special methods may exhibit different\nbehaviour for different instances of a single old-style class if the\nappropriate special attributes are set differently:\n\n   >>> class C:\n   ...     pass\n   ...\n   >>> c1 = C()\n   >>> c2 = C()\n   >>> c1.__len__ = lambda: 5\n   >>> c2.__len__ = lambda: 9\n   >>> len(c1)\n   5\n   >>> len(c2)\n   9\n\n\nSpecial method lookup for new-style classes\n===========================================\n\nFor new-style classes, implicit invocations of special methods are\nonly guaranteed to work correctly if defined on an object\'s type, not\nin the object\'s instance dictionary.  That behaviour is the reason why\nthe following code raises an exception (unlike the equivalent example\nwith old-style classes):\n\n   >>> class C(object):\n   ...     pass\n   ...\n   >>> c = C()\n   >>> c.__len__ = lambda: 5\n   >>> len(c)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: object of type \'C\' has no len()\n\nThe rationale behind this behaviour lies with a number of special\nmethods such as ``__hash__()`` and ``__repr__()`` that are implemented\nby all objects, including type objects. If the implicit lookup of\nthese methods used the conventional lookup process, they would fail\nwhen invoked on the type object itself:\n\n   >>> 1 .__hash__() == hash(1)\n   True\n   >>> int.__hash__() == hash(int)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: descriptor \'__hash__\' of \'int\' object needs an argument\n\nIncorrectly attempting to invoke an unbound method of a class in this\nway is sometimes referred to as \'metaclass confusion\', and is avoided\nby bypassing the instance when looking up special methods:\n\n   >>> type(1).__hash__(1) == hash(1)\n   True\n   >>> type(int).__hash__(int) == hash(int)\n   True\n\nIn addition to bypassing any instance attributes in the interest of\ncorrectness, implicit special method lookup generally also bypasses\nthe ``__getattribute__()`` method even of the object\'s metaclass:\n\n   >>> class Meta(type):\n   ...    def __getattribute__(*args):\n   ...       print "Metaclass getattribute invoked"\n   ...       return type.__getattribute__(*args)\n   ...\n   >>> class C(object):\n   ...     __metaclass__ = Meta\n   ...     def __len__(self):\n   ...         return 10\n   ...     def __getattribute__(*args):\n   ...         print "Class getattribute invoked"\n   ...         return object.__getattribute__(*args)\n   ...\n   >>> c = C()\n   >>> c.__len__()                 # Explicit lookup via instance\n   Class getattribute invoked\n   10\n   >>> type(c).__len__(c)          # Explicit lookup via type\n   Metaclass getattribute invoked\n   10\n   >>> len(c)                      # Implicit lookup\n   10\n\nBypassing the ``__getattribute__()`` machinery in this fashion\nprovides significant scope for speed optimisations within the\ninterpreter, at the cost of some flexibility in the handling of\nspecial methods (the special method *must* be set on the class object\nitself in order to be consistently invoked by the interpreter).\n\n-[ Footnotes ]-\n\n[1] It *is* possible in some cases to change an object\'s type, under\n    certain controlled conditions. It generally isn\'t a good idea\n    though, since it can lead to some very strange behaviour if it is\n    handled incorrectly.\n\n[2] For operands of the same type, it is assumed that if the non-\n    reflected method (such as ``__add__()``) fails the operation is\n    not supported, which is why the reflected method is not called.\n',
+ 'specialnames': u'\nSpecial method names\n********************\n\nA class can implement certain operations that are invoked by special\nsyntax (such as arithmetic operations or subscripting and slicing) by\ndefining methods with special names. This is Python\'s approach to\n*operator overloading*, allowing classes to define their own behavior\nwith respect to language operators.  For instance, if a class defines\na method named ``__getitem__()``, and ``x`` is an instance of this\nclass, then ``x[i]`` is roughly equivalent to ``x.__getitem__(i)`` for\nold-style classes and ``type(x).__getitem__(x, i)`` for new-style\nclasses.  Except where mentioned, attempts to execute an operation\nraise an exception when no appropriate method is defined (typically\n``AttributeError`` or ``TypeError``).\n\nWhen implementing a class that emulates any built-in type, it is\nimportant that the emulation only be implemented to the degree that it\nmakes sense for the object being modelled.  For example, some\nsequences may work well with retrieval of individual elements, but\nextracting a slice may not make sense.  (One example of this is the\n``NodeList`` interface in the W3C\'s Document Object Model.)\n\n\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 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 the Total Ordering recipe in the ASPN cookbook.\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 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\n\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``)\nfor class 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.\n   This method should return the (computed) attribute value or raise\n   an ``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\n   for efficiency reasons and because otherwise ``__getattr__()``\n   would have no way to access other attributes of the instance.  Note\n   that at least for instance variables, you can fake total control by\n   not 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\n   cause a recursive call to itself.  Instead, it should insert the\n   value in the dictionary of instance attributes, e.g.,\n   ``self.__dict__[name] = value``.  For new-style classes, rather\n   than accessing the instance dictionary, it should call the base\n   class method with the same name, for example,\n   ``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\n   ``__getattr__()``, the latter will not be called unless\n   ``__getattribute__()`` either calls it explicitly or raises an\n   ``AttributeError``. This method should return the (computed)\n   attribute value or raise an ``AttributeError`` exception. In order\n   to avoid infinite recursion in this method, its implementation\n   should always call the base class method with the same name to\n   access any attributes it needs, for example,\n   ``object.__getattribute__(self, name)``.\n\n   Note: This method may still be bypassed when looking up special methods\n     as the result of implicit invocation via language syntax or\n     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 the\nclass dictionary of another new-style class, known as the *owner*\nclass. In the examples below, "the attribute" refers to the attribute\nwhose name is the key of the property in the owner class\'\n``__dict__``.  Descriptors can only be implemented as new-style\nclasses themselves.\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\n   ``AttributeError`` 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,\nit is 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\n``type()``).\n\nThe starting point for descriptor invocation is a binding, ``a.x``.\nHow the 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\n   ``A`` immediately preceding ``B`` and then invokes the descriptor\n   with the call: ``A.__dict__[\'m\'].__get__(obj, A)``.\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__()``.\nIf it does not define ``__get__()``, then accessing the attribute will\nreturn the descriptor object itself unless there is a value in the\nobject\'s instance dictionary.  If the descriptor defines ``__set__()``\nand/or ``__delete__()``, it is a data descriptor; if it defines\nneither, it is a non-data descriptor.  Normally, data descriptors\ndefine both ``__get__()`` and ``__set__()``, while non-data\ndescriptors have just the ``__get__()`` method.  Data descriptors with\n``__set__()`` and ``__get__()`` defined always override a redefinition\nin an instance dictionary.  In contrast, non-data descriptors can be\noverridden by instances.\n\nPython methods (including ``staticmethod()`` and ``classmethod()``)\nare implemented 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 defining\n  *__slots__* do not support weak references to its instances. If weak\n  reference support is needed, then add ``\'__weakref__\'`` to the\n  sequence of strings in the *__slots__* 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\n  a 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 instance\n  variable defined by the base class slot is inaccessible (except by\n  retrieving its descriptor directly from the base class). This\n  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\n  ``tuple``.\n\n* Any non-string iterable may be assigned to *__slots__*. Mappings may\n  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\n\nCustomizing class creation\n==========================\n\nBy default, new-style classes are constructed using ``type()``. A\nclass definition is read into a separate namespace and the value of\nclass name is bound to the result of ``type(name, bases, dict)``.\n\nWhen the class definition is read, if *__metaclass__* is defined then\nthe callable assigned to it will be called instead of ``type()``. This\nallows classes or functions to be written which monitor or alter the\nclass creation process:\n\n* Modifying the class dictionary prior to the class being created.\n\n* Returning an instance of another class -- essentially performing the\n  role of a factory function.\n\nThese steps will have to be performed in the metaclass\'s ``__new__()``\nmethod -- ``type.__new__()`` can then be called from this method to\ncreate a class with different properties.  This example adds a new\nelement to the class dictionary before creating the class:\n\n   class metacls(type):\n       def __new__(mcs, name, bases, dict):\n           dict[\'foo\'] = \'metacls was here\'\n           return type.__new__(mcs, name, bases, dict)\n\nYou can of course also override other class methods (or add new\nmethods); for example defining a custom ``__call__()`` method in the\nmetaclass allows custom behavior when the class is called, e.g. not\nalways creating a new instance.\n\n__metaclass__\n\n   This variable can be any callable accepting arguments for ``name``,\n   ``bases``, and ``dict``.  Upon class creation, the callable is used\n   instead of the built-in ``type()``.\n\n   New in version 2.2.\n\nThe appropriate metaclass is determined by the following precedence\nrules:\n\n* If ``dict[\'__metaclass__\']`` exists, it is used.\n\n* Otherwise, if there is at least one base class, its metaclass is\n  used (this looks for a *__class__* attribute first and if not found,\n  uses its type).\n\n* Otherwise, if a global variable named __metaclass__ exists, it is\n  used.\n\n* Otherwise, the old-style, classic metaclass (types.ClassType) is\n  used.\n\nThe potential uses for metaclasses are boundless. Some ideas that have\nbeen explored including logging, interface checking, automatic\ndelegation, automatic property creation, proxies, frameworks, and\nautomatic resource locking/synchronization.\n\n\nCustomizing instance and subclass checks\n========================================\n\nNew in version 2.6.\n\nThe following methods are used to override the default behavior of the\n``isinstance()`` and ``issubclass()`` built-in functions.\n\nIn particular, the metaclass ``abc.ABCMeta`` implements these methods\nin order to allow the addition of Abstract Base Classes (ABCs) as\n"virtual base classes" to any class or type (including built-in\ntypes), and including to other ABCs.\n\nclass.__instancecheck__(self, instance)\n\n   Return true if *instance* should be considered a (direct or\n   indirect) instance of *class*. If defined, called to implement\n   ``isinstance(instance, class)``.\n\nclass.__subclasscheck__(self, subclass)\n\n   Return true if *subclass* should be considered a (direct or\n   indirect) subclass of *class*.  If defined, called to implement\n   ``issubclass(subclass, class)``.\n\nNote that these methods are looked up on the type (metaclass) of a\nclass.  They cannot be defined as class methods in the actual class.\nThis is consistent with the lookup of special methods that are called\non instances, only that in this case the instance is itself a class.\n\nSee also:\n\n   **PEP 3119** - Introducing Abstract Base Classes\n      Includes the specification for customizing ``isinstance()`` and\n      ``issubclass()`` behavior through ``__instancecheck__()`` and\n      ``__subclasscheck__()``, with motivation for this functionality\n      in the context of adding Abstract Base Classes (see the ``abc``\n      module) to the language.\n\n\nEmulating callable objects\n==========================\n\nobject.__call__(self[, args...])\n\n   Called when the instance is "called" as a function; if this method\n   is defined, ``x(arg1, arg2, ...)`` is a shorthand for\n   ``x.__call__(arg1, arg2, ...)``.\n\n\nEmulating container types\n=========================\n\nThe following methods can be defined to implement container objects.\nContainers usually are sequences (such as lists or tuples) or mappings\n(like dictionaries), but can represent other containers as well.  The\nfirst set of methods is used either to emulate a sequence or to\nemulate a mapping; the difference is that for a sequence, the\nallowable keys should be the integers *k* for which ``0 <= k < N``\nwhere *N* is the length of the sequence, or slice objects, which\ndefine a range of items. (For backwards compatibility, the method\n``__getslice__()`` (see below) can also be defined to handle simple,\nbut not extended slices.) It is also recommended that mappings provide\nthe methods ``keys()``, ``values()``, ``items()``, ``has_key()``,\n``get()``, ``clear()``, ``setdefault()``, ``iterkeys()``,\n``itervalues()``, ``iteritems()``, ``pop()``, ``popitem()``,\n``copy()``, and ``update()`` behaving similar to those for Python\'s\nstandard dictionary objects.  The ``UserDict`` module provides a\n``DictMixin`` class to help create those methods from a base set of\n``__getitem__()``, ``__setitem__()``, ``__delitem__()``, and\n``keys()``. Mutable sequences should provide methods ``append()``,\n``count()``, ``index()``, ``extend()``, ``insert()``, ``pop()``,\n``remove()``, ``reverse()`` and ``sort()``, like Python standard list\nobjects.  Finally, sequence types should implement addition (meaning\nconcatenation) and multiplication (meaning repetition) by defining the\nmethods ``__add__()``, ``__radd__()``, ``__iadd__()``, ``__mul__()``,\n``__rmul__()`` and ``__imul__()`` described below; they should not\ndefine ``__coerce__()`` or other numerical operators.  It is\nrecommended that both mappings and sequences implement the\n``__contains__()`` method to allow efficient use of the ``in``\noperator; for mappings, ``in`` should be equivalent of ``has_key()``;\nfor sequences, it should search through the values.  It is further\nrecommended that both mappings and sequences implement the\n``__iter__()`` method to allow efficient iteration through the\ncontainer; for mappings, ``__iter__()`` should be the same as\n``iterkeys()``; for sequences, it should iterate through the values.\n\nobject.__len__(self)\n\n   Called to implement the built-in function ``len()``.  Should return\n   the length of the object, an integer ``>=`` 0.  Also, an object\n   that doesn\'t define a ``__nonzero__()`` method and whose\n   ``__len__()`` method returns zero is considered to be false in a\n   Boolean context.\n\nobject.__getitem__(self, key)\n\n   Called to implement evaluation of ``self[key]``. For sequence\n   types, the accepted keys should be integers and slice objects.\n   Note that the special interpretation of negative indexes (if the\n   class wishes to emulate a sequence type) is up to the\n   ``__getitem__()`` method. If *key* is of an inappropriate type,\n   ``TypeError`` may be raised; if of a value outside the set of\n   indexes for the sequence (after any special interpretation of\n   negative values), ``IndexError`` should be raised. For mapping\n   types, if *key* is missing (not in the container), ``KeyError``\n   should be raised.\n\n   Note: ``for`` loops expect that an ``IndexError`` will be raised for\n     illegal indexes to allow proper detection of the end of the\n     sequence.\n\nobject.__setitem__(self, key, value)\n\n   Called to implement assignment to ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support changes to the values for keys, or if new keys\n   can be added, or for sequences if elements can be replaced.  The\n   same exceptions should be raised for improper *key* values as for\n   the ``__getitem__()`` method.\n\nobject.__delitem__(self, key)\n\n   Called to implement deletion of ``self[key]``.  Same note as for\n   ``__getitem__()``.  This should only be implemented for mappings if\n   the objects support removal of keys, or for sequences if elements\n   can be removed from the sequence.  The same exceptions should be\n   raised for improper *key* values as for the ``__getitem__()``\n   method.\n\nobject.__iter__(self)\n\n   This method is called when an iterator is required for a container.\n   This method should return a new iterator object that can iterate\n   over all the objects in the container.  For mappings, it should\n   iterate over the keys of the container, and should also be made\n   available as the method ``iterkeys()``.\n\n   Iterator objects also need to implement this method; they are\n   required to return themselves.  For more information on iterator\n   objects, see *Iterator Types*.\n\nobject.__reversed__(self)\n\n   Called (if present) by the ``reversed()`` built-in to implement\n   reverse iteration.  It should return a new iterator object that\n   iterates over all the objects in the container in reverse order.\n\n   If the ``__reversed__()`` method is not provided, the\n   ``reversed()`` built-in will fall back to using the sequence\n   protocol (``__len__()`` and ``__getitem__()``).  Objects that\n   support the sequence protocol should only provide\n   ``__reversed__()`` if they can provide an implementation that is\n   more efficient than the one provided by ``reversed()``.\n\n   New in version 2.6.\n\nThe membership test operators (``in`` and ``not in``) are normally\nimplemented as an iteration through a sequence.  However, container\nobjects can supply the following special method with a more efficient\nimplementation, which also does not require the object be a sequence.\n\nobject.__contains__(self, item)\n\n   Called to implement membership test operators.  Should return true\n   if *item* is in *self*, false otherwise.  For mapping objects, this\n   should consider the keys of the mapping rather than the values or\n   the key-item pairs.\n\n   For objects that don\'t define ``__contains__()``, the membership\n   test first tries iteration via ``__iter__()``, then the old\n   sequence iteration protocol via ``__getitem__()``, see *this\n   section in the language reference*.\n\n\nAdditional methods for emulation of sequence types\n==================================================\n\nThe following optional methods can be defined to further emulate\nsequence objects.  Immutable sequences methods should at most only\ndefine ``__getslice__()``; mutable sequences might define all three\nmethods.\n\nobject.__getslice__(self, i, j)\n\n   Deprecated since version 2.0: Support slice objects as parameters\n   to the ``__getitem__()`` method. (However, built-in types in\n   CPython currently still implement ``__getslice__()``.  Therefore,\n   you have to override it in derived classes when implementing\n   slicing.)\n\n   Called to implement evaluation of ``self[i:j]``. The returned\n   object should be of the same type as *self*.  Note that missing *i*\n   or *j* in the slice expression are replaced by zero or\n   ``sys.maxint``, respectively.  If negative indexes are used in the\n   slice, the length of the sequence is added to that index. If the\n   instance does not implement the ``__len__()`` method, an\n   ``AttributeError`` is raised. No guarantee is made that indexes\n   adjusted this way are not still negative.  Indexes which are\n   greater than the length of the sequence are not modified. If no\n   ``__getslice__()`` is found, a slice object is created instead, and\n   passed to ``__getitem__()`` instead.\n\nobject.__setslice__(self, i, j, sequence)\n\n   Called to implement assignment to ``self[i:j]``. Same notes for *i*\n   and *j* as for ``__getslice__()``.\n\n   This method is deprecated. If no ``__setslice__()`` is found, or\n   for extended slicing of the form ``self[i:j:k]``, a slice object is\n   created, and passed to ``__setitem__()``, instead of\n   ``__setslice__()`` being called.\n\nobject.__delslice__(self, i, j)\n\n   Called to implement deletion of ``self[i:j]``. Same notes for *i*\n   and *j* as for ``__getslice__()``. This method is deprecated. If no\n   ``__delslice__()`` is found, or for extended slicing of the form\n   ``self[i:j:k]``, a slice object is created, and passed to\n   ``__delitem__()``, instead of ``__delslice__()`` being called.\n\nNotice that these methods are only invoked when a single slice with a\nsingle colon is used, and the slice method is available.  For slice\noperations involving extended slice notation, or in absence of the\nslice methods, ``__getitem__()``, ``__setitem__()`` or\n``__delitem__()`` is called with a slice object as argument.\n\nThe following example demonstrate how to make your program or module\ncompatible with earlier versions of Python (assuming that methods\n``__getitem__()``, ``__setitem__()`` and ``__delitem__()`` support\nslice objects as arguments):\n\n   class MyClass:\n       ...\n       def __getitem__(self, index):\n           ...\n       def __setitem__(self, index, value):\n           ...\n       def __delitem__(self, index):\n           ...\n\n       if sys.version_info < (2, 0):\n           # They won\'t be defined if version is at least 2.0 final\n\n           def __getslice__(self, i, j):\n               return self[max(0, i):max(0, j):]\n           def __setslice__(self, i, j, seq):\n               self[max(0, i):max(0, j):] = seq\n           def __delslice__(self, i, j):\n               del self[max(0, i):max(0, j):]\n       ...\n\nNote the calls to ``max()``; these are necessary because of the\nhandling of negative indices before the ``__*slice__()`` methods are\ncalled.  When negative indexes are used, the ``__*item__()`` methods\nreceive them as provided, but the ``__*slice__()`` methods get a\n"cooked" form of the index values.  For each negative index value, the\nlength of the sequence is added to the index before calling the method\n(which may still result in a negative index); this is the customary\nhandling of negative indexes by the built-in sequence types, and the\n``__*item__()`` methods are expected to do this as well.  However,\nsince they should already be doing that, negative indexes cannot be\npassed in; they must be constrained to the bounds of the sequence\nbefore being passed to the ``__*item__()`` methods. Calling ``max(0,\ni)`` conveniently returns the proper value.\n\n\nEmulating numeric types\n=======================\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``//``, ``%``, ``divmod()``,\n   ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``).  For\n   instance, to evaluate the expression ``x + y``, where *x* is an\n   instance of a class that has an ``__add__()`` method,\n   ``x.__add__(y)`` is called.  The ``__divmod__()`` method should be\n   the equivalent to using ``__floordiv__()`` and ``__mod__()``; it\n   should not be related to ``__truediv__()`` (described below).  Note\n   that ``__pow__()`` should be defined to accept an optional third\n   argument if the ternary version of the built-in ``pow()`` function\n   is to be supported.\n\n   If one of those methods does not support the operation with the\n   supplied arguments, it should return ``NotImplemented``.\n\nobject.__div__(self, other)\nobject.__truediv__(self, other)\n\n   The division operator (``/``) is implemented by these methods.  The\n   ``__truediv__()`` method is used when ``__future__.division`` is in\n   effect, otherwise ``__div__()`` is used.  If only one of these two\n   methods is defined, the object will not support division in the\n   alternate context; ``TypeError`` will be raised instead.\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rdiv__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n   These methods are called to implement the binary arithmetic\n   operations (``+``, ``-``, ``*``, ``/``, ``%``, ``divmod()``,\n   ``pow()``, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``) with\n   reflected (swapped) operands.  These functions are only called if\n   the left operand does not support the corresponding operation and\n   the operands are of different types. [2] For instance, to evaluate\n   the expression ``x - y``, where *y* is an instance of a class that\n   has an ``__rsub__()`` method, ``y.__rsub__(x)`` is called if\n   ``x.__sub__(y)`` returns *NotImplemented*.\n\n   Note that ternary ``pow()`` will not try calling ``__rpow__()``\n   (the coercion rules would become too complicated).\n\n   Note: If the right operand\'s type is a subclass of the left operand\'s\n     type and that subclass provides the reflected method for the\n     operation, this method will be called before the left operand\'s\n     non-reflected method.  This behavior allows subclasses to\n     override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__idiv__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n   These methods are called to implement the augmented arithmetic\n   assignments (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,\n   ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``).  These methods\n   should attempt to do the operation in-place (modifying *self*) and\n   return the result (which could be, but does not have to be,\n   *self*).  If a specific method is not defined, the augmented\n   assignment falls back to the normal methods.  For instance, to\n   execute the statement ``x += y``, where *x* is an instance of a\n   class that has an ``__iadd__()`` method, ``x.__iadd__(y)`` is\n   called.  If *x* is an instance of a class that does not define a\n   ``__iadd__()`` method, ``x.__add__(y)`` and ``y.__radd__(x)`` are\n   considered, as with the evaluation of ``x + y``.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n   Called to implement the unary arithmetic operations (``-``, ``+``,\n   ``abs()`` and ``~``).\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__long__(self)\nobject.__float__(self)\n\n   Called to implement the built-in functions ``complex()``,\n   ``int()``, ``long()``, and ``float()``.  Should return a value of\n   the appropriate type.\n\nobject.__oct__(self)\nobject.__hex__(self)\n\n   Called to implement the built-in functions ``oct()`` and ``hex()``.\n   Should return a string value.\n\nobject.__index__(self)\n\n   Called to implement ``operator.index()``.  Also called whenever\n   Python needs an integer object (such as in slicing).  Must return\n   an integer (int or long).\n\n   New in version 2.5.\n\nobject.__coerce__(self, other)\n\n   Called to implement "mixed-mode" numeric arithmetic.  Should either\n   return a 2-tuple containing *self* and *other* converted to a\n   common numeric type, or ``None`` if conversion is impossible.  When\n   the common type would be the type of ``other``, it is sufficient to\n   return ``None``, since the interpreter will also ask the other\n   object to attempt a coercion (but sometimes, if the implementation\n   of the other type cannot be changed, it is useful to do the\n   conversion to the other type here).  A return value of\n   ``NotImplemented`` is equivalent to returning ``None``.\n\n\nCoercion rules\n==============\n\nThis section used to document the rules for coercion.  As the language\nhas evolved, the coercion rules have become hard to document\nprecisely; documenting what one version of one particular\nimplementation does is undesirable.  Instead, here are some informal\nguidelines regarding coercion.  In Python 3.0, coercion will not be\nsupported.\n\n* If the left operand of a % operator is a string or Unicode object,\n  no coercion takes place and the string formatting operation is\n  invoked instead.\n\n* It is no longer recommended to define a coercion operation. Mixed-\n  mode operations on types that don\'t define coercion pass the\n  original arguments to the operation.\n\n* New-style classes (those derived from ``object``) never invoke the\n  ``__coerce__()`` method in response to a binary operator; the only\n  time ``__coerce__()`` is invoked is when the built-in function\n  ``coerce()`` is called.\n\n* For most intents and purposes, an operator that returns\n  ``NotImplemented`` is treated the same as one that is not\n  implemented at all.\n\n* Below, ``__op__()`` and ``__rop__()`` are used to signify the\n  generic method names corresponding to an operator; ``__iop__()`` is\n  used for the corresponding in-place operator.  For example, for the\n  operator \'``+``\', ``__add__()`` and ``__radd__()`` are used for the\n  left and right variant of the binary operator, and ``__iadd__()``\n  for the in-place variant.\n\n* For objects *x* and *y*, first ``x.__op__(y)`` is tried.  If this is\n  not implemented or returns ``NotImplemented``, ``y.__rop__(x)`` is\n  tried.  If this is also not implemented or returns\n  ``NotImplemented``, a ``TypeError`` exception is raised.  But see\n  the following exception:\n\n* Exception to the previous item: if the left operand is an instance\n  of a built-in type or a new-style class, and the right operand is an\n  instance of a proper subclass of that type or class and overrides\n  the base\'s ``__rop__()`` method, the right operand\'s ``__rop__()``\n  method is tried *before* the left operand\'s ``__op__()`` method.\n\n  This is done so that a subclass can completely override binary\n  operators. Otherwise, the left operand\'s ``__op__()`` method would\n  always accept the right operand: when an instance of a given class\n  is expected, an instance of a subclass of that class is always\n  acceptable.\n\n* When either operand type defines a coercion, this coercion is called\n  before that type\'s ``__op__()`` or ``__rop__()`` method is called,\n  but no sooner.  If the coercion returns an object of a different\n  type for the operand whose coercion is invoked, part of the process\n  is redone using the new object.\n\n* When an in-place operator (like \'``+=``\') is used, if the left\n  operand implements ``__iop__()``, it is invoked without any\n  coercion.  When the operation falls back to ``__op__()`` and/or\n  ``__rop__()``, the normal coercion rules apply.\n\n* In ``x + y``, if *x* is a sequence that implements sequence\n  concatenation, sequence concatenation is invoked.\n\n* In ``x * y``, if one operator is a sequence that implements sequence\n  repetition, and the other is an integer (``int`` or ``long``),\n  sequence repetition is invoked.\n\n* Rich comparisons (implemented by methods ``__eq__()`` and so on)\n  never use coercion.  Three-way comparison (implemented by\n  ``__cmp__()``) does use coercion under the same conditions as other\n  binary operations use it.\n\n* In the current implementation, the built-in numeric types ``int``,\n  ``long`` and ``float`` do not use coercion; the type ``complex``\n  however does use coercion for binary operators and rich comparisons,\n  despite the above rules.  The difference can become apparent when\n  subclassing these types.  Over time, the type ``complex`` may be\n  fixed to avoid coercion. All these types implement a\n  ``__coerce__()`` method, for use by the built-in ``coerce()``\n  function.\n\n\nWith Statement Context Managers\n===============================\n\nNew in version 2.5.\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a ``with`` statement. The context\nmanager handles the entry into, and the exit from, the desired runtime\ncontext for the execution of the block of code.  Context managers are\nnormally invoked using the ``with`` statement (described in section\n*The with statement*), but can also be used by directly invoking their\nmethods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n   Enter the runtime context related to this object. The ``with``\n   statement will bind this method\'s return value to the target(s)\n   specified in the ``as`` clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n   Exit the runtime context related to this object. The parameters\n   describe the exception that caused the context to be exited. If the\n   context was exited without an exception, all three arguments will\n   be ``None``.\n\n   If an exception is supplied, and the method wishes to suppress the\n   exception (i.e., prevent it from being propagated), it should\n   return a true value. Otherwise, the exception will be processed\n   normally upon exit from this method.\n\n   Note that ``__exit__()`` methods should not reraise the passed-in\n   exception; this is the caller\'s responsibility.\n\nSee also:\n\n   **PEP 0343** - The "with" statement\n      The specification, background, and examples for the Python\n      ``with`` statement.\n\n\nSpecial method lookup for old-style classes\n===========================================\n\nFor old-style classes, special methods are always looked up in exactly\nthe same way as any other method or attribute. This is the case\nregardless of whether the method is being looked up explicitly as in\n``x.__getitem__(i)`` or implicitly as in ``x[i]``.\n\nThis behaviour means that special methods may exhibit different\nbehaviour for different instances of a single old-style class if the\nappropriate special attributes are set differently:\n\n   >>> class C:\n   ...     pass\n   ...\n   >>> c1 = C()\n   >>> c2 = C()\n   >>> c1.__len__ = lambda: 5\n   >>> c2.__len__ = lambda: 9\n   >>> len(c1)\n   5\n   >>> len(c2)\n   9\n\n\nSpecial method lookup for new-style classes\n===========================================\n\nFor new-style classes, implicit invocations of special methods are\nonly guaranteed to work correctly if defined on an object\'s type, not\nin the object\'s instance dictionary.  That behaviour is the reason why\nthe following code raises an exception (unlike the equivalent example\nwith old-style classes):\n\n   >>> class C(object):\n   ...     pass\n   ...\n   >>> c = C()\n   >>> c.__len__ = lambda: 5\n   >>> len(c)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: object of type \'C\' has no len()\n\nThe rationale behind this behaviour lies with a number of special\nmethods such as ``__hash__()`` and ``__repr__()`` that are implemented\nby all objects, including type objects. If the implicit lookup of\nthese methods used the conventional lookup process, they would fail\nwhen invoked on the type object itself:\n\n   >>> 1 .__hash__() == hash(1)\n   True\n   >>> int.__hash__() == hash(int)\n   Traceback (most recent call last):\n     File "<stdin>", line 1, in <module>\n   TypeError: descriptor \'__hash__\' of \'int\' object needs an argument\n\nIncorrectly attempting to invoke an unbound method of a class in this\nway is sometimes referred to as \'metaclass confusion\', and is avoided\nby bypassing the instance when looking up special methods:\n\n   >>> type(1).__hash__(1) == hash(1)\n   True\n   >>> type(int).__hash__(int) == hash(int)\n   True\n\nIn addition to bypassing any instance attributes in the interest of\ncorrectness, implicit special method lookup generally also bypasses\nthe ``__getattribute__()`` method even of the object\'s metaclass:\n\n   >>> class Meta(type):\n   ...    def __getattribute__(*args):\n   ...       print "Metaclass getattribute invoked"\n   ...       return type.__getattribute__(*args)\n   ...\n   >>> class C(object):\n   ...     __metaclass__ = Meta\n   ...     def __len__(self):\n   ...         return 10\n   ...     def __getattribute__(*args):\n   ...         print "Class getattribute invoked"\n   ...         return object.__getattribute__(*args)\n   ...\n   >>> c = C()\n   >>> c.__len__()                 # Explicit lookup via instance\n   Class getattribute invoked\n   10\n   >>> type(c).__len__(c)          # Explicit lookup via type\n   Metaclass getattribute invoked\n   10\n   >>> len(c)                      # Implicit lookup\n   10\n\nBypassing the ``__getattribute__()`` machinery in this fashion\nprovides significant scope for speed optimisations within the\ninterpreter, at the cost of some flexibility in the handling of\nspecial methods (the special method *must* be set on the class object\nitself in order to be consistently invoked by the interpreter).\n\n-[ Footnotes ]-\n\n[1] It *is* possible in some cases to change an object\'s type, under\n    certain controlled conditions. It generally isn\'t a good idea\n    though, since it can lead to some very strange behaviour if it is\n    handled incorrectly.\n\n[2] For operands of the same type, it is assumed that if the non-\n    reflected method (such as ``__add__()``) fails the operation is\n    not supported, which is why the reflected method is not called.\n',
  'string-conversions': u'\nString conversions\n******************\n\nA string conversion is an expression list enclosed in reverse (a.k.a.\nbackward) quotes:\n\n   string_conversion ::= "\'" expression_list "\'"\n\nA string conversion evaluates the contained expression list and\nconverts the resulting object into a string according to rules\nspecific to its type.\n\nIf the object is a string, a number, ``None``, or a tuple, list or\ndictionary containing only objects whose type is one of these, the\nresulting string is a valid Python expression which can be passed to\nthe built-in function ``eval()`` to yield an expression with the same\nvalue (or an approximation, if floating point numbers are involved).\n\n(In particular, converting a string adds quotes around it and converts\n"funny" characters to escape sequences that are safe to print.)\n\nRecursive objects (for example, lists or dictionaries that contain a\nreference to themselves, directly or indirectly) use ``...`` to\nindicate a recursive reference, and the result cannot be passed to\n``eval()`` to get an equal value (``SyntaxError`` will be raised\ninstead).\n\nThe built-in function ``repr()`` performs exactly the same conversion\nin its argument as enclosing it in parentheses and reverse quotes\ndoes.  The built-in function ``str()`` performs a similar but more\nuser-friendly conversion.\n',
  'string-methods': u'\nString Methods\n**************\n\nBelow are listed the string methods which both 8-bit strings and\nUnicode objects support. Note that none of these methods take keyword\narguments.\n\nIn addition, Python\'s strings support the sequence type methods\ndescribed in the *Sequence Types --- str, unicode, list, tuple,\nbuffer, xrange* section. To output formatted strings use template\nstrings or the ``%`` operator described in the *String Formatting\nOperations* section. Also, see the ``re`` module for string functions\nbased on regular expressions.\n\nstr.capitalize()\n\n   Return a copy of the string with its first character capitalized\n   and the rest lowercased.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.center(width[, fillchar])\n\n   Return centered in a string of length *width*. Padding is done\n   using the specified *fillchar* (default is a space).\n\n   Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.count(sub[, start[, end]])\n\n   Return the number of non-overlapping occurrences of substring *sub*\n   in the range [*start*, *end*].  Optional arguments *start* and\n   *end* are interpreted as in slice notation.\n\nstr.decode([encoding[, errors]])\n\n   Decodes the string using the codec registered for *encoding*.\n   *encoding* defaults to the default string encoding.  *errors* may\n   be given to set a different error handling scheme.  The default is\n   ``\'strict\'``, meaning that encoding errors raise ``UnicodeError``.\n   Other possible values are ``\'ignore\'``, ``\'replace\'`` and any other\n   name registered via ``codecs.register_error()``, see section *Codec\n   Base Classes*.\n\n   New in version 2.2.\n\n   Changed in version 2.3: Support for other error handling schemes\n   added.\n\nstr.encode([encoding[, errors]])\n\n   Return an encoded version of the string.  Default encoding is the\n   current default string encoding.  *errors* may be given to set a\n   different error handling scheme.  The default for *errors* is\n   ``\'strict\'``, meaning that encoding errors raise a\n   ``UnicodeError``.  Other possible values are ``\'ignore\'``,\n   ``\'replace\'``, ``\'xmlcharrefreplace\'``, ``\'backslashreplace\'`` and\n   any other name registered via ``codecs.register_error()``, see\n   section *Codec Base Classes*. For a list of possible encodings, see\n   section *Standard Encodings*.\n\n   New in version 2.0.\n\n   Changed in version 2.3: Support for ``\'xmlcharrefreplace\'`` and\n   ``\'backslashreplace\'`` and other error handling schemes added.\n\nstr.endswith(suffix[, start[, end]])\n\n   Return ``True`` if the string ends with the specified *suffix*,\n   otherwise return ``False``.  *suffix* can also be a tuple of\n   suffixes to look for.  With optional *start*, test beginning at\n   that position.  With optional *end*, stop comparing at that\n   position.\n\n   Changed in version 2.5: Accept tuples as *suffix*.\n\nstr.expandtabs([tabsize])\n\n   Return a copy of the string where all tab characters are replaced\n   by one or more spaces, depending on the current column and the\n   given tab size.  The column number is reset to zero after each\n   newline occurring in the string. If *tabsize* is not given, a tab\n   size of ``8`` characters is assumed.  This doesn\'t understand other\n   non-printing characters or escape sequences.\n\nstr.find(sub[, start[, end]])\n\n   Return the lowest index in the string where substring *sub* is\n   found, such that *sub* is contained in the slice ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` if *sub* is not found.\n\nstr.format(*args, **kwargs)\n\n   Perform a string formatting operation.  The string on which this\n   method is called can contain literal text or replacement fields\n   delimited by braces ``{}``.  Each replacement field contains either\n   the numeric index of a positional argument, or the name of a\n   keyword argument.  Returns a copy of the string where each\n   replacement field is replaced with the string value of the\n   corresponding argument.\n\n   >>> "The sum of 1 + 2 is {0}".format(1+2)\n   \'The sum of 1 + 2 is 3\'\n\n   See *Format String Syntax* for a description of the various\n   formatting options that can be specified in format strings.\n\n   This method of string formatting is the new standard in Python 3.0,\n   and should be preferred to the ``%`` formatting described in\n   *String Formatting Operations* in new code.\n\n   New in version 2.6.\n\nstr.index(sub[, start[, end]])\n\n   Like ``find()``, but raise ``ValueError`` when the substring is not\n   found.\n\nstr.isalnum()\n\n   Return true if all characters in the string are alphanumeric and\n   there is at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isalpha()\n\n   Return true if all characters in the string are alphabetic and\n   there is at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isdigit()\n\n   Return true if all characters in the string are digits and there is\n   at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.islower()\n\n   Return true if all cased characters in the string are lowercase and\n   there is at least one cased character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isspace()\n\n   Return true if there are only whitespace characters in the string\n   and there is at least one character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.istitle()\n\n   Return true if the string is a titlecased string and there is at\n   least one character, for example uppercase characters may only\n   follow uncased characters and lowercase characters only cased ones.\n   Return false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.isupper()\n\n   Return true if all cased characters in the string are uppercase and\n   there is at least one cased character, false otherwise.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.join(iterable)\n\n   Return a string which is the concatenation of the strings in the\n   *iterable* *iterable*.  The separator between elements is the\n   string providing this method.\n\nstr.ljust(width[, fillchar])\n\n   Return the string left justified in a string of length *width*.\n   Padding is done using the specified *fillchar* (default is a\n   space).  The original string is returned if *width* is less than\n   ``len(s)``.\n\n   Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.lower()\n\n   Return a copy of the string converted to lowercase.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.lstrip([chars])\n\n   Return a copy of the string with leading characters removed.  The\n   *chars* argument is a string specifying the set of characters to be\n   removed.  If omitted or ``None``, the *chars* argument defaults to\n   removing whitespace.  The *chars* argument is not a prefix; rather,\n   all combinations of its values are stripped:\n\n   >>> \'   spacious   \'.lstrip()\n   \'spacious   \'\n   >>> \'www.example.com\'.lstrip(\'cmowz.\')\n   \'example.com\'\n\n   Changed in version 2.2.2: Support for the *chars* argument.\n\nstr.partition(sep)\n\n   Split the string at the first occurrence of *sep*, and return a\n   3-tuple containing the part before the separator, the separator\n   itself, and the part after the separator.  If the separator is not\n   found, return a 3-tuple containing the string itself, followed by\n   two empty strings.\n\n   New in version 2.5.\n\nstr.replace(old, new[, count])\n\n   Return a copy of the string with all occurrences of substring *old*\n   replaced by *new*.  If the optional argument *count* is given, only\n   the first *count* occurrences are replaced.\n\nstr.rfind(sub[, start[, end]])\n\n   Return the highest index in the string where substring *sub* is\n   found, such that *sub* is contained within ``s[start:end]``.\n   Optional arguments *start* and *end* are interpreted as in slice\n   notation.  Return ``-1`` on failure.\n\nstr.rindex(sub[, start[, end]])\n\n   Like ``rfind()`` but raises ``ValueError`` when the substring *sub*\n   is not found.\n\nstr.rjust(width[, fillchar])\n\n   Return the string right justified in a string of length *width*.\n   Padding is done using the specified *fillchar* (default is a\n   space). The original string is returned if *width* is less than\n   ``len(s)``.\n\n   Changed in version 2.4: Support for the *fillchar* argument.\n\nstr.rpartition(sep)\n\n   Split the string at the last occurrence of *sep*, and return a\n   3-tuple containing the part before the separator, the separator\n   itself, and the part after the separator.  If the separator is not\n   found, return a 3-tuple containing two empty strings, followed by\n   the string itself.\n\n   New in version 2.5.\n\nstr.rsplit([sep[, maxsplit]])\n\n   Return a list of the words in the string, using *sep* as the\n   delimiter string. If *maxsplit* is given, at most *maxsplit* splits\n   are done, the *rightmost* ones.  If *sep* is not specified or\n   ``None``, any whitespace string is a separator.  Except for\n   splitting from the right, ``rsplit()`` behaves like ``split()``\n   which is described in detail below.\n\n   New in version 2.4.\n\nstr.rstrip([chars])\n\n   Return a copy of the string with trailing characters removed.  The\n   *chars* argument is a string specifying the set of characters to be\n   removed.  If omitted or ``None``, the *chars* argument defaults to\n   removing whitespace.  The *chars* argument is not a suffix; rather,\n   all combinations of its values are stripped:\n\n   >>> \'   spacious   \'.rstrip()\n   \'   spacious\'\n   >>> \'mississippi\'.rstrip(\'ipz\')\n   \'mississ\'\n\n   Changed in version 2.2.2: Support for the *chars* argument.\n\nstr.split([sep[, maxsplit]])\n\n   Return a list of the words in the string, using *sep* as the\n   delimiter string.  If *maxsplit* is given, at most *maxsplit*\n   splits are done (thus, the list will have at most ``maxsplit+1``\n   elements).  If *maxsplit* is not specified, then there is no limit\n   on the number of splits (all possible splits are made).\n\n   If *sep* is given, consecutive delimiters are not grouped together\n   and are deemed to delimit empty strings (for example,\n   ``\'1,,2\'.split(\',\')`` returns ``[\'1\', \'\', \'2\']``).  The *sep*\n   argument may consist of multiple characters (for example,\n   ``\'1<>2<>3\'.split(\'<>\')`` returns ``[\'1\', \'2\', \'3\']``). Splitting\n   an empty string with a specified separator returns ``[\'\']``.\n\n   If *sep* is not specified or is ``None``, a different splitting\n   algorithm is applied: runs of consecutive whitespace are regarded\n   as a single separator, and the result will contain no empty strings\n   at the start or end if the string has leading or trailing\n   whitespace.  Consequently, splitting an empty string or a string\n   consisting of just whitespace with a ``None`` separator returns\n   ``[]``.\n\n   For example, ``\' 1  2   3  \'.split()`` returns ``[\'1\', \'2\', \'3\']``,\n   and ``\'  1  2   3  \'.split(None, 1)`` returns ``[\'1\', \'2   3  \']``.\n\nstr.splitlines([keepends])\n\n   Return a list of the lines in the string, breaking at line\n   boundaries.  Line breaks are not included in the resulting list\n   unless *keepends* is given and true.\n\nstr.startswith(prefix[, start[, end]])\n\n   Return ``True`` if string starts with the *prefix*, otherwise\n   return ``False``. *prefix* can also be a tuple of prefixes to look\n   for.  With optional *start*, test string beginning at that\n   position.  With optional *end*, stop comparing string at that\n   position.\n\n   Changed in version 2.5: Accept tuples as *prefix*.\n\nstr.strip([chars])\n\n   Return a copy of the string with the leading and trailing\n   characters removed. The *chars* argument is a string specifying the\n   set of characters to be removed. If omitted or ``None``, the\n   *chars* argument defaults to removing whitespace. The *chars*\n   argument is not a prefix or suffix; rather, all combinations of its\n   values are stripped:\n\n   >>> \'   spacious   \'.strip()\n   \'spacious\'\n   >>> \'www.example.com\'.strip(\'cmowz.\')\n   \'example\'\n\n   Changed in version 2.2.2: Support for the *chars* argument.\n\nstr.swapcase()\n\n   Return a copy of the string with uppercase characters converted to\n   lowercase and vice versa.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.title()\n\n   Return a titlecased version of the string where words start with an\n   uppercase character and the remaining characters are lowercase.\n\n   The algorithm uses a simple language-independent definition of a\n   word as groups of consecutive letters.  The definition works in\n   many contexts but it means that apostrophes in contractions and\n   possessives form word boundaries, which may not be the desired\n   result:\n\n      >>> "they\'re bill\'s friends from the UK".title()\n      "They\'Re Bill\'S Friends From The Uk"\n\n   A workaround for apostrophes can be constructed using regular\n   expressions:\n\n      >>> import re\n      >>> def titlecase(s):\n              return re.sub(r"[A-Za-z]+(\'[A-Za-z]+)?",\n                            lambda mo: mo.group(0)[0].upper() +\n                                       mo.group(0)[1:].lower(),\n                            s)\n\n      >>> titlecase("they\'re bill\'s friends.")\n      "They\'re Bill\'s Friends."\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.translate(table[, deletechars])\n\n   Return a copy of the string where all characters occurring in the\n   optional argument *deletechars* are removed, and the remaining\n   characters have been mapped through the given translation table,\n   which must be a string of length 256.\n\n   You can use the ``maketrans()`` helper function in the ``string``\n   module to create a translation table. For string objects, set the\n   *table* argument to ``None`` for translations that only delete\n   characters:\n\n   >>> \'read this short text\'.translate(None, \'aeiou\')\n   \'rd ths shrt txt\'\n\n   New in version 2.6: Support for a ``None`` *table* argument.\n\n   For Unicode objects, the ``translate()`` method does not accept the\n   optional *deletechars* argument.  Instead, it returns a copy of the\n   *s* where all characters have been mapped through the given\n   translation table which must be a mapping of Unicode ordinals to\n   Unicode ordinals, Unicode strings or ``None``. Unmapped characters\n   are left untouched. Characters mapped to ``None`` are deleted.\n   Note, a more flexible approach is to create a custom character\n   mapping codec using the ``codecs`` module (see ``encodings.cp1251``\n   for an example).\n\nstr.upper()\n\n   Return a copy of the string converted to uppercase.\n\n   For 8-bit strings, this method is locale-dependent.\n\nstr.zfill(width)\n\n   Return the numeric string left filled with zeros in a string of\n   length *width*.  A sign prefix is handled correctly.  The original\n   string is returned if *width* is less than ``len(s)``.\n\n   New in version 2.2.2.\n\nThe following methods are present only on unicode objects:\n\nunicode.isnumeric()\n\n   Return ``True`` if there are only numeric characters in S,\n   ``False`` otherwise. Numeric characters include digit characters,\n   and all characters that have the Unicode numeric value property,\n   e.g. U+2155, VULGAR FRACTION ONE FIFTH.\n\nunicode.isdecimal()\n\n   Return ``True`` if there are only decimal characters in S,\n   ``False`` otherwise. Decimal characters include digit characters,\n   and all characters that that can be used to form decimal-radix\n   numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.\n',
  'strings': u'\nString literals\n***************\n\nString literals are described by the following lexical definitions:\n\n   stringliteral   ::= [stringprefix](shortstring | longstring)\n   stringprefix    ::= "r" | "u" | "ur" | "R" | "U" | "UR" | "Ur" | "uR"\n   shortstring     ::= "\'" shortstringitem* "\'" | \'"\' shortstringitem* \'"\'\n   longstring      ::= "\'\'\'" longstringitem* "\'\'\'"\n                  | \'"""\' longstringitem* \'"""\'\n   shortstringitem ::= shortstringchar | escapeseq\n   longstringitem  ::= longstringchar | escapeseq\n   shortstringchar ::= <any source character except "\\" or newline or the quote>\n   longstringchar  ::= <any source character except "\\">\n   escapeseq       ::= "\\" <any ASCII character>\n\nOne syntactic restriction not indicated by these productions is that\nwhitespace is not allowed between the **stringprefix** and the rest of\nthe string literal. The source character set is defined by the\nencoding declaration; it is ASCII if no encoding declaration is given\nin the source file; see section *Encoding declarations*.\n\nIn plain English: String literals can be enclosed in matching single\nquotes (``\'``) or double quotes (``"``).  They can also be enclosed in\nmatching groups of three single or double quotes (these are generally\nreferred to as *triple-quoted strings*).  The backslash (``\\``)\ncharacter is used to escape characters that otherwise have a special\nmeaning, such as newline, backslash itself, or the quote character.\nString literals may optionally be prefixed with a letter ``\'r\'`` or\n``\'R\'``; such strings are called *raw strings* and use different rules\nfor interpreting backslash escape sequences.  A prefix of ``\'u\'`` or\n``\'U\'`` makes the string a Unicode string.  Unicode strings use the\nUnicode character set as defined by the Unicode Consortium and ISO\n10646.  Some additional escape sequences, described below, are\navailable in Unicode strings. The two prefix characters may be\ncombined; in this case, ``\'u\'`` must appear before ``\'r\'``.\n\nIn triple-quoted strings, unescaped newlines and quotes are allowed\n(and are retained), except that three unescaped quotes in a row\nterminate the string.  (A "quote" is the character used to open the\nstring, i.e. either ``\'`` or ``"``.)\n\nUnless an ``\'r\'`` or ``\'R\'`` prefix is present, escape sequences in\nstrings are interpreted according to rules similar to those used by\nStandard C.  The recognized escape sequences are:\n\n+-------------------+-----------------------------------+---------+\n| Escape Sequence   | Meaning                           | Notes   |\n+===================+===================================+=========+\n| ``\\newline``      | Ignored                           |         |\n+-------------------+-----------------------------------+---------+\n| ``\\\\``            | Backslash (``\\``)                 |         |\n+-------------------+-----------------------------------+---------+\n| ``\\\'``            | Single quote (``\'``)              |         |\n+-------------------+-----------------------------------+---------+\n| ``\\"``            | Double quote (``"``)              |         |\n+-------------------+-----------------------------------+---------+\n| ``\\a``            | ASCII Bell (BEL)                  |         |\n+-------------------+-----------------------------------+---------+\n| ``\\b``            | ASCII Backspace (BS)              |         |\n+-------------------+-----------------------------------+---------+\n| ``\\f``            | ASCII Formfeed (FF)               |         |\n+-------------------+-----------------------------------+---------+\n| ``\\n``            | ASCII Linefeed (LF)               |         |\n+-------------------+-----------------------------------+---------+\n| ``\\N{name}``      | Character named *name* in the     |         |\n|                   | Unicode database (Unicode only)   |         |\n+-------------------+-----------------------------------+---------+\n| ``\\r``            | ASCII Carriage Return (CR)        |         |\n+-------------------+-----------------------------------+---------+\n| ``\\t``            | ASCII Horizontal Tab (TAB)        |         |\n+-------------------+-----------------------------------+---------+\n| ``\\uxxxx``        | Character with 16-bit hex value   | (1)     |\n|                   | *xxxx* (Unicode only)             |         |\n+-------------------+-----------------------------------+---------+\n| ``\\Uxxxxxxxx``    | Character with 32-bit hex value   | (2)     |\n|                   | *xxxxxxxx* (Unicode only)         |         |\n+-------------------+-----------------------------------+---------+\n| ``\\v``            | ASCII Vertical Tab (VT)           |         |\n+-------------------+-----------------------------------+---------+\n| ``\\ooo``          | Character with octal value *ooo*  | (3,5)   |\n+-------------------+-----------------------------------+---------+\n| ``\\xhh``          | Character with hex value *hh*     | (4,5)   |\n+-------------------+-----------------------------------+---------+\n\nNotes:\n\n1. Individual code units which form parts of a surrogate pair can be\n   encoded using this escape sequence.\n\n2. Any Unicode character can be encoded this way, but characters\n   outside the Basic Multilingual Plane (BMP) will be encoded using a\n   surrogate pair if Python is compiled to use 16-bit code units (the\n   default).  Individual code units which form parts of a surrogate\n   pair can be encoded using this escape sequence.\n\n3. As in Standard C, up to three octal digits are accepted.\n\n4. Unlike in Standard C, exactly two hex digits are required.\n\n5. In a string literal, hexadecimal and octal escapes denote the byte\n   with the given value; it is not necessary that the byte encodes a\n   character in the source character set. In a Unicode literal, these\n   escapes denote a Unicode character with the given value.\n\nUnlike Standard C, all unrecognized escape sequences are left in the\nstring unchanged, i.e., *the backslash is left in the string*.  (This\nbehavior is useful when debugging: if an escape sequence is mistyped,\nthe resulting output is more easily recognized as broken.)  It is also\nimportant to note that the escape sequences marked as "(Unicode only)"\nin the table above fall into the category of unrecognized escapes for\nnon-Unicode string literals.\n\nWhen an ``\'r\'`` or ``\'R\'`` prefix is present, a character following a\nbackslash is included in the string without change, and *all\nbackslashes are left in the string*.  For example, the string literal\n``r"\\n"`` consists of two characters: a backslash and a lowercase\n``\'n\'``.  String quotes can be escaped with a backslash, but the\nbackslash remains in the string; for example, ``r"\\""`` is a valid\nstring literal consisting of two characters: a backslash and a double\nquote; ``r"\\"`` is not a valid string literal (even a raw string\ncannot end in an odd number of backslashes).  Specifically, *a raw\nstring cannot end in a single backslash* (since the backslash would\nescape the following quote character).  Note also that a single\nbackslash followed by a newline is interpreted as those two characters\nas part of the string, *not* as a line continuation.\n\nWhen an ``\'r\'`` or ``\'R\'`` prefix is used in conjunction with a\n``\'u\'`` or ``\'U\'`` prefix, then the ``\\uXXXX`` and ``\\UXXXXXXXX``\nescape sequences are processed while  *all other backslashes are left\nin the string*. For example, the string literal ``ur"\\u0062\\n"``\nconsists of three Unicode characters: \'LATIN SMALL LETTER B\', \'REVERSE\nSOLIDUS\', and \'LATIN SMALL LETTER N\'. Backslashes can be escaped with\na preceding backslash; however, both remain in the string.  As a\nresult, ``\\uXXXX`` escape sequences are only recognized when there are\nan odd number of backslashes.\n',
 What's New in Python 2.6.8 rc 1?
 ================================
 
-*Release date: XXXX-XX-XX*
+*Release date: 2012-02-23*
 
 Core and Builtins
 -----------------

Misc/RPM/python-2.6.spec

 
 %define name python
 #--start constants--
-%define version 2.6.7
-%define libver 2.6
+%define version 2.6.8rc1
+%define libvers 2.6
 #--end constants--
 %define release 1pydotorg
 %define __prefix /usr
-This is Python version 2.6.7
-============================
+This is Python version 2.6.8 rc 1
+=================================
 
-Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011
+Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
+              2011, 2012
 Python Software Foundation.
 All rights reserved.
 
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